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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The breakdown of plant biomass in rumen depends on interactions between bacteria, archaea, fungi, and protozoa; however, the majority of studies of the microbiome of ruminants, including the few studies of the rumen of camels, only studied one of these microbial groups. In this study, we applied total rRNA sequencing to identify active microbial communities in twenty-two solid and liquid rumen samples from eleven camels reared under three feeding systems. These camels were separated in three groups, G1 (n=3), G2 (n=6) and G3 (n=2) and fed Egyptian clover hay and wheat straw and concentrates feed mixture, fresh Egyptian clover, and wheat straw, respectively. Bacteria dominated the libraries of reads generated from all rumen samples, followed by protozoa, archaea, and fungi respectively.. Firmicutes, Thermoplasmatales, Diplodinium, and Neocallimastix dominated bacterial, archaeal, protozoal and fungal communities, respectively in all samples. Feeding systems influenced the microbial diversity and relative abundance of microbial groups; libraries generated from camels fed fresh clover showed the highest alpha diversity. Principal co-ordinate analysis and linear discriminate analysis showed clusters associated with feeding system and that the relative abundance of microbes varied between liquid and solid fractions. In addition, the analysis showed positive and negative correlations between the microbial groups. This study is the first to assess all the active microbial profiles in the rumen of camels under different feeding systems to expand our knowledge regarding microbial communities and their symbiotic and competitive interactions for maintaining the normal functions of the rumen.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Camels (Camelus dromedaries) can produce milk and meat in hot, arid and semi-arid regions and can provide food security as the climate warms <ns0:ref type='bibr' target='#b84'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b20'>Faye, 2013)</ns0:ref>. Camels also provide textiles (fiber and hair) and are commonly used for daily human activities such as transportation, agriculture, tourism, race and riding <ns0:ref type='bibr' target='#b77'>(Rabee et al., 2019)</ns0:ref>. The unique feeding behavior and the functional structure of digestive tract of these pseudo-ruminants is well adapted to deserts <ns0:ref type='bibr' target='#b44'>(Kay et al., 1989)</ns0:ref>. The retention time of feed particles in the camel forestomach is longer than cows, sheep and other true ruminants, which prolongs the exposure of plant biomasses to the symbiotic microorganisms and helps in the efficient digestion <ns0:ref type='bibr'>(Lechner-Dolland and Engelhardt, 1989)</ns0:ref>. Camel production lies under three systems based on feeding type. Camels in traditional extensive system depend on low quality feeds; while, camels in semi-intensive system depend on highquality forage and camels in intensive system depend on high-quality forage and concentrates supplements <ns0:ref type='bibr' target='#b20'>(Faye, 2013)</ns0:ref>. Diet and feeding plan, determine the diversity of rumen microbial communities but age, animal breed can also influence the structure of this microbiome <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. The chemical composition of the diet shapes fermentation in the rumen. For instance, cellulolytic and hemicellulytic diets favor the fibrolytic microbes; while, starch and sugars are the major components of concentrate-based diets; thus, favoring the amylolytic <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2012)</ns0:ref>. Also, the microbial composition and diversity varied between liquid and solid rumen fractions, which might indicate different roles in rumen fermentation; for instance, plant-adherent microbiota might have a major role in fiber degradation <ns0:ref type='bibr' target='#b79'>(Ren et al., 2020)</ns0:ref>. Digestion in the camel depends on microbial fermentation in the rumen <ns0:ref type='bibr' target='#b84'>(Samsudin et al., 2011)</ns0:ref>. The efficiency of microbial fermentations in the rumen depends on interactions between a wide variety of microbial groups, including bacteria, archaea, fungi and protozoa <ns0:ref type='bibr' target='#b97'>(Yanagita et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra, 2005)</ns0:ref>. Camels can utilize lignocelulolytic shrubs that other domestic ruminants avoid <ns0:ref type='bibr' target='#b84'>(Samsudin et al., 2011)</ns0:ref>. Consequently, camel rumen microbes must have the capacity to degrade such poor-quality feeds <ns0:ref type='bibr' target='#b24'>(Gharechahi et al., 2015)</ns0:ref>. However, the microbial community in the rumen of dromedary camel received less attention than other domesticated ruminants. The investigation of rumen microbial community has many implications, including the possibility of improving animal productivity and the reduction of greenhouse gas emission <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. The development of the next-generation sequencing technologies offer the possibility to use various metagenomic and metatranscriptomic techniques for the rapid identification of rumen microbiomes and overcome the intrinsic constraints of traditional culture-based methods <ns0:ref type='bibr' target='#b84'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b36'>Ishaq and Wright, 2014)</ns0:ref>. Most of PCR-based assessments of microbial groups in the rumen have relied on amplicon sequencing, which target a specific variable region on 16S rRNA gene <ns0:ref type='bibr' target='#b56'>(Li et al. 2016)</ns0:ref>. This approach needs a wide range of primers to study different microbial communities <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013)</ns0:ref>. Therefore, the output could be biased due to the primer selection and amplification cycling conditions <ns0:ref type='bibr' target='#b27'>(Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b19'>Elekwachi et al., 2017)</ns0:ref>. Total RNA sequencing (RNA-Seq) offers the advantage of specifically targeting active microbes and avoids biases associated with primer selection and chimera generation in PCR <ns0:ref type='bibr' target='#b22'>(Gaidos et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b27'>Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016)</ns0:ref>. In addition, RNA-Seq approach is capable of identifying novel microbes as it is not reliant on primers for known microbes <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>. High-throughput metatranscriptome sequencing provides a comprehensive understanding of the biological systems by characterization of different groups of organisms in the same environment based on the sequencing of coding and noncoding RNA <ns0:ref type='bibr' target='#b19'>(Elekwachi et al., 2017)</ns0:ref>. Total RNA-Seq was applied to investigate microbial communities in many different systems including, for example, the microbial community in human gut <ns0:ref type='bibr' target='#b75'>(Qin et al., 2012)</ns0:ref>, and cow rumen <ns0:ref type='bibr' target='#b56'>(Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b19'>Elekwachi et al., 2017 )</ns0:ref>.</ns0:p><ns0:p>All the microbiome studies on the camel rumen have characterized one or two microbial groups using classical or molecular approaches. For example, the protozoal community in camel rumen was studied heavily by conventional microscopic methods <ns0:ref type='bibr' target='#b23'>(Ghali et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b3'>Baraka, 2012)</ns0:ref>. Only three molecular-based studies are available on the bacterial community <ns0:ref type='bibr' target='#b84'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b6'>Bhatt et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b24'>Gharechahi et al., 2015)</ns0:ref>. Furthermore, only one study classified the rumen archaea <ns0:ref type='bibr' target='#b24'>(Gharechahi et al., 2015)</ns0:ref>. Regarding the anaerobic fungi, a new fungal genus, Oontomyces was isolated from the rumen of Indian camel <ns0:ref type='bibr' target='#b13'>(Dagar et al., 2015)</ns0:ref>, and only one study investigated the whole fungal community in the gut of the camel <ns0:ref type='bibr' target='#b77'>(Rabee et al., 2019)</ns0:ref>.</ns0:p><ns0:p>Moreover, no study provided a comprehensive analysis of potential active rumen microbiotas in the camel. In the present study, total rRNA sequencing was applied to 1) get insight into the composition of active microbiota in the rumen of camels reared under different feeding systems; 2) describe the distribution of microbial groups among the solid and liquid rumen fractions; 3) investigate the correlations between all the microbial groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Rumen samples</ns0:head><ns0:p>Rumen samples were collected from eleven adult dromedary camels under three different feeding systems. Camels in group G1 (n=3) were housed in the Maryout Research Station, Alexendria, Egypt and were fed on Egyptian clover hay (Trifolium alexandrinum), wheat straw and concentrates feed mixture. Camels in group G2 (n=6) were fed on fresh Egyptian clover (100 % high-quality forage diet) then slaughtered in the Kom Hammada slaughterhouse, Elbehera, Egypt. Animals of group G3 (n=2) were fed on wheat straw (100 % low-quality forage diet) then were slaughtered in Pasateen slaughterhouse, Cairo, Egypt. All the animals kept on the diet for at least one month before the sampling time. The proximate analysis of feeds illustrated in supplementary table <ns0:ref type='table'>S1</ns0:ref>. Details regarding the camel rumen samples in this study presented in Supplementary table <ns0:ref type='table'>S2</ns0:ref>. The rumen contents were strained immediately by two layers cheesecloth to separate the liquid and solid to form twenty-two samples, frozen using liquid nitrogen and stored at -80 o C before further processing <ns0:ref type='bibr' target='#b19'>(Elekwachi et al., 2017)</ns0:ref>. The project was approved and all samples were collected according to the Institutional Animal Care and Use Committee, Faculty of Veterinary Medicine, University of Sadat City, Egypt (Approval number: VUSC00003).</ns0:p></ns0:div> <ns0:div><ns0:head>RNA isolation, quality and quantity estimation and sequencing</ns0:head><ns0:p>The frozen rumen samples were ground using liquid nitrogen. About 0.5 gram of frozen fine powder was used for total RNA isolation using Trizol-Reagent protocol (Invitrogen, Carlsbad, CA), followed by RNA clean up using MEGA clear Kit (Invitrogen). Total RNA quality and quantity were estimated using an Agilent 2100 bioanalyzer (Agilent Technologies, USA) and RNA 6000 Nano kit (Agilent Technologies, USA). One hundred nanogram of total RNA was reversetranscribed into first strand cDNA and sequenced using Illumina rRNA MiSeq preparation kit (Illumina, USA) by Illumina MiSeq platform.</ns0:p></ns0:div> <ns0:div><ns0:head>Bioinformatic data analysis</ns0:head><ns0:p>The generated RNA sequence reads were analysed using pipeline developed by <ns0:ref type='bibr' target='#b19'>Elekwachi et al. (2017)</ns0:ref>. Briefly, the sequence quality was checked using the FastQC program v. 0.11.4 <ns0:ref type='bibr' target='#b0'>(Andrews, 2010)</ns0:ref>, then Trimmomatic program v. 0.35 <ns0:ref type='bibr' target='#b8'>(Bolger et al., 2014)</ns0:ref> was used to trim adaptors, barcodes, ambiguous and low quality reads. PEAR program v. 0.9.6 <ns0:ref type='bibr' target='#b99'>(Zhang et al., 2014)</ns0:ref> was used to merge read 1 and read 2 using default options. Then after, the hidden Markov models rRNA-HMM tool of the rapid analysis of multiple metagenomes with a clustering and annotation pipeline (RAMMCAP) <ns0:ref type='bibr' target='#b55'>(Li, 2009)</ns0:ref> was used to sort the reads into archaea and bacteria (16S, 23S), and eukaryote (18S, 23S) rRNA sequences. Merged sequence files were then sub-sampled as needed using <ns0:ref type='bibr'>MEME program v. 4.10.2 (Bailey et al., 2009)</ns0:ref>. For each sample, 70,000 reads were run through the pipeline. For subsequent analysis steps, 20 000, 10 000, and 2000 sequences were used for bacteria, eukaryote and archaea, respectively. Taxonomy binning for eukaryote and archaeal SSU rRNA sequences was performed using BLASTN. The sub-sampled query sequences were searched against the SILVA SSURef-111 database using an e-value of 1e -5 . Bacterial SSU sequences were binned into operational taxonomic units (OTUs) using the 'classify. seqs' command of Mothur v. 1.33.1 program <ns0:ref type='bibr' target='#b85'>(Schloss et al., 2009)</ns0:ref>. The SSURef -108 gene and the SSURef-108b taxonomy databases were used. Principal co-ordinate analysis (PCoA) using Bray Curtis dissimilarity and alpha diversity indices (Chao1, Shannon and Inverse Simpson) were evaluated by Mothur <ns0:ref type='bibr' target='#b85'>(Schloss et al., 2009)</ns0:ref> based on sub-sampling of 70,000 reads per sample according the protocol 'Community Structure Analysis Based on OTU Clustering' outlined in <ns0:ref type='bibr' target='#b19'>Elekwachi et al. (2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>Data of relative abundance of bacterial phyla, protozoal genera, fungal genera and archaea genera and order Thermoplasmatales were tested for normality and homogeneity using Shapiro-Wilk test and variables that were deemed non-normal were then arcsine transformed. Linear Discriminate Analysis (LDA) and Bray Curtis Permutational Multivariate Analysis of Variance (PERMANOVA) tests depended on the relative abundance of bacterial phyla. All the protozoal, fungal and archaeal genera and the order Thermoplasmatales were used to show the differences in community structure and to compare the clustering of samples. Pearson correlation analysis was used to identify correlation within and between microbial communities and the correlation scores were visualized as a heatmap. The statistical analyses were performed using the SPSS v. 20.0 software package (SPSS, 1999) and PAST <ns0:ref type='bibr' target='#b30'>(Hammer et al., 2001)</ns0:ref>. All the sequences were deposited to the sequence read archive (SRA) under the accession number: SRP107370.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>The composition and diversity of active microbial community</ns0:head><ns0:p>Total rRNA sequencing in twenty-two solid and liquid rumen samples from eleven camels resulted in a total of 3958591 reads with average of 359871.9 &#177; 85365.7 (mean &#177; standard error (SE)) reads per animal in the solid fraction (SF) and 3386392 reads with an average of 307853.8 &#177; 60989.6 reads per animal in the liquid fraction (LF). The sequence reads of bacteria dominated the active microbial community, followed by protozoa, archaea and fungi (Table <ns0:ref type='table'>1</ns0:ref>). The relative abundance of protozoa was higher in LF-G1 (liquid fraction of G1), while the relative abundance of bacteria was higher in SF-G1 (solid fraction of G1). The highest population of archaea was observed in G2 camels. Additionally, G3 camels showed the highest relative abundance of fungi (Table <ns0:ref type='table'>1</ns0:ref>; Supplementary Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). Number of OTUs and Alpha-diversity indices, Chao1, Shannon and Inverse Simpson, were higher in the rumen of LF-G2 samples (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>The composition of bacterial community varied little between treatments and consisted of 12 phyla. The five most predominant phyla were Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetes and Fibrobacteres, respectively (Table <ns0:ref type='table'>2</ns0:ref>). Phylum Firmicutes dominated the bacterial community in all groups and was higher in G2 followed by G1 and G3 camels, respectively, and was also higher in SF compared to LF (Table <ns0:ref type='table'>2</ns0:ref>). On the family level, the Firmicutes phylum was dominated by Lachnospiraceae and Ruminococcuceae. In addition, six genera dominated this phylum, including Butyrivibrio, RFN8-YE57, Ruminococcus, vadinHA42, Acetitomaculum and Blautia (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and supplementary Table <ns0:ref type='table'>S3</ns0:ref>). The second largest phylum, Bacteroidetes, showed the highest relative abundance in G3 followed by G1 and G2 camels and was higher in LF than SF (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and supplementary Table <ns0:ref type='table'>S3</ns0:ref>). On the family and genera levels, Bacteroidetes was dominated by three families (Prevotellaceae, BS11_ gut_ group, Rikenellaceae) and two genera (Prevotella, RC9_gut_group) besides uncultured Bacteroidetes. Proteobacteria, phylum showed a higher relative abundance in LF-G1 samples and was dominated by Succinivibrionaceae family and Desulfovibrio genus (Table <ns0:ref type='table'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, supplementary Table <ns0:ref type='table'>S3</ns0:ref>). The Spirochaetes phylum was higher in the SF-G3 and it was classified into two families including Spirochaetaceae and PL-11B10 and was dominated by Treponema genus. The Fibrobacteres phylum was higher in SF-G3 (Table <ns0:ref type='table'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, supplementary Table <ns0:ref type='table'>S3</ns0:ref>). The other phyla, including Actinobacteria, that was higher in SF-G2 samples, Tenricutes phylum was higher in the LF-G1 samples and Lentisphaerae phylum, was about 3-fold higher in the LF as relative to SF and accounted for a large population in the camels of G3 (Table <ns0:ref type='table'>2</ns0:ref>). Additionally, several minor bacterial phyla were also observed in the rumen of camels such as Verrucomicrobia, Elusimicrobia, Cyanobacteria and Chloroflexi (Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p><ns0:p>All Bacterial genera were observed in all groups except seven genera, including uncultured Marinilabiaceae (Bacteroidetes), Quinella (Firmicutes) and Streptococcus (Firmicutes) that were observed only in G2 and G3 camels. Ruminobacter (Proteobacteria) was observed only in G1 and G2 camels. On the other hand, Arcobacter and Succinivibrio within phylum Proteobacteria were observed only in G1 camels and Betaproteobacteria (Proteobacteria) was observed only in G3 camels. Moreover, many unclassified bacteria were observed across samples and accounted for 38.53% of total bacterial reads. Most of these unclassified bacterial reads were observed in phylum Firmicutes and Bacteroidetes.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>All archaeal reads were assigned to the phylum Euryacheota. The order level classification revealed three orders, including Thermoplasmatales, Methanobacteriale and Methanomicrobial. Thermoplasmatales dominated the archaeal community and showed the highest population in LF-G3 camels, this order was not classified out of order level (Table <ns0:ref type='table'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>). All the Methanobacteriale reads were belonged to family Methanobacteriacea that classified into three genera; Methanobrevibacter, Methanophera and Methanobacterium. Methanobrevibacter is the second largest contributor in archaeal population and was higher in SF-G1 camels. Methanosphaera exhibited higher relative abundance in SF-G2 camels. Methanobacterium was absent in G3 camels; however, a small proportion of this genus was found in the camels of G1 and G2. Methanomicrobium genus, which belongs to order Methanomicrobiales and family Methanomicrobiaceae was the least contributor in archaeal population and was more prevalent in LF-G3 camels (Table <ns0:ref type='table'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>The protozoal population in camels of the current study was grouped in two cultured families, Ophryoscolecidae and Isotrichidae (Table <ns0:ref type='table'>4</ns0:ref>). The Ophryoscolecidae family consisted of seven genera, Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium, Epidinium and Trichostomatia. In addition, Isotrichidae consisted of two genera, Dasytricha and Isotricha. The variation among the camels in protozoal population was clearly observed and seemed to be higher than other microbial communities; however, the protozoal community composition was similar among the camels (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>). The most dominant protozoal genera were Diplodinium, Ophryoscolex and Entodinium. Camels in G1 had the highest population of Entodinium and Epidinium. Camels in G2 had the greatest population of Eudiplodinium, Ophryoscolex, Isotricha and Dasytricha. The camels in G3 had the greatest population of Diplodinium, Polyplastron and Trichostomatia. On the sample fraction level, the solid fraction had a higher representation of Ophryoscolex, Polyplastron, Eudiplodinium, Epidinium and Diplodinium while the liquid fraction had a higher representation of Entodinium, Isotricha and Dasytricha (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>The characterization of rumen fungi revealed four fungal genera; three of which were anaerobic fungi related to phylum Neocallimastigomycota and family Neocallimasticeceae including Neocallimastix, which dominated the fungal community in the current study, followed by Piromyces and Cyllamyces (Table <ns0:ref type='table'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>). These anaerobic fungal genera represented &gt; 99.5 % of the fungal population. In addition, genus Spizellomyces, which is related to phylum Chytridiomycota and family Spizellomycetaceae, was noted in a very small proportion (&lt;0.5 %) (Table <ns0:ref type='table'>5</ns0:ref>). Neocallimastix was more abundant in the SF-G1 samples while Piromyces and Cyllamyces were more abundant in LF-G2 and SF-G3 respectively (Table <ns0:ref type='table'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Effect of feeding system on the composition of microbial communities</ns0:head><ns0:p>Multivariate analysis separated libraries by feeding system distinctly (Figs. <ns0:ref type='figure' target='#fig_4'>2 and 3</ns0:ref>). Also, bacteria, dominated by phylum Firmicutes were the main driver of differences between animals (Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>). Furthermore, Entodinium, Thermoplasmatales, Neocallimastix were the main drivers of differences in protozoal, archaeal and fungal communities, respectively. PERMANOVA analysis revealed that the difference between camel groups was significant (P &lt; 0.01) in all microbial groups (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Pairwise comparison between camel groups based on Bonferroni-corrected p-value demonstrated that the difference was significant (P &lt; 0.05) between camels of G2 and G3 in bacterial and archaeal communities (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Moreover, the difference was significant between the three groups in the protozoal community (P &lt; 0.05) whereas, in the fungal community, the difference was significant only between camels in group G1 and G2 (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Pearson correlation between microbes in the rumen of dromedary camel</ns0:head><ns0:p>Pearson correlation analysis (Fig. <ns0:ref type='figure' target='#fig_6'>4A, 4B</ns0:ref>), revealed many significant positive and negative correlations (P &lt; 0.05). For example, in active bacteria, Bacteroidetes correlated positively with Cyllamyces and negatively with Butyrivibrio, Methanosphaera and Trichostomatia. Prevotellaceae correlated positively with Neocallimastix and Entodinium and negatively with Ruminococcaceae, Methanosphaera and Diplodinium. Fibrobacteres correlated positively with Cyllamyces, Methanomicrobium, Thermoplasmatales and Diplodinium and negatively with Methanosphaera, Epidinium, Ruminococcaceae and Butyrivibrio. Firmicutes correlated positively with Methanosphaera and negatively with Piromyces, Thermoplasmatales and Methanomicrobium.</ns0:p><ns0:p>In active archaea, Thermoplasmatales correlated positively with Diplodinium and negatively with Methanobrevibacter and Methanosphaera. In active protozoa, there was a negative correlation between Polyplastron, Entodinium, Ophryoscolex and Epidinium. In active fungi, a negative correlation was observed between Cyllamyces, Neocallimastix and Piromyces and between Piromyces and Entodinium.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Rumen microbes can ferment a wide variety of feed components, including cellulose, xylan, amylose and protein <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref> and produce volatile fatty acids that provide the animal with approximately 70% of daily energy requirements <ns0:ref type='bibr' target='#b4'>(Bergman, 1990)</ns0:ref>. Furthermore, the rumen fermentation generates methane, which contributes to global warming and represents 2-12% loss of feed energy for the animal <ns0:ref type='bibr' target='#b41'>(Johnson and Ward, 1996;</ns0:ref><ns0:ref type='bibr' target='#b11'>Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b38'>Jami et al., 2014)</ns0:ref>. Therefore, investigation of these microbial communities is the key to understand their roles and maximize ruminal fermentation and fiber digestion <ns0:ref type='bibr' target='#b54'>(Lee et al., 2012)</ns0:ref>. The rumen microbiome varied little between animals sampled. As predicted, feeding system had an impact on the microbial diversity and the relative abundance of microbial groups. PCoA, LDA and PERMANOVA analyses confirmed the finding of this study and was in agreement with the results of other ruminant studies <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Camels in the present study were fed on different forages; Egyptian clover and wheat straw (Supplementary Table <ns0:ref type='table'>S1</ns0:ref>). Egyptian clover is the most balanced and nutritious fodder widely used for feeding camels <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b1'>Bakheit, 2013;</ns0:ref><ns0:ref type='bibr' target='#b88'>Shrivastava et al., 2014)</ns0:ref>, which might supported the high microbial diversity in G2 camels compared to other groups (Table <ns0:ref type='table'>1</ns0:ref>). This was consistent with previous studies on cows <ns0:ref type='bibr' target='#b72'>(Pitta et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b87'>Shanks et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>. Highly degradable carbohydrates support the bacterial and protozoal growth <ns0:ref type='bibr' target='#b17'>(Dijkstra and Tamminga, 1995;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>, which could demonstrate their higher population in G1 camels. Additionally, the higher bacterial population slows the fungi growth <ns0:ref type='bibr' target='#b91'>(Stewart et al., 1992;</ns0:ref><ns0:ref type='bibr' target='#b66'>Orpin and Joblin, 1997)</ns0:ref>, which was illustrated by the low fungal population in G1 camels.</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>Firmicutes phylum was found to be more abundant than Bacteroidetes and both phyla comprised &gt; 75% of all bacterial reads (Table <ns0:ref type='table'>2</ns0:ref>), which is in agreement with the results of previous studies on different animals including camels <ns0:ref type='bibr' target='#b84'>(Samsudin et al., 2011)</ns0:ref>, Surti Buffalo <ns0:ref type='bibr' target='#b67'>(Pandya et al., 2010)</ns0:ref> and Muskoxen <ns0:ref type='bibr' target='#b82'>(Salgado-Flores et al., 2016)</ns0:ref>. The majority of Firmicutes' members have a potential role in fiber digestion, which might illustrate their higher population in G2 camels that were fed on high-quality forage and also in solid fraction. This speculation was supported by the high proportion of Ruminococcaceae and Lachnospiraceae families that found to be active in fiber digestion in the rumen <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b62'>Nathani et al., 2015)</ns0:ref>. Bothe Blautia and Acetitomaculum genera have a key role as reductive acetogens (Le <ns0:ref type='bibr' target='#b50'>Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b98'>Yang et al., 2016)</ns0:ref> and varied with feeding system among the camel groups in this study. This finding could indicate that the reductive acetogenesis pathway could be maximized by diet to minimize methane production (Le <ns0:ref type='bibr' target='#b50'>Van et al., 1998)</ns0:ref>. Bacteroidetes were higher in poor quality forage (G3), which was similar to results found in cattle <ns0:ref type='bibr' target='#b69'>(Pitta et al., 2014b)</ns0:ref>. The phylum was dominated by family Prevotellaceae, which confirms <ns0:ref type='bibr' target='#b24'>Gharechahi et al. (2015)</ns0:ref>. The members of Bacteroidetes possess diverse enzymes that can target cellulose, pectin and soluble polysaccharides released in the liquid phase <ns0:ref type='bibr' target='#b59'>(Mackenzie et al., 2015)</ns0:ref>. Additionally, Prevotella genus is involved in propionate production that is used for energy by the host <ns0:ref type='bibr' target='#b62'>(Nathani et al., 2015)</ns0:ref>. We speculate that Bacteroidetes species contribute to the adaptation of camels to arid conditions. The RC9_gut_group found in this study belongs to uncultured genera and was found also in the gut of Rhinoceros hindgut <ns0:ref type='bibr' target='#b7'>(Bian et al., 2013)</ns0:ref>. Unclassified Bacteroidetes are specialized in lignocellulose degradation <ns0:ref type='bibr' target='#b59'>(Mackenzie et al., 2015)</ns0:ref>, which could support their high proportion in G3 camels. The Fibrobacteres was higher (3.1%) in this study compared to the other findings on camels <ns0:ref type='bibr' target='#b24'>(Gharechahi et al., 2015)</ns0:ref>. Interestingly, Fibrobacteres has been shown in previous studies to be the principal cellulolytic bacteria in the rumen <ns0:ref type='bibr' target='#b78'>(Ransom-Jones et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b62'>Nathani et al., 2015)</ns0:ref> which might illustrate its higher relative abundance in solid fraction and in the rumen of camels fed on wheat straw (G3) (Table <ns0:ref type='table'>2</ns0:ref>) that is rich in lignocellulose. We also identified that the members of Proteobacteria were lower in G2 and G3 camels that were fed on diet rich in fiber contents. These findings highlighted this phylum's function as a protein-degrading bacteria as it was reported by <ns0:ref type='bibr' target='#b57'>Liu et al. (2017)</ns0:ref>. The abundance of Treponema was higher in the solid fraction and in G3 camels (Figure <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>). Treponema is the dominant genus in Spirochaetes phylum and it is fiber-associated bacteria, which could indicate to its cellulytic and xylanolytic activities <ns0:ref type='bibr' target='#b35'>(Ishaq and Wright, 2012)</ns0:ref>.</ns0:p><ns0:p>The dominant bacterial genera in this study were Butyriovibrio, RFN8-YE57, Ruminococcus, Prevotella, Fibrobacter, Treponema and VadinHA. These genera were higher in the SF except RFN8-YE57 compared to the LF; this finding was consistent with a previous study on camels <ns0:ref type='bibr' target='#b24'>(Gharechahi et al., 2015)</ns0:ref>, which confirms that the attached microbes play a major role in ruminal fiber digestion <ns0:ref type='bibr' target='#b39'>(Jewell et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b64'>Noel et al., 2017)</ns0:ref>. Most of Elusimicrobia in this study were uncultured; some members of this phylum were isolated from the termite's gut that degrades cellulose <ns0:ref type='bibr' target='#b32'>(Herlemann et al., 2009)</ns0:ref>. Therefore, we speculate that this phylum has a role in fiber digestion and that might illustrate their high proportion in G3 camels. Actinobacteria observed also in the rumen of moose and some members of this phylum have acetogenic activities <ns0:ref type='bibr' target='#b37'>(Ishaq et al., 2015)</ns0:ref>. Some members of Victivallis within Lentisphaerae phylum were involved in cellobiose degrading activity <ns0:ref type='bibr' target='#b100'>(Zoetendal et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Unclassified bacteria in our study (38% of total bacterial reads) were less than the percentage found in a study of Muskoxen (53.7-59.3%) <ns0:ref type='bibr' target='#b82'>(Salgado-Flores et al., 2016)</ns0:ref>. The presence of unclassified bacteria in the gut was commonly observed <ns0:ref type='bibr' target='#b25'>(Gruninger et al., 2016)</ns0:ref> and could be a result of the presence of new bacteria that has the ability to ferment plant biomass <ns0:ref type='bibr' target='#b82'>(Salgado-Flores et al., 2016)</ns0:ref> or related to the sequencing approach used where short reads were generated from RNA-seq <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>The archaeal population has important roles in the rumen and in methane emission mitigation strategies as they convert the H 2 and CO 2 produced in the rumen to methane <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010)</ns0:ref>. Additionally, acetate produced in fiber breakdown is used to provide a methyl group for methanogenesis; therefore, methanogens population could be shifted by alteration of diet composition or feed additives and plant compounds <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b92'>Tapio et al., 2017 )</ns0:ref>, which could demonstrate the variation in the relative abundance of archaea between camel groups. Camels of the second group (G2) that fed fresh clover, showed the highest archaeal population (Table <ns0:ref type='table'>2</ns0:ref>) and the archaeal community was dominated by Thermoplasmatales, a methylotrophic methanogens order (Table <ns0:ref type='table'>3</ns0:ref>) which was consistent with the results on cattle <ns0:ref type='bibr' target='#b10'>(Carberry et al., 2014)</ns0:ref> and camels <ns0:ref type='bibr' target='#b24'>(Gharechahi et al., 2015)</ns0:ref>. Thermoplasmatales produces methane from methyl amine and its population was decreased by the addition of rapeseed oil to animal diet, making it a high potential target in future strategies to mitigate methane emissions <ns0:ref type='bibr'>(Poulsen et al., 2013)</ns0:ref>. The Methanobrevibacter, Methanosphaera, Methanomicrobium and Methanobacterium (Table <ns0:ref type='table'>4</ns0:ref>) are the other dominant archaea that were also observed in this study and in accordance with the results found in beef cattle <ns0:ref type='bibr' target='#b10'>(Carberry et al., 2014)</ns0:ref>. Methanobrevibacter dominated the methanogens in other ruminant <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref> and was associated with high methane emissions <ns0:ref type='bibr' target='#b92'>(Tapio et al., 2017)</ns0:ref>. Moreover, Methanomicrobium had its highest proportion with the feeding system of poor quality forage diet (G3), which was similar to results found in buffalo <ns0:ref type='bibr' target='#b21'>(Franzolin and Wright, 2016)</ns0:ref>, and In vitro <ns0:ref type='bibr' target='#b94'>(Wang et al., 2018)</ns0:ref>. In rumen, Methanomicrobium has been shown to be responsible for the conversion of H 2 and/or formate into CH 4 <ns0:ref type='bibr' target='#b51'>(Leahy et al., 2013)</ns0:ref>. The abundance of Thermoplasmatales was also negatively correlated with Methanobrevibacter which is consistent with previous results <ns0:ref type='bibr' target='#b14'>(Danielsson et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b60'>McGovern et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>The majority of protozoal reads were related to Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium and Epidinium (Table <ns0:ref type='table'>4</ns0:ref>). Similar findings were observed in other study on different ruminants <ns0:ref type='bibr' target='#b3'>(Baraka, 2012)</ns0:ref>. The relative abundance of protozoal was influenced by feeding system, which was in the same line with results on cattle <ns0:ref type='bibr' target='#b34'>(Hristov et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b95'>Weimer, 2015)</ns0:ref>. The Diplodinium dominated the protozoal community and was prevalent in the G3 camels, which highlighted the cellulolytic activity of this genus <ns0:ref type='bibr' target='#b12'>(Coleman et al., 1976)</ns0:ref>. Also, some species of genus Diplodinium were discovered in the rumen of Egyptian camel and is considered to be peculiar in camel such as Diplodinium cameli, <ns0:ref type='bibr' target='#b48'>(Kubesy and Dehority, 2002)</ns0:ref>. In addition, Entodinium was higher in G1 camels that were fed on concentrates feed mixture that increase the protozoa. Also, previous studies showed that this genus was dominant in rumen of camels <ns0:ref type='bibr' target='#b86'>(Selim et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b23'>Ghali et al., 2005)</ns0:ref> and cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2012)</ns0:ref>. Moreover, the study of <ns0:ref type='bibr' target='#b47'>Kittelmann and Janssen (2011)</ns0:ref> showed that the Polyplastron was the dominant genus in cattle. On the function level, all the genus Eudiplidinum, Epidinum and Diplodinum have cellulolytic activity <ns0:ref type='bibr' target='#b12'>(Coleman et al., 1976)</ns0:ref> whereas, Polyplastrone and Epidinium have a xylanolytic activity <ns0:ref type='bibr' target='#b16'>(Devillard, 1999;</ns0:ref><ns0:ref type='bibr' target='#b5'>B&#233;ra-Maillet et al., 2005)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>The highest fungal population was observed in the solid fraction and rumen of G3 camels (Table <ns0:ref type='table'>1</ns0:ref>). These findings were in agreement with the results of different studies stated that the fibre-based diets stimulated the fungal growth <ns0:ref type='bibr' target='#b65'>(Orpin, 1977;</ns0:ref><ns0:ref type='bibr' target='#b80'>Roger et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b28'>Haitjema et al., 2014)</ns0:ref>. This speculation could explain the low fungal population in G1 camels in our study. Moreover, the longer retention time and neutral pH in camel's forestomach <ns0:ref type='bibr' target='#b81'>(Russell and Wilson, 1996)</ns0:ref> make it more suitable for the survival of rumen fungi. The genus Neocallimastix dominated the fungal community and found to be higher in the G1 camels which was similar to other results on sheep and camels <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013</ns0:ref><ns0:ref type='bibr' target='#b77'>, Rabee et al., 2019)</ns0:ref>. This genus produces enzymes capable of hydrolyzing cellulose, xylan and starch <ns0:ref type='bibr' target='#b68'>(Pearce and Bauchop, 1985)</ns0:ref>. In the other side, Cyllamyces that was observed in small population, has the ability to degrade poor-quality feeds <ns0:ref type='bibr' target='#b90'>(Sridhar et al., 2014)</ns0:ref>, which might explain its high population in solid fraction and G3 camels. Piromyces was the second dominant genus in the camel rumen of this study and has been shown to produce cellulolytic and xylanolytic enzymes <ns0:ref type='bibr' target='#b93'>(Teunissen et al., 1992)</ns0:ref>. Therefore, the fungi were more prevalent in ruminants of G2 camels, which fed high-quality forage with high fiber contents than in G2 and G3 camels. The genus Spizellomyces is closely related to Chytridiomctes <ns0:ref type='bibr' target='#b9'>(Bowman et al., 1992)</ns0:ref>, and common in grassland and crop soil <ns0:ref type='bibr' target='#b58'>(Lozupone and</ns0:ref><ns0:ref type='bibr'>Klein, 2002, Kittelmann et al., 2012)</ns0:ref>. Thus, the presence of this fungus in the camel rumen in the current study could be explained by a contamination of the forages by soil.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between rumen microbes</ns0:head><ns0:p>The interactions between rumen microbes are the main driver of feed degradation and methane formation in the rumen, which influence the animal production and the environment <ns0:ref type='bibr' target='#b96'>(Williams et al., 1994;</ns0:ref><ns0:ref type='bibr' target='#b54'>Lee et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Positive and negative correlations were observed within and between microbial communities in this study (Fig. <ns0:ref type='figure' target='#fig_6'>4</ns0:ref>). Methanogens colonize the protozoa and this relationship was believed to enhance methane formation <ns0:ref type='bibr' target='#b63'>(Newbold et al., 1995)</ns0:ref>, which highlighted some positive correlations between protozoa and archaea. Additionally, the fibrolytic bacteria produce the important substrates mainly hydrogen and methyl groups that methanogens use for growth, <ns0:ref type='bibr' target='#b40'>(Johnson and Johnson, 1995)</ns0:ref>, which demonstrated the positive correlations found between Fibrobacteres and some methanogens. Also, positive correlation between the methylotrophic Methanosphaera and Lachnospiraceae that has been implicated in pectin degradation and provides methanol as a substrate for the methylotrophs <ns0:ref type='bibr' target='#b15'>(Dehority, 1969)</ns0:ref>. On the other hand, Prevotella is a hydrogen utilizer and produces propionate which has a negative impact on methanogenesis in the rumen <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>, which also illustrated the negative correlation obtained in this study between Prevotellaceae and archaea.</ns0:p><ns0:p>Since the rumen anaerobic fungi produce abundant H 2 through the fermentation of carbohydrate; they can interact positively with H 2 utilizers such as archaea, Prevotellaceae, Blautia and Acetitomaculum <ns0:ref type='bibr' target='#b66'>(Orpin and Joblin, 1997;</ns0:ref><ns0:ref type='bibr' target='#b50'>Le Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b98'>Yang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>. Additionally, the anaerobic fungi penetrate plant tissue, which provides an increased surface area for bacterial colonization <ns0:ref type='bibr' target='#b66'>(Orpin and Joblin, 1997)</ns0:ref>, which could explain the positive correlation between fungi and both Butyrivibrio and Fibrobacteres in this study. However, fungi are known to be negatively impacted by the presence of some bacteria and protozoa as the fungal zoospores are likely to be a prey for protozoa <ns0:ref type='bibr' target='#b61'>(Morgavi et al., 1994)</ns0:ref>, which demonstrated the negative correlation between both Neocallimastix and Piromyces with Diplodinium and Entodinium. Furthermore, Ruminococcus produces compounds that inhibit the growth of rumen fungi <ns0:ref type='bibr' target='#b91'>(Stewart et al., 1992)</ns0:ref>, which support the negative correlation between Neocallimastix and Ruminococcaceae. Polyplastron predates upon other protozoa like Epidinium, Eudiplodinium, Diplodinium, and Ostracodinium <ns0:ref type='bibr' target='#b18'>(Eadie, 1967)</ns0:ref>, which might explained the negative correlation between Polyplastron and other Protozoa.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study applied total rRNA sequencing to get insight into the active microbial groups in the rumen of dromedary camels. However, using the DNA-amplicon sequencing with RNA sequencing is recommended in the future studies to compare the composition of active microbial groups (from RNA sequencing) with the composition of the whole microbial community. As a major conclusion of our study, the microbial community in camel rumen was diverse and similar in composition between the camels. However, the feeding system impacted the relative abundance of active microbial communities where the fresh Egyptian clover provided the highest microbial diversity. The majority of camel rumen microbes (bacteria, fungi, and protozoa) were fibrolytic or have a possible role in fiber digestion, which might illustrate the ability of camel to live in desert harsh conditions under poor feeds. Moreover, the structure of microbial community in rumen of camel found to be similar to other ruminant studies with a shown difference in the relative abundances. The present results should open new perspectives for further cultivation and isolation studies on the unclassified microorganisms found in the rumen of camels to classify them and assign their functions.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>The relative abundance of microbial groups </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Comparison of relative abundance of genera of the microbiota in dromedary camel. bacterial (a), archaeal (b), protozoal (c) and fungi (d) in ruminal solid (SF) and liquid (LF) fractions of camels under different feeding systems.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2: Principal Co-ordinated analysis derived from OTUs from twenty-two ruminal liquid (LF) and solid (SF) samples distributed on three camel groups. G1 camels (red circles), G2 (white circle and G3(blue circles).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3:Linear Discriminant analysis of microbial communities in the samples based on the relative abundance of genera of active bacteria (a), archaea (b), protozoa (c) and fungi i (d)in ruminal solid (SF), and liquid (LF) fractions of camels under three feeding systems, G1 (black dots), G2 (blue squares) and G3 (coral triangles).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4: Heatmap based on Pearson correlation coefficients between and within the relative abundance of bacteria, archaea, protozoa and fungi in solid (A) and liquid (B) rumen fractions of dromedary camel. The black boxed ellipses refer to the significant correlations at P &lt; 0.05.</ns0:figDesc></ns0:figure> </ns0:body> "

" Desert Research Center 22th April, 2020 1Mathaf El Matariya St.B.O.P.11753 Matariya- Cairo,Egypt Phone: (+202)26332846 - 26374800 FAX: (+202) 26357858 Email: [email protected] [email protected] Dear Editors, We thank you and the Reviewers for their constructive comments and corrections. We responded to all comments and we responded to the comments of editorial office. I also enclosed unclean paper including all comments colored by three colors, yellow for Editor’s comments, green for the Reviewer’s comments and pink for editorial office’s comments. Below are the responses to all the comments. We appreciate the opportunity to submit our manuscript to Peer J. Yours sincerely, Dr. Alaa Rabee Researcher at Desert Research Center, Egypt On behalf of all authors Comments Manuscript title: “Comparative analysis of the metabolically active microbial communities in the rumen of dromedary camels under different feeding systems using total rRNA sequencing ” In the unclean or marked manuscript you could notice that colored comments using three colors, yellow for Editor’s comments, green for the first Reviewer’s comments, and pink for editorial office’s comments. Editor Reviewer 1 Editorial office Editor’s comments Line 39. Combine to “protozoa; however, the..” >>combined, thank you Line 60. Revise to “Camels (Camelus dromedaries) can produce milk and meat in hot, arid and semi-arid regions and can provide food security as the climate warms…” >> modified Line 62. Revise to “Camels also provide textiles (fiber and hair) and are commonly… >> modified Line 64. Replace “This unique..tract (Kay…” with “The unique feeding behavior and the functional structure of digestive tract of these pseudo-ruminants is well adapted to deserts (Kay..” >>Replaced, thank you Line 66. Revise to “is longer than cows, sheep and other true ruminants, which…” >> modified. Line 69. Revise to “feeding type. Camels…” >> modified. Line 72. Replace “Many factors a...determiner of the diversity of rumen microbial communities” with “Diet and feeding plan, determine the diversity of rumen microbial communities but age, animal breed can also influence the structure of this microbiome.” >> modified, thank you. Line 75. Replace “diet is the major shaper of fermentation” with “diet shapes fermentation” >>Replaced, thank you. Line 296. Replace “The structure of microbial community in the camel rumen was similar in the composition; however, feeding…” with “The rumen microbiome varied little between animals sampled. As predicted, feeding…” >>Replaced, thank you. Line 302. Replace “The Egyptian clover is considered …mixture (Carberry..” with “Egyptian clover is the most balanced and nutritious fodder widely used for feeding camels (Carberry..” >> modified. Line 320. Avoid phrases like “are known to” and “found to be” Revise to “genera have a key role as reductive acetogens (Le Van et al., 1998; Yang et al., 2016) and varied with feeding system…” >> modified. Line 325. Revise to “…2014b). The phylum was dominated by family Prevotellaceae, which confirms Gharechahi et al. (2015).” >> modified, thank you Line 329. Replace “Taken together, we speculate..their molecular roles.” With “We speculate that Bacteroidetes species contribute to the adaptation of camels to arid conditions.” >> modified, thank you Line 350. Revise to “…2015) and which..play a major role” with “…2015), which confirms that the attached microbes play a major role..” >> modified, thank you Line 352. Leave calls for future work to reviews and proposals. Delete “Further work is needed to examine …the rumen.” >> Deleted, thank you. Line 361. Present reasonable significant figures (38% not 38.53%). >>Done. Line 362, Revise to “a study of Muskoxen” >>Done Line 366. Again, do not call for more work. Delete “These unclassified bacteria need more studies to enable their isolation and identification.” >> Deleted, thank you. Reviewer 1 Line 45: Bacteria dominated, followed protozoa, archaea, and fungi, libraries of reads generated from all camel rumen samples………….Rephrase this text. >> Rephrased, thank you. Line 77: Remove fermentation >> Removed. Line 78: Remove microbes >> removed. Line 80: Add major before role >> Added, thank you. Line 109: change characterized to have characterized. >> Changed, thank you. Line 136: remove then were. >> Removed. Line 145: change Nanogram to nanogram >> Modified. Line 212: add required spaces. >>Added. Line 325: add space before references. >> Added. Line 357: Italicize Victivallis. >> Italicized. Line 388: write H2 and CH4 properly. >> Modified, thank you. Figure 1 and 4: Please italicize the genera names in the figures. Tables : Please italicize the genera names here and elsewhere >> Modified, thank you. Changes needed by editorial office 1: Authorship Authors Robert Forster, Chijioke Elekwachi, and Ebrahim Sabra still need to confirm their co-authorship using the email they received from PeerJ. Please ask them to check their spam folders. >>All the authors confirmed their authorship through your system except Dr. Robert Forester, who was retired about two years ago. I sent him many messages to his official and personal emails; however, he did not respond. Until now, I published three papers with him, the last one was in August 2019 and this paper is the fourth one. Also, I have a plan to publish another paper with him this year after the current paper. Below the links of the three papers. https://www.frontiersin.org/articles/10.3389/fmicb.2017.01814/full https://onlinelibrary.wiley.com/doi/full/10.1002/jobm.201800323 https://link.springer.com/article/10.1007/s10123-019-00093-1 2: Affiliations • We notice that the author affiliations (for Robert Forster, Chijioke Elekwachi, Ebrahim Sabra) you have provided in the system are slightly different to those in the document. System version: • Lethbridge Research and Development Centre, Agriculture and Agrifood Canada, Lethbridge, Alberta, Canada • Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, Alberta, Canada • Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Sadat City, Menoufia, Egypt Manuscript version: • Lethbridg Research center, Lethbridge, Canada • University of Sadat City, Sadat City, Egypt • As our system will use the author names/affiliations entered in the system for publication, and the text document for a reference, please ensure that both versions are complete and the same. Please do not include any address information such as street addresses or postal codes. • Please edit the author affiliations using the 'Edit' button to the right of the names in the system and/or edit your manuscript source file and upload it at the next revision. >> Modified, thank you. 3: References In the reference section, please provide the full author name lists for any references with 'et al.' including this reference: “Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., et al. (2012).' >> Modified, thank you 4: Figures • Only vector PDFs are acceptable. Please replace Figures 2, 3, and 4 (which are bitmap PDFs) with either PNG, EPS or vector PDF, measuring minimum 900 pixels and maximum 3000 pixels on all sides and eliminating excess white space around the images. • Figure 4 has multiple parts. Each figure with multiple parts should have alphabetical (e.g. A, B, C) labels on each part and all parts of each single figure should be submitted together in one file. 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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The breakdown of plant biomass in rumen depends on interactions between bacteria, archaea, fungi, and protozoa; however, the majority of studies of the microbiome of ruminants, including the few studies of the rumen of camels, only studied one of these microbial groups. In this study, we applied total rRNA sequencing to identify active microbial communities in twenty-two solid and liquid rumen samples from eleven camels reared under three feeding systems. These camels were separated in three groups, G1 (n=3), G2 (n=6) and G3 (n=2) and fed Egyptian clover hay and wheat straw and concentrates feed mixture, fresh Egyptian clover, and wheat straw, respectively. Bacteria dominated the libraries of reads generated from all rumen samples, followed by protozoa, archaea, and fungi respectively.. Firmicutes, Thermoplasmatales, Diplodinium, and Neocallimastix dominated bacterial, archaeal, protozoal and fungal communities, respectively in all samples. Feeding systems influenced the microbial diversity and relative abundance of microbial groups; libraries generated from camels fed fresh clover showed the highest alpha diversity. Principal co-ordinate analysis and linear discriminate analysis showed clusters associated with feeding system and that the relative abundance of microbes varied between liquid and solid fractions. In addition, the analysis showed positive and negative correlations between the microbial groups. This study is the first to assess all the active microbial profiles in the rumen of camels under different feeding systems to expand our knowledge regarding microbial communities and their symbiotic and competitive interactions for maintaining the normal functions of the rumen.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Camels (Camelus dromedaries) can produce milk and meat in hot, arid and semi-arid regions and can provide food security as the climate warms <ns0:ref type='bibr' target='#b82'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b22'>Faye, 2013)</ns0:ref>. Camels also provide textiles (fiber and hair) and are commonly used for daily human activities such as transportation, agriculture, tourism, race and riding <ns0:ref type='bibr' target='#b76'>(Rabee et al., 2019)</ns0:ref>. The unique feeding behavior and the functional structure of digestive tract of these pseudo-ruminants is well adapted to deserts <ns0:ref type='bibr' target='#b44'>(Kay et al., 1989)</ns0:ref>. The retention time of feed particles in the camel forestomach is longer than cows, sheep and other true ruminants, which prolongs the exposure of plant biomasses to the symbiotic microorganisms and helps in the efficient digestion <ns0:ref type='bibr'>(Lechner-Dolland and Engelhardt, 1989)</ns0:ref>. Camel production lies under three systems based on feeding type. Camels in traditional extensive system depend on low quality feeds; while, camels in semi-intensive system depend on highquality forage and camels in intensive system depend on high-quality forage and concentrates supplements <ns0:ref type='bibr' target='#b22'>(Faye, 2013)</ns0:ref>. Diet and feeding plan, determine the diversity of rumen microbial communities but age, animal breed can also influence the structure of this microbiome <ns0:ref type='bibr' target='#b32'>(Henderson et al., 2015)</ns0:ref>. The chemical composition of the diet shapes fermentation in the rumen. For instance, cellulolytic and hemicellulytic diets favor the fibrolytic microbes; while, starch and sugars are the major components of concentrate-based diets; thus, favoring the amylolytic <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012)</ns0:ref>. Also, the microbial composition and diversity varied between liquid and solid rumen fractions, which might indicate different roles in rumen fermentation; for instance, plant-adherent microbiota might have a major role in fiber degradation <ns0:ref type='bibr' target='#b78'>(Ren et al., 2020)</ns0:ref>. Digestion in the camel depends on microbial fermentation in the rumen <ns0:ref type='bibr' target='#b82'>(Samsudin et al., 2011)</ns0:ref>. The efficiency of microbial fermentations in the rumen depends on interactions between a wide variety of microbial groups, including bacteria, archaea, fungi and protozoa <ns0:ref type='bibr' target='#b96'>(Yanagita et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra, 2005)</ns0:ref>. Camels can utilize lignocelulolytic shrubs that other domestic ruminants avoid <ns0:ref type='bibr' target='#b82'>(Samsudin et al., 2011)</ns0:ref>. Consequently, camel rumen microbes must have the capacity to degrade such poor-quality feeds <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. However, the microbial community in the rumen of dromedary camel received less attention than other domesticated ruminants. The investigation of rumen microbial community has many implications, including the possibility of improving animal productivity and the reduction of greenhouse gas emission <ns0:ref type='bibr' target='#b32'>(Henderson et al., 2015)</ns0:ref>. The development of the next-generation sequencing technologies offer the possibility to use various metagenomic and metatranscriptomic techniques for the rapid identification of rumen microbiomes and overcome the intrinsic constraints of traditional culture-based methods <ns0:ref type='bibr' target='#b82'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b37'>Ishaq and Wright, 2014)</ns0:ref>. Most of PCR-based assessments of microbial groups in the rumen have relied on amplicon sequencing, which target a specific variable region on 16S rRNA gene <ns0:ref type='bibr' target='#b56'>(Li et al. 2016)</ns0:ref>. This approach needs a wide range of primers to study different microbial communities <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013)</ns0:ref>. Therefore, the output could be biased due to the primer selection and amplification cycling conditions <ns0:ref type='bibr' target='#b29'>(Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b21'>Elekwachi et al., 2017)</ns0:ref>. Total RNA sequencing (RNA-Seq) offers the advantage of specifically targeting active microbes and avoids biases associated with primer selection and chimera generation in PCR <ns0:ref type='bibr' target='#b24'>(Gaidos et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b29'>Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016)</ns0:ref>. In addition, RNA-Seq approach is capable of identifying novel microbes as it is not reliant on primers for known microbes <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>. High-throughput metatranscriptome sequencing provides a comprehensive understanding of the biological systems by characterization of different groups of organisms in the same environment based on the sequencing of coding and noncoding RNA <ns0:ref type='bibr' target='#b21'>(Elekwachi et al., 2017)</ns0:ref>. Total RNA-Seq was applied to investigate microbial communities in many different systems including, for example, the microbial community in human gut <ns0:ref type='bibr' target='#b75'>(Qin et al., 2012)</ns0:ref>, and cow rumen <ns0:ref type='bibr' target='#b56'>(Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b21'>Elekwachi et al., 2017 )</ns0:ref>.</ns0:p><ns0:p>All the microbiome studies on the camel rumen have characterized one or two microbial groups using classical or molecular approaches. For example, the protozoal community in camel rumen was studied heavily by conventional microscopic methods <ns0:ref type='bibr' target='#b25'>(Ghali et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b4'>Baraka, 2012)</ns0:ref>. Only three molecular-based studies are available on the bacterial community <ns0:ref type='bibr' target='#b82'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b7'>Bhatt et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b26'>Gharechahi et al., 2015)</ns0:ref>. Furthermore, only one study classified the rumen archaea <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. Regarding the anaerobic fungi, a new fungal genus, Oontomyces was isolated from the rumen of Indian camel <ns0:ref type='bibr' target='#b15'>(Dagar et al., 2015)</ns0:ref>, and only one study investigated the whole fungal community in the gut of the camel <ns0:ref type='bibr' target='#b76'>(Rabee et al., 2019)</ns0:ref>.</ns0:p><ns0:p>Moreover, no study provided a comprehensive analysis of potential active rumen microbiotas in the camel. In the present study, total rRNA sequencing was applied to 1) get insight into the composition of active microbiota in the rumen of camels reared under different feeding systems; 2) describe the distribution of microbial groups among the solid and liquid rumen fractions; 3) investigate the correlations between all the microbial groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Rumen samples</ns0:head><ns0:p>Rumen samples were collected from eleven adult dromedary camels under three different feeding systems. Camels in group G1 (n=3) were housed in the Maryout Research Station, Alexendria, Egypt and were fed on Egyptian clover hay (Trifolium alexandrinum), wheat straw and concentrates feed mixture. Camels in group G2 (n=6) were fed on fresh Egyptian clover (100 % high-quality forage diet) then slaughtered in the Kom Hammada slaughterhouse, Elbehera, Egypt. Animals of group G3 (n=2) were fed on wheat straw (100 % low-quality forage diet) then were slaughtered in Pasateen slaughterhouse, Cairo, Egypt. All the animals kept on the diet for at least one month before the sampling time. The proximate analysis of feeds illustrated in supplementary table <ns0:ref type='table'>S1</ns0:ref>. Details regarding the camel rumen samples in this study presented in Supplementary table <ns0:ref type='table'>S2</ns0:ref>. The rumen contents were strained immediately by two layers cheesecloth to separate the liquid and solid to form twenty-two samples, frozen using liquid nitrogen and stored at -80 o C before further processing <ns0:ref type='bibr' target='#b21'>(Elekwachi et al., 2017)</ns0:ref>. The project was approved and all samples were collected according to the Institutional Animal Care and Use Committee, Faculty of Veterinary Medicine, University of Sadat City, Egypt (Approval number: VUSC00003).</ns0:p></ns0:div> <ns0:div><ns0:head>RNA isolation, quality and quantity estimation and sequencing</ns0:head><ns0:p>The frozen rumen samples were ground using liquid nitrogen. About 0.5 gram of frozen fine powder was used for total RNA isolation using Trizol-Reagent protocol (Invitrogen, Carlsbad, CA), followed by RNA clean up using MEGA clear Kit (Invitrogen). Total RNA quality and quantity were estimated using an Agilent 2100 bioanalyzer (Agilent Technologies, USA) and RNA 6000 Nano kit (Agilent Technologies, USA). One hundred nanogram of total RNA was reversetranscribed into first strand cDNA and sequenced using Illumina rRNA MiSeq preparation kit (Illumina, USA) by Illumina MiSeq platform.</ns0:p></ns0:div> <ns0:div><ns0:head>Bioinformatic data analysis</ns0:head><ns0:p>The generated RNA sequence reads were analysed using pipeline developed by <ns0:ref type='bibr' target='#b21'>Elekwachi et al. (2017)</ns0:ref>. Briefly, the sequence quality was checked using the FastQC program v. 0.11.4 <ns0:ref type='bibr' target='#b0'>(Andrews, 2010)</ns0:ref>, then Trimmomatic program v. 0.35 <ns0:ref type='bibr' target='#b9'>(Bolger et al., 2014)</ns0:ref> was used to trim adaptors, barcodes, ambiguous and low quality reads. PEAR program v. 0.9.6 <ns0:ref type='bibr' target='#b99'>(Zhang et al., 2014)</ns0:ref> was used to merge read 1 and read 2 using default options. Then after, the hidden Markov models rRNA-HMM tool of the rapid analysis of multiple metagenomes with a clustering and annotation pipeline (RAMMCAP) <ns0:ref type='bibr' target='#b55'>(Li, 2009)</ns0:ref> was used to sort the reads into archaea and bacteria (16S, 23S), and eukaryote (18S, 23S) rRNA sequences. Merged sequence files were then sub-sampled as needed using <ns0:ref type='bibr'>MEME program v. 4.10.2 (Bailey et al., 2009)</ns0:ref>. For each sample, 70,000 reads were run through the pipeline. For subsequent analysis steps, 20 000, 10 000, and 2000 sequences were used for bacteria, eukaryote and archaea, respectively. Taxonomy binning for eukaryote and archaeal SSU rRNA sequences was performed using BLASTN. The sub-sampled query sequences were searched against the SILVA SSURef-111 database using an e-value of 1e -5 . Bacterial SSU sequences were binned into operational taxonomic units (OTUs) using the 'classify. seqs' command of Mothur v. 1.33.1 program <ns0:ref type='bibr' target='#b83'>(Schloss et al., 2009)</ns0:ref>. The SSURef -108 gene and the SSURef-108b taxonomy databases were used. Principal co-ordinate analysis (PCoA) using Bray Curtis dissimilarity and alpha diversity indices (Chao1, Shannon and Inverse Simpson) were evaluated by Mothur <ns0:ref type='bibr' target='#b83'>(Schloss et al., 2009)</ns0:ref> based on sub-sampling of 70,000 reads per sample according the protocol 'Community Structure Analysis Based on OTU Clustering' outlined in <ns0:ref type='bibr' target='#b21'>Elekwachi et al. (2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>Data of relative abundance of bacterial phyla, protozoal genera, fungal genera and archaea genera and order Thermoplasmatales were tested for normality and homogeneity using Shapiro-Wilk test and variables that were deemed non-normal were then arcsine transformed. Linear Discriminate Analysis (LDA) and Bray Curtis Permutational Multivariate Analysis of Variance (PERMANOVA) tests depended on the relative abundance of bacterial phyla. All the protozoal, fungal and archaeal genera and the order Thermoplasmatales were used to show the differences in community structure and to compare the clustering of samples. Pearson correlation analysis was used to identify correlation within and between microbial communities and the correlation scores were visualized as a heatmap. The statistical analyses were performed using the SPSS v. 20.0 software package (SPSS, 1999) and PAST <ns0:ref type='bibr' target='#b31'>(Hammer et al., 2001)</ns0:ref>. All the sequences were deposited to the sequence read archive (SRA) under the accession number: SRP107370.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>The composition and diversity of active microbial community</ns0:head><ns0:p>Total rRNA sequencing in twenty-two solid and liquid rumen samples from eleven camels resulted in a total of 3958591 reads with average of 359871.9 &#177; 85365.7 (mean &#177; standard error (SE)) reads per animal in the solid fraction (SF) and 3386392 reads with an average of 307853.8 &#177; 60989.6 reads per animal in the liquid fraction (LF). The sequence reads of bacteria dominated the active microbial community, followed by protozoa, archaea and fungi (Table <ns0:ref type='table'>1</ns0:ref>). The relative abundance of protozoa was higher in LF-G1 (liquid fraction of G1), while the relative abundance of bacteria was higher in SF-G1 (solid fraction of G1). The highest population of archaea was observed in G2 camels. Additionally, G3 camels showed the highest relative abundance of fungi (Table <ns0:ref type='table'>1</ns0:ref>; Supplementary Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>). Number of OTUs and Alpha-diversity indices, Chao1, Shannon and Inverse Simpson, were higher in the rumen of LF-G2 samples (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>The composition of bacterial community varied little between treatments and consisted of 12 phyla. The five most predominant phyla were Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetes and Fibrobacteres, respectively (Table <ns0:ref type='table'>2</ns0:ref>). Phylum Firmicutes dominated the bacterial community in all groups and was higher in G2 followed by G1 and G3 camels, respectively, and was also higher in SF compared to LF (Table <ns0:ref type='table'>2</ns0:ref>). On the family level, the Firmicutes phylum was dominated by Lachnospiraceae and Ruminococcuceae. In addition, six genera dominated this phylum, including Butyrivibrio, RFN8-YE57, Ruminococcus, vadinHA42, Acetitomaculum and Blautia (Fig. <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref> and supplementary Table <ns0:ref type='table'>S3</ns0:ref>). The second largest phylum, Bacteroidetes, showed the highest relative abundance in G3 followed by G1 and G2 camels and was higher in LF than SF (Fig. <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref> and supplementary Table <ns0:ref type='table'>S3</ns0:ref>). On the family and genera levels, Bacteroidetes was dominated by three families (Prevotellaceae, BS11_ gut_ group, Rikenellaceae) and two genera (Prevotella, RC9_gut_group) besides uncultured Bacteroidetes. Proteobacteria, phylum showed a higher relative abundance in LF-G1 samples and was dominated by Succinivibrionaceae family and Desulfovibrio genus (Table <ns0:ref type='table'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref>, supplementary Table <ns0:ref type='table'>S3</ns0:ref>). The Spirochaetes phylum was higher in the SF-G3 and it was classified into two families including Spirochaetaceae and PL-11B10 and was dominated by Treponema genus. The Fibrobacteres phylum was higher in SF-G3 (Table <ns0:ref type='table'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref>, supplementary Table <ns0:ref type='table'>S3</ns0:ref>). The other phyla, including Actinobacteria, that was higher in SF-G2 samples, Tenricutes phylum was higher in the LF-G1 samples and Lentisphaerae phylum, was about 3-fold higher in the LF as relative to SF and accounted for a large population in the camels of G3 (Table <ns0:ref type='table'>2</ns0:ref>). Additionally, several minor bacterial phyla were also observed in the rumen of camels such as Verrucomicrobia, Elusimicrobia, Cyanobacteria and Chloroflexi (Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p><ns0:p>All Bacterial genera were observed in all groups except seven genera, including uncultured Marinilabiaceae (Bacteroidetes), Quinella (Firmicutes) and Streptococcus (Firmicutes) that were observed only in G2 and G3 camels. Ruminobacter (Proteobacteria) was observed only in G1 and G2 camels. On the other hand, Arcobacter and Succinivibrio within phylum Proteobacteria were observed only in G1 camels and Betaproteobacteria (Proteobacteria) was observed only in G3 camels. Moreover, many unclassified bacteria were observed across samples and accounted for 38.53% of total bacterial reads. Most of these unclassified bacterial reads were observed in phylum Firmicutes and Bacteroidetes.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>All archaeal reads were assigned to the phylum Euryacheota. The order level classification revealed three orders, including Thermoplasmatales, Methanobacteriale and Methanomicrobial. Thermoplasmatales dominated the archaeal community and showed the highest population in LF-G3 camels, this order was not classified out of order level (Table <ns0:ref type='table'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1b</ns0:ref>). All the Methanobacteriale reads were belonged to family Methanobacteriacea that classified into three genera; Methanobrevibacter, Methanophera and Methanobacterium. Methanobrevibacter is the second largest contributor in archaeal population and was higher in SF-G1 camels. Methanosphaera exhibited higher relative abundance in SF-G2 camels. Methanobacterium was absent in G3 camels; however, a small proportion of this genus was found in the camels of G1 and G2. Methanomicrobium genus, which belongs to order Methanomicrobiales and family Methanomicrobiaceae was the least contributor in archaeal population and was more prevalent in LF-G3 camels (Table <ns0:ref type='table'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1b</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>The protozoal population in camels of the current study was grouped in two cultured families, Ophryoscolecidae and Isotrichidae (Table <ns0:ref type='table'>4</ns0:ref>). The Ophryoscolecidae family consisted of seven genera, Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium, Epidinium and Trichostomatia. In addition, Isotrichidae consisted of two genera, Dasytricha and Isotricha. The variation among the camels in protozoal population was clearly observed and seemed to be higher than other microbial communities; however, the protozoal community composition was similar among the camels (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1c</ns0:ref>). The most dominant protozoal genera were Diplodinium, Ophryoscolex and Entodinium. Camels in G1 had the highest population of Entodinium and Epidinium. Camels in G2 had the greatest population of Eudiplodinium, Ophryoscolex, Isotricha and Dasytricha. The camels in G3 had the greatest population of Diplodinium, Polyplastron and Trichostomatia. On the sample fraction level, the solid fraction had a higher representation of Ophryoscolex, Polyplastron, Eudiplodinium, Epidinium and Diplodinium while the liquid fraction had a higher representation of Entodinium, Isotricha and Dasytricha (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1c</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>The characterization of rumen fungi revealed four fungal genera; three of which were anaerobic fungi related to phylum Neocallimastigomycota and family Neocallimasticeceae including Neocallimastix, which dominated the fungal community in the current study, followed by Piromyces and Cyllamyces (Table <ns0:ref type='table'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1d</ns0:ref>). These anaerobic fungal genera represented &gt; 99.5 % of the fungal population. In addition, genus Spizellomyces, which is related to phylum Chytridiomycota and family Spizellomycetaceae, was noted in a very small proportion (&lt;0.5 %) (Table <ns0:ref type='table'>5</ns0:ref>). Neocallimastix was more abundant in the SF-G1 samples while Piromyces and Cyllamyces were more abundant in LF-G2 and SF-G3 respectively (Table <ns0:ref type='table'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1d</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Effect of feeding system on the composition of microbial communities</ns0:head><ns0:p>Multivariate analysis separated libraries by feeding system distinctly (Figs. <ns0:ref type='figure' target='#fig_5'>2 and 3</ns0:ref>). Also, bacteria, dominated by phylum Firmicutes were the main driver of differences between animals (Fig. <ns0:ref type='figure' target='#fig_5'>3</ns0:ref>). Furthermore, Entodinium, Thermoplasmatales, Neocallimastix were the main drivers of differences in protozoal, archaeal and fungal communities, respectively. PERMANOVA analysis revealed that the difference between camel groups was significant (P &lt; 0.01) in all microbial groups (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Pairwise comparison between camel groups based on Bonferroni-corrected p-value demonstrated that the difference was significant (P &lt; 0.05) between camels of G2 and G3 in bacterial and archaeal communities (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Moreover, the difference was significant between the three groups in the protozoal community (P &lt; 0.05) whereas, in the fungal community, the difference was significant only between camels in group G1 and G2 (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Pearson correlation between microbes in the rumen of dromedary camel</ns0:head><ns0:p>Pearson correlation analysis (Fig. <ns0:ref type='figure' target='#fig_7'>4A, 4B</ns0:ref>), revealed many significant positive and negative correlations (P &lt; 0.05). For example, in active bacteria, Bacteroidetes correlated positively with Cyllamyces and negatively with Butyrivibrio, Methanosphaera and Trichostomatia. Prevotellaceae correlated positively with Neocallimastix and Entodinium and negatively with Ruminococcaceae, Methanosphaera and Diplodinium. Fibrobacteres correlated positively with Cyllamyces, Methanomicrobium, Thermoplasmatales and Diplodinium and negatively with Methanosphaera, Epidinium, Ruminococcaceae and Butyrivibrio. Firmicutes correlated positively with Methanosphaera and negatively with Piromyces, Thermoplasmatales and Methanomicrobium.</ns0:p><ns0:p>In active archaea, Thermoplasmatales correlated positively with Diplodinium and negatively with Methanobrevibacter and Methanosphaera. In active protozoa, there was a negative correlation between Polyplastron, Entodinium, Ophryoscolex and Epidinium. In active fungi, a negative correlation was observed between Cyllamyces, Neocallimastix and Piromyces and between Piromyces and Entodinium.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Rumen microbes can ferment a wide variety of feed components, including cellulose, xylan, amylose and protein <ns0:ref type='bibr' target='#b32'>(Henderson et al., 2015)</ns0:ref> and produce volatile fatty acids that provide the animal with approximately 70% of daily energy requirements <ns0:ref type='bibr' target='#b5'>(Bergman, 1990)</ns0:ref>. Furthermore, the rumen fermentation generates methane, which contributes to global warming and represents 2-12% loss of feed energy for the animal <ns0:ref type='bibr' target='#b42'>(Johnson and Ward, 1996;</ns0:ref><ns0:ref type='bibr' target='#b12'>Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b39'>Jami et al., 2014)</ns0:ref>. Therefore, investigation of these microbial communities is the key to understand their roles and maximize ruminal fermentation and fiber digestion <ns0:ref type='bibr' target='#b54'>(Lee et al., 2012)</ns0:ref>. The rumen microbiome varied little between animals sampled. As predicted, feeding system had an impact on the microbial diversity and the relative abundance of microbial groups. PCoA, LDA and PERMANOVA analyses confirmed the finding of this study and was in agreement with the results of other ruminant studies <ns0:ref type='bibr' target='#b32'>(Henderson et al., 2015)</ns0:ref>. Camels in the present study were fed on different forages; Egyptian clover and wheat straw (Supplementary Table <ns0:ref type='table'>S1</ns0:ref>). Egyptian clover is the most balanced and nutritious fodder widely used for feeding camels <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr'>Bakheit, 2013;</ns0:ref><ns0:ref type='bibr' target='#b87'>Shrivastava et al., 2014)</ns0:ref>, which might supported the high microbial diversity in G2 camels compared to other groups (Table <ns0:ref type='table'>1</ns0:ref>). This was consistent with previous studies on cows <ns0:ref type='bibr' target='#b73'>(Pitta et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b86'>Shanks et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>. Highly degradable carbohydrates support the bacterial and protozoal growth <ns0:ref type='bibr' target='#b19'>(Dijkstra and Tamminga, 1995;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>, which could demonstrate their higher population in G1 camels. Additionally, the higher bacterial population slows the fungi growth <ns0:ref type='bibr' target='#b90'>(Stewart et al., 1992;</ns0:ref><ns0:ref type='bibr' target='#b67'>Orpin and Joblin, 1997)</ns0:ref>, which was illustrated by the low fungal population in G1 camels.</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>Firmicutes phylum was found to be more abundant than Bacteroidetes and both phyla comprised &gt; 75% of all bacterial reads (Table <ns0:ref type='table'>2</ns0:ref>), which is in agreement with the results of previous studies on different animals including camels <ns0:ref type='bibr' target='#b82'>(Samsudin et al., 2011)</ns0:ref>, Surti Buffalo <ns0:ref type='bibr' target='#b68'>(Pandya et al., 2010)</ns0:ref> and Muskoxen <ns0:ref type='bibr' target='#b81'>(Salgado-Flores et al., 2016)</ns0:ref>. The majority of Firmicutes' members have a potential role in fiber digestion, which might illustrate their higher population in G2 camels that were fed on high-quality forage and also in solid fraction. This speculation was supported by the high proportion of Ruminococcaceae and Lachnospiraceae families that found to be active in fiber digestion in the rumen <ns0:ref type='bibr' target='#b71'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b63'>Nathani et al., 2015)</ns0:ref>. Bothe Blautia and Acetitomaculum genera have a key role as reductive acetogens (Le <ns0:ref type='bibr'>Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b97'>Yang et al., 2016)</ns0:ref> and varied with feeding system among the camel groups in this study. This finding could indicate that the reductive acetogenesis pathway could be maximized by diet to minimize methane production (Le <ns0:ref type='bibr'>Van et al., 1998)</ns0:ref>. Bacteroidetes were higher in poor quality forage (G3), which was similar to results found in cattle <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014b)</ns0:ref>. The phylum was dominated by family Prevotellaceae, which confirms <ns0:ref type='bibr' target='#b26'>Gharechahi et al. (2015)</ns0:ref>. The members of Bacteroidetes possess diverse enzymes that can target cellulose, pectin and soluble polysaccharides released in the liquid phase <ns0:ref type='bibr' target='#b60'>(Mackenzie et al., 2015)</ns0:ref>. Additionally, Prevotella genus is involved in propionate production that is used for energy by the host <ns0:ref type='bibr' target='#b63'>(Nathani et al., 2015)</ns0:ref>. We speculate that Bacteroidetes species contribute to the adaptation of camels to arid conditions. The RC9_gut_group found in this study belongs to uncultured genera and was found also in the gut of Rhinoceros hindgut <ns0:ref type='bibr' target='#b8'>(Bian et al., 2013)</ns0:ref>. Unclassified Bacteroidetes are specialized in lignocellulose degradation <ns0:ref type='bibr' target='#b60'>(Mackenzie et al., 2015)</ns0:ref>, which could support their high proportion in G3 camels. The Fibrobacteres was higher (3.1%) in this study compared to the other findings on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. Interestingly, Fibrobacteres has been shown in previous studies to be the principal cellulolytic bacteria in the rumen <ns0:ref type='bibr' target='#b77'>(Ransom-Jones et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b63'>Nathani et al., 2015)</ns0:ref> which might illustrate its higher relative abundance in solid fraction and in the rumen of camels fed on wheat straw (G3) (Table <ns0:ref type='table'>2</ns0:ref>) that is rich in lignocellulose. We also identified that the members of Proteobacteria were lower in G2 and G3 camels that were fed on diet rich in fiber contents. These findings highlighted this phylum's function as a protein-degrading bacteria as it was reported by <ns0:ref type='bibr' target='#b57'>Liu et al. (2017)</ns0:ref>. The abundance of Treponema was higher in the solid fraction and in G3 camels (Figure <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref>). Treponema is the dominant genus in Spirochaetes phylum and it is fiber-associated bacteria, which could indicate to its cellulytic and xylanolytic activities <ns0:ref type='bibr' target='#b36'>(Ishaq and Wright, 2012)</ns0:ref>.</ns0:p><ns0:p>The dominant bacterial genera in this study were Butyriovibrio, RFN8-YE57, Ruminococcus, Prevotella, Fibrobacter, Treponema and VadinHA. These genera were higher in the SF except RFN8-YE57 compared to the LF; this finding was consistent with a previous study on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>, which confirms that the attached microbes play a major role in ruminal fiber digestion <ns0:ref type='bibr' target='#b40'>(Jewell et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b65'>Noel et al., 2017)</ns0:ref>. Most of Elusimicrobia in this study were uncultured; some members of this phylum were isolated from the termite's gut that degrades cellulose <ns0:ref type='bibr' target='#b33'>(Herlemann et al., 2009)</ns0:ref>. Therefore, we speculate that this phylum has a role in fiber digestion and that might illustrate their high proportion in G3 camels. Actinobacteria observed also in the rumen of moose and some members of this phylum have acetogenic activities <ns0:ref type='bibr' target='#b38'>(Ishaq et al., 2015)</ns0:ref>. Some members of Victivallis within Lentisphaerae phylum were involved in cellobiose degrading activity <ns0:ref type='bibr' target='#b100'>(Zoetendal et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Unclassified bacteria in our study (38% of total bacterial reads) were less than the percentage found in a study of Muskoxen (53.7-59.3%) <ns0:ref type='bibr' target='#b81'>(Salgado-Flores et al., 2016)</ns0:ref>. The presence of unclassified bacteria in the gut was commonly observed <ns0:ref type='bibr' target='#b27'>(Gruninger et al., 2016)</ns0:ref> and could be a result of the presence of new bacteria that has the ability to ferment plant biomass <ns0:ref type='bibr' target='#b81'>(Salgado-Flores et al., 2016)</ns0:ref> or related to the sequencing approach used where short reads were generated from RNA-seq <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>The archaeal population has important roles in the rumen and in methane emission mitigation strategies as they convert the H 2 and CO 2 produced in the rumen to methane <ns0:ref type='bibr' target='#b34'>(Hook et al., 2010)</ns0:ref>. Additionally, acetate produced in fiber breakdown is used to provide a methyl group for methanogenesis; therefore, methanogens population could be shifted by alteration of diet composition or feed additives and plant compounds <ns0:ref type='bibr' target='#b34'>(Hook et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b91'>Tapio et al., 2017 )</ns0:ref>, which could demonstrate the variation in the relative abundance of archaea between camel groups. Camels of the second group (G2) that fed fresh clover, showed the highest archaeal population (Table <ns0:ref type='table'>2</ns0:ref>) and the archaeal community was dominated by Thermoplasmatales, a methylotrophic methanogens order (Table <ns0:ref type='table'>3</ns0:ref>) which was consistent with the results on cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref> and camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. Thermoplasmatales produces methane from methyl amine and its population was decreased by the addition of rapeseed oil to animal diet, making it a high potential target in future strategies to mitigate methane emissions <ns0:ref type='bibr' target='#b74'>(Poulsen et al., 2013)</ns0:ref>. The Methanobrevibacter, Methanosphaera, Methanomicrobium and Methanobacterium (Table <ns0:ref type='table'>4</ns0:ref>) are the other dominant archaea that were also observed in this study and in accordance with the results found in beef cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref>. Methanobrevibacter dominated the methanogens in other ruminant <ns0:ref type='bibr' target='#b32'>(Henderson et al., 2015)</ns0:ref> and was associated with high methane emissions <ns0:ref type='bibr' target='#b91'>(Tapio et al., 2017)</ns0:ref>. Moreover, Methanomicrobium had its highest proportion with the feeding system of poor quality forage diet (G3), which was similar to results found in buffalo <ns0:ref type='bibr' target='#b23'>(Franzolin and Wright, 2016)</ns0:ref>, and In vitro <ns0:ref type='bibr' target='#b93'>(Wang et al., 2018)</ns0:ref>. In rumen, Methanomicrobium has been shown to be responsible for the conversion of H 2 and/or formate into CH 4 <ns0:ref type='bibr' target='#b52'>(Leahy et al., 2013)</ns0:ref>. The abundance of Thermoplasmatales was also negatively correlated with Methanobrevibacter which is consistent with previous results <ns0:ref type='bibr' target='#b16'>(Danielsson et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b61'>McGovern et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>The majority of protozoal reads were related to Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium and Epidinium (Table <ns0:ref type='table'>4</ns0:ref>). Similar findings were observed in other study on different ruminants <ns0:ref type='bibr' target='#b4'>(Baraka, 2012)</ns0:ref>. The relative abundance of protozoal was influenced by feeding system, which was in the same line with results on cattle <ns0:ref type='bibr' target='#b35'>(Hristov et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b94'>Weimer, 2015)</ns0:ref>. The Diplodinium dominated the protozoal community and was prevalent in the G3 camels, which highlighted the cellulolytic activity of this genus <ns0:ref type='bibr' target='#b13'>(Coleman et al., 1976)</ns0:ref>. Also, some species of genus Diplodinium were discovered in the rumen of Egyptian camel and is considered to be peculiar in camel such as Diplodinium cameli, <ns0:ref type='bibr' target='#b48'>(Kubesy and Dehority, 2002)</ns0:ref>. In addition, Entodinium was higher in G1 camels that were fed on concentrates feed mixture that increase the protozoa. Also, previous studies showed that this genus was dominant in rumen of camels <ns0:ref type='bibr' target='#b85'>(Selim et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b25'>Ghali et al., 2005)</ns0:ref> and cattle <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012)</ns0:ref>. Moreover, the study of <ns0:ref type='bibr' target='#b47'>Kittelmann and Janssen (2011)</ns0:ref> showed that the Polyplastron was the dominant genus in cattle. On the function level, all the genus Eudiplidinum, Epidinum and Diplodinum have cellulolytic activity <ns0:ref type='bibr' target='#b13'>(Coleman et al., 1976)</ns0:ref> whereas, Polyplastrone and Epidinium have a xylanolytic activity <ns0:ref type='bibr' target='#b18'>(Devillard, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>B&#233;ra-Maillet et al., 2005)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>The highest fungal population was observed in the solid fraction and rumen of G3 camels (Table <ns0:ref type='table'>1</ns0:ref>). These findings were in agreement with the results of different studies stated that the fibre-based diets stimulated the fungal growth <ns0:ref type='bibr' target='#b66'>(Orpin, 1977;</ns0:ref><ns0:ref type='bibr' target='#b79'>Roger et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b30'>Haitjema et al., 2014)</ns0:ref>. This speculation could explain the low fungal population in G1 camels in our study. Moreover, the longer retention time and neutral pH in camel's forestomach <ns0:ref type='bibr' target='#b80'>(Russell and Wilson, 1996)</ns0:ref> make it more suitable for the survival of rumen fungi. The genus Neocallimastix dominated the fungal community and found to be higher in the G1 camels which was similar to other results on sheep and camels <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013</ns0:ref><ns0:ref type='bibr' target='#b76'>, Rabee et al., 2019)</ns0:ref>. This genus produces enzymes capable of hydrolyzing cellulose, xylan and starch <ns0:ref type='bibr' target='#b69'>(Pearce and Bauchop, 1985)</ns0:ref>. In the other side, Cyllamyces that was observed in small population, has the ability to degrade poor-quality feeds <ns0:ref type='bibr' target='#b89'>(Sridhar et al., 2014)</ns0:ref>, which might explain its high population in solid fraction and G3 camels. Piromyces was the second dominant genus in the camel rumen of this study and has been shown to produce cellulolytic and xylanolytic enzymes <ns0:ref type='bibr' target='#b92'>(Teunissen et al., 1992)</ns0:ref>. Therefore, the fungi were more prevalent in ruminants of G2 camels, which fed high-quality forage with high fiber contents than in G2 and G3 camels. The genus Spizellomyces is closely related to Chytridiomctes <ns0:ref type='bibr' target='#b10'>(Bowman et al., 1992)</ns0:ref>, and common in grassland and crop soil <ns0:ref type='bibr' target='#b59'>(Lozupone and</ns0:ref><ns0:ref type='bibr'>Klein, 2002, Kittelmann et al., 2012)</ns0:ref>. Thus, the presence of this fungus in the camel rumen in the current study could be explained by a contamination of the forages by soil.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between rumen microbes</ns0:head><ns0:p>The interactions between rumen microbes are the main driver of feed degradation and methane formation in the rumen, which influence the animal production and the environment <ns0:ref type='bibr' target='#b95'>(Williams et al., 1994;</ns0:ref><ns0:ref type='bibr' target='#b54'>Lee et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b32'>Henderson et al., 2015)</ns0:ref>. Positive and negative correlations were observed within and between microbial communities in this study (Fig. <ns0:ref type='figure' target='#fig_7'>4</ns0:ref>). Methanogens colonize the protozoa and this relationship was believed to enhance methane formation <ns0:ref type='bibr' target='#b64'>(Newbold et al., 1995)</ns0:ref>, which highlighted some positive correlations between protozoa and archaea. Additionally, the fibrolytic bacteria produce the important substrates mainly hydrogen and methyl groups that methanogens use for growth, <ns0:ref type='bibr' target='#b41'>(Johnson and Johnson, 1995)</ns0:ref>, which demonstrated the positive correlations found between Fibrobacteres and some methanogens. Also, positive correlation between the methylotrophic Methanosphaera and Lachnospiraceae that has been implicated in pectin degradation and provides methanol as a substrate for the methylotrophs <ns0:ref type='bibr' target='#b17'>(Dehority, 1969)</ns0:ref>. On the other hand, Prevotella is a hydrogen utilizer and produces propionate which has a negative impact on methanogenesis in the rumen <ns0:ref type='bibr' target='#b71'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>, which also illustrated the negative correlation obtained in this study between Prevotellaceae and archaea.</ns0:p><ns0:p>Since the rumen anaerobic fungi produce abundant H 2 through the fermentation of carbohydrate; they can interact positively with H 2 utilizers such as archaea, Prevotellaceae, Blautia and Acetitomaculum <ns0:ref type='bibr' target='#b67'>(Orpin and Joblin, 1997;</ns0:ref><ns0:ref type='bibr'>Le Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b97'>Yang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>. Additionally, the anaerobic fungi penetrate plant tissue, which provides an increased surface area for bacterial colonization <ns0:ref type='bibr' target='#b67'>(Orpin and Joblin, 1997)</ns0:ref>, which could explain the positive correlation between fungi and both Butyrivibrio and Fibrobacteres in this study. However, fungi are known to be negatively impacted by the presence of some bacteria and protozoa as the fungal zoospores are likely to be a prey for protozoa <ns0:ref type='bibr' target='#b62'>(Morgavi et al., 1994)</ns0:ref>, which demonstrated the negative correlation between both Neocallimastix and Piromyces with Diplodinium and Entodinium. Furthermore, Ruminococcus produces compounds that inhibit the growth of rumen fungi <ns0:ref type='bibr' target='#b90'>(Stewart et al., 1992)</ns0:ref>, which support the negative correlation between Neocallimastix and Ruminococcaceae. Polyplastron predates upon other protozoa like Epidinium, Eudiplodinium, Diplodinium, and Ostracodinium <ns0:ref type='bibr' target='#b20'>(Eadie, 1967)</ns0:ref>, which might explained the negative correlation between Polyplastron and other Protozoa.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study applied total rRNA sequencing to get insight into the active microbial groups in the rumen of dromedary camels. However, using the DNA-amplicon sequencing with RNA sequencing is recommended in the future studies to compare the composition of active microbial groups (from RNA sequencing) with the composition of the whole microbial community. As a major conclusion of our study, the microbial community in camel rumen was diverse and similar in composition between the camels. However, the feeding system impacted the relative abundance of active microbial communities where the fresh Egyptian clover provided the highest microbial diversity. The majority of camel rumen microbes (bacteria, fungi, and protozoa) were fibrolytic or have a possible role in fiber digestion, which might illustrate the ability of camel to live in desert harsh conditions under poor feeds. Moreover, the structure of microbial community in rumen of camel found to be similar to other ruminant studies with a shown difference in the relative abundances. The present results should open new perspectives for further cultivation and isolation studies on the unclassified microorganisms found in the rumen of camels to classify them and assign their functions. Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 1</ns0:note><ns0:p>The relative abundance of microbial groups </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2019:12:44048:3:0:REVIEW 5 May 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Comparison of relative abundance of genera of the microbiota in dromedary camel. bacterial (a), archaeal (b), protozoal (c) and fungi (d) in ruminal solid (SF) and liquid (LF) fractions of camels under different feeding systems.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2: Principal Co-ordinated analysis derived from OTUs from twenty-two ruminal liquid (LF) and solid (SF) samples distributed on three camel groups. G1 camels (red circles), G2 (white circle and G3(blue circles).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3:Linear Discriminant analysis of microbial communities in the samples based on the relative abundance of genera of active bacteria (a), archaea (b), protozoa (c) and fungi i (d)in ruminal solid (SF), and liquid (LF) fractions of camels under three feeding systems, G1 (black dots), G2 (blue squares) and G3 (coral triangles).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4: Heatmap based on Pearson correlation coefficients between and within the relative abundance of bacteria, archaea, protozoa and fungi in solid (A) and liquid (B) rumen fractions of dromedary camel. The black boxed ellipses refer to the significant correlations at P &lt; 0.05.</ns0:figDesc></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2019:12:44048:3:0:REVIEW 5 May 2020)</ns0:note> </ns0:body> "

" Desert Research Center 5th May, 2020 1Mathaf El Matariya St.B.O.P.11753 Matariya- Cairo,Egypt Phone: (+202)26332846 - 26374800 FAX: (+202) 26357858 Email: [email protected] [email protected] Dear Editor, We thank you for your comments. We formatted the references to match the journal style, I also enclosed unclean paper to show the changes. Regarding the authorship, all the authors confirmed their authorship except Dr. Robert Forester, I sent him many invitations to his official and personal emails and I sent him messages to his Facebook page; however, he did not respond. I would like to know the Journal’s policy in this case; would it available to publish the paper without his confirmation? If NO, what the journal policy in this case also to take the appropriate action?. We appreciate the opportunity to submit our manuscript to Peer J. Yours sincerely, Dr. Alaa Rabee Researcher at Desert Research Center, Egypt On behalf of all authors Comments Manuscript title: “Comparative analysis of the metabolically active microbial communities in the rumen of dromedary camels under different feeding systems using total rRNA sequencing ” In the unclean or marked manuscript you could notice that colored comments using three colors, yellow for Editor’s comments, green for the first Reviewer’s comments, and pink for editorial office’s comments. Editor Reviewer 1 Editorial office Editor’s comments Changes needed by editorial office 1: Authorship Authors Robert Forster, Chijioke Elekwachi, and Ebrahim Sabra still need to confirm their co-authorship using the email they received from PeerJ. Please ask them to check their spam folders. >>All the authors confirmed their authorship through your system except Dr. Robert Forester, who was retired about two years ago. I sent him many messages to his official and personal emails; however, he did not respond. Until now, I published three papers with him, the last one was in August 2019 and this paper is the fourth one. Also, I have a plan to publish another paper with him this year after the current paper. Below the links of the three papers. https://www.frontiersin.org/articles/10.3389/fmicb.2017.01814/full https://onlinelibrary.wiley.com/doi/full/10.1002/jobm.201800323 https://link.springer.com/article/10.1007/s10123-019-00093-1 2: Affiliations • We notice that the author affiliations (for Robert Forster, Chijioke Elekwachi, Ebrahim Sabra) you have provided in the system are slightly different to those in the document. System version: • Lethbridge Research and Development Centre, Agriculture and Agrifood Canada, Lethbridge, Alberta, Canada • Lethbridge Research and Development Centre, Agriculture and Agri-Food Canada, Lethbridge, Alberta, Canada • Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Sadat City, Menoufia, Egypt Manuscript version: • Lethbridg Research center, Lethbridge, Canada • University of Sadat City, Sadat City, Egypt • As our system will use the author names/affiliations entered in the system for publication, and the text document for a reference, please ensure that both versions are complete and the same. Please do not include any address information such as street addresses or postal codes. • Please edit the author affiliations using the 'Edit' button to the right of the names in the system and/or edit your manuscript source file and upload it at the next revision. >> Modified, thank you. 3: References In the reference section, please provide the full author name lists for any references with 'et al.' including this reference: “Qin, J., Li, Y., Cai, Z., Li, S., Zhu, J., Zhang, F., et al. (2012).' >> Modified, thank you 4: Figures • Only vector PDFs are acceptable. Please replace Figures 2, 3, and 4 (which are bitmap PDFs) with either PNG, EPS or vector PDF, measuring minimum 900 pixels and maximum 3000 pixels on all sides and eliminating excess white space around the images. • Figure 4 has multiple parts. Each figure with multiple parts should have alphabetical (e.g. A, B, C) labels on each part and all parts of each single figure should be submitted together in one file. In this case: the 2 parts of Figure 4 should be labeled A-B. Please provide a replacement figure measuring minimum 900 pixels and maximum 3000 pixels on all sides, saved as PNG, EPS, or PDF (vector images only) file format without excess white space around the images. The file name should be formatted as 'Figure4.png'. >> modified, thank you. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The breakdown of plant biomass in rumen depends on interactions between bacteria, archaea, fungi, and protozoa; however, the majority of studies of the microbiome of ruminants, including the few studies of the rumen of camels, only studied one of these microbial groups. In this study, we applied total rRNA sequencing to identify active microbial communities in twenty-two solid and liquid rumen samples from eleven camels reared under three feeding systems. These camels were separated in three groups, G1 (n=3), G2 (n=6) and G3 (n=2) and fed Egyptian clover hay and wheat straw and concentrates feed mixture, fresh Egyptian clover, and wheat straw, respectively. Bacteria dominated the libraries of reads generated from all rumen samples, followed by protozoa, archaea, and fungi respectively. Firmicutes, Thermoplasmatales, Diplodinium, and Neocallimastix dominated bacterial, archaeal, protozoal and fungal communities, respectively in all samples. Feeding systems influenced the microbial diversity and relative abundance of microbial groups; libraries generated from camels fed fresh clover showed the highest alpha diversity. Principal co-ordinate analysis and linear discriminate analysis showed clusters associated with feeding system and the relative abundance of microbes varied between liquid and solid fractions. In addition, the analysis showed positive and negative correlations between the microbial groups. This provides preliminary evidence that bacteria dominate the microbial communities of the camel rumen and that feed changes that microbiome.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Camels (Camelus dromedaries) can produce milk and meat in hot, arid and semi-arid regions and can provide food security as the climate warms <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b22'>Faye, 2013)</ns0:ref>. Camels also provide textiles (fiber and hair) and are commonly used for transportation, agriculture, tourism, race and riding <ns0:ref type='bibr' target='#b74'>(Rabee et al., 2019)</ns0:ref>. The unique feeding behavior and the functional structure of digestive tract of these pseudo-ruminants is well adapted to deserts <ns0:ref type='bibr' target='#b43'>(Kay et al., 1989)</ns0:ref>. The retention time of feed particles in the camel forestomach is longer than cows, sheep and other true ruminants, which prolongs the exposure of plant biomasses to the symbiotic microorganisms and helps in the efficient digestion <ns0:ref type='bibr'>(Lechner-Dolland and Engelhardt, 1989)</ns0:ref>. Camel production lies under three systems based on feeding type. Camels in traditional extensive system depend on low quality feeds; while, camels in semi-intensive system depend on highquality forage and camels in intensive system depend on high-quality forage and concentrated supplements <ns0:ref type='bibr' target='#b22'>(Faye, 2013)</ns0:ref>. Diet and feeding plan, determine the diversity of rumen microbial communities but age, animal breed can also influence the structure of this microbiome <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. The chemical composition of the diet shapes fermentation in the rumen. For instance, cellulolytic and hemicellulytic diets favor the fibrolytic microbes; while, starch and sugars favor amylolytic <ns0:ref type='bibr' target='#b13'>(Carberry et al., 2012)</ns0:ref>. Also, the microbial composition and diversity varies between liquid and solid rumen fractions, which might indicate different roles in rumen fermentation; for instance, plant-adherent microbiota might have a major role in fiber degradation <ns0:ref type='bibr' target='#b76'>(Ren et al., 2020)</ns0:ref>. Digestion in the camel depends on microbial fermentation in the rumen <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>.</ns0:p><ns0:p>The efficiency of microbial fermentations in the rumen depends on interactions between a wide variety of microbial groups, including bacteria, archaea, fungi and protozoa <ns0:ref type='bibr' target='#b93'>(Yanagita et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b42'>Kamra, 2005)</ns0:ref>. Analysis of these microbial communities could lead to increases in animal productivity and reduction of greenhouse gas emissions <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Camels can utilize lignocelulolytic shrubs that other domestic ruminants avoid <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>. Consequently, camel rumen microbes must have the capacity to degrade such poor-quality feeds <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. However, the microbial community in the rumen of dromedary camel received less attention than other domesticated ruminants. Next generation sequencing technologies provide a rapid method of microbial identification of rumen and overcome the intrinsic constraints of traditional culture-based methods <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b36'>Ishaq and Wright, 2014)</ns0:ref>. Most of PCR-based assessments of microbial groups in the rumen have relied on amplicon sequencing, which target a specific variable region on 16S rRNA gene <ns0:ref type='bibr' target='#b55'>(Li et al. 2016)</ns0:ref>. This approach needs a wide range of primers to study different microbial communities <ns0:ref type='bibr' target='#b45'>(Kittelmann et al., 2013)</ns0:ref>. Therefore, the output could be biased due to the primer selection and amplification cycling conditions <ns0:ref type='bibr' target='#b28'>(Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b55'>Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b21'>Elekwachi et al., 2017)</ns0:ref>. Total RNA sequencing (RNA-Seq) offers the advantage of specifically targeting active microbes and avoids biases associated with primer selection and chimera generation in PCR <ns0:ref type='bibr' target='#b24'>(Gaidos et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b28'>Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b55'>Li et al., 2016)</ns0:ref>. In addition, RNA-Seq approach is capable of identifying novel microbes as it is not reliant on primers for known microbes <ns0:ref type='bibr' target='#b55'>(Li et al., 2016)</ns0:ref>. High-throughput metatranscriptome sequencing provides a comprehensive understanding of the biological systems by characterization of different groups of organisms in the same environment based on the sequencing of coding and noncoding RNA <ns0:ref type='bibr' target='#b21'>(Elekwachi et al., 2017)</ns0:ref>. Total RNA-Seq was applied to investigate microbial communities in many different systems including, for example, the microbial community in human gut <ns0:ref type='bibr' target='#b73'>(Qin et al., 2012)</ns0:ref>, and cow rumen <ns0:ref type='bibr' target='#b55'>(Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b21'>Elekwachi et al., 2017 )</ns0:ref>.</ns0:p><ns0:p>Previous microbiome studies on the camel rumen have characterized one or two microbial groups using classical or molecular approaches. For example, the protozoal community in camel rumen was studied heavily by conventional microscopic methods <ns0:ref type='bibr' target='#b25'>(Ghali et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b4'>Baraka, 2012)</ns0:ref>. Regarding the anaerobic fungi, a new fungal genus, Oontomyces was isolated from the rumen of Indian camel <ns0:ref type='bibr' target='#b15'>(Dagar et al., 2015)</ns0:ref>, and only one study investigated the whole fungal community in the gut of the camel <ns0:ref type='bibr' target='#b74'>(Rabee et al., 2019)</ns0:ref>. Only three molecular-based studies are available on the bacterial community <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b7'>Bhatt et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b26'>Gharechahi et al., 2015)</ns0:ref>. Furthermore, only one study classified the rumen archaea <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. In the present study, total rRNA sequencing was applied to 1) get insight into the composition of active microbiota in the rumen of camels reared under different feeding systems; 2) describe the distribution of microbial groups among the solid and liquid rumen fractions; 3) investigate the correlations between all the microbial groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Rumen samples</ns0:head><ns0:p>Rumen samples were collected from eleven adult dromedary camels under three different feeding systems. Camels in group G1 (n=3) were housed in the Maryout Research Station, Alexendria, Egypt and were fed on Egyptian clover hay (Trifolium alexandrinum), wheat straw and concentrates feed mixture. Camels in group G2 (n=6) were fed on fresh Egyptian clover (100 % high-quality forage diet) then slaughtered in the Kom Hammada slaughterhouse, Elbehera, Egypt. Camels of group G3 (n=2) were fed on wheat straw (100 % low-quality forage diet) then were slaughtered in Pasateen slaughterhouse, Cairo, Egypt. All the animals kept on the diet for at least one month before the sampling time. The proximate analysis of feeds is illustrated in supplementary table <ns0:ref type='table'>S1</ns0:ref>. Details regarding the camel rumen samples in this study presented in Supplementary table <ns0:ref type='table'>S2</ns0:ref>. The rumen contents were strained immediately by two layers cheesecloth to separate the liquid and solid to form twenty-two samples, frozen using liquid nitrogen and stored at -80 o C before further processing <ns0:ref type='bibr' target='#b21'>(Elekwachi et al., 2017)</ns0:ref>. The project was approved and all samples were collected according to the Institutional Animal Care and Use Committee, Faculty of Veterinary Medicine, University of Sadat City, Egypt (Approval number: VUSC00003).</ns0:p></ns0:div> <ns0:div><ns0:head>RNA isolation, quality and quantity estimation and sequencing</ns0:head><ns0:p>The frozen rumen samples were ground using liquid nitrogen. About 0.5 gram of frozen fine powder was used for total RNA isolation using Trizol-Reagent protocol (Invitrogen, Carlsbad, CA), followed by RNA clean up using MEGA clear Kit (Invitrogen). Total RNA quality and quantity were estimated using an Agilent 2100 bioanalyzer (Agilent Technologies, USA) and RNA 6000 Nano kit (Agilent Technologies, USA). One hundred nanogram of total RNA was reversetranscribed into first strand cDNA and sequenced using Illumina rRNA MiSeq preparation kit (Illumina, USA) by Illumina MiSeq platform.</ns0:p></ns0:div> <ns0:div><ns0:head>Bioinformatic data analysis</ns0:head><ns0:p>The generated RNA sequence reads were analysed using pipeline developed by <ns0:ref type='bibr' target='#b21'>Elekwachi et al. (2017)</ns0:ref>. Briefly, the sequence quality was checked using the FastQC program v. 0.11.4 <ns0:ref type='bibr' target='#b0'>(Andrews, 2010)</ns0:ref>, then Trimmomatic program v. 0.35 <ns0:ref type='bibr' target='#b9'>(Bolger et al., 2014)</ns0:ref> was used to trim adaptors, barcodes, ambiguous and low quality reads. PEAR program v. 0.9.6 <ns0:ref type='bibr' target='#b96'>(Zhang et al., 2014)</ns0:ref> was used to merge read 1 and read 2 using default options. Then after, the hidden Markov models rRNA-HMM tool of the rapid analysis of multiple metagenomes with a clustering and annotation pipeline (RAMMCAP) <ns0:ref type='bibr' target='#b54'>(Li, 2009)</ns0:ref> was used to sort the reads into archaea and bacteria (16S, 23S), and eukaryote (18S, 23S) rRNA sequences. Merged sequence files were then sub-sampled as needed using MEME program v. 4.10.2 <ns0:ref type='bibr'>(Bailey et al., 2009)</ns0:ref>. For each sample, 70,000 reads were run through the pipeline. For subsequent analysis steps, 20 000, 10 000, and 2000 sequences were used for bacteria, eukaryote and archaea, respectively. Taxonomy binning for eukaryote and archaeal SSU rRNA sequences was performed using BLASTN. The sub-sampled query sequences were searched against the SILVA SSURef-111 database using an e-value of 1e -5 . Bacterial SSU sequences were binned into operational taxonomic units (OTUs) using the 'classify. seqs' command of Mothur v. 1.33.1 program <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref>. The SSURef -108 gene and the SSURef-108b taxonomy databases were used. Principal co-ordinate analysis (PCoA) using Bray Curtis dissimilarity and alpha diversity indices (Chao1, Shannon and Inverse Simpson) were evaluated by Mothur <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref> based on sub-sampling of 70,000 reads per sample according the protocol 'Community Structure Analysis Based on OTU Clustering' outlined in <ns0:ref type='bibr' target='#b21'>Elekwachi et al. (2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>Data of relative abundance of bacterial phyla, protozoal genera, fungal genera and archaea genera and order Thermoplasmatales were tested for normality and homogeneity using Shapiro-Wilk test and variables that were deemed non-normal were then arcsine transformed. Linear Discriminate Analysis (LDA) and Bray Curtis Permutational Multivariate Analysis of Variance (PERMANOVA) tests depended on the relative abundance of bacterial phyla. All the protozoal, fungal and archaeal genera and the order Thermoplasmatales were used to show the differences in community structure and to compare the clustering of samples. Pearson correlation analysis was used to identify correlation within and between microbial communities and the correlation scores were visualized as a heatmap. The statistical analyses were performed using the SPSS v. 20.0 software package (SPSS, 1999) and PAST <ns0:ref type='bibr' target='#b30'>(Hammer et al., 2001)</ns0:ref>. Sequences were deposited to the sequence read archive (SRA) under the accession number: SRP107370.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>The composition and diversity of active microbial community</ns0:head><ns0:p>Total rRNA sequencing in twenty-two solid and liquid rumen samples from eleven camels resulted in a total of 3958591 reads with average of 359872 &#177; 85366 (mean &#177; standard error (SE)) reads per animal in the solid fraction (SF) and 3386392 reads with an average of 307854 &#177; 60989 reads per animal in the liquid fraction (LF). The sequence reads of bacteria dominated the active microbial community, followed by protozoa, archaea and fungi (Table <ns0:ref type='table'>1</ns0:ref>). The relative abundance of protozoa was higher in LF-G1 (liquid fraction of G1), while the relative abundance of bacteria was higher in SF-G1 (solid fraction of G1). The highest population of archaea was observed in G2 camels. Additionally, G3 camels showed the highest relative abundance of fungi (Table <ns0:ref type='table'>1</ns0:ref>; Supplementary Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). Number of OTUs and Alpha-diversity indices, Chao1, Shannon and Inverse Simpson, were higher in the rumen of LF-G2 samples (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>The composition of bacterial community varied little between treatments and consisted of 12 phyla. The five most predominant phyla were Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetes and Fibrobacteres, respectively (Table <ns0:ref type='table'>2</ns0:ref>). Phylum Firmicutes dominated the bacterial community in all groups and was higher in G2 followed by G1 and G3 camels, respectively, and was also higher in SF compared to LF (Table <ns0:ref type='table'>2</ns0:ref>). On the family level, the Firmicutes phylum was dominated by Lachnospiraceae and Ruminococcuceae. In addition, six genera dominated this phylum, including Butyrivibrio, RFN8-YE57, Ruminococcus, vadinHA42, Acetitomaculum and Blautia (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and supplementary Table <ns0:ref type='table'>S3</ns0:ref>). The second largest phylum, Bacteroidetes, showed the highest relative abundance in G3 followed by G1 and G2 camels and was higher in LF than SF (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and supplementary Table <ns0:ref type='table'>S3</ns0:ref>). On the family and genera levels, Bacteroidetes was dominated by three families (Prevotellaceae, BS11_ gut_ group, Rikenellaceae) and two genera (Prevotella, RC9_gut_group) higher relative abundance in LF-G1 samples and was dominated by Succinivibrionaceae family and Desulfovibrio genus (Table <ns0:ref type='table'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, supplementary Table <ns0:ref type='table'>S3</ns0:ref>). The Spirochaetes phylum was higher in the SF-G3 and it was classified into two families including Spirochaetaceae and PL-11B10 and was dominated by Treponema genus. The Fibrobacteres phylum was higher in SF-G3 (Table <ns0:ref type='table'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, supplementary Table <ns0:ref type='table'>S3</ns0:ref>). The other phyla, including Actinobacteria, that was higher in SF-G2 samples, Tenricutes phylum was higher in the LF-G1 samples and Lentisphaerae phylum, was about 3-fold higher in the LF as relative to SF and accounted for a large population in the camels of G3 (Table <ns0:ref type='table'>2</ns0:ref>). Additionally, several minor bacterial phyla were also observed in the rumen of camels such as Verrucomicrobia, Elusimicrobia, Cyanobacteria and Chloroflexi (Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p><ns0:p>All Bacterial genera were observed in all groups except seven genera, including uncultured Marinilabiaceae (Bacteroidetes), Quinella (Firmicutes) and Streptococcus (Firmicutes) that were observed only in G2 and G3 camels. Ruminobacter (Proteobacteria) was observed only in G1 and G2 camels. On the other hand, Arcobacter and Succinivibrio within phylum Proteobacteria were observed only in G1 camels and Betaproteobacteria (Proteobacteria) was observed only in G3 camels. Moreover, many unclassified bacteria were observed across samples and accounted for 39% of total bacterial reads. Most of these unclassified bacterial reads were observed in phylum Firmicutes and Bacteroidetes.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>Reads that classified as archaea were further classified to three orders within the phylum Euryacheota: Thermoplasmatales, Methanobacteriale and Methanomicrobial. Thermoplasmatales dominated the archaeal community and showed the highest population in LF-G3 camels, this order was not classified out of order level (Table <ns0:ref type='table'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>). Reads that classified in the Methanobacteriale were further classified to family Methanobacteriacea that includes three genera: Methanobrevibacter, Methanophera and Methanobacterium. Methanobrevibacter is the second largest contributor in archaeal population and was higher in SF-G1 camels. Methanosphaera exhibited higher relative abundance in SF-G2 camels. Methanobacterium was absent in G3 camels; however, a small proportion of this genus was found in the camels of G1 and G2. Methanomicrobium genus, which belongs to order Methanomicrobiales and family Methanomicrobiaceae was the least contributor in archaeal population and was more prevalent in LF-G3 camels (Table <ns0:ref type='table'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>Reads that classified as protozoa were further classified to two families: Ophryoscolecidae and Isotrichidae (Table <ns0:ref type='table'>4</ns0:ref>). Reads that classified in the Ophryoscolecidae were further classified to seven genera, Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium, Epidinium and Trichostomatia. Reads that classified in the Isotrichidae were further classified to two genera, Dasytricha and Isotricha. The variation among the camels in protozoal population was clearly observed and seemed to be higher than other microbial communities; however, the protozoal community composition was similar among the camels (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>). The most dominant protozoal genera were Diplodinium, Ophryoscolex and Entodinium. Camels in G1 had the highest population of Entodinium and Epidinium. Camels in G2 had the greatest population of Eudiplodinium, Ophryoscolex, Isotricha and Dasytricha. The camels in G3 had the greatest population of Diplodinium, Polyplastron and Trichostomatia. On the sample fraction level, the solid fraction had a higher representation of Ophryoscolex, Polyplastron, Eudiplodinium, Epidinium and Diplodinium while the liquid fraction had a higher representation of Entodinium, Isotricha and Dasytricha (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2019:12:44048:4:0:NEW 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>Reads that classified as rumen fungi were further classified to two phyla: Neocallimastigomycota and Chytridiomycota. Reads that classified in the Neocallimastigomycota were further classified to family Neocallimasticeceae that includes three genera, Neocallimastix, Piromyces and Cyllamyces. Neocallimastix dominated the fungal community, followed by Piromyces and Cyllamyces (Table <ns0:ref type='table' target='#tab_1'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>). These anaerobic fungal genera represented &gt; 99.5 % of the fungal population. In addition, reads that classified in the Chytridiomycota were further classified to family Spizellomycetaceae that includes genus Spizellomyces, which was noted in a very small proportion (&lt;0.5 %) (Table <ns0:ref type='table' target='#tab_1'>5</ns0:ref>). Neocallimastix was more abundant in the SF-G1 samples while Piromyces and Cyllamyces were more abundant in LF-G2 and SF-G3 respectively (Table <ns0:ref type='table' target='#tab_1'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Effect of feeding system on the composition of microbial communities</ns0:head><ns0:p>Multivariate analysis separated libraries by feeding system distinctly (Figs. <ns0:ref type='figure' target='#fig_3'>2 and 3</ns0:ref>). Also, bacteria, dominated by phylum Firmicutes were the main driver of differences between animals (Fig. <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>). Furthermore, Entodinium, Thermoplasmatales, Neocallimastix were the main drivers of differences in protozoal, archaeal and fungal communities, respectively. PERMANOVA analysis revealed that the difference between camel groups was significant (P &lt; 0.01) in all microbial groups (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Pairwise comparison between camel groups based on Bonferroni-corrected p-value demonstrated that the difference was significant (P &lt; 0.05) between camels of G2 and G3 in bacterial and archaeal communities (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Moreover, the difference was significant between the three groups in the protozoal community (P &lt; 0.05) whereas, in the fungal community, the difference was significant only between camels in group G1 and G2 (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Pearson correlation between microbes in the rumen of dromedary camel</ns0:head><ns0:p>Pearson correlation analysis (Fig. <ns0:ref type='figure' target='#fig_5'>4A, 4B</ns0:ref>), revealed many significant positive and negative correlations (P &lt; 0.05). For example, in active bacteria, Bacteroidetes correlated positively with Cyllamyces and negatively with Butyrivibrio, Methanosphaera and Trichostomatia. Prevotellaceae correlated positively with Neocallimastix and Entodinium and negatively with Ruminococcaceae, Methanosphaera and Diplodinium. Fibrobacteres correlated positively with Cyllamyces, Methanomicrobium, Thermoplasmatales and Diplodinium and negatively with Methanosphaera, Epidinium, Ruminococcaceae and Butyrivibrio. Firmicutes correlated positively with Methanosphaera and negatively with Piromyces, Thermoplasmatales and Methanomicrobium.</ns0:p><ns0:p>In active archaea, Thermoplasmatales correlated positively with Diplodinium and negatively with Methanobrevibacter and Methanosphaera. In active protozoa, there was a negative correlation between Polyplastron, Entodinium, Ophryoscolex and Epidinium. In active fungi, a negative correlation was observed between Cyllamyces, Neocallimastix and Piromyces and between Piromyces and Entodinium.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Rumen microbes can ferment a wide variety of feed components, including cellulose, xylan, amylose and protein <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref> and produce volatile fatty acids that provide the animal with approximately 70% of daily energy requirements <ns0:ref type='bibr' target='#b5'>(Bergman, 1990)</ns0:ref>. Furthermore, the rumen fermentation generates methane, which contributes to global warming and represents 2-12% loss of feed energy for the animal <ns0:ref type='bibr' target='#b41'>(Johnson and Ward, 1996;</ns0:ref><ns0:ref type='bibr' target='#b13'>Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b38'>Jami et al., 2014)</ns0:ref>. Therefore, investigation of these microbial communities is the key to understand their roles and maximize ruminal fermentation and fiber digestion <ns0:ref type='bibr' target='#b53'>(Lee et al., 2012)</ns0:ref>. The rumen microbiome varied little between animals sampled. As predicted, feeding system had an impact on the microbial diversity and the relative abundance of microbial groups. PCoA, LDA and PERMANOVA analyses confirmed the finding of this study and was in agreement with the results of other ruminant studies <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Camels in the present study were fed on different forages; Egyptian clover and wheat straw (Supplementary Table <ns0:ref type='table'>S1</ns0:ref>). Egyptian clover is the most balanced and nutritious fodder widely used for feeding camels <ns0:ref type='bibr' target='#b13'>(Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr'>Bakheit, 2013;</ns0:ref><ns0:ref type='bibr' target='#b84'>Shrivastava et al., 2014)</ns0:ref>, which might supported the high microbial diversity in G2 camels compared to other groups (Table <ns0:ref type='table'>1</ns0:ref>). This was consistent with previous studies on cows <ns0:ref type='bibr' target='#b71'>(Pitta et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b83'>Shanks et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b48'>Kumar et al., 2015)</ns0:ref>. Highly degradable carbohydrates support the bacterial and protozoal growth <ns0:ref type='bibr' target='#b19'>(Dijkstra and Tamminga, 1995;</ns0:ref><ns0:ref type='bibr' target='#b48'>Kumar et al., 2015)</ns0:ref>, which could demonstrate their higher population in G1 camels. Additionally, the higher bacterial population slows the fungi growth <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992;</ns0:ref><ns0:ref type='bibr' target='#b65'>Orpin and Joblin, 1997)</ns0:ref>, which was illustrated by the low fungal population in G1 camels.</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>Firmicutes phylum was appeared more abundant than Bacteroidetes and both phyla comprised &gt; 75% of all bacterial reads (Table <ns0:ref type='table'>2</ns0:ref>), which is in agreement with previous studies on different animals including camels <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>, Surti Buffalo <ns0:ref type='bibr' target='#b66'>(Pandya et al., 2010)</ns0:ref> and Muskoxen <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref>. The majority of Firmicutes' members have a potential role in fiber digestion, which might illustrate their higher population in G2 camels that were fed on high-quality forage and also in solid fraction. This speculation was supported by the high proportion of Ruminococcaceae and Lachnospiraceae families that found to be active in fiber digestion in the rumen <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b61'>Nathani et al., 2015)</ns0:ref>. Bothe Blautia and Acetitomaculum genera have a key role as reductive acetogens (Le <ns0:ref type='bibr'>Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b95'>Yang et al., 2016)</ns0:ref> and varied with feeding system among the camel groups in this study. This finding could indicate that the reductive acetogenesis pathway could be maximized by diet to minimize methane production (Le <ns0:ref type='bibr'>Van et al., 1998)</ns0:ref>. Bacteroidetes were higher in poor quality forage (G3), which was similar to results found in cattle <ns0:ref type='bibr' target='#b69'>(Pitta et al., 2014b)</ns0:ref>. The phylum was dominated by family Prevotellaceae, which confirms <ns0:ref type='bibr' target='#b26'>Gharechahi et al. (2015)</ns0:ref>. The members of Bacteroidetes possess diverse enzymes that can target cellulose, pectin and soluble polysaccharides released in the liquid phase <ns0:ref type='bibr' target='#b58'>(Mackenzie et al., 2015)</ns0:ref>. Additionally, Prevotella genus is involved in propionate production that is used for energy by the host <ns0:ref type='bibr' target='#b61'>(Nathani et al., 2015)</ns0:ref>. We speculate that Bacteroidetes species contribute to the adaptation of camels to arid conditions. The RC9_gut_group found in this study belongs to uncultured genera and was found also in the gut of Rhinoceros hindgut <ns0:ref type='bibr' target='#b8'>(Bian et al., 2013)</ns0:ref>. Unclassified Bacteroidetes are specialized in lignocellulose degradation <ns0:ref type='bibr' target='#b58'>(Mackenzie et al., 2015)</ns0:ref>, which could support their high proportion in G3 camels. Fibrobacteres was higher (3.1%) in this study compared to the other findings on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>; this phylum is the principal cellulolytic bacteria in the rumen <ns0:ref type='bibr' target='#b75'>(Ransom-Jones et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b61'>Nathani et al., 2015)</ns0:ref>, which might illustrate its higher relative abundance in solid fraction and in the rumen of camels fed on wheat straw (G3) (Table <ns0:ref type='table'>2</ns0:ref>). The members of Proteobacteria were lower in G2 and G3 camels that were fed on diet rich in fiber contents. These findings highlighted this phylum's function as a protein-degrading bacteria as it was reported by <ns0:ref type='bibr' target='#b56'>Liu et al. (2017)</ns0:ref>. The abundance of Treponema was higher in the solid fraction and in G3 camels (Figure <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>). Treponema is the dominant genus in Spirochaetes phylum and it is fiber-associated bacteria, which could indicate to its cellulytic and xylanolytic activities <ns0:ref type='bibr' target='#b35'>(Ishaq and Wright, 2012)</ns0:ref>.</ns0:p><ns0:p>The dominant bacterial genera in this study were Butyriovibrio, RFN8-YE57, Ruminococcus, Prevotella, Fibrobacter, Treponema and VadinHA. These genera were higher in the SF except RFN8-YE57 compared to the LF; this finding was consistent with a previous study on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>, and confirms that the solid-attached microbes could play a major role in ruminal fiber digestion <ns0:ref type='bibr' target='#b39'>(Jewell et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b63'>Noel et al., 2017)</ns0:ref>. Most of Elusimicrobia in this study were uncultured; some members of this phylum were isolated from the termite's gut that degrades cellulose <ns0:ref type='bibr' target='#b32'>(Herlemann et al., 2009)</ns0:ref>. Therefore, we speculate that this phylum has a role in fiber digestion and that might illustrate their high proportion in G3 camels. Actinobacteria observed also in the rumen of moose and some members of this phylum have acetogenic activities <ns0:ref type='bibr' target='#b37'>(Ishaq et al., 2015)</ns0:ref>. Some members of Victivallis within Lentisphaerae phylum were involved in cellobiose degrading activity <ns0:ref type='bibr' target='#b97'>(Zoetendal et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Unclassified bacteria in our study (39% of total bacterial reads) were less than the percentage found in a study of Muskoxen (53.7-59.3%) <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref>. The presence of unclassified bacteria in the gut was commonly observed <ns0:ref type='bibr' target='#b27'>(Gruninger et al., 2016)</ns0:ref> and could be a result of the presence of new bacteria that ferment plant biomass <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref> or related to short reads were generated from RNAsequncing <ns0:ref type='bibr' target='#b55'>(Li et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>The archaeal population has important roles in the rumen and in methane emission mitigation strategies as they convert the H 2 and CO 2 produced in the rumen to methane <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010)</ns0:ref>. Additionally, acetate produced in fiber breakdown is used to provide a methyl group for methanogenesis; therefore, methanogens population could be shifted by alteration of diet composition or feed additives and plant compounds <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b88'>Tapio et al., 2017 )</ns0:ref>, which could demonstrate the variation in the relative abundance of archaea between camel groups. Camels of the second group (G2) that fed fresh clover, showed the highest archaeal population (Table <ns0:ref type='table'>2</ns0:ref>) and the archaeal community was dominated by Thermoplasmatales, a methylotrophic methanogens order (Table <ns0:ref type='table'>3</ns0:ref>) which was consistent with the results on cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref> and camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. Thermoplasmatales produces methane from methyl amine and its population was decreased by the addition of rapeseed oil to animal diet, making it a high potential target in future strategies to mitigate methane emissions <ns0:ref type='bibr' target='#b72'>(Poulsen et al., 2013)</ns0:ref>. The Methanobrevibacter, Methanosphaera, Methanomicrobium and Methanobacterium (Table <ns0:ref type='table'>4</ns0:ref>) are the other dominant archaea that were also observed in this study and in accordance with the results found in beef cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref>. Methanobrevibacter dominated the methanogens in other ruminant <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref> and was associated with high methane emissions <ns0:ref type='bibr' target='#b88'>(Tapio et al., 2017)</ns0:ref>. Moreover, Methanomicrobium had its highest proportion with the feeding system of poor quality forage diet (G3), which was similar to results found in buffalo <ns0:ref type='bibr' target='#b23'>(Franzolin and Wright, 2016)</ns0:ref>, and In vitro <ns0:ref type='bibr' target='#b90'>(Wang et al., 2018)</ns0:ref>. In rumen, Methanomicrobium has been shown to be responsible for the conversion of H 2 and/or formate into CH 4 <ns0:ref type='bibr' target='#b51'>(Leahy et al., 2013)</ns0:ref>. The abundance of Thermoplasmatales was also negatively correlated with Methanobrevibacter which is consistent with previous results <ns0:ref type='bibr' target='#b16'>(Danielsson et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b59'>McGovern et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>The majority of protozoal reads were related to Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium and Epidinium (Table <ns0:ref type='table'>4</ns0:ref>). Similar findings were observed in other study on different ruminants <ns0:ref type='bibr' target='#b4'>(Baraka, 2012)</ns0:ref>. The relative abundance of protozoal was influenced by feeding system, which was in the same line with results on cattle <ns0:ref type='bibr' target='#b34'>(Hristov et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b91'>Weimer, 2015)</ns0:ref>. The Diplodinium dominated the protozoal community and was prevalent in the G3 camels, which highlighted the cellulolytic activity of this genus <ns0:ref type='bibr' target='#b14'>(Coleman et al., 1976)</ns0:ref>. Also, some species of genus Diplodinium were discovered in the rumen of Egyptian camel and is considered to be peculiar in camel such as Diplodinium cameli, <ns0:ref type='bibr' target='#b47'>(Kubesy and Dehority, 2002)</ns0:ref>. In addition, Entodinium was higher in G1 camels that were fed on concentrates feed mixture that increase the protozoa. Also, previous studies showed that this genus was dominant in rumen of camels <ns0:ref type='bibr' target='#b82'>(Selim et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b25'>Ghali et al., 2005)</ns0:ref> and cattle <ns0:ref type='bibr' target='#b13'>(Carberry et al., 2012)</ns0:ref>. Moreover, the study of <ns0:ref type='bibr' target='#b46'>Kittelmann and Janssen (2011)</ns0:ref> showed that the Polyplastron was the dominant genus in cattle. On the function level, all the genus Eudiplidinum, Epidinum and Diplodinum have cellulolytic activity <ns0:ref type='bibr' target='#b14'>(Coleman et al., 1976)</ns0:ref> whereas, Polyplastrone and Epidinium have a xylanolytic activity <ns0:ref type='bibr' target='#b18'>(Devillard, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>B&#233;ra-Maillet et al., 2005)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>The highest fungal population was observed in the solid fraction and rumen of G3 camels (Table <ns0:ref type='table'>1</ns0:ref>). These findings were in agreement with the results of different studies stated that the fibre-based diets stimulated the fungal growth <ns0:ref type='bibr' target='#b64'>(Orpin, 1977;</ns0:ref><ns0:ref type='bibr' target='#b77'>Roger et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b42'>Kamra et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b29'>Haitjema et al., 2014)</ns0:ref>. This speculation could explain the low fungal population in G1 camels in our study. Moreover, the longer retention time and neutral pH in camel's forestomach <ns0:ref type='bibr' target='#b78'>(Russell and Wilson, 1996)</ns0:ref> make it more suitable for the survival of rumen fungi. The genus Neocallimastix dominated the fungal community and found to be higher in the G1 camels which was similar to other results on sheep and camels <ns0:ref type='bibr' target='#b45'>(Kittelmann et al., 2013</ns0:ref><ns0:ref type='bibr' target='#b74'>, Rabee et al., 2019)</ns0:ref>. This genus produces enzymes capable of hydrolyzing cellulose, xylan and starch <ns0:ref type='bibr' target='#b67'>(Pearce and Bauchop, 1985)</ns0:ref>. In the other side, Cyllamyces that was observed in small population, has the ability to degrade poor-quality feeds <ns0:ref type='bibr' target='#b86'>(Sridhar et al., 2014)</ns0:ref>, which might explain its high population in solid fraction and G3 camels. Piromyces was the second dominant genus in the camel rumen of this study and has been shown to produce cellulolytic and xylanolytic enzymes <ns0:ref type='bibr' target='#b89'>(Teunissen et al., 1992)</ns0:ref>. Therefore, the fungi were more prevalent in ruminants of G2 camels, which fed high-quality forage with high fiber contents than in G2 and G3 camels. The genus Spizellomyces is closely related to Chytridiomctes <ns0:ref type='bibr' target='#b10'>(Bowman et al., 1992)</ns0:ref>, and common in grassland and crop soil <ns0:ref type='bibr' target='#b57'>(Lozupone and</ns0:ref><ns0:ref type='bibr'>Klein, 2002, Kittelmann et al., 2012)</ns0:ref>. Thus, the presence of this fungus in the camel rumen in the current study could be explained by a contamination of the forages by soil.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between rumen microbes</ns0:head><ns0:p>The interactions between rumen microbes are the main driver of feed degradation and methane formation in the rumen, which influence the animal production and the environment <ns0:ref type='bibr' target='#b92'>(Williams et al., 1994;</ns0:ref><ns0:ref type='bibr' target='#b53'>Lee et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Positive and negative correlations were observed within and between microbial communities in this study (Fig. <ns0:ref type='figure' target='#fig_5'>4</ns0:ref>). Methanogens colonize the protozoa and this relationship was believed to enhance methane formation <ns0:ref type='bibr' target='#b62'>(Newbold et al., 1995)</ns0:ref>, which highlighted some positive correlations between protozoa and archaea. Additionally, the fibrolytic bacteria produce the important substrates mainly hydrogen and methyl groups that methanogens use for growth <ns0:ref type='bibr' target='#b40'>(Johnson and Johnson, 1995)</ns0:ref>, which demonstrated the positive correlations found between Fibrobacteres and some methanogens. Also, positive correlation between the methylotrophic Methanosphaera and Lachnospiraceae that has been implicated in pectin degradation and provides methanol as a substrate for the methylotrophs <ns0:ref type='bibr' target='#b17'>(Dehority, 1969)</ns0:ref>. On the other hand, Prevotella is a hydrogen utilizer and produces propionate which has a negative impact on methanogenesis in the rumen <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b56'>Liu et al., 2017)</ns0:ref>, which also illustrated the negative correlation obtained in this study between Prevotellaceae and archaea.</ns0:p><ns0:p>Since the rumen anaerobic fungi produce abundant H 2 through the fermentation of carbohydrate; they can interact positively with H 2 utilizers such as archaea, Prevotellaceae, Blautia and Acetitomaculum <ns0:ref type='bibr' target='#b65'>(Orpin and Joblin, 1997;</ns0:ref><ns0:ref type='bibr'>Le Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b95'>Yang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b56'>Liu et al., 2017)</ns0:ref>. Additionally, the anaerobic fungi penetrate plant tissue, which provides an increased surface area for bacterial colonization <ns0:ref type='bibr' target='#b65'>(Orpin and Joblin, 1997)</ns0:ref>, which could explain the positive correlation between fungi and both Butyrivibrio and Fibrobacteres in this study. However, fungi are known to be negatively impacted by the presence of some bacteria and protozoa as the fungal zoospores are likely to be a prey for protozoa <ns0:ref type='bibr' target='#b60'>(Morgavi et al., 1994)</ns0:ref>, which demonstrated the negative correlation between both Neocallimastix and Piromyces with Diplodinium and Entodinium. Furthermore, Ruminococcus produces compounds that inhibit the growth of rumen fungi <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992)</ns0:ref>, which support the negative correlation between Neocallimastix and Ruminococcaceae. Polyplastron predates upon other protozoa like Epidinium, Eudiplodinium, Diplodinium, and Ostracodinium <ns0:ref type='bibr' target='#b20'>(Eadie, 1967)</ns0:ref>, which might explained the negative correlation between Polyplastron and other Protozoa.</ns0:p><ns0:p>This study applied the rRNA sequencing to identify the metabolically active microbial groups in the rumen of three camel groups fed different diets and reared under different housing systems. Also, RNA in some samples was degraded during the processing, which generated unequal sample numbers between the camel groups. Therefore, using a high number of animals reared under different treatments under the same housing system is recommended in future studies.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study applied total rRNA sequencing to get insight into the active microbial groups in the rumen of dromedary camels. However, using the DNA-amplicon sequencing with RNA sequencing is recommended in the future studies to compare the composition of active microbial groups (from RNA sequencing) with the composition of the whole microbial community. As a major conclusion of our study, the microbial community in camel rumen was diverse and similar in composition between the camels. However, the feeding system impacted the relative abundance of active microbial communities where the fresh Egyptian clover provided the highest microbial diversity. The majority of camel rumen microbes (bacteria, fungi, and protozoa) were fibrolytic or have a possible role in fiber digestion, which might illustrate the ability of camel to live in desert harsh conditions under poor feeds. Moreover, the structure of microbial community in rumen of camel found to be similar to other ruminant studies with a shown difference in the relative abundances. The present results should open new perspectives for further cultivation and isolation studies on the unclassified microorganisms found in the rumen of camels to classify them and assign their functions.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>The relative abundance of microbial groups Manuscript to be reviewed Relative abundance (%) of fungal genera </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Comparison of relative abundance of genera of the microbiota in dromedary camel. bacterial (a), archaeal (b), protozoal (c) and fungi (d) in ruminal solid (SF) and liquid (LF) fractions of camels under different feeding systems.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3:Linear Discriminant analysis of microbial communities in the samples based on the relative abundance of genera of active bacteria (a), archaea (b), protozoa (c) and fungi i (d)in ruminal solid (SF), and liquid (LF) fractions of camels under three feeding systems, G1 (black dots), G2 (blue squares) and G3 (coral triangles).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4: Heatmap based on Pearson correlation coefficients between and within the relative abundance of bacteria, archaea, protozoa and fungi in solid (A) and liquid (B) rumen fractions of dromedary camel. The black boxed ellipses refer to the significant correlations at P &lt; 0.05.</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 5 :</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Relative abundance (%) of fungal genera in the ruminal solid (SF) and liquid fraction (LF) of camels under different feeding systems. Camels in G1 fed a mixed ration, animals in G2 fed high-quality forage, and animals in G3 fed low-quality forage (Mean &#177; SE).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Fungi</ns0:cell><ns0:cell>G1</ns0:cell><ns0:cell>G2</ns0:cell><ns0:cell>G3</ns0:cell><ns0:cell>Overall mean</ns0:cell></ns0:row><ns0:row><ns0:cell>Spizellomyces SF</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0.09</ns0:cell><ns0:cell>0.017</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>Spizellomyces LF 0.3 &#177; 0.1 0.25 &#177; 0.1</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces SF</ns0:cell><ns0:cell>2&#177; 0.6</ns0:cell><ns0:cell>3&#177; 1.5</ns0:cell><ns0:cell>7&#177; 4</ns0:cell><ns0:cell>3.5&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces LF</ns0:cell><ns0:cell>2&#177; 0.78</ns0:cell><ns0:cell>3&#177; 0.8</ns0:cell><ns0:cell>10&#177; 1</ns0:cell><ns0:cell>4&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces SF</ns0:cell><ns0:cell>6&#177; 3</ns0:cell><ns0:cell>12&#177; 0.7</ns0:cell><ns0:cell>8&#177; 1</ns0:cell><ns0:cell>9&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces LF</ns0:cell><ns0:cell>6&#177;4</ns0:cell><ns0:cell>12&#177;2</ns0:cell><ns0:cell>10&#177;6</ns0:cell><ns0:cell>10&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix SF</ns0:cell><ns0:cell>92&#177;3</ns0:cell><ns0:cell>85&#177;1</ns0:cell><ns0:cell>85&#177;3</ns0:cell><ns0:cell>87&#177;1</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix LF</ns0:cell><ns0:cell>92&#177;4</ns0:cell><ns0:cell>85&#177;1.5</ns0:cell><ns0:cell>81&#177;7</ns0:cell><ns0:cell>86&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>ND: Non Determined</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:12:44048:4:0:NEW 8 Jun 2020) Manuscript to be reviewed PeerJ reviewing PDF | (2019:12:44048:4:0:NEW 8 Jun 2020)</ns0:note></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2019:12:44048:4:0:NEW 8 Jun 2020)</ns0:note> </ns0:body> "

" Desert Research Center 8th June, 2020 1Mathaf El Matariya St.B.O.P.11753 Matariya- Cairo,Egypt Phone: (+202)26332846 - 26374800 FAX: (+202) 26357858 Email: [email protected] [email protected] Dear Editor, We thank you for your comments. We responded to all of your valuable comments and enclosed unclean paper including all comments colored by yellow. Below are the responses to all the comments. We appreciate the opportunity to submit our manuscript to Peer J. Yours sincerely, Dr. Alaa Rabee Researcher at Desert Research Center, Egypt On behalf of all authors Comments Manuscript title: “Comparative analysis of the metabolically active microbial communities in the rumen of dromedary camels under different feeding systems using total rRNA sequencing ” Editor’s comments On further review, it appears that camels receiving different treatments (feed) were housed in different facilities (line 126). This would make it difficult to differentiate the difference between feed and facility. I do not think this is a fatal case of pseudoreplication (Hurlbert 1984) but I do think Methods have to be clarified and this potential flaw in experimental design, as well as the limited number of samples, needs to be addressed in Discussion. >>Thank you for your comment, we have added a section at the end of the discussion to address this issue. Also, supplementary table S1 has all the required details about the animals. Figure 2 is not publication quality. >> We have sent all the figures in EPS format with high quality format for the production. Line 46. Remove extra period. >> Removed Line 53. Replace “This study...of the rumen” with something more specific like “This provides preliminary evidence that bacteria dominate the microbial communities of the camel rumen and that feed changes that microbiome.” >> Thank you, modified. Line 62. Delete “daily human activities such as.” >>Deleted Line 70. Revise to “concentrated” >> Modified, thank you. Line 76. Replace “...sugars are the...favoring the amylolytic” with “sugars favor amylolytic” >> Modified. Line 77. Present published facts in present tense. Replace “varied” with “varies” >> Replaced. Line 81 -89. This section needs reorganization. Move the last sentence up to the start of the paragraph. Revise to “The efficiency of microbial fermentations in the rumen depends on ...Kamra, 2005). Analysis of these microbial communities could lead to increases in animal productivity and reduction of greenhouse gas emissions ....” >> Modified, thank you. Line 90. Replace “The development of the next-generation sequencing technologies...for the rapid identification...” with “Next generation sequencing technologies provide a rapid method of microbial identification... >> Replaced. Line 108. Replace “All the” with “Previous” >> Replaced. Line 113. Move “Regarding the anaerobic...camel.” to before “Only three molecular-...(line 111). >> Moved, thank you. Line 116. Delete “Moreover, no study provided ....the camel.” >> Deleted. Line 130. Present parallel things in parallel form. “Camels in group G1...” Camels in group G2..” Camels in group G3...” >> Modified. Line 132-133. These sentences need verbs. >> Revised. Line 178. Delete “All the” >> Deleted. Line 183. Here and throughout, present reasonable significant figures (359872 ± 85366). See also line 221 (39% not 38.53%) and Table 1, 3 and 4. >> Modified. Line 224. Replace with “Reads that classified as archaea were further classified to three orders with in the phylum Euryacheota: Thermoplasmatales ..” >> Replaced. Line 228. Replace “All the Methanobacteriale reads were belonged to family” with “Reads that classified in the ... were further classified...” >> Modified, thank you. Line 237. Follow the example provided above for the protozoa (“Reads that classified as protozoa were further...”) and fungi. >> Modified. Line 310. Replace “was found to be” with “appeared” >>Replaced. Line 311. Delete “with the results of” >> Deleted. Line 329. I stop edits here. The authors must revise this section for style. >> Thank you, we revised it and improved it. Line 470. “Nucleic acids research 37: ?” >> It is a web Server Issue and we modified it, you could check: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2703892/ Line 491. Why do some references have a period after the page number and some do not? >> all references were revised, thank you. Line 503. Why do some references provide the issue but most do not? >> the issue numbers were removed according the journal style. Line 507, 509, 521, 551.... Cap first letter of journal titles. (Frontiers in microbiology 8:e226, Journal of bacteriology). >> Modified. Line 531. Is this a journal? Why is it formatted differently and who cares when you accessed it? >> Modified, thank you. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The breakdown of plant biomass in rumen depends on interactions between bacteria, archaea, fungi, and protozoa; however, the majority of studies of the microbiome of ruminants, including the few studies of the rumen of camels, only studied one of these microbial groups. In this study, we applied total rRNA sequencing to identify active microbial communities in twenty-two solid and liquid rumen samples from eleven camels reared under three feeding systems. These camels were separated in three groups, G1 (n=3), G2 (n=6) and G3 (n=2) and fed Egyptian clover hay and wheat straw and concentrates feed mixture, fresh Egyptian clover, and wheat straw, respectively. Bacteria dominated the libraries of reads generated from all rumen samples, followed by protozoa, archaea, and fungi respectively. Firmicutes, Thermoplasmatales, Diplodinium, and Neocallimastix dominated bacterial, archaeal, protozoal and fungal communities, respectively in all samples. Feeding systems influenced the microbial diversity and relative abundance of microbial groups; libraries generated from camels fed fresh clover showed the highest alpha diversity. Principal co-ordinate analysis and linear discriminate analysis showed clusters associated with feeding system and the relative abundance of microbes varied between liquid and solid fractions. In addition, the analysis showed positive and negative correlations between the microbial groups. This provides preliminary evidence that bacteria dominate the microbial communities of the camel rumen and that feed changes that microbiome.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Camels (Camelus dromedaries) can produce milk and meat in hot, arid and semi-arid regions and can provide food security as the climate warms <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b22'>Faye, 2013)</ns0:ref>. Camels also provide textiles (fiber and hair) and are commonly used for transportation, agriculture, tourism, race and riding <ns0:ref type='bibr' target='#b74'>(Rabee et al., 2019)</ns0:ref>. The unique feeding behavior and the functional structure of digestive tract of these pseudo-ruminants is well adapted to deserts <ns0:ref type='bibr' target='#b44'>(Kay et al., 1989)</ns0:ref>. The retention time of feed particles in the camel forestomach is longer than other true ruminants, which prolongs the exposure of plant biomasses to the symbiotic microorganisms, which helps the efficient digestion <ns0:ref type='bibr'>(Lechner-Dolland and Engelhardt, 1989)</ns0:ref>. Based on feeding type, camel production lies under three systems: camels in traditional extensive system depend on low quality feeds; while, camels in semi-intensive system depend on highquality forage and camels in intensive system depend on high-quality forage and concentrated supplements <ns0:ref type='bibr' target='#b22'>(Faye, 2013)</ns0:ref>. Diet and feeding plan, determine the diversity of rumen microbial communities but age, animal breed can also influence the structure of this microbiome <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. The chemical composition of the diet shapes fermentation in the rumen. For instance, cellulolytic and hemicellulytic diets favor the fibrolytic microorganisms; while, starch and sugars favor the amylolytic <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012)</ns0:ref>. Also, the microbial composition and diversity varies between liquid and solid rumen fractions, which might indicate different roles in rumen fermentation; for instance, plant-adherent microbiota might have a major role in fiber degradation <ns0:ref type='bibr' target='#b76'>(Ren et al., 2020)</ns0:ref>. Digestion in the camel depends on microbial fermentation in the rumen <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref> and the efficiency of this microbial fermentations is based on the interactions between a wide variety of microbial groups, including bacteria, archaea, fungi and protozoa <ns0:ref type='bibr' target='#b93'>(Yanagita et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra, 2005)</ns0:ref>. Analysis of these microbial communities could lead to increases in animal productivity and reduction of greenhouse gas emissions <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Unlike other ruminants, camels can utilize thorny and low quality plants like shrubs with high lignocelulolytic content <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>. Consequently, camel rumen microbes must have the capacity to degrade such poor-quality feeds <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. However, the microbial community in the rumen of dromedary camel received less attention than other domesticated ruminants. Most of PCR-based assessments of microbial groups in the rumen have relied on amplicon sequencing, which target a specific variable region on 16S rRNA gene <ns0:ref type='bibr' target='#b56'>(Li et al. 2016)</ns0:ref>. This approach needs a wide range of primers to study different microbial communities <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013)</ns0:ref>. Therefore, the output could be biased due to the primer selection and amplification cycling conditions <ns0:ref type='bibr' target='#b28'>(Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b21'>Elekwachi et al., 2017)</ns0:ref>. The recent development of next generation sequencing technologies provide a rapid method of microbial identification in rumen and overcome the intrinsic constraints of traditional culture-based methods <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b36'>Ishaq and Wright, 2014)</ns0:ref>. Total RNA sequencing (RNA-Seq) offers the advantage of specifically targeting active microbes and avoids biases associated with primer selection and chimera generation in PCR <ns0:ref type='bibr' target='#b24'>(Gaidos et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b28'>Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016)</ns0:ref>. In addition, RNA-Seq approach is capable of identifying novel microbes as it is not reliant on primers for known microbes <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>. Highthroughput metatranscriptome sequencing provides a comprehensive understanding of the biological systems by characterization of different groups of organisms in the same environment based on the sequencing of coding and noncoding RNA <ns0:ref type='bibr' target='#b21'>(Elekwachi et al., 2017)</ns0:ref>. Total RNA-Seq was applied to investigate microbial communities in many different systems including, for example, human gut <ns0:ref type='bibr' target='#b73'>(Qin et al., 2012)</ns0:ref>, and cow rumen <ns0:ref type='bibr' target='#b56'>(Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b21'>Elekwachi et al., 2017 )</ns0:ref>.</ns0:p><ns0:p>Previous microbiome studies on the camel rumen have characterized one or two microbial groups using classical or molecular approaches. For example, the protozoal community in camel rumen was studied heavily by conventional microscopic methods <ns0:ref type='bibr' target='#b25'>(Ghali et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b4'>Baraka, 2012)</ns0:ref>. Regarding the anaerobic fungi, a new fungal genus, Oontomyces was isolated from the rumen of Indian camel <ns0:ref type='bibr' target='#b15'>(Dagar et al., 2015)</ns0:ref>, and only one study investigated the whole fungal community in the gut of the camel <ns0:ref type='bibr' target='#b74'>(Rabee et al., 2019)</ns0:ref>. Only three molecular-based studies are available on the bacterial community <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b7'>Bhatt et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b26'>Gharechahi et al., 2015)</ns0:ref>. Furthermore, only one study classified the rumen archaea <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. In the present study, total rRNA sequencing was applied to 1) get insight into the composition of active microbiota in the rumen of camels reared under different feeding systems; 2) describe the distribution of microbial groups among the solid and liquid rumen fractions; 3) investigate the correlations between all the microbial groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Rumen samples</ns0:head><ns0:p>Rumen samples were collected from eleven adult dromedary camels under three different feeding systems. Camels in group G1 (n=3) were housed in the Maryout Research Station, Alexendria, Egypt and were fed on Egyptian clover hay (Trifolium alexandrinum), wheat straw and concentrates feed mixture. Camels in group G2 (n=6) were fed on fresh Egyptian clover (100 % high-quality forage diet) then slaughtered in the Kom Hammada slaughterhouse, Elbehera, Egypt. Camels of group G3 (n=2) were fed on wheat straw (100 % low-quality forage diet) then were slaughtered in Pasateen slaughterhouse, Cairo, Egypt. All the animals kept on the diet for at least one month before the sampling time. The proximate analysis of feeds is illustrated in Supplementary table <ns0:ref type='table'>S1</ns0:ref>. Details regarding the camel rumen samples in this study presented in Supplementary table <ns0:ref type='table' target='#tab_2'>S2</ns0:ref>. The rumen contents were strained immediately by two layers cheesecloth to separate the liquid and solid to form twenty-two samples, frozen using liquid nitrogen and stored at -80 o C before further processing <ns0:ref type='bibr' target='#b21'>(Elekwachi et al., 2017)</ns0:ref>. The project was approved and all samples were collected according to the Institutional Animal Care and Use Committee, Faculty of Veterinary Medicine, University of Sadat City, Egypt (Approval number: VUSC00003).</ns0:p></ns0:div> <ns0:div><ns0:head>RNA isolation, quality and quantity estimation and sequencing</ns0:head><ns0:p>The frozen rumen samples were ground using liquid nitrogen. About 0.5 gram of frozen fine powder was used for total RNA isolation using Trizol-Reagent protocol (Invitrogen, Carlsbad, CA), followed by RNA clean up using MEGA clear Kit (Invitrogen). Total RNA quality and quantity were estimated using an Agilent 2100 bioanalyzer (Agilent Technologies, USA) and RNA 6000 Nano kit (Agilent Technologies, USA). One hundred nanogram of total RNA was reversetranscribed into first strand cDNA and sequenced using Illumina rRNA MiSeq preparation kit (Illumina, USA) by Illumina MiSeq platform.</ns0:p></ns0:div> <ns0:div><ns0:head>Bioinformatic data analysis</ns0:head><ns0:p>The generated RNA sequence reads were analysed using pipeline developed by <ns0:ref type='bibr' target='#b21'>Elekwachi et al. (2017)</ns0:ref>. Briefly, the sequence quality was checked using the FastQC program v. 0.11.4 <ns0:ref type='bibr' target='#b0'>(Andrews, 2010)</ns0:ref>, then Trimmomatic program v. 0.35 <ns0:ref type='bibr' target='#b9'>(Bolger et al., 2014)</ns0:ref> was used to trim adaptors, barcodes, ambiguous and low quality reads. PEAR program v. 0.9.6 <ns0:ref type='bibr' target='#b95'>(Zhang et al., 2014)</ns0:ref> was used to merge read 1 and read 2 using default options. Then after, the hidden Markov models rRNA-HMM tool of the rapid analysis of multiple metagenomes with a clustering and annotation pipeline (RAMMCAP) <ns0:ref type='bibr' target='#b55'>(Li, 2009)</ns0:ref> was used to sort the reads into archaea and bacteria (16S, 23S), and eukaryote (18S, 23S) rRNA sequences. Merged sequence files were then sub-sampled as needed using MEME program v. 4.10.2 <ns0:ref type='bibr'>(Bailey et al., 2009)</ns0:ref>. For each sample, 70,000 reads were run through the pipeline. For subsequent analysis steps, 20 000, 10 000, and 2000 sequences were used for bacteria, eukaryote and archaea, respectively. Taxonomy binning for eukaryote and archaeal SSU rRNA sequences was performed using BLASTN. The sub-sampled query sequences were searched against the SILVA SSURef-111 database using an e-value of 1e -5 . Bacterial SSU sequences were binned into operational taxonomic units (OTUs) using the 'classify. seqs' command of Mothur v. 1.33.1 program <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref>. The SSURef -108 gene and the SSURef-108b taxonomy databases were used. Principal co-ordinate analysis (PCoA) using Bray Curtis dissimilarity and alpha diversity indices (Chao1, Shannon and Inverse Simpson) were evaluated by Mothur <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref> based on sub-sampling of 70,000 reads per sample according the protocol 'Community Structure Analysis Based on OTU Clustering' outlined in <ns0:ref type='bibr' target='#b21'>Elekwachi et al. (2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>Data of relative abundance of bacterial phyla, protozoal genera, fungal genera and archaea genera and order Thermoplasmatales were tested for normality and homogeneity using Shapiro-Wilk test and variables that were deemed non-normal were then arcsine transformed. Linear Discriminate Analysis (LDA) and Bray Curtis Permutational Multivariate Analysis of Variance (PERMANOVA) tests depended on the relative abundance of bacterial phyla. All the protozoal, fungal and archaeal genera and the order Thermoplasmatales were used to show the differences in community structure and to compare the clustering of samples. Pearson correlation analysis was used to identify correlation within and between microbial communities and the correlation scores were visualized as a heatmap. The statistical analyses were performed using the SPSS v. 20.0 software package (SPSS, 1999) and PAST <ns0:ref type='bibr' target='#b30'>(Hammer et al., 2001)</ns0:ref>. Sequences were deposited to the sequence read archive (SRA) under the accession number: SRP107370.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>The composition and diversity of active microbial community</ns0:head><ns0:p>Total rRNA sequencing in twenty-two solid and liquid rumen samples from eleven camels resulted in a total of 3958591 reads with average of 359872 &#177; 85366 (mean &#177; standard error (SE)) reads per animal in the solid fraction (SF) and 3386392 reads with an average of 307854 &#177; 60989 reads per animal in the liquid fraction (LF). The sequence reads of bacteria dominated the active microbial community, followed by protozoa, archaea and fungi (Table <ns0:ref type='table'>1</ns0:ref>). The relative abundance of protozoa was higher in LF-G1 (liquid fraction of G1), while the relative abundance of bacteria was higher in SF-G1 (solid fraction of G1). The highest population of archaea was observed in G2 camels. Additionally, G3 camels showed the highest relative abundance of fungi (Table <ns0:ref type='table'>1</ns0:ref>; Supplementary Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>). Number of OTUs and Alpha-diversity indices, Chao1, Shannon and Inverse Simpson, were higher in the rumen of LF-G2 samples (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>The composition of bacterial community varied little between treatments and consisted of 12 phyla. The five most predominant phyla were Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetes and Fibrobacteres, respectively (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Phylum Firmicutes dominated the bacterial community in all groups and was higher in G2 followed by G1 and G3 camels, respectively, and was also higher in SF compared to LF (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). On the family level, the Firmicutes phylum was dominated by Lachnospiraceae and Ruminococcuceae. In addition, six genera dominated this phylum, including Butyrivibrio, RFN8-YE57, Ruminococcus, vadinHA42, Acetitomaculum and Blautia (Fig. <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref> and Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). The second largest phylum, Bacteroidetes, showed the highest relative abundance in G3 followed by G1 and G2 camels and was higher in LF than SF (Fig. <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref> and Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). On the family and genus levels, Bacteroidetes was dominated by three families (Prevotellaceae, BS11_ gut_ group, Rikenellaceae) and two genera (Prevotella, RC9_gut_group) higher relative abundance in LF-G1 samples and was dominated by Succinivibrionaceae family and Desulfovibrio genus (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref>, Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). The Spirochaetes phylum was higher in the SF-G3 and it was classified into two families including Spirochaetaceae and PL-11B10 and was dominated by Treponema genus. The Fibrobacteres phylum was higher in SF-G3 (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref>, Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). The other phyla, including Actinobacteria, that was higher in SF-G2 samples, Tenricutes phylum was higher in the LF-G1 samples and Lentisphaerae phylum, was about 3-fold higher in the LF as relative to SF and accounted for a large population in the camels of G3 (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Additionally, several minor bacterial phyla were also observed in the rumen of camels such as Verrucomicrobia, Elusimicrobia, Cyanobacteria and Chloroflexi (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>).</ns0:p><ns0:p>All Bacterial genera were observed in all groups except seven genera, including uncultured Marinilabiaceae (Bacteroidetes), Quinella (Firmicutes) and Streptococcus (Firmicutes) that were observed only in G2 and G3 camels. Ruminobacter (Proteobacteria) was observed only in G1 and G2 camels. On the other hand, Arcobacter and Succinivibrio within phylum Proteobacteria were observed only in G1 camels and Betaproteobacteria (Proteobacteria) was observed only in G3 camels. Moreover, many unclassified bacteria were observed across samples and accounted for 39% of total bacterial reads. Most of these unclassified bacterial reads were observed in phylum Firmicutes and Bacteroidetes.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>Reads that classified as archaea were further classified to three orders within the phylum Euryacheota: Thermoplasmatales, Methanobacteriale and Methanomicrobial. Thermoplasmatales dominated the archaeal community and showed the highest population in LF-G3 camels, this order was not classified out of order level (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1b</ns0:ref>). Reads that classified in the Methanobacteriale were further classified to family Methanobacteriacea that includes three genera: Methanobrevibacter, Methanophera and Methanobacterium. Methanobrevibacter is the second largest contributor in archaeal population and was higher in SF-G1 camels. Methanosphaera exhibited higher relative abundance in SF-G2 camels. Methanobacterium was absent in G3 camels; however, a small proportion of this genus was found in the camels of G1 and G2. Methanomicrobium genus, which belongs to order Methanomicrobiales and family Methanomicrobiaceae was the least contributor in archaeal population and was more prevalent in LF-G3 camels (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1b</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>Reads that classified as protozoa were further classified to two families: Ophryoscolecidae and Isotrichidae (Table <ns0:ref type='table'>4</ns0:ref>). Reads that classified in the Ophryoscolecidae were further classified to seven genera, Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium, Epidinium and Trichostomatia. Reads that classified in the Isotrichidae were further classified to two genera, Dasytricha and Isotricha. The variation among the camels in protozoal population was clearly observed and seemed to be higher than other microbial communities; however, the protozoal community composition was similar among the camels (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1c</ns0:ref>). The most dominant protozoal genera were Diplodinium, Ophryoscolex and Entodinium. Camels in G1 had the highest population of Entodinium and Epidinium. Camels in G2 had the greatest population of Eudiplodinium, Ophryoscolex, Isotricha and Dasytricha and camels in G3 had the greatest population of Diplodinium, Polyplastron and Trichostomatia. On the sample fraction level, the solid fraction had a higher representation of Ophryoscolex, Polyplastron, Eudiplodinium, Epidinium and Diplodinium, while the liquid fraction had a higher representation of Entodinium, Isotricha and Dasytricha (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1c</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2019:12:44048:5:0:NEW 23 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>Reads that classified as rumen fungi were further classified to two phyla: Neocallimastigomycota and Chytridiomycota. Reads that classified in the Neocallimastigomycota were further classified to family Neocallimasticeceae that includes three genera, Neocallimastix, Piromyces and Cyllamyces. Neocallimastix dominated the fungal community, followed by Piromyces and Cyllamyces (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1d</ns0:ref>). These anaerobic fungal genera represented &gt; 99.5 % of the fungal population. In addition, reads that classified in the Chytridiomycota were further classified to family Spizellomycetaceae that includes genus Spizellomyces, which was noted in a very small proportion (&lt;0.5 %) (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>). Neocallimastix was more abundant in the SF-G1 samples while Piromyces and Cyllamyces were more abundant in LF-G2 and SF-G3 respectively (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_1'>1d</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Effect of feeding system on the composition of microbial communities</ns0:head><ns0:p>Multivariate analysis separated libraries by feeding system distinctly (Figs. <ns0:ref type='figure' target='#fig_4'>2 and 3</ns0:ref>). Also, bacteria, dominated by phylum Firmicutes were the main driver of differences between animals (Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>). Furthermore, Entodinium, Thermoplasmatales, Neocallimastix were the main drivers of differences in protozoal, archaeal and fungal communities, respectively. PERMANOVA analysis revealed that the difference between camel groups was significant (P &lt; 0.01) in all microbial groups (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Pairwise comparison between camel groups based on Bonferroni-corrected p-value demonstrated that the difference was significant (P &lt; 0.05) between camels of G2 and G3 in bacterial and archaeal communities (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Moreover, the difference was significant between the three groups in the protozoal community (P &lt; 0.05), whereas, in the fungal community, the difference was significant only between camels in group G1 and G2 (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Pearson correlation between microbes in the rumen of dromedary camel</ns0:head><ns0:p>Pearson correlation analysis (Fig. <ns0:ref type='figure' target='#fig_5'>4A, 4B</ns0:ref>), revealed many significant positive and negative correlations (P &lt; 0.05). For example, in active bacteria, Bacteroidetes correlated positively with Cyllamyces and negatively with Butyrivibrio, Methanosphaera and Trichostomatia. Prevotellaceae correlated positively with Neocallimastix and Entodinium and negatively with Ruminococcaceae, Methanosphaera and Diplodinium. Fibrobacteres correlated positively with Cyllamyces, Methanomicrobium, Thermoplasmatales and Diplodinium and negatively with Methanosphaera, Epidinium, Ruminococcaceae and Butyrivibrio. Firmicutes correlated positively with Methanosphaera and negatively with Piromyces, Thermoplasmatales and Methanomicrobium.</ns0:p><ns0:p>In active archaea, Thermoplasmatales correlated positively with Diplodinium and negatively with Methanobrevibacter and Methanosphaera. In active protozoa, there was a negative correlation between Polyplastron, Entodinium, Ophryoscolex and Epidinium. In active fungi, a negative correlation was observed between Cyllamyces, Neocallimastix and Piromyces and between Piromyces and Entodinium.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Rumen microbes can ferment a wide variety of feed components, including cellulose, xylan, amylose and protein and produce volatile fatty acids that provide the animal with approximately 70% of daily energy requirements <ns0:ref type='bibr' target='#b5'>(Bergman, 1990;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Furthermore, the rumen fermentation generates methane, which contributes to global warming and represents 2-12% loss of feed energy for the animal <ns0:ref type='bibr' target='#b42'>(Johnson and Ward, 1996;</ns0:ref><ns0:ref type='bibr' target='#b12'>Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b38'>Jami et al., 2014)</ns0:ref>. Therefore, investigation of these microbial communities is the key to understand their roles and maximize ruminal fermentation and fiber digestion and reduction of greenhouse gas emissions <ns0:ref type='bibr' target='#b54'>(Lee et al., 2012)</ns0:ref>. Camels groups fed different diets and reared in different locations. However, the diet type has the main effect on the diversity and relative abundance of microbial communities. This speculation is supported by the similarity of microbial groups across the samples. Furthermore, the variation in the relative abundance of microbial groups was associated with diet composition, more details could be seen in Supplementary note S1. In addition, PCoA, LDA and PERMANOVA analyses confirmed the finding of this study and was in agreement with the results of other ruminant studies <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Camels in the present study were fed on different forages; Egyptian clover and wheat straw (Supplementary Table <ns0:ref type='table'>S1</ns0:ref>). Egyptian clover is the most balanced and nutritious fodder widely used for feeding camels <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr'>Bakheit, 2013;</ns0:ref><ns0:ref type='bibr' target='#b84'>Shrivastava et al., 2014)</ns0:ref>, which might supported the high microbial diversity in G2 camels compared to other groups (Table <ns0:ref type='table'>1</ns0:ref>). This was consistent with previous studies on cows <ns0:ref type='bibr' target='#b71'>(Pitta et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b83'>Shanks et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>. Highly degradable carbohydrates support the bacterial and protozoal growth <ns0:ref type='bibr' target='#b19'>(Dijkstra and Tamminga, 1995;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>, which could demonstrate their higher population in G1 camels. Additionally, the higher bacterial population slows the fungi growth <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992;</ns0:ref><ns0:ref type='bibr' target='#b66'>Orpin and Joblin, 1997)</ns0:ref>, which was illustrated by the low fungal population in G1 camels.</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>Firmicutes phylum was appeared more abundant than Bacteroidetes and both phyla comprised &gt; 75% of all bacterial reads (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>), which is in agreement with previous studies on different animals including camels <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>, Surti Buffalo <ns0:ref type='bibr' target='#b67'>(Pandya et al., 2010)</ns0:ref> and Muskoxen <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref>. The majority of Firmicutes' members have a potential role in fiber digestion, which might illustrate their higher population in G2 camels that were fed on high-quality forage and also in solid fraction. This speculation was supported by the high proportion of Ruminococcaceae and Lachnospiraceae families that found to be active in fiber digestion in the rumen <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b62'>Nathani et al., 2015)</ns0:ref>. Bothe Blautia and Acetitomaculum genera have a key role as reductive acetogens (Le <ns0:ref type='bibr'>Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b94'>Yang et al., 2016)</ns0:ref> and varied with feeding system among the camel groups in this study. This finding could indicate that the reductive acetogenesis pathway could be maximized by diet to minimize methane production (Le <ns0:ref type='bibr'>Van et al., 1998)</ns0:ref>. Bacteroidetes were higher in poor-quality diet (G3), which was similar to results found in cattle <ns0:ref type='bibr' target='#b69'>(Pitta et al., 2014b)</ns0:ref>. The phylum was dominated by family Prevotellaceae, which confirms <ns0:ref type='bibr' target='#b26'>Gharechahi et al. (2015)</ns0:ref>. The members of Bacteroidetes possess diverse enzymes that can target cellulose, pectin and soluble polysaccharides released in the liquid phase <ns0:ref type='bibr' target='#b59'>(Mackenzie et al., 2015)</ns0:ref>. Additionally, Prevotella genus is involved in propionate production that is used for energy by the host <ns0:ref type='bibr' target='#b62'>(Nathani et al., 2015)</ns0:ref>. We speculate that Bacteroidetes species contribute to the adaptation of camels to arid conditions. The RC9_gut_group found in this study belongs to uncultured genera and was found also in the gut of Rhinoceros hindgut <ns0:ref type='bibr' target='#b8'>(Bian et al., 2013)</ns0:ref>. Unclassified Bacteroidetes are specialized in lignocellulose degradation <ns0:ref type='bibr' target='#b59'>(Mackenzie et al., 2015)</ns0:ref>, which could support their high proportion in G3 camels. Fibrobacteres was higher (3.1%) in this study compared to the other findings on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>; this phylum is the principal cellulolytic bacteria in the rumen <ns0:ref type='bibr' target='#b75'>(Ransom-Jones et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b62'>Nathani et al., 2015)</ns0:ref>, which might illustrate its higher relative abundance in solid fraction and in the rumen of camels fed on wheat straw (G3) (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). The members of Proteobacteria were lower in G2 and G3 camels that were fed on diet rich in fiber contents. These findings highlighted this phylum's function as a protein-degrading bacteria as it was reported by <ns0:ref type='bibr' target='#b57'>Liu et al. (2017)</ns0:ref>. The abundance of Treponema was higher in the solid fraction and in G3 camels (Figure <ns0:ref type='figure' target='#fig_1'>1a</ns0:ref>). Treponema is the dominant genus in Spirochaetes phylum and it is fiber-associated bacteria, which could indicate to its cellulytic and xylanolytic activities <ns0:ref type='bibr' target='#b35'>(Ishaq and Wright, 2012)</ns0:ref>.</ns0:p><ns0:p>The dominant bacterial genera in this study were Butyriovibrio, RFN8-YE57, Ruminococcus, Prevotella, Fibrobacter, Treponema and VadinHA. These genera were higher in the SF except RFN8-YE57 compared to the LF; this finding was consistent with a previous study on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>, and confirms that the solid-attached microbes could play a major role in ruminal fiber digestion <ns0:ref type='bibr' target='#b39'>(Jewell et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b64'>Noel et al., 2017)</ns0:ref>. Most of Elusimicrobia in this study were uncultured; some members of this phylum were isolated from the termite's gut that degrades cellulose <ns0:ref type='bibr' target='#b32'>(Herlemann et al., 2009)</ns0:ref>. Therefore, we speculate that this phylum has a role in fiber digestion and that might illustrate their high proportion in G3 camels. Actinobacteria observed also in the rumen of moose and some members of this phylum have acetogenic activities <ns0:ref type='bibr' target='#b37'>(Ishaq et al., 2015)</ns0:ref>. Some members of Victivallis within Lentisphaerae phylum were involved in cellobiose degrading activity <ns0:ref type='bibr' target='#b96'>(Zoetendal et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Unclassified bacteria in our study (39% of total bacterial reads) were less than the percentage found in a study of <ns0:ref type='bibr'>Muskoxen (53.7-59.3%) (Salgado-Flores et al., 2016)</ns0:ref>. The presence of unclassified bacteria in the gut was commonly observed <ns0:ref type='bibr' target='#b27'>(Gruninger et al., 2016)</ns0:ref> and could be a result of the presence of new bacteria that ferment plant biomass <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref> or related to short reads were generated from RNAsequncing <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>The archaeal population has important roles in methane emission mitigation strategies as they convert the H 2 and CO 2 produced in the rumen to methane <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010)</ns0:ref>. Additionally, acetate produced in fiber breakdown is used to provide a methyl group for methanogenesis; therefore, methanogens population could be shifted by alteration of diet composition or feed additives and plant compounds <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b88'>Tapio et al., 2017 )</ns0:ref>, which could demonstrate the variation in the relative abundance of archaea between camel groups. Camels of the second group (G2) that fed fresh clover, showed the highest archaeal population (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>) and the archaeal community was dominated by Thermoplasmatales, a methylotrophic methanogens order (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>) which was consistent with the results on cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref> and camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. Thermoplasmatales produces methane from methyl amine and its population was decreased by the addition of rapeseed oil to animal diet, making it a high potential target in future strategies to mitigate methane emissions <ns0:ref type='bibr' target='#b72'>(Poulsen et al., 2013)</ns0:ref>. The Methanobrevibacter, Methanosphaera, Methanomicrobium and Methanobacterium (Table <ns0:ref type='table'>4</ns0:ref>) are the other dominant archaea in this study and in accordance with the results found in beef cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref>. Methanobrevibacter dominated the methanogens in other ruminant <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref> and was associated with high methane emissions <ns0:ref type='bibr' target='#b88'>(Tapio et al., 2017)</ns0:ref>. Moreover, Methanomicrobium had its highest proportion with the feeding system of poor quality forage diet (G3), which was similar to results found in buffalo <ns0:ref type='bibr' target='#b23'>(Franzolin and Wright, 2016)</ns0:ref>, and In vitro <ns0:ref type='bibr' target='#b90'>(Wang et al., 2018)</ns0:ref>. In rumen, Methanomicrobium has been shown to be responsible for the conversion of H 2 and/or formate into CH 4 <ns0:ref type='bibr' target='#b52'>(Leahy et al., 2013)</ns0:ref>. The abundance of Thermoplasmatales was also negatively correlated with Methanobrevibacter which is consistent with previous results <ns0:ref type='bibr' target='#b16'>(Danielsson et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b60'>McGovern et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>The majority of protozoal reads were related to Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium and Epidinium (Table <ns0:ref type='table'>4</ns0:ref>). Similar findings were observed in other study on different ruminants <ns0:ref type='bibr' target='#b4'>(Baraka, 2012)</ns0:ref>. The relative abundance of protozoal was influenced by feeding system, which was in the same line with results on cattle <ns0:ref type='bibr' target='#b34'>(Hristov et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b91'>Weimer, 2015)</ns0:ref>. The Diplodinium dominated the protozoal community and was prevalent in the G3 camels, which highlighted the cellulolytic activity of this genus <ns0:ref type='bibr' target='#b14'>(Coleman et al., 1976)</ns0:ref>. Also, some species of genus Diplodinium were discovered in the rumen of Egyptian camel and is considered to be peculiar in camel such as Diplodinium cameli, <ns0:ref type='bibr' target='#b48'>(Kubesy and Dehority, 2002)</ns0:ref>. In addition, Entodinium was higher in G1 camels that were fed on concentrates feed mixture that increase the protozoa. Also, previous studies showed that this genus was dominant in rumen of camels <ns0:ref type='bibr' target='#b82'>(Selim et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b25'>Ghali et al., 2005)</ns0:ref> and cattle <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012)</ns0:ref>. Moreover, the study of <ns0:ref type='bibr' target='#b47'>Kittelmann and Janssen (2011)</ns0:ref> showed that the Polyplastron was the dominant genus in cattle. On the function level, all the genus Eudiplidinum, Epidinum and Diplodinum have cellulolytic activity <ns0:ref type='bibr' target='#b14'>(Coleman et al., 1976)</ns0:ref>, whereas, Polyplastrone and Epidinium have a xylanolytic activity <ns0:ref type='bibr' target='#b18'>(Devillard, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>B&#233;ra-Maillet et al., 2005)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>The highest fungal population was observed in the solid fraction and rumen of G3 camels (Table <ns0:ref type='table'>1</ns0:ref>). These findings were in agreement with the results of different studies stated that the fibre-based diets stimulated the fungal growth <ns0:ref type='bibr' target='#b65'>(Orpin, 1977;</ns0:ref><ns0:ref type='bibr' target='#b77'>Roger et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b29'>Haitjema et al., 2014)</ns0:ref>. This speculation could explain the low fungal population in G1 camels in our study. Moreover, the longer retention time and neutral pH in camel's forestomach <ns0:ref type='bibr' target='#b78'>(Russell and Wilson, 1996)</ns0:ref> make it more suitable for the survival of rumen fungi. The genus Neocallimastix dominated the fungal community and found to be higher in the G1 camels which was similar to other results on sheep and camels <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013</ns0:ref><ns0:ref type='bibr' target='#b74'>, Rabee et al., 2019)</ns0:ref>. This genus produces enzymes capable of hydrolyzing cellulose, xylan and starch <ns0:ref type='bibr' target='#b68'>(Pearce and Bauchop, 1985)</ns0:ref>. Cyllamyces that was observed in small population, has the ability to degrade poor-quality feeds <ns0:ref type='bibr' target='#b86'>(Sridhar et al., 2014)</ns0:ref>, which might explain its high population in solid fraction and G3 camels. Piromyces was the second dominant genus in the camel rumen of this study and has been shown to produce cellulolytic and xylanolytic enzymes <ns0:ref type='bibr' target='#b89'>(Teunissen et al., 1992)</ns0:ref>. Therefore, the fungi were more prevalent in ruminants of G2 camels, which fed high-quality forage with high fiber contents than in G2 and G3 camels. The genus Spizellomyces is closely related to Chytridiomctes <ns0:ref type='bibr' target='#b10'>(Bowman et al., 1992)</ns0:ref>, and common in grassland and crop soil <ns0:ref type='bibr' target='#b58'>(Lozupone and</ns0:ref><ns0:ref type='bibr'>Klein, 2002, Kittelmann et al., 2012)</ns0:ref>. Thus, the presence of this fungus in the camel rumen in the current study could be explained by a contamination of the forages by soil.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between rumen microbes</ns0:head><ns0:p>The interactions between rumen microbes are the main driver of feed degradation and methane formation in the rumen, which influence the animal production and the environment <ns0:ref type='bibr' target='#b92'>(Williams et al., 1994;</ns0:ref><ns0:ref type='bibr' target='#b54'>Lee et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Positive and negative correlations were observed within and between microbial communities in this study (Fig. <ns0:ref type='figure' target='#fig_5'>4</ns0:ref>). Methanogens colonize the protozoa and this relationship was believed to enhance methane formation <ns0:ref type='bibr' target='#b63'>(Newbold et al., 1995)</ns0:ref>, which highlighted some positive correlations between protozoa and archaea. Additionally, the fibrolytic bacteria produce the important substrates mainly hydrogen and methyl groups that methanogens use for growth <ns0:ref type='bibr' target='#b41'>(Johnson and Johnson, 1995)</ns0:ref>, which demonstrated the positive correlations found between Fibrobacteres and some methanogens. Also, positive correlation between the methylotrophic Methanosphaera and Lachnospiraceae that has been implicated in pectin degradation and provides methanol as a substrate for the methylotrophs <ns0:ref type='bibr' target='#b17'>(Dehority, 1969)</ns0:ref>. On the other hand, Prevotella is a hydrogen utilizer and produces propionate which has a negative impact on methanogenesis in the rumen <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>, which also illustrated the negative correlation obtained in this study between Prevotellaceae and archaea.</ns0:p><ns0:p>Since the rumen anaerobic fungi produce abundant H 2 through the fermentation of carbohydrate; they can interact positively with H 2 utilizers such as archaea, Prevotellaceae, Blautia and Acetitomaculum <ns0:ref type='bibr' target='#b66'>(Orpin and Joblin, 1997</ns0:ref>; Le <ns0:ref type='bibr'>Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b94'>Yang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>. Additionally, the anaerobic fungi penetrate plant tissue, which provides an increased surface area for bacterial colonization <ns0:ref type='bibr' target='#b66'>(Orpin and Joblin, 1997)</ns0:ref>, which could explain the positive correlation between fungi and both Butyrivibrio and Fibrobacteres in this study. However, fungi are known to be negatively impacted by the presence of some bacteria and protozoa as the fungal zoospores are likely to be a prey for protozoa <ns0:ref type='bibr' target='#b61'>(Morgavi et al., 1994)</ns0:ref>, which demonstrated the negative correlation between both Neocallimastix and Piromyces with Diplodinium and Entodinium. Furthermore, Ruminococcus produces compounds that inhibit the growth of rumen fungi <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992)</ns0:ref>, which support the negative correlation between Neocallimastix and Ruminococcaceae. Polyplastron predates upon other protozoa like Epidinium, Eudiplodinium, Diplodinium, and Ostracodinium <ns0:ref type='bibr' target='#b20'>(Eadie, 1967)</ns0:ref>, which might explained the negative correlation between Polyplastron and other Protozoa.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study applied total rRNA sequencing to get insight into the active microbial groups in the rumen of dromedary camels. However, using the DNA-amplicon sequencing with RNA sequencing is recommended in the future studies to compare the composition of active microbial groups (from RNA sequencing) with the composition of the whole microbial community. Furthermore, it is recommended to use larger population in future studies. As a major conclusion of our study, the microbial community in camel rumen was diverse and similar in composition between the camels. However, the feeding system impacted the relative abundance of active microbial communities where the fresh Egyptian clover provided the highest microbial diversity. The majority of camel rumen microbes (bacteria, fungi, and protozoa) were fibrolytic or have a possible role in fiber digestion, which might illustrate the ability of camel to live in desert harsh conditions under poor feeds. Moreover, the structure of microbial community in rumen of camel Manuscript to be reviewed found to be similar to other ruminant studies with a shown difference in the relative abundances. The present results should open new perspectives for further cultivation and isolation studies on the unclassified microorganisms found in the rumen of camels to classify them and assign their functions.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>The relative abundance of microbial groups Manuscript to be reviewed Relative abundance (%) of bacterial phyla Manuscript to be reviewed Relative abundance (%) of archaeal orders and genera Manuscript to be reviewed Relative abundance (%) of fungal genera </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2019:12:44048:5:0:NEW 23 Jun 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Comparison of relative abundance of genera of the microbiota in dromedary camel. bacterial (a), archaeal (b), protozoal (c) and fungi (d) in ruminal solid (SF) and liquid (LF) fractions of camels under different feeding systems.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3:Linear Discriminant analysis of microbial communities in the samples based on the relative abundance of genera of active bacteria (a), archaea (b), protozoa (c) and fungi i (d)in ruminal solid (SF), and liquid (LF) fractions of camels under three feeding systems, G1 (black dots), G2 (blue squares) and G3 (coral triangles).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>.07 0.2&#177;0.04 0.8&#177;0.4 0.4&#177;0.1 a The value was calculated from one animal. PeerJ reviewing PDF | (2019:12:44048:5:0:NEW 23 Jun 2020)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Relative abundance (%) of bacterial phyla in the ruminal solid (SF) and liquid (LF)</ns0:figDesc><ns0:table><ns0:row><ns0:cell>fractions of camels fed a mixed ration(G1), high-quality forage(G2) and low-quality forage</ns0:cell></ns0:row><ns0:row><ns0:cell>(G3) (Mean &#177; Standard Error (SE)).</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:12:44048:5:0:NEW 23 Jun 2020)Manuscript to be reviewed</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Relative abundance (%) of archaeal orders and genera observed in the ruminal solid (SF), and liquid (LF) fractions of camels under different feeding systems. Animals in G1 fed a mixed ration, animal in G2 fed high-quality forage and animal in G3 fed low qualityforage (Mean &#177; Standard Error (SE)).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Protozoa</ns0:cell><ns0:cell>G1</ns0:cell><ns0:cell>G2</ns0:cell><ns0:cell>G3</ns0:cell><ns0:cell>Overall mean</ns0:cell></ns0:row><ns0:row><ns0:cell>Entodinium SF</ns0:cell><ns0:cell>23&#177;6</ns0:cell><ns0:cell>6.5&#177;0.6</ns0:cell><ns0:cell>6&#177;0.8</ns0:cell><ns0:cell>11&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell>Entodinium LF</ns0:cell><ns0:cell>54&#177;9.5</ns0:cell><ns0:cell>15&#177;2.5</ns0:cell><ns0:cell>5&#177;0.8</ns0:cell><ns0:cell>24&#177;6</ns0:cell></ns0:row><ns0:row><ns0:cell>Polyplastron S F</ns0:cell><ns0:cell>10&#177;1</ns0:cell><ns0:cell>17.5&#177;2</ns0:cell><ns0:cell>25&#177;3</ns0:cell><ns0:cell>17&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Polyplastron LF</ns0:cell><ns0:cell>6&#177;0.8</ns0:cell><ns0:cell>11&#177;0.2</ns0:cell><ns0:cell>24&#177;3</ns0:cell><ns0:cell>12&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Diplodinium S F</ns0:cell><ns0:cell>23&#177;1</ns0:cell><ns0:cell>35&#177;3</ns0:cell><ns0:cell>49&#177;10</ns0:cell><ns0:cell>34&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell>Diplodinium LF</ns0:cell><ns0:cell>13&#177;3</ns0:cell><ns0:cell>27&#177;3</ns0:cell><ns0:cell>61&#177;6</ns0:cell><ns0:cell>29&#177;5</ns0:cell></ns0:row><ns0:row><ns0:cell>Eudiplodinium SF</ns0:cell><ns0:cell>8&#177;0.6</ns0:cell><ns0:cell>8&#177;2</ns0:cell><ns0:cell>2&#177;0.7</ns0:cell><ns0:cell>7&#177;1</ns0:cell></ns0:row><ns0:row><ns0:cell>Eudiplodinium LF</ns0:cell><ns0:cell>4&#177;1</ns0:cell><ns0:cell>5.5&#177;0.9</ns0:cell><ns0:cell>2.5&#177;0.4</ns0:cell><ns0:cell>4.5&#177;0.6</ns0:cell></ns0:row><ns0:row><ns0:cell>Epidinium SF</ns0:cell><ns0:cell>5&#177;0.76</ns0:cell><ns0:cell>4&#177;1</ns0:cell><ns0:cell>2&#177;1</ns0:cell><ns0:cell>4&#177;0.1</ns0:cell></ns0:row><ns0:row><ns0:cell>Epidinium LF</ns0:cell><ns0:cell>3&#177;0.8</ns0:cell><ns0:cell>4.5&#177;0.6</ns0:cell><ns0:cell>1&#177;0.7</ns0:cell><ns0:cell>3.5&#177;0.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Ophryoscolex SF</ns0:cell><ns0:cell>30&#177;4</ns0:cell><ns0:cell>27&#177;3</ns0:cell><ns0:cell>15&#177;5</ns0:cell><ns0:cell>26&#177;2.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Ophryoscolex LF</ns0:cell><ns0:cell>19&#177;4</ns0:cell><ns0:cell>29&#177;0.6</ns0:cell><ns0:cell>6.5&#177;3.8</ns0:cell><ns0:cell>22&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Trichostomatia SF 0.1&#177;0.02</ns0:cell><ns0:cell>1&#177;0.25</ns0:cell><ns0:cell>0.3&#177;0.15</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Trichostomatia LF 0.2&#177;0.04</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell><ns0:cell>1&#177;0.1</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell></ns0:row><ns0:row><ns0:cell>Isotricha SF</ns0:cell><ns0:cell cols='3'>0.2&#177;0.04 0.3&#177;0.05 0.3&#177;0.004</ns0:cell><ns0:cell>0.3&#177;0.03</ns0:cell></ns0:row><ns0:row><ns0:cell>Isotricha LF</ns0:cell><ns0:cell>0.5&#177;0.2</ns0:cell><ns0:cell cols='2'>2&#177;0.85 0.3&#177;0.007</ns0:cell><ns0:cell>1&#177;0.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Dasytricha SF</ns0:cell><ns0:cell cols='3'>0.04&#177;0.008 1.5&#177;0.3 0.2&#177;0.15</ns0:cell><ns0:cell>1&#177;0.3</ns0:cell></ns0:row><ns0:row><ns0:cell>Dasytricha LF</ns0:cell><ns0:cell cols='2'>0.1&#177;0.002 5.5&#177;0.8</ns0:cell><ns0:cell>0.5&#177;0.3</ns0:cell><ns0:cell>3&#177;1</ns0:cell></ns0:row></ns0:table><ns0:note>2PeerJ reviewing PDF | (2019:12:44048:5:0:NEW 23 Jun 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 5 :</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Relative abundance (%) of fungal genera in the ruminal solid (SF) and liquid fraction (LF) of camels under different feeding systems. Camels in G1 fed a mixed ration, animals in G2 fed high-quality forage, and animals in G3 fed low-quality forage (Mean &#177; SE).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Fungi</ns0:cell><ns0:cell>G1</ns0:cell><ns0:cell>G2</ns0:cell><ns0:cell>G3</ns0:cell><ns0:cell>Overall mean</ns0:cell></ns0:row><ns0:row><ns0:cell>Spizellomyces SF</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0.09</ns0:cell><ns0:cell>0.017</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>Spizellomyces LF 0.3 &#177; 0.1 0.25 &#177; 0.1</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces SF</ns0:cell><ns0:cell>2&#177; 0.6</ns0:cell><ns0:cell>3&#177; 1.5</ns0:cell><ns0:cell>7&#177; 4</ns0:cell><ns0:cell>3.5&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces LF</ns0:cell><ns0:cell>2&#177; 0.78</ns0:cell><ns0:cell>3&#177; 0.8</ns0:cell><ns0:cell>10&#177; 1</ns0:cell><ns0:cell>4&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces SF</ns0:cell><ns0:cell>6&#177; 3</ns0:cell><ns0:cell>12&#177; 0.7</ns0:cell><ns0:cell>8&#177; 1</ns0:cell><ns0:cell>9&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces LF</ns0:cell><ns0:cell>6&#177;4</ns0:cell><ns0:cell>12&#177;2</ns0:cell><ns0:cell>10&#177;6</ns0:cell><ns0:cell>10&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix SF</ns0:cell><ns0:cell>92&#177;3</ns0:cell><ns0:cell>85&#177;1</ns0:cell><ns0:cell>85&#177;3</ns0:cell><ns0:cell>87&#177;1</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix LF</ns0:cell><ns0:cell>92&#177;4</ns0:cell><ns0:cell>85&#177;1.5</ns0:cell><ns0:cell>81&#177;7</ns0:cell><ns0:cell>86&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>ND: Non Determined</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:12:44048:5:0:NEW 23 Jun 2020) Manuscript to be reviewed PeerJ reviewing PDF | (2019:12:44048:5:0:NEW 23 Jun 2020)</ns0:note></ns0:figure> </ns0:body> "

"Desert Research Center 1Mathaf El Matariya St.B.O.P.11753 Matariya- Cairo,Egypt Phone: (+202)26332846 - 26374800 FAX: (+202) 26357858 Email:[email protected] 23th June, 2020 Dear Editor, We thank you for your comments. We responded to your comments and enclosed unclean paper including all comments colored by yellow. Below are the responses to all the comments. We appreciate the opportunity to submit our manuscript to Peer J. Yours sincerely, Dr. Alaa Rabee Researcher at Desert Research Center, Egypt On behalf of all authors Comments Manuscript title: “Comparative analysis of the metabolically active microbial communities in the rumen of dromedary camels under different feeding systems using total rRNA sequencing ” Editor’s comments Before I send this to reviewers, I need your group of authors to carefully proofread it. I only briefly reviewed this version and I noticed several minor points, which suggests the manuscript has not been adequately proof read by the coauthors. >> We have revised it. My major concern was not addressed. The discussion of the limitations of the experimental design (line 445-449) doesn't make clear that you can tell that the treatment effects were due to feed or location. That should be made clear in lines 293 - 307, with appropriate references on pseudoreplication. You cannot address the flaws in experimental design by simply providing recommendations for the next study. >> We modified this paragraph at the beginning of the discussion and removed the paragraph at the end of the discussion and make minor change in the conclusion. Furthermore, we included a supplementary not S1, which clarify why the diet has the major impact on the microbial communities, thank you. line 127. Always cap Table and Figures. >> Modified Table 2 and throughout. When presenting mean and SE, always present the same significant figures (5 +/- 1 not 5 +/- 0.001). >> Modified. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The breakdown of plant biomass in rumen depends on interactions between bacteria, archaea, fungi, and protozoa; however, the majority of studies of the microbiome of ruminants, including the few studies of the rumen of camels, only studied one of these microbial groups. In this study, we applied total rRNA sequencing to identify active microbial communities in twenty-two solid and liquid rumen samples from eleven camels reared under three feeding systems. These camels were reared at three stations that use different feeding systems: clover, hay and wheat straw (G1), fresh clover (G2), and wheat straw (G3).Bacteria dominated the libraries of sequence reads generated from all rumen samples, followed by protozoa, archaea, and fungi respectively. Firmicutes, Thermoplasmatales, Diplodinium, and Neocallimastix dominated bacterial, archaeal, protozoal and fungal communities, respectively in all samples. Libraries generated from camels reared at facility G2, where they were fed fresh clover, showed the highest alpha diversity. Principal co-ordinate analysis and linear discriminate analysis showed clusters associated with facility/feed and the relative abundance of microbes varied between liquid and solid fractions. This provides preliminary evidence that bacteria dominate the microbial communities of the camel rumen.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Camels (Camelus dromedaries) can produce milk and meat in hot, arid and semi-arid regions and can provide food security as the climate warms <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b22'>Faye, 2013)</ns0:ref>. Camels also provide textiles (fiber and hair) and are commonly used for transportation, agriculture, tourism, race and riding <ns0:ref type='bibr' target='#b73'>(Rabee et al., 2019)</ns0:ref>. The unique feeding behavior and the functional structure of digestive tract of these pseudo-ruminants is well adapted to deserts <ns0:ref type='bibr' target='#b43'>(Kay et al., 1989)</ns0:ref>. The retention time of feed particles in the camel forestomach is longer than other true ruminants, which prolongs the exposure of plant biomasses to the symbiotic microorganisms. This long retention improves the efficiency of digestion <ns0:ref type='bibr'>(Lechner-Dolland and Engelhardt, 1989)</ns0:ref>. The feed ranchers provide camels, which ranges from forage in traditional pastures to concentrated supplements in intensive feedlots, influences the structure of the camel microbiome <ns0:ref type='bibr' target='#b22'>(Faye, 2013;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al. 2015)</ns0:ref>. The chemical composition of the diet shapes fermentation in the rumen. For instance, cellulolytic and hemicellulytic diets favor the fibrolytic microorganisms; while, starch and sugars favor the amylolytic <ns0:ref type='bibr' target='#b13'>(Carberry et al., 2012)</ns0:ref>. Also, the microbial composition and diversity varies between liquid and solid rumen fractions, which might indicate different roles in rumen fermentation; for instance, plant-adherent microbiota might have a major role in fiber degradation <ns0:ref type='bibr' target='#b76'>(Ren et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Digestion in the camel depends on microbial fermentation in rumen <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref> and the efficiency of this microbial fermentations is based on the interactions between a wide variety of microbial groups, including bacteria, archaea, fungi and protozoa <ns0:ref type='bibr' target='#b93'>(Yanagita et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b42'>Kamra, 2005)</ns0:ref>. Analysis of these microbial communities could lead to increases in animal productivity and reduction of greenhouse gas emissions <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Unlike other ruminants, camels can utilize thorny and low quality plants like shrubs with high lignocelulolytic content <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>. Consequently, camel rumen microbes must have the capacity to degrade such poor-quality feeds <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. However, the microbial community in the rumen of dromedary camel received less attention than other domesticated ruminants. The recent development of next generation sequencing technologies provide a rapid method of microbial identification in rumen and overcome the intrinsic constraints of traditional culturebased methods <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b36'>Ishaq and Wright, 2014)</ns0:ref>. Most of assessments of microbial groups in the rumen have relied on amplicon sequencing, which target a specific variable region on 16S rRNA gene <ns0:ref type='bibr' target='#b55'>(Li et al. 2016)</ns0:ref>. This approach needs a wide range of primers to study different microbial communities <ns0:ref type='bibr' target='#b45'>(Kittelmann et al., 2013)</ns0:ref>. Therefore, the output could be biased due to the primer selection and amplification cycling conditions <ns0:ref type='bibr' target='#b28'>(Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b55'>Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b21'>Elekwachi et al., 2017)</ns0:ref>. Total RNA sequencing (RNA-Seq) offers the advantage of specifically targeting active microbes and avoids biases associated with primer selection and chimera generation in PCR <ns0:ref type='bibr' target='#b24'>(Gaidos et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b28'>Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b55'>Li et al., 2016)</ns0:ref>. In addition, RNA-Seq approach is capable of identifying novel microbes as it is not reliant on primers for known microbes <ns0:ref type='bibr' target='#b55'>(Li et al., 2016)</ns0:ref>. Highthroughput metatranscriptomic sequencing provides a comprehensive understanding of the biological systems by characterization of different groups of organisms in the same environment based on the sequencing of coding and noncoding RNA <ns0:ref type='bibr' target='#b21'>(Elekwachi et al., 2017)</ns0:ref>. Total RNA-Seq was applied to investigate microbial communities in many different systems including, for example, human gut <ns0:ref type='bibr' target='#b72'>(Qin et al., 2012)</ns0:ref>, and cow rumen <ns0:ref type='bibr' target='#b55'>(Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b21'>Elekwachi et al., 2017 )</ns0:ref>.</ns0:p><ns0:p>Previous microbiome studies on camel rumen have characterized one or two microbial groups using classical or molecular approaches. For example, the protozoal community in camel rumen was studied heavily by conventional microscopic methods <ns0:ref type='bibr' target='#b25'>(Ghali et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b4'>Baraka, 2012)</ns0:ref>. Regarding the anaerobic fungi, a new fungal genus, Oontomyces was isolated from the rumen of Indian camel <ns0:ref type='bibr' target='#b15'>(Dagar et al., 2015)</ns0:ref>, and only one study investigated the whole fungal community in the gut of the camel <ns0:ref type='bibr' target='#b73'>(Rabee et al., 2019)</ns0:ref>. Only three molecular-based studies are available on the bacterial community <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b8'>Bhatt et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b26'>Gharechahi et al., 2015)</ns0:ref>. Furthermore, only one study classified the rumen archaea <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. In the present study, total rRNA sequencing was applied to 1) get insight into the composition of active microbiota in the rumen of camels; 2) describe the distribution of microbial groups among solid and liquid rumen fractions; 3) investigate the correlations between all the microbial groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Rumen samples</ns0:head><ns0:p>Rumen samples were collected from eleven adult dromedary camels reared at three stations that use different feeding systems. Camels in group G1 (n=3) were housed in the Maryout Research Station, Alexendria, Egypt and were fed on Egyptian clover hay (Trifolium alexandrinum), wheat straw and concentrates feed mixture. Camels in group G2 (n=6) were housed at the commercial farm in the Kom Hammada and fed on fresh Egyptian clover (100 % high-quality forage diet) then slaughtered in the Kom Hammada slaughterhouse, Elbehera, Egypt. Camels of group G3 (n=2) were housed at the commercial farm in Cairo area and fed on wheat straw (100 % low-quality forage diet) then were slaughtered in Pasateen slaughterhouse, Cairo, Egypt. All the animals kept on the diet for at least one month before the sampling time. The proximate analysis of feeds is illustrated in Supplementary table <ns0:ref type='table'>S1</ns0:ref>. Details regarding the camel rumen samples in this study presented in Supplementary table <ns0:ref type='table' target='#tab_2'>S2</ns0:ref>. Rumen contents were strained immediately by two layers cheesecloth to separate the liquid and solid to form twenty-two samples, frozen using liquid nitrogen and stored at -80 o C before further processing <ns0:ref type='bibr' target='#b21'>(Elekwachi et al., 2017)</ns0:ref>. The project was approved and all samples were collected according to the Institutional Animal Care and Use Committee, Faculty of Veterinary Medicine, University of Sadat City, Egypt (Approval number: VUSC00003).</ns0:p></ns0:div> <ns0:div><ns0:head>RNA isolation, quality and quantity estimation and sequencing</ns0:head><ns0:p>The frozen rumen samples were ground using liquid nitrogen. About 0.5 gram of frozen fine powder was used for total RNA isolation using Trizol-Reagent protocol (Invitrogen, Carlsbad, CA), followed by RNA clean up using MEGA clear Kit (Invitrogen). Total RNA quality and quantity were estimated using an Agilent 2100 bioanalyzer (Agilent Technologies, USA) and RNA 6000 Nano kit (Agilent Technologies, USA). One hundred nanogram of total RNA was reversetranscribed into first strand cDNA and sequenced using Illumina rRNA MiSeq preparation kit (Illumina, USA) by Illumina MiSeq platform.</ns0:p></ns0:div> <ns0:div><ns0:head>Bioinformatic data analysis</ns0:head><ns0:p>The generated RNA sequence reads were analysed using pipeline developed by <ns0:ref type='bibr' target='#b21'>Elekwachi et al. (2017)</ns0:ref>. Briefly, the sequence quality was checked using the FastQC program v. 0.11.4 <ns0:ref type='bibr' target='#b0'>(Andrews, 2010)</ns0:ref>, then Trimmomatic program v. 0.35 <ns0:ref type='bibr' target='#b10'>(Bolger et al., 2014)</ns0:ref> was used to trim adaptors, barcodes, ambiguous and low quality reads. PEAR program v. 0.9.6 <ns0:ref type='bibr' target='#b95'>(Zhang et al., 2014)</ns0:ref> was used to merge read 1 and read 2 using default options. Then after, the hidden Markov models rRNA-HMM tool of the rapid analysis of multiple metagenomes with a clustering and annotation pipeline (RAMMCAP) <ns0:ref type='bibr' target='#b54'>(Li, 2009)</ns0:ref> was used to sort the reads into archaea and bacteria (16S, 23S), and eukaryote (18S, 23S) rRNA sequences. Merged sequence files were then sub-sampled as needed using MEME program v. 4.10.2 <ns0:ref type='bibr'>(Bailey et al., 2009)</ns0:ref>. For each sample, 70,000 reads were run through the pipeline. For subsequent analysis steps, 20 000, 10 000, and 2000 sequences were used for bacteria, eukaryote and archaea, respectively. Taxonomy binning for eukaryote and archaeal SSU rRNA sequences was performed using BLASTN. The sub-sampled query sequences were searched against the SILVA SSURef-111 database using an e-value of 1e -5 . Bacterial SSU sequences were binned into operational taxonomic units (OTUs) using the 'classify. seqs' command of Mothur v. 1.33.1 program <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref>. The SSURef -108 gene and the SSURef-108b taxonomy databases were used. Principal co-ordinate analysis (PCoA) using Bray Curtis dissimilarity and alpha diversity indices (Chao1, Shannon and Inverse Simpson) were evaluated by Mothur <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref> based on sub-sampling of 70,000 reads per sample according the protocol 'Community Structure Analysis Based on OTU Clustering' outlined in <ns0:ref type='bibr' target='#b21'>Elekwachi et al. (2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>Data of relative abundance of bacterial phyla, protozoal genera, fungal genera and archaea genera and order Thermoplasmatales were tested for normality and homogeneity using Shapiro-Wilk test and variables that were deemed non-normal were then arcsine transformed. Linear Discriminate Analysis (LDA) and Bray Curtis Permutational Multivariate Analysis of Variance (PERMANOVA) tests depended on the relative abundance of bacterial phyla. All the protozoal, fungal and archaeal genera and the order Thermoplasmatales were used to show the differences in community structure and to compare the clustering of samples. Pearson correlation analysis was used to identify correlation within and between microbial communities and the correlation scores were visualized as a heatmap. The statistical analyses were performed using the SPSS v. 20.0 software package (SPSS, 1999) and PAST <ns0:ref type='bibr' target='#b30'>(Hammer et al., 2001)</ns0:ref>. Sequences were deposited to the sequence read archive (SRA) under the accession number: SRP107370.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>The composition and diversity of active microbial community</ns0:head><ns0:p>Total rRNA sequencing in twenty-two solid and liquid rumen samples from eleven camels resulted in a total of 3958591 reads with average of 359872 &#177; 85366 (mean &#177; standard error (SE)) reads per animal in the solid fraction (SF) and 3386392 reads with an average of 307854 &#177; 60989 reads per animal in the liquid fraction (LF). The sequence reads of bacteria dominated the active microbial community, followed by protozoa, archaea and fungi (Table <ns0:ref type='table'>1</ns0:ref>). The relative abundance of protozoa was higher in LF-G1 (liquid fraction of G1), while the relative abundance of bacteria was higher in SF-G1 (solid fraction of G1). The highest population of archaea was observed in G2 camels. Additionally, G3 camels showed the highest relative abundance of fungi (Table <ns0:ref type='table'>1</ns0:ref>; Supplementary Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). Number of OTUs and Alpha-diversity indices, Chao1, Shannon and Inverse Simpson, were higher in the rumen of LF-G2 samples (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>The composition of bacterial community varied little between groups and consisted of 12 phyla. The five most predominant phyla were Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetes and Fibrobacteres, respectively (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Phylum Firmicutes dominated the bacterial community in all groups and was higher in G2 followed by G1 and G3 camels, respectively, and was also higher in SF compared to LF (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). On the family level, the Firmicutes phylum was dominated by Lachnospiraceae and Ruminococcuceae. In addition, six genera dominated this phylum, including Butyrivibrio, RFN8-YE57, Ruminococcus, vadinHA42, Acetitomaculum and Blautia (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). The second largest phylum, Bacteroidetes, showed the highest relative abundance in G3 followed by G1 and G2 camels and was higher in LF than SF (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). On the family and genus levels, Bacteroidetes was dominated by three families (Prevotellaceae, BS11_ gut_ group, Rikenellaceae) and two genera (Prevotella, RC9_gut_group) higher relative abundance in LF-G1 samples and was dominated by Succinivibrionaceae family and Desulfovibrio genus (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). The Spirochaetes phylum was higher in the SF-G3 and it was classified into two families including Spirochaetaceae and PL-11B10 and was dominated by Treponema genus. The Fibrobacteres phylum was higher in SF-G3 (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). Actinobacteria were higher in SF-G2 samples, Tenricutes phylum was higher in the LF-G1 samples and Lentisphaerae phylum, was about 3-fold higher in the LF as relative to SF and accounted for a large population in the camels of G3 (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Additionally, several minor bacterial phyla were also observed in the rumen of camels such as Verrucomicrobia, Elusimicrobia, Cyanobacteria and Chloroflexi (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>).</ns0:p><ns0:p>All Bacterial genera were observed in all groups except seven genera, including uncultured Marinilabiaceae (Bacteroidetes), Quinella (Firmicutes) and Streptococcus (Firmicutes) that were observed only in G2 and G3 camels. Ruminobacter (Proteobacteria) was observed only in G1 and G2 camels. On the other hand, Arcobacter and Succinivibrio within phylum Proteobacteria were observed only in G1 camels and Betaproteobacteria (Proteobacteria) was observed only in G3 camels. Moreover, many unclassified bacteria were observed across samples and accounted for 39% of total bacterial reads. Most of these unclassified bacterial reads were observed in phylum Firmicutes and Bacteroidetes.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>Reads that classified as archaea were further classified to three orders within the phylum Euryacheota: Thermoplasmatales, Methanobacteriale and Methanomicrobial. Thermoplasmatales dominated the archaeal community and showed the highest population in LF-G3 samples, this order was not classified out of order level (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>). Reads that classified in the Methanobacteriale were further classified to family Methanobacteriacea that includes three genera: Methanobrevibacter, Methanophera and Methanobacterium. Methanobrevibacter is the second largest contributor in archaeal population and was higher in SF-G1 samples. Methanosphaera exhibited higher relative abundance in SF-G2 samples. Methanobacterium was absent in G3 camels; however, a small proportion of this genus was found in the camels of G1 and G2. Methanomicrobium genus, which belongs to order Methanomicrobiales and family Methanomicrobiaceae was the least contributor in archaeal population and was more prevalent in LF-G3 samples (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>Reads that classified as protozoa were further classified to two families: Ophryoscolecidae and Isotrichidae (Table <ns0:ref type='table'>4</ns0:ref>). Reads that classified in the Ophryoscolecidae were further classified to seven genera, Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium, Epidinium and Trichostomatia. Reads that classified in the Isotrichidae were further classified to two genera, Dasytricha and Isotricha. The variation among the camels in protozoal population was clearly observed and seemed to be higher than other microbial communities; however, the protozoal community composition was similar among the camels (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>). The most dominant protozoal genera were Diplodinium, Ophryoscolex and Entodinium. Camels in G1 had the highest population of Entodinium and Epidinium. Camels in G2 had the greatest population of Eudiplodinium, Ophryoscolex, Isotricha and Dasytricha and camels in G3 had the greatest population of Diplodinium, Polyplastron and Trichostomatia. On the sample fraction level, the solid fraction had a higher representation of Ophryoscolex, Polyplastron, Eudiplodinium, Epidinium and Diplodinium, while the liquid fraction had a higher representation of Entodinium, Isotricha and Dasytricha (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>Reads that classified as rumen fungi were further classified to two phyla: Neocallimastigomycota and Chytridiomycota. Reads that classified in the Neocallimastigomycota were further classified to family Neocallimasticeceae that includes three genera, Neocallimastix, Piromyces and Cyllamyces. Neocallimastix dominated the fungal community, followed by Piromyces and Cyllamyces (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>). These anaerobic fungal genera represented &gt; 99.5 % of the fungal population. In addition, reads that classified in the Chytridiomycota were further classified to family Spizellomycetaceae that includes genus Spizellomyces, which was noted in a very small proportion (&lt; 0.5 %) (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>). Neocallimastix was more abundant in the SF-G1 samples while Piromyces and Cyllamyces were more abundant in LF-G2 and SF-G3 respectively (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Effect of feeding system and facility on the composition of microbial communities</ns0:head><ns0:p>Multivariate analysis separated libraries by feeding system and housing facility distinctly (Figs. <ns0:ref type='figure' target='#fig_3'>2 and 3</ns0:ref>). Also, bacteria, dominated by phylum Firmicutes were the main driver of differences between animals (Fig. <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>). Furthermore, Entodinium, Thermoplasmatales, Neocallimastix were the main drivers of differences in protozoal, archaeal and fungal communities, respectively. PERMANOVA analysis revealed that the difference between camel groups was significant (P &lt; 0.01) in all microbial groups (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Pairwise comparison between camel groups based on Bonferroni-corrected p-value demonstrated that the difference was significant (P &lt; 0.05) between camels of G2 and G3 in bacterial and archaeal communities (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Moreover, the difference was significant between the three groups in the protozoal community (P &lt; 0.05), whereas, in the fungal community, the difference was significant only between camels in group G1 and G2 (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Pearson correlation between microbes in the rumen of dromedary camel</ns0:head><ns0:p>Pearson correlation analysis (Fig. <ns0:ref type='figure' target='#fig_4'>4A, 4B</ns0:ref>), revealed many significant positive and negative correlations (P &lt; 0.05). For example, in active bacteria, Bacteroidetes correlated positively with Cyllamyces and negatively with Butyrivibrio, Methanosphaera and Trichostomatia. Prevotellaceae correlated positively with Neocallimastix and Entodinium and negatively with Ruminococcaceae, Methanosphaera and Diplodinium. Fibrobacteres correlated positively with Cyllamyces, Methanomicrobium, Thermoplasmatales and Diplodinium and negatively with Methanosphaera, Epidinium, Ruminococcaceae and Butyrivibrio. Firmicutes correlated positively with Methanosphaera and negatively with Piromyces, Thermoplasmatales and Methanomicrobium.</ns0:p><ns0:p>In active archaea, Thermoplasmatales correlated positively with Diplodinium and negatively with Methanobrevibacter and Methanosphaera. In active protozoa, there was a negative correlation between Polyplastron, Entodinium, Ophryoscolex and Epidinium. In active fungi, a negative correlation was observed between Cyllamyces, Neocallimastix and Piromyces and between Piromyces and Entodinium.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Rumen microbes can ferment a wide variety of feed components, including cellulose, xylan, amylose and protein and produce volatile fatty acids that provide the animal with approximately 70% of daily energy requirements <ns0:ref type='bibr' target='#b5'>(Bergman, 1990;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Furthermore, the rumen fermentation generates methane, which contributes to global warming and represents 2-12% loss of feed energy for the animal <ns0:ref type='bibr' target='#b41'>(Johnson and Ward, 1996;</ns0:ref><ns0:ref type='bibr' target='#b13'>Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b38'>Jami et al., 2014)</ns0:ref>. Therefore, investigation of these microbial communities is the key to understand their roles and maximize ruminal fermentation and fiber digestion and reduction of greenhouse gas emissions <ns0:ref type='bibr' target='#b53'>(Lee et al., 2012)</ns0:ref>. Camels groups were fed different diets and reared in different locations. The diversity and relative abundance of microbial communities varied between camel groups, which was supported by the results of PCoA, LDA and PERMANOVA analyses. This result is in agreement with the results of other ruminants <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>.Camels in the present study were fed on different forages; Egyptian clover and wheat straw (Supplementary Table <ns0:ref type='table'>S1</ns0:ref>). Egyptian clover is the most balanced and nutritious fodder widely used for feeding camels <ns0:ref type='bibr' target='#b13'>(Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr'>Bakheit, 2013;</ns0:ref><ns0:ref type='bibr' target='#b84'>Shrivastava et al., 2014)</ns0:ref>, which might supported the high microbial diversity in G2 camels compared to other groups (Table <ns0:ref type='table'>1</ns0:ref>). This was consistent with previous studies on cows <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b83'>Shanks et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b48'>Kumar et al., 2015)</ns0:ref>. Highly degradable carbohydrates support bacterial and protozoal growth <ns0:ref type='bibr' target='#b19'>(Dijkstra and Tamminga, 1995;</ns0:ref><ns0:ref type='bibr' target='#b48'>Kumar et al., 2015)</ns0:ref>, which could demonstrate their higher population in G1 camels. Additionally, higher bacterial population slows the fungi growth <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992;</ns0:ref><ns0:ref type='bibr' target='#b65'>Orpin and Joblin, 1997)</ns0:ref>, which was illustrated by low fungal population in G1 camels.</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>Firmicutes phylum appeared more abundant than Bacteroidetes and both phyla comprised &gt; 75% of all bacterial reads (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>), which is in agreement with studies on camels <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>, Surti Buffalo <ns0:ref type='bibr' target='#b66'>(Pandya et al., 2010)</ns0:ref> and Muskoxen <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref>. The majority of Firmicutes' members have a potential role in fiber digestion, which might illustrate their higher population in G2 camels that were fed on high-quality forage and also in solid fraction. This speculation was supported by the high proportion of Ruminococcaceae and Lachnospiraceae families that active in fiber digestion in rumen <ns0:ref type='bibr' target='#b69'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b61'>Nathani et al., 2015)</ns0:ref>. Bothe Blautia and Acetitomaculum genera have a key role as reductive acetogens (Le <ns0:ref type='bibr'>Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b94'>Yang et al., 2016)</ns0:ref> and varied among the camel groups in this study. This finding could indicate that the reductive acetogenesis pathway could be maximized by diet to minimize methane production (Le <ns0:ref type='bibr'>Van et al., 1998)</ns0:ref>. Bacteroidetes were higher in samples collected from animals reared in the station that used lowquality feed (G3), which was similar to results on cattle <ns0:ref type='bibr' target='#b68'>(Pitta et al., 2014b)</ns0:ref>. The phylum was dominated by family Prevotellaceae, which confirms <ns0:ref type='bibr' target='#b26'>Gharechahi et al. (2015)</ns0:ref>. The members of Bacteroidetes possess diverse enzymes that can target cellulose, pectin and soluble polysaccharides released in the liquid phase <ns0:ref type='bibr' target='#b58'>(Mackenzie et al., 2015)</ns0:ref>. Additionally, Prevotella genus is involved in propionate production that is used for energy by the host <ns0:ref type='bibr' target='#b61'>(Nathani et al., 2015)</ns0:ref>. We speculate that Bacteroidetes species contribute to the adaptation of camels to arid conditions. The RC9_gut_group found in this study belongs to uncultured genera and was found also in the Rhinoceros hindgut <ns0:ref type='bibr' target='#b9'>(Bian et al., 2013)</ns0:ref>. Unclassified Bacteroidetes specialize in lignocellulose degradation <ns0:ref type='bibr' target='#b58'>(Mackenzie et al., 2015)</ns0:ref>, which could support their high proportion in G3 camels. Fibrobacteres was higher (3.1%) in this study compared to the other findings on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>; this phylum is the principal cellulolytic bacteria in the rumen <ns0:ref type='bibr' target='#b74'>(Ransom-Jones et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b61'>Nathani et al., 2015)</ns0:ref>, which might illustrate its higher relative abundance in solid fraction and in the rumen of camels fed on wheat straw (G3) (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). The members of Proteobacteria were lower in G2 and G3 camels that were fed on diet rich in fiber contents. These findings highlighted this phylum's function as a protein-degrading bacteria as it was reported by <ns0:ref type='bibr' target='#b56'>Liu et al. (2017)</ns0:ref>. The abundance of Treponema was higher in the solid fraction and in G3 camels (Figure <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>). Treponema is the dominant genus in Spirochaetes phylum and it is fiber-associated bacteria, which could indicate to its cellulytic and xylanolytic activities <ns0:ref type='bibr' target='#b35'>(Ishaq and Wright, 2012)</ns0:ref>.</ns0:p><ns0:p>The dominant bacterial genera in this study were Butyriovibrio, RFN8-YE57, Ruminococcus, Prevotella, Fibrobacter, Treponema and VadinHA. These genera were higher in the SF except RFN8-YE57 compared to the LF; this finding was consistent with a study on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>, and confirms that the solid-attached microbes could play a major role in ruminal fiber digestion <ns0:ref type='bibr' target='#b39'>(Jewell et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b63'>Noel et al., 2017)</ns0:ref>. Most of Elusimicrobia in this study were uncultured; some members of this phylum were isolated from the termite's gut that degrades cellulose <ns0:ref type='bibr' target='#b32'>(Herlemann et al., 2009)</ns0:ref>. Therefore, we speculate that this phylum has a role in fiber digestion and that might illustrate their high proportion in G3 camels. Actinobacteria observed also in the rumen of moose and some members of this phylum have acetogenic activities <ns0:ref type='bibr' target='#b37'>(Ishaq et al., 2015)</ns0:ref>. Some members of Victivallis within Lentisphaerae phylum were involved in cellobiose degradation <ns0:ref type='bibr' target='#b96'>(Zoetendal et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Unclassified bacteria in our study (39% of total bacterial reads) were less than the percentage found in a study of Muskoxen (54%) <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref>. The presence of unclassified bacteria in the gut was commonly observed <ns0:ref type='bibr' target='#b27'>(Gruninger et al., 2016)</ns0:ref> and could be a result of the presence of new bacteria that ferment plant biomass <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref> or related to short reads were generated from RNA sequencing <ns0:ref type='bibr' target='#b55'>(Li et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>The archaeal population has important roles in methane emission mitigation strategies as they convert the H 2 and CO 2 produced in the rumen to methane <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010)</ns0:ref>. Additionally, acetate produced in fiber breakdown provides a methyl group for methanogenesis; therefore, alteration of diet shifts the structure of methanogen populations <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b88'>Tapio et al., 2017 )</ns0:ref>, which could demonstrate the variation in the relative abundance of archaea between camel groups. Camels of the second group (G2) that fed fresh clover, showed the highest archaeal population (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>) and the archaeal community was dominated by Thermoplasmatales, a methylotrophic methanogens order (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>), which was consistent with the results on cattle <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2014)</ns0:ref> and camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. Thermoplasmatales produce methane from methyl amine and its population was decreased by the addition of rapeseed oil to animal diet, making it a high potential target in future strategies to mitigate methane emissions <ns0:ref type='bibr' target='#b71'>(Poulsen et al., 2013)</ns0:ref>. The Methanobrevibacter, Methanosphaera, Methanomicrobium and Methanobacterium (Table <ns0:ref type='table'>4</ns0:ref>) are the other dominant archaea in this study and in accordance with the results found in beef cattle <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2014)</ns0:ref>. Methanobrevibacter dominated the methanogens in other ruminant <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref> and was associated with high methane emissions <ns0:ref type='bibr' target='#b88'>(Tapio et al., 2017)</ns0:ref>. Moreover, Methanomicrobium was higher in the camels of G3 that were fed on poor quality forage, which was similar to results found in buffalo <ns0:ref type='bibr' target='#b23'>(Franzolin and Wright, 2016)</ns0:ref>, and In vitro <ns0:ref type='bibr' target='#b90'>(Wang et al., 2018)</ns0:ref>. In rumen, Methanomicrobium converts H 2 and/or formate into CH 4 <ns0:ref type='bibr' target='#b51'>(Leahy et al., 2013)</ns0:ref>. The abundance of Thermoplasmatales was also negatively correlated with Methanobrevibacter, which is consistent with previous results <ns0:ref type='bibr' target='#b16'>(Danielsson et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b59'>McGovern et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>The majority of protozoal reads were related to Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium and Epidinium (Table <ns0:ref type='table'>4</ns0:ref>). Similar findings were observed on different ruminants <ns0:ref type='bibr' target='#b4'>(Baraka, 2012)</ns0:ref>. The relative abundance of protozoal was influenced by feeding system and housing facility, which was in the same line with results on cattle <ns0:ref type='bibr' target='#b34'>(Hristov et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b91'>Weimer, 2015)</ns0:ref>. The Diplodinium dominated the protozoal community and was prevalent in the G3 camels, which highlighted the cellulolytic activity of this genus <ns0:ref type='bibr' target='#b14'>(Coleman et al., 1976)</ns0:ref>. Also, some species of genus Diplodinium were discovered in the rumen of Egyptian camel and is considered to be peculiar in camel such as Diplodinium cameli <ns0:ref type='bibr' target='#b47'>(Kubesy and Dehority, 2002)</ns0:ref>. In addition, Entodinium was higher in G1 camels that were fed on concentrates feed mixture that increase the protozoa. Also, this genus predominates rumen of camels <ns0:ref type='bibr' target='#b82'>(Selim et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b25'>Ghali et al., 2005)</ns0:ref> and cattle <ns0:ref type='bibr' target='#b13'>(Carberry et al., 2012)</ns0:ref>. Moreover, <ns0:ref type='bibr' target='#b46'>Kittelmann and Janssen (2011)</ns0:ref> showed that the Polyplastron was the dominant genus in cattle. On the function level, all the genus Eudiplidinum, Epidinum and Diplodinum have cellulolytic activity <ns0:ref type='bibr' target='#b14'>(Coleman et al., 1976)</ns0:ref>, whereas, Polyplastrone and Epidinium have a xylanolytic activity <ns0:ref type='bibr' target='#b18'>(Devillard, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>B&#233;ra-Maillet et al., 2005)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>The highest fungal population was observed in the solid fraction and rumen of G3 camels (Table <ns0:ref type='table'>1</ns0:ref>). These findings were in agreement with the results of studies stated that the fibre-based diets stimulated the fungal growth <ns0:ref type='bibr' target='#b64'>(Orpin, 1977;</ns0:ref><ns0:ref type='bibr' target='#b77'>Roger et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b42'>Kamra et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b29'>Haitjema et al., 2014)</ns0:ref>. This speculation could explain the low fungal population in G1 camels in our study. Moreover, the longer retention time and neutral pH in camel's forestomach <ns0:ref type='bibr' target='#b78'>(Russell and Wilson, 1996)</ns0:ref> make it more suitable for the survival of rumen fungi. The genus Neocallimastix dominated the fungal community and was higher in the G1 camels, which was similar to other results on sheep and camels <ns0:ref type='bibr' target='#b45'>(Kittelmann et al., 2013</ns0:ref><ns0:ref type='bibr' target='#b73'>, Rabee et al., 2019)</ns0:ref>. This genus produces enzymes capable of hydrolyzing cellulose, xylan and starch <ns0:ref type='bibr' target='#b67'>(Pearce and Bauchop, 1985)</ns0:ref>. Cyllamyces that was observed in small population, has the ability to degrade poor-quality feeds <ns0:ref type='bibr' target='#b86'>(Sridhar et al., 2014)</ns0:ref>, which might explain its high population in solid fraction and G3 camels. Piromyces was the second dominant genus in the camel rumen of this study and produces cellulolytic and xylanolytic enzymes <ns0:ref type='bibr' target='#b89'>(Teunissen et al., 1992)</ns0:ref>. Therefore, the fungi were more prevalent in ruminants of G2 camels, which were fed high-quality forage with high fiber contents than in G2 and G3 camels. The genus Spizellomyces is closely related to Chytridiomctes <ns0:ref type='bibr' target='#b11'>(Bowman et al., 1992)</ns0:ref>, and common in grassland and crop soil <ns0:ref type='bibr' target='#b57'>(Lozupone and</ns0:ref><ns0:ref type='bibr'>Klein, 2002, Kittelmann et al., 2012)</ns0:ref>. Thus, contamination of the forages by soil could explain the presence of this fungus in the camel rumen.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between rumen microbes</ns0:head><ns0:p>Interactions between rumen microbes drive feed degradation and methane formation in the rumen, which influence the animal production and the environment <ns0:ref type='bibr' target='#b92'>(Williams et al., 1994;</ns0:ref><ns0:ref type='bibr' target='#b53'>Lee et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Positive and negative correlations were observed within and between microbial communities in this study (Fig. <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>). Methanogens colonize the protozoa and this relationship enhances methane formation <ns0:ref type='bibr' target='#b62'>(Newbold et al., 1995)</ns0:ref>, which highlighted some positive correlations between protozoa and archaea. Additionally, the fibrolytic bacteria produce the important substrates mainly hydrogen and methyl groups that methanogens use for growth <ns0:ref type='bibr' target='#b40'>(Johnson and Johnson, 1995)</ns0:ref>, which demonstrated the positive correlations found between Fibrobacteres and some methanogens. Also, positive correlation between the methylotrophic Methanosphaera and Lachnospiraceae that has been implicated in pectin degradation and provides methanol as a substrate for the methylotrophs <ns0:ref type='bibr' target='#b17'>(Dehority, 1969)</ns0:ref>. On the other hand, Prevotella is a hydrogen utilizer and produces propionate that impact the methanogenesis in the rumen negatively <ns0:ref type='bibr' target='#b69'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b56'>Liu et al., 2017)</ns0:ref>, which illustrates the negative correlation between Prevotellaceae and archaea.</ns0:p><ns0:p>Since the rumen anaerobic fungi produce abundant H 2 through the fermentation of carbohydrate; they can interact positively with H 2 utilizers such as archaea, Prevotellaceae, Blautia and Acetitomaculum <ns0:ref type='bibr' target='#b65'>(Orpin and Joblin, 1997;</ns0:ref><ns0:ref type='bibr'>Le Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b94'>Yang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b56'>Liu et al., 2017)</ns0:ref>. Additionally, the anaerobic fungi penetrate plant tissue, which provides an increased surface area for bacterial colonization <ns0:ref type='bibr' target='#b65'>(Orpin and Joblin, 1997)</ns0:ref>, which could explain the positive correlation between fungi and both Butyrivibrio and Fibrobacteres. However, fungi are negatively impacted by the presence of some bacteria and protozoa as the fungal zoospores are likely to be a prey for protozoa <ns0:ref type='bibr' target='#b60'>(Morgavi et al., 1994)</ns0:ref>, which demonstrated the negative correlation between both Neocallimastix and Piromyces with Diplodinium and Entodinium. Furthermore, Ruminococcus produces compounds that inhibit the growth of rumen fungi <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992)</ns0:ref>, which support the negative correlation between Neocallimastix and Ruminococcaceae. Polyplastron predates upon other protozoa like Epidinium, Eudiplodinium, Diplodinium, and Ostracodinium <ns0:ref type='bibr' target='#b20'>(Eadie, 1967)</ns0:ref>, which might explained the negative correlation between Polyplastron and other Protozoa.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>The microbial community in camel rumen was diverse and similar in composition between the camels. The majority of camel rumen microbes (bacteria, fungi, and protozoa) were fibrolytic or have a possible role in fiber digestion, which might illustrate the ability of camel to live in desert harsh conditions under poor feeds. Moreover, the structure of microbial community in rumen of camel found to be similar to other ruminants with a shown difference in the relative abundances. The present results should open new perspectives for further cultivation and isolation studies on the unclassified microorganisms found in the rumen of camels to classify them and assign their functions.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>The relative abundance of microbial groups Relative abundance (%) of bacterial phyla Manuscript to be reviewed Relative abundance (%) of archaeal orders and genera Manuscript to be reviewed Relative abundance (%) of fungal genera </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Comparison of relative abundance of genera of the microbiota in dromedary camel. bacterial (a), archaeal (b), protozoal (c) and fungi (d) in ruminal solid (SF) and liquid (LF) fractions of camels under different feeding systems.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3:Linear Discriminant analysis of microbial communities in the samples based on the relative abundance of genera of active bacteria (a), archaea (b), protozoa (c) and fungi i (d)in ruminal solid (SF), and liquid (LF) fractions of camels under three feeding systems, G1 (black dots), G2 (blue squares) and G3 (coral triangles).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>.07 0.2&#177;0.04 0.8&#177;0.4 0.4&#177;0.1 a The value was calculated from one animal. PeerJ reviewing PDF | (2019:12:44048:6:0:NEW 27 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Relative abundance (%) of bacterial phyla in the ruminal solid (SF) and liquid (LF)</ns0:figDesc><ns0:table><ns0:row><ns0:cell>fractions of camels fed a mixed ration(G1), high-quality forage(G2) and low-quality forage</ns0:cell></ns0:row><ns0:row><ns0:cell>(G3) (Mean &#177; Standard Error (SE)).</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:12:44048:6:0:NEW 27 Jul 2020)Manuscript to be reviewed</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Relative abundance (%) of archaeal orders and genera observed in the ruminal solid (SF), and liquid (LF) fractions of camels under different feeding systems. Animals in G1 fed a mixed ration, animal in G2 fed high-quality forage and animal in G3 fed low qualityforage (Mean &#177; Standard Error (SE)).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Protozoa</ns0:cell><ns0:cell>G1</ns0:cell><ns0:cell>G2</ns0:cell><ns0:cell>G3</ns0:cell><ns0:cell>Overall mean</ns0:cell></ns0:row><ns0:row><ns0:cell>Entodinium SF</ns0:cell><ns0:cell>23&#177;6</ns0:cell><ns0:cell>6.5&#177;0.6</ns0:cell><ns0:cell>6&#177;1</ns0:cell><ns0:cell>11&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell>Entodinium LF</ns0:cell><ns0:cell>54&#177;10</ns0:cell><ns0:cell>15&#177;2.5</ns0:cell><ns0:cell>5&#177;1</ns0:cell><ns0:cell>24&#177;6</ns0:cell></ns0:row><ns0:row><ns0:cell>Polyplastron S F</ns0:cell><ns0:cell>10&#177;1</ns0:cell><ns0:cell>17.5&#177;2</ns0:cell><ns0:cell>25&#177;3</ns0:cell><ns0:cell>17&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Polyplastron LF</ns0:cell><ns0:cell>6&#177;1</ns0:cell><ns0:cell>11&#177;0.2</ns0:cell><ns0:cell>24&#177;3</ns0:cell><ns0:cell>12&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Diplodinium S F</ns0:cell><ns0:cell>23&#177;1</ns0:cell><ns0:cell>35&#177;3</ns0:cell><ns0:cell>49&#177;10</ns0:cell><ns0:cell>34&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell>Diplodinium LF</ns0:cell><ns0:cell>13&#177;3</ns0:cell><ns0:cell>27&#177;3</ns0:cell><ns0:cell>61&#177;6</ns0:cell><ns0:cell>29&#177;5</ns0:cell></ns0:row><ns0:row><ns0:cell>Eudiplodinium SF</ns0:cell><ns0:cell>8&#177;0.6</ns0:cell><ns0:cell>8&#177;2</ns0:cell><ns0:cell>2&#177;0.7</ns0:cell><ns0:cell>7&#177;1</ns0:cell></ns0:row><ns0:row><ns0:cell>Eudiplodinium LF</ns0:cell><ns0:cell>4&#177;1</ns0:cell><ns0:cell>5.5&#177;1</ns0:cell><ns0:cell>2.5&#177;0.5</ns0:cell><ns0:cell>4.5&#177;0.6</ns0:cell></ns0:row><ns0:row><ns0:cell>Epidinium SF</ns0:cell><ns0:cell>5&#177;0.8</ns0:cell><ns0:cell>4&#177;1</ns0:cell><ns0:cell>2&#177;1</ns0:cell><ns0:cell>4&#177;0.1</ns0:cell></ns0:row><ns0:row><ns0:cell>Epidinium LF</ns0:cell><ns0:cell>3&#177;0.8</ns0:cell><ns0:cell>4.5&#177;0.6</ns0:cell><ns0:cell>1&#177;0.7</ns0:cell><ns0:cell>3.5&#177;0.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Ophryoscolex SF</ns0:cell><ns0:cell>30&#177;4</ns0:cell><ns0:cell>27&#177;3</ns0:cell><ns0:cell>15&#177;5</ns0:cell><ns0:cell>26&#177;2.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Ophryoscolex LF</ns0:cell><ns0:cell>19&#177;4</ns0:cell><ns0:cell>29&#177;0.6</ns0:cell><ns0:cell>6.5&#177;4</ns0:cell><ns0:cell>22&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Trichostomatia SF 0.1&#177;0.02</ns0:cell><ns0:cell>1&#177;0.25</ns0:cell><ns0:cell>0.3&#177;0.15</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Trichostomatia LF 0.2&#177;0.04</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell><ns0:cell>1&#177;0.1</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell></ns0:row><ns0:row><ns0:cell>Isotricha SF</ns0:cell><ns0:cell cols='3'>0.2&#177;0.04 0.3&#177;0.05 0.3&#177;0.004</ns0:cell><ns0:cell>0.3&#177;0.03</ns0:cell></ns0:row><ns0:row><ns0:cell>Isotricha LF</ns0:cell><ns0:cell>0.5&#177;0.2</ns0:cell><ns0:cell>2&#177;0.9</ns0:cell><ns0:cell>0.3&#177;0.01</ns0:cell><ns0:cell>1&#177;0.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Dasytricha SF</ns0:cell><ns0:cell cols='3'>0.04&#177;0.01 1.5&#177;0.3 0.2&#177;0.15</ns0:cell><ns0:cell>1&#177;0.3</ns0:cell></ns0:row><ns0:row><ns0:cell>Dasytricha LF</ns0:cell><ns0:cell cols='2'>0.1&#177;0.002 5.5&#177;0.8</ns0:cell><ns0:cell>0.5&#177;0.3</ns0:cell><ns0:cell>3&#177;1</ns0:cell></ns0:row></ns0:table><ns0:note>2PeerJ reviewing PDF | (2019:12:44048:6:0:NEW 27 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 5 :</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Relative abundance (%) of fungal genera in the ruminal solid (SF) and liquid fraction (LF) of camels under different feeding systems. Camels in G1 fed a mixed ration, animals in G2 fed high-quality forage, and animals in G3 fed low-quality forage (Mean &#177; SE).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Fungi</ns0:cell><ns0:cell>G1</ns0:cell><ns0:cell>G2</ns0:cell><ns0:cell>G3</ns0:cell><ns0:cell>Overall mean</ns0:cell></ns0:row><ns0:row><ns0:cell>Spizellomyces SF</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0.1</ns0:cell><ns0:cell>0.02</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>Spizellomyces LF 0.3 &#177; 0.1 0.25 &#177; 0.1</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces SF</ns0:cell><ns0:cell>2&#177; 0.6</ns0:cell><ns0:cell>3&#177; 1.5</ns0:cell><ns0:cell>7&#177; 4</ns0:cell><ns0:cell>3.5&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces LF</ns0:cell><ns0:cell>2&#177; 0.8</ns0:cell><ns0:cell>3&#177; 0.8</ns0:cell><ns0:cell>10&#177; 1</ns0:cell><ns0:cell>4&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces SF</ns0:cell><ns0:cell>6&#177; 3</ns0:cell><ns0:cell>12&#177; 0.7</ns0:cell><ns0:cell>8&#177; 1</ns0:cell><ns0:cell>9&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces LF</ns0:cell><ns0:cell>6&#177;4</ns0:cell><ns0:cell>12&#177;2</ns0:cell><ns0:cell>10&#177;6</ns0:cell><ns0:cell>10&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix SF</ns0:cell><ns0:cell>92&#177;3</ns0:cell><ns0:cell>85&#177;1</ns0:cell><ns0:cell>85&#177;3</ns0:cell><ns0:cell>87&#177;1</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix LF</ns0:cell><ns0:cell>92&#177;4</ns0:cell><ns0:cell>85&#177;1.5</ns0:cell><ns0:cell>81&#177;7</ns0:cell><ns0:cell>86&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>ND: Non Determined</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:12:44048:6:0:NEW 27 Jul 2020) Manuscript to be reviewed PeerJ reviewing PDF | (2019:12:44048:6:0:NEW 27 Jul 2020)</ns0:note></ns0:figure> </ns0:body> "

" Desert Research Center 27th July, 2020 1Mathaf El Matariya St.B.O.P.11753 Matariya- Cairo,Egypt Phone: (+202)26332846 - 26374800 FAX: (+202) 26357858 Email:[email protected] Dear Editor, We thank you for your comments. We responded to your comments and enclosed unclean paper including all comments colored by yellow. Below are the responses to all the comments. We appreciate the opportunity to submit our manuscript to Peer J. Yours sincerely, Dr. Alaa Rabee Researcher at Desert Research Center, Egypt On behalf of all authors Comments Manuscript title: “Comparative analysis of the metabolically active microbial communities in the rumen of dromedary camels under different feeding systems using total rRNA sequencing ” Editor’s comments You cannot distinguish the effect of station and feed. The manuscript must state that clearly and remove all conclusions about the effect of feed. Supplemental note S1 is not appropriate or convincing. >> Thank you, we modified the paper and removed Supplemental note S1. The authors do not appear to have addressed my previous comments about style and format or carefully reviewed the manuscript before submission. The writing needs careful revision using the following examples. This means not just correcting the comment but also looking for similar errors throughout the manuscript. For example, phrases like “Methonomicrobium has been shown to be responsible for the conversion of.. (line 379)” are wordy. The reader can presume that scientific facts come from previous scientific publications, as indicated by the citation. Replace with “Methonomicrobium converts..” and remove phrases like “previous studies showed that (line 393)” and “the study of (line 394)” at those lines and throughout the manuscript. >> we revised the paper and improved it based on your examples. Line 42. Revise to “These camels were reared at three stations that use different feeding systems: clover, hay and wheat straw (G1), fresh clover (G2), and wheat straw (G3). >> Modified. Line 48. Delete “Feeding system…microbial groups.” You cannot say if it was feed or facility. Here and throughout, revise to statements like “..camels reared at facility G2, where they were fed fresh clover, showed…” >> Deleted. Line 51. Revise to “…with facility/feed and…” >> Revised in the whole paper. Line 52. The statement “..analysis showed positive and negative correlations…” adds little. Provide an interesting example or delete. >> Deleted. Line 54. Delete conclusion about feed type. >> Deleted. Line 63. Here and throughout, never use “which” twice in a sentence. Revise to “…microorganisms. This long retention improves the efficiency of digestion..” >> we revised it in the whole paper. Line 65. This paragraph needs reorganization. Delete “Based on …. Concentrated supplements.” Start paragraph with “The feed ranchers provide camels, which ranges from forage in traditional pastures to concentrated supplements in intensive feedlots, influences the structure of the camel microbiome (Henderson et al. 2015).' >> the paragraph was reorganized. Line 76. Start a new paragraph with “Digestion in the camel… >> Modified. Line 85. Delete “of PCR-based” >> Deleted. Line 89-92. Move “The recent development…culture-based methods..” to start of paragraph. >> Moved. Line 111. Delete “reared under different feeding systems” >> Deleted. Line 119. Replace “under three different feeding systems” with “reared at three stations that use different feeding systems” >> Replaced. Line 122. Provide the location of the farm, as you did for G1. I suggest “Camels in group G2 were housed at the xxxx Station and fed fresh.. >> The location was provided. Line 124. As above, revise to “…G3 were housed xxxx and fed wheat…” >> The location was provided. Line 202. Delete “The other phyla including” and replace “that was” with “were” >> Deleted. Line 296. Revise to “Camels groups were fed…” Also, as stated above, the experimental design does not allow you to conclude that “diet type has the main effect.” Delete “However…In addition (line 296-298).” >> Revised. Line 301. Replace “confirmed the finding of this study and” >> we improved this part. Line 307. Avoid superfluous determiners. Delete “the” here, in line 309 and 310. Search for this article (the) throughout text and determine if it is necessary. >> Revised in whole paper. Line 313. Delete “was” >> Deleted. Line 319. Delete “that was found to be” >> Deleted. Line 324. Revise to “..higher in samples collected from animals reared in the station that used low-quality feed..” >> Revised. Line 333. Replace “are specialized” with “specialize” >> Replaced. Line 356. Here and throughout, use reasonable and consistent significant figures (54% not 53.7%) >> Revised. Line 363. Replace “is used to provide” with “provides” >> Replaced. Line 364. Avoid the passive voice. Revise to “alteration of diet shifts the structure of methanogen populations…” >> Revised. Line 370. Revise to “produce” >> Revised. Line 379. Replace “has been shown to be responsible for the conversion of” with “converts” >> Replaced. Line 381. Always add a comma before “which” >> Revised. Line 393. Replace “previous studies …dominant in” with “This genus predominates rumen” >> Replaced. Line 394. Delete “the study of” >> Deleted. Line 416. Avoid the passive voice. Revise to “contamination of forage… could explain the presence…” >> Revised. Line 419. Delete “the” and replace “are the main driver” with “drive” >> Deleted. Line 423. Delete “was believed to,” unless you no longer believe it. >> Deleted. Line 438. Delete “known to be” >> Deleted. Line 448. Conclusions should provide clear statements of what you observed not what you didn’t do. Delete “This study applied…of our study (line 453).” >> The conclusion was modified. Line 454. Remove conclusions about the effect of feed. >> Removed. Line 467, 470, 473,....As stated in my previous comments, cap the first letter of journal titles. (Journal of Crop Science not Journal of crop science). This comment applies to all references. >> All the journal names was revised and caped. Table 1. Be consistent in significant figures, as below. Archaea SF 2.3±0.2, 3.4±0.4, 2.2±1.0, 3.0±0.3 Archaea LF 2.2±0.2, 2.8±0.4, 1.8± 0.2, 2.0± 0.3 Table 2, 3, 4 and 5. Again, present significant figures. 63±2… >> Revised, thank you. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The breakdown of plant biomass in rumen depends on interactions between bacteria, archaea, fungi, and protozoa; however, the majority of studies of the microbiome of ruminants, including the few studies of the rumen of camels, only studied one of these microbial groups. In this study, we applied total rRNA sequencing to identify active microbial communities in twenty-two solid and liquid rumen samples from eleven camels. These camels were reared at three stations that use different feeding systems: clover, hay and wheat straw (G1), fresh clover (G2), and wheat straw (G3). Bacteria dominated the libraries of sequence reads generated from all rumen samples, followed by protozoa, archaea, and fungi respectively. Firmicutes, Thermoplasmatales, Diplodinium, and Neocallimastix dominated bacterial, archaeal, protozoal and fungal communities, respectively in all samples. Libraries generated from camels reared at facility G2, where they were fed fresh clover, showed the highest alpha diversity. Principal co-ordinate analysis and linear discriminate analysis showed clusters associated with facility/feed and the relative abundance of microbes varied between liquid and solid fractions. This provides preliminary evidence that bacteria dominate the microbial communities of the camel rumen.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Camels (Camelus dromedaries) can produce milk and meat in hot, arid and semi-arid regions and can provide food security as the climate warms <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b21'>Faye, 2013)</ns0:ref>. Camels also provide textiles (fiber and hair) and are commonly used for transportation, agriculture, tourism, race and riding <ns0:ref type='bibr' target='#b74'>(Rabee et al., 2019)</ns0:ref>. The unique feeding behavior and the functional structure of digestive tract of these pseudo-ruminants is well adapted to deserts <ns0:ref type='bibr' target='#b44'>(Kay et al., 1989)</ns0:ref>. The retention time of feed particles in the camel forestomach is longer than other true ruminants, which prolongs the exposure of plant biomasses to the symbiotic microorganisms. This long retention improves the efficiency of digestion <ns0:ref type='bibr'>(Lechner-Dolland and Engelhardt, 1989)</ns0:ref>. The feed ranchers provide camels, which ranges from forage in traditional pastures to concentrated supplements in intensive feedlots, influences the structure of the camel microbiome <ns0:ref type='bibr' target='#b21'>(Faye, 2013;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al. 2015)</ns0:ref>. The chemical composition of diet shapes fermentation in rumen. For instance, cellulolytic and hemicellulytic diets favor the fibrolytic microorganisms; while, starch and sugars favor the amylolytic <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012)</ns0:ref>. Also, the microbial composition and diversity varies between liquid and solid rumen fractions, which might indicate different roles in rumen fermentation; for instance, plant-adherent microbiota might have a major role in fiber degradation <ns0:ref type='bibr' target='#b76'>(Ren et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Digestion in the camel depends on microbial fermentation in rumen <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref> and the efficiency of this microbial fermentations is based on the interactions between a wide variety of microbial groups, including bacteria, archaea, fungi and protozoa <ns0:ref type='bibr' target='#b94'>(Yanagita et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra, 2005)</ns0:ref>. Analysis of these microbial communities could lead to increases in animal productivity and reduction of greenhouse gas emissions <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Unlike other ruminants, camels can utilize thorny and low quality plants like shrubs with high lignocelulolytic content <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>. Consequently, camel rumen microbes must have the capacity to degrade such poorquality feeds <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. However, the microbial community in the rumen of dromedary camel received less attention than other domesticated ruminants.</ns0:p><ns0:p>Recent development of next generation sequencing technologies provide a rapid method of microbial identification in rumen and overcome the intrinsic constraints of traditional culturebased methods <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b36'>Ishaq and Wright, 2014)</ns0:ref>. Most of assessments of microbial groups in the rumen have relied on amplicon sequencing, which target a specific variable region on 16S rRNA gene <ns0:ref type='bibr' target='#b56'>(Li et al. 2016)</ns0:ref>. This approach needs a wide range of primers to study different microbial communities <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013)</ns0:ref>. Therefore, the output could be biased due to the primer selection and amplification cycling conditions <ns0:ref type='bibr' target='#b28'>(Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b20'>Elekwachi et al., 2017)</ns0:ref>. Total RNA sequencing (RNA-Seq) offers the advantage of specifically targeting active microbes and avoids biases associated with primer selection and chimera generation in PCR <ns0:ref type='bibr' target='#b24'>(Gaidos et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b28'>Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016)</ns0:ref>. In addition, RNA-Seq approach is capable of identifying novel microbes as it is not reliant on primers for known microbes <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>. Highthroughput metatranscriptomic sequencing provides a comprehensive understanding of biological systems by characterization of different groups of organisms in the same environment based on the sequencing of coding and noncoding RNA <ns0:ref type='bibr' target='#b20'>(Elekwachi et al., 2017)</ns0:ref>. Total RNA-Seq was applied to investigate microbial communities in many different systems including, for example, human gut <ns0:ref type='bibr' target='#b73'>(Qin et al., 2012)</ns0:ref>, and cow rumen <ns0:ref type='bibr' target='#b56'>(Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b20'>Elekwachi et al., 2017 )</ns0:ref>.</ns0:p><ns0:p>Previous microbiome studies on camel rumen have characterized one or two microbial groups using classical or molecular approaches. For example, the protozoal community in camel rumen was studied heavily by conventional microscopic methods <ns0:ref type='bibr' target='#b25'>(Ghali et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b4'>Baraka, 2012)</ns0:ref>. Regarding the anaerobic fungi, a new fungal genus, Oontomyces was isolated from the rumen of Indian camel <ns0:ref type='bibr' target='#b14'>(Dagar et al., 2015)</ns0:ref>, and only one study investigated whole fungal community in the gut of camel <ns0:ref type='bibr' target='#b74'>(Rabee et al., 2019)</ns0:ref>. Only three molecular-based studies are available on the bacterial community <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b7'>Bhatt et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b26'>Gharechahi et al., 2015)</ns0:ref>. Furthermore, only one study classified rumen archaea <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. In the present study, total rRNA sequencing was applied to 1) get insight into the composition of active microbiota in the rumen of camels; 2) describe the distribution of microbial groups among solid and liquid rumen fractions; 3) investigate the correlations between all the microbial groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Rumen samples</ns0:head><ns0:p>Rumen samples were collected from eleven adult dromedary camels reared at three stations that use different feeding systems. Camels in group G1 (n=3) were housed in the Maryout Research Station, Alexendria, Egypt and were fed on Egyptian clover hay (Trifolium alexandrinum), wheat straw and concentrates feed mixture. Camels in group G2 (n=6) were housed at the commercial farm in the Kom Hammada and fed on fresh Egyptian clover (100 % high-quality forage diet) then slaughtered in the Kom Hammada slaughterhouse, Elbehera, Egypt. Camels of group G3 (n=2) were housed at the commercial farm in Cairo area and fed on wheat straw (100 % low-quality forage diet) then were slaughtered in Pasateen slaughterhouse, Cairo, Egypt. Animals were kept on these diets for at least one month before the sampling time. The proximate analysis of feeds is illustrated in Supplementary table S1. Details regarding camel rumen samples in this study presented in Supplementary table <ns0:ref type='table' target='#tab_2'>S2</ns0:ref>. Rumen contents were strained immediately by two layers cheesecloth to separate the liquid and solid to form twenty-two samples, frozen using liquid nitrogen and stored at -80 o C before further processing <ns0:ref type='bibr' target='#b20'>(Elekwachi et al., 2017)</ns0:ref>. The project was approved and all samples were collected according to the Institutional Animal Care and Use Committee, Faculty of Veterinary Medicine, University of Sadat City, Egypt (Approval number: VUSC00003).</ns0:p></ns0:div> <ns0:div><ns0:head>RNA isolation, quality and quantity estimation and sequencing</ns0:head><ns0:p>The frozen rumen samples were ground using liquid nitrogen. About 0.5 gram of frozen fine powder was used for total RNA isolation using Trizol-Reagent protocol (Invitrogen, Carlsbad, CA), followed by RNA clean up using MEGA clear Kit (Invitrogen). Total RNA quality and quantity were estimated using an Agilent 2100 bioanalyzer (Agilent Technologies, USA) and RNA 6000 Nano kit (Agilent Technologies, USA). One hundred nanogram of total RNA was reversetranscribed into first strand cDNA and sequenced using Illumina rRNA MiSeq preparation kit (Illumina, USA) by Illumina MiSeq platform.</ns0:p></ns0:div> <ns0:div><ns0:head>Bioinformatic data analysis</ns0:head><ns0:p>The generated RNA sequence reads were analysed using pipeline developed by <ns0:ref type='bibr' target='#b20'>Elekwachi et al. (2017)</ns0:ref>. Briefly, the sequence quality was checked using the FastQC program v. 0.11.4 <ns0:ref type='bibr' target='#b0'>(Andrews, 2010)</ns0:ref>, then Trimmomatic program v. 0.35 <ns0:ref type='bibr' target='#b9'>(Bolger et al., 2014)</ns0:ref> was used to trim adaptors, barcodes, ambiguous and low quality reads. PEAR program v. 0.9.6 <ns0:ref type='bibr' target='#b96'>(Zhang et al., 2014)</ns0:ref> was used to merge read 1 and read 2 using default options. Then after, the hidden Markov models rRNA-HMM tool of the rapid analysis of multiple metagenomes with a clustering and annotation pipeline (RAMMCAP) <ns0:ref type='bibr' target='#b55'>(Li, 2009)</ns0:ref> was used to sort the reads into archaea and bacteria (16S, 23S), and eukaryote (18S, 23S) rRNA sequences. Merged sequence files were then sub-sampled as needed using MEME program v. 4.10.2 <ns0:ref type='bibr'>(Bailey et al., 2009)</ns0:ref>. For each sample, 70,000 reads were run through the pipeline. For subsequent analysis steps, 20 000, 10 000, and 2000 sequences were used for bacteria, eukaryote and archaea, respectively. Taxonomy binning for eukaryote and archaeal SSU rRNA sequences was performed using BLASTN. The sub-sampled query sequences were searched against the SILVA SSURef-111 database using an e-value of 1e -5 . Bacterial SSU sequences were binned into operational taxonomic units (OTUs) using the 'classify. seqs' command of Mothur v. 1.33.1 program <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref>. The SSURef -108 gene and the SSURef-108b taxonomy databases were used. Principal co-ordinate analysis (PCoA) using Bray Curtis dissimilarity and alpha diversity indices (Chao1, Shannon and Inverse Simpson) were evaluated by Mothur <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref> based on sub-sampling of 70,000 reads per sample according the protocol 'Community Structure Analysis Based on OTU Clustering' outlined in <ns0:ref type='bibr' target='#b20'>Elekwachi et al. (2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>Data of relative abundance of bacterial phyla, protozoal genera, fungal genera and archaea genera and order Thermoplasmatales were tested for normality and homogeneity using Shapiro-Wilk test and variables that were deemed non-normal were then arcsine transformed. Linear Discriminate Analysis (LDA) and Bray Curtis Permutational Multivariate Analysis of Variance (PERMANOVA) tests depended on the relative abundance of bacterial phyla. All the protozoal, fungal and archaeal genera and the order Thermoplasmatales were used to show the differences in community structure and to compare the clustering of samples. Pearson correlation analysis was used to identify correlation within and between microbial communities and the correlation scores were visualized as a heatmap. The statistical analyses were performed using the SPSS v. 20.0 software package (SPSS, 1999) and PAST <ns0:ref type='bibr' target='#b30'>(Hammer et al., 2001)</ns0:ref>. Sequences were deposited to the sequence read archive (SRA) under the accession number: SRP107370.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>The composition and diversity of active microbial community</ns0:head><ns0:p>Total rRNA sequencing in twenty-two solid and liquid rumen samples from eleven camels resulted in a total of 3958591 reads with average of 359872 &#177; 85366 (mean &#177; standard error (SE)) reads per animal in the solid fraction (SF) and 3386392 reads with an average of 307854 &#177; 60989 reads per animal in the liquid fraction (LF). The sequence reads of bacteria dominated the active microbial community, followed by protozoa, archaea and fungi (Table <ns0:ref type='table'>1</ns0:ref>). Relative abundance of protozoa was higher in LF-G1 (liquid fraction of G1), while relative abundance of bacteria was higher in SF-G1 (solid fraction of G1). The highest population of archaea was observed in G2 camels. Additionally, G3 camels showed the highest relative abundance of fungi (Table <ns0:ref type='table'>1</ns0:ref>; Supplementary Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). Number of OTUs and Alpha-diversity indices, Chao1, Shannon and Inverse Simpson, were higher in the rumen of LF-G2 samples (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>The composition of bacterial community varied little between groups and consisted of 12 phyla. The five most predominant phyla were Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetes and Fibrobacteres, respectively (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Phylum Firmicutes dominated the bacterial community in all groups and was higher in G2 followed by G1 and G3 camels, respectively, and was also higher in SF compared to LF (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). On the family level, the Firmicutes phylum was dominated by Lachnospiraceae and Ruminococcuceae. In addition, six genera dominated this phylum, including Butyrivibrio, RFN8-YE57, Ruminococcus, vadinHA42, Acetitomaculum and Blautia (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). The second largest phylum, Bacteroidetes, showed the highest relative abundance in G3 followed by G1 and G2 camels and was higher in LF than SF (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). On the family and genus levels, Bacteroidetes was dominated by three families (Prevotellaceae, BS11_ gut_ group, Rikenellaceae) and two genera (Prevotella, RC9_gut_group) higher relative abundance in LF-G1 samples and was dominated by Succinivibrionaceae family and Desulfovibrio genus (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). The Spirochaetes phylum was higher in the SF-G3 and it was classified into two families including Spirochaetaceae and PL-11B10 and was dominated by Treponema genus. Fibrobacteres phylum was higher in SF-G3 (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). Actinobacteria were higher in SF-G2 samples, Tenricutes phylum was higher in LF-G1 samples and Lentisphaerae phylum, was about 3-fold higher in LF as relative to SF and accounted for a large population in the camels of G3 (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Additionally, several minor bacterial phyla were also observed in the rumen of camels such as Verrucomicrobia, Elusimicrobia, Cyanobacteria and Chloroflexi (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>).</ns0:p><ns0:p>Of the 74 genera observed, only seven were observed exclusively in libraries generated from a specific facility, including uncultured Marinilabiaceae (Bacteroidetes), Quinella (Firmicutes) and Streptococcus (Firmicutes) that were observed only in G2 and G3 camels. Ruminobacter (Proteobacteria) was observed only in G1 and G2 camels. On the other hand, Arcobacter and Succinivibrio within phylum Proteobacteria were observed only in G1 camels and Betaproteobacteria (Proteobacteria) was observed only in G3 camels. Moreover, many unclassified bacteria were observed across samples and accounted for 39% of total bacterial reads. Most of these unclassified bacterial reads were observed in phylum Firmicutes and Bacteroidetes.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>Reads that classified as archaea were further classified to three orders within the phylum Euryacheota: Thermoplasmatales, Methanobacteriale and Methanomicrobial. Thermoplasmatales dominated the archaeal community and showed the highest population in LF-G3 samples, this order was not classified out of order level (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>). Reads that classified in the Methanobacteriale were further classified to family Methanobacteriacea that includes three genera: Methanobrevibacter, Methanophera and Methanobacterium. Methanobrevibacter is the second largest contributor in archaeal population and was higher in SF-G1 samples. Methanosphaera exhibited higher relative abundance in SF-G2 samples. Methanobacterium was absent in G3 camels; however, a small proportion of this genus was found in the camels of G1 and G2. Methanomicrobium genus, which belongs to order Methanomicrobiales and family Methanomicrobiaceae was the least contributor in archaeal population and was more prevalent in LF-G3 samples (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>Reads that classified as protozoa were further classified to two families: Ophryoscolecidae and Isotrichidae (Table <ns0:ref type='table'>4</ns0:ref>). Reads that classified in the Ophryoscolecidae were further classified to seven genera, Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium, Epidinium and Trichostomatia. Reads that classified in the Isotrichidae were further classified to two genera, Dasytricha and Isotricha. The variation among the camels in protozoal population was clearly observed and seemed to be higher than other microbial communities; however, the protozoal community composition was similar among the camels (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>). The most dominant protozoal genera were Diplodinium, Ophryoscolex and Entodinium. Camels in G1 had the highest population of Entodinium and Epidinium. Camels in G2 had the greatest population of Eudiplodinium, Ophryoscolex, Isotricha and Dasytricha and camels in G3 had the greatest population of Diplodinium, Polyplastron and Trichostomatia. On the sample fraction level, solid fraction had a higher representation of Ophryoscolex, Polyplastron, Eudiplodinium, Epidinium and Diplodinium, while liquid fraction had a higher representation of Entodinium, Isotricha and Dasytricha (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>Reads that classified as rumen fungi were further classified to two phyla: Neocallimastigomycota and Chytridiomycota. Reads that classified in the Neocallimastigomycota were further classified to family Neocallimasticeceae that includes three genera, Neocallimastix, Piromyces and Cyllamyces. Neocallimastix dominated the fungal community, followed by Piromyces and Cyllamyces (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>). These anaerobic fungal genera represented &gt; 99.5 % of the fungal population. In addition, reads that classified in the Chytridiomycota were further classified to family Spizellomycetaceae that includes genus Spizellomyces, which was noted in a very small proportion (&lt; 0.5 %) (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>). Neocallimastix was more abundant in the SF-G1 samples while Piromyces and Cyllamyces were more abundant in LF-G2 and SF-G3 respectively (Table 5, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Effect of feeding system and facility on the composition of microbial communities</ns0:head><ns0:p>Multivariate analysis separated libraries by feeding system and housing facility distinctly (Figs. <ns0:ref type='figure' target='#fig_3'>2 and 3</ns0:ref>). Also, bacteria, dominated by phylum Firmicutes were the main driver of differences between animals (Fig. <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>). Furthermore, Entodinium, Thermoplasmatales, Neocallimastix were the main drivers of differences in protozoal, archaeal and fungal communities, respectively. PERMANOVA analysis revealed that the difference between camel groups was significant (P &lt; 0.01) in all microbial groups (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Pairwise comparison between camel groups based on Bonferroni-corrected p-value demonstrated that the difference was significant (P &lt; 0.05) between camels of G2 and G3 in bacterial and archaeal communities (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Moreover, the difference was significant between the three groups in the protozoal community (P &lt; 0.05), whereas, in the fungal community, the difference was significant only between camels in group G1 and G2 (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Pearson correlation between microbes in the rumen of dromedary camel</ns0:head><ns0:p>Pearson correlation analysis (Fig. <ns0:ref type='figure' target='#fig_4'>4A, 4B</ns0:ref>), revealed many significant positive and negative correlations (P &lt; 0.05). For example, in active bacteria, Bacteroidetes correlated positively with Cyllamyces and negatively with Butyrivibrio, Methanosphaera and Trichostomatia. Prevotellaceae correlated positively with Neocallimastix and Entodinium and negatively with Ruminococcaceae, Methanosphaera and Diplodinium. Fibrobacteres correlated positively with Cyllamyces, Methanomicrobium, Thermoplasmatales and Diplodinium and negatively with Methanosphaera, Epidinium, Ruminococcaceae and Butyrivibrio. Firmicutes correlated positively with Methanosphaera and negatively with Piromyces, Thermoplasmatales and Methanomicrobium.</ns0:p><ns0:p>In active archaea, Thermoplasmatales correlated positively with Diplodinium and negatively with Methanobrevibacter and Methanosphaera. In active protozoa, there was a negative correlation between Polyplastron, Entodinium, Ophryoscolex and Epidinium. In active fungi, a negative correlation was observed between Cyllamyces, Neocallimastix and Piromyces and between Piromyces and Entodinium.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Rumen microbes can ferment a wide variety of feed components, including cellulose, xylan, amylose and protein and produce volatile fatty acids that provide the animal with approximately 70% of daily energy requirements <ns0:ref type='bibr' target='#b5'>(Bergman, 1990;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Furthermore, rumen fermentation generates methane, which contributes to global warming and represents 2-12% loss of feed energy for the animal <ns0:ref type='bibr' target='#b42'>(Johnson and Ward, 1996;</ns0:ref><ns0:ref type='bibr' target='#b12'>Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b39'>Jami et al., 2014)</ns0:ref>. Investigation of these microbial communities could improve our understanding of their function in fiber digestion and lead to practices that maximize the efficiency of ruminal fermentation and minimize greenhouse gas release <ns0:ref type='bibr' target='#b54'>(Lee et al., 2012)</ns0:ref>. Camels groups were fed different diets and reared in different locations. The diversity and relative abundance of microbial communities varied between camel groups, which was supported by the results of PCoA, LDA and PERMANOVA analyses. This result agrees with the results of other ruminants <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Camels in the present study were fed on different forages; Egyptian clover and wheat straw (Supplementary Table <ns0:ref type='table'>S1</ns0:ref>). Egyptian clover is the most balanced and nutritious fodder widely used for feeding camels <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr'>Bakheit, 2013;</ns0:ref><ns0:ref type='bibr' target='#b84'>Shrivastava et al., 2014)</ns0:ref>, which might supported the high microbial diversity in G2 camels compared to other groups (Table <ns0:ref type='table'>1</ns0:ref>). This was consistent with previous studies on cows <ns0:ref type='bibr' target='#b71'>(Pitta et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b83'>Shanks et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>. Highly degradable carbohydrates support bacterial and protozoal growth <ns0:ref type='bibr' target='#b18'>(Dijkstra and Tamminga, 1995;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>, which could demonstrate their higher population in G1 camels. Additionally, higher bacterial population slows the fungi growth <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992;</ns0:ref><ns0:ref type='bibr' target='#b66'>Orpin and Joblin, 1997)</ns0:ref>, which was illustrated by low fungal population in G1 camels.</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>Firmicutes phylum was more abundant than Bacteroidetes and both phyla comprised &gt; 75% of all bacterial reads (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>), which agrees with studies on camels <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>, Surti Buffalo <ns0:ref type='bibr' target='#b67'>(Pandya et al., 2010)</ns0:ref> and Muskoxen <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref>. The majority of Firmicutes' members have a potential role in fiber digestion, which might illustrate their higher population in G2 camels that were fed on high-quality forage and also in solid fraction. The high proportion of Ruminococcaceae and Lachnospiraceae supports this speculation <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b62'>Nathani et al., 2015)</ns0:ref>. Blautia and Acetitomaculum genera have a key role as reductive acetogens (Le <ns0:ref type='bibr'>Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b95'>Yang et al., 2016)</ns0:ref> and varied among the camel groups in this study. This suggests that manipulation of diet can enhance reductive acetogenesis in rumen and minimize methanogenesis (Le <ns0:ref type='bibr'>Van et al., 1998)</ns0:ref>. Bacteroidetes were higher in samples collected from animals reared in the station that used lowquality feed (G3), which was similar to results on cattle <ns0:ref type='bibr' target='#b69'>(Pitta et al., 2014b)</ns0:ref>. The phylum was dominated by family Prevotellaceae, which confirms <ns0:ref type='bibr' target='#b26'>Gharechahi et al. (2015)</ns0:ref>. Members of Bacteroidetes possess diverse enzymes that can target cellulose, pectin and soluble polysaccharides released in the liquid phase <ns0:ref type='bibr' target='#b59'>(Mackenzie et al., 2015)</ns0:ref>. Additionally, Prevotella genus produces propionate that is used for energy by the host <ns0:ref type='bibr' target='#b62'>(Nathani et al., 2015)</ns0:ref>. We speculate that Bacteroidetes species contribute to the adaptation of camels to arid conditions. The RC9_gut_group found in this study belongs to uncultured genera and was found also in the Rhinoceros hindgut <ns0:ref type='bibr' target='#b8'>(Bian et al., 2013)</ns0:ref>. Unclassified Bacteroidetes specialize in lignocellulose degradation <ns0:ref type='bibr' target='#b59'>(Mackenzie et al., 2015)</ns0:ref>, which could support their high proportion in G3 camels. Fibrobacteres was higher (3.1%) in this study compared to the other findings on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>; this phylum is the principal cellulolytic bacteria in the rumen <ns0:ref type='bibr' target='#b75'>(Ransom-Jones et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b62'>Nathani et al., 2015)</ns0:ref>, which might illustrate its higher relative abundance in solid fraction and in the rumen of G3 camels that fed on wheat straw (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). The members of Proteobacteria were lower in G2 and G3 camels that were fed on diet rich in fiber contents. These findings highlighted this phylum's function as a protein-degrading bacteria as it was reported by <ns0:ref type='bibr' target='#b57'>Liu et al. (2017)</ns0:ref>. The abundance of Treponema was higher in the solid fraction and in G3 camels (Figure <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>). Treponema is the dominant genus in Spirochaetes phylum and it is fiber-associated bacteria, which could indicate to its cellulytic and xylanolytic activities <ns0:ref type='bibr' target='#b35'>(Ishaq and Wright, 2012)</ns0:ref>.</ns0:p><ns0:p>The dominant bacterial genera in this study were Butyriovibrio, RFN8-YE57, Ruminococcus, Prevotella, Fibrobacter, Treponema and VadinHA. These genera were higher in the SF except RFN8-YE57 compared to the LF; this finding was consistent with a study on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>, and confirms that solid-attached microbes could play a major role in ruminal fiber digestion <ns0:ref type='bibr' target='#b40'>(Jewell et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b64'>Noel et al., 2017)</ns0:ref>. Most of Elusimicrobia in this study were uncultured; some members of this phylum were isolated from the termite's gut that degrades cellulose <ns0:ref type='bibr' target='#b32'>(Herlemann et al., 2009)</ns0:ref>. Therefore, we speculate that this phylum has a role in fiber digestion and that might illustrate their high proportion in G3 camels. Actinobacteria observed also in the rumen of moose and some members of this phylum have acetogenic activities <ns0:ref type='bibr' target='#b37'>(Ishaq et al., 2015)</ns0:ref>. Some members of Victivallis within Lentisphaerae phylum were involved in cellobiose degradation <ns0:ref type='bibr' target='#b97'>(Zoetendal et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Unclassified bacteria in our study (39% of total bacterial reads) were less than the percentage found in a study of Muskoxen (54%) <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref>. The presence of unclassified bacteria in the gut was commonly observed <ns0:ref type='bibr' target='#b27'>(Gruninger et al., 2016)</ns0:ref> and could be a result of the presence of new bacteria that ferment plant biomass <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref> or related to short reads were generated from RNA sequencing <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>Since some archaea produce CH 4 from H 2 and CO 2 , this phyla may control methane emission from ruminants <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010)</ns0:ref>. Additionally, acetate produced in fiber breakdown provides a methyl group for methanogenesis; therefore, alteration of diet shifts the structure of methanogen populations <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b88'>Tapio et al., 2017 )</ns0:ref>, which could demonstrate the variation in the relative abundance of archaea between camel groups. Camels of the second group (G2) that fed fresh clover, showed the highest archaeal population (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>) and archaeal community was dominated by Thermoplasmatales, a methylotrophic methanogens order (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>), which was consistent with the results on cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref> and camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. Thermoplasmatales produce methane from methyl amine and its population was decreased by the addition of rapeseed oil to animal diet, making it a high potential target in future strategies to mitigate methane emissions <ns0:ref type='bibr' target='#b72'>(Poulsen et al., 2013)</ns0:ref>. The Methanobrevibacter, Methanosphaera, Methanomicrobium and Methanobacterium (Table <ns0:ref type='table'>4</ns0:ref>) are the other dominant archaea in this study and in accordance with the results found in beef cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref>. Methanobrevibacter dominated the methanogens in other ruminant <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref> and was associated with high methane emissions <ns0:ref type='bibr' target='#b88'>(Tapio et al., 2017)</ns0:ref>. Moreover, Methanomicrobium was higher in the camels of G3 that were fed on poor quality forage, which was similar to results of buffalo <ns0:ref type='bibr' target='#b22'>(Franzolin and Wright, 2016)</ns0:ref>, and In vitro <ns0:ref type='bibr' target='#b90'>(Wang et al., 2018)</ns0:ref>. In rumen, Methanomicrobium converts H 2 and/or formate into CH 4 <ns0:ref type='bibr' target='#b52'>(Leahy et al., 2013)</ns0:ref>. The abundance of Thermoplasmatales was also negatively correlated with Methanobrevibacter, which is consistent with previous results <ns0:ref type='bibr' target='#b15'>(Danielsson et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b60'>McGovern et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>The majority of protozoal reads were classified as Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium and Epidinium (Table <ns0:ref type='table'>4</ns0:ref>). Similar findings were observed on different ruminants <ns0:ref type='bibr' target='#b4'>(Baraka, 2012)</ns0:ref>. Feed appeared to influence the relative abundance of protozoa, as reported previously for cattle <ns0:ref type='bibr' target='#b34'>(Hristov et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b91'>Weimer, 2015)</ns0:ref>; however, we cannot differentiate the effects of feed from facility. Diplodinium dominated protozoal community and was prevalent in G3 camels, which highlighted the cellulolytic activity of this genus <ns0:ref type='bibr' target='#b13'>(Coleman et al., 1976)</ns0:ref>. Some species of genus Diplodinium, such as Diplodinium cameli, were discovered in, and are unique to, the rumen of Egyptian camel <ns0:ref type='bibr' target='#b48'>(Kubesy and Dehority, 2002)</ns0:ref>. In addition, Entodinium was higher in G1 camels that were fed on concentrates feed mixture that increase the protozoa. Also, this genus predominates rumen of camels <ns0:ref type='bibr' target='#b82'>(Selim et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b25'>Ghali et al., 2005)</ns0:ref> and cattle <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012)</ns0:ref>. Moreover, <ns0:ref type='bibr' target='#b47'>Kittelmann and Janssen (2011)</ns0:ref> showed that the Polyplastron was the dominant genus in cattle. On the function level, all the genus Eudiplidinum, PeerJ reviewing PDF | (2019:12:44048:7:1:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Epidinum and Diplodinum have cellulolytic activity <ns0:ref type='bibr' target='#b13'>(Coleman et al., 1976)</ns0:ref>, whereas, Polyplastrone and Epidinium have a xylanolytic activity <ns0:ref type='bibr' target='#b17'>(Devillard, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>B&#233;ra-Maillet et al., 2005)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>The highest fungal population was observed in the solid fraction and rumen of G3 camels (Table <ns0:ref type='table'>1</ns0:ref>). These findings were in agreement with the results of studies stated that the fibre-based diets stimulated the fungal growth <ns0:ref type='bibr' target='#b65'>(Orpin, 1977;</ns0:ref><ns0:ref type='bibr' target='#b77'>Roger et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b29'>Haitjema et al., 2014)</ns0:ref>. This speculation could explain the low fungal population in G1 camels in our study. Moreover, the longer retention time and neutral pH in camel's forestomach <ns0:ref type='bibr' target='#b78'>(Russell and Wilson, 1996)</ns0:ref> make it more suitable for the survival of rumen fungi. Neocallimastix dominated the fungal community and was higher in the G1 camels, which was similar to other results on sheep and camels <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013</ns0:ref><ns0:ref type='bibr' target='#b74'>, Rabee et al., 2019)</ns0:ref>. This genus produces enzymes capable of hydrolyzing cellulose, xylan and starch <ns0:ref type='bibr' target='#b68'>(Pearce and Bauchop, 1985)</ns0:ref>. Cyllamyces that was observed in small population, has the ability to degrade poor-quality feeds <ns0:ref type='bibr' target='#b86'>(Sridhar et al., 2014)</ns0:ref>, which might explain its high population in solid fraction and G3 camels. Piromyces was the second dominant genus in the camel rumen of this study and produces cellulolytic and xylanolytic enzymes <ns0:ref type='bibr' target='#b89'>(Teunissen et al., 1992)</ns0:ref>. Therefore, the fungi were more prevalent in ruminants of G2 camels, which were fed high-quality forage with high fiber contents than in G1 and G3 camels. The genus Spizellomyces is closely related to Chytridiomctes <ns0:ref type='bibr' target='#b10'>(Bowman et al., 1992)</ns0:ref>, and common in grassland and crop soil <ns0:ref type='bibr' target='#b58'>(Lozupone and</ns0:ref><ns0:ref type='bibr'>Klein, 2002, Kittelmann et al., 2012)</ns0:ref>. Thus, contamination of the forages by soil could explain the presence of this fungus in the camel rumen.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between rumen microbes</ns0:head><ns0:p>Interactions between rumen microbes drive feed degradation and methane formation in the rumen, which influence the animal production and the environment <ns0:ref type='bibr' target='#b93'>(Williams et al., 1994;</ns0:ref><ns0:ref type='bibr' target='#b54'>Lee et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Positive and negative correlations were observed within and between microbial communities in this study (Fig. <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>). Methanogens colonize the protozoa and this relationship enhances methane formation <ns0:ref type='bibr' target='#b63'>(Newbold et al., 1995)</ns0:ref>, which highlighted some positive correlations between protozoa and archaea. Additionally, fibrolytic bacteria produce important substrates mainly hydrogen and methyl groups that methanogens use for growth <ns0:ref type='bibr' target='#b41'>(Johnson and Johnson, 1995)</ns0:ref>, which demonstrated positive correlations found between Fibrobacteres and some methanogens. Also, positive correlation between the methylotrophic Methanosphaera and Lachnospiraceae that has been implicated in pectin degradation and provides methanol as a substrate for the methylotrophs <ns0:ref type='bibr' target='#b16'>(Dehority, 1969)</ns0:ref>. On the other hand, Prevotella is a hydrogen utilizer and produces propionate that impact the methanogenesis in the rumen negatively <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>, which illustrates negative correlation between Prevotellaceae and archaea.</ns0:p><ns0:p>Since the rumen anaerobic fungi produce abundant H 2 through the fermentation of carbohydrate; they can interact positively with H 2 utilizers such as archaea, Prevotellaceae, Blautia and Acetitomaculum <ns0:ref type='bibr' target='#b66'>(Orpin and Joblin, 1997;</ns0:ref><ns0:ref type='bibr'>Le Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b95'>Yang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>. Additionally, anaerobic fungi penetrate plant tissue, which provides an increased surface area for bacterial colonization <ns0:ref type='bibr' target='#b66'>(Orpin and Joblin, 1997)</ns0:ref>, which could explain positive correlation between fungi and both Butyrivibrio and Fibrobacteres. However, fungi are negatively impacted by the presence of some bacteria and protozoa as the fungal zoospores are likely to be a prey for protozoa <ns0:ref type='bibr' target='#b61'>(Morgavi et al., 1994)</ns0:ref>, which demonstrated the negative correlation between both Neocallimastix and Piromyces with Diplodinium and Entodinium. Furthermore, Ruminococcus produces compounds that inhibit the growth of rumen fungi <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992)</ns0:ref>, which support the negative correlation between Neocallimastix and Ruminococcaceae. Polyplastron predates upon other protozoa like Epidinium, Eudiplodinium, Diplodinium, and Ostracodinium <ns0:ref type='bibr' target='#b19'>(Eadie, 1967)</ns0:ref>, which might explained the negative correlation between Polyplastron and other Protozoa.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>The microbial community in camel rumen was diverse and similar in composition between the camels. The majority of camel rumen microbes (bacteria, fungi, and protozoa) were fibrolytic or have a possible role in fiber digestion, which might illustrate the ability of camel to live in desert harsh conditions under poor feeds. Moreover, the structure of microbial community in rumen of camel found to be similar to other ruminants with a shown difference in the relative abundances. The present results should open new perspectives for further cultivation and isolation studies on the unclassified microorganisms found in the rumen of camels to classify them and assign their functions.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>The relative abundance of microbial groups Relative abundance (%) of bacterial phyla Manuscript to be reviewed Relative abundance (%) of archaeal orders and genera Manuscript to be reviewed Relative abundance (%) of fungal genera </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Comparison of relative abundance of genera of the microbiota in dromedary camel. bacterial (a), archaeal (b), protozoal (c) and fungi (d) in ruminal solid (SF) and liquid (LF) fractions of camels under different feeding systems.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3:Linear Discriminant analysis of microbial communities in the samples based on the relative abundance of genera of active bacteria (a), archaea (b), protozoa (c) and fungi i (d)in ruminal solid (SF), and liquid (LF) fractions of camels under three feeding systems, G1 (black dots), G2 (blue squares) and G3 (coral triangles).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Relative abundance (%) of bacterial phyla in the ruminal solid (SF) and liquid (LF) 7&#177;0.6 1.5&#177;0.3 0.4&#177;0.1 1.8&#177;0.4 Verrucomicrobia SF 0.3&#177;0.1 0.20&#177;0.1 0.6&#177;0.4 0.30&#177;0.1 Verrucomicrobia LF 2.2&#177;0.4 1&#177;0.3 1.3&#177;0.3 1.3&#177;0.3</ns0:figDesc><ns0:table><ns0:row><ns0:cell>fractions of camels fed a mixed ration(G1), high-quality forage(G2) and low-quality forage</ns0:cell></ns0:row><ns0:row><ns0:cell>(G3) (Mean &#177; Standard Error (SE)).</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:12:44048:7:1:NEW 14 Aug 2020)Manuscript to be reviewed a The value was calculated from one animal.PeerJ reviewing PDF | (2019:12:44048:7:1:NEW 14 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Relative abundance (%) of archaeal orders and genera observed in the ruminal solid (SF), and liquid (LF) fractions of camels under different feeding systems. Animals in G1 fed a mixed ration, animal in G2 fed high-quality forage and animal in G3 fed low qualityforage (Mean &#177; Standard Error (SE)).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Protozoa</ns0:cell><ns0:cell>G1</ns0:cell><ns0:cell>G2</ns0:cell><ns0:cell>G3</ns0:cell><ns0:cell>Overall mean</ns0:cell></ns0:row><ns0:row><ns0:cell>Entodinium SF</ns0:cell><ns0:cell>23&#177;6</ns0:cell><ns0:cell>6.5&#177;0.6</ns0:cell><ns0:cell>6&#177;1</ns0:cell><ns0:cell>11&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell>Entodinium LF</ns0:cell><ns0:cell>54&#177;10</ns0:cell><ns0:cell>15&#177;2.5</ns0:cell><ns0:cell>5&#177;1</ns0:cell><ns0:cell>24&#177;6</ns0:cell></ns0:row><ns0:row><ns0:cell>Polyplastron S F</ns0:cell><ns0:cell>10&#177;1</ns0:cell><ns0:cell>17.5&#177;2</ns0:cell><ns0:cell>25&#177;3</ns0:cell><ns0:cell>17&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Polyplastron LF</ns0:cell><ns0:cell>6&#177;1</ns0:cell><ns0:cell>11&#177;0.2</ns0:cell><ns0:cell>24&#177;3</ns0:cell><ns0:cell>12&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Diplodinium S F</ns0:cell><ns0:cell>23&#177;1</ns0:cell><ns0:cell>35&#177;3</ns0:cell><ns0:cell>49&#177;10</ns0:cell><ns0:cell>34&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell>Diplodinium LF</ns0:cell><ns0:cell>13&#177;3</ns0:cell><ns0:cell>27&#177;3</ns0:cell><ns0:cell>61&#177;6</ns0:cell><ns0:cell>29&#177;5</ns0:cell></ns0:row><ns0:row><ns0:cell>Eudiplodinium SF</ns0:cell><ns0:cell>8&#177;0.6</ns0:cell><ns0:cell>8&#177;2</ns0:cell><ns0:cell>2&#177;0.7</ns0:cell><ns0:cell>7&#177;1</ns0:cell></ns0:row><ns0:row><ns0:cell>Eudiplodinium LF</ns0:cell><ns0:cell>4&#177;1</ns0:cell><ns0:cell>5.5&#177;1</ns0:cell><ns0:cell>2.5&#177;0.5</ns0:cell><ns0:cell>4.5&#177;0.6</ns0:cell></ns0:row><ns0:row><ns0:cell>Epidinium SF</ns0:cell><ns0:cell>5&#177;0.8</ns0:cell><ns0:cell>4&#177;1</ns0:cell><ns0:cell>2&#177;1</ns0:cell><ns0:cell>4&#177;0.1</ns0:cell></ns0:row><ns0:row><ns0:cell>Epidinium LF</ns0:cell><ns0:cell>3&#177;0.8</ns0:cell><ns0:cell>4.5&#177;0.6</ns0:cell><ns0:cell>1&#177;0.7</ns0:cell><ns0:cell>3.5&#177;0.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Ophryoscolex SF</ns0:cell><ns0:cell>30&#177;4</ns0:cell><ns0:cell>27&#177;3</ns0:cell><ns0:cell>15&#177;5</ns0:cell><ns0:cell>26&#177;2.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Ophryoscolex LF</ns0:cell><ns0:cell>19&#177;4</ns0:cell><ns0:cell>29&#177;0.6</ns0:cell><ns0:cell>6.5&#177;4</ns0:cell><ns0:cell>22&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Trichostomatia SF 0.1&#177;0.02</ns0:cell><ns0:cell>1&#177;0.25</ns0:cell><ns0:cell>0.3&#177;0.15</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Trichostomatia LF 0.2&#177;0.04</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell><ns0:cell>1&#177;0.1</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell></ns0:row><ns0:row><ns0:cell>Isotricha SF</ns0:cell><ns0:cell cols='3'>0.2&#177;0.04 0.3&#177;0.05 0.3&#177;0.004</ns0:cell><ns0:cell>0.3&#177;0.03</ns0:cell></ns0:row><ns0:row><ns0:cell>Isotricha LF</ns0:cell><ns0:cell>0.5&#177;0.2</ns0:cell><ns0:cell>2&#177;0.9</ns0:cell><ns0:cell>0.3&#177;0.01</ns0:cell><ns0:cell>1&#177;0.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Dasytricha SF</ns0:cell><ns0:cell cols='3'>0.04&#177;0.01 1.5&#177;0.3 0.2&#177;0.15</ns0:cell><ns0:cell>1&#177;0.3</ns0:cell></ns0:row><ns0:row><ns0:cell>Dasytricha LF</ns0:cell><ns0:cell cols='2'>0.1&#177;0.002 5.5&#177;0.8</ns0:cell><ns0:cell>0.5&#177;0.3</ns0:cell><ns0:cell>3&#177;1</ns0:cell></ns0:row></ns0:table><ns0:note>2PeerJ reviewing PDF | (2019:12:44048:7:1:NEW 14 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 5 :</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Relative abundance (%) of fungal genera in the ruminal solid (SF) and liquid fraction (LF) of camels under different feeding systems. Camels in G1 fed a mixed ration, animals in G2 fed high-quality forage, and animals in G3 fed low-quality forage (Mean &#177; SE).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Fungi</ns0:cell><ns0:cell>G1</ns0:cell><ns0:cell>G2</ns0:cell><ns0:cell>G3</ns0:cell><ns0:cell>Overall mean</ns0:cell></ns0:row><ns0:row><ns0:cell>Spizellomyces SF</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0.1</ns0:cell><ns0:cell>0.02</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>Spizellomyces LF 0.3 &#177; 0.1 0.3 &#177; 0.1</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces SF</ns0:cell><ns0:cell>2&#177; 0.6</ns0:cell><ns0:cell>3&#177; 1.5</ns0:cell><ns0:cell>7&#177; 4</ns0:cell><ns0:cell>3.5&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces LF</ns0:cell><ns0:cell>2&#177; 0.8</ns0:cell><ns0:cell cols='2'>3&#177; 0.8 10&#177; 1</ns0:cell><ns0:cell>4&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces SF</ns0:cell><ns0:cell>6&#177; 3</ns0:cell><ns0:cell cols='2'>12&#177; 0.7 8&#177; 1</ns0:cell><ns0:cell>9&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces LF</ns0:cell><ns0:cell>6&#177;4</ns0:cell><ns0:cell>12&#177;2</ns0:cell><ns0:cell>10&#177;6</ns0:cell><ns0:cell>10&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix SF</ns0:cell><ns0:cell>92&#177;3</ns0:cell><ns0:cell>85&#177;1</ns0:cell><ns0:cell>85&#177;3</ns0:cell><ns0:cell>87&#177;1</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix LF</ns0:cell><ns0:cell>92&#177;4</ns0:cell><ns0:cell cols='2'>85&#177;1.5 81&#177;7</ns0:cell><ns0:cell>86&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>ND: Non Determined</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:12:44048:7:1:NEW 14 Aug 2020) Manuscript to be reviewed PeerJ reviewing PDF | (2019:12:44048:7:1:NEW 14 Aug 2020)</ns0:note></ns0:figure> </ns0:body> "

" Desert Research Center 4th August, 2020 1Mathaf El Matariya St.B.O.P.11753 Matariya- Cairo,Egypt Phone: (+202)26332846 - 26374800 FAX: (+202) 26357858 Email:[email protected] Dear Editor, Its our pleasure to submit our responses to the comments of 7th round of revision. Thank you for your comments, we responded to all comments and enclosed unclean paper including all comments colored by yellow. We eager to hear your final decision on this manuscript. We appreciate the opportunity to submit our manuscript to Peer J. Yours sincerely, Dr. Alaa Rabee Researcher at Desert Research Center, Egypt On behalf of all authors Comments Manuscript title: “Comparative analysis of the metabolically active microbial communities in the rumen of dromedary camels under different feeding systems using total rRNA sequencing ” Editor’s comments Line 42. Delete “reared under three feeding systems” >> Deleted. Line 44. Add space before “Bacteria” and “Camels (line 287)” >>Added. Line 116. Revise to “…animals were kept on these diets..” >> Modified. Line 200. The statement “All Bacterial genera were observed,” suggests you observed all known bacterial genera, which doesn’t seem likely. Provide the total number of genera and revise to “Of the ___ genera observer, only seven were observed exclusively in libraries generated from a specific facility.” >> Modified. Line 278. Delete “the”. >> Deleted. Line 281. Replace “Therefore, investigation of these microbial communities is the key to understand their roles and maximize ruminal fermentation and fiber digestion and reduction of greenhouse gas” with “Investigation of these microbial communities could improve our understanding of their function in fiber digestion and lead to practices that maximize the efficiency of ruminal fermentation and minimize greenhouse gas release.” >> Modified. Line 299. Replace “is in agreement with” with “agrees with” >>Replaced. Line 303. Avoid the passive voice. Replace “This speculation was supported by the high proportion of Ruminococcaceae and Lachnospiraceae…” with “The high proportion of Ruminococcaceae and Lachnospiraceae supports this speculation.” >> Replaced. Line 304. Delete “Bothe” >>Deleted. Line 307. Replace “This finding could indicate that the reductive acetogenesis pathway could be maximized by diet to minimize methane...” With “This suggests that manipulation of diet can enhance reductive acetogenesis in rumen and minimize methanogenesis…” >> Modified. Line 345. Replace “The archaeal population has important roles in methane emission mitigation strategies as they convert the H2 and CO2 produced in the rumen to methane.” With “Since some archaea produce CH4 from H2 and CO2, this phyla may control methane emission from ruminants.” >> Modified. Line 367. Replace “were related to” with “were classified as” >> Modified. Line 369. Here and throughout, write actively. Replace “The relative abundance of protozoal was influenced by feeding system and housing facility, which was in the same line with results on cattle” with “Feed appeared to influence the relative abundance of protozoa, as reported previously for cattle (Hristov et al., 2001; Weimer, 2015); however, we cannot differentiate the effects of feed from facility.” >> Revised. Line 371. Here and throughout, avoid superfluous determiners. Delete “The” >>Revised. Line 374. Here and throughout, delete phrases like “is considered to be,” unless you doubt that fact. Replace with such as Diplodinium cameli (Kubesy and Dehority, 2002) “some species of genus Diplodinium, such as Diplodinium cameli, were discovered in, and are unique to, the rumen of Egyptian camel.” >> Revised. Line 388. Delete “This genus” >> Deleted Line 508. Delete “Available at: http://livestocklibrary.com.au/handle/1234/20056. Accessed June 8, 2020” >> Deleted Line 533. Volume is 2010. >>Modified Line 667. Page number is e000066 >> Modified. Table 1, 2, and 5. Be consistent with significant figures. >> Modified. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Breakdown of plant biomass in rumen depends on interactions between bacteria, archaea, fungi, and protozoa; however, the majority of studies of the microbiome of ruminants, including the few studies of the rumen of camels, only studied one of these microbial groups. In this study, we applied total rRNA sequencing to identify active microbial communities in twenty-two solid and liquid rumen samples from eleven camels. These camels were reared at three stations that use different feeding systems: clover, hay and wheat straw (G1), fresh clover (G2), and wheat straw (G3). Bacteria dominated the libraries of sequence reads generated from all rumen samples, followed by protozoa, archaea, and fungi respectively. Firmicutes, Thermoplasmatales, Diplodinium, and Neocallimastix dominated bacterial, archaeal, protozoal and fungal communities, respectively in all samples. Libraries generated from camels reared at facility G2, where they were fed fresh clover, showed the highest alpha diversity. Principal co-ordinate analysis and linear discriminate analysis showed clusters associated with facility/feed and the relative abundance of microbes varied between liquid and solid fractions. This provides preliminary evidence that bacteria dominate the microbial communities of the camel rumen and these communities varies between populations of domesticated camels.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Camels (Camelus dromedaries) can produce milk and meat in hot, arid and semi-arid regions and can provide food security as the climate warms <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b21'>Faye, 2013)</ns0:ref>. Camels also provide textiles (fiber and hair) and are commonly used for transportation, agriculture, tourism, race and riding <ns0:ref type='bibr' target='#b74'>(Rabee et al., 2019)</ns0:ref>. The unique feeding behavior and the functional structure of digestive tract of these pseudo-ruminants is well adapted to deserts <ns0:ref type='bibr' target='#b44'>(Kay et al., 1989)</ns0:ref>. The retention time of feed particles in the camel forestomach is longer than other true ruminants, which prolongs the exposure of plant biomasses to the symbiotic microorganisms. This long retention improves the efficiency of digestion <ns0:ref type='bibr'>(Lechner-Dolland and Engelhardt, 1989)</ns0:ref>. The feed ranchers provide camels, which ranges from forage in traditional pastures to concentrated supplements in intensive feedlots, influences the structure of the camel microbiome <ns0:ref type='bibr' target='#b21'>(Faye, 2013;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al. 2015)</ns0:ref>. The chemical composition of diet shapes fermentation in rumen. For instance, cellulolytic and hemicellulytic diets favor the fibrolytic microorganisms; while, starch and sugars favor the amylolytic <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012)</ns0:ref>. Also, the microbial composition and diversity varies between liquid and solid rumen fractions, which might indicate different roles in rumen fermentation; for instance, plant-adherent microbiota might have a major role in fiber degradation <ns0:ref type='bibr' target='#b76'>(Ren et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Digestion in the camels depends on microbial fermentation in rumen <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref> and the efficiency of this microbial fermentations is based on the interactions between a wide variety of microbial groups, including bacteria, archaea, fungi and protozoa <ns0:ref type='bibr' target='#b94'>(Yanagita et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra, 2005)</ns0:ref>. Analysis of these microbial communities could lead to increases in animal productivity and reduction of greenhouse gas emissions <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Unlike other ruminants, camels can utilize thorny and low quality plants like shrubs with high lignocelulolytic content <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>. Consequently, camel rumen microbes must have the capacity to degrade such poor-quality feeds <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. However, the microbial community in the rumen of dromedary camel received less attention than other domesticated ruminants. Recent development of next generation sequencing technologies provide a rapid method of microbial identification in rumen and overcome the intrinsic constraints of traditional culturebased methods <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b36'>Ishaq and Wright, 2014)</ns0:ref>. Most of assessments of microbial groups in the rumen have relied on amplicon sequencing, which target a specific variable region on 16S rRNA gene <ns0:ref type='bibr' target='#b56'>(Li et al. 2016)</ns0:ref>. This approach needs a wide range of primers to study different microbial communities <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013)</ns0:ref>. Therefore, Primer selection and amplification conditions could bias the output <ns0:ref type='bibr' target='#b28'>(Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b20'>Elekwachi et al., 2017)</ns0:ref>. Total RNA sequencing (RNA-Seq) offers the advantage of specifically targeting active microbes and avoids biases associated with primer selection and chimera generation in PCR <ns0:ref type='bibr' target='#b24'>(Gaidos et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b28'>Guo et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b56'>Li et al., 2016)</ns0:ref>. In addition, RNA-Seq approach is capable of identifying novel microbes as it is not reliant on primers for known microbes <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>. Highthroughput metatranscriptomic sequencing provides a comprehensive understanding of biological systems by characterization of different groups of organisms in the same environment based on the sequencing of coding and noncoding RNA <ns0:ref type='bibr' target='#b20'>(Elekwachi et al., 2017)</ns0:ref>. Total RNA-Seq was applied to investigate microbial communities in many different systems including, for example, human gut <ns0:ref type='bibr' target='#b73'>(Qin et al., 2012)</ns0:ref>, and cow rumen <ns0:ref type='bibr' target='#b56'>(Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b20'>Elekwachi et al., 2017 )</ns0:ref>.</ns0:p><ns0:p>Previous microbiome studies on camel rumen have characterized one or two microbial groups using classical or molecular approaches. For example, the protozoal community in camel rumen was studied heavily by conventional microscopic methods <ns0:ref type='bibr' target='#b25'>(Ghali et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b4'>Baraka, 2012)</ns0:ref>. Regarding the anaerobic fungi, a new fungal genus, Oontomyces was isolated from the rumen of Indian camel <ns0:ref type='bibr' target='#b14'>(Dagar et al., 2015)</ns0:ref>, and only one study investigated whole fungal community in the gut of camel <ns0:ref type='bibr' target='#b74'>(Rabee et al., 2019)</ns0:ref>. Only three molecular-based studies are available on the bacterial community <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b7'>Bhatt et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b26'>Gharechahi et al., 2015)</ns0:ref>. Furthermore, only one study classified rumen archaea <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. In the present study, total rRNA sequencing was applied to 1) get insight into the composition of active microbiota in the rumen of camels; 2) describe the distribution of microbial groups among solid and liquid rumen fractions; 3) assessing the heterogeneity of these microbial populations within different populations of domestic camels.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Rumen samples</ns0:head><ns0:p>Rumen samples were collected from eleven adult dromedary camels reared at three stations that use different feeding systems. Camels in group G1 (n=3) were housed in the Maryout Research Station, Alexendria, Egypt and were fed on Egyptian clover hay (Trifolium alexandrinum), wheat straw and concentrates feed mixture. Camels in group G2 (n=6) were housed at the commercial farm in the Kom Hammada and fed on fresh Egyptian clover (100 % high-quality forage diet) then slaughtered in the Kom Hammada slaughterhouse, Elbehera, Egypt. Camels of group G3 (n=2) were housed at the commercial farm in Cairo area and fed on wheat straw (100 % low-quality forage diet) then were slaughtered in Pasateen slaughterhouse, Cairo, Egypt. Animals were kept on these diets for at least one month before the sampling time. The proximate analysis of feeds is illustrated in Supplementary table <ns0:ref type='table'>S1</ns0:ref>. Details regarding camel rumen samples in this study presented in Supplementary table <ns0:ref type='table' target='#tab_2'>S2</ns0:ref>. Rumen contents were strained immediately by two layers cheesecloth to separate the liquid and solid to form twenty-two samples, frozen using liquid nitrogen and stored at -80 o C before further processing <ns0:ref type='bibr' target='#b20'>(Elekwachi et al., 2017)</ns0:ref>. The project was approved and all samples were collected according to the Institutional Animal Care and Use Committee, Faculty of Veterinary Medicine, University of Sadat City, Egypt (Approval number: VUSC00003).</ns0:p></ns0:div> <ns0:div><ns0:head>RNA isolation, quality and quantity estimation and sequencing</ns0:head><ns0:p>The frozen rumen samples were ground using liquid nitrogen. About 0.5 gram of frozen fine powder was used for total RNA isolation using Trizol-Reagent protocol (Invitrogen, Carlsbad, CA), followed by RNA clean up using MEGA clear Kit (Invitrogen). Total RNA quality and quantity were estimated using an Agilent 2100 bioanalyzer (Agilent Technologies, USA) and RNA 6000 Nano kit (Agilent Technologies, USA). One hundred nanogram of total RNA was reversetranscribed into first strand cDNA and sequenced using Illumina rRNA MiSeq preparation kit (Illumina, USA) by Illumina MiSeq platform.</ns0:p></ns0:div> <ns0:div><ns0:head>Bioinformatic data analysis</ns0:head><ns0:p>The generated RNA sequence reads were analysed using pipeline developed by <ns0:ref type='bibr' target='#b20'>Elekwachi et al. (2017)</ns0:ref>. Briefly, the sequence quality was checked using the FastQC program v. 0.11.4 <ns0:ref type='bibr' target='#b0'>(Andrews, 2010)</ns0:ref>, then Trimmomatic program v. 0.35 <ns0:ref type='bibr' target='#b9'>(Bolger et al., 2014)</ns0:ref> was used to trim adaptors, barcodes, ambiguous and low quality reads. PEAR program v. 0.9.6 <ns0:ref type='bibr' target='#b96'>(Zhang et al., 2014)</ns0:ref> was used to merge read 1 and read 2 using default options. Then after, the hidden Markov models rRNA-HMM tool of the rapid analysis of multiple metagenomes with a clustering and annotation pipeline (RAMMCAP) <ns0:ref type='bibr' target='#b55'>(Li, 2009)</ns0:ref> was used to sort the reads into archaea and bacteria (16S, 23S), and eukaryote (18S, 23S) rRNA sequences. Merged sequence files were then sub-sampled as needed using <ns0:ref type='bibr'>MEME program v. 4.10.2 (Bailey et al., 2009)</ns0:ref>. For each sample, 70,000 reads were run through the pipeline. For subsequent analysis steps, 20 000, 10 000, and 2000 sequences were used for bacteria, eukaryote and archaea, respectively. Taxonomy binning for eukaryote and archaeal SSU rRNA sequences was performed using BLASTN. The sub-sampled query sequences were searched against the SILVA SSURef-111 database using an e-value of 1e -5 . Bacterial SSU sequences were binned into operational taxonomic units (OTUs) using the 'classify. seqs' command of Mothur v. 1.33.1 program <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref>. The SSURef -108 gene and the SSURef-108b taxonomy databases were used. Principal co-ordinate analysis (PCoA) using Bray Curtis dissimilarity and alpha diversity indices (Chao1, Shannon and Inverse Simpson) were evaluated by Mothur <ns0:ref type='bibr' target='#b81'>(Schloss et al., 2009)</ns0:ref> based on sub-sampling of 70,000 reads per sample according the protocol 'Community Structure Analysis Based on OTU Clustering' outlined in <ns0:ref type='bibr' target='#b20'>Elekwachi et al. (2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>Data of relative abundance of bacterial phyla, protozoal genera, fungal genera and archaea genera and order Thermoplasmatales were tested for normality and homogeneity using Shapiro-Wilk test and variables that were deemed non-normal were then arcsine transformed. Linear Discriminate Analysis (LDA) and Bray Curtis Permutational Multivariate Analysis of Variance (PERMANOVA) tests depended on the relative abundance of bacterial phyla. All the protozoal, fungal and archaeal genera and the order Thermoplasmatales were used to show the differences in community structure and to compare the clustering of samples. Pearson correlation analysis was used to identify correlation within and between microbial communities and the correlation scores were visualized as a heatmap. The statistical analyses were performed using the SPSS v. 20.0 software package (SPSS, 1999) and PAST <ns0:ref type='bibr' target='#b30'>(Hammer et al., 2001)</ns0:ref>. Sequences were deposited to the sequence read archive (SRA) under the accession number: SRP107370.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>The composition and diversity of active microbial community</ns0:head><ns0:p>Total rRNA sequencing in twenty-two solid and liquid rumen samples from eleven camels resulted in a total of 3958591 reads with average of 359872 &#177; 85366 (mean &#177; standard error (SE)) reads per animal in the solid fraction (SF) and 3386392 reads with an average of 307854 &#177; 60989 reads per animal in the liquid fraction (LF). The sequence reads of bacteria dominated the active microbial community, followed by protozoa, archaea and fungi (Table <ns0:ref type='table'>1</ns0:ref>). Relative abundance of protozoa was higher in LF-G1 (liquid fraction of G1), while relative abundance of bacteria was higher in SF-G1 (solid fraction of G1). The highest population of archaea was observed in G2 camels. Additionally, G3 camels showed the highest relative abundance of fungi (Table <ns0:ref type='table'>1</ns0:ref>; Supplementary Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). Number of OTUs and Alpha-diversity indices, Chao1, Shannon and Inverse Simpson, were higher in the rumen of LF-G2 samples (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>The composition of bacterial community varied little between groups and consisted of 12 phyla. The five most predominant phyla were Firmicutes, Bacteroidetes, Proteobacteria, Spirochaetes and Fibrobacteres, respectively (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Firmicutes dominated the bacterial community in all groups and was higher in G2 followed by G1 and G3 camels, respectively, and was also higher in SF compared to LF (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). At the family level, Lachnospiraceae and Ruminococcuceae dominated the Firmicutes. In addition, six genera dominated this phylum, including Butyrivibrio, RFN8-YE57, Ruminococcus, vadinHA42, Acetitomaculum and Blautia (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). The second largest phylum, Bacteroidetes, showed the highest relative abundance in G3 followed by G1 and G2 camels and was higher in LF than SF (Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref> and Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). At the family level, Prevotellaceae, BS11_ gut_ group, and Rikenellaceae dominated the Bacteroidetes; and at the genus level, Prevotella, RC9_gut_group dominated the Bacteroidetes. Proteobacteria, phylum showed a higher relative abundance in LF-G1 samples and was dominated by Succinivibrionaceae family and Desulfovibrio genus (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). The Spirochaetes phylum was higher in the SF-G3 and it was classified into two families including Spirochaetaceae and PL-11B10 and was dominated by Treponema genus. Fibrobacteres phylum was higher in SF-G3 (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>, Supplementary Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>). Actinobacteria were higher in SF-G2 samples, Tenricutes phylum was higher in LF-G1 samples and Lentisphaerae phylum, was about 3-fold higher in LF as relative to SF and accounted for a large population in the camels of G3 (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Additionally, several minor bacterial phyla were also observed in the rumen of camels such as Verrucomicrobia, Elusimicrobia, Cyanobacteria and Chloroflexi (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>).</ns0:p><ns0:p>Of the 74 genera observed, only seven were observed exclusively in libraries generated from a specific facility, including uncultured Marinilabiaceae (Bacteroidetes), Quinella (Firmicutes) and Streptococcus (Firmicutes) that were observed only in G2 and G3 camels. Ruminobacter (Proteobacteria) was observed only in G1 and G2 camels. On the other hand, Arcobacter and Succinivibrio within phylum Proteobacteria were observed only in G1 camels and Betaproteobacteria (Proteobacteria) was observed only in G3 camels. Moreover, many unclassified bacteria were observed across samples and accounted for 39% of total bacterial reads. Most of these unclassified bacterial reads were observed in phylum Firmicutes and Bacteroidetes.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>Reads that classified as archaea were further classified to three orders within the phylum Euryacheota: Thermoplasmatales, Methanobacteriale and Methanomicrobial. Thermoplasmatales dominated the archaeal community and showed the highest population in LF-G3 samples, this order was not classified out of order level (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>). Reads that classified in the Methanobacteriale were further classified to family Methanobacteriacea that includes three genera: Methanobrevibacter, Methanophera and Methanobacterium. Methanobrevibacter is the second largest contributor in archaeal population and was higher in SF-G1 samples. Methanosphaera exhibited higher relative abundance in SF-G2 samples. Methanobacterium was absent in G3 camels; however, a small proportion of this genus was found in the camels of G1 and G2. Methanomicrobium genus, which belongs to order Methanomicrobiales and family Methanomicrobiaceae was the least contributor in archaeal population and was more prevalent in LF-G3 samples (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1b</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>Reads that classified as protozoa were further classified to two families: Ophryoscolecidae and Isotrichidae (Table <ns0:ref type='table'>4</ns0:ref>). Reads that classified in the Ophryoscolecidae were further classified to seven genera, Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium, Epidinium and Trichostomatia. Reads that classified in the Isotrichidae were further classified to two genera, Dasytricha and Isotricha. The variation among the camels in protozoal population was clearly observed and seemed to be higher than other microbial communities; however, the protozoal community composition was similar among the camels (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>). The most dominant protozoal genera were Diplodinium, Ophryoscolex and Entodinium. Camels in G1 had the highest population of Entodinium and Epidinium. Camels in G2 had the greatest population of Eudiplodinium, Ophryoscolex, Isotricha and Dasytricha and camels in G3 had the greatest population of Diplodinium, Polyplastron and Trichostomatia. On the sample fraction level, solid fraction had a higher representation of Ophryoscolex, Polyplastron, Eudiplodinium, Epidinium and Diplodinium, while liquid fraction had a higher representation of Entodinium, Isotricha and Dasytricha (Table <ns0:ref type='table'>4</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>Reads that classified as rumen fungi were further classified to two phyla: Neocallimastigomycota and Chytridiomycota. Reads that classified in the Neocallimastigomycota were further classified to family Neocallimasticeceae that includes three genera, Neocallimastix, Piromyces and Cyllamyces. Neocallimastix dominated the fungal community, followed by Piromyces and Cyllamyces (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>). These anaerobic fungal genera represented &gt; 99.5 % of the fungal population. In addition, reads that classified in the Chytridiomycota were further classified to family Spizellomycetaceae that includes genus Spizellomyces, which was noted in a very small proportion (&lt; 0.5 %) (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>). Neocallimastix was more abundant in the SF-G1 samples while Piromyces and Cyllamyces were more abundant in LF-G2 and SF-G3 respectively (Table <ns0:ref type='table' target='#tab_5'>5</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_0'>1d</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Effect of feeding system and facility on the composition of microbial communities</ns0:head><ns0:p>Multivariate analysis separated libraries by feeding system and housing facility distinctly (Figs. <ns0:ref type='figure' target='#fig_3'>2 and 3</ns0:ref>). Also, bacteria, dominated by Firmicutes, drove differences between animals (Fig. <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>). Furthermore, Entodinium, Thermoplasmatales, Neocallimastix drove differences in protozoal, archaeal and fungal communities, respectively. PERMANOVA analysis revealed that the difference between camel groups was significant (P &lt; 0.01) in all microbial groups (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Pairwise comparison between camel groups based on Bonferronicorrected p-value demonstrated that the difference was significant (P &lt; 0.05) between camels of G2 and G3 in bacterial and archaeal communities (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>). Moreover, the difference was significant between the three groups in the protozoal community (P &lt; 0.05), whereas, in the fungal community, the difference was significant only between camels in group G1 and G2 (Supplementary Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Pearson correlation between microbes in the rumen of dromedary camel</ns0:head><ns0:p>Pearson correlation analysis (Fig. <ns0:ref type='figure' target='#fig_4'>4A, 4B</ns0:ref>), revealed many significant positive and negative correlations (P &lt; 0.05). For example, in active bacteria, Bacteroidetes correlated positively with Cyllamyces and negatively with Butyrivibrio, Methanosphaera and Trichostomatia. Prevotellaceae correlated positively with Neocallimastix and Entodinium and negatively with Ruminococcaceae, Methanosphaera and Diplodinium. Fibrobacteres correlated positively with Cyllamyces, Methanomicrobium, Thermoplasmatales and Diplodinium and negatively with Methanosphaera, Epidinium, Ruminococcaceae and Butyrivibrio. Firmicutes correlated positively with Methanosphaera and negatively with Piromyces, Thermoplasmatales and Methanomicrobium.</ns0:p><ns0:p>In active archaea, Thermoplasmatales correlated positively with Diplodinium and negatively with Methanobrevibacter and Methanosphaera. In active protozoa, there was a negative correlation between Polyplastron, Entodinium, Ophryoscolex and Epidinium. In active fungi, a negative correlation was observed between Cyllamyces, Neocallimastix and Piromyces and between Piromyces and Entodinium.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Rumen microbes can ferment a wide variety of feed components, including cellulose, xylan, amylose and protein and produce volatile fatty acids that provide the animal with approximately 70% of daily energy requirements <ns0:ref type='bibr' target='#b5'>(Bergman, 1990;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Furthermore, rumen fermentation generates methane, which contributes to global warming and represents 2-12% loss of feed energy for the animal <ns0:ref type='bibr' target='#b42'>(Johnson and Ward, 1996;</ns0:ref><ns0:ref type='bibr' target='#b12'>Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b39'>Jami et al., 2014)</ns0:ref>. Investigation of these microbial communities could improve our understanding of their function in fiber digestion and lead to practices that maximize the efficiency of ruminal fermentation and minimize greenhouse gas release <ns0:ref type='bibr' target='#b54'>(Lee et al., 2012)</ns0:ref>. In this study, camel groups were fed different diets and reared in different locations. The diversity and relative abundance of microbial communities varied between camel groups, which was supported by the results of PCoA, LDA and PERMANOVA analyses. This result agrees with the results of studies of other ruminants <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref>. Camels in the present study were fed on different forages; Egyptian clover and wheat straw (Supplementary Table <ns0:ref type='table'>S1</ns0:ref>). Egyptian clover is the most balanced and nutritious fodder widely used for feeding camels <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012;</ns0:ref><ns0:ref type='bibr'>Bakheit, 2013;</ns0:ref><ns0:ref type='bibr' target='#b84'>Shrivastava et al., 2014)</ns0:ref>, which might supported the high microbial diversity in G2 camels compared to other groups (Table <ns0:ref type='table'>1</ns0:ref>). This was consistent with previous studies on cows <ns0:ref type='bibr' target='#b71'>(Pitta et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b83'>Shanks et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>. Highly degradable carbohydrates support bacterial and protozoal growth <ns0:ref type='bibr' target='#b18'>(Dijkstra and Tamminga, 1995;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kumar et al., 2015)</ns0:ref>, which could demonstrate their higher population in G1 camels. Additionally, higher bacterial population slows the fungi growth <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992;</ns0:ref><ns0:ref type='bibr' target='#b66'>Orpin and Joblin, 1997)</ns0:ref>, which was illustrated by low fungal population in G1 camels.</ns0:p></ns0:div> <ns0:div><ns0:head>Bacterial community</ns0:head><ns0:p>Firmicutes phylum was more abundant than Bacteroidetes and both phyla comprised &gt; 75% of all bacterial reads (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>), which agrees with studies on camels <ns0:ref type='bibr' target='#b80'>(Samsudin et al., 2011)</ns0:ref>, Surti Buffalo <ns0:ref type='bibr' target='#b67'>(Pandya et al., 2010)</ns0:ref> and muskoxen <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref>. The majority of Firmicutes' members have a potential role in fiber digestion, which might illustrate their higher population in G2 camels that were fed on high-quality forage and also in solid fraction. The high proportion of Ruminococcaceae and Lachnospiraceae supports this speculation <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b62'>Nathani et al., 2015)</ns0:ref>. Blautia and Acetitomaculum genera have a key role as reductive acetogens (Le <ns0:ref type='bibr'>Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b95'>Yang et al., 2016)</ns0:ref> and varied among the camel groups in this study. This supports the observation that manipulation of diet can enhance reductive acetogenesis in rumen and minimize methanogenesis (Le <ns0:ref type='bibr'>Van et al., 1998)</ns0:ref>. Bacteroidetes were higher in samples collected from animals reared in the station that used lowquality feed (G3), which was similar to results on cattle <ns0:ref type='bibr' target='#b69'>(Pitta et al., 2014b)</ns0:ref>. The phylum was dominated by family Prevotellaceae, which confirms <ns0:ref type='bibr' target='#b26'>Gharechahi et al. (2015)</ns0:ref>. Members of Bacteroidetes possess diverse enzymes that can target cellulose, pectin and soluble polysaccharides released in the liquid phase <ns0:ref type='bibr' target='#b59'>(Mackenzie et al., 2015)</ns0:ref>. Additionally, Prevotella genus produces propionate that is used for energy by the host <ns0:ref type='bibr' target='#b62'>(Nathani et al., 2015)</ns0:ref>. We speculate that Bacteroidetes species contribute to the adaptation of camels to arid conditions. The RC9_gut_group found in this study belongs to uncultured genera and was found also in the Rhinoceros hindgut <ns0:ref type='bibr' target='#b8'>(Bian et al., 2013)</ns0:ref>. Unclassified Bacteroidetes specialize in lignocellulose degradation <ns0:ref type='bibr' target='#b59'>(Mackenzie et al., 2015)</ns0:ref>, which could support their high proportion in G3 camels. Fibrobacteres was higher (3.1%) in this study compared to the other findings on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>; this phylum is the principal cellulolytic bacteria in the rumen <ns0:ref type='bibr' target='#b75'>(Ransom-Jones et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b62'>Nathani et al., 2015)</ns0:ref>, which might illustrate its higher relative abundance in solid fraction and in the rumen of G3 camels that fed on wheat straw (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). The members of Proteobacteria were lower in G2 and G3 camels that were fed on diet rich in fiber contents. These findings highlighted this phylum's function as a protein-degrading bacteria <ns0:ref type='bibr' target='#b57'>(Liu et al., 2017)</ns0:ref>. The abundance of Treponema was higher in the solid fraction and in G3 camels (Figure <ns0:ref type='figure' target='#fig_0'>1a</ns0:ref>). Treponema is the dominant genus in Spirochaetes phylum and it is fiber-associated bacteria, which could indicate to its cellulytic and xylanolytic activities <ns0:ref type='bibr' target='#b35'>(Ishaq and Wright, 2012)</ns0:ref>.</ns0:p><ns0:p>The dominant bacterial genera in this study were Butyriovibrio, RFN8-YE57, Ruminococcus, Prevotella, Fibrobacter, Treponema and VadinHA. These genera were higher in the SF except RFN8-YE57 compared to the LF; this finding was consistent with a study on camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>, and confirms that solid-attached microbes could play a major role in ruminal fiber digestion <ns0:ref type='bibr' target='#b40'>(Jewell et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b64'>Noel et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Most of Elusimicrobia in this study</ns0:head><ns0:p>Most of Elusimicrobia observed in this study have yet to be cultured; some members of this phylum were isolated from the termite's gut that degrades cellulose <ns0:ref type='bibr' target='#b32'>(Herlemann et al., 2009)</ns0:ref>. Therefore, we speculate that this phylum has a role in fiber digestion and that might illustrate their high proportion in G3 camels. Actinobacteria observed also in the rumen of moose and some members of this phylum have acetogenic activities <ns0:ref type='bibr' target='#b37'>(Ishaq et al., 2015)</ns0:ref>. Some members of Victivallis within Lentisphaerae phylum were involved in cellobiose degradation <ns0:ref type='bibr' target='#b97'>(Zoetendal et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Unclassified bacteria in our study (39% of total bacterial reads) were less than the percentage found in a study of muskoxen (54%) <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref>. The presence of unclassified bacteria in the gut was commonly observed <ns0:ref type='bibr' target='#b27'>(Gruninger et al., 2016)</ns0:ref> and could be a result of the presence of new bacteria that ferment plant biomass <ns0:ref type='bibr' target='#b79'>(Salgado-Flores et al., 2016)</ns0:ref> or related to short reads were generated from RNA sequencing <ns0:ref type='bibr' target='#b56'>(Li et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Archaeal community</ns0:head><ns0:p>Since some archaea produce CH 4 from H 2 and CO 2 , this phyla may control methane emission from ruminants <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010)</ns0:ref>. Additionally, acetate produced in fiber breakdown provides a methyl group for methanogenesis; therefore, alteration of diet shifts the structure of methanogen populations <ns0:ref type='bibr' target='#b33'>(Hook et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b88'>Tapio et al., 2017 )</ns0:ref>, which could demonstrate the variation in the relative abundance of archaea between camel groups. Camels of the second group (G2) that were fed fresh clover, showed the highest archaeal population (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>) and archaeal community was dominated by Thermoplasmatales, a methylotrophic methanogens order (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>), which was consistent with the results on cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref> and camels <ns0:ref type='bibr' target='#b26'>(Gharechahi et al., 2015)</ns0:ref>. Thermoplasmatales produce methane from methyl amine and supplementing of animal's diet with rapeseed oil decreases the abundance of this order, making it a high potential target in future strategies to mitigate methane emissions <ns0:ref type='bibr' target='#b72'>(Poulsen et al., 2013)</ns0:ref>. The Methanobrevibacter, Methanosphaera, Methanomicrobium and Methanobacterium (Table <ns0:ref type='table'>4</ns0:ref>) dominated the reads classified as archaea in this study, which agrees with trends reported for beef cattle <ns0:ref type='bibr' target='#b11'>(Carberry et al., 2014)</ns0:ref>. Methanobrevibacter dominated the methanogens in other ruminant <ns0:ref type='bibr' target='#b31'>(Henderson et al., 2015)</ns0:ref> and was associated with high methane emissions <ns0:ref type='bibr' target='#b88'>(Tapio et al., 2017)</ns0:ref>. Moreover, Methanomicrobium was higher in the camels of G3 that were fed on poor quality forage, which was similar to results of buffalo <ns0:ref type='bibr' target='#b22'>(Franzolin and Wright, 2016)</ns0:ref>, and in vitro <ns0:ref type='bibr' target='#b90'>(Wang et al., 2018)</ns0:ref>. In rumen, Methanomicrobium converts H 2 and/or formate into CH 4 <ns0:ref type='bibr' target='#b52'>(Leahy et al., 2013)</ns0:ref>. The abundance of Thermoplasmatales was also negatively correlated with Methanobrevibacter, which is consistent with previous results <ns0:ref type='bibr' target='#b15'>(Danielsson et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b60'>McGovern et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Protozoal community</ns0:head><ns0:p>The majority of protozoal reads were classified as Diplodinium, Ophryoscolex, Entodinium, Polyplastron, Eudiplodinium and Epidinium (Table <ns0:ref type='table'>4</ns0:ref>). Similar findings were observed on different ruminants <ns0:ref type='bibr' target='#b4'>(Baraka, 2012)</ns0:ref>. Feed appeared to influence the relative abundance of protozoa, as reported previously for cattle <ns0:ref type='bibr' target='#b34'>(Hristov et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b91'>Weimer, 2015)</ns0:ref>; however, we cannot differentiate the effects of feed from facility. Diplodinium dominated protozoal community and was prevalent in G3 camels, which highlighted the cellulolytic activity of this genus <ns0:ref type='bibr' target='#b13'>(Coleman et al., 1976)</ns0:ref>. Some species of genus Diplodinium, such as Diplodinium cameli, were discovered in, and are unique to, the rumen of Egyptian camel <ns0:ref type='bibr' target='#b48'>(Kubesy and Dehority, 2002)</ns0:ref>. In addition, Entodinium was higher in G1 camels that were fed on concentrates feed mixture that increase the protozoa. Also, this genus predominates rumen of camels <ns0:ref type='bibr' target='#b82'>(Selim et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b25'>Ghali et al., 2005)</ns0:ref> and cattle <ns0:ref type='bibr' target='#b12'>(Carberry et al., 2012)</ns0:ref>. Moreover, <ns0:ref type='bibr' target='#b47'>Kittelmann and Janssen (2011)</ns0:ref> showed that the Polyplastron was the dominant genus in cattle. On the function level, all the genus Eudiplidinum, Epidinum and Diplodinum have cellulolytic activity <ns0:ref type='bibr' target='#b13'>(Coleman et al., 1976)</ns0:ref>, whereas, Polyplastrone and Epidinium have a xylanolytic activity <ns0:ref type='bibr' target='#b17'>(Devillard, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>B&#233;ra-Maillet et al., 2005)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Anaerobic rumen fungal community</ns0:head><ns0:p>The highest fungal population was observed in the solid fraction and rumen of G3 camels (Table <ns0:ref type='table'>1</ns0:ref>). These findings were in agreement with the results of studies stated that the fibre-based diets stimulated the fungal growth <ns0:ref type='bibr' target='#b65'>(Orpin, 1977;</ns0:ref><ns0:ref type='bibr' target='#b77'>Roger et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kamra et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b29'>Haitjema et al., 2014)</ns0:ref>. This could explain the low fungal population in G1 camels in our study. Moreover, the longer retention time and neutral pH in camel's forestomach <ns0:ref type='bibr' target='#b78'>(Russell and Wilson, 1996)</ns0:ref> make it more suitable for the survival of rumen fungi. Neocallimastix dominated the fungal community and was higher in the G1 camels, which was similar to other results on sheep and camels <ns0:ref type='bibr' target='#b46'>(Kittelmann et al., 2013</ns0:ref><ns0:ref type='bibr' target='#b74'>, Rabee et al., 2019)</ns0:ref>. This genus produces enzymes capable of hydrolyzing cellulose, xylan and starch <ns0:ref type='bibr' target='#b68'>(Pearce and Bauchop, 1985)</ns0:ref>. Cyllamyces that was observed in small population, has the ability to degrade poor-quality feeds <ns0:ref type='bibr' target='#b86'>(Sridhar et al., 2014)</ns0:ref>, which might explain its high population in solid fraction and G3 camels. Piromyces was the second dominant genus in the camel rumen of this study and produces cellulolytic and xylanolytic enzymes <ns0:ref type='bibr' target='#b89'>(Teunissen et al., 1992)</ns0:ref>. Therefore, this genus was most abundant in rumen collected from the G2 group of camels. The genus Spizellomyces is closely related to Chytridiomctes <ns0:ref type='bibr' target='#b10'>(Bowman et al., 1992)</ns0:ref>, and common in grassland and crop soil <ns0:ref type='bibr' target='#b58'>(Lozupone and</ns0:ref><ns0:ref type='bibr'>Klein, 2002, Kittelmann et al., 2012)</ns0:ref>. Thus, contamination of forages by soil could explain the presence of this fungus in camel rumen.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between rumen microbes</ns0:head><ns0:p>Interactions between rumen microbes drive feed degradation and methane formation in the rumen, which influence the animal production and the environment <ns0:ref type='bibr' target='#b93'>(Williams et al., 1994;</ns0:ref><ns0:ref type='bibr' target='#b54'>Lee et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b31'>Henderson et al., 2015)</ns0:ref>. Positive and negative correlations were observed within and between microbial communities in this study (Fig. <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>). Methanogens colonize protozoa and this relationship enhances methane formation <ns0:ref type='bibr' target='#b63'>(Newbold et al., 1995)</ns0:ref>. Additionally, fibrolytic bacteria produce hydrogen and methyl groups that methanogens use for growth <ns0:ref type='bibr' target='#b41'>(Johnson and Johnson, 1995)</ns0:ref>, which demonstrated positive correlations found between Fibrobacteres and some methanogens. Also, positive correlation between methylotrophic Methanosphaera and Lachnospiraceae that has been implicated in pectin degradation and provides methanol as a substrate for the methylotrophs <ns0:ref type='bibr' target='#b16'>(Dehority, 1969)</ns0:ref>. On the other hand, Prevotella is a hydrogen utilizer and produces propionate that impact the methanogenesis in the rumen negatively <ns0:ref type='bibr' target='#b70'>(Pitta et al., 2014a;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>, which illustrates negative correlation between Prevotellaceae and archaea.</ns0:p><ns0:p>Since the rumen anaerobic fungi produce abundant H 2 through the fermentation of carbohydrate; they can interact positively with H 2 utilizers such as archaea, Prevotellaceae, Blautia and Acetitomaculum <ns0:ref type='bibr' target='#b66'>(Orpin and Joblin, 1997</ns0:ref>; Le <ns0:ref type='bibr'>Van et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b95'>Yang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b57'>Liu et al., 2017)</ns0:ref>. Additionally, anaerobic fungi penetrate plant tissue, providing an increased surface area for bacterial colonization <ns0:ref type='bibr' target='#b66'>(Orpin and Joblin, 1997)</ns0:ref>, which could explain positive correlation between fungi and both Butyrivibrio and Fibrobacteres. However, some bacteria and protozoa prey on fungal zoospores <ns0:ref type='bibr' target='#b61'>(Morgavi et al., 1994)</ns0:ref>, which demonstrated the negative correlation between both Neocallimastix and Piromyces with Diplodinium and Entodinium. Furthermore, Ruminococcus produces compounds that inhibit the growth of rumen fungi <ns0:ref type='bibr' target='#b87'>(Stewart et al., 1992)</ns0:ref>, which supports the negative correlation between Neocallimastix and Ruminococcaceae. Polyplastron predates upon other protozoa like Epidinium, Eudiplodinium, Diplodinium, and Ostracodinium <ns0:ref type='bibr' target='#b19'>(Eadie, 1967)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>The microbial community in camel rumen was diverse and similar in composition between the groups of camels. The majority of camel rumen microbes (bacteria, fungi, and protozoa) were fibrolytic or have a possible role in fiber digestion, which might illustrate the ability of camel to live in desert harsh conditions under poor feeds. Moreover, the structure of microbial community in rumen of camels was similar to other ruminants.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>The relative abundance of microbial groups Relative abundance (%) of bacterial phyla Manuscript to be reviewed Relative abundance (%) of archaeal orders and genera Manuscript to be reviewed Relative abundance (%) of fungal genera </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Comparison of relative abundance of genera of the microbiota in dromedary camel. bacterial (a), archaeal (b), protozoal (c) and fungi (d) in ruminal solid (SF) and liquid (LF) fractions of camels under different feeding systems.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3:Linear Discriminant analysis of microbial communities in the samples based on the relative abundance of genera of active bacteria (a), archaea (b), protozoa (c) and fungi i (d)in ruminal solid (SF), and liquid (LF) fractions of camels under three feeding systems, G1 (black dots), G2 (blue squares) and G3 (coral triangles).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>.07 0.2&#177;0.04 0.8&#177;0.4 0.4&#177;0.1 a The value was calculated from one animal. PeerJ reviewing PDF | (2019:12:44048:8:0:NEW 8 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Relative abundance (%) of bacterial phyla in the ruminal solid (SF) and liquid (LF)</ns0:figDesc><ns0:table><ns0:row><ns0:cell>fractions of camels fed a mixed ration(G1), high-quality forage(G2) and low-quality forage</ns0:cell></ns0:row><ns0:row><ns0:cell>(G3) (Mean &#177; Standard Error (SE)).</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:12:44048:8:0:NEW 8 Sep 2020)Manuscript to be reviewed</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Relative abundance (%) of archaeal orders and genera observed in the ruminal solid (SF), and liquid (LF) fractions of camels under different feeding systems. Animals in G1 fed a mixed ration, animal in G2 fed high-quality forage and animal in G3 fed low qualityforage (Mean &#177; Standard Error (SE)).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Protozoa</ns0:cell><ns0:cell>G1</ns0:cell><ns0:cell>G2</ns0:cell><ns0:cell>G3</ns0:cell><ns0:cell>Overall mean</ns0:cell></ns0:row><ns0:row><ns0:cell>Entodinium SF</ns0:cell><ns0:cell>23&#177;6</ns0:cell><ns0:cell>6.5&#177;0.6</ns0:cell><ns0:cell>6&#177;1</ns0:cell><ns0:cell>11&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell>Entodinium LF</ns0:cell><ns0:cell>54&#177;10</ns0:cell><ns0:cell>15&#177;2.5</ns0:cell><ns0:cell>5&#177;1</ns0:cell><ns0:cell>24&#177;6</ns0:cell></ns0:row><ns0:row><ns0:cell>Polyplastron S F</ns0:cell><ns0:cell>10&#177;1</ns0:cell><ns0:cell>17.5&#177;2</ns0:cell><ns0:cell>25&#177;3</ns0:cell><ns0:cell>17&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Polyplastron LF</ns0:cell><ns0:cell>6&#177;1</ns0:cell><ns0:cell>11&#177;0.2</ns0:cell><ns0:cell>24&#177;3</ns0:cell><ns0:cell>12&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Diplodinium S F</ns0:cell><ns0:cell>23&#177;1</ns0:cell><ns0:cell>35&#177;3</ns0:cell><ns0:cell>49&#177;10</ns0:cell><ns0:cell>34&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell>Diplodinium LF</ns0:cell><ns0:cell>13&#177;3</ns0:cell><ns0:cell>27&#177;3</ns0:cell><ns0:cell>61&#177;6</ns0:cell><ns0:cell>29&#177;5</ns0:cell></ns0:row><ns0:row><ns0:cell>Eudiplodinium SF</ns0:cell><ns0:cell>8&#177;0.6</ns0:cell><ns0:cell>8&#177;2</ns0:cell><ns0:cell>2&#177;0.7</ns0:cell><ns0:cell>7&#177;1</ns0:cell></ns0:row><ns0:row><ns0:cell>Eudiplodinium LF</ns0:cell><ns0:cell>4&#177;1</ns0:cell><ns0:cell>5.5&#177;1</ns0:cell><ns0:cell>2.5&#177;0.5</ns0:cell><ns0:cell>4.5&#177;0.6</ns0:cell></ns0:row><ns0:row><ns0:cell>Epidinium SF</ns0:cell><ns0:cell>5&#177;0.8</ns0:cell><ns0:cell>4&#177;1</ns0:cell><ns0:cell>2&#177;1</ns0:cell><ns0:cell>4&#177;0.1</ns0:cell></ns0:row><ns0:row><ns0:cell>Epidinium LF</ns0:cell><ns0:cell>3&#177;0.8</ns0:cell><ns0:cell>4.5&#177;0.6</ns0:cell><ns0:cell>1&#177;0.7</ns0:cell><ns0:cell>3.5&#177;0.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Ophryoscolex SF</ns0:cell><ns0:cell>30&#177;4</ns0:cell><ns0:cell>27&#177;3</ns0:cell><ns0:cell>15&#177;5</ns0:cell><ns0:cell>26&#177;2.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Ophryoscolex LF</ns0:cell><ns0:cell>19&#177;4</ns0:cell><ns0:cell>29&#177;0.6</ns0:cell><ns0:cell>6.5&#177;4</ns0:cell><ns0:cell>22&#177;3</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Trichostomatia SF 0.1&#177;0.02</ns0:cell><ns0:cell>1&#177;0.25</ns0:cell><ns0:cell>0.3&#177;0.15</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Trichostomatia LF 0.2&#177;0.04</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell><ns0:cell>1&#177;0.1</ns0:cell><ns0:cell>1&#177;0.2</ns0:cell></ns0:row><ns0:row><ns0:cell>Isotricha SF</ns0:cell><ns0:cell cols='3'>0.2&#177;0.04 0.3&#177;0.05 0.3&#177;0.004</ns0:cell><ns0:cell>0.3&#177;0.03</ns0:cell></ns0:row><ns0:row><ns0:cell>Isotricha LF</ns0:cell><ns0:cell>0.5&#177;0.2</ns0:cell><ns0:cell>2&#177;0.9</ns0:cell><ns0:cell>0.3&#177;0.01</ns0:cell><ns0:cell>1&#177;0.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Dasytricha SF</ns0:cell><ns0:cell cols='3'>0.04&#177;0.01 1.5&#177;0.3 0.2&#177;0.15</ns0:cell><ns0:cell>1&#177;0.3</ns0:cell></ns0:row><ns0:row><ns0:cell>Dasytricha LF</ns0:cell><ns0:cell cols='2'>0.1&#177;0.002 5.5&#177;0.8</ns0:cell><ns0:cell>0.5&#177;0.3</ns0:cell><ns0:cell>3&#177;1</ns0:cell></ns0:row></ns0:table><ns0:note>2PeerJ reviewing PDF | (2019:12:44048:8:0:NEW 8 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 5 :</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Relative abundance (%) of fungal genera in the ruminal solid (SF) and liquid fraction (LF) of camels under different feeding systems. Camels in G1 fed a mixed ration, animals in G2 fed high-quality forage, and animals in G3 fed low-quality forage (Mean &#177; SE).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Fungi</ns0:cell><ns0:cell>G1</ns0:cell><ns0:cell>G2</ns0:cell><ns0:cell>G3</ns0:cell><ns0:cell>Overall mean</ns0:cell></ns0:row><ns0:row><ns0:cell>Spizellomyces SF</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0.1</ns0:cell><ns0:cell>0.02</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>Spizellomyces LF 0.3 &#177; 0.1 0.3 &#177; 0.1</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>ND</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces SF</ns0:cell><ns0:cell>2&#177; 0.6</ns0:cell><ns0:cell>3&#177; 1.5</ns0:cell><ns0:cell>7&#177; 4</ns0:cell><ns0:cell>3.5&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Cyllamyces LF</ns0:cell><ns0:cell>2&#177; 0.8</ns0:cell><ns0:cell cols='2'>3&#177; 0.8 10&#177; 1</ns0:cell><ns0:cell>4&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces SF</ns0:cell><ns0:cell>6&#177; 3</ns0:cell><ns0:cell cols='2'>12&#177; 0.7 8&#177; 1</ns0:cell><ns0:cell>9&#177; 1</ns0:cell></ns0:row><ns0:row><ns0:cell>Piromyces LF</ns0:cell><ns0:cell>6&#177;4</ns0:cell><ns0:cell>12&#177;2</ns0:cell><ns0:cell>10&#177;6</ns0:cell><ns0:cell>10&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix SF</ns0:cell><ns0:cell>92&#177;3</ns0:cell><ns0:cell>85&#177;1</ns0:cell><ns0:cell>85&#177;3</ns0:cell><ns0:cell>87&#177;1</ns0:cell></ns0:row><ns0:row><ns0:cell>Neocallimastix LF</ns0:cell><ns0:cell>92&#177;4</ns0:cell><ns0:cell cols='2'>85&#177;1.5 81&#177;7</ns0:cell><ns0:cell>86&#177;2</ns0:cell></ns0:row><ns0:row><ns0:cell>ND: Non Determined</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:12:44048:8:0:NEW 8 Sep 2020) Manuscript to be reviewed PeerJ reviewing PDF | (2019:12:44048:8:0:NEW 8 Sep 2020)</ns0:note></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2019:12:44048:8:0:NEW 8 Sep 2020)</ns0:note> </ns0:body> "

" Desert Research Center 6th September, 2020 1Mathaf El Matariya St.B.O.P.11753 Matariya- Cairo,Egypt Phone: (+202)26332846 - 26374800 FAX: (+202) 26357858 Email:[email protected] Dear Editor, Its our pleasure to submit our responses to the comments of 8th round of revision. Thank you for your comments, we responded to all comments and enclosed unclean paper including all comments colored by yellow. We appreciate the opportunity to submit our manuscript to Peer J. Yours sincerely, Dr. Alaa Rabee Researcher at Desert Research Center, Egypt On behalf of all authors Comments Manuscript title: “Comparative analysis of the metabolically active microbial communities in the rumen of dromedary camels under different feeding systems using total rRNA sequencing ” Editor’s comments Line 38. Avoid superfluous determiners. Delete “The” in “The breakdown…” and replace “the camel” with “camels” (line 68) >> Modified, thank you. Line 51. On further review, something is missing here. I suggest revising to “...bacteria dominate the microbial communities of the camel rumen and these communities varies between populations of domesticated camels.” >>Revised. Line 82. Avoid the passive voice. Replace “Therefore, the output could be biased due to the primer selection and amplification cycling conditions” with “Primer selection and amplification conditions could bias the output…” See also lines 182, 187, 189, 247, 350… >> Modified. Line 104. Something is missing here. I suggest revising to “… rumen fractions; 3) assessing the heterogeneity of these microbial populations within different populations of domestic camels.” >> Modified. Line 180. Delete “Phylum” >> Deleted Line 182. Again, here and throughout, avoid the passive voice. Replace “On the family level, the Firmicutes phylum was dominated by Lachnospiraceae and Ruminococcuceae.” With “At the family level, Lachnospiraceae and Ruminococcuceae dominated the Firmicutes.” >> Modified. Line 247. Replace “..bacteria, dominated by phylum Firmicutes were the main driver of differences…” with “bacteria, dominated by Firmicutes, drove differences…” See also line 248. >> Modified. Line 282. Revise to “In this study, camel groups..” >> Modified. Line 284. Revise to “…with the results of studies of other ruminants..” >> Modified. Line 298. Why cap “Muskoxen” (see also line 337)? >> Revised. Line 304. Revise to “This supports the observation that manipulation…” >> Modified. Line 321. Delete “as is was reported by” >> Deleted. Line 330. Replace “Most of Elusimicrobia in this study were uncultured” with “Most of Elusimicrobia observed in this study have yet to be cultured…” >> Modified. Line 346. Revise to “that were fed” >> Modified. Line 350. Replace “and its population was decreased by the addition of rapeseed oil to animal diet” with “and supplementing of animal’s diet with rapeseed oil decreases the abundance of this order” >> Replaced. Line 352.present your results in past tense. Revise to “ …(table 4) dominated the reads classified as Archaea in this study, which agrees with trends reported for beef cattle.. >> Revised. Line 358. Why cap “in vitro”? >> Revised. Line 382. Delete “speculation” >> Deleted. Line 391. Replace “Therefore, the fungi were more prevalent in ruminants of G2 camels, which were fed high-quality forage with high fiber contents than in G1 and G3 camels” with “Fungi were most abundant in rumen collected from the G2 group of camels.” >> Modified. Line 395. Delete “the” in “the forages” and “the camel”. >> Deleted. Line 400, 407. Delete “the” >> Deleted. Line 401. Delete “which highlighted some positive correlations between protozoa and archaea.” >> Deleted. Line 402. Delete “important substrates mainly” >> Deleted. Line 414. You cannot have to phrases that start with “which” in the same sentence. >> Modified. Line 416. Replace “fungi are negatively impacted by the presence of some bacteria and protozoa as the fungal zoospores are likely to be a prey for protozoa” with “some bacteria and protozoa prey on fungal zoospores” >> Modified. Line 420. Revise to “which supports” >> Modified. Line 423. Again, too many dangling phrases. Delete “which might…Protozoa.” >> Deleted. Line 425. Revise “between groups of camels.” >> Revised. Line 429. Replace “camel found to be similar to other ruminants with a shown difference in the relative abundances” with “camels was similar to other ruminants.” >> Replaced. Line 430. Delete “The present…their functions.” >> Deleted. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Staphylococcus aureus is a drug-resistant pathogen, capable of colonizing diverse ecological niches in its human host and causing a broad spectrum of infections related to community and healthcare. The whole-genome analysis provides an insight into the genomic structure and constituents that offers to compare between the strains and investigate the outbreak. This study reported the whole-genome features, and comparative genomic analysis of S. aureus isolates originated from Germany and Hungary.</ns0:p><ns0:p>The Hungarian isolate with ST22-SCCmec type IVa acquires less multiple resistance antibiotic genes reported in Germany isolates. Germany isolate, SA G6 acquires aminoglycoside (ant(6)-Ia and aph(3')-III) and nucleoside (sat-4) resistance genes via phages and may determine its pathogenic potential. Also, more virulence genes were recognized in Germany isolates with a higher number of prophages in the genomic island regions. The comparative genome study allowed the segregation of isolates of geographical origin and differentiation of the clinical isolates from the commensal isolates.</ns0:p><ns0:p>This study suggested that Germany and Hungarian isolates are genetically diverse and showing variation among them due to the gain or loss of MGEs. The event of MGEs transfer was observed in ST5, ST225, and ST228. An interesting finding is the addition of SA G6 genome responsible for the drastic decline of the core/pan-genome ratio curve and causing the pan-genome to open wider and suggested that HGT was not limited within the S. aureus strains. Functional characterizations revealed that S. aureus isolates survival are maintained by the amino acids catabolism and favor adaptation to growing in a proteinrich medium. The interpretation from the dispersible and singleton genes content analysis of S. aureus genomes allows us to understand the genetic variation among the CC5 and CC22 groups. Phylogenetic analysis suggests that SA G6 and S. aureus subsp. aureus ST228 strains are distinct from its group. The acquisition of plasmid and prophage functional modules in S. aureus isolates may contribute a major role in the rapid evolution of pathogenic S. aureus lineages and that confer specific advantages in a defined host</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Staphylococcus aureus is a notorious nosocomial, and community-acquired pathogen <ns0:ref type='bibr' target='#b28'>(Chambers and Deleo, 2009)</ns0:ref>. It has the capability of colonizing diverse ecological niches within its human host, including the skin, blood, respiratory tract, and nasal passages <ns0:ref type='bibr' target='#b38'>(Deleo et al., 2009)</ns0:ref> and causing diverse ranges of the hospital and community-acquired infections such as skin and soft tissue infections (SSI) for example, carbuncles, abscesses, styes, and impetigo and lifethreatening infections such as bacteremia, necrotizing pneumonia, osteomyelitis, endocarditis, and sepsis <ns0:ref type='bibr' target='#b52'>(G&#246;tz et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b110'>Mottola et al., 2016)</ns0:ref>. Methicillin-resistant S. aureus (MRSA) acquired a mobile genetic element called Staphylococcal chromosomal cassette mec <ns0:ref type='bibr'>(SCCmec)</ns0:ref> accompanied by methicillin resistance gene (mecA) <ns0:ref type='bibr' target='#b152'>(Zhang et al., 2012)</ns0:ref>. The &#946;-lactam insensitive protein, penicillin-binding protein (PBP2a) encoded by mecA gene reduces affinity to penicillin and &#946;-lactam antibiotics including methicillin, oxacillin, cefoxitin, etc., and develop resistance toward the &#946;-lactam antibiotics <ns0:ref type='bibr' target='#b68'>(Jansen et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b106'>Mistry et al., 2016)</ns0:ref>. MRSA acquires an arsenal of antibiotic resistance genes (ARGs) and virulence factor encoding genes (VFGs) through horizontal gene transfer (HGT) and recombination <ns0:ref type='bibr' target='#b29'>(Chan et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b65'>Hughes et al., 2005)</ns0:ref>.</ns0:p><ns0:p>MRSA can anchor and colonize on epithelial surfaces and produce biofilm <ns0:ref type='bibr'>(Goudarzi et al., 2017)</ns0:ref>. The biofilm produced by MRSA strains encase its cells in the exopolysaccharide matrix reduces the activity of antibacterial agents and immune defense. The dispersal of bacterial cells from the biofilm can result in secondary site infections and leading infections worsen and difficult to eradicate <ns0:ref type='bibr' target='#b93'>(Lister and Horswill, 2014)</ns0:ref>. Biofilm formation is a complex process that consists of an extracellular polymeric matrix (ECM) formation involving polysaccharide intercellular adhesin (PIA), protein-protein interactions, and the incorporation of extracellular DNA (eDNA) <ns0:ref type='bibr' target='#b118'>(O'Gara, 2007;</ns0:ref><ns0:ref type='bibr'>Payne and Boles, 2016)</ns0:ref>. The biofilm formation is determined by the icaADBC gene cluster, responsible for PIA and capsular polysaccharide/adhesion synthesis <ns0:ref type='bibr' target='#b27'>(Chaieb et al., 2005)</ns0:ref>. MRSA possesses adhesive matrix molecules that are encoded by elastin (ebps), laminin (eno), clumping factors A and B (clfA and clfB), fibronectin A and B (fnbA and fnbB), collagen (cna), fibrinogen (fib), bone sialoprotein (bbp), etc <ns0:ref type='bibr' target='#b91'>(Lindsay et al., 2006)</ns0:ref>. These molecules are exported to the bacterial cell surface to enable adherence with host tissues, leading to play a role in pathogenesis <ns0:ref type='bibr' target='#b97'>(Mazmanian et al., 1999)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed S. aureus acquires an arsenal of ARGs and VFGs that are subjected to HGT and recombination <ns0:ref type='bibr' target='#b29'>(Chan et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b65'>Hughes et al., 2005)</ns0:ref>. Hospital-associated MRSA (HA-MRSA) is often associated with metastatic infections and significant morbidity and mortality <ns0:ref type='bibr' target='#b54'>(Gould, 2005)</ns0:ref>.</ns0:p><ns0:p>However, Community-associated MRSA (CA-MRSA) infections have seen a high increase in prevalence, posing a greater threat to the public <ns0:ref type='bibr' target='#b108'>(Morens and Fauci, 2013)</ns0:ref>. The genomic plasticity of S. aureus has facilitated the development of hypervirulent and drug-resistant strains, result in challenging issues to antibiotic treatment and health concern.</ns0:p><ns0:p>The classical techniques such as antibiotic susceptibility test (AST) patterns and molecular typing methods such as SCCmec-typing, Pulse-Field Gel Electrophoresis (PFGE), Multi-Locus Sequence Typing (MLST), Multi-locus variable-number tandem-repeat (VNTR) analysis (MLVA), S. aureus protein A (spa)-typing, accessory gene regulator (agr)-typing are widely used to detect and differentiate several MRSA strains, and helpful for identifying the risk factors associated with MRSA infection which support the establishment of adequate infection control programs <ns0:ref type='bibr' target='#b152'>(Zhang et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b106'>Mistry et al., 2016)</ns0:ref>. However, these methods are expensive and time-consuming, and have limitations in infection control and investigating the nosocomial transmission due to low resolution <ns0:ref type='bibr' target='#b40'>(Du et al., 2011)</ns0:ref>. In this modern era, whole-genome sequence-based typing offers an excellent resolution in global and local epidemiologic investigations of pathogen outbreaks and offers further data mining activities essentially for ARGs and VFGs profiling <ns0:ref type='bibr' target='#b77'>(K&#246;ser et al., 2012)</ns0:ref>. So, the Next Generation Sequencer (NGS) basedgenome sequencing technique has become an essential tool in the clinical microbiology arenas for comparative genomic analysis of several other species of the Staphylococcus genus in terms of the niche adaptation, combat antibiotics, and emergence of new virulent strains in real-time.</ns0:p><ns0:p>In our preliminary study, the polyphasic characterization of 35 S. aureus strains originated from Germany, and Hungary was performed. This characterization includes antibiotic resistance test (ART), biochemical tests, biofilm-forming assay, and PCR based typing techniques involving the amplification of mecA, pvl, SCCmec-type, spa type, coa-HaeIII-RFLP, and biofilm-associated genes. Principal component analysis from polyphasic characterization data showed that the strains originated from the same geographical region were found in the close group while SA G8, Germany strain was grouped with other Hungarian strains <ns0:ref type='bibr'>(Naorem et al., in press</ns0:ref>). The Hungarian strains (SA H27 and SA H32) belonged to the same Clonal Complex (ST22/SCCmec-IV) were clustered in the same group, however, these strains were isolated from the different sites of infections (nostrils and trachea) and showed different antibiotic resistance patterns and biofilm-forming abilities. Similarly, the strains collected from Germany viz., SA G6, and SA G8 belonged to same Clonal Complex (ST228/SCCmec-I and ST225/ SCCmec-II) having similar antibiotic resistance pattern, and biofilm-forming profiles, but these strains were isolated from the different site of infections (skin and other body sites) and not clustered in the same group <ns0:ref type='bibr'>(Naorem et al., in press</ns0:ref>). Based on this information, these four S. aureus strains were chosen for in-depth comparative genome levels study to better understand the genomic differences among the stains. We assumed that the selected strains have a different genetic background in terms of the presence of ARGs, VFGs, prophages, plasmids, and secondary metabolite biosynthesis genes that may play a crucial role in niche adaptation and pathogenesis. To clarify these assumptions, we performed a comparative genome analysis of these four strains and observed many differences in their genomic compositions.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Bacterial strains used in this study</ns0:head><ns0:p>In this study, four S. aureus isolates collected from Germany (SA G6, and SA G8) and Hungarian (SA H27, and SA H32) were used. Hungarian isolate, SA H27 was reported as a strong biofilm producer among them <ns0:ref type='bibr'>(Naorem et al., in press)</ns0:ref>.</ns0:p><ns0:p>pH tolerance assay S. aureus strains were cultured overnight at 37&#186; C in tryptic soy broth (TSB) (DB, Germany).</ns0:p><ns0:p>The cell density (colony forming units, CFU) was adjusted to a final concentration of ~10&#8310; CFU/ml in pH 4.5 TSB and pH 9.5 TSB. Cell suspension (200 &#181;l) were loaded into the 96-well flat-bottomed polystyrene microtiter plate (Costar 3599; Corning; USA). The plates were incubated at 37&#186; C for 24 h without shaking, then the growth was measured at 492 nm wavelength using a Multiskan Ex microtiter plate reader (Thermo Electron Corporation, USA).</ns0:p><ns0:p>The experiments were performed in triplicate and analyzed using GraphPad Prism 6 software package (Graphpad Software Inc, San Diego, CA).</ns0:p></ns0:div> <ns0:div><ns0:head>Genomic DNA isolation and sequencing</ns0:head><ns0:p>The genomic DNA was extracted using the GenElute&#8482; Bacterial Genomic DNA Kit (Sigma, USA) following the manufacturer instructions. The concentration and purity of genomic DNA was measured using dsDNA HS (High Sensitivity) Assay Kit in Qubit 3.0 fluorometer (Thermo Fisher Scientific Inc., USA) and subsequently DNA quality was visualized by agarose gel electrophoresis.</ns0:p><ns0:p>Genomic libraries were prepared by using the NEB Next Fast DNA Fragmentation and Library Preparation Kit, developed for Ion Torrent (New England Biolabs) and used according to 200 bp protocol. After chemical fragmentation, DNA size selection was performed on precast 2% E-Gel Size Select Gel (Thermo Fisher Scientific Inc., USA). The quality of the libraries was verified using Agilent high sensitivity DNA assay kit (Agilent Technologies Inc., USA) in Agilent 2100</ns0:p><ns0:p>Bioanalyzer System (Agilent Technologies Inc., USA). For the template preparation, Ion PGM Hi-Q View OT2 Kit was used (Thermo Fisher Scientific Inc., USA). The template positive beads were loaded on Ion 316v2 Chip and sequenced using Ion PGM Hi-Q View Sequencing Kit on Ion Torrent PGM sequencer (Thermo Fisher Scientific Inc., USA).</ns0:p></ns0:div> <ns0:div><ns0:head>Genome assembly and annotation</ns0:head><ns0:p>In-silico trimming of adapter and barcode sequences and data analysis were performed using Torrent Suite 5.4.0 (Thermo Fisher Scientific Inc., USA) and the trimmed paired-end reads were assembled by de novo assembler SPAdes 3.7.1 software with <ns0:ref type='bibr'>21, 33, 55, 77, 99, 127 k-mer values (Nurk et al., 2013)</ns0:ref>. The assembly-stats and quality of genome completeness for each strain were estimated using the web platform QUEST <ns0:ref type='bibr' target='#b60'>(Gurevich et al., 2013)</ns0:ref>. For identifying the closely related strains, the genome assemblies were analyzed by the kmerFinder 2.0 webplatform <ns0:ref type='bibr'>(Larsen et al., 2014)</ns0:ref>. The genome assembly was aligned against the reference genome for the contigs rearrangement using the 'Move Contigs' algorithm in Mauve 2.4.0 <ns0:ref type='bibr' target='#b37'>(Darling et al., 2010)</ns0:ref> and further, scaffolds were generated with reference genome/ genome of closely related strains predicted by kmerFinder 2.0 as a guide for alignment using the reference-based scaffolder MeDuSa <ns0:ref type='bibr' target='#b20'>(Bosi et al., 2015)</ns0:ref>. Gene annotation of the genome assemblies was performed via the fully automated RAST (Rapid Annotation using Subsystem Technology) <ns0:ref type='bibr'>(Aziz et al., 2008)</ns0:ref> and PATRIC 3.5.7 (Pathosystems Resource Integration Center) <ns0:ref type='bibr' target='#b122'>(Wattam et al., 2013)</ns0:ref> pipelines using the reference genome.</ns0:p></ns0:div> <ns0:div><ns0:head>In-silico characterization of genome assemblies</ns0:head><ns0:p>In-silico epidemiologic characterization of genome assemblies was performed using SCCmecFinder-1.2 for the identification of SCCmec types <ns0:ref type='bibr' target='#b72'>(Kaya et al., 2018)</ns0:ref>, spaTyper 1.0 <ns0:ref type='bibr' target='#b12'>(Bartels et al., 2014)</ns0:ref> for spa type and MLST 1.8 <ns0:ref type='bibr' target='#b83'>(Larsen et al., 2012)</ns0:ref> for Multilocus Sequence Type in a web-based server provided by the Center for Genomic Epidemiology (https://cge.cbs.dtu.dk/services/). In-silico arg (accessory gene regulator)-typing was performed using the primers described by <ns0:ref type='bibr' target='#b134'>Shopsin et al. (Shopsin et al. 2003)</ns0:ref> in in-silico PCR amplification tools <ns0:ref type='bibr' target='#b16'>(Bikandi et al., 2004)</ns0:ref>.</ns0:p><ns0:p>The genome assemblies were screened for plasmid replicon (rep) genes using PlasmidFinder 2.1 <ns0:ref type='bibr' target='#b25'>(Carattoli et al., 2014)</ns0:ref> with default parameters. The identified nonaligned contig or scaffold associated with plasmid sequences were extracted and used for the identification of full-length plasmid regions using PLSDB (Plasmid Database) version-2020-03-04 <ns0:ref type='bibr' target='#b47'>(Galata et al., 2018)</ns0:ref> with search strategy Mash screen, and the default values were a maximum P-value of 0.1 and a minimum identity of 0.99 (https://ccb-microbe.cs.uni-saarland.de/plsdb/). Identified plasmids were compared with the closest reference plasmids using Easyfig version 2.2.3 <ns0:ref type='bibr' target='#b140'>(Sullivan et al., 2011)</ns0:ref>. The identification and annotation of prophage sequences were performed by screening the genome assemblies using PHASTER (PHAge Search Tool Enhanced Release) <ns0:ref type='bibr' target='#b8'>(Arndt et al., 2016)</ns0:ref> and identified template phages were classified for their lifestyles using PHACTS (Phage Classification Tool Set) <ns0:ref type='bibr' target='#b100'>(McNair et al., 2012)</ns0:ref>.</ns0:p><ns0:p>In-silico mining of candidate ARGs and VFGs were performed using CARD (Comprehensive Antibiotic Resistance Database) version 3.0.8 in RGI (Resistance Gene Identifier) version 5.1.0 platform (https://card.mcmaster.ca/analyze/rgi) <ns0:ref type='bibr'>(Alcock et al., 2020)</ns0:ref> and comprehensive set of S.</ns0:p><ns0:p>aureus VFGs was analyzed using VFDB (Virulence Factor Database) in VFanalyzer <ns0:ref type='bibr' target='#b30'>(Liu et al., 2019)</ns0:ref> and the PATRIC tool version 3.6.3 (https://www.patricbrc.org/) <ns0:ref type='bibr' target='#b122'>(Wattam et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Further, heatmap and hierarchical clustering were generated to visualize the presence and absence of VFGS and ARGs in S. aureus strains using a web-based application, Morpheus, (https://software.broadinstitute.org/morpheus). Secondary metabolite biosynthesis gene clusters and the detection of genes encoding bacteriocins were analyzed using antiSMASH 5.0 <ns0:ref type='bibr'>(Blin et al., 2019) and</ns0:ref><ns0:ref type='bibr'>BAGEL4 (Van Heel et al., 2018)</ns0:ref>. The prediction of chromosomal genomic islands was predicted by using IslandViewer 4 <ns0:ref type='bibr' target='#b15'>(Bertelli et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparative genomic analysis</ns0:head><ns0:p>The ANI was determined based on BLAST+ using the JSpeciesWS webserver <ns0:ref type='bibr'>(Richter et al., 2016)</ns0:ref>. The pairwise comparisons between the genomes of S. aureus isolates and their nearest reference genomes were conducted using GBDP (Genome BLAST Distance Phylogeny) under the algorithm trimming and distance formula d5, and calculated each distance with 100 replicates <ns0:ref type='bibr' target='#b103'>(Meier-Kolthoff et al., 2013)</ns0:ref>. dDDH (Digital DNA-DNA Hybridization) values and confidence intervals were calculated using the recommended settings of the GGDC 2.1 <ns0:ref type='bibr' target='#b103'>(Meier-Kolthoff et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Genomes of S. aureus isolates and their reference strains were compared with CGViewer (Circular Genome Viewer) server <ns0:ref type='bibr' target='#b55'>(Grant et al., 2008)</ns0:ref>. The functional annotation was performed using EggNOG (Evolutionary Genealogy of Genes: Non-supervised Orthologous Groups) mapper 5.0 database <ns0:ref type='bibr'>(Huerta-Cepas et al., 2019)</ns0:ref> and RAST server-based SEED viewer <ns0:ref type='bibr'>(Overbeek et al., 2014)</ns0:ref>.</ns0:p><ns0:p>The pan-genome, core-genome, and singletons were calculated using four study genomes of S. aureus isolates in EDGAR version 2.0 software framework <ns0:ref type='bibr' target='#b18'>(Blom et al., 2016)</ns0:ref>. This pangenome analysis was extended using four study genomes coupled with three reference genomes of S. aureus strains. The core-genome was analyzed in the genomes set using reciprocal best BLAST hits of all CDS using EDGAR version 2.0 software framework <ns0:ref type='bibr' target='#b18'>(Blom et al., 2016)</ns0:ref>. The singletons were calculated for the contig of a strain by comparing to the CDS of a set of contigs in EDGAR. The CDS that has no match with SRV (Score Ratio Value Plots) higher or equal the master cut-off in any of the contigs were considered as singletons. The development of pangenome and core-genome sizes was analyzed using the core/pan development feature and as well, the pan vs. core development plot was generated in EDGAR. Heap's Law function was applied to calculate whether the pan-genome open or closed using the equation n=k*N^ <ns0:ref type='bibr'>(-&#945;)</ns0:ref> where n= expected a number of genes; N= number of genomes; k and &#945; (&#945; =1-&#947;) are proportionality constant and exponent, respectively <ns0:ref type='bibr' target='#b143'>(Tettelin et al., 2008</ns0:ref>). Heap's law predicted that closed pan-genome (when &#945; &gt; 1 (&#947; &lt; 0)), and open pan-genome (when &#945; &lt; 1 (0 &lt; &#947; &lt; 1)).</ns0:p><ns0:p>According to <ns0:ref type='bibr' target='#b143'>Tettelin et al., 2008</ns0:ref>, core-genome and singletons developments were calculated by the least-square fitting of exponential decay functions.</ns0:p><ns0:p>The Rcp (ratio of core-genome to that of pan-genome) was calculated <ns0:ref type='bibr' target='#b51'>(Ghatak et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Then, genomic subsets, including the number of core-genome and singletons in the gene pool, were extracted, and flowerplot was drawn using in-house R scripts.</ns0:p></ns0:div> <ns0:div><ns0:head>Phylogenetic analysis</ns0:head><ns0:p>The genome assemblies of the isolates were used for a whole genome-based phylogeny analysis using TYGS (Type/Strain Genome Server) (Meier-Kolthoff and G&#246;ker, 2019) engaging with genomes of closely related strains of S. aureus. The phylogenomic trees were reconstructed using FastME 2.1.6.1 <ns0:ref type='bibr' target='#b84'>(Lefort et al., 2015)</ns0:ref> from the GBDP (Genome BLAST Distance Phylogeny) distances calculated from genome sequences under the algorithm 'coverage' and distance formula d5 <ns0:ref type='bibr' target='#b103'>(Meier-Kolthoff et al., 2013)</ns0:ref>. The trees were rooted at the midpoint <ns0:ref type='bibr' target='#b43'>(Farris, 1972)</ns0:ref>; branch supports were inferred from 100 pseudo-bootstrap replicates and visualized with Interative Tool Of Life v4 (iTOL) <ns0:ref type='bibr' target='#b86'>(Letunic and Bork, 2019)</ns0:ref>. The core SNPs of genome sequences were extracted using Panseq <ns0:ref type='bibr' target='#b82'>(Laing et al., 2010)</ns0:ref> and the phylogenetic tree was constructed using PhyML+SMS module in NGPhylogeny.fr <ns0:ref type='bibr' target='#b85'>(Lemoine et al., 2019)</ns0:ref> to select the best evolutionary model, further the tree was annotated in Interative Tool Of Life v4 (iTOL) <ns0:ref type='bibr' target='#b86'>(Letunic and Bork, 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The S. aureus isolates could survive at pH 4.5 trough pH 9.5 conditions with a survival rate of 45% -84%. SA G8 isolate showed the highest cell survival rate of 84.4% at acidic pH but its cell survival rate drops down by 7% when subjected to alkaline pH conditions.</ns0:p></ns0:div> <ns0:div><ns0:head>General genomic features of S. aureus isolates</ns0:head><ns0:p>The genomic DNA of S. aureus isolates was successfully sequenced in the IonTorrent PGM sequencing platform and the average raw reads obtained from the genome of SA G6, SA G8, SA <ns0:ref type='bibr'>H27,</ns0:ref><ns0:ref type='bibr'>and SA H32 are ~ 88.9,</ns0:ref><ns0:ref type='bibr'>69.6,</ns0:ref><ns0:ref type='bibr'>128.3 and 92.7 million bases (Mb)</ns0:ref> for genomes of SA G6, SA G8, SA H27, and SA H32 strains respectively. The closely related strains identified by kmerFinder 2.0 were S. aureus subsp. aureus ST228 (HE579073) for SA G6, S. aureus subsp. aureus JH9 (CP000703) for SA G8, and S. aureus subsp. aureus S. aureus subsp. aureus HO 5096 0412 (HE681097.1) for SA H27 and SA H32. Amongst the S. aureus isolates, SA G8 isolate possesses the largest genome size (28633393 bp) with a %GC content of 32.81%. The numbers of protein-coding sequences (CDSs) in the S. aureus strains varied from 2630 (SA H27) to 2743 (SA G8). The comparison of draft genome assemblies, genome annotation, epidemiologic characteristics, plasmid, and prophage features for S. aureus genomes were summarized in Table <ns0:ref type='table'>1</ns0:ref>. <ns0:ref type='table'>PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head></ns0:div> <ns0:div><ns0:head>Genes encoding plasmids</ns0:head><ns0:p>The putative plasmids were detected in nonaligned contigs or scaffolds that exhibited an unexpected high coverage level after the genome assemblies. A putative plasmid (p1G6) of 13331bp length was identified at Scaffold 4 of the SA G6 genome consisting of the replication gene (repA). The p1G6 plasmid has 30.97% sequence coverage with plasmids pTW20_1 (FN433597.1) in NCBI database (Fig. <ns0:ref type='figure' target='#fig_7'>1A</ns0:ref>). The p1G6 plasmid being small size, showed low sequence similarity to pTW20_1, it is quite evident that this plasmid has similarity in gene contents and physical distribution. The sequence coverage region of p1G6 with pTW20_1 constitutes the genes that encode for proteins such as IS6 family transposase, replicationassociated protein (Rep), cadmium resistance transporter (CadD), cadmium efflux system accessory protein (CadX), replication initiation protein A (RepA), quaternary ammonium compound efflux MFS transporter (QacA), multidrug-binding transcriptional regulator (QacR), DUF536 domain-containing protein (mP), AAA family ATPase (Abp), hypothetical proteins, HAD hydrolase family protein, and IS257 family transposase. The SA H32 genome also consists of a putative plasmid (p2H32) having a length of 2530 bp located at Scaffold 3 and showed 71.32% sequence coverage with plasmids AR_0472 (NZ_CP029648.1). It consists of a replication gene (repL) and carried an erythromycin resistance gene (emrC) (Fig. <ns0:ref type='figure' target='#fig_7'>1B</ns0:ref>). The identified plasmids of S. aureus encode no other factors for their transfer, such plasmids may transfer via a phage <ns0:ref type='bibr' target='#b98'>(McCarthy and Lindsay, 2012)</ns0:ref>. The linear graphical map of plasmid comparison was represented in Fig. <ns0:ref type='figure' target='#fig_7'>1</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Characteristic of prophages-like elements</ns0:head><ns0:p>The genomes of S. aureus isolates have several prophages and phage-like element regions and these prophages were belonged to the Siphoviridae family and having temperate lifestyles. The highest number of prophage regions was found in the genome of SA G8 isolate including three intact prophages (phiG8.2, phiG8.3, and phiG8.4), a questionable (phiG8.1), and an incomplete (phiG8.5) prophages. Four prophage regions were found in the genome of SA G6 isolate including an intact prophage (phiG6.3), two questionable prophages (phiG6.1 and phiG6.4), and an incomplete prophage (phiG6.2). The genome of SA H27 isolate harbor three intact prophages (phiH27.1, phiH27.2, and phiH27.3) while the genome of SA H32 harbor only one intact prophage (phiH32.1). The lukF-PV and lukM genes (Bicomponent leukotoxins), and plc gene (Phospholipase C) were identified in the prophages of phiG6.4, phiG8.4, phiH27.2, and phiH32.1. The prophages of phiG6.3, phiG8.4, and phiH27.2 carried sak gene (staphylokinase) and scn gene (staphylococcal complement inhibitor). Chemotaxis inhibitory protein encoded by chp gene was identified in phiG8.4 and phiH27.2 prophages. Enterotoxin A encoded by sea gene was harbored by the prophages of phiG6.3 and phiG8.4. Hemolysin genes such as hlb (&#946;hemolysin), and hlgB (-hemolysin B) were found in the prophages of phiH27.2, and phiH32.1.</ns0:p><ns0:p>In addition to virulence factors, phiG6.4 prophage carried ARGs genes that conferred resistance to beta-lactamase (blaZ), aminoglycoside (ant(6)-Ia and aph(3')-III) and nucleoside (sat-4) antibiotics. The comparative analysis of VFGs associated with putative prophages was summarized in Table <ns0:ref type='table'>S1</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>In-silico analysis of antimicrobial resistance and associated genes in the genomes</ns0:head><ns0:p>Four study genomes of S. aureus isolates shared 63.3% (19/30) of antibiotic resistance and associated genes (Fig. <ns0:ref type='figure' target='#fig_8'>2</ns0:ref>). The shared genes comprise methicillin-resistant PBP2a (mecA and mecR1); multidrug resistance efflux (ygaD); fluoroquinolone (norA and gyrA); fluoroquinolone and acridine dye (arlS and arlR); glycylcycline (mepA); tetracycline (tet-38); tetracycline, penam, cephalosporin, glycylcycline, rifamycin, phenicol, triclosan, fluoroquinolone (mgrA and marR); lipopeptide (pgsA, clsA and rpoC); rifampicin (rpoB); aminocoumarin (gyrB and parE); dihydrofolate reductase (dfrA/folA) and defensin (mprF/fmtC, multiple peptide resistance factor) that play roles in resistance mechanism including antibiotic efflux, antibiotic target alteration, and antibiotic target replacement. The comparative analysis of ARGs revealed that the genome of SA G6 isolate acquired additional ARGs responsible for the resistance of aminoglycoside (aph (3')-IIIa, ant (6')-I and aac (6')-II), nucleoside (sat), fluoroquinolone (qacA). The macrolide, lincosamide, streptogramin (MLS) erythromycin antibiotic resistance genes (emrA) were detected in the genomes of SA G6 and SA G8 isolates while the genome of SA H32 isolate present emrC gene. The penicillin resistance gene (blaZ) was found absent in SA G8 isolate. This in-silico identification and antibiotic susceptibility test results were correlated with betalactam, erythromycin (MLS), and vancomycin antibiotic resistance analysis. The secondary metabolite biosynthetic gene clusters identified among the genomes were staphylobactin, aureusimine, bacteriocin, and staphyloferrin A. The auto-inducing peptide (AIP)-II gene was identified in SA G6 and SA G8 genomes while AIP-I gene was identified in SA H27 and SA H32 genomes. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>In-silico analysis of virulence-factors encoding genes in the genomes</ns0:head><ns0:p>The VFGs predicated against the VFDB revealed 59 VFGs were shared in all strains that are responsible for adherence, toxin, anti-phagocytosis immune evasion, secretion system, exoenzyme activity, and iron uptake (Fig. <ns0:ref type='figure'>3</ns0:ref>). The genome of SA G8 isolate has occupied 3.40% of VFGs against its CDS, whereas the genome of SA H32 isolate has 2.97% of VFGs against its CDS.</ns0:p><ns0:p>Adherence associated genes shared in all genomes of S. aureus isolates were 63.63% (14/22) such as autolysin (atl), cell wall-associated fibronectin-binding protein (ebh), elastin binding protein (ebp), fibrinogen binding protein (efb), fibronectin-binding proteins A (fnbA), intercellular adhesin (icaA, icaB, icaC, icaD, icaR), ser-Asp rich fibrinogen-binding proteins (sdrC, sdrD, sdrE), staphylococcal protein A (spa) (Fig. <ns0:ref type='figure'>3A</ns0:ref>). The genome of SA G8 isolates present 77.27% (17/22) of adherence associated genes with additional genes of clumping factor A (clfA), clumping factor B (clfB), and fibronectin-binding proteins (fnbB). Type VII secretion system involves in membrane-associated proteins (esaA, essA, essB, and essC), soluble cytosolic (esaB, esaE, esaG), and secreted virulence factors (esxA, esxB, esxC, esxD, and esaD) were identified in the genomes of SAG6 and SA G8 isolates while the SAH27 and SAH32 isolates absence esaD, esaE, esxB, esxC, and esxD genes (Fig. <ns0:ref type='figure'>3A</ns0:ref>).</ns0:p><ns0:p>The genomes of all isolates shared 29.41% (10/34) of toxin genes such as alpha-hemolysin gene (hla), beta-hemolysin gene (hlb), delta hemolysin gene (hld), gamma hemolysin A (hlgA), gamma hemolysin B (hlgB), gamma hemolysin C (hlgC), enterotoxin-like O (selo), exfoliative toxin type A (eta), and exotoxin (set13, set15) (Fig. <ns0:ref type='figure'>3B</ns0:ref>). The highest number of toxin genes were identified in the genome of SA G8 i.e., 73.52% (25/34) and in addition to shared genes, the extra genes were enterotoxin A (sea), enterotoxin B (seg), enterotoxin Yent1 (yent1), enterotoxin-like K (selk), enterotoxin-like M (selm), enterotoxin-like N (seln), exotoxin (set6, set7, set9, set11, set34, set37, set39), leukotoxin D (lukD), Panton-Valentine leukocidin (lukF-</ns0:p></ns0:div> <ns0:div><ns0:head>PV).</ns0:head><ns0:p>The genes involve in anti-phagocytosis namely capsular polysaccharide synthesis genes belong to stereotype 5 and 8 predominantly present in all the genomes of isolates were capsular polysaccharide synthesis enzyme Cap5A (cap8A), capsular polysaccharide synthesis enzyme Cap5B (cap8B), capsular polysaccharide synthesis enzyme Cap5C (cap8C), probable polysaccharide biosynthesis protein EpsC (cap8D), capsular polysaccharide synthesis enzyme Cap8E (cap8E), capsular polysaccharide synthesis enzyme Cap5F (cap8F), UDP-N-acetyl-Lfucosamine synthase (cap8G), capsular polysaccharide synthesis enzyme Cap5L (cap8L), capsular polysaccharide synthesis enzyme Cap8M (cap8M), capsular polysaccharide synthesis enzyme Cap8N (cap8N), UDP-N-acetyl-D-mannosamine dehydrogenase (cap8O) and UDP-Nacetylglucosamine 2-epimerase (cap8P) (Fig. <ns0:ref type='figure'>3C</ns0:ref>). Other genes responsible for the host immune evasion such as IgG-binding protein (sbi), staphylococcal complement inhibitor (scn), and chemotaxis inhibiting protein (chp) were identified in all isolates.</ns0:p><ns0:p>Several exoenzymes encoding genes namely cysteine protease/ staphopain (sspB, sspC), hyaluronate lyase (hysA), lipase (geh, lip) serine V8 protease (sspa), staphylocoagulase (coa), staphylokinase (sak) and thermonuclease (nuc) were present in the genomes of all isolates.</ns0:p><ns0:p>However, five genes cluster for serine protease <ns0:ref type='bibr'>(splA, splB, splC, splD, splF)</ns0:ref> were absent in the genomes of SA H27 and SA H32 isolates (Fig. <ns0:ref type='figure'>3C</ns0:ref>).</ns0:p><ns0:p>Eight genes involved in iron uptake mechanism including cell surface protein (isdA), cell surface receptor (isdB) and cell wall anchor proteins (isdC), heme transporter component (isdD), highaffinity heme uptake system protein (isdE), heme-iron transport system permease protein (isdF), sortase B (srtB), heme-degrading monooxygenase; staphylobilin-producing (isdG) were identified in all the genomes of isolates.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparative genome analysis</ns0:head><ns0:p>The genome comparative analysis based on ANIb matrices results indicated that the genome of SA G8 isolate exhibits the nearest identities to all genomes, and the SA G8 genome showed ~99.5% identities to SA G6 genome. S. aureus subsp. aureus ST228 (HE579071.1) genome exhibited ~99.7% identities to the genomes of SA G6 and SA G8. Also, the genomes of SA H27 and SA H32 showed 99.9% identities to each other and these two genomes displayed the highest identities (99.9%) to S. aureus subsp. aureus HO 5096 0412 (HE681097.1). S. aureus subsp. aureus JH9 (CP000703.1) exhibits the nearest identities (99.03%) to all the genomes (Fig. <ns0:ref type='figure' target='#fig_7'>S1</ns0:ref>).</ns0:p><ns0:p>The digital DDH values between the genome of S. aureus isolates and the closest relative genomes were 90.7-100% (using GBDP distance formula d0), 77.1-97.0% (using GBDP distance formula d4) and 91.1-99.9% (using GBDP distance formula d6). SA H27 and SA H32 genomes exhibit the nearest identities of 99.9%, 99.8%, and 100 % using the formula d0, d4, and d6 respectively and displayed G+C difference of 0.01%. However, the SA G6 genome showed Manuscript to be reviewed less identity to all the comparative genomes based on dDDH. The high G+C constituent difference (0.1%) was observed in the case of isolated strains of SA G8 and SA H32 genomes.</ns0:p><ns0:p>A whole-genome circular comparative map of four S. aureus genomes and their close reference genomes was generated against S. aureus subsp. aureus HO 5096 0412 (HE681097.1) genome using CGView server based on BLAST sequence similarities. Each genome was indicated by a different color, and the darker areas in the circular genome showed a 100% sequence similarity with the reference genome, while the lighter (gray) areas showed a 70% sequence similarity (Fig. <ns0:ref type='figure'>4</ns0:ref>). The map revealed less gap between the SA H27 (CP032161) and SA H32 (RAHP00000000) genomes showing high proximity between them when compared to other genomes. SA G6 (RAHA00000000) genome has many gaps with white color than the other genomes showing a distant relationship.</ns0:p><ns0:p>The SEED subsystem categories identified by RAST revealed that the genomes of all the isolates possessed 'amino acids and derivatives' was the largest subsystem, followed by 'carbohydrates', 'protein metabolism', and 'cofactors, vitamins, prosthetic groups, pigments' (Fig. <ns0:ref type='figure'>5A</ns0:ref>). The 'carbohydrate', and 'protein metabolism' subsystems were found largest in SA H27 (12.76%) and SA H32 (10.47%) genomes, respectively. Subsystem belongs to 'phages, prophages, pathogenicity island' (2.5%) was identified as highest in the SA G8 genome.</ns0:p><ns0:p>Amongst the genomes, the SA G6 genome has the largest subsystem of 'amino acids and derivatives' (15.9%), and 'virulence, disease, and defense' (4.43%). In the 'virulence, disease, and defense' subsystem of SA G6, 93 genes associated with adhesion, bacitracin stress response, colicin v, and bacteriocin production cluster, copper homeostasis, bile hydrolysis, cobalt-zinccadmium resistances, multidrug resistances, 2-protein, mercuric reductase, mercury resistance operon, streptothricin resistance, teicoplanin-resistances, aminoglycoside adenylyltransferases, fluoroquinolone resistances, arsenic resistance, fosfomycin resistance, beta-lactamase, cadmium resistance, multidrug resistance efflux pumps, and invasion and intracellular resistances. In the comparative eggNOG function study of S. aureus genomes, 'amino acid transport and metabolism' was observed as for the majority of COGs, followed by those COGs related to 'translation, ribosomal structure, and biogenesis', 'transcription', and 'cell wall/membrane/envelope'. The eggNOG analysis results revealed that the SA G6 genome has the highest number of COGs associated with defense mechanisms (Fig. <ns0:ref type='figure'>5B</ns0:ref>). In the core genomes, 9.46%, 7.21%, and 6.9% of COGs had functions associated to 'amino acid transport Manuscript to be reviewed and metabolism (E)', 'translation, ribosomal structure, and biogenesis (J)', and 'transcription (K)', respectively. Amongst the functional prediction of genomes, most COGs were associated with 'function unknown (S)'.</ns0:p></ns0:div> <ns0:div><ns0:head>Pan-genome, core-genome, and singletons analysis</ns0:head><ns0:p>The orthologous groups are categories into three groups based on the pan-genome distribution such as core (present in all genomes of S. aureus strains), dispensable (present in at least two strains, but not all), and singleton genes (present no orthologs in any other genomes). The comparison of four study S. aureus genomes generated a pan-genome size of 3265 genes, of which 2304 (70.6%) genes were core genome, 462 (14.2%) genes were dispensable, and 499 (15.3%) genes were singletons. The Rcp value for the genomes of S. aureus isolates was calculated and the ratio Rcp was 0.70 and it is indicated that the genomes of S. aureus isolates were high inter-species diversity. A total of 499 singleton genes were calculated across the genomes of four S. aureus isolates, of which SA G6 genome acquired the highest number of singleton genes (143) that constitute the genes encode for proteins viz. aminoglycoside 3phosphotransferase, aminoglycoside 6-phosphotransferase, aminoglycoside N(6)acetyltransferase, streptothricin acetyltransferase, antiseptic resistance protein, cadmium resistance proteins, cadmium efflux system accessory protein, cadmium-transporting ATPase, ferric siderophore transport system, mercuric ion reductase, anti-adhesin, Tn552 transposase, pathogenicity islands (SaPI and SaPIn2), prophage-like elements, mobile elements, phage associated hypothetical proteins, hypothetical proteins, etc. These singleton genes were detected within the genomic island (GI) located between 2804353-2873411base pair sequence region of genomic sequence and this GI was an unaligned region with reference strains S. aureus subsp. aureus ST228. While the SA H27 genome has the least singleton genes (6) constituting the genes encode for hypothetical proteins and phage proteins. The difference in the genomic constituents between the genome of SA H27 and SA H32 isolates revealed that SA H32 acquired the genes encoding for 23S rRNA (adenine(2058)-N(6))-dimethyltransferase, replication and maintenance protein, hypothetical proteins, phage-like elements, and mobile element protein. The genes shared by four study genomes and their respective singletons is represented in Fig. <ns0:ref type='figure'>6A</ns0:ref>. When the three reference S. aureus genomes were included in the pan-genome analysis, the core/pangenome ratio drop down by 18.97% with inflation of pan-genome to 3415 genes and deflation of core-genome to 1762 genes. The core-genome and singleton genes formed by seven genomes of Manuscript to be reviewed S. aureus strains is represented in flower plot (Fig. <ns0:ref type='figure'>6B</ns0:ref>). When the three reference genomes of S. aureus strains were included in the pan-genome analysis, SA G6 isolate occupied the highest number of singleton genes (104) while SA H27 isolate has the lowest singleton gene (2) (Fig. <ns0:ref type='figure'>6B</ns0:ref>). In the pan-genome development analysis of seven S. aureus strains, &#945; value (the power-law co-efficient) was estimated as 0.141 which corresponds to the growing and open pan-genome model (Fig. <ns0:ref type='figure' target='#fig_8'>S2</ns0:ref>). The pan vs. core development plot appeared the progression of the pan and core-genomes as additional genomes are added for analysis, and showing that the sharp decline of the core-genome size with the introduction of S. aureus subsp. aureus ST228 (HE579073) (Fig. <ns0:ref type='figure'>6C</ns0:ref>). In the plot of core-genome development, the core-genome size approach (&#937;) value revealed that the core-genome size of seven S. aureus would be declined to 1404.8 (Fig. <ns0:ref type='figure'>S3</ns0:ref>). The singleton development analysis suggested that the pan-genome size will continue to expand at the rate of 35.9 genes per novel, representative genome (Fig. <ns0:ref type='figure'>S4</ns0:ref>). The shape of the pan-genome vs. core-genome curve showed fluctuation in their gene numbers when different order of the genomes was set, even so, pan-genome and core genome developmental plots result remained unaffected by the genomes order.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparative phylogenetic tree analysis</ns0:head><ns0:p>The phylogenomic analysis of S. aureus isolates provide the tree into three major clades (Fig. <ns0:ref type='figure'>7A</ns0:ref>). The clade A consists of 5 strains that belonged to CC22 and showing that Hungarian isolates, SA H27 and SA H32 have the highest proximity. Germany isolates, SA G6 and SA G8 isolate and other strains belonged to CC5 were clustered in the clade C, showing that SA G6 isolate has closely relatedness to S. aureus subsp. aureus ST228 (HE579071.1) and the SA G8 isolate has a higher relatedness to S. aureus subsp. aureus JH9 (CP000703.1) than SA G6 isolate.</ns0:p><ns0:p>The phylogenetic relationship inferred from core-genome SNPs holds a similar agreement with the whole genome-based phylogenetic analysis, and these methods could be useful in distinguishing the genomes even in the strain level and phylogenetic trees are illustrated in Fig.</ns0:p></ns0:div> <ns0:div><ns0:head>7B.</ns0:head></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>S. aureus is a significant causative agent of both hospital and community-associated infections <ns0:ref type='bibr' target='#b28'>(Chambers and DeLeo, 2009)</ns0:ref>. The study of such pathogen at a molecular level through genome comparative analysis improve the ideas of pathogenesis and evolution. Further, such a study provides advantages in diagnosis, treatments, and infection controls <ns0:ref type='bibr' target='#b79'>(Kwong et al., 2015)</ns0:ref>. In the present study, we used whole-genome sequencing (WGS) and in-silico analysis to determine the comparative ARGs, VRGs, pH tolerance associated genes, and evolutionary relationship of four S. aureus isolated from different sites of human infection such as skin, nostril, trachea, and others.</ns0:p><ns0:p>The molecular epidemiology study of MRSA helps to find the risk factors associated with MRSA infections and able to differentiate the several MRSA strains <ns0:ref type='bibr' target='#b106'>(Mistry et al., 2016)</ns0:ref>. The genome-based molecular epidemiology studies found that Germany isolates exhibit SCCmec type I with ST228, and SCCmec type II with ST225 while Hungarian isolates hold SCCmec type IVa with ST22. Also, agr type II and I were owned by Germany and Hungarian isolates, respectively (Table <ns0:ref type='table'>1</ns0:ref>). According to previous studies suggested that MRSA strains with SCCmec types I or II or III are dominant among the HA-MRSA, while SCCmec types IV or V are the characteristic of CA-MRSA <ns0:ref type='bibr' target='#b107'>(Monecke et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b34'>Chua et al., 2014)</ns0:ref>. The STs of Germany isolates belonged to CC5 which is typical of HA-MRSA, while Hungarian isolates suggest its relationship CA-MRSA. In hospitals, the multidrug-resistance SCCmec type III was replaced by the multidrug-susceptible SCCmec type IV (ST22) strains slowly <ns0:ref type='bibr'>(D'Souza et al., 2010)</ns0:ref>. The Hungarian isolates were found positive to Panton-Valentine Leukocidin (PVL) toxin, which is commonly used as a marker of CA-MRSA <ns0:ref type='bibr' target='#b135'>(Shukla et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b137'>Singh et al., 2015)</ns0:ref> besides this toxin has shown to play role necrosis, accelerating apoptosis and polynuclear-and mononuclear cells lysis, thereby contributing morbidity and mortality <ns0:ref type='bibr' target='#b11'>(Barrera-Rivas et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b88'>Lina et al., 1999)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Staphylococcal beta-lactamase encoded by blaZ gene is carried by the transposon Tn552 or</ns0:head><ns0:p>Tn552-like elements located on a large plasmid and can be non-inducible or inducible with antibiotics <ns0:ref type='bibr' target='#b95'>(Maddux, 1991)</ns0:ref>. It was noticed that blaZ gene was absent in SA G8 isolate, probably due to the curing of blaZ positive plasmid <ns0:ref type='bibr' target='#b127'>(Pugazhendhi et al., 2020)</ns0:ref>. Erythromycin resistance gene (ermA) was detected in the chromosome of SA G6, and SA G8 isolates, however, emrC gene was found in the plasmid of SA H32 (Fig. <ns0:ref type='figure' target='#fig_7'>1B</ns0:ref>). It was suggested that these genes may not be involved in the loss of specific ARGs for environmental adaptation, but it is expected to be essential for these isolates <ns0:ref type='bibr' target='#b87'>(Lim et al., 2015)</ns0:ref>.</ns0:p><ns0:p>MRSA is responsible for causing biofilm infections that are more difficult to treat and need more intensive care as compared to Staphylococcus epidermidis biofilm <ns0:ref type='bibr' target='#b128'>(Reffuveille et al., 2017)</ns0:ref>. The Manuscript to be reviewed principal component of biofilm formation is PIA which consists of different intracellular adhesion (ica) genes <ns0:ref type='bibr' target='#b36'>(Cramton et al., 1999)</ns0:ref> and play a crucial role in the initial stage of bacterial cell adherence to surfaces and intercellular adhesion for the cells to aggregate <ns0:ref type='bibr' target='#b42'>(Farran et al. 2013</ns0:ref>). These genes were detected in all isolates however, the biofilm production ability varies from weak to strong were observed. SA G6 isolate obtained from skin infection showed a weak biofilm-forming ability. The low biofilm formation in SA G6 might be degraded the biofilm by DNase enzyme found in skin cells <ns0:ref type='bibr' target='#b41'>(Eckhart et al., 2007)</ns0:ref>. The previous study revealed that the presence of the ica genes did not always correlate with biofilm <ns0:ref type='bibr' target='#b109'>(M&#248;retr&#248; et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b113'>Nasr et al., 2012)</ns0:ref>. Some authors reported that despite the presence of ica operon, some staphylococcal isolates produce weak biofilm production due to the inactivation of icaA by insertion of IS256 <ns0:ref type='bibr' target='#b33'>(Cho et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b74'>Kiem et al., 2004)</ns0:ref>. Further reported that the insertion of IS256 inactivates mutS and contributes to vancomycin resistance development in vancomycin-intermediate S.</ns0:p><ns0:p>aureus strains <ns0:ref type='bibr' target='#b76'>(Kleinert et al., 2016)</ns0:ref>. Also, the upregulation of icaA and icaD genes during acidic stress promotes biofilm formation which in-turn plays a role to resist it from acidic and alkaline environments and establishes the niche adaptation in Staphylococcus strains <ns0:ref type='bibr' target='#b91'>(Lindsay et al., 2006)</ns0:ref>. In addition to ica locus, the presence of clfA, clfB, and epbs genes initiates the biofilm formation <ns0:ref type='bibr' target='#b49'>(Ghasemian et al., 2015)</ns0:ref>, however in the present study, the SA H27 isolate carried clfA, and epbs genes and showed strong biofilm formation compared to other isolates while SA G8 and SA H32 isolates carried clfA, clfB, and epbs genes though their biofilm formation was relatively low, suggesting that presence or absence of such genes have no significant in biofilm formation. A recent study reported that sdrC mutant exhibited significantly inhibited biofilm formation <ns0:ref type='bibr' target='#b30'>(Chen et al., 2019)</ns0:ref> and the expression of the ica operon and sdrC are highly responsive to biofilm formation <ns0:ref type='bibr' target='#b133'>(Shin et al., 2013)</ns0:ref>. Our study revealed the sequence variation in sdrC in Hungarian isolates, this variation might influence the biofilm formation. The global regulatory gene, agr repression has been associated with biofilm formation and its induction through AIP results in seeding dispersal in mature biofilm <ns0:ref type='bibr' target='#b19'>(Boles and Horswill, 2008)</ns0:ref>. CA-MRSA strains showed higher activity of agr, which controls and enhance the virulence (Aires-De-Sousa, 2017). It was reported that S. aureus strains belonged to agr I group exhibited a strong biofilm-forming ability than the strains belonged to agr IV group <ns0:ref type='bibr' target='#b153'>(Zhang et al., 2018</ns0:ref>) and a similar result was observed in one of our isolate SA H27. In addition to this extracellular adherence protein (encoded by eap gene), and beta toxin (encoded by hlb gene) play a role in biofilm maturation <ns0:ref type='bibr' target='#b66'>(Huseby et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b138'>Sugimoto et al., 2013)</ns0:ref>. In our finding showed that eap gene was present only in the SA H27 isolate and this gene might be attributed to high biofilm formation. Since biofilm formation involves many factors/ genes that take part in PIA dependent or independent biofilm, biofilm formation by regulator genes and eDNA <ns0:ref type='bibr' target='#b6'>(Archer et al., 2011)</ns0:ref>. Also, the presence of such genes in S. aureus may not provide much impact on biofilm formation profiling. There was a difference in the prevalence of biofilm-associated genes between the isolated strains and suggests that the presence of genes encoding biofilm formation is not an absolute determinant of biofilm formation ability. Thus, our future studies will focus on the expression profiling of such relevant genes which may be necessary to determine the key genes involved in biofilm formation. The high survival rates were observed in both acidic and alkaline pH conditions in all isolates was evaluated by the genomic study, it is elucidated that all the isolates possessed the arginine deiminase and urease operon that aids in the generation of ammonia due to the hydrolysis of Larginine and urea by arginine deiminase and urease. The released ammonia and urea counteract the acidic environment <ns0:ref type='bibr' target='#b35'>(Cotter and Hill, 2003;</ns0:ref><ns0:ref type='bibr' target='#b144'>Valenzuela et al., 2003)</ns0:ref>. Further, the proton efflux pump (F&#8320;F&#8321; ATPase) plays a role to extrude H&#8314; out of the cells and maintains the pH homeostasis <ns0:ref type='bibr' target='#b46'>(Foster, 2004;</ns0:ref><ns0:ref type='bibr' target='#b96'>Maurer et al., 2005)</ns0:ref>. However, in the case of alkaline tolerance, it was reported that the S. aureus genome encodes a unique Ktr-like system where the cytoplasmic gating protein KtrC regulates the uptake of K&#8314; that is essential for maintaining cytoplasmic pH and supporting H&#8314; efflux under alkaline conditions <ns0:ref type='bibr' target='#b56'>(Gries et al., 2016)</ns0:ref>.</ns0:p><ns0:p>The ability of S. aureus as a pathogen can be accredited to its arsenal of virulence factors among which secreted pore-forming toxins (PFTs), exfoliative toxins (ETs), ESAT-6-like proteins, exoenzymes and superantigens (SAgs) play a significant role in the pathogenesis of invading infections in healthy individuals <ns0:ref type='bibr' target='#b120'>(Otto et al., 2014</ns0:ref><ns0:ref type='bibr'>, Bartiett et al., 2010)</ns0:ref>. The presence of hlb gene in the isolates contributes to the phagosomal escape of S. aureus and influences biofilm development <ns0:ref type='bibr' target='#b66'>(Huseby et al., 2010</ns0:ref><ns0:ref type='bibr' target='#b126'>, Periasamy et al., 2012)</ns0:ref>. The PVL toxin was identified in the prophages of Hungarian isolates and expressing Sa2 integrase. These isolates have cytolytic activity against blood cells and leukocytes, contributing to the S. aureus pathogenicity <ns0:ref type='bibr' target='#b146'>(Vandenesch et al., 2003)</ns0:ref>. Staphylococcal enterotoxins (SEs) or staphylococcal superantigens proteins (SAgs) are well-known for causing food poisoning, localized epidermal infections Manuscript to be reviewed <ns0:ref type='bibr'>et al., 2014</ns0:ref><ns0:ref type='bibr' target='#b7'>et al., , Argud&#237;n et al., 2010))</ns0:ref>. SEs encoding genes are located on mobile elements including bacteriophages, pathogenicity islands (SaPI), or plasmids. In this study, SEs encoding genes such as sea, seg, sei, yent1, yent2, selk, selm, seln, and selo were identified. Hungarian isolates, SA H27, and SA H32 acquired seg and sei genes, however sei gene was absent in Germany isolates, SA G6, and SA G8. These seg and sei genes belong to egc (enterotoxin gene cluster), involve in staphylococcal food poisoning TSS, and SSF <ns0:ref type='bibr' target='#b69'>(Jarraud et al., 2001</ns0:ref><ns0:ref type='bibr' target='#b31'>, Chen et al., 2004)</ns0:ref> and egc was distributed widely in clinical isolates and playing a role in pathogenesis <ns0:ref type='bibr' target='#b69'>(Jarraud et al., 2001)</ns0:ref>. Exfoliative toxins (ETs) are known as epidermolytic toxins that induce skin shedding and blister formation <ns0:ref type='bibr'>(Melish and Glasgow, 1971)</ns0:ref>. In this study, eta gene encoded for ETA toxin was found in all the isolates and responsible for causing human skin damage, and most prevalent in Europe <ns0:ref type='bibr' target='#b81'>(Ladhani, 2001)</ns0:ref>. Capsular polysaccharide synthesis genes are almost all detected in clinical isolates S. aureus showing significant virulence by targeting the antibodies that protect against Staphylococcal infections <ns0:ref type='bibr'>(Su et al., 1997)</ns0:ref>. Type VII secretion system (T7SS) was present in Germany isolates (Fig. <ns0:ref type='figure'>3A</ns0:ref>) and promoting them to persist in their hosts <ns0:ref type='bibr' target='#b142'>(Tchoupa et al., 2019)</ns0:ref>. The esxA and esxB gene show a significant role in distribution and colonization of S. aureus, and activation of the cell-mediated immune responses, boost the pathogenesis <ns0:ref type='bibr' target='#b22'>(Burts et al., 2005)</ns0:ref>. Also, esaD gene found only in Germany isolates suggesting that this gene can inhibit the growth of other closely related S. aureus strains and playing a role in an intra-species competition <ns0:ref type='bibr' target='#b24'>(Cao et al., 2016)</ns0:ref>. The family of beta-hemolysin converting phage encodes proteins such as SCIN (staphylococcal complement inhibitor) and CHIPS (chemotaxis inhibiting protein of staphylococcus) involved in host-pathogen interaction and contribute to evading human innate immune response <ns0:ref type='bibr' target='#b148'>(Wamel et al., 2006)</ns0:ref>, these proteins were identified in intact prophages of SA G8 and SA G27 genomes but CHIPs was absent in the prophages of SA H32 genome. Therefore, prophages were the reservoir of virulence and resistance factors that play a role in the evolution of virulence strains and causing a major threat to human and animal health <ns0:ref type='bibr' target='#b11'>(Barrera-Rivas et al., 2017)</ns0:ref>. The presence of ARGs and VFGs in the prophage regions of SA G6 genome differentiates it from the other S. aureus isolates and may determine its greater pathogenic potential by modifying its antigenicity <ns0:ref type='bibr' target='#b11'>(Barrera-Rivas et al., 2017)</ns0:ref>. Also, plasmid p1G6 carried qacA gene, which is known to decrease chlorhexidine (antiseptic) susceptibility and giving an event of MGEs transfer evidence of qacA across the S. aureus strains <ns0:ref type='bibr' target='#b80'>(LaBreck et al., 2018)</ns0:ref>. The harbor of MGEs (mosaic features of prophages and plasmids) contributes to the tremendous diversity of Manuscript to be reviewed ARGs and VFGs among the S. aureus isolates <ns0:ref type='bibr' target='#b98'>(McCarthy and Lindsay, 2012;</ns0:ref><ns0:ref type='bibr' target='#b99'>McCarthy et al., 2014)</ns0:ref>. This MGEs transfer event could be useful for the survival of S. aureus in different ecological niches <ns0:ref type='bibr' target='#b89'>(Lindsay, 2010)</ns0:ref>.</ns0:p><ns0:p>The pangenome described here is composed of 3415 genes, of these, 1762 genes are shared among S. aureus isolates (Fig. <ns0:ref type='figure'>6B</ns0:ref>). Functional annotation of the core-genome revelated that they are mostly associated transcription and translation, and different metabolism categories, such similar result was reported previously <ns0:ref type='bibr' target='#b21'>(Bosi et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b132'>Sharma et al., 2018)</ns0:ref>. The core-genome and accessory genome functional characterizations revealed that S. aureus isolates required amino acids than carbohydrates as the energy source and suggests that these isolates adapted to grow in a protein-rich medium than carbohydrates (Fig. <ns0:ref type='figure'>5A and 5B</ns0:ref>). It was suggested that the survival of S. aureus can be maintained by the catabolism of amino acids <ns0:ref type='bibr' target='#b61'>(Halsey et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The core-genome has 51.6% of genes and validated that S. aureus is a clonal species <ns0:ref type='bibr' target='#b44'>(Feil et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b21'>Bosi et al., 2016)</ns0:ref>. The mutation event that occurred in the core-genome of closely related S. aureus provides important roles in virulence and persistence of S. aureus strains <ns0:ref type='bibr' target='#b73'>(Kennedy et al., 2008)</ns0:ref>. So, an in-depth analysis of strain-specific genetic variation is required for further understanding of the pathogenicity. The inflation of pan-genome and deflation of core-genome was seen after the introduction of reference genomes and its regression analysis revealed that the pan-genome is open, suggesting that the gene repertoire of this species is theoretically limitless.</ns0:p><ns0:p>A similar finding was observed in the DNA microarray experiment of thirty-six S. aureus isolates <ns0:ref type='bibr' target='#b45'>(Fitzgerald et al., 2001)</ns0:ref>. The drastic decline of the core/pan-genome ratio after the introduction HE579071.1 (S. aureus subsp. aureus ST228) and SA G6 suggested that these two strains have distinct genomic contents (Fig. <ns0:ref type='figure'>6C</ns0:ref>). The genomic content variation between the genomes is due to the acquisition of certain genes that encode for virulence and resistance factors, pathogenicity islands, prophage-like elements, plasmids, mobile element proteins, and hypothetical proteins in the GIs. These GIs are mobilized across organisms via HGT events <ns0:ref type='bibr' target='#b131'>(Schmidt and Hensel, 2004)</ns0:ref>. This finding was supported by gaps that appeared in the genome ring of SA G6 genome and suggesting that this isolate showed a distant relationship to others (Fig. <ns0:ref type='figure'>4</ns0:ref>). The gaps that appeared in the map are due to the GC% content difference in the comparative genomes, and it results from the event of MGEs transfer via HGT and the GC skewed regions indicated the regions where HGT occurred <ns0:ref type='bibr' target='#b63'>(Hayek, 2013)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>We specifically analyzed the presence of ARGs and VFGs in the core genomes and pangenomes. Some genes involved in multidrug resistance or drug efflux such ygaD, arlR, arlS, and mepA are components of the core-genome (Fig. <ns0:ref type='figure' target='#fig_8'>2</ns0:ref>). The large repertoire of genes (29%) in the accessory genome gives advantages in adaptation and that can contribute to pathogenicity or niche specificity of strains <ns0:ref type='bibr' target='#b101'>(Medini et al., 2005)</ns0:ref>. The analysis of pangenome is essential to understand the event of MGEs transfer and S. aureus evolution <ns0:ref type='bibr' target='#b124'>(Ozer, 2018)</ns0:ref>. The interpretation from the dispersible and singleton genes content analysis of S. aureus genomes allows us to understand the genetic variation among the CC5 and CC22. Juhas et al. reported that most dispensable and singleton genes were acquired through HGT and operate an important role in drug resistance or virulence <ns0:ref type='bibr' target='#b70'>(Juhas et al., 2012)</ns0:ref>. A high portion of unique genes or singletons in S. aureus genomes were related to MGEs, which could drive the gaining of novel functional elements especially drug resistance and virulence via HGT. These singletons are the main drivers of the phenotypic variation within S. aureus strains and the evolution of S. aureus <ns0:ref type='bibr' target='#b26'>(Carvalho et al., 2019)</ns0:ref>.</ns0:p><ns0:p>The phylogenetic trees based on whole-genome and core-genome SNP methods support each other and revealed that these methods were able to distinguish between strains at a higher resolution in terms of the geographic origin of strains and phylogenetic trees are illustrated in Fig. <ns0:ref type='figure'>7</ns0:ref>. The phylogenomic analysis revealed that the strains with ST225 (Germany), ST228 (Germany, Switzerland), ST105 (USA) and ST5 (Japan) were clustered in the same CC5 clade (Cluster C), and different clade (Cluster A) was noticed among the UK origin ST22 (CC22) and diverged from Germany origin strains (Fig. <ns0:ref type='figure'>7A</ns0:ref>), this finding was in good agreement with the previously published article <ns0:ref type='bibr' target='#b0'>(Aanensen et al., 2016)</ns0:ref>. The CC5 (ST225) and CC22 (ST22) were found to be the most dominant clones circulating in Europe <ns0:ref type='bibr' target='#b59'>(Grundmann et al., 2014)</ns0:ref>. The comparative genome analysis revealed that Germany isolates, and Hungarian isolates are genetically diverse and showing variation among them due to the gain or loss of MGEs such as SCCmec, plasmid, phage elements, or the insertion of transposase. The event of MGEs transfer was observed in ST5, ST225, and ST228 (Fig. <ns0:ref type='figure'>7A</ns0:ref>) and similar results were also reported previously <ns0:ref type='bibr'>(N&#252;bel et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b114'>N&#252;bel et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b147'>Vogel et al., 2012)</ns0:ref>. The SNPs located in the core-genome define as the element present in S. aureus strains, these SNPs based phylogenetic tree was constructed to avoid the HGT of MGEs misuse phylogenetic interpretation, as well as this tree, resolved the subdivision within cluster C of Fig. <ns0:ref type='figure'>7A</ns0:ref> indicating that SA G6 isolates and S. aureus subsp. aureus ST228 exhibits the closest strains (Fig. <ns0:ref type='figure'>7B</ns0:ref>). These strains shared the genetic background (ST228/SCCmec-I) and revealing 99.8% OrthoANIu similarity value in their genomes, likewise, Hungarian isolates (SA H27 and SA H32) in clade A (Fig. <ns0:ref type='figure'>7B</ns0:ref>) shared molecular epidemiological background in terms of SCCmec-IVa, and ST-22 and showing 99.8% OrthoANIu value. However, SA G8 isolate and S. aureus subsp. aureus ST228 belongs to ST225 and ST105, respectively were clustered together (Fig. <ns0:ref type='figure'>7B</ns0:ref>). The strains with the same genetic background were clustered together in both phylogenetic trees which suggest that these strains are highly alike, however comparative genome analysis exposed that the acquisition of phage elements and plasmids through the events of MGEs transfer contribute to differences in their phenotypic characters. Such events provide an impact on the fitness or pathogenicity or epidemicity of the strains.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Using WGS, we characterized the four clinical MRSA isolates that infect the skin, nostril, trachea, and other sites. The data generated from the WGS confirmed the diversity of MRSA among the same CC5 and CC22. It is clearly stated that the biofilm-forming ability of MRSA was not correlated with the presence of biofilm-forming encoding genes, also the genetic constituents have no information regarding the infection sites. So, expression profiling of biofilm-related genes is required to define the key genes involved in biofilm formation. The comparative genome study allowed the segregation of isolates of geographical origin, and differentiation of clinical isolates from the commensal isolates. An interesting finding is the addition of SA G6 genome responsible for open pan-genome and diversity among genomes. The openness of pan-genomes of S. aureus isolates relies on the acquisition of MGEs, thus HGT was not limited within the S. aureus strains. The evidence of MGEs transfer event especially in SA G6 is supported by the drastic drop of the core/pan-genome ratio curve, and gaps and GC skewed regions in comparative genome map. The presence of ant( <ns0:ref type='formula'>6</ns0:ref>)-Ia, aph(3')-III) and sat-4 in GI region of SA G6 are likely acquired and these genes may provide fitness and a selective advantage during host-adaptation and colonization. Phylogenetic analysis suggests that SA G6 and S. aureus subsp. aureus ST228 strains are distinct from its group. The acquisition of plasmid and prophage functional modules such as ARGs and VFGs in S. aureus isolates contributes a major role in the rapid evolution of pathogenic S. aureus lineages and that confer specific advantages in a defined host under environmental conditions. Through this comparative genome analysis would improve the knowledge about the pathogenic S. aureus strain's characterization, adaptation, and dynamic evolutionary process in the transmission of infections globally. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>bullous impetigo) and generalized diseases (Staphylococcal scalded skin syndrome) (Grumann PeerJ reviewing PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:1:1:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='45,42.52,70.87,525.00,378.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='47,42.52,275.62,525.00,330.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='48,42.52,270.37,525.00,285.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='49,42.52,250.12,525.00,268.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='51,42.52,70.87,525.00,402.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='52,42.52,275.62,525.00,368.25' type='bitmap' /></ns0:figure> </ns0:body> "

"UNIVERSITY OF PÉCS Faculty of Sciences Institute of Biology Dr. habil. Csaba Fekete Ph.D University of Pécs, Deputy director of the Institute of Biology, Head of the Department of General and Environmental Microbiology, Leader of the Microbial Biotechnology Group 7624 Pécs, Ifjúság u. 6., Hungary, Tel.: +36 72 503600, ext.: 24815 or +36 72 501 500, ext.: 29291 Tel./Fax: ++(36)72 501 573 E-mail: [email protected] Date:12/08/2020 Dear Editors We would like to thank the anonymous reviewers for their kind efforts to improve the manuscript by pointing out several mistakes. As per the suggestions of the reviewers we have modified and corrected manuscripts to comply with the questions raised by the reviewers. We hope that the manuscript is suitable for publication in your esteemed PeerJ Journal. Thanking you for your valuable time and looking forward to hearing from you With kindly regard. Sincerely yours, Dr. Csaba Fekete Professor and Head of Department of General and Environmental Microbiology On behalf of the authors. University of Pécs, Department of General and Environmental Microbiology, 7624 Pécs, Ifjúság u.6., Hungary, Tel.: ++(36) 72 503 600; Extension: 4815 or 4810 Tel./Fax: ++(36)72 501 573 E-mail: [email protected] Reviewer: Juan J Valdez A Basic reporting 1. The manuscript requires a thorough revision of English language; it is recommended that the final English edition be done by a native English speaker or a professional language editing service. Also, there are some typographical mistakes in the body of the manuscript and in tables and figures. Reply: As per your suggestion, we modified those mistakes in this current manuscript. 2. Several articles are available in databases that already analyze comparative genomics of Hospital Acquired- and Community-Acquired MRSA isolates, which seems to be the case of this report. The isolates selected for this work seem to fit with these features. None of those articles are cited in this work. Reply: Thank you for your suggestion, we included few citations that deal with comparative genome analysis of MRSA. The cited parts are in line numbers: 605-607; 615-617; 618-624; 630-634; 639-640; 644-647; 655-661. 3. There is not a clear hypothesis stated or suggested by the authors. It seems a comparative genomics study of four randomly selected Staphylococcus aureus isolates. It is important to define which were the reasons or criteria to select those clones, in order to also establish a proper hypothesis. Reply: The hypothesis is mentioned in the line number 110-130. Experimental design The research presented fits with the Aims and Scope of the Journal. 1. The main question to be resolved by the research, and the hypothesis so on, are not clearly stated. It is not clear which were the criteria to select the clones analyzed, so it is not possible to generate a research question justifying the comparative genomics. Comparative genomics is performed with enough rigor to support the results. Methods are described with enough detail to be reproduced and are adequate to reach the goal of comparative genomics. Reply: We agree with your suggestion and we have modified the manuscript and a hypothesis is postulated (Line number 110-130). Validity of the findings Since the main goal of the research is to find differences among genomes of the four S. aureus isolates tested, the manuscript is mainly descriptive of the findings and differences, with little opportunity to establish correlations with pathology, genetic background or epidemiological data related to the isolates. Genomic analysis sounds robust and well analyzed with appropriate analysis tools. Since there is not a clear research question or a hypothesis, little or no conclusions may emerge from the extensive description of similarities and differences of genomes. Reply: As per your suggestion, we made modifications in the manuscript. Comments for the Author 1. The manuscript presents a detailed description of the comparative genomics of four isolates of Staphylococcus aureus resistant to methicillin (MRSA) from Germany and Hungary. Although the methodology and results are well described, authors should consider several issues to improve their manuscript before it could be accepted for publication. Reply: Thank you very much for providing an extensive review of our manuscript. We agree with your suggestions, and tried our level best to improve the manuscript as far as possible. 2. The title must represent the major findings or major research topics of the manuscript and be specific. For example “Genome-wide comparison of four MRSA clinical isolates from Germany and Hungary” (obviously, to make comparative genomics, whole-genome sequencing is needed; it is not necessary to indicate it in the title). Reply: As per your kind suggestion, we have modified the title and the new title is given as “Genome-wide comparison of four MRSA clinical isolates from Germany and Hungary” 3. A hypothesis is not clearly stated, and that is because there is not a clear question behind the analysis. The authors should provide a clear justification for the selection of the four isolates to analyze. Why compare Germanic with Hungarian isolates? Which is the relationship between these countries with respect to the research? Was any other criterion for the selection of the isolates (particular pathologies, representatives of an outbreak, any physiological feature that makes them interesting for research)? This is important because the rationale behind the selection of the strains may direct the search of similarities and differences and establish correlations with particular features. Reply: As per your suggestion we have modified the manuscript and a hypothesis is postulated (Line number 110-130). The reasons behind the selection of these strains are given below: In our preliminary study (Naorem et al., 2020), we found that the strains collected from Germany viz., SA G6 and SA G8 were similar in terms of survival at acidic and alkaline pH condition and biofilm formation. However, both the isolates belonged to different Sequence Types (ST 228 and ST225) and SCCmec Types (II and I). In the case of Hungarian strains, both the strains belonged to the same Sequence Type (ST22) and SCCmec Type (IVa). However, these two strains were from Nostril and Trachea showed different antibiotic resistance patterns and biofilm profiles. On epidemiological background, Germany isolates belonged to Clonal Complex 5, Hospital-Acquired MRSA while the Hungarian isolates (SA H27 and SA H32) belonged to Clonal Complex 22, Community-Acquired MRSA. These findings made us assume that there may be certain differences in the genomic context of these isolates and we wanted perform an indepth study of these isolates to highlight the genetic composition that governs the phenotypic difference in terms of antibiotic resistance, virulence factors, and biofilm formation through WGS. 4. Authors should also emphasize which is the particular contribution of their research to the scientific community. There are hundreds of papers already published in comparative genomics of Staphylococcus aureus strains, must of them comparing few reference, well-characterized strains, or dozens of clinical isolates. Reply: The basic significance of this study is that WGS analysis provides better insight into the genomic context of the isolates and helps differentiate among closely related strains that were clustered by polyphasic approach. This study able to segregate isolates of geographical origin, and specific genetic signatures distinguishing the clinical isolates from the commensal isolates. The acquisition of plasmid and prophage functional modules such as ARGs and VFGs in S. aureus isolates contributes a major role in the rapid evolution of pathogenic S. aureus lineages and that confer specific advantages in a defined host under environmental conditions. Also, S. aureus isolates survival are maintained by the catabolism of amino acids and favor adaptation to growing in a protein-rich medium than carbohydrates. This comparative genome analysis would be responsible for clinically important phenotypic differences among the S. aureus strains. 5. Genomic typing of bacterial isolates of clinical importance has been intended with a variety of methods. The authors should present in the introduction a brief analysis of the advantages and disadvantages of other methods (MLST, PFGE, VNTRs, spa typing, SCCmec-typing, agr-typing) used for Staphylococcus aureus against whole genome sequence analysis. Reply: As per your valuable suggestion, we have incorporated the necessary data in line numbers 95-106. 6. Biofilm is analyzed but not presented in the introduction section as a goal of the research. Reply: The manuscript has been modified and the biofilm section has been removed. 7. Results on biofilm formation and tolerance to pH are not properly referred in Table S1. Reply: Biofilm formation was discussed in our previous article (Naorem et al., 2020). The Table S1 is removed from the supplementary file. 8. Improve the presentation of figure S1 by specifying the name of the strains in the lanes and the identification of the amplification products, either by size or name. Make this match with the figure caption. Reply: This figure was highlighted in our previous article (Naorem et al., 2020). We removed this figure S1 from the manuscript supplementary file. 9. Avoid superlative subjective adjectives as “intriguingly, surprisingly, unexpectedly” and attach to the quantitative or qualitative description of data. Reply: As per your suggestion Superlative subjective adjectives have been removed. 10. Line 259: specify which is the antiseptic agent, name, or category. Reply: The category of the antiseptic agent was added as quaternary ammonium compound efflux MFS transporter (QacA) in line number 277-278. 11. Although low similarity at the sequence level between plasmids p1G6 and pTW20_1, it is quite evident the similarity in physical distribution and content of the genes. A more detailed description and comparative analysis are necessary. Reply: Thank you for your suggestion and the necessary modification have been incorporated in line numbers: 272-286. 12. Lines 270-272. The authors should briefly describe the distribution of toxin among strains. Reply: We completely agree with your advice and a brief description is added in line number 290-306. 13. Lines 291-293. If genes including different autoinducing peptides were detected among the isolates, this suggests the presence of an accessory global regulator locus (agr) which encodes the autoinducing peptides. Agr locus information is also used for agr-typing, which may be determined from the sequence and included as another molecular typing method in table 1. Reply: We agree with your point, we included this part in line number 180-182, 490-491 and Table 1. 14. Lines 295-299. There is confusion in the numbers indicating proportions, which represents the number in the denominator. Reply: The text has been modified in line number 329-333. 15. Figure 4 caption should refer to the genome accession numbers with the isolates. Reply: As per your advice the Figure 4 caption has been modified. 16. In order to improve discussion, authors must take advantage of the information provided by the deduced sequence typing methods, such as MLST, spa-typing, SCCmec-typing and agrtyping (not included in this analysis). Together these methods may provide a molecular epidemiology background of these isolates in relation to comparative genomics. For example, German isolates are STs included in the Clonal Complex 5 which is typical of Hospital Acquired MRSA, while Hungarian isolates also pertain to Clonal Complex 5, but ST22 background suggests its relationship with Community Acquired MRSA. The presence of some virulence genes are particularly frequent in each kind of pathology. For example, PVL toxin was commonly used as a marker of Community Acquired MRSA and is related to particular pathologies. Reply: We completely agree with your suggestion. We have added this suggestion in the line number 486-501. 17. Discussion is more a review of literature rather than contrasting the findings of this research with previously published papers. As I commented previously, there are no literature references to other comparative genomic studies for the discussion. Because of the lack of a solid scientific question, conclusions presented are to general that may describe any other genomic comparison between any kind of bacterial isolates. Reply: As per your kind suggestion the discussion part has been modified, and we have added a few citations that deal with comparative genome analysis of other bacteria. The modification and cited parts are in line numbers: 605-607; 615-617; 618-624; 630-634; 639-640; 644-647; 655661. 18. Because of the lack of a solid scientific question, conclusions presented are to general that may describe any other genomic comparison between any kind of bacterial isolates. Reply: We completely agree, and the conclusion part was modified based on our findings. It is presented in line number 677-698. Reviewer 2 (Anonymous) Basic reporting In this work Feteke et. al. analyzed and compare the genome of four methicillin resistant Staphylococcus aureus (MRSA). The aim and scope of the article is very interesting and relevant. However, the manuscript is not clear and unambiguous, and the writing must be improved. Reply: As per your kind observation, the manuscript has been improved to the best of our knowledge. • The authors provide enough references and field background; however, the authors could take into account the next references: Aanensen, D. M., Feil, E. J., Holden, M. T., Dordel, J., Yeats, C. A., Fedosejev, A., ... & Chlebowicz, M. A. (2016). Whole-genome sequencing for routine pathogen surveillance in public health: a population snapshot of invasive Staphylococcus aureus in Europe. MBio, 7(3). Kleinert, F., Kallies, R., Zweynert, A., & Bierbaum, G. (2016). Draft genome sequences of three northern German epidemic Staphylococcus aureus (ST247) strains containing multiple copies of IS256. Genome announcements, 4(5). The structure of the article has a standard format. The figures are relevant and help to understand the paper. MRSA genome number accessions are reported. Reply: We must thank you for providing such relevant articles from you, and we have cited the suggested articles in the discussion part. Experimental design Bioinformatics and experimental findings are original and within Aims and Scope of the journal. The genome analysis of MRSA is well conducted, following high technical standard. However, some experimental data is not enough to support all the findings. Reply: Thank you for your valuable suggestion. We have modified our article such that the experimental data supports the findings. Most of the results and findings are well supported. However, there are some issues that must be clarified. 1. SA H27 biofilm formation was almost four times bigger than other three strains, however, this finding did not were described neither discussed. Reply: We agree with your suggestion and this part has been added in line number 539-540. 2. Since involved genes in biofilm formation are present in all four strains, an expression gene/protein experiment must be designed and performed to understand this point. Reply: We strongly agree with your suggestion. Since biofilm formation is complex and it consists of different pathways, protein-protein interaction networks. Expression profiling through qPCR of few genes related biofilm formation will give a basic idea about the biofilm forming capabilities of the strains. As you all aware about the situation during this COVID-19 pandemic, it is not possible for us to perform the qPCR experiment because the research lab is in Pecs, Hungary (under lockdown) and the first-author is in India. We deeply regret and apologize for our inability to perform this experiment. This part is the limitation of our study, and we are planning to perform a transcriptome analysis in the future. 3. Strain SA G6 is proposed to be more pathogenic than other three strain because of HGT gained genes; this is speculative, and an experimental approach must be carried out to prove this point. Reply: We agree with your suggestion, it must be performed using a cell-line or model organism (mouse) to evaluate the SA G6 infection rate. However, at this moment this is not possible and therefore we have removed this statement from the manuscript. 4. To validate HGT of SA G6 genes, a phylogenetic analysis must be performed. Reply: We completely agree with your suggestion. There are some tools available in Github for this analysis however, due to lack of expertise in programming languages we have opted a different strategy. We used Islandviewer 4 to search for Genomic Island and identified the presence of aminoglycoside 3 phosphotransferase, aminoglycoside 6 nucleotidyl transferase, and streptothricin acetyl transferase (sat-4) within the prophage region (phiG6.4) of SA G6. We have cited some relevant articles that support our findings. 5. In the phylogenetic analysis (Figure 7C) it will be desirable to increase the number of OTUs to gain knowledge about strains origin. Reply: As per your suggestion necessary corrections have been made. Core-SNPs tree was generated with 17 related strains. It is shown in figure 7B. 6. Phylogenetic analysis was poorly discussed; this section must be re-written. Reply: As per your suggestion necessary we have incorporated an elaborated discussion of the phylogenetic analysis (line number 648-675). 7. There was no discussion about the findings about SA pan-genome. Reply: As per your suggestion necessary corrections have been made. We have included the discussion regarding pan-genome in line numbers 608-647. Minor corrections • Homogenize name plasmids in text lines 258 and 260 within table 1. Reply: As per your suggestion Plasmid names were placed within table 1. • Correct pan-genome in line 428. Reply: As per your suggestion necessary corrections have been made (line number 455). • Correct syntaxis in line 519 (but sei gene was not found in Germany isolates). Reply: As per your suggestion necessary corrections have been made (line number 577). • Correct SA H27 and SA G8 (separate acronyms) in line 539. Reply: As per your suggestion it is corrected in line number 595-596. • All scientific names should be italicized or underlined in figure legends. Reply: As per your suggestion we corrected the figure legends. • In figure 4, strain names, SA G6, SA G8, SA H27, SA H32, must be shown to identification of strains. Reply: As per your suggestion, the figure 4 has been modified. • Figure 7A and 16S rRNA analysis must be deleted since this tree has to low information to resolve taxonomy at strain level. Reply: Thank you for your advice. The 16S rRNA gene-based phylogeny has been removed. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Staphylococcus aureus is a drug-resistant pathogen, capable of colonizing diverse ecological niches and causing a broad spectrum of infections related to a community and healthcare. In this study, we choose four methicillin-resistant S. aureus (MRSA) clinical isolates from Germany and Hungary based on our previous polyphasic characterization finding. We assumed that the selected strains have a different genetic background in terms of the presence of resistance and virulence genes, prophages, plasmids, and secondary metabolite biosynthesis genes that may play a crucial role in niche adaptation and pathogenesis. To clarify these assumptions, we performed a comparative genome analysis of these strains and observed many differences in their genomic compositions.</ns0:p><ns0:p>The Hungarian isolates (SA H27 and SA H32) with ST22-SCCmec type IVa have fewer genes for multiple-drug resistance, virulence, and prophages reported in Germany isolates.</ns0:p><ns0:p>Germany isolate, SA G6 acquires aminoglycoside (ant(6)-Ia and aph(3')-III) and nucleoside (sat-4) resistance genes via phage transduction and may determine its pathogenic potential. The comparative genome study allowed the segregation of isolates of geographical origin and differentiation of the clinical isolates from the commensal isolates.</ns0:p><ns0:p>This study suggested that Germany and Hungarian isolates are genetically diverse and showing variation among them due to the gain or loss of mobile genetic elements (MGEs).</ns0:p><ns0:p>An interesting finding is the addition of SA G6 genome responsible for the drastic decline of the core/pan-genome ratio curve and causing the pan-genome to open wider. Functional characterizations revealed that S. aureus isolates survival are maintained by the amino acids catabolism and favor adaptation to growing in a protein-rich medium. The dispersible and singleton genes content of S. aureus genomes allows us to understand the genetic variation among the CC5 and CC22 groups. The strains with the same genetic background were clustered together which suggests that these strains are highly alike, however comparative genome analysis exposed that the acquisition of phage elements, and plasmids through the events of MGEs transfer contribute to differences in their phenotypic</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Staphylococcus aureus is a notorious nosocomial, and community-acquired pathogen <ns0:ref type='bibr' target='#b28'>(Chambers and Deleo, 2009)</ns0:ref>. It has the capability of colonizing diverse ecological niches within its human host, including the skin, blood, respiratory tract, and nasal passages <ns0:ref type='bibr' target='#b38'>(Deleo et al., 2009)</ns0:ref> and causing diverse ranges of the hospital and community-acquired infections such as skin and soft tissue infections (SSI) for example, carbuncles, abscesses, styes, and impetigo and lifethreatening infections such as bacteremia, necrotizing pneumonia, osteomyelitis, endocarditis, and sepsis <ns0:ref type='bibr' target='#b52'>(G&#246;tz et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b110'>Mottola et al., 2016)</ns0:ref>. Methicillin-resistant S. aureus (MRSA) acquired a mobile genetic element called Staphylococcal chromosomal cassette mec <ns0:ref type='bibr'>(SCCmec)</ns0:ref> accompanied by methicillin resistance gene (mecA) <ns0:ref type='bibr' target='#b152'>(Zhang et al., 2012)</ns0:ref>. The &#946;-lactam insensitive protein, penicillin-binding protein (PBP2a) encoded by mecA gene reduces affinity to penicillin and &#946;-lactam antibiotics including methicillin, oxacillin, cefoxitin, etc., and develop resistance toward the &#946;-lactam antibiotics <ns0:ref type='bibr' target='#b68'>(Jansen et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b106'>Mistry et al., 2016)</ns0:ref>. MRSA acquires an arsenal of antibiotic resistance genes (ARGs) and virulence factor encoding genes (VFGs) through horizontal gene transfer (HGT) and recombination <ns0:ref type='bibr' target='#b29'>(Chan et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b65'>Hughes et al., 2005)</ns0:ref>.</ns0:p><ns0:p>MRSA can anchor and colonize on epithelial surfaces and produce biofilm <ns0:ref type='bibr'>(Goudarzi et al., 2017)</ns0:ref>. The biofilm produced by MRSA strains encase its cells in the exopolysaccharide matrix reduces the activity of antibacterial agents and immune defense. The dispersal of bacterial cells from the biofilm can result in secondary site infections and leading infections worsen and difficult to eradicate <ns0:ref type='bibr' target='#b93'>(Lister and Horswill, 2014)</ns0:ref>. Biofilm formation is a complex process that consists of an extracellular polymeric matrix (ECM) formation involving polysaccharide intercellular adhesin (PIA), protein-protein interactions, and the incorporation of extracellular DNA (eDNA) <ns0:ref type='bibr' target='#b118'>(O'Gara, 2007;</ns0:ref><ns0:ref type='bibr'>Payne and Boles, 2016)</ns0:ref>. The biofilm formation is determined by the icaADBC gene cluster, responsible for PIA and capsular polysaccharide/adhesion synthesis <ns0:ref type='bibr' target='#b27'>(Chaieb et al., 2005)</ns0:ref>. MRSA possesses adhesive matrix molecules that are encoded by elastin (ebps), laminin (eno), clumping factors A and B (clfA and clfB), fibronectin A and B (fnbA and fnbB), collagen (cna), fibrinogen (fib), bone sialoprotein (bbp), etc <ns0:ref type='bibr' target='#b91'>(Lindsay et al., 2006)</ns0:ref>. These molecules are exported to the bacterial cell surface to enable adherence with host tissues, leading to play a role in pathogenesis <ns0:ref type='bibr' target='#b97'>(Mazmanian et al., 1999)</ns0:ref>. Manuscript to be reviewed S. aureus acquires an arsenal of ARGs and VFGs that are subjected to HGT and recombination <ns0:ref type='bibr' target='#b29'>(Chan et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b65'>Hughes et al., 2005)</ns0:ref>. Hospital-associated MRSA (HA-MRSA) is often associated with metastatic infections and significant morbidity and mortality <ns0:ref type='bibr' target='#b54'>(Gould, 2005)</ns0:ref>.</ns0:p><ns0:p>However, Community-associated MRSA (CA-MRSA) infections have seen a high increase in prevalence, posing a greater threat to the public <ns0:ref type='bibr' target='#b108'>(Morens and Fauci, 2013)</ns0:ref>. The genomic plasticity of S. aureus has facilitated the development of hypervirulent and drug-resistant strains, result in challenging issues to antibiotic treatment and health concern.</ns0:p><ns0:p>The classical techniques such as antibiotic susceptibility test (AST) patterns and molecular typing methods such as SCCmec-typing, Pulse-Field Gel Electrophoresis (PFGE), Multi-Locus Sequence Typing (MLST), Multi-locus variable-number tandem-repeat (VNTR) analysis (MLVA), S. aureus protein A (spa)-typing, accessory gene regulator (agr)-typing are widely used to detect and differentiate several MRSA strains, and helpful for identifying the risk factors associated with MRSA infection which support the establishment of adequate infection control programs <ns0:ref type='bibr' target='#b152'>(Zhang et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b106'>Mistry et al., 2016)</ns0:ref>. However, these methods are expensive and time-consuming, and have limitations in infection control and investigating the nosocomial transmission due to low resolution <ns0:ref type='bibr' target='#b40'>(Du et al., 2011)</ns0:ref>. In this modern era, whole-genome sequence-based typing offers an excellent resolution in global and local epidemiologic investigations of pathogen outbreaks and offers further data mining activities essentially for ARGs and VFGs profiling <ns0:ref type='bibr' target='#b77'>(K&#246;ser et al., 2012)</ns0:ref>. So, the Next Generation Sequencer (NGS) basedgenome sequencing technique has become an essential tool in the clinical microbiology arenas for comparative genomic analysis of several other species of the Staphylococcus genus in terms of the niche adaptation, combat antibiotics, and emergence of new virulent strains in real-time.</ns0:p><ns0:p>In our preliminary study, the polyphasic characterization of 35 S. aureus strains originated from Germany, and Hungary was performed. This characterization included antibiotic resistance test (ART), biochemical tests, biofilm-forming assay, and PCR based typing techniques involving the amplification of mecA, pvl, SCCmec-type, spa type, coa-HaeIII-RFLP, and biofilm-associated genes. Principal component analysis from polyphasic characterization data showed that the strains originated from the same geographical region were found in the close group while SA G8, Germany strain was grouped with other Hungarian strains <ns0:ref type='bibr' target='#b112'>(Naorem et al., 2020)</ns0:ref>. The Hungarian strains (SA H27 and SA H32) belonged to the same Clonal Complex (ST22/SCCmec-IV) were clustered in the same group, however, these strains were isolated from the different sites of infections (nostrils and trachea) and showed different antibiotic resistance patterns and biofilmforming abilities. Similarly, the strains collected from Germany viz., SA G6, and SA G8 belonged to the same Clonal Complex (ST228/SCCmec-I and ST225/ SCCmec-II) having similar antibiotic resistance pattern, and biofilm-forming profiles, but these strains were isolated from the different site of infections (skin and other body sites) and not clustered in the same group <ns0:ref type='bibr' target='#b112'>(Naorem et al., 2020)</ns0:ref>. Based on this information, these four S. aureus strains were chosen for indepth comparative genome levels study to better understand the genomic differences among the strains. We assumed that the selected strains have a different genetic background in terms of the presence of ARGs, VFGs, prophages, plasmids, and secondary metabolite biosynthesis genes that may play a crucial role in niche adaptation and pathogenesis. To clarify these assumptions, we performed a comparative genome analysis of these four strains and observed many differences in their genomic compositions.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Bacterial strains used in this study</ns0:head><ns0:p>In this study, four S. aureus isolates collected from Germany (SA G6, and SA G8) and Hungarian (SA H27, and SA H32) were used. Hungarian isolate, SA H27 was reported as a strong biofilm producer among them <ns0:ref type='bibr' target='#b112'>(Naorem et al., 2020)</ns0:ref>.</ns0:p><ns0:p>pH tolerance assay S. aureus strains were cultured overnight at 37&#186; C in tryptic soy broth (TSB) (DB, Germany).</ns0:p><ns0:p>The cell density (colony forming units, CFU) was adjusted to a final concentration of ~10&#8310; CFU/ml in pH 4.5 TSB and pH 9.5 TSB. Cell suspension (200 &#181;l) were loaded into the 96-well flat-bottomed polystyrene microtiter plate (Costar 3599; Corning; USA). The plates were incubated at 37&#186; C for 24 h without shaking, then the growth was measured at 492 nm wavelength using a Multiskan Ex microtiter plate reader (Thermo Electron Corporation, USA).</ns0:p><ns0:p>The experiments were performed in triplicate and analyzed using GraphPad Prism 6 software package (Graphpad Software Inc, San Diego, CA).</ns0:p></ns0:div> <ns0:div><ns0:head>Genomic DNA isolation and sequencing</ns0:head><ns0:p>The genomic DNA was extracted using the GenElute&#8482; Bacterial Genomic DNA Kit (Sigma, USA) following the manufacturer instructions. The concentration and purity of genomic DNA was measured using dsDNA HS (High Sensitivity) Assay Kit in Qubit 3.0 fluorometer (Thermo Fisher Scientific Inc., USA) and subsequently DNA quality was visualized by agarose gel electrophoresis.</ns0:p><ns0:p>Genomic libraries were prepared by using the NEB Next Fast DNA Fragmentation and Library Preparation Kit, developed for Ion Torrent (New England Biolabs) and used according to 200 bp protocol. After chemical fragmentation, DNA size selection was performed on precast 2% E-Gel Size Select Gel (Thermo Fisher Scientific Inc., USA). The quality of the libraries was verified using Agilent high sensitivity DNA assay kit (Agilent Technologies Inc., USA) in Agilent 2100</ns0:p><ns0:p>Bioanalyzer System (Agilent Technologies Inc., USA). For the template preparation, Ion PGM Hi-Q View OT2 Kit was used (Thermo Fisher Scientific Inc., USA). The template positive beads were loaded on Ion 316v2 Chip and sequenced using Ion PGM Hi-Q View Sequencing Kit on Ion Torrent PGM sequencer (Thermo Fisher Scientific Inc., USA).</ns0:p></ns0:div> <ns0:div><ns0:head>Genome assembly and annotation</ns0:head><ns0:p>In-silico trimming of adapter and barcode sequences and data analysis were performed using Torrent Suite 5.4.0 (Thermo Fisher Scientific Inc., USA) and the trimmed paired-end reads were assembled by de novo assembler SPAdes 3.7.1 software with <ns0:ref type='bibr'>21, 33, 55, 77, 99, 127 k-mer values (Nurk et al., 2013)</ns0:ref>. The assembly-stats and quality of genome completeness for each strain were estimated using the web platform QUEST <ns0:ref type='bibr' target='#b60'>(Gurevich et al., 2013)</ns0:ref>. For identifying the closely related strains, the genome assemblies were analyzed by the kmerFinder 2.0 webplatform <ns0:ref type='bibr'>(Larsen et al., 2014)</ns0:ref>. The genome assembly was aligned against the reference genome for the contigs rearrangement using the 'Move Contigs' algorithm in Mauve 2.4.0 <ns0:ref type='bibr' target='#b37'>(Darling et al., 2010)</ns0:ref> and further, scaffolds were generated with reference genome/ genome of closely related strains predicted by kmerFinder 2.0 as a guide for alignment using the reference-based scaffolder MeDuSa <ns0:ref type='bibr' target='#b20'>(Bosi et al., 2015)</ns0:ref>. Gene annotation of the genome assemblies was performed via the fully automated RAST (Rapid Annotation using Subsystem Technology) <ns0:ref type='bibr'>(Aziz et al., 2008)</ns0:ref> and PATRIC 3.5.7 (Pathosystems Resource Integration Center) <ns0:ref type='bibr' target='#b122'>(Wattam et al., 2013)</ns0:ref> pipelines using the reference genome.</ns0:p></ns0:div> <ns0:div><ns0:head>In-silico characterization of genome assemblies</ns0:head><ns0:p>In-silico epidemiologic characterization of genome assemblies was performed using SCCmecFinder-1.2 for the identification of SCCmec types <ns0:ref type='bibr' target='#b72'>(Kaya et al., 2018)</ns0:ref>, spaTyper 1.0 <ns0:ref type='bibr' target='#b12'>(Bartels et al., 2014)</ns0:ref> for spa type, and MLST 1.8 <ns0:ref type='bibr' target='#b83'>(Larsen et al., 2012)</ns0:ref> for Multilocus Sequence Type in a web-based server provided by the Center for Genomic Epidemiology (https://cge.cbs.dtu.dk/services/). In-silico arg (accessory gene regulator)-typing was performed using the primers described by <ns0:ref type='bibr' target='#b134'>Shopsin et al. (Shopsin et al. 2003)</ns0:ref> in in-silico PCR amplification tools <ns0:ref type='bibr' target='#b16'>(Bikandi et al., 2004)</ns0:ref>.</ns0:p><ns0:p>The genome assemblies were screened for plasmid replicon (rep) genes using PlasmidFinder 2.1 <ns0:ref type='bibr' target='#b25'>(Carattoli et al., 2014)</ns0:ref> with default parameters. The identified nonaligned contig or scaffold associated with plasmid sequences were extracted and used for the identification of full-length plasmid regions using PLSDB (Plasmid Database) version-2020-03-04 <ns0:ref type='bibr' target='#b47'>(Galata et al., 2018)</ns0:ref> with search strategy Mash screen, and the default values were a maximum P-value of 0.1 and a minimum identity of 0.99 (https://ccb-microbe.cs.uni-saarland.de/plsdb/). Identified plasmids were compared with the closest reference plasmids using Easyfig version 2.2.3 <ns0:ref type='bibr' target='#b140'>(Sullivan et al., 2011)</ns0:ref>. The identification and annotation of prophage sequences were performed by screening the genome assemblies using PHASTER (PHAge Search Tool Enhanced Release) <ns0:ref type='bibr' target='#b8'>(Arndt et al., 2016)</ns0:ref>, and identified template phages were classified for their lifestyles using PHACTS (Phage Classification Tool Set) <ns0:ref type='bibr' target='#b100'>(McNair et al., 2012)</ns0:ref>.</ns0:p><ns0:p>In-silico mining of candidate ARGs and VFGs were performed using CARD (Comprehensive Antibiotic Resistance Database) version 3.0.8 in RGI (Resistance Gene Identifier) version 5.1.0 platform (https://card.mcmaster.ca/analyze/rgi) <ns0:ref type='bibr'>(Alcock et al., 2020)</ns0:ref>, and a comprehensive set of S. aureus VFGs was analyzed using VFDB (Virulence Factor Database) in VFanalyzer <ns0:ref type='bibr' target='#b30'>(Liu et al., 2019)</ns0:ref> and the PATRIC tool version 3.6.3 (https://www.patricbrc.org/) <ns0:ref type='bibr' target='#b122'>(Wattam et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Further, heatmap and hierarchical clustering were generated to visualize the presence and absence of VFGS and ARGs in S. aureus strains using a web-based application, Morpheus, (https://software.broadinstitute.org/morpheus). Secondary metabolite biosynthesis gene clusters and the detection of genes encoding bacteriocins were analyzed using antiSMASH 5.0 <ns0:ref type='bibr'>(Blin et al., 2019) and</ns0:ref><ns0:ref type='bibr'>BAGEL4 (Van Heel et al., 2018)</ns0:ref>. The prediction of chromosomal genomic islands was predicted by using IslandViewer 4 <ns0:ref type='bibr' target='#b15'>(Bertelli et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparative genomic analysis</ns0:head><ns0:p>The ANI was determined based on BLAST+ using the JSpeciesWS webserver <ns0:ref type='bibr'>(Richter et al., 2016)</ns0:ref>. The pairwise comparisons between the genomes of S. aureus isolates and their nearest reference genomes were conducted using GBDP (Genome BLAST Distance Phylogeny) under the algorithm trimming and distance formula d5, and calculated each distance with 100 replicates <ns0:ref type='bibr' target='#b103'>(Meier-Kolthoff et al., 2013)</ns0:ref>. dDDH (Digital DNA-DNA Hybridization) values and confidence intervals were calculated using the recommended settings of the GGDC 2.1 <ns0:ref type='bibr' target='#b103'>(Meier-Kolthoff et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Genomes of S. aureus isolates and their reference strains were compared with CGViewer (Circular Genome Viewer) server <ns0:ref type='bibr' target='#b55'>(Grant et al., 2008)</ns0:ref>. The functional annotation was performed using EggNOG (Evolutionary Genealogy of Genes: Non-supervised Orthologous Groups) mapper 5.0 database <ns0:ref type='bibr'>(Huerta-Cepas et al., 2019)</ns0:ref> and RAST server-based SEED viewer <ns0:ref type='bibr'>(Overbeek et al., 2014)</ns0:ref>.</ns0:p><ns0:p>The pan-genome, core-genome, and singletons were calculated using four study genomes of S. aureus isolates in EDGAR version 2.0 software framework <ns0:ref type='bibr' target='#b18'>(Blom et al., 2016)</ns0:ref>. This pangenome analysis was extended using four study genomes coupled with three reference genomes of S. aureus strains. The core-genome was analyzed in the genomes set using reciprocal best BLAST hits of all CDS using EDGAR version 2.0 software framework <ns0:ref type='bibr' target='#b18'>(Blom et al., 2016)</ns0:ref>. The singletons were calculated for the contig of a strain by comparing to the CDS of a set of contigs in EDGAR. The CDS that has no match with SRV (Score Ratio Value Plots) higher or equal the master cut-off in any of the contigs were considered as singletons. The development of pangenome and core-genome sizes was analyzed using the core/pan development feature and as well, the pan vs. core development plot was generated in EDGAR. Heap's Law function was applied to calculate whether the pan-genome open or closed using the equation n=k*N^ <ns0:ref type='bibr'>(-&#945;)</ns0:ref> where n= expected a number of genes; N= number of genomes; k and &#945; (&#945; =1-&#947;) are proportionality constant and exponent, respectively <ns0:ref type='bibr' target='#b143'>(Tettelin et al., 2008</ns0:ref>). Heap's law predicted that closed pan-genome (when &#945; &gt; 1 (&#947; &lt; 0)), and open pan-genome (when &#945; &lt; 1 (0 &lt; &#947; &lt; 1)).</ns0:p><ns0:p>According to <ns0:ref type='bibr' target='#b143'>Tettelin et al., 2008</ns0:ref>, core-genome and singletons developments were calculated by the least-square fitting of exponential decay functions.</ns0:p><ns0:p>The Rcp (ratio of core-genome to that of pan-genome) was calculated <ns0:ref type='bibr' target='#b51'>(Ghatak et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Then, genomic subsets, including the number of core-genome and singletons in the gene pool, were extracted, and flowerplot was drawn using in-house R scripts.</ns0:p></ns0:div> <ns0:div><ns0:head>Phylogenetic analysis</ns0:head><ns0:p>The genome assemblies of the isolates were used for a whole genome-based phylogeny analysis using TYGS (Type/Strain Genome Server) (Meier-Kolthoff and G&#246;ker, 2019) engaging with genomes of closely related strains of S. aureus. The phylogenomic trees were reconstructed using FastME 2.1.6.1 <ns0:ref type='bibr' target='#b84'>(Lefort et al., 2015)</ns0:ref> from the GBDP (Genome BLAST Distance Phylogeny) distances calculated from genome sequences under the algorithm 'coverage' and distance formula d5 <ns0:ref type='bibr' target='#b103'>(Meier-Kolthoff et al., 2013)</ns0:ref>. The trees were rooted at the midpoint <ns0:ref type='bibr' target='#b43'>(Farris, 1972)</ns0:ref>; branch supports were inferred from 100 pseudo-bootstrap replicates and visualized with Interative Tool Of Life v4 (iTOL) <ns0:ref type='bibr' target='#b86'>(Letunic and Bork, 2019)</ns0:ref>. The core SNPs of genome sequences were extracted using Panseq <ns0:ref type='bibr' target='#b82'>(Laing et al., 2010)</ns0:ref> and the phylogenetic tree was constructed using PhyML+SMS module in NGPhylogeny.fr <ns0:ref type='bibr' target='#b85'>(Lemoine et al., 2019)</ns0:ref> to select the best evolutionary model, further the tree was annotated in Interative Tool Of Life v4 (iTOL) <ns0:ref type='bibr' target='#b86'>(Letunic and Bork, 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The S. aureus isolates could survive at pH 4.5 through pH 9.5 conditions with a survival rate of ~ 45% -84%. SA G8 isolate showed the highest cell survival rate of 84.4% at acidic pH but its cell survival rate drops down by 7% when subjected to alkaline pH conditions (Table <ns0:ref type='table'>S1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>General genomic features of S. aureus isolates</ns0:head><ns0:p>The genomic DNA of S. aureus isolates was successfully sequenced in the IonTorrent PGM sequencing platform. The average raw reads obtained from the genome sequencing of SA G6, SA G8, SA <ns0:ref type='bibr'>H27,</ns0:ref><ns0:ref type='bibr'>and SA H32 are ~ 88.9,</ns0:ref><ns0:ref type='bibr'>69.6,</ns0:ref><ns0:ref type='bibr'>128.3,</ns0:ref><ns0:ref type='bibr'>and 92.7 million bases (Mb)</ns0:ref> for genomes of SA G6, SA G8, SA H27, and SA H32 strains respectively. The closely related strains identified by kmerFinder 2.0 were S. aureus subsp. aureus ST228 (HE579073), S. aureus subsp. aureus JH9 (CP000703) for SA G6 and SA G8 strains, respectively. Also, S. aureus subsp. aureus HO 5096 0412 (HE681097.1) was identified closely related strains for SA H27 and SA H32 strains. Among the S. aureus isolates, SA G8 has the largest genome size (28633393 bp) with high % GC content (32.81%). The numbers of protein-coding sequences (CDSs) in the S. aureus strains varied from 2630 (SA H27) to 2743 (SA G8). The comparison of draft genome assemblies, genome annotation, molecular typing, plasmid, and prophage features for S. aureus genomes were summarized in Table <ns0:ref type='table'>1</ns0:ref>. <ns0:ref type='table'>PDF | (2020:05:49105:2:0:NEW 17 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head></ns0:div> <ns0:div><ns0:head>Genes encoding plasmids</ns0:head><ns0:p>The putative plasmids were detected in nonaligned contigs or scaffolds that exhibited an unexpected high coverage level after the genome assemblies. A putative plasmid (p1G6) of 13331bp length was identified at Scaffold 4 of the SA G6 genome consisting of the replication gene (repA). The p1G6 plasmid has 30.97% sequence coverage with plasmids pTW20_1 (FN433597.1) (Fig. <ns0:ref type='figure' target='#fig_8'>1A</ns0:ref>). The sequence coverage region of p1G6 with pTW20_1 constitutes the genes that encode for proteins such as IS6 family transposase, replication-associated protein (Rep), cadmium resistance transporter (CadD), cadmium efflux system accessory protein (CadX), replication initiation protein A (RepA), quaternary ammonium compound efflux MFS transporter (QacA), multidrug-binding transcriptional regulator (QacR), DUF536 domaincontaining protein (mP), AAA family ATPase (Abp), hypothetical proteins, HAD hydrolase family protein, and IS257 family transposase. The SA H32 genome also consists of a putative plasmid (p2H32) having a length of 2530 bp located at Scaffold 3 and showed 71.32% sequence coverage with plasmids AR_0472 (NZ_CP029648.1). It consists of a replication gene (repL) and carried an erythromycin resistance gene (emrC) (Fig. <ns0:ref type='figure' target='#fig_8'>1B</ns0:ref>). The identified plasmids of S. aureus encode no other factors for their transfer, such plasmids may transfer via phage transduction <ns0:ref type='bibr' target='#b98'>(McCarthy and Lindsay, 2012)</ns0:ref>. The linear graphical map of plasmid comparison was represented in Fig. <ns0:ref type='figure' target='#fig_8'>1</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Characteristic of prophages-like elements</ns0:head><ns0:p>The genomes of S. aureus isolates have several prophages and phage-like element regions and these prophages were belonged to the Siphoviridae family and having temperate lifestyles. The highest number of prophage regions was found in the genome of SA G8 isolate including three intact prophages (phiG8.2, phiG8.3, and phiG8.4), a questionable (phiG8.1), and an incomplete (phiG8.5) prophages. Four prophage regions were found in the genome of SA G6 isolate including an intact prophage (phiG6.3), two questionable prophages (phiG6.1 and phiG6.4), and an incomplete prophage (phiG6.2). The genome of SA H27 isolate harbor three intact prophages (phiH27.1, phiH27.2, and phiH27.3) while the genome of SA H32 harbor only one intact prophage (phiH32.1). The lukF-PV and lukM genes (Bicomponent leukotoxins), and plc gene (Phospholipase C) were identified in the prophages of phiG6.4, phiG8.4, phiH27.2, and phiH32.1. The prophages of phiG6.3, phiG8.4, and phiH27.2 carried sak gene (staphylokinase) and scn gene (staphylococcal complement inhibitor). Chemotaxis inhibitory protein encoded by chp gene was identified in phiG8.4 and phiH27.2 prophages. Enterotoxin A encoded by sea gene was harbored by the prophages of phiG6.3 and phiG8.4. Hemolysin genes such as hlb (&#946;hemolysin), and hlgB (-hemolysin B) were found in the prophages of phiH27.2, and phiH32.1.</ns0:p><ns0:p>In addition to virulence factors, phiG6.4 prophage carried ARGs genes that conferred resistance to beta-lactamase (blaZ), aminoglycoside (ant(6)-Ia and aph(3')-III) and nucleoside (sat-4) antibiotics. The comparative analysis of VFGs associated with putative prophages was summarized in Table <ns0:ref type='table'>S2</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>In-silico analysis of antimicrobial resistance and associated genes in the genomes</ns0:head><ns0:p>Four study genomes of S. aureus isolates shared 63.3% (19/30) of antibiotic resistance and associated genes (Fig. <ns0:ref type='figure' target='#fig_9'>2</ns0:ref>). The shared genes comprise methicillin-resistant PBP2a (mecA and mecR1); multidrug resistance efflux (ygaD); fluoroquinolone (norA and gyrA); fluoroquinolone and acridine dye (arlS and arlR); glycylcycline (mepA); tetracycline (tet-38); tetracycline, penam, cephalosporin, glycylcycline, rifamycin, phenicol, triclosan, fluoroquinolone (mgrA and marR); lipopeptide (pgsA, clsA and rpoC); rifampicin (rpoB); aminocoumarin (gyrB and parE); dihydrofolate reductase (dfrA/folA) and defensin (mprF/fmtC, multiple peptide resistance factor) that play roles in resistance mechanism including antibiotic efflux, antibiotic target alteration, and antibiotic target replacement. The comparative analysis of ARGs revealed that the genome of SA G6 isolate acquired additional ARGs responsible for the resistance of aminoglycoside (aph (3')-IIIa, ant (6')-I and aac (6')-II), nucleoside (sat), fluoroquinolone (qacA). The macrolide, lincosamide, streptogramin (MLS) erythromycin antibiotic resistance genes (emrA) were detected in the genomes of SA G6 and SA G8 isolates while the genome of SA H32 isolate present emrC gene. The penicillin resistance gene (blaZ) was found absent in SA G8 isolate. This in-silico identification and our previous antibiotic susceptibility test results were correlated with beta-lactam, erythromycin (MLS), and vancomycin antibiotic resistance analysis <ns0:ref type='bibr' target='#b112'>(Naorem, et al., 2020)</ns0:ref>. The secondary metabolite biosynthetic gene clusters identified among the genomes were staphylobactin, aureusimine, bacteriocin, and staphyloferrin A. The auto-inducing peptide (AIP)-II gene was identified in SA G6 and SA G8 genomes while AIP-I gene was identified in SA H27 and SA H32 genomes. </ns0:p></ns0:div> <ns0:div><ns0:head>In-silico analysis of virulence-factors encoding genes in the genomes</ns0:head></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The VFGs predicated against the VFDB revealed 59 VFGs were shared in all strains that are responsible for adherence, toxin, anti-phagocytosis immune evasion, secretion system, exoenzyme activity, and iron uptake (Fig. <ns0:ref type='figure'>3</ns0:ref>). The genome of SA G8 isolate has occupied 3.40% of VFGs against its CDS, whereas the genome of SA H32 isolate has 2.97% of VFGs against its CDS.</ns0:p><ns0:p>Adherence associated genes shared in all genomes of S. aureus isolates were 63.63% (14/22) such as autolysin (atl), cell wall-associated fibronectin-binding protein (ebh), elastin binding protein (ebp), fibrinogen binding protein (efb), fibronectin-binding proteins A (fnbA), intercellular adhesin (icaA, icaB, icaC, icaD, icaR), ser-Asp rich fibrinogen-binding proteins (sdrC, sdrD, sdrE), staphylococcal protein A (spa) (Fig. <ns0:ref type='figure'>3A</ns0:ref>). The genome of SA G8 isolates present 77.27% (17/22) of adherence associated genes with additional genes of clumping factor A (clfA), clumping factor B (clfB), and fibronectin-binding proteins (fnbB). Type VII secretion system involves in membrane-associated proteins (esaA, essA, essB, and essC), soluble cytosolic (esaB, esaE, esaG), and secreted virulence factors (esxA, esxB, esxC, esxD, and esaD) were identified in the genomes of SAG6 and SA G8 isolates while the SAH27 and SAH32 isolates absence esaD, esaE, esxB, esxC, and esxD genes (Fig. <ns0:ref type='figure'>3A</ns0:ref>).</ns0:p><ns0:p>The genomes of all isolates shared 29.41% (10/34) of toxin genes such as alpha-hemolysin gene (hla), beta-hemolysin gene (hlb), delta hemolysin gene (hld), gamma hemolysin A (hlgA), gamma hemolysin B (hlgB), gamma hemolysin C (hlgC), enterotoxin-like O (selo), exfoliative toxin type A (eta), and exotoxin (set13, set15) (Fig. <ns0:ref type='figure'>3B</ns0:ref>). The highest number of toxin genes were identified in the genome of SA G8 i.e., 73.52% (25/34), and in addition to shared genes, the extra genes were enterotoxin A (sea), enterotoxin B (seg), enterotoxin Yent1 (yent1), enterotoxin-like K (selk), enterotoxin-like M (selm), enterotoxin-like N (seln), exotoxin (set6, set7, set9, set11, set34, set37, set39), leukotoxin D (lukD), Panton-Valentine leukocidin (lukF-</ns0:p></ns0:div> <ns0:div><ns0:head>PV).</ns0:head><ns0:p>The genes involve in anti-phagocytosis namely capsular polysaccharide synthesis genes belong to stereotype 5 and 8 predominantly present in all the genomes of isolates were capsular polysaccharide synthesis enzyme Cap5A (cap8A), capsular polysaccharide synthesis enzyme Cap5B (cap8B), capsular polysaccharide synthesis enzyme Cap5C (cap8C), probable polysaccharide biosynthesis protein EpsC (cap8D), capsular polysaccharide synthesis enzyme Manuscript to be reviewed fucosamine synthase (cap8G), capsular polysaccharide synthesis enzyme Cap5L (cap8L), capsular polysaccharide synthesis enzyme Cap8M (cap8M), capsular polysaccharide synthesis enzyme Cap8N (cap8N), UDP-N-acetyl-D-mannosamine dehydrogenase (cap8O) and UDP-Nacetylglucosamine 2-epimerase (cap8P) (Fig. <ns0:ref type='figure'>3C</ns0:ref>). Other genes responsible for the host immune evasion such as IgG-binding protein (sbi), staphylococcal complement inhibitor (scn), and chemotaxis inhibiting protein (chp) were identified in all isolates.</ns0:p><ns0:p>Several exoenzymes encoding genes namely cysteine protease/ staphopain (sspB, sspC), hyaluronate lyase (hysA), lipase (geh, lip) serine V8 protease (sspa), staphylocoagulase (coa), staphylokinase (sak), and thermonuclease (nuc) were present in the genomes of all isolates.</ns0:p><ns0:p>However, five genes cluster for serine protease <ns0:ref type='bibr'>(splA, splB, splC, splD, splF)</ns0:ref> were absent in the genomes of SA H27 and SA H32 isolates (Fig. <ns0:ref type='figure'>3C</ns0:ref>).</ns0:p><ns0:p>Eight genes involved in iron uptake mechanism including cell surface protein (isdA), cell surface receptor (isdB) and cell wall anchor proteins (isdC), heme transporter component (isdD), highaffinity heme uptake system protein (isdE), heme-iron transport system permease protein (isdF), sortase B (srtB), heme-degrading monooxygenase; staphylobilin-producing (isdG) were identified in all the genomes of isolates.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparative genome analysis</ns0:head><ns0:p>The genome comparative analysis based on ANIb matrices results indicated that the genome of SA G8 isolate exhibits the nearest identities to all genomes. SA G8 genome showed ~99.5% identities to SA G6 genome. The genomes of SA G6 and SA G8 exhibited ~99.7% identities to S. aureus subsp. aureus ST228 (HE579071.1). Also, the genomes of SA H27 and SA H32 showed 99.9% identities to each other and these two genomes displayed the highest identities (99.9%) to S. aureus subsp. aureus HO 5096 0412 (HE681097.1) (Fig. <ns0:ref type='figure' target='#fig_8'>S1</ns0:ref>). The digital DDH values between the genome of S. aureus isolates and the closest relative genomes were 90.7-100% (using GBDP distance formula d0), 77.1-97.0% (using GBDP distance formula d4), and 91.1-99.9% (using GBDP distance formula d6). SA H27 and SA H32 genomes exhibit the nearest identities of 99.9%, 99.8%, and 100 % using the formula d0, d4, and d6 respectively and displayed G+C difference of 0.01%. However, the SA G6 genome showed less identity to all the comparative genomes based on dDDH. The high G+C constituent difference (0.1%) was observed in the case of isolated strains of SA G8 and SA H32 genomes.</ns0:p><ns0:p>A whole-genome circular comparative map of four S. aureus genomes and their close reference genomes was generated against S. aureus subsp. aureus HO 5096 0412 (HE681097.1) genome using CGView server based on BLAST sequence similarities. Each genome was indicated by a different color, and the darker areas in the circular genome showed a 100% sequence similarity with the reference genome, while the lighter (gray) areas showed a 70% sequence similarity (Fig. <ns0:ref type='figure'>4</ns0:ref>). The map revealed less gap between the SA H27 (CP032161) and SA H32 (RAHP00000000) genomes showing high proximity between them when compared to other genomes. SA G6 (RAHA00000000) genome has many gaps with white color than the other genomes showing a distant relationship.</ns0:p><ns0:p>The SEED subsystem categories identified by RAST revealed that the genomes of all the isolates possessed 'amino acids and derivatives' was the largest subsystem, followed by 'carbohydrates', 'protein metabolism', and 'cofactors, vitamins, prosthetic groups, pigments' (Fig. <ns0:ref type='figure'>5A</ns0:ref>). The 'carbohydrate', and 'protein metabolism' subsystems were found largest in SA H27 (12.76%) and SA H32 (10.47%) genomes, respectively. The subsystem belongs to 'phages, prophages, pathogenicity island' (2.5%) was identified as highest in the SA G8 genome.</ns0:p><ns0:p>Amongst the genomes, the SA G6 genome has the largest subsystem of 'amino acids and derivatives' (15.9%), and 'virulence, disease, and defense' (4.43%). In the 'virulence, disease, and defense' subsystem of SA G6, 93 genes associated with adhesion, bacitracin stress response, colicin v, and bacteriocin production cluster, copper homeostasis, bile hydrolysis, cobalt-zinccadmium resistances, multidrug resistances, 2-protein, mercuric reductase, mercury resistance operon, streptothricin resistance, teicoplanin-resistances, aminoglycoside adenylyltransferases, fluoroquinolone resistances, arsenic resistance, fosfomycin resistance, beta-lactamase, cadmium resistance, multidrug resistance efflux pumps, and invasion and intracellular resistances. In the comparative eggNOG function study of S. aureus genomes, 'amino acid transport and metabolism' was observed as for the majority of COGs, followed by those COGs related to 'translation, ribosomal structure, and biogenesis', 'transcription', and 'cell wall/membrane/envelope'. The eggNOG analysis results revealed that the SA G6 genome has the highest number of COGs associated with defense mechanisms (Fig. <ns0:ref type='figure'>5B</ns0:ref>). In the core genomes, 9.46%, 7.21%, and 6.9% of COGs had functions associated to 'amino acid transport and metabolism (E)', 'translation, ribosomal structure, and biogenesis (J)', and 'transcription Manuscript to be reviewed (K)', respectively. Amongst the functional prediction of genomes, most COGs were associated with 'function unknown (S)'.</ns0:p></ns0:div> <ns0:div><ns0:head>Pan-genome, core-genome, and singletons analysis</ns0:head><ns0:p>The orthologous groups are categories into three groups based on the pan-genome distribution such as core (present in all genomes of S. aureus strains), dispensable (present in at least two strains, but not all), and singleton genes (present no orthologs in any other genomes). The comparison of four study S. aureus genomes generated a pan-genome size of 3265 genes, of which 2304 (70.6%) genes were core genome, 462 (14.2%) genes were dispensable, and 499 (15.3%) genes were singletons. The Rcp value for the genomes of S. aureus isolates was calculated and the ratio Rcp was 0.70 and it is indicated that the genomes of S. aureus isolates were high inter-species diversity. A total of 499 singleton genes were calculated across the genomes of four S. aureus isolates, of which SA G6 genome acquired the highest number of singleton genes (220) that constitute the genes encode for proteins viz. aminoglycoside 3phosphotransferase, aminoglycoside 6-phosphotransferase, aminoglycoside N(6)acetyltransferase, streptothricin acetyltransferase, antiseptic resistance protein, cadmium resistance proteins, cadmium efflux system accessory protein, cadmium-transporting ATPase, ferric siderophore transport system, mercuric ion reductase, anti-adhesin, Tn552 transposase, pathogenicity islands (SaPI and SaPIn2), prophage-like elements, mobile elements, phage associated hypothetical proteins, hypothetical proteins, etc. The identified singleton genes of SA G6 genome were present within the genomic island (GI). This GI region is located between 2804353-2873411 base pair sequence region of the genomic sequence. While the SA H27 genome has the least singleton genes (6) constituting the genes encode for hypothetical proteins and phage proteins. The difference in the genomic constituents between the genome of SA H27 and SA H32 isolates revealed that SA H32 acquired the genes encoding for 23S rRNA (adenine(2058)-N( <ns0:ref type='formula'>6</ns0:ref>))-dimethyltransferase, replication and maintenance protein, hypothetical proteins, phage-like elements, and mobile element protein. The genes shared by four study genomes and their respective singletons is represented in Fig. <ns0:ref type='figure'>6A</ns0:ref>. When the three reference S. aureus genomes were included in the pan-genome analysis, the core/pan-genome ratio drop down by 18.97% with inflation of pan-genome to 3415 genes and deflation of core-genome to 1762 genes. The core-genome and singleton genes formed by seven genomes of S. aureus strains is represented in flower-plot (Fig. <ns0:ref type='figure'>6B</ns0:ref>). When the three reference genomes of S. aureus strains were included in the pan-genome analysis, SA G6 isolate occupied the highest number of singleton genes (104) while SA H27 isolate has the lowest singleton gene (2) (Fig. <ns0:ref type='figure'>6B</ns0:ref>). In the pan-genome development analysis of seven S. aureus strains, &#945; value (the power-law coefficient) was estimated as 0.141 which corresponds to the growing and open pan-genome model (Fig. <ns0:ref type='figure' target='#fig_9'>S2</ns0:ref>). The pan vs. core development plot appeared the progression of the pan and coregenomes as additional genomes are added for analysis, and showing that the sharp decline of the core-genome size with the introduction of S. aureus subsp. aureus ST228 (HE579073) (Fig. <ns0:ref type='figure'>6C</ns0:ref>).</ns0:p><ns0:p>In the plot of core-genome development, the core-genome size approach (&#937;) value revealed that the core-genome size of seven S. aureus would be declined to 1404.8 (Fig. <ns0:ref type='figure'>S3</ns0:ref>). The singleton development analysis suggested that the pan-genome size will continue to expand at the rate of 35.9 genes per novel, representative genome (Fig. <ns0:ref type='figure'>S4</ns0:ref>). The shape of the pan-genome vs. coregenome curve showed fluctuation in their gene numbers when different order of the genomes was set, even so, pan-genome and core genome developmental plots result remained unaffected by the genomes order.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparative phylogenetic tree analysis</ns0:head><ns0:p>The phylogenomic analysis of S. aureus isolates provide the tree into three major clades (Fig. <ns0:ref type='figure'>7A</ns0:ref>). The clade A consists of 5 strains that belonged to CC22 and showing that Hungarian isolates, SA H27 and SA H32 have the highest proximity. Germany isolates, SA G6 and SA G8 isolate and other strains belonged to CC5 were clustered in the clade C, showing that SA G6 isolate has closely relatedness to S. aureus subsp. aureus ST228 (HE579071.1) and the SA G8 isolate has a higher relatedness to S. aureus subsp. aureus JH9 (CP000703.1) than SA G6 isolate.</ns0:p><ns0:p>The phylogenetic relationship inferred from core-genome SNPs holds a similar agreement with the whole genome-based phylogenetic analysis, and these methods could be useful in distinguishing the genomes even in the strain level and phylogenetic trees are illustrated in Fig.</ns0:p></ns0:div> <ns0:div><ns0:head>7B.</ns0:head></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>S. aureus is a significant causative agent of both hospital and community-associated infections <ns0:ref type='bibr' target='#b28'>(Chambers and DeLeo, 2009)</ns0:ref>. The study of such pathogen at a molecular level through genome comparative analysis improve the ideas of pathogenesis and evolution. Further, such a study provides advantages in diagnosis, treatments, and infection controls <ns0:ref type='bibr' target='#b79'>(Kwong et al., 2015)</ns0:ref>. In the present study, we used whole-genome sequencing (WGS) and in-silico analysis to determine the comparative ARGs, VRGs, pH tolerance associated genes, and evolutionary relationship of four S. aureus isolated from different sites of human infection such as skin, nostril, trachea, and others.</ns0:p><ns0:p>The molecular epidemiology study of MRSA helps to find the risk factors associated with MRSA infections and able to differentiate the several MRSA strains <ns0:ref type='bibr' target='#b106'>(Mistry et al., 2016)</ns0:ref>. The genome-based molecular epidemiology studies found that Germany isolates exhibit SCCmec type I with ST228, and SCCmec type II with ST225 while Hungarian isolates hold SCCmec type IVa with ST22. Also, agr type II and I were owned by Germany and Hungarian isolates, respectively (Table <ns0:ref type='table'>1</ns0:ref>). According to previous studies suggested that MRSA strains with SCCmec types I or II or III are dominant among the HA-MRSA, while SCCmec types IV or V are the characteristic of CA-MRSA <ns0:ref type='bibr' target='#b107'>(Monecke et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b34'>Chua et al., 2014)</ns0:ref>. The STs of Germany isolates belonged to CC5 which is typical of HA-MRSA, while Hungarian isolates suggest its relationship CA-MRSA. In hospitals, the multidrug-resistance SCCmec type III was replaced by the multidrug-susceptible SCCmec type IV (ST22) strains slowly <ns0:ref type='bibr'>(D'Souza et al., 2010)</ns0:ref>. The Hungarian isolates were found positive to Panton-Valentine Leukocidin (PVL) toxin, which is commonly used as a marker of CA-MRSA <ns0:ref type='bibr' target='#b135'>(Shukla et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b137'>Singh et al., 2015)</ns0:ref> besides this toxin has shown to play a role necrosis, accelerating apoptosis and polynuclear-and mononuclear cells lysis, thereby contributing morbidity and mortality <ns0:ref type='bibr' target='#b11'>(Barrera-Rivas et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b88'>Lina et al., 1999)</ns0:ref>.</ns0:p><ns0:p>Staphylococcal &#946;-lactamase encoded by blaZ gene is carried by the transposon Tn552 or Tn552like elements located on a large plasmid and can be non-inducible or inducible with antibiotics <ns0:ref type='bibr' target='#b95'>(Maddux, 1991)</ns0:ref>. It was noticed that blaZ gene was absent in SA G8 isolate, probably due to the curing of blaZ positive plasmid <ns0:ref type='bibr' target='#b127'>(Pugazhendhi et al., 2020)</ns0:ref>. Erythromycin resistance gene (ermA) was detected in the chromosome of SA G6, and SA G8 isolates, however, emrC gene was found in the plasmid of SA H32 (Fig. <ns0:ref type='figure' target='#fig_8'>1B</ns0:ref>). It was suggested that these genes may not be involved in the loss of specific ARGs for environmental adaptation, but it is expected to be essential for these isolates <ns0:ref type='bibr' target='#b87'>(Lim et al., 2015)</ns0:ref>.</ns0:p><ns0:p>MRSA is responsible for causing biofilm infections that are more difficult to treat and need more intensive care as compared to Staphylococcus epidermidis biofilm <ns0:ref type='bibr' target='#b128'>(Reffuveille et al., 2017)</ns0:ref>. The principal component of biofilm formation is PIA which consists of different intracellular Manuscript to be reviewed adhesion (ica) genes <ns0:ref type='bibr' target='#b36'>(Cramton et al., 1999)</ns0:ref> and play a crucial role in the initial stage of bacterial cell adherence to surfaces and intercellular adhesion for the cells to aggregate <ns0:ref type='bibr' target='#b42'>(Farran et al. 2013</ns0:ref>). These genes were detected in all isolates however, the biofilm production ability varies from weak to strong were observed in our previous study <ns0:ref type='bibr' target='#b112'>(Naorem et al., 2020)</ns0:ref>. Our previous study identified that SA G6 isolate obtained from skin infection showed a weak biofilm-forming ability <ns0:ref type='bibr' target='#b112'>(Naorem et al., 2020)</ns0:ref>. The low biofilm formation in SA G6 might be degraded the biofilm by DNase enzyme found in skin cells <ns0:ref type='bibr' target='#b41'>(Eckhart et al., 2007)</ns0:ref>. The previous study revealed that the presence of the ica genes did not always correlate with biofilm <ns0:ref type='bibr' target='#b109'>(M&#248;retr&#248; et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b113'>Nasr et al., 2012)</ns0:ref>. Some authors reported that despite the presence of ica operon, some staphylococcal isolates produce weak biofilm production due to the inactivation of icaA by insertion of IS256 <ns0:ref type='bibr' target='#b33'>(Cho et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b74'>Kiem et al., 2004)</ns0:ref>. Further reported that the insertion of IS256 inactivates mutS and contributes to vancomycin resistance development in vancomycin-intermediate S.</ns0:p><ns0:p>aureus strains <ns0:ref type='bibr' target='#b76'>(Kleinert et al., 2016)</ns0:ref>. Also, the upregulation of icaA and icaD genes during acidic stress promotes biofilm formation which in-turn plays a role to resist it from acidic and alkaline environments and establishes the niche adaptation in Staphylococcus strains <ns0:ref type='bibr' target='#b91'>(Lindsay et al., 2006)</ns0:ref>. In addition to ica locus, the presence of clfA, clfB, and epbs genes initiates the biofilm formation <ns0:ref type='bibr' target='#b49'>(Ghasemian et al., 2015)</ns0:ref>, however in the present study, the SA H27 isolate carried clfA, and epbs genes and showed strong biofilm formation in our previous study <ns0:ref type='bibr' target='#b112'>(Naorem et al., 2020)</ns0:ref> compared to other isolates while SA G8 and SA H32 isolates carried clfA, clfB, and epbs genes though their biofilm formation was relatively low, suggesting that presence or absence of such genes have no significant in biofilm formation. A recent study reported that sdrC mutant exhibited significantly inhibited biofilm formation <ns0:ref type='bibr' target='#b30'>(Chen et al., 2019)</ns0:ref> and the expression of the ica operon and sdrC are highly responsive to biofilm formation <ns0:ref type='bibr' target='#b133'>(Shin et al., 2013)</ns0:ref>. Our study revealed the sequence variation in sdrC in Hungarian isolates, this variation might influence the biofilm formation. The global regulatory gene, agr repression has been associated with biofilm formation and its induction through AIP results in seeding dispersal in mature biofilm <ns0:ref type='bibr' target='#b19'>(Boles and Horswill, 2008)</ns0:ref>. CA-MRSA strains showed higher activity of agr, which controls and enhance the virulence (Aires-De-Sousa, 2017). It was reported that S. aureus strains belonged to agr I group exhibited a strong biofilm-forming ability than the strains belonged to agr IV group <ns0:ref type='bibr' target='#b153'>(Zhang et al., 2018</ns0:ref>) and a similar result was observed in one of our isolate SA H27. In addition to this extracellular adherence protein (encoded by eap gene), and beta toxin (encoded by hlb gene) play a role in biofilm maturation <ns0:ref type='bibr' target='#b66'>(Huseby et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b138'>Sugimoto et al., 2013)</ns0:ref>. In our finding showed that eap gene was present only in the SA H27 isolate and this gene might be attributed to high biofilm formation. Since biofilm formation involves many factors/ genes that take part in PIA dependent or independent biofilm, biofilm formation by regulator genes and eDNA <ns0:ref type='bibr' target='#b6'>(Archer et al., 2011)</ns0:ref>. Also, the presence of such genes in S. aureus may not provide much impact on biofilm formation profiling. There was a difference in the prevalence of biofilmassociated genes between the isolated strains and suggests that the presence of genes encoding biofilm formation is not an absolute determinant of biofilm formation ability observed in our previous study <ns0:ref type='bibr' target='#b112'>(Naorem et al., 2020)</ns0:ref>. Thus, our future studies will focus on the expression profiling of such relevant genes which may be necessary to determine the key genes involved in biofilm formation. The high survival rates were observed in both acidic and alkaline pH conditions in all isolates was evaluated by the genomic study, it is elucidated that all the isolates possessed the arginine deiminase and urease operon that aids in the generation of ammonia due to the hydrolysis of Larginine and urea by arginine deiminase and urease. The released ammonia and urea counteract the acidic environment <ns0:ref type='bibr' target='#b35'>(Cotter and Hill, 2003;</ns0:ref><ns0:ref type='bibr' target='#b144'>Valenzuela et al., 2003)</ns0:ref>. Further, the proton efflux pump (F&#8320;F&#8321; ATPase) plays a role to extrude H&#8314; out of the cells and maintains the pH homeostasis <ns0:ref type='bibr' target='#b46'>(Foster, 2004;</ns0:ref><ns0:ref type='bibr' target='#b96'>Maurer et al., 2005)</ns0:ref>. However, in the case of alkaline tolerance, it was reported that the S. aureus genome encodes a unique Ktr-like system where the cytoplasmic gating protein KtrC regulates the uptake of K&#8314; that is essential for maintaining cytoplasmic pH and supporting H&#8314; efflux under alkaline conditions <ns0:ref type='bibr' target='#b56'>(Gries et al., 2016)</ns0:ref>.</ns0:p><ns0:p>The ability of S. aureus as a pathogen can be accredited to its arsenal of virulence factors among which secreted pore-forming toxins (PFTs), exfoliative toxins (ETs), ESAT-6-like proteins, exoenzymes, and superantigens (SAgs) play a significant role in the pathogenesis of invading infections in healthy individuals <ns0:ref type='bibr' target='#b120'>(Otto et al., 2014</ns0:ref><ns0:ref type='bibr'>, Bartiett et al., 2010)</ns0:ref>. The presence of hlb gene in the isolates contributes to the phagosomal escape of S. aureus and influences biofilm development <ns0:ref type='bibr' target='#b66'>(Huseby et al., 2010</ns0:ref><ns0:ref type='bibr' target='#b126'>, Periasamy et al., 2012)</ns0:ref>. The PVL toxin was identified in the prophages of Hungarian isolates and expressing Sa2 integrase. These isolates have cytolytic activity against blood cells and leukocytes, contributing to the S. aureus pathogenicity <ns0:ref type='bibr' target='#b146'>(Vandenesch et al., 2003)</ns0:ref>. Staphylococcal enterotoxins (SEs) or staphylococcal superantigens proteins (SAgs) are well-known for causing food poisoning, localized epidermal infections Manuscript to be reviewed (bullous impetigo), and generalized diseases (Staphylococcal scalded skin syndrome) <ns0:ref type='bibr' target='#b57'>(Grumann et al., 2014</ns0:ref><ns0:ref type='bibr' target='#b7'>, Argud&#237;n et al., 2010)</ns0:ref>. SEs encoding genes are located on mobile elements including bacteriophages, pathogenicity islands (SaPI), or plasmids. In this study, SEs encoding genes such as sea, seg, sei, yent1, yent2, selk, selm, seln, and selo were identified. Hungarian isolates, SA H27, and SA H32 acquired seg and sei genes, however sei gene was absent in Germany isolates, SA G6, and SA G8. These seg and sei genes belong to egc (enterotoxin gene cluster), involve in staphylococcal food poisoning TSS, and SSF <ns0:ref type='bibr' target='#b69'>(Jarraud et al., 2001</ns0:ref><ns0:ref type='bibr' target='#b31'>, Chen et al., 2004)</ns0:ref> and egc was distributed widely in clinical isolates and playing a role in pathogenesis <ns0:ref type='bibr' target='#b69'>(Jarraud et al., 2001)</ns0:ref>. Exfoliative toxins (ETs) are known as epidermolytic toxins that induce skin shedding and blister formation <ns0:ref type='bibr'>(Melish and Glasgow, 1971)</ns0:ref>. In this study, eta gene encoded for ETA toxin was found in all the isolates and responsible for causing human skin damage, and most prevalent in Europe <ns0:ref type='bibr' target='#b81'>(Ladhani, 2001)</ns0:ref>. Capsular polysaccharide synthesis genes are almost all detected in clinical isolates S. aureus showing significant virulence by targeting the antibodies that protect against Staphylococcal infections <ns0:ref type='bibr'>(Su et al., 1997)</ns0:ref>. Type VII secretion system (T7SS) was present in Germany isolates (Fig. <ns0:ref type='figure'>3A</ns0:ref>) and promoting them to persist in their hosts <ns0:ref type='bibr' target='#b142'>(Tchoupa et al., 2019)</ns0:ref>. The esxA and esxB gene show a significant role in the distribution and colonization of S. aureus, and activation of the cell-mediated immune responses, boost the pathogenesis <ns0:ref type='bibr' target='#b22'>(Burts et al., 2005)</ns0:ref>. Also, esaD gene found only in Germany isolates suggesting that this gene can inhibit the growth of other closely related S. aureus strains and playing a role in an intra-species competition <ns0:ref type='bibr' target='#b24'>(Cao et al., 2016)</ns0:ref>. The family of beta-hemolysin converting phage encodes proteins such as SCIN (staphylococcal complement inhibitor) and CHIPS (chemotaxis inhibiting protein of staphylococcus) involved in host-pathogen interaction and contribute to evading human innate immune response <ns0:ref type='bibr' target='#b148'>(Wamel et al., 2006)</ns0:ref>, these proteins were identified in intact prophages of SA G8 and SA G27 genomes but CHIPs was absent in the prophages of SA H32 genome. Therefore, prophages were the reservoir of virulence and resistance factors that play a role in the evolution of virulence strains and causing a major threat to human and animal health <ns0:ref type='bibr' target='#b11'>(Barrera-Rivas et al., 2017)</ns0:ref>. The presence of ARGs and VFGs in the prophage regions of SA G6 genome differentiates it from the other S. aureus isolates and may determine its greater pathogenic potential by modifying its antigenicity <ns0:ref type='bibr' target='#b11'>(Barrera-Rivas et al., 2017)</ns0:ref>. Also, plasmid p1G6 carried qacA gene, which is known to decrease chlorhexidine (antiseptic) susceptibility and giving an event of MGEs transfer evidence of qacA across the S. aureus strains <ns0:ref type='bibr' target='#b80'>(LaBreck et al., 2018)</ns0:ref>. The harbor Manuscript to be reviewed of MGEs (mosaic features of prophages and plasmids) contributes to the tremendous distribution of ARGs and VFGs among the S. aureus isolates <ns0:ref type='bibr' target='#b98'>(McCarthy and Lindsay, 2012;</ns0:ref><ns0:ref type='bibr' target='#b99'>McCarthy et al., 2014)</ns0:ref>. This MGEs transfer event could be useful for the survival of S. aureus in different ecological niches <ns0:ref type='bibr' target='#b89'>(Lindsay, 2010)</ns0:ref>.</ns0:p><ns0:p>The pangenome described here is composed of 3415 genes, of these, 1762 genes are shared among S. aureus isolates (Fig. <ns0:ref type='figure'>6B</ns0:ref>). Functional annotation of the core-genome revelated that they are mostly associated transcription and translation, and different metabolism categories, such similar result was reported previously <ns0:ref type='bibr' target='#b21'>(Bosi et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b132'>Sharma et al., 2018)</ns0:ref>. The core-genome and accessory genome functional characterizations revealed that S. aureus isolates required amino acids than carbohydrates as the energy source and suggests that these isolates adapted to grow in a protein-rich medium than carbohydrates (Fig. <ns0:ref type='figure'>5A and 5B</ns0:ref>). It was suggested that the survival of S. aureus can be maintained by the catabolism of amino acids <ns0:ref type='bibr' target='#b61'>(Halsey et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The core-genome has 51.6% of genes and validated that S. aureus is a clonal species <ns0:ref type='bibr' target='#b44'>(Feil et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b21'>Bosi et al., 2016)</ns0:ref>. The mutation event that occurred in the core-genome of closely related S. aureus provides important roles in virulence and persistence of S. aureus strains <ns0:ref type='bibr' target='#b73'>(Kennedy et al., 2008)</ns0:ref>. So, an in-depth analysis of strain-specific genetic variation is required for further understanding of the pathogenicity. The inflation of pan-genome and deflation of core-genome was seen after the introduction of reference genomes and its regression analysis revealed that the pan-genome is open, suggesting that the gene repertoire of this species is theoretically limitless.</ns0:p><ns0:p>A similar finding was observed in the DNA microarray experiment of thirty-six S. aureus isolates <ns0:ref type='bibr' target='#b45'>(Fitzgerald et al., 2001)</ns0:ref>. The drastic decline of the core/pan-genome ratio after the introduction HE579071.1 (S. aureus subsp. aureus ST228) and SA G6 suggested that these two strains have distinct genomic contents (Fig. <ns0:ref type='figure'>6C</ns0:ref>). The genomic content variation between the genomes is due to the acquisition of certain genes that encode for virulence and resistance factors, pathogenicity islands, prophage-like elements, plasmids, mobile element proteins, and hypothetical proteins in the GIs. These GIs are mobilized across organisms via HGT events <ns0:ref type='bibr' target='#b131'>(Schmidt and Hensel, 2004)</ns0:ref>. This finding was supported by gaps that appeared in the genome ring of SA G6 genome and suggesting that this isolate showed a distant relationship to others (Fig. <ns0:ref type='figure'>4</ns0:ref>). The gaps that appeared in the map are due to the GC% content difference in the comparative genomes, and it results from the event of MGEs transfer via HGT and the GC skewed regions indicated the regions where HGT occurred <ns0:ref type='bibr' target='#b63'>(Hayek, 2013)</ns0:ref>. </ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>We specifically analyzed the presence of ARGs and VFGs in the core genomes and pangenomes. Some genes involved in multidrug resistance or drug efflux such ygaD, arlR, arlS, and mepA are components of the core-genome (Fig. <ns0:ref type='figure' target='#fig_9'>2</ns0:ref>). The large repertoire of genes (29%) in the accessory genome gives advantages in adaptation and that can contribute to pathogenicity or niche specificity of strains <ns0:ref type='bibr' target='#b101'>(Medini et al., 2005)</ns0:ref>. The analysis of pangenome is essential to understand the event of MGEs transfer and S. aureus evolution <ns0:ref type='bibr' target='#b124'>(Ozer, 2018)</ns0:ref>. The interpretation from the dispersible and singleton genes content analysis of S. aureus genomes allows us to understand the genetic variation among the CC5 and CC22. Juhas et al. reported that most dispensable and singleton genes were acquired through HGT and operate an important role in drug resistance or virulence <ns0:ref type='bibr' target='#b70'>(Juhas et al., 2012)</ns0:ref>. A high portion of unique genes or singletons in S. aureus genomes were related to MGEs, which could drive the gaining of novel functional elements especially drug resistance and virulence. These singletons are the main drivers of the phenotypic variation within S. aureus strains and the evolution of S. aureus <ns0:ref type='bibr' target='#b26'>(Carvalho et al., 2019)</ns0:ref>.</ns0:p><ns0:p>The phylogenetic trees based on whole-genome and core-genome SNP methods support each other and revealed that these methods were able to distinguish between strains at a higher resolution in terms of the geographic origin of strains and phylogenetic trees are illustrated in Fig. <ns0:ref type='figure'>7</ns0:ref>. The phylogenomic analysis revealed that the strains with ST225 (Germany), ST228 (Germany, Switzerland), ST105 (USA), and ST5 (Japan) were clustered in the same CC5 clade (Cluster C), and a different clade (Cluster A) was noticed among the UK origin ST22 (CC22) and diverged from Germany origin strains (Fig. <ns0:ref type='figure'>7A</ns0:ref>), this finding was in good agreement with the previously published article <ns0:ref type='bibr' target='#b0'>(Aanensen et al., 2016)</ns0:ref>. The CC5 (ST225) and CC22 (ST22) were found to be the most dominant clones circulating in Europe <ns0:ref type='bibr' target='#b59'>(Grundmann et al., 2014)</ns0:ref>. The comparative genome analysis revealed that Germany and Hungarian isolates are genetically diverse and showing variation among them due to the gain or loss of MGEs such as SCCmec, plasmid, phage elements, or the insertion of transposase. The event of MGEs transfer was observed in ST5, ST225, and ST228 (Fig. <ns0:ref type='figure'>7A</ns0:ref>), and similar results were also reported previously <ns0:ref type='bibr'>(N&#252;bel et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b114'>N&#252;bel et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b147'>Vogel et al., 2012)</ns0:ref>. The SNPs located in the core-genome define as the element present in S. aureus strains, these SNPs based phylogenetic tree was constructed to avoid the HGT of MGEs misuse phylogenetic interpretation, as well as this tree, resolved the subdivision within cluster C of Fig. <ns0:ref type='figure'>7A</ns0:ref> indicating that SA G6 isolates and S. aureus subsp. aureus ST228 exhibits the closest strains (Fig. <ns0:ref type='figure'>7B</ns0:ref>). These strains shared the genetic background (ST228/SCCmec-I) and revealing 99.8% OrthoANIu similarity value in their genomes, likewise, Hungarian isolates (SA H27 and SA H32) in clade A (Fig. <ns0:ref type='figure'>7B</ns0:ref>) shared molecular epidemiological background in terms of SCCmec-IVa, and ST-22 and showing 99.8% OrthoANIu value. However, SA G8 isolate and S. aureus subsp. aureus ST228 belongs to ST225 and ST105, respectively were clustered together (Fig. <ns0:ref type='figure'>7B</ns0:ref>). The strains with the same genetic background were clustered together in both phylogenetic trees which suggest that these strains are highly alike, however comparative genome analysis exposed that the acquisition of phage elements and plasmids through the events of MGEs transfer contribute to differences in their phenotypic characters. Such events provide an impact on the fitness or pathogenicity or epidemicity of the strains.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Using WGS, we characterized the four clinical MRSA isolates that infect the skin, nostrils, trachea, and other sites. The data generated from the WGS confirmed the diversity of MRSA among the same CC5 and CC22. It is clearly stated that the biofilm-forming ability of MRSA was not correlated with the presence of biofilm-forming encoding genes, also the genetic constituents have no information regarding the infection sites. So, expression profiling of biofilm-related genes is required to define the key genes involved in biofilm formation. The comparative genome study allowed the segregation of isolates of geographical origin, and differentiation of clinical isolates from the commensal isolates. An interesting finding is the addition of SA G6 genome responsible for open pan-genome and diversity among genomes. The openness of pan-genomes of S. aureus isolates relies on the acquisition of MGEs. The evidence of MGEs transfer event especially in SA G6 is supported by the drastic drop of the core/pangenome ratio curve, and gaps and GC skewed regions in comparative genome map. The presence of ant( <ns0:ref type='formula'>6</ns0:ref>)-Ia, aph(3')-III) and sat-4 in the GI region of SA G6 are likely acquired and these genes may provide fitness and a selective advantage during host-adaptation and colonization. Phylogenetic analysis suggests that SA G6 and S. aureus subsp. aureus ST228 strains are distinct from its group. The acquisition of plasmid and prophage functional modules such as ARGs and VFGs in S. aureus isolates contributes a major role in the rapid evolution of pathogenic S. aureus lineages and that confer specific advantages in a defined host under environmental conditions. Through this comparative genome analysis would improve the knowledge about the pathogenic </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:2:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:2:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Cap8E (cap8E), capsular polysaccharide synthesis enzyme Cap5F (cap8F), UDP-N-acetyl-L-PeerJ reviewing PDF | (2020:05:49105:2:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:2:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:2:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:2:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:2:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49105:2:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='45,42.52,70.87,525.00,378.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='47,42.52,275.62,525.00,330.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='48,42.52,270.37,525.00,285.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='49,42.52,250.12,525.00,268.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='51,42.52,70.87,525.00,402.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='52,42.52,275.62,525.00,368.25' type='bitmap' /></ns0:figure> </ns0:body> "

"UNIVERSITY OF PÉCS Faculty of Sciences Institute of Biology Dear Editors, Pecs, 17, September 2020 We would like to thank the anonymous reviewers for their kind efforts to improve the manuscript by pointing out several mistakes. As per the suggestions of the reviewers we have modified and corrected manuscripts to comply with the questions raised by the reviewers. We hope that the manuscript is suitable for publication in your esteemed PeerJ Journal. Thanking you for your valuable time and looking forward to hearing from you. With kindly regard Sincerely yours, Dr. habil. Csaba Fekete, PhD Prof. and Head, Department of General and Environmental Microbiology, Leader of the Microbial Biotechnology Group, Former Deputy Director of the Institute On the behalf of all authors. University of Pécs, Department of General and Environmental Microbiology, 7624 Pécs, Ifjúság u.6., Hungary, Tel.: ++(36) 72 503 600; Extension: 4815 or 4810, Tel./Fax: ++(36)72 501 573, E-mail: [email protected] Reviewer 1 (Juan J Valdez A) Basic reporting The manuscript has been revised for the English style and is now more properly written. However, there are still some details in verb conjugation along the manuscript, please review grammar in more detail. Again, a professional language editing service may be useful. Authors have reviewed literature on comparative genomics of MRSA genomes and included it for introduction and discussion. Authors have also inserted an hypothesis and justification for the selection of the strains, so the comparative genomics is now justified. Literature references were complemented and are in accordance with the results analysis and discussion. Figures are relevant for the manuscript. Reply: As per your suggestion, we modified those mistakes in this current manuscript Experimental design The research presented fits with the Aims and Scope of the Journal. The main question has now been stated and an hypothesis has been presented, so the comparative genomics analyisis is justified. Comparative genomics is performed with enough rigor to support the results. Methods are described with enough detail to be reproduced and are adequate to reach the goal of comparative genomics Validity of the findings Differences in the genetic background of the selected strains were already known by the authors and now they have been provided to enrich the genomic analysis and the interpretation of the findings. Genomic analysis is robust and well analysed with appropriate analysis tools. Clear genetic background description of the tested strains is now available, and certainly helps to clarify relatedness and differences among strains. Comments for the Author The manuscript presents a detailed description of the comparative genomics of four isolates of Staphylococcus aureus resistant to methicillin (MRSA) from Germany and Hungary. Although the methodology and results are well described, authors should consider several issues to improve their manuscript before it could be accepted for publication. Abstract: Although a hypothesis has been elaborated, this must be clearly stated in the abstract, and clear identification of the strains tested in the work must be included. The abstract content is clumpsy but it contains the information that is relevant to the research. Reply: As per your suggestion, the abstract was corrected. All of my previous suggestions on information presentation, analysis and discussion were attended, and were properly directed to improve the contributions of the manuscript to general knowledge on the topic. Besides, they included an important analysis of gene distribution in pangenome, core genome and distribution of singletons among strains that contribute to understand potential pathogenic features of the analysed strains. Some minor observations.: Line 34: indicate the identifier of the Hungarian isolate Reply: As per your suggestion, we included the strain/ isolate names in line number 37. Line 111. An example of the need of reviewing grammar; authors cite a previously published work and conjugate “includes” in present tense. Reply: We agreed your suggestion, the “includes” word has changed to “included” in line 111. Lines 251 to 253. There is no reference to the table that present those results. Reply: As per your suggestion, we include the reference table as Table S1 in line 251 and Table S1 was uploaded in supplementary file as Supplementary Table S1. Lines 255 to 262. This phrase is to long; divide in several phrases and improve syntaxis. Reply: Thanks for your suggestion, we modified the text (line numbers 255-262) Line 265: The term “epidemiologic characteristics” refer to the surrounding, environmental or social factors that are related to the outcome of a disease. The authors refer to molecular techniques that are frequently used in molecular epidemiology studies that provide information on the genetic background of the strains. Please rephrase to fit these concepts. Reply: Thanks for your suggestion, we modified the term “epidemiologic characteristics” as molecular type in line 265. Line 285. Probably authors mean “phage transduction”. Reply: As per your suggestion, we corrected as phage transduction instead of word phage in line 282. Line 306. Table S1. Please correct the Greek letter in beta-lactamase. Reply: We agreed your suggestion, we replaced beta with Greek letter in Table S1. Line 502. Correct the Greek letter in beta-lactamase Reply: We agreed your suggestion, we replaced beta with Greek letter in line 499. Line 638. “Distribution” instead of “diversity”? Reply: As per your suggestion, the text was corrected in line 603. Lines 685 to 687. It is not clear to me why this conclusion: “….thus HGT was not limited within S. aureus strains”. Does it mean that authors have evidence of HGT from other species or from strains outside of this study? Which is that evidence? Please clarify. Reply: As per your suggestion, the text has modified. We did not perform any bioinformatics analysis to show the evidence. We simplified the text in line 684-685. Reviewer 2 (Anonymous) Basic reporting In this work Feteke et. al. performs a genome analysis of four strains from methicillin-resistant Staphylococcus aureus (MRSA). The aim and scope of the article is very interesting and relevant. However, the manuscript is not clear and unambiguous, and the writing must be improved since it is difficult to follow in some parts. Some examples are: • It is not clear the origin and reasons why the four strains were selected from the previous study (lines 110124). Reply: In our previous study, the polyphasic characterization showed that SA H27 and SA H32 were group together and both were belonged to same Clonal complex (CC22) and origin, however SA G6 and SA G8 were clustered in different groups even though both the isolates belonged to same clonal complex (CC5) and origin. Also, SA G8 isolate (Germany strain) was found clustered with other Hungarian isolates instead of clustering with Germany isolates S. aureus. This polyphasic characterization provide no in-dept data/result in case of gene level difference or similar among the isolates. So, we selected these four strains for in-depth comparative genome levels study to better understand the genomic differences among the strains. This manuscript is merely extended part of our previous article. • MGE abbreviation was not defined (line 42). Reply: As per your suggestion, we mentioned the abbreviation of MGEs in line 44. • Results from pH tolerance assay were not referenced to the corresponding table. Reply: As per your suggestion, we inserted the reference (Table S1) in line 253 and corresponding table in Supplementary section named as Table S1. • There are incomplete ideas (e.g. line 272-274). Reply: These lines were omitted from the manuscript. • Ideas from lines 377-383, 439-442 were not understandable. Reply: We agreed to your suggestion and we edited the text in line 375-380, 436-438. • There is a discordance between text and figure 6A SA G6 singletons number (143 vs 220). Reply: Thank you for finding this mistake, I corrected the text in line 430. It must be 220 singletons. An all-text detailed revision should be done. Experimental design Bioinformatics and experimental findings are original and within Aims and Scope of the journal. The genome analysis of MRSA is well conducted, following high technical standard. However, some experimental data is not enough to support all the findings. Validity of the findings Most of the results and findings are well supported. However, there are some issues that must be clarified. 1. Since involved genes in acidic and alkaline pH conditions resistance are present in all four strains, an expression gene experiment must be designed and performed to validate this point. Reply: We strongly agreed with your suggestion, identifying the key genes for the acid and alkaline environments tolerance through qPCR experiment would be no easy task, also based on literatures we noticed many genes and regulatory genes are involved in pH tolerance, so we thought that we will perform differential transcriptome studies from the selected best strains in future. As you all aware about the situation during this COVID-19 pandemic, it is not possible for us to perform the qPCR experiment/ transcriptome study because the research lab is in Pecs, Hungary (under lockdown) and the first-author is in India. We deeply regret and apologize for our inability to perform this experiment. This part is the limitation of our study, and we are planning to perform a transcriptome analysis in the future. 2. It was not clear the reason to use S. aureus subsp. aureus HO 5096 0412 to compare al genomes in figure 4. Reply: The reason for choosing the S. aureus subsp. aureus HO 5096 0412 genome as a reference genome in comparative map: the highest number of core-genome was generated after using S. aureus subsp. aureus HO 5096 0412 genome as reference genome. Again, the ANIb result showed that this genome has ~98.3 to 100% identities to all the study genomes, however other reference genomes showed 97.8 to 100% identities to all the genomes. Also, S. aureus subsp. aureus HO 5096 0412 genome which is one of the closest to SA H27 and SA H32 genomes. 3. A correlation between ARGs identification and antibiotic resistance analysis is mentioned (line 322), but antibiotic resistance analyses were not done in this study. Reply: We strongly agreed, we corrected the text in line 320-322. 4. Biofilm formation was widely discussed; however, biofilm formation analyses were not present in this work. Reply: Thank you for finding these mistakes. This manuscript is extension of our previous study. We inserted the citation of our previous study published article to correlate with the present finding/ genomic study. The citation was inserted in line 513-515, 527-528, 549. 5. It was discussed that S. aureus subsp. aureus ST228 (HE579071.1) and SA G6 addition to pangenome drastic decline of the core/pan- genome ratio, however, ¿in four strain pangenome analysis this decline was observed when SA G6 was added? Reply: Yes, in four strains pangenome analysis, the same decline of core-genome was also observed after the introduction of SA G6 genome. The main reason is that such strain/genome has large singletons due to the presence of many prophages and others MGEs. 6. To validate that singletons genes could be acquired by HGT (line 644-646), a datailed bioinformatic analysis must be performed. Reply: We strongly agreed with your suggestion, to validate this event we need to perform phylogenetic analysis of certain genes that played role in HGT, however most of the tools and softwares are supported in linux or command line platform. This validation part could be another research area. We removed the term HGT in line 645. Due to lack of expertise in programming languages we have opted a different strategy. We used Islandviewer 4 to search for Genomic Island and identified the singletons genes such as aminoglycoside 3 phosphotransferase, aminoglycoside 6 nucleotidyl transferase, and streptothricin acetyl transferase (sat-4) within the prophage region (phiG6.4) of SA G6. We have cited some relevant articles that support our findings in line 644 and 645. 7. In the phylogenomic analysis, ST105, ST22 and ST5 are central to understand this result, however it is not clear its origin and relevance. Reply: In the phylogenomic analysis, the represented strains of cluster A (CC22) are belonged to ST22 and these UK origin strains are circulated in European regions and extended to other continents. The strains of Cluster C (CC5) consist of ST105 which was originated from Western Switzerland and its derivative clone with ST5 was found in New York and Japan and termed as New York/Japan clone. This clone is considered as the major epidemic clone. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Conservation genetic approaches for elasmobranchs have focused on regions of the mitochondrial genome or a handful of nuclear microsatellites. High-throughput sequencing offers a powerful alternative for examining population structure using many loci distributed across the nuclear and mitochondrial genomes. These single nucleotide polymorphisms are expected to provide finer scale and more accurate population level data; however, there have been few genomic studies applied to elasmobranch species. The desire to apply next-generation sequencing approaches is often tempered by the costs, which can be offset by pooling specimens prior to sequencing (pool-seq). In this study, we assess the utility of pool-seq by applying this method to the same individual silky sharks, Carcharhinus falciformis, previously surveyed with the mtDNA control region in the Atlantic and Indian Oceans. Pool-seq methods were able to recover the entire mitochondrial genome as well as thousands of nuclear markers. This volume of sequence data enabled the detection of population structure between regions of the Atlantic Ocean populations, undetected in the previous study (inter-Atlantic mitochondrial SNPs FST values comparison ranging from 0.029 to 0.135 and nuclear SNPs from 0.015 to 0.025). Our results reinforce the conclusion that sampling the mitochondrial control region alone may fail to detect finescale population structure, and additional sampling across the genome may increase resolution for some species. Additionally, this study shows that the costs of analyzing 4,988 loci using pool-seq methods are equivalent to the standard Sanger-sequenced markers and become less expensive when large numbers of individuals (&gt;300) are analyzed.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Many elasmobranchs around the globe have experienced devastating population declines due to overfishing in both target and non-target fisheries <ns0:ref type='bibr'>(Musick et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b27'>Clarke et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b48'>F. Ferretti et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b64'>Heupel et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b42'>Dulvy et al., 2014;</ns0:ref><ns0:ref type='bibr'>Oliver et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b45'>Dulvy &amp; Trebilco, 2018)</ns0:ref>. These species are especially vulnerable to overfishing due to life history traits such as late maturity, slow growth, low fecundity, and high juvenile mortality, which collectively result in low intrinsic rate of population increase <ns0:ref type='bibr' target='#b8'>(Baum et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b41'>Dulvy et al., 2008)</ns0:ref>.</ns0:p><ns0:p>Elasmobranch populations take decades to recover from overfishing, and only if fishing pressure is relieved for an extended period <ns0:ref type='bibr'>(Stevens et al., 2000)</ns0:ref>. Furthermore, many threatened and endangered elasmobranchs have little to no population genetic data that would assist in the resolution of management units (reviewed in <ns0:ref type='bibr' target='#b38'>Domingues et al., 2018a)</ns0:ref>.</ns0:p><ns0:p>Genetically distinct populations are isolated management units known as stocks; however, stocks can be defined on a smaller scale than genetic populations through other criteria, such as an exclusive economic zone boundry <ns0:ref type='bibr' target='#b20'>(Carvalho &amp; Hauser, 1994;</ns0:ref><ns0:ref type='bibr'>Ovenden et al., 2015)</ns0:ref>. Reduced gene flow indicates that if a population is overfished it will not be replenished by immigrants from surrounding populations. This is why managing on a genetic stock-by-stock basis is essential for successful maintenance of exploited species and is sorely needed for over-harvested elasmobranchs <ns0:ref type='bibr' target='#b33'>(Dizon et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b62'>Heist, 2004;</ns0:ref><ns0:ref type='bibr'>Tallmon et al., 2010)</ns0:ref>.</ns0:p><ns0:p>For the past two decades the standard for examining population structure in elasmobranchs has been a section of the mitochondrial genome, usually the control region (mtCR) (e.g. <ns0:ref type='bibr' target='#b46'>Duncan et al. 2006;</ns0:ref><ns0:ref type='bibr' target='#b67'>Hoelzel et al. 2006;</ns0:ref><ns0:ref type='bibr' target='#b76'>Keeney &amp; Heist 2006;</ns0:ref><ns0:ref type='bibr' target='#b21'>Castro et al. 2007;</ns0:ref><ns0:ref type='bibr'>Whitney et al. 2012;</ns0:ref><ns0:ref type='bibr'>Clarke et al. 2015</ns0:ref>; reviewed in <ns0:ref type='bibr' target='#b38'>Domingues et al. 2018a)</ns0:ref>. Though recent studies are moving PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed towards multi-marker approaches <ns0:ref type='bibr' target='#b87'>(Momigliano et al., 2017;</ns0:ref><ns0:ref type='bibr'>Pazmi&#241;o et al., 2018</ns0:ref><ns0:ref type='bibr' target='#b59'>: Green et al., 2019)</ns0:ref>, there is still a large body of literature focusing on mtCR. The mitochondrial genome has a higher rate of mutation than most of the nuclear genome <ns0:ref type='bibr' target='#b17'>(Brown et al., 1979;</ns0:ref><ns0:ref type='bibr' target='#b23'>Charlesworth &amp; Wright, 2001;</ns0:ref><ns0:ref type='bibr'>Neiman &amp; Taylor, 2009)</ns0:ref> and this rate of mutation is a key advantage in vertebrates with slowly-evolving genomes <ns0:ref type='bibr' target='#b5'>(Avise et al., 1992;</ns0:ref><ns0:ref type='bibr' target='#b84'>Martin et al., 1992)</ns0:ref>.</ns0:p><ns0:p>Elasmobranch mtDNA studies to date have been successful in elucidating population partitions and evolutionary divergences, but the maternal inheritance of mtDNA can limit conclusions about gene flow in cases of sex-biased (usually male) dispersal. Both mtDNA and nuclear markers often have concordant results in sedentary species (e.g., <ns0:ref type='bibr'>Lavery et al., 1996;</ns0:ref><ns0:ref type='bibr'>Avise, 2004;</ns0:ref><ns0:ref type='bibr'>Zink &amp; Barrowclough, 2008;</ns0:ref><ns0:ref type='bibr' target='#b32'>DiBattista et al., 2015)</ns0:ref> but, when examined alone, may miss key components of population structure, particularly in migratory fauna <ns0:ref type='bibr'>(Pardini et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b13'>Bowen et al., 2005;</ns0:ref><ns0:ref type='bibr'>Toews &amp; Brelsford, 2012)</ns0:ref>. When highly mobile elasmobranchs are examined with both mtDNA and nuclear markers (usually microsatellites), a different picture often emerges in which females are more resident and males are dispersive <ns0:ref type='bibr'>(Pardini et al., 2001;</ns0:ref><ns0:ref type='bibr'>Schultz et al., 2008;</ns0:ref><ns0:ref type='bibr'>Portnoy, et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b73'>Karl, Castro, Lopez, Charvet, &amp; Burgess, 2011;</ns0:ref><ns0:ref type='bibr' target='#b29'>Daly-Engel et al., 2012;</ns0:ref><ns0:ref type='bibr'>Portnoy et al., 2015</ns0:ref><ns0:ref type='bibr' target='#b10'>: Bernard et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b39'>Domingues et al., 2018b)</ns0:ref>.</ns0:p><ns0:p>Identifying outlier SNPs in the nuclear genome can highlight genes possibly under selection, or show functional responses to environmental changes that have important management consequences <ns0:ref type='bibr'>(Barrio et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b51'>Fischer et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b60'>Guo et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b72'>Jones et al., 2012)</ns0:ref>.</ns0:p><ns0:p>Therefore, the combination of mitochondrial and nuclear markers can yield fundamental ecological and evolutionary insights.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>High-throughput sequencing is a powerful tool for revealing fine-scale population structure that may be missed by single locus studies <ns0:ref type='bibr' target='#b3'>(Andrews et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b68'>Hohenlohe et al., 2018)</ns0:ref>. However, this method can be costly, especially when examining many individuals as is typical of population genetic or phylogeography studies, and the perceived cost may prevent some from considering a high-throughput sequencing approach. For population genetics approaches based on differences in allele frequencies among populations, equimolar pooling of samples before sequencing is an affordable and accurate strategy for large-scale genetic analysis <ns0:ref type='bibr'>(Schl&#246;tterer et al., 2014)</ns0:ref>. Several studies have successfully resolved population structure using a pooled siteassociated DNA approach known as pool-seq, including some in commercially valuable marine species (e.g. <ns0:ref type='bibr' target='#b58'>Gautier et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b86'>Mimee et al., 2015)</ns0:ref>. Pool-seq provides estimates of allele frequencies for thousands of loci distributed across the genome simultaneously, which in some cases gives greater statistical power that can actually exceed the accuracy of allele frequency estimates based on individual sequencing <ns0:ref type='bibr' target='#b53'>(Futschik &amp; Schl&#246;tterer, 2010</ns0:ref>, but also see <ns0:ref type='bibr' target='#b1'>Anderson et al. 2014)</ns0:ref>. Therefore, a comparison of results between the standard mtCR analysis and highthroughput pool-seq is informative in evaluating the relative power and cost of the two approaches for examining population structure.</ns0:p><ns0:p>The silky shark (Carcharhinus falciformis (M&#252;ller &amp; Henle, 1839)) is the second most commonly harvested shark on Earth <ns0:ref type='bibr'>(Oliver et al., 2015;</ns0:ref><ns0:ref type='bibr'>Rice &amp; Harley, 2013)</ns0:ref>. They are one of the top contributors to the shark fin trade and the most common elasmobranch bycatch species in tuna purse-seine fisheries around the world <ns0:ref type='bibr'>(Cardenosa et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b27'>Clarke et al., 2006;</ns0:ref><ns0:ref type='bibr'>Oliver et al., 2015)</ns0:ref>. This pelagic shark, formerly abundant in all tropical oceans, has declined by an estimated 85% in the last 20 years, and is now listed as vulnerable and declining by the Currently silky shark population assessments are conducted at the scale of regional fishery management organization, and conservation management measures are implemented at this scale in the absence of genetic or movement data to define population boundaries. <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref> surveyed silky sharks across these regional management regions and found the western Atlantic was strongly differentiated from the Indian Ocean, but the North Atlantic, Gulf of Mexico, and Brazil could not be differentiated and appeared to comprise a single population. In contrast, using the same mtCR marker, <ns0:ref type='bibr' target='#b35'>Domingues et al. (2017)</ns0:ref> examined five regions across the Western Atlantic and found the North Western Atlantic was distinct from the South Western Atlantic. The difference between the two studies results from additional sampling in the South West Atlantic from further south than <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref>.</ns0:p><ns0:p>In an era where wildlife management needs far exceed the financial resources to address them, many seek to find the most accessible, robust, and economical means to define management units. In this study, we provide a direct comparison of population genetic analysis methods between Sanger sequencing of the mtCR region and high-throughput sequencing of regional pools of individuals. The same individuals from <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref> were re-sequenced using pool-seq approaches. Regions re-sequenced included Gulf of Mexico, North West Atlantic, and Brazil, as well as one geographically distant location in the Red Sea (Fig <ns0:ref type='figure' target='#fig_13'>1</ns0:ref>). We focused this analysis on SNPs from the mitochondrial DNA as well as nuclear DNA. We did not analyze any microsatellite loci because they were not a part of <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref>. We then evaluate the economics of conducting pool-seq relative to conventional Sanger sequencing of these same PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed individuals. Ecological and management implications will be addressed in a subsequent companion paper.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sampling and sequencing</ns0:head><ns0:p>A total of 143 silky shark fin clips or muscle sections were sampled from commercial or artisanal fisheries across four geographic regions and are the same samples examined in <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref>. Specifically, we sampled the Gulf of Mexico (GM, n =39), the North Atlantic (NA, n = 33), Brazil (BR, n = 34), and the Red Sea (RS, n = 37). These sample sizes are slightly lower than <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref>. This reduction was due to DNA degradation over time and the need for high-quality genomic DNA for pool-seq. This is contrary to the DNA quality needed for amplifying a single marker from the mitochondrial control region. Additionally only a subset of the Red Sea samples were randomly selected to keep sample sizes relatively similar.</ns0:p><ns0:p>DNA was extracted using Qiagen DNeasy Blood &amp; Tissue kit (Qiagen, Mississauga, ON, Canada), following manufacturer protocols. Extracted DNA quality was assessed visually by gel electrophoresis and imaged using Gel Doc E-Z System (BIO RAD, Hercules, California, USA).</ns0:p><ns0:p>Only DNA aliquots with strong genomic DNA bands were further processed, while degraded or overly digested DNA was discarded. Aliquots of high-quality DNA were quantified using an AccuClear Ultra high sensitivity dsDNA quantitation kit (Biotium, Fremont CA, USA) and a SpectroMax M2 (Molecular Devices, Sunnyvale, CA, USA). Libraries were pooled with an <ns0:ref type='table'>2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p><ns0:p>No PCR was performed to ensure individual DNA contribution was kept equal within and across libraries <ns0:ref type='bibr' target='#b1'>(Anderson et al., 2014)</ns0:ref>. The rest of the library preparation followed the ezRAD library preparation protocol <ns0:ref type='bibr'>(Toonen et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b77'>Knapp et al., 2016)</ns0:ref>. This included DNA digested with DpnII restriction enzyme and adapters ligated using a Kapa hyper Prep Kit (Kapa Biosystems, Wilmington, MA, USA). Pooled libraries were sequenced using Illumina MiSeq (v3 2x300bp PE) at the Hawai'i Institute of Marine Biology EPSCoR Core sequencing facility.</ns0:p></ns0:div> <ns0:div><ns0:head>Genetic analyses</ns0:head><ns0:p>MultiQC was used to assess sequence quality scores, sequence length distributions, duplication levels, and overrepresented sequences <ns0:ref type='bibr' target='#b47'>(Ewels et al., 2016)</ns0:ref>. To analyze the mitochondrial genome, a previously published mitochondrial genome from Carcharhinus falciformis was used as a reference (GeneBank accession number KF801102). Raw paired-end reads were trimmed with TRIMMOMATIC, mapped to the mitochondrial genome reference BWA (mem algorithm), and variants called using the dDocent bioinformatics pipeline, modified for pool-seq (Puritz et al.</ns0:p></ns0:div> <ns0:div><ns0:head>2014, see below for details</ns0:head><ns0:p>). Called SNPs were then analyzed with AssessPool (github.com/ToBoDev/assessPool, see below for details).</ns0:p><ns0:p>The bioinformatics pipeline included dDocent followed by AssessPool. Given that no reference genome was available, a reference was constructed using the dDocent de novo assembly and optimized utilizing the reference optimization steps provided on the dDocent assembly tutorial (http://ddocent.com/assembly/). Before assembly reads were trimmed using default settings and then an overlap (OL) assembly was performed, followed by clustering with CD-HIT with a -c parameter of 90% similarity. Manuscript to be reviewed tested during optimization but did not improve mapping. Within-pool (K1) and between-pool (K2) minimum locus depth values selected for the de novo assembly did impact the results. dDocent provides graphical outputs to help select these values; however, testing a few different values of each is recommended to fully explore the potential of the data by balancing number of contigs by coverage depth (see ddocent.com/UserGuide for details). Selected values for K1 and K2 were 3 and 3 respectively. Once assembled, sequences were mapped, SNPs were called within the dDocent pipeline using FreeBayes, modified for SNP calling in pools <ns0:ref type='bibr'>(Garrison and</ns0:ref> Marth 2012, https://github.com/ekg/freebayes). Any contigs that aligned to the mitochondrial genome were removed from this nuclear dataset. The contigs that aligned specifically to the mitochondrial control region were saved for SNP validation to directly compare the results from this pool-seq approach to those previously reported by <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref>. SNP calling with FreeBayes was optimized for pooled samples using the 'pooled-continuous' option, and minor allele frequency was decreased to 0.05 to capture alleles with frequency greater than 5% in the population (See Supplementary Material for code). The dDocent pipeline outputs SNPs in two variant call format files (.vcf), one being all raw SNPs (TotalRawSNPs.vcf) and another with filtered SNPs (Final.recode.vcf) however dDocent does not optimize filtering for pool-seq data. Therefore, the raw SNPs were processed with the pool-seq specific program AssessPool which uses VCFtools and vcflib to filter SNPs <ns0:ref type='bibr' target='#b30'>(Danecek et al., 2011)</ns0:ref>. SNPs were processed with the following filters: minimum pool number of 2, minimum quality score of 20, minimum depth threshold of 30, maximum amount of missing data of 3, maximum allele length of 10, quality score to depth ratio of 0.25 as well as mean depth per site vs. quality score, and finally a maximum mean depth threshold of 1000 (Table <ns0:ref type='table'>S1</ns0:ref>). AssessPool then sends filtered Manuscript to be reviewed SNPs to either PoPoolation2 <ns0:ref type='bibr' target='#b79'>(Kofler et al., 2011)</ns0:ref> or poolfstat <ns0:ref type='bibr' target='#b65'>(Hivert et al., 2018)</ns0:ref>. PoPoolation2 calculates mean pairwise F ST values and significance in the form of p-values obtained using Fisher's exact test and combined using Fisher's method (as described in <ns0:ref type='bibr'>Ryman et al. 2006)</ns0:ref>.</ns0:p><ns0:p>Poolfstat <ns0:ref type='bibr' target='#b65'>(Hivert et al. 2018</ns0:ref>) takes a different approach, calculating F ST values based on an analysis-of-variance framework (sensu Wier &amp; Cockerham 1984) to eliminate biases associated with varying pool sizes. AssessPool then organizes, summarizes, and creates visualizations of the data using RStudio (RStudio Team 2020).</ns0:p><ns0:p>As a quality control test, sequences from <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref> were downloaded from GenBank (accession numbers KM267565-KM267626), and SNPs from these data were compared directly to SNPs called within the control region of the mitochondrial pool-seq data generated here.</ns0:p><ns0:p>Concordance of this validation set of SNPs was determined by Mantel test in R <ns0:ref type='bibr' target='#b83'>(Legendre &amp; Legendre, 1998)</ns0:ref> comparing the matrices of pairwise F ST values among populations.</ns0:p></ns0:div> <ns0:div><ns0:head>Cost Analysis</ns0:head><ns0:p>The cost of pool-seq approach compared to Sanger sequencing of individual loci was calculated based on library preparation and sequencing cost at our facility. We did not include labor but calculated the total cost to generate sequence data from each sample included here from such expenses as the extraction, laboratory consumables, PCR amplification, library preparation, reaction clean-ups, quantification, quality control testing, and sequencing costs. These costs were translated into functions in RStudio <ns0:ref type='bibr'>(RStudio Team, 2020)</ns0:ref> where Sanger sequencing is a fixed rate per individual and pool-seq costs are fixed per flow cell on our MiSeq, but individual cost varies based on number of individuals and number of pooled regions per sequencing run. These functions were then plotted together for comparison. </ns0:p></ns0:div> <ns0:div><ns0:head>Mitochondrial Genome</ns0:head><ns0:p>Analysis of the complete mitochondrial genome (17,774 bp) revealed 804 variable sites: 681 biallelic and 17 multiallelic SNPs. Because coverage in this dataset was fairly low on average, most of these SNPs did not meet the filter threshold. After further filtering for the highest quality markers, 30 SNPs were selected to calculate allele frequencies. Pairwise F ST values were all significant (Fig 2, Table <ns0:ref type='table'>S2</ns0:ref>). The Red Sea had much higher F ST values (ranging from 0.367 to 0.745) than any inter-Atlantic comparison (ranging from 0.029 to 0.135). However, all comparisons within the Atlantic still showed significant F ST values, the highest being between <ns0:ref type='table'>S2</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Nuclear loci</ns0:head><ns0:p>Our nuclear data showed 4,988 variants of which 3,422 were biallelic SNPs and 151 were multialleleic SNPs. A total of 346 SNPs remained after the same filtering process for the highest quality SNPs was applied as for the mitochondrial genome. Nuclear markers showed lower F ST values between locations than the mitochondrial data, yet all P-values were still significant (Fig <ns0:ref type='table'>S2</ns0:ref>). The Red Sea showed consistently higher F ST values in comparison to inter-Atlantic comparisons except for the North Atlantic to Gulf of Mexico comparison, which showed the second highest mean <ns0:ref type='table'>S2</ns0:ref>). The highest value (F ST = 0.035) was observed between Gulf of Mexico and the Red Sea, whereas the lowest (F ST = 0.014) was between the North Atlantic and Brazil, which had the highest F ST value within the Atlantic for the mitochondrial data.</ns0:p></ns0:div> <ns0:div><ns0:head>2, Table</ns0:head><ns0:formula xml:id='formula_0'>F ST value (Fig 2, Table</ns0:formula></ns0:div> <ns0:div><ns0:head>SNP validation</ns0:head><ns0:p>SNPs called in the mitochondrial control region using the pool-seq protocol were compared with those reported in <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref>. Of the 34 SNPs in their study 14 of them had a minor allele count (MAC) of less than or equal to 3 and several were singletons. These SNPs are removed from the pool-seq data due to MAC SNP filter of &gt;3 to remove sequencing errors that might be scored as rare alleles during high-throughput sequencing. Therefore, singletons or any rare allele represented fewer than 3 times in a population will inherently be removed from poolseq data sets. Fortunately those rare alleles do not tend to overly impact Fst values and should Manuscript to be reviewed not bias interpretations of population structure <ns0:ref type='bibr' target='#b12'>(Bird et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b12'>Toonen et al. 2011)</ns0:ref>. Three SNPs were found in the Clarke study with a MAC of &gt;3 that were not present in the pool-seq data; however, the remining 17 SNPs were all present in our data, plus one that was not found in the <ns0:ref type='bibr'>Clarke study (Fig S1)</ns0:ref>. Despite the loss of these rare alleles from the SNP validation set, pairwise F ST values estimated by both methods remained highly correlated (Mantel test, r 2 = 0.96, p &lt; 0.05), and comparisons between the Red Sea and all three Atlantic populations showed the same relative magnitude between both methods.</ns0:p></ns0:div> <ns0:div><ns0:head>Cost Analysis</ns0:head><ns0:p>The findings for cost analysis indicate that pool-seq reaches a threshold at approximately 300 individuals, after which this approach offers cheaper results than individual Sanger sequences.</ns0:p><ns0:p>Furthermore, the cost is only twice as expensive at just over 100 individuals (Fig <ns0:ref type='figure' target='#fig_16'>3a</ns0:ref>). The poolseq approach provides a far higher ratio of information for the cost, yielding greater population resolution. This cost assessment does not include analytical time, labor, or effort associated with pool-seq analyses such as access to computer resources and expertise with bioinformatic pipelines. However these costs are likely to decrease in the near future as bioinformatic pipelines are improved and become more widely available, for example as applications deployed via cloud based platforms such as Galaxy (https://usegalaxy.org/) or CyVerse (https://cyverse.org/). It is also important to note that the choice of pool-seq methodology has many caveats, which are discussed in greater detail in the 'considerations on pool-seq' section of the discussion below.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Elasmobranchs are being harvested at unsustainable levels in several commercial fishing industries around the world. A fundamental step in successful management of any species is Manuscript to be reviewed resolving population boundaries so they can be managed on a genetic stock by stock basis. As genetic sequencing technologies advance, there is greater opportunity to detect even small-scale genetic differences between populations. When these differences amount to statically significant allele frequencies at the population level, this indicates limited exchange among distinct stocks.</ns0:p><ns0:p>Here, we validate the utility of pool-seq using the same individuals as a previous study <ns0:ref type='bibr'>(Clarke et al. 2015)</ns0:ref> and show that pool-seq recovers additional population structure relative to Sanger sequencing of the mtDNA control region. Pool-seq was able to detect isolated populations between the Gulf of Mexico, Western Atlantic, and along the Brazilian coast, where <ns0:ref type='bibr'>Clarke et al. (2015)</ns0:ref> found no population structure. As expected, the Red Sea population was highly isolated from Atlantic conspecifics using both approaches.</ns0:p><ns0:p>One advantage of this pool-seq approach is that we recover SNPs throughout the entire mitochondrial genome along with thousands of additional nuclear loci that together provide greater statistical power to detect finer scale population structure <ns0:ref type='bibr'>(Ryman &amp; Palm 2006;</ns0:ref><ns0:ref type='bibr' target='#b82'>Larsson et al. 2009;</ns0:ref><ns0:ref type='bibr' target='#b81'>Kurland et al. 2019)</ns0:ref>. The pool-seq approach yielded significant genetic structure among inter-Atlantic regions in both mtDNA and nuclear loci, whereas Sanger sequencing of the mtCR lacked power to resolve significant differences among the same populations. The congruence between the mitochondrial genome and nuclear loci reinforces the conclusion of population structure among all regions sampled in this study.</ns0:p><ns0:p>In this case, pool-seq lived up to the promise of increased power to detect fine-scale structure, but does it live up to the promise <ns0:ref type='bibr' target='#b49'>(Ferretti et al., 2013;</ns0:ref><ns0:ref type='bibr'>Schl&#246;tterer et al., 2014)</ns0:ref> Therefore, analyzing more than 12 pools would require additional sequencing runs and result in a step increase in the cost per individual/pool, although this would differ among other Illumina machines (such as the HiSeq, NextSeq or NovaSeq) or other high-throughput sequencing platforms (such as the PacBio Sequel II). Larger numbers of pools could be run on some of these machines, but with differing individual read lengths and sequencing depths, which also bring other trade-offs. Likewise, samples can also be run with individual barcodes, therefore gaining the individual information lost by pooling specimens, but with increased initial setup and sequencing costs. There are so many options by which to apply these methods that we cannot possibly consider them all here, and the availability, cost, and trade-offs associated with each should be ideally considered by individuals when designing high-throughput sequencing projects. In our case, we considered only the options currently available to us through our campus sequencing core, and all these pool-seq price comparisons are to a single Sanger-PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed sequenced marker. Thus, when considering the information acquired from pool-seq compared to the cost from traditional single mitochondrial marker the price per individual advantage is massively amplified.</ns0:p></ns0:div> <ns0:div><ns0:head>Considerations with pool-seq</ns0:head><ns0:p>As with any sequencing technique, there are still several factors to consider before deciding if pool-seq is appropriate for a particular study. Multiple reviews have been published on highthroughput and pool-seq approaches demonstrating pros, cons, and considerations with these methods, which are beyond the scope of this study. Interested readers should consult Perez-Enciso &amp; Ferretti (2010), <ns0:ref type='bibr' target='#b53'>Futschik &amp; Schl&#246;tterer (2010)</ns0:ref>, <ns0:ref type='bibr' target='#b78'>Kofler et al. (2012</ns0:ref><ns0:ref type='bibr' target='#b49'>), Ferretti et al. (2013</ns0:ref><ns0:ref type='bibr'>), Schl&#246;tterer et al., 2014</ns0:ref><ns0:ref type='bibr' target='#b2'>, Andrews &amp; Luikart (2014)</ns0:ref>, <ns0:ref type='bibr' target='#b3'>Andrews et al. (2016), and</ns0:ref><ns0:ref type='bibr' target='#b81'>Kurland et al. (2019)</ns0:ref>.</ns0:p><ns0:p>Pooling assumes individuals are from the interbreeding individuals within a single population of the same species. Therefore, care needs to be taken to avoid cryptic species, combining multiple populations (Wahlund effect), or other unintentional bias when selecting individuals to pool <ns0:ref type='bibr' target='#b55'>(Garnier-G&#233;r&#233; &amp; Chikhi 2013)</ns0:ref>. For wide ranging pelagic species such as the blue shark or oceanic whitetip it seems reasonable to pool individuals from a larger area than it would be for small benthic species such as horn sharks, wobbegongs, or most rays. Population structure may be obscured if the geographic range per pool is too large or if there is complex population structure (sensu <ns0:ref type='bibr' target='#b13'>Bowen et al. 2005)</ns0:ref>, because individuals from multiple sub-populations will be mixed into a single pool from which allele frequencies are calculated. Certainly pool-seq is not appropriate in all cases. It is a cost-saving approach for analyses based on allele frequencies Manuscript to be reviewed only, because individual information is lost by pooling, including haplotypes/genotypes and linkage disequilibrium information. Also, pooling makes it difficult to distinguish between low frequency alleles in the population and sequencing error. Therefore, careful filtering must be applied to ensure only valid SNPs are analyzed instead of analyzing sequencing noise <ns0:ref type='bibr' target='#b0'>(Anand et al., 2016;</ns0:ref><ns0:ref type='bibr'>Schl&#246;tterer et al., 2014)</ns0:ref>. Finally, the estimation of F ST from pooled data remains a subject of some debate, and new approaches and bias corrections are being actively developed <ns0:ref type='bibr' target='#b79'>(Kofler et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b65'>Hivert et al. 2018)</ns0:ref>. To account for this uncertainty, we include analyses based on both the original PoPoolation2 <ns0:ref type='bibr' target='#b79'>(Kofler et al., 2011)</ns0:ref> package and the newer poolfstat <ns0:ref type='bibr' target='#b65'>(Hivert et al., 2018)</ns0:ref> that explicitly considers potential biases associated with varying pool sizes.</ns0:p><ns0:p>The two approaches yield slightly different F ST values (see Table <ns0:ref type='table'>S2</ns0:ref>), however a comparison of the two F ST matrices shows strong correlation (Mantel r=0.991 for mitochondrial and r=0.978 for nuclear data, p &lt; 0.05). Therefore, only those F ST values calculated by PoPoolation2 are reported in the main text for ease of presentation.</ns0:p><ns0:p>Though pool-seq has been shown to be an affordable and reliable tool for population genomics <ns0:ref type='bibr' target='#b53'>(Futschik &amp; Schl&#246;tterer, 2010;</ns0:ref><ns0:ref type='bibr' target='#b58'>Gautier et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b51'>Rellstab et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b80'>Konczal et al. 2014;</ns0:ref><ns0:ref type='bibr'>Schl&#246;tterer et al. 2014;</ns0:ref><ns0:ref type='bibr' target='#b81'>Kurland et al. 2019)</ns0:ref> Manuscript to be reviewed developing countries, and having a cost-effective alternative to single marker studies will continue to be invaluable to many.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>The finding of population structure on the scale of North Atlantic/Gulf of Mexico/Brazil is nearly unprecedented for a pelagic shark. Population structure in globally distributed sharks is typically detected on a scale of ocean basins (Atlantic versus Indo-Pacific, <ns0:ref type='bibr' target='#b21'>Castro et al. 2007;</ns0:ref><ns0:ref type='bibr'>Graves &amp; McDowell, 2015)</ns0:ref> and a few pelagic fishes have no population structure on a global scale (e.g. Basking shark, Cetorhinus maximus, <ns0:ref type='bibr' target='#b67'>Hoelzel et al. 2006;</ns0:ref><ns0:ref type='bibr'>Blue shark Prionace glauca, Ver&#237;ssimo et al. 2017;</ns0:ref><ns0:ref type='bibr'>Wahoo, Acanthocybium solandri , Theisen et al. 2008)</ns0:ref>. The resolution of isolated populations on the scale of North Atlantic Ocean is more typical of coastal species than pelagic species. The silky shark seems to be a pelagic species with a somewhat coastal population structure. This has strong implications for international management because smaller stocks imply smaller populations which are more readily depleted. At a minimum, these data require rethinking a single population management approach for the Atlantic, and this pattern needs to be investigated for this species across the Indo-Pacific as well.</ns0:p><ns0:p>Overall this study demonstrates pool-seq is a powerful and cost-effective tool for analyzing large portions of the genome which the methods traditionally used for elasmobranchs could not supply. Sharks and rays are an imperiled group of species that could benefit from advanced genomic studies to outline appropriate management units. Finally, although the technology is becoming cheaper and easier to apply, it is a common pitfall to assume everyone in the field can afford, or must use, these approaches to produce defensible science. <ns0:ref type='bibr' target='#b15'>Bowen et al. (2014)</ns0:ref> advocate judicious rather than wholesale application of genomic approaches as the most robust Manuscript to be reviewed course of study, particularly when considering the global inequities in available research budgets.</ns0:p><ns0:p>Sanger sequencing is still more cost effective for small numbers of individuals, but as the number of individuals included in a study rise, the cost per individual reaches the point where high throughput sequencing studies can be cheaper than sequencing a single mitochondrial marker from each individual. We provide an example of just such a case here, and highlight the potential advantage of cost savings together with increased power for resolution of fine scale population structure. Though there is still additional cost of using cluster computer servers and bioinformatics programs, these cost are dropping as technology advances. When study organism and sampling strategies are assessed and implemented into the study design, pool-seq has great promise for augmenting the scientific foundations for management of marine recourses. Cost comparisons between sequencing projects using a single Sanger marker to projects using Pool-seq with varying numbers of pools. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020) Manuscript to be reviewed International Union for the Conservation of Nature (Rice &amp; Harley, 2013; IUCN, 2017).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>equal amount of DNA (ng/&#181;l) contributed per individual to minimize individual contribution bias, totaling 2000 ng of DNA per library. Number of individuals per pool are displayed in Fig 1.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>For mapping using BWA (mem algorithm) all match, mismatch, and gap open penalty score parameters were also default settings. Different parameters were PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)Manuscript to be reviewedResultsA total of 30.8 million reads were generated for the four geographic regions, which averaged 7.7 &#177; 3.0 million reads per pooled library. Results from the MutliQC assessment showed fairly homogenous output between libraries in regard to sequence quality scores, GC and per base sequence content, sequence length distributions, duplication levels, overrepresented sequences, and adapter content. Once assembled, aligned, and mapped, 5,792 SNPs were resolved across the mitochondrial and nuclear genomes combined. There were 4,103 biallelic SNPs, 168 were multialleleic SNPs and 48 were insertions and deletions (INDELs). INDELs and multiallelic SNPs remain a challenge for quantification software, so we restricted our analysis to biallelic loci(Fracassetti et al. 2015). AssessPool creates visualizations of F ST values and allows for visual outlier inspection. No visual outliers were present and given these SNPs are distributed haphazardly across the genome, they are assumed to be putatively neutral.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020) Manuscript to be reviewed the North Atlantic and Brazil, and the lowest between Brazil and Gulf of Mexico (Fig 2, Table</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>of being cost-PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020) Manuscript to be reviewed effective? Individual extraction costs remain fixed across both approaches and Sanger sequencing generally has a flat rate per individual, including PCR primers and reagents, and sequencing per individual per locus. In contrast, pool-seq has a flat sequencing cost determined by the number of reads generated from the high-throughput sequencing platform, plus a small additional cost per pool for the exact quantification of DNA for equimolar pooling and the library preparation for high-throughput sequencing. Comparing costs at our institution between a single Sanger sequencing marker and pool-seq on the Illumina MiSeq platform indicates poolseq becomes less expensive when sample size of the study rises above 300 individuals. Although the cost per pool is essentially fixed, when higher numbers of individuals are included per pool, the price per individual analyzed is further reduced (Fig 3b). Our comparison here is limited to 12 pools due to the maximum number of reads per lane produced on the MiSeq platform.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head /><ns0:label /><ns0:figDesc>, projects with larger budgets could allocate funds for any of a variety of other genomic sequencing techniques such as individual RADseq libraries (Hohenlohe et al. 2010), GBS (Narum et al. 2013), SNP arrays (Qi et al. 2017), bait capture (Feutry et al. 2020), or low coverage genomewide sequencing (Therkildsen &amp; Palumbi 2017).These approaches allow for individual genotyping to examine questions that require individuallevel information and could provide a deeper assessment of populations. However it is also important to consider not all labs can afford to generate genomic level data, especially in PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51011:1:0:NEW 5 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Figure 2 F</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head>( A )</ns0:head><ns0:label>A</ns0:label><ns0:figDesc>Sequencing costs comparing number of individuals to total cost between Sanger at our facility and three Pool-seq projects at our facility containing 4, 8, and 12 pools respectively, where pool sizes change with number of individuals. (B) Sequencing cost per individual with fixed pools across different number of Pools.</ns0:figDesc></ns0:figure> </ns0:body> "

"Derek Kraft August 24th, 2020 Hawaii Institute of Marine Biology, 46-007 Lilipuna Road, Kaneohe, Hawaii 96744 Email: [email protected] Dear Editor, Thank you for all the comments and edits by both reviewers. We have updated the manuscript and replied to comments line by line in the pages below. Our response to comments are written in red. Specifically we have cleared up the passages about maternally inherited mitochondrial genes relative to using both mitochondrial and nuclear genes. Additionally, we made sure the emphasize the importance of computing and bioinformatics costs associated with any high throughput sequencing analysis. We hope the manuscript is now ready for publication in PeerJ. Sincerely, Derek W. Kraft Ph.D. Candidate Hawai’i Institute of Marine Biology On behalf of all authors. Editor comments (Antonio Amorim) MINOR REVISIONS Besides the answers to Reviewers’ comments, I further ask the Authors to comment on the limitations of mtDNA for the purpose of detecting population structure due to uniparental mode of transmission. Reviewer 1 (Cesar Amaral) Basic reporting The manuscript fully meets PeerJ standards. The english is professional and unambiguous, the figures are well prepared and informative. Raw and supplementary data are included and the previos MER review and the improved version (with track changes) were a nice add. Experimental design The research is within the Aims and Scope of the journal. The questions is well defined and relevant. The methods are described in detail and all info is included such as the raw data and the supplementarymaterial. Validity of the findings Please check the 'General comments for the authors' field. Comments for the Author First of all, congrats for the authors for the manuscript. It is clearly written in professional, unambiguous language. The Figures are informative and well described. I’ve included my considerations/suggestions within the attached PDF file. In general, this is a really nice and already revised, and improved manuscript. It definitely deserves to be published since it touches a sensible point regarding the recent high-throughput molecular methods, i.e., its cost effectiveness. However, the choice for the pool-seq is not only related with the per sample cost but to several parameters and I suggest to stress this out along the Discussion and also within the manuscript’s Conclusions. However, I finished the manuscript without a clear idea on how much cost a unique sample in both compared techniques and I believe, regarding the scope of the manuscript, that it should be a nice and important result. Ok, it will vary a lot depending the chemistry, platform, laboratory, etc, etc… but I believe we should finish reading this manuscript able to figure out the magnitude of costs per sample we are talking about. The reviewer makes a good point, cost does vary a lot depending on the platform, laboratory, local facilities, etc. The cost also varies drastically depending on the study design and how many samples are in use. If we ran one sample with sanger sequencing the estimated cost is around $11. But if we ran one sample in a flow cell of the HiSeq ($2800), NextSeq ($3300), or MiSeq ($1900) at 2x150bp, that same sample would be thousands of dollars. As you add samples the price per sample on one of these high throughput platforms drops, but exactly how much depends on the number of samples, sequencing platform, and read length, which quickly becomes complicated. Figure 3B shows an example cost per individual depending on how many pools are assessed. I hope this highlights the magnitude of costs per sample the reviewer is looking for. Together with the points presented within the PDF, please check the Competing Interest Statement since there is no CIS, just a sentence saying that one of the authors is a PeerJ Editor. A formal CI Statement should be included prior the acceptance following the PeerJ guidelines for submission. The raw data as well as additional supplementary material are available and are a great source of info. Thanks for providing them. Finally, I commend the authors for their work and manuscript. Imho this manuscript is good to go. Thank you Dr. Amaral! Annotated manuscript The reviewer has also provided an annotated manuscript as part of their review: Download Annotated Manuscript Edits the manuscript have been made based on reviews in annotated manuscript. A few replies to comments within the annotated manuscript are provided below Line 291 (now line 323): Reviewer brings up an interesting topic, the relationship between stocks and genetically distinct populations, but this is beyond the scope of our paper. There is not a standard threshold for delimiting a stock for management. These thresholds are going to differ depending on data type, data set, and organism. Line 330 (now line 368): We reworded and added a reference as requested. The logic behind is explained directly below in lines 332-337. Line 347 (now line 387): We agree and Poolfstat data are presented in Table S2. Line 359-364 (now 406): Management implications for Silky sharks will be explored in a sister paper currently being prepared for publication. Reviewer 2 (Dareen Almojil) Basic reporting Kraft et al. present a manuscript entitled “Genomics versus mtDNA for resolving stock structure in the silky shark (Carcharhinus falciformis)”, where they tested the use of pool-seq as an alternative, cost effective and more sensitive tool for the delination of the C. falciformis stock structure. They examined the population structure from four different geographical sites of the Silky Shark C. falciformis. The advantage of this study is that they used the same individuals examined by Clarke et al. 2015, who used sanger sequencing of mtCR of these populations, and therefore were able to compare their findings and limit any introduced variation. Findings showed that the pool-seq revealed similar Fst values to Clarke et al. 2015, but also revealed finer structure which was not picked up by sanger sequencing on mtCR. In my opinion, this manuscript fills an important gap in the field of conservation genetics of elasmobranch, which has been hindered and restricted by the use of few mtDNA and microsatellite markers only. The huge genome size of many elasmobranch species and lack of reference genomes in many cases has also contributed to the limited advancement in this field. I believe this work will contribute towards filling this gap. However, I do have few concerns regarding few points in the manuscript, I listed these concerns based on scale and mentioned them in two sections; major and minor comments as listed section 1.3. 1) Structure and Criteria: 1.1: Basic Reporting: The manuscript is written in clear English and follows a logical flow. Authors introduced the subject well and transition points were well in place with sufficient referencing to the needed background. Experimental design 1.2: Experimental design: The manuscript has clearly stated the research question, the gap intended to fill which fits within the scope of PeerJ. Methods are well explained, reproducible but need to provided more information to evaluate the findings (which I mention in the major and minor comments). Validity of the findings 1.3: Validity of the findings: The data are made available in repository. I was happy to see that the data were analyzed and validated using two different systems in measuring Fst, which seems to be a center of debate in pool-seq. These two methods were the poolfstat and popoolation. The conclusions are clearly stated and connected to the main question investigated. In general, the study is well presented. However, I do think the manuscript still posses some parts that needs clarification and perhaps modifications. In the general comments for the authors section, I will present the major comments followed by another section that is more specific and minor. Comments for the Author - Major comments: 1) Authors have noted in their manuscript that in order to reduce cost, it is important to have a large number of samples in the pool, I think its important to also mention to the readers what challenges (e.g. sequencing errors) come with increasing pool size, how it effects the accuracy of allele frequencies and may be list some reference that mentions solutions to handle this challenge. May be add a few sentences in the discussion to highlighting this point and to handle it. There are a multitude of papers which validate the use of Pool-seq to infer population differentiation and diversity (Dorant et al., 2019; Ferretti et al., 2013; Gautier et al., 2013; Hivert et al., 2018; Kofler et al., 2016; Schlötterer et al., 2014) even in species lacking any close reference genome (Kurland et al., 2019; Rellstab et al., 2013). Larger pool sizes together with high mapping and coverage cut-offs tend to result in more robust estimations of population genomic differentiation (Graham et al. 2020). In particular, the work of Schlötterer et al. (2014) found that allele frequencies from Pool-seq were highly reliable and comparable to individual sequencing, and Rellstab et al. (2013) similarly reported R2>0.9 between individual and pool-seq data, irrespective of whether paired-ends were mapped onto a de novo assembly or a closely related genome. We have intentionally explored a range of approaches and used multiple strategies to ensure that our data are robust to the challenges of pool-seq. 2) Identification of rare variants: Rare variants are very useful in identifying fine-scale structure, and I think it would add more strength to your argument of using pool-seq with elasmobranchs, given that population structure in most elasmobranchs is determined at a fine scale. In your study you have chosen to set your MAF to 5% (Methods, in line-189), which has very likely removed informative rare variants and possibly some private variants that could be very useful in identifying fine scale population structure. I understand the risk here is that these rare variants could be confounded with sequencing errors specially in pools with large sample size, generating many false positives. But I have two points that I would like to suggest in here: a. First; would you consider changing your MAF to 1% instead of 5%, since you pools are composed of a mean of 36 individuals (72 autosomes), you optimum lower detection limit for variant alleles in your pools will be: 1/72 (AF= ~ 0.01). b. Second; if you decide to change your MAF to 1%, it would be useful to verify the accuracy of MAFs in your pool-seq by using CRISP [Comprehensive Read analysis for Identification of Single Nucleotide Polymorphisms (SNPs) from Pooled sequencing] to remove spurious variants due to sequencing errors yet still incorporate real rare variant alleles (As was presented in Anand et al. 2016, which you also reference in your manuscript). In this paper, they also presented a filtering guideline using Kolmogorov-Smirnov (KS) test, to help validate rare variants from large pools. Have you considered using CRISP to generate quality score for each variant, then use that score to apply a quality based filtering using the Kolmogorov-Smirnov (KS) test. Paper: Anand, S., Mangano, E., Barizzone, N., Bordoni, R., Sorosina, M., Clarelli, F., ... & De Bellis, G. (2016). Next generation sequencing of pooled samples: guideline for variants’ filtering. Scientific reports, 6, 33735. While we agree that geographically restricted variants are highly informative and helpful when identifying fine scale structure, measures of genetic differentiation based on Fst are relatively insensitive to low frequency alleles (Bird et al. 2011). This current work focuses on comparing single marker mtDNA to population genomic scale data and we explored a range of MAF cutoffs to ensure that the results were robust to the inclusion or exclusion of rare variants here, but settled on MAF of 0.05 based on Linck & Battey (2019) who explored the impacts of MAF thresholds on inferences of population structure from genomic datasets and made best practice recommendations for the field. We did not explore CRISP but appreciate the recommendation for our next paper that will expand upon this current work to look at fine scale structure across the species range. We are looking forward to testing out this approach for that study, but feel it is beyond the scope of this current analysis focused on comparing population genomic scale data to previous results based on mtDNA. 3) Estimates of genetic differentiation Fst: The manuscript main objective is to validate the use of pool-seq by comparing it with mtCR of a published study (Clarke et al. 2015), yet in the main Figures of the manuscript there is not a single Figure that clearly shows and highlight the results of this comparison. The results are distributed between Figure 2 and table S2. I think its important to combine these two into Figure 2 so the reader has an immediate access to this comparison which is the main core of the study. We agree with the reviewer and have updated Figure 2 to also include Clarke et al. 2015 values and significance values to provide a clearer comparison for the reader. - Minor and more specific comments: • Abstract: Line-38: In this line where you mention “thousands” of nuclear markers, I suggest to replace “thousands” by the exact number of nuclear markers that you have actually used after filtration. Agreed and updated. • Introduction: Line-49: Many elasmobranchs through out the ocean; the reference of the ocean here is quite vague and does not add value, I suggest you either drop the ocean or be more specific, for example; Many elasmobranchs through out the five ocean basins… Sentence revised Line-72: the reference Domingues et al. 2017a: I believe the “a” is left by mistake as I only see one Domingues et al. 2017 in the reference list. This was an oversight and is now corrected Line-106: I understand that within the scope of this paper you are focused on evaluating pool-seq functionality compared to mtCR, as these were the data provided by Clarke et al. 2015 and you are using the same individuals. But as you mentioned earlier in your introduction, the combination of mtDNA and microsatellites for the assessment of population structure in migratory species is essential. Could you add a sentence here acknowledging that; in this study you are only focused on mtDNA because it was the tool tested by Clarke et al. 2015. Also, it could be useful to add a sentence mentioning that one of the additional advantages of using pool-seq is the fact that through one tool you would be able to analysis both mtCR and nuclear markers, SNPs in this case, which are also easier to score and analyze than microsatellite (e.g more prone to genotyping errors effecting the analysis through; null allele, slippage, or allele drop-out). I think this could be another reason to justify and support your call to use pool-seq as an alternative tool. Agreed this will strengthen the paper. We have revised lines 133-136 for the addition of this information as suggested. Line-123: Again, Domingues et al. 2017b, there is only one Domingues et al. 2017 in the reference list!! Now corrected, thank you for pointing this out Line-124: At the end of this paragraph, could you provide a sentence explaining why you think Domingues et al. 2017 showed different results than Clarke et al. 2015 between the north and south Western Atlantic. (i.e. possibly due to sampling higher number of samples and the south western Atlantic was represented by a further south samples). Agreed this information is now provided. See line 125-127 for update. • Methods: Line-152: the sentence “Number of individuals per samples are displayed in Fig 1”, what do you mean by “per samples”? Sample pool? Also the number of samples obtained from Clarke et al. 2015 is the same as the listed samples in the map, however you have dropped some samples that showed degradation or were overly digested from the pool-seq. Could you add a sentence to clarify the net number of the used samples per location/pool after dropping the degraded samples. Since pool-seq is based on estimates of the allele frequencies of the pooled samples, and you do not obtain individual genotyping data that are needed to run the basic assessment of neutrality (HWE and LD), I would suggest to generate a figure showing the overall distribution of allele frequency from each pool and evaluate their distribution trends compare to each other. For your SNP outlier test, I assume it was a PCA assessment? If what you have performed is a PCA outlier test, I think having a figure in the supplementary on the distribution of allele frequency from each pool is useful and will give the reader more information to evaluate the state at each pool. I believe all your selected SNPs are bi-allelic so the expected HWE distribution for your SNP markers would be a binomial distribution, would be interesting to see how they deviate from that and if this deviation is the product of structure or genotyping error (compare the distribution between structured groups compared to overall). We agree this would be interesting but feel that it is more appropriate for the companion paper currently in preparation and beyond the scope of the current manuscript that focuses on the direct comparison of these methods. To address this, we have clarified the text to ‘Number of individuals per pool are displayed in fig 1.’. The explanation for samples dropped was added to line 149-153. Fst values were plotted, visually inspected, and nothing resembles an outlier other than one possible comparison between the Red Sea and North Atlantic (Fig. 1A below), but removing that point does not change the Fst value. The nuclear data has 3 potential outliers (Fig. 1B below) but the most extreme values still fall below 0.2 and again do not change the magnitude of Fst or our interpretations of these results. Thus, we again feel that this is beyond the scope of this manuscript and would distract from the main focus of the paper on the comparison between approaches. A. B. Rebuttal Letter Figure 1. Box plots showing spread of Fst values per marker. A. shows mitochondrial SNP Fst values. B. shows nuclear SNP Fst values. The abbreviations are not the same as manuscript figures, here: RSO1= Red Sea (RS), GOM1= Gulf of Mexico (GM), BRA1 = Brazil (BRA), WNA1= North Atlantic (NA). • Results: Line-236: 30 SNPs is quite a low number, another reason why changing MAF to 1% could add more information to the analysis. We agree the number of SNPs is relatively low, but adding more SNPs does not necessarily make for a more robust test. For the comparison here, we wanted a conservative analysis to test for consistency among approaches in the inferred population structure, but we have tried both ways and the qualitative results and interpretation are unchanged. Thus, we follow the example of Graham et al. (2020) who found that using more stringent filters, even at the cost of having far fewer SNPs, led to more robust inferences of population structure. Further, as explained above, we selected the MAF here from a range of tested values. Our choice of MAF here follows the best practices recommended by the most extensive evaluation of the impacts of MAF thresholds on inferences of population structure from genomic datasets available in the literature to date (Linck & Battey 2019). Figures and tables: - Figure-2: As mentioned earlier, I think it would be very useful to modify this figure to incorporate Fst values generated by Clarke et al 2015. I am aware that you have mentioned it in the manuscript text, but having it in a figure is also useful. - Fig.2: RD or RS?!! Thank you for catching this typo! It is corrected. Supplementary data: - I have noticed that your supplementary tables do not have headers and figures were provided with out captions, could you kindly add this information. Apologies, these had headers and captions, but they did not seem to make it through the upload process. We will try to correct that issue during submission of this revision. • Discussions: - Line-286: rephrase: “Pool-seq was able to detect isolated populations within the Gulf of Mexico, in the Western Atlantic, and along the Brazilian coast, where Clarke et al. (2015) found no population structure”. Please correct me if I am wrong, my understanding is that you had one sample site from Gulf of Mexico? While in this statement you mention that you detect isolated populations “within the Gulf of Mexico” is that righ? Correct, we have clarified this line to state “detected isolated populations between the Gulf of Mexico, Western Atlantic, and along the Brazilian coast, where Clarke et al. (2015) found no population structure. I think it would be important to clearly mention in few sentences at the end of your discussion that pool-seq is a cost effective tool but is limited. For high budget projects its more reliable and informative to other tools such as RADseq and SNP array which are individual based genotyping methods that will allow deeper assessment of the sampled populations. However, pool-seq is suited for cases that needs rapid and cost effective assessment to serve the immediate and extensive need in providing population structure studies to serve their management. We agree, therefore the last two paragraphs of the discussion speak to the limitations of Pool-seq. Additionally we did add that sequencing individual genotypes yields a deeper analysis and should be used when funds allow. See line 365-368. • Acknowledgment: Please provide what is supposed to be filled in place of “#XXXX” in line 380 and 381 These numbers are only provided after the paper is accepted and are place holders for them to be corrected in the proofs if the manuscript is accepted. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Although anguillid eel populations have decreased remarkably in recent decades, few detailed ecological studies have been conducted on tropical eels such as the giant mottled eel whose range extends across the whole Indo-Pacific. This species was studied throughout the entire 0.5 km mainstem reaches of Oganeku River on the subtropical Amami-Oshima Island of Japan over a two-year period using 4 sampling periods to understand its habitat preference, early life-stage dispersal process, movements, and annual growth using a mark-recapture experiment conducted with quantitative electrofishing. A total of 396 juvenile growth-phase A. marmorata eels were caught and tagged, with 48 individuals being recaptured at least once. Their density irrespective of size of eels was most strongly determined by distance from the river mouth, followed by riverbank type according to random forest models. Eel density decreased with increasing distance from the freshwater tidal limit located about 100-150 m from the river mouth. Eels preferred vegetated riverbanks, while they avoided those of concrete and sand. The density of small eels (total length: TL &lt; 240 mm) was also associated with depth and velocity, with small eels tending to prefer riffle or run habitats. In contrast, large eels (TL &#8805; 240 mm) were found in habitats of any depth and velocity. The TL of eels had a minimum peak at around the tidal limit, and it increased with increasing distance from the tidal limit.</ns0:p><ns0:p>The observed density and size gradients of eels in relation to the distance from the river mouth suggested that A. marmorata initially recruited to freshwater tidal limit areas and then dispersed in both downstream and upstream directions. The growth rate of eels varied greatly among individuals that were at large for various periods of time and ranged from 0 to 163.2 mm/year (mean &#177; SD of 31.8 &#177; 31.0 mm/year). Of the recaptured eels, 52.1% were recaptured in a section that was different from the original capture section,</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The eels of the genus Anguilla comprise 16 species of catadromous fishes that undertake largescale oceanic migrations between their offshore spawning areas and growth habitats in continental waters during their life histories. Populations of anguillid eels are distributed throughout much of the world from tropical to temperate regions that include more than 150 countries <ns0:ref type='bibr' target='#b35'>(Jacoby et al., 2015)</ns0:ref>. Ten species are distributed in tropical regions (i.e., tropical eels), whereas the remaining six species are distributed in temperate regions (i.e., temperate eels).</ns0:p><ns0:p>Anguillid eels have ecological, commercial, and cultural importance in many regions <ns0:ref type='bibr' target='#b35'>(Jacoby et al., 2015)</ns0:ref> and are increasingly considered as important representative species for freshwater biodiversity conservation efforts <ns0:ref type='bibr' target='#b29'>(Itakura et al., 2020a)</ns0:ref>. Because of population declines, 10 of the 16 anguillid eel species (3 of which are subdivided into subspecies) are listed as 'Threatened' or 'Nearly Threatened' in the International Union for Conservation of Nature (IUCN) Red List of Threatened Species <ns0:ref type='bibr'>(IUCN, 2019)</ns0:ref>. Although, the northern hemisphere temperate anguillids have shown well-documented declines, some tropical eels are also of concern for conservation even though their freshwater ecology has not been studied and they are of lower economic commercial importance than the more extensively studied temperate species <ns0:ref type='bibr' target='#b35'>(Jacoby et al., 2015)</ns0:ref>. Thus, ecological knowledge about tropical eels is clearly essential for the conservation and management of anguillid eels in the Indo-Pacific.</ns0:p><ns0:p>One of the tropical eels, the giant mottled eel, A. marmorata, is the most widespread anguillid species in the world, because it is distributed in the Indian Ocean, and across the Indo-Pacific to French Polynesia in the South Pacific Ocean <ns0:ref type='bibr' target='#b15'>(Ege, 1939;</ns0:ref><ns0:ref type='bibr' target='#b77'>Watanabe, Aoyama &amp; Tsukamoto, 2004</ns0:ref>). The species has multiple genetically distinct populations <ns0:ref type='bibr' target='#b50'>(Minegishi, Aoyama &amp; Tsukamoto, 2008)</ns0:ref>, one of which spawns in the North Equatorial Current region of the western North Pacific Ocean, where the Japanese eel, A. japonica, spawns <ns0:ref type='bibr' target='#b45'>(Kuroki et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b69'>Tsukamoto et al., 2011)</ns0:ref>. Because of a recent increase in demand for A. marmorata as a fisheries/aquaculture replacement for temperate eels, especially in East Asia <ns0:ref type='bibr' target='#b17'>(Gollock et al., 2018)</ns0:ref>, understanding the ecology of A. marmorata is particularly important.</ns0:p><ns0:p>Ecological aspects of growth-phase anguillid eels have been extensively studied in temperate eels such as the American eels (A. rostrata), European eels (A. anguilla), and A. japonica. After larval development and migration in the open ocean, the leptocephalus larvae of anguillid eels metamorphose into glass eels (early juvenile phase) that enter rivers. Glass eels appear to initially accumulate at the freshwater tidal limit of estuaries, and then disperse in both upstream and downstream directions <ns0:ref type='bibr' target='#b23'>(Haro &amp; Krueger, 1991;</ns0:ref><ns0:ref type='bibr' target='#b14'>Edeline et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b40'>Kaifu et al., 2010;</ns0:ref><ns0:ref type='bibr'>Wakiya et al., 2019)</ns0:ref>. They then settle and spend their growth phase in a variety of habitats ranging from saline bays or brackish estuaries to rivers all the way to upland headwaters, and they also live in lakes <ns0:ref type='bibr' target='#b53'>(Moriarty, 2003)</ns0:ref>. While small eels exhibit dispersal or movement behaviors <ns0:ref type='bibr' target='#b47'>(Laffaille, Acou &amp; Guillou&#235;t, 2005;</ns0:ref><ns0:ref type='bibr' target='#b26'>Imbert et al., 2010)</ns0:ref>, large individuals mostly display sedentary behavior with limited movements and small home ranges <ns0:ref type='bibr'>(Gunning &amp; Shoop, 1962;</ns0:ref><ns0:ref type='bibr' target='#b60'>Parker, 1995;</ns0:ref><ns0:ref type='bibr' target='#b37'>Jellyman &amp; Sykes, 2003;</ns0:ref><ns0:ref type='bibr' target='#b58'>Ovidio et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b28'>Itakura et al., 2017)</ns0:ref>. Some individuals however, are increasingly realized to exhibit habitat shifts or seasonal movements between the different habitats <ns0:ref type='bibr' target='#b38'>(Jessop et al., 2002;</ns0:ref><ns0:ref type='bibr'>Daverat et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b82'>Yokouchi et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b4'>B&#233;guer-Pon et al., 2015)</ns0:ref>.</ns0:p><ns0:p>Many studies have reported that the abundance of eels in rivers decline with increasing distance from the tidal limit of estuaries <ns0:ref type='bibr' target='#b25'>(Ibbotson et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b0'>Aprahamian et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b10'>Costa et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b40'>Kaifu et al., 2010;</ns0:ref><ns0:ref type='bibr'>Wakiya et al., 2019)</ns0:ref>. Riverine distribution of eels can be also affected by other environmental factors in microhabitats such as depth, velocity, sediment, aquatic vegetation, riverbank conditions, effects of which can differ depending on the body size of eels <ns0:ref type='bibr' target='#b16'>(Glova, Jellyman &amp; Bonnett, 1998;</ns0:ref><ns0:ref type='bibr' target='#b48'>Laffaille et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b44'>Kume et al., 2019)</ns0:ref>. These types of environmental factors have the potential to influence the distribution of A. marmorata.</ns0:p><ns0:p>The basic habitat use patterns of tropical eels has been studied recently in a few locations where qualitative sampling or otolith microelement analysis were used. Several studies have found that although A. marmorata tends to live in freshwater areas rather than in brackish and marine habitats <ns0:ref type='bibr' target='#b63'>(Shiao et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b55'>Nguyen, Tsukamoto &amp; Lokman, 2018;</ns0:ref><ns0:ref type='bibr' target='#b24'>Hsu, Chen &amp; Han, 2019)</ns0:ref>, the species can occupy a broad range of habitats from brackish estuaries to upland headwaters <ns0:ref type='bibr' target='#b2'>(Arai &amp; Chino, 2018;</ns0:ref><ns0:ref type='bibr' target='#b20'>Hagihara et al., 2018a;</ns0:ref><ns0:ref type='bibr'>Wakiya, Itakura &amp; Kaifu, 2019;</ns0:ref><ns0:ref type='bibr' target='#b42'>Kumai, Tsukamoto &amp; Kuroki, 2020)</ns0:ref>. There are often sympatries of multiple eel species in tropical rivers that appear to affect the patterns of habitat use among the species presumably to reduce interspecific competition <ns0:ref type='bibr' target='#b49'>(Marquet &amp; Galzin, 1991;</ns0:ref><ns0:ref type='bibr' target='#b1'>Arai &amp; Abdul Kadir, 2017;</ns0:ref><ns0:ref type='bibr' target='#b20'>Hagihara et al., 2018a)</ns0:ref>, and sympatries of temperate and tropical eels also occur in subtropical regions of their distribution ranges <ns0:ref type='bibr' target='#b63'>(Shiao et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b24'>Hsu, Chen &amp; Han, 2019;</ns0:ref><ns0:ref type='bibr' target='#b30'>Itakura et al., 2020b)</ns0:ref>. In rivers where a single eel species such as A. marmorata is highly dominant among anguillid species, it is found throughout the river network <ns0:ref type='bibr' target='#b61'>(Robinet et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b33'>Itakura et al., 2019;</ns0:ref><ns0:ref type='bibr'>Wakiya, Itakura &amp; Kaifu, 2019)</ns0:ref>.</ns0:p><ns0:p>The growth rate (GR) of anguillid eels is another key aspect of their ecology that reflects many characteristics of the environments where they live. It has been intensively studied for temperate eels (e.g., <ns0:ref type='bibr' target='#b70'>V&#248;llestad, 1992;</ns0:ref><ns0:ref type='bibr' target='#b54'>Morrison &amp; Secor, 2003;</ns0:ref><ns0:ref type='bibr' target='#b13'>Daverat &amp; Tom&#225;s, 2006;</ns0:ref><ns0:ref type='bibr' target='#b80'>Yokouchi et al., 2008)</ns0:ref>, and GR was recently studied for tropical eels as well <ns0:ref type='bibr' target='#b21'>(Hagihara et al., 2018b;</ns0:ref><ns0:ref type='bibr'>Wakiya, Itakura &amp; Kaifu, 2019;</ns0:ref><ns0:ref type='bibr' target='#b42'>Kumai, Tsukamoto &amp; Kuroki, 2020)</ns0:ref>. There is considerable intra-interspecific variation in the annual GR of eels that is related to their latitudinally expanded distributional regions <ns0:ref type='bibr' target='#b21'>(Hagihara et al., 2018b)</ns0:ref> and the different environments of the wide-range of continental habitats where eels are present <ns0:ref type='bibr' target='#b54'>(Morrison &amp; Secor, 2003;</ns0:ref><ns0:ref type='bibr' target='#b80'>Yokouchi et al., 2008)</ns0:ref>. Eel GR also varies substantially among different ages, years, and individuals <ns0:ref type='bibr' target='#b81'>(Yokouchi &amp; Daverat, 2013)</ns0:ref>. The annual GR of eels has usually been calculated by dividing the body length at capture by age that is estimated based on otolith annual rings after the eels recruit as glass eels, but this method probably overlooks extremely low or high GRs due to inconsistent ring deposition, which would not reflect the actual diversity the GR of eels.</ns0:p><ns0:p>Therefore, ideally, the actual increase of body length during a known period of time of individual eels should be directly measured by mark-recapture experiments, which will provide a more precise understanding of their growth strategies. Our objective was to conduct a comprehensive survey and mark-recapture experiment for two years in a small subtropical island river to understand the habitat preference, early life-stage dispersal, movement, and growth of giant mottled eels on Amami-Oshima Island, Japan. Anguilla marmorata is clearly the dominant anguillid species throughout the rivers in this island <ns0:ref type='bibr'>(Wakiya, Itakura &amp; Kaifu, 2019;</ns0:ref><ns0:ref type='bibr'>Itakura et al., 2020b,a)</ns0:ref>, thus this island offers suitable study sites for a case study to investigate their ecology in small rivers that have minimal interspecific competition.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Study area and sampling</ns0:head><ns0:p>This study was conducted in the Oganeku River on Amami-Oshima Island, Kagoshima Prefecture, Japan (Fig. <ns0:ref type='figure' target='#fig_11'>1</ns0:ref>; 28&#176;21'42.2'N 129&#176;21'03.4'E). Amami-Oshima Island is located between the southern mainland of Japan and Okinawa Island adjacent to the western North Pacific Ocean and next to the Kuroshio Current that is one of the strongest western boundary currents. This is the second largest island in the Nansei Islands (Okinawa is the largest) in terms of area (712.35 km 2 ).</ns0:p><ns0:p>The climate of this island is characterized by a warm and wet climate with an average annual temperature of 21.6&#186;C (monthly range: 14.8-28.7&#186;C), with a peak in July and annual precipitation of 2837.7 mm (monthly range: 156.9-410.3 mm) with a peak in June (1981-2010 data of the Japan Meteorological Agency, https://www.jma.go.jp/jma/index.html).</ns0:p><ns0:p>The study river is approximately 0.5 km in length, and flows through agricultural and forest lands (Fig. <ns0:ref type='figure' target='#fig_4'>2</ns0:ref>). The elevation of the river increases dramatically to &gt;10 m from around the 320 m area from the river mouth where the riverscape transitioned to higher-gradient upstream environments. There is a waterfall &gt;10 m height at 520 m from the river mouth (elevation = 50 m). Although some eels might be able to climb the waterfall, we surveyed from the river mouth to the waterfall, because we were not able to access areas above the waterfall. Because the river width around the waterfall is much narrower (&lt;1m), the river flow may originate not far above the waterfall. Thus, our surveyed area was considered to cover almost all of the mainstem of the river. The width of the river was 3.2 &#177; 2.0 m (mean &#177; SD; range: 0.5-8.4 m), and the depth was 22.2 &#177; 16.7 cm (range: 3-75 cm). The freshwater tidal limit of the river was observed during our surveys to be located at about 100-150 m from the river mouth based on tidally influenced increases in water depth during high tides. The freshwater areas of this island are dominated by diadromous species <ns0:ref type='bibr' target='#b29'>(Itakura et al., 2020a)</ns0:ref>. A total of 33 species (24 fishes and 9 crustaceans) was identified in the study river during the sampling surveys, all of which were diadromous species (Table <ns0:ref type='table'>S1</ns0:ref>). A. marmorata was the dominant fish species in terms of both abundance and biomass in the river. This island is near the northern limit of the distribution range of A. marmorata <ns0:ref type='bibr' target='#b36'>(Jacoby &amp; Gollock, 2014)</ns0:ref>, but some eels also recruit to areas farther north in mainland Japan <ns0:ref type='bibr' target='#b52'>(Mizuno &amp; Nagasawa, 2010)</ns0:ref>.</ns0:p><ns0:p>We chose this river because (1) such a small stream allowed us to conduct quantitative sampling throughout all the main reaches of a river using electrofishing, and (2) there are no artificial migration barriers (e.g., weirs and dams) that can impede eel movement in the river, thus providing a good model system to examine their ecology without the effects of barriers. A recent study conducted in other rivers on this island showed that the density of A. marmorata was strongly negatively associated with cumulative height of the barriers <ns0:ref type='bibr' target='#b29'>(Itakura et al., 2020a)</ns0:ref>.</ns0:p><ns0:p>Quantitative sampling for eels was carried out a total of four times during August and November 2016, July 2017, and September 2018 (25 month period). We captured anguillid eels over almost the entire area of the river from the river mouth to the uppermost reaches of the river (below the waterfall) using a back-pack electroshocker (LR-20B, Smith-Root, Inc., Vancouver, WA, USA) and hand nets by two people during daytime. Each 10 m interval of the river channel was regarded as a sampling section (defined by the downstream border), and each section was defined by the distance from the river month. Each section was sampled by moving side to side starting from the downstream direction moving upstream, with each section being marked with wooden stakes along the riverbank. Sampling was performed during low tides at sections below the freshwater tidal limit of the river in order to avoid the effect of salinity on the efficiency of electrofishing. As a result, we confirmed the sections were freshwater during low tides. Captured eels were held in river water until they were anaesthetized with 10% eugenol solution (FA100; DS Pharma Animal Health Co., Ltd. Japan). Each specimen was identified morphologically following <ns0:ref type='bibr' target='#b77'>Watanabe, Aoyama &amp; Tsukamoto, (2004)</ns0:ref>, and their growth stage was confirmed based on the color of its body and pectoral fins following previous studies <ns0:ref type='bibr' target='#b57'>(Okamura et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b19'>Hagihara et al., 2012)</ns0:ref>. One sexually-maturing A. marmorata (580 mm in TL) was collected at the 290 m section on September 2018 and this was excluded from this study, because it might have already started its early migration to the ocean to spawn.</ns0:p><ns0:p>The TL and body weight (BW) of each eel were measured to the nearest 1 mm and 0.1 g, respectively, and then they were individually tagged and released back into the capture sites after they fully recovered from the anaesthesia. Each eel was tagged using different methods depending on its body weight. Large eels with BW &#8805; 10 g were individually tagged by injecting a passive integrated transponder (PIT tag; BIO8.B03, Biomark, ID, USA; 1.4 mm diameter) tags into the abdominal cavity (228 eels), while small ones with BW &lt; 10 g were tagged using injected visible implant elastomer (VIE tag; Northwest Marine technology, WA, USA) tags (105 eels). The small eels were individually distinguished based on a combination of different elastomer colors and the area of the body where they were injected (i.e., jaw, eye, and near anus).</ns0:p><ns0:p>The sampling was conducted under the guidance and with the permission of the Fisheries Adjustment Rules of Kagoshima Prefecture <ns0:ref type='bibr'>(approval number: 2006-5 for 2016 and 2006-10 for 2017 and 2018)</ns0:ref>.</ns0:p><ns0:p>Environmental conditions at each sampling section were measured and recorded immediately after the sampling in August 2016, which was during typical water flow conditions compared to the other sampling periods. The depth and water velocity were measured at the center of the river in the middle of each 10 m section, while the river width was measured at the downstream border of each section. The sediment was categorised into six types: mud, sand, gravel, boulder, concrete or bedrock, and mud and boulder. The riverbank was categorised into seven types by the combination of left and right banks: sand, boulder, vegetation, concrete, concrete and gravel, concrete and vegetation, and concrete and boulder (i.e., 2 classifications per section).</ns0:p></ns0:div> <ns0:div><ns0:head>Growth and movement</ns0:head><ns0:p>The growth rate (GR; mm/year) of each recaptured eel was calculated as: &#119866;&#119877; =</ns0:p><ns0:p>where TL 1 and TL 2 are TL of eels at t 1 (date at capture) and t 2 ( (&#119879;&#119871; 2 -&#119879;&#119871; 1 ) (&#119905; 2 -&#119905; 1 ) ) &#215; 365 (date at recapture).</ns0:p><ns0:p>The distance travelled (m) of recaptured eels was calculated as distance between the capture and recapture sections. As we did not document where eels were captured within each section, eel movement was quantified only when an eel was recaptured in a section that is different from the original capture section. The eel movement distance was regarded as 0 m (absence of movement, i.e., travel distance &lt; 10 m) when they were recaptured in the same section where they were originally captured, whereas it was regarded as a 10 m movement when they were recaptured in an adjacent section. Technically, this means that the eel movements between adjacent sections could have ranged from 0 (on the section borderline) to 20 m (on opposite borderlines). Thus, for analyzing relationships between eel TL and presence of movement, we used both 10 and 20 m distances for adjacent-section movements.</ns0:p></ns0:div> <ns0:div><ns0:head>Data analysis</ns0:head><ns0:p>All statistical analyses were performed with R 3.6.0. To evaluate the riverine distribution of TL of eels, we used a generalized additive model (GAM; gam function in the mgcv) <ns0:ref type='bibr' target='#b79'>(Wood, 2019)</ns0:ref>, which included TL as a response variable (gaussian distribution with an identity-link function), and distance from the river mouth as a predictor variable. To assess how the eel movement changed as the eels grew, we used a generalized linear model (GLM), which included either the presence or absence of eel movement (i.e., 1 or 0) as a response variable (binomial distribution with a logit-link function), and TL as a predictor variable. The relationship between TL at initial capture before each recapture and distance travelled of recaptured eels was also evaluated using a GLM with a negative binomial distribution and a log-link function. In addition, the effects of TL class (small and large eels), TL at initial capture before each recapture, the study period (i.e., duration between capture and recapture), the eel movement (i.e., distance travelled of 0 m, &lt;80 m, &#8805;80 m), and the sampling section from the river mouth on the GR of recaptured eels were assessed using a GLM with a gaussian distribution and an identity-link function. The GR was log-transformed by adding 1, to meet the assumption of normality of the residuals. In the growth model, variable selections were performed according to Akaike's information criterion (AIC) using dredge in the package MuMIn <ns0:ref type='bibr' target='#b3'>(Barto&#324;, 2019)</ns0:ref>. Moreover, the proportion of eels that moved and the distance travelled by eels were compared between small and large eels using the Fisher's exact test and the Exact Wilcoxon-Mann-Whitney test, respectively. TL of eels at initial capture before each recapture was also compared between eels that moved and those that did not move using the Exact Wilcoxon-Mann-Whitney test. We defined eels &lt; 240 mm TL as small eels, and eels &#8805; 240 mm TL as large eels, following previous studies for growth-phase European and Japanese eels that reported that the mobility of eels can change at around 240 mm TL <ns0:ref type='bibr' target='#b26'>(Imbert et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b76'>Wakiya, Kaifu &amp; Mochioka, 2016)</ns0:ref>, because there is no information on the TLmobility relationship for A. marmorata.</ns0:p><ns0:p>To evaluate the effects of environmental factors on the density of eels, we used the permutation-based random forest (RF) machine learning algorithm <ns0:ref type='bibr' target='#b22'>(Hapfelmeier &amp; Ulm, 2013)</ns0:ref>. The RF is an ensemble learning algorithm that builds a predictive regression model (forests) by taking an average from outputs of a large number of decision tree models <ns0:ref type='bibr' target='#b9'>(Breiman, 2001)</ns0:ref>. We selected the RF algorithm, because RF (1) does not require normality or independence of the variables, ( <ns0:ref type='formula'>2</ns0:ref>) is able to handle non-linear relationships well, (3) is not prone to overfitting by averaging a large number of decision tree models <ns0:ref type='bibr' target='#b9'>(Breiman, 2001)</ns0:ref>, (4) fairly evaluates the relative importance between continuous and categorical variables without bias <ns0:ref type='bibr' target='#b65'>(Strobl et al., 2008)</ns0:ref>, and (5) can perform variable selection and assess the relative importance among highly correlated variables <ns0:ref type='bibr' target='#b56'>(Nicodemus et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b5'>Bergmann et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The density of A. marmorata in each sampling section was calculated by dividing the number of captured eels by area of the study section (m 2 ). The densities of eels of three size classes were used as response variables: all eels, small eels (TL&lt;240 mm), and large eels (TL&#8805;240 mm). The environmental factors including depth, water velocity, distance from the river mouth, sediment, and riverbank were used as predictor variables. We used the RF algorithm for performing multiple regressions for variable selection <ns0:ref type='bibr' target='#b22'>(Hapfelmeier &amp; Ulm, 2013;</ns0:ref><ns0:ref type='bibr' target='#b62'>Ryo et al., 2018)</ns0:ref>. The RF algorithm with variable selection by <ns0:ref type='bibr' target='#b22'>Hapfelmeier &amp; Ulm (2013)</ns0:ref> first performs a multiple regression using all predictor variables to estimate a statistical significance for each variable. Then, the RF algorithm performs a multiple regression using only significant variables to construct the final RF model and to estimate a relative importance score for each variable (see <ns0:ref type='bibr' target='#b22'>Hapfelmeier &amp;</ns0:ref><ns0:ref type='bibr' target='#b22'>Ulm, 2013 and</ns0:ref><ns0:ref type='bibr' target='#b62'>Ryo et al., 2018</ns0:ref> for more detail about the RF algorithm). We set the significance level to 0.01 with Bonferroni correction for the number of predictor variables following <ns0:ref type='bibr' target='#b62'>Ryo et al. (2018)</ns0:ref>. The relative importance score of each variable was quantified by evaluating how much model accuracy can decrease when the model removes the focal variable <ns0:ref type='bibr' target='#b9'>(Breiman, 2001)</ns0:ref>. The modelled relationships between the predictor variables and each response variable were visualized using partial dependence plots, which represent the marginal effect of a particular response variable on the modelled function after marginalizing out the effects of all the other variables. The procedure calculates a partial dependence score that indicates the relative extent of the response variable. In our case, the higher the score, the higher the density of eels.</ns0:p><ns0:p>Model performance was evaluated based on explanatory and predictive powers (R 2 ). Explanatory power was evaluated based on the coefficient of determination by comparing observed and fitted values as explained variance. In contrast, prediction power (validation accuracy) is a metric to estimate an expected model performance for prediction when a new dataset is analyzed.</ns0:p><ns0:p>Prediction power was also evaluated based on the coefficient of determination using 1/3 of the samples that were not used in the tree construction, following the out-of-bag technique <ns0:ref type='bibr' target='#b8'>(Breiman, 1996)</ns0:ref>. We used the R script available in <ns0:ref type='bibr' target='#b62'>Ryo et al. (2018)</ns0:ref>, which was modified from the script by <ns0:ref type='bibr' target='#b22'>Hapfelmeier &amp; Ulm (2013)</ns0:ref>. The script is based on ctree and cforest functions in the package party <ns0:ref type='bibr' target='#b66'>(Strobl, Hothorn &amp; Zeileis, 2009)</ns0:ref> for RF modeling, cforeststats and postResample functions in the package caret <ns0:ref type='bibr' target='#b41'>(Kuhn et al., 2020)</ns0:ref> for evaluating model performance, and the generatePartialDependenceData function in the package mlr <ns0:ref type='bibr' target='#b7'>(Bischl et al., 2020)</ns0:ref> for partial dependence plots. All parameters in the functions were set to defaults.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Number of collected eels, size and density</ns0:head><ns0:p>A total of 396 growth-phase A. marmorata were collected in this study (this includes number of recaptured eels). Eels were collected in each of the 4 sampling times of August 2016 (152 eels), November 2016 (80 eels), July 2017 (60 eels), and September 2018 (104 eels). The size of all captured eels ranged from 62 to 770 mm TL with a mean &#177; SD of 336.8 &#177; 153.0 mm (Fig. <ns0:ref type='figure' target='#fig_5'>3</ns0:ref>) and their BW ranged from 0.5 to 1219.0 g with a mean &#177; SD of 136.7 &#177; 167.5 g. The number of collected eels per sampling section ranged from 0 to 19 individuals, with the greatest singlesection catch (n = 19) consisting of only large eels (TL &#8805; 240 mm, 431.1 &#177; 89.4 mm, 246-590 mm) that were collected at a section 60 m from the river mouth that consisted of concrete and boulder riverbanks and mud sediment (Fig. <ns0:ref type='figure' target='#fig_6'>4</ns0:ref>). The density of eels in each section (when more than 1 individual was collected) ranged from 0.01 to 0.69 eels m -2 , with a mean &#177; SD of 0.15 &#177; 0.13 eels m -2 (Fig. <ns0:ref type='figure' target='#fig_11'>S1A</ns0:ref>). Of the collected eels, 48 individuals were recaptured at least once (39 PIT tagged eels, 9 elastomer tagged; 8 recaptures 2-3 times), and thus a total of 339 unique individuals were collected in this study. We obtained 57 records on movement events and 57 records for annual GR of the 48 recaptured eels. The TL of these eels at first-capture was 381.3 &#177; 131.0 mm, with a range from 105 to 656 mm, and those at recapture were 408.1 &#177; 135.8 mm in TL, with a range from 139 to 770 mm. A total of seven A. japonica were collected at 60, 80, 90, 100, 150, 170, and 280 m sections where the sediment consisted of gravel and riverbanks consisted of boulders or vegetation, and water velocities were &lt;40 cm -2 (Fig. <ns0:ref type='figure' target='#fig_6'>4</ns0:ref>). Their TL was 364.0 &#177; 161.7 mm, with a range from 126.0 to 541.0 mm (Fig. <ns0:ref type='figure' target='#fig_6'>4C</ns0:ref>). The captured A. japonica were omitted from the analyses of this study.</ns0:p></ns0:div> <ns0:div><ns0:head>Size distribution</ns0:head><ns0:p>Almost all small eels (TL &lt; 240 mm) were collected in the sections that were about 100-300 m from the river mouth, and more of the smallest eels &lt; 100 mm TL were collected in the 100-200 m sections (Fig. <ns0:ref type='figure' target='#fig_6'>4C</ns0:ref>). Conversely, large eels (TL &#8805; 240 mm) were collected throughout the river (Fig. <ns0:ref type='figure' target='#fig_6'>4C</ns0:ref>), although they were not evenly distributed. Large eels were caught in 82% of the total sections, but small eels were caught only in 54% of the total sections. The GAM showed that the TL of A. marmorata was significantly associated with distance from the river mouth (Effective d.f. = 8.556, Reference d.f. = 8.927, F = 15.45, p &lt; 0.001; Fig. <ns0:ref type='figure' target='#fig_6'>4C</ns0:ref>). The predicted TL reached a minimum value at around the 100-150 m sections in part due to few large eels being caught there, and it increased with increasing distance upstream because only 3 small eels were caught above 300 m (Fig. <ns0:ref type='figure' target='#fig_6'>4C</ns0:ref>). However, large eels &#8805; 240 mm TL were caught from very near the river mouth to the farthest upstream sections, with the most eels &gt; 600 mm TL being caught near 300 m where a wide size range (141-770 mm TL) was present in an area that was pool and run habitats with gravel or mud sediments and concrete and boulder riverbanks (Fig. <ns0:ref type='figure' target='#fig_6'>4</ns0:ref>, Figs. S1A, S1B, S1C).</ns0:p></ns0:div> <ns0:div><ns0:head>Habitat preference</ns0:head><ns0:p>Distance from the river mouth was the most important explanatory variable to predict density of eels followed by riverbank type, both of which were selected by the RF models for all three sizeclasses (i.e., all eels, small eels, and large eels) (Fig. <ns0:ref type='figure' target='#fig_7'>5</ns0:ref>). Conversely, velocity and depth were only selected by the model for small eels. The explanatory powers (R 2 value) were 45.7%, 40.9%, and 32.3% of the variation in densities of all, small, and large eels, respectively (validation accuracy: 30.3%, 23.6%, and 16.4%, respectively).</ns0:p><ns0:p>The density of eels peaked at around 130-200 m sections where both large and small eels were present, and it decreased with increasing distance from the peaks where fewer mostly large eels were found (Fig. <ns0:ref type='figure' target='#fig_8'>6A</ns0:ref>). The density of small eels was consistently low at more reaches of the river upstream of the 300 m section (less than 0.02 eels m 2 ), especially considering that only 4</ns0:p><ns0:p>(August 2016), 0 (November 2016), 0 (July 2017), and 3 (September 2018) small eels were caught (Fig. <ns0:ref type='figure' target='#fig_12'>S2</ns0:ref>). Eels were abundant just below the 310 m section, which was a pool habitat followed by concrete riverbank and sediment habitats at 320-350 m sections, and then the riverscape greatly changed to high elevation gradient (&gt;10 m) upstream environments (boulder riverbank and boulder and gravel sediments) at the 360 m section (Fig. <ns0:ref type='figure' target='#fig_4'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_6'>4</ns0:ref>). The density of eels was consistently lower among all three size-classes when riverbanks consisted of concrete and sand, while it was the highest when riverbanks consisted of vegetation, some of which extended into the water where some eels were collected (Figs. <ns0:ref type='figure' target='#fig_9'>6B, 7D</ns0:ref>). The density of small eels decreased when water depth was more than 15 cm (Fig. <ns0:ref type='figure' target='#fig_8'>6C</ns0:ref>) and when water velocity was less than 20 cm -S (Fig. <ns0:ref type='figure' target='#fig_8'>6D</ns0:ref>). In contrast, large individuals were found in a broader range of habitats with any depth and velocity (Figs. <ns0:ref type='figure' target='#fig_9'>7A, 7B</ns0:ref>).</ns0:p><ns0:p>Although sediment type was not selected the RF models for all three size-classes as a significant variable, the density of eels appeared to differ among sediment types (Fig. <ns0:ref type='figure' target='#fig_8'>6C</ns0:ref>). Eels were rarely found in sediment consisting of concrete and sand, and no large eels were found there. Almost all small eels were found in gravel sediment habitats that were located from 70 m to 300 m sections (Figs. 4, 7C), while they were rarely found in other sediment types. Large eels were found in a broader range sediment types with their densities being higher in mud and boulder sediments, and in combinations of habitats (Figs. <ns0:ref type='figure' target='#fig_9'>4, 7C</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Movements of tagged eels</ns0:head><ns0:p>Of the recaptured eels, 47.9% were recaptured from their original section of capture (i.e., distance travelled &lt;10 m) (Figs. <ns0:ref type='figure' target='#fig_10'>8A, 8B</ns0:ref>), and the distance travelled of 75.9% of eels that were recaptured in a section that is different from the original capture section (i.e., distance travelled &#8805; 10 m) were less than 50 m. Of the observed movement events (n = 31), 54.8% of the eels travelled in the upstream direction from the original section of capture (Fig. <ns0:ref type='figure' target='#fig_10'>8B</ns0:ref>). The distance travelled of recaptured eels that moved &#8805; 10 m ranged from 10 m to 380 m with a mean &#177; SD of The proportion of movements more than 10 m was higher in small eels (75.0%) than in large eels (51.1%), but there was not a significant difference (Fisher's Exact Test, P = 0.191).</ns0:p><ns0:p>The distance travelled of small eels (mean &#177; SD = 84.4 &#177; 121.9 m, median = 20) was greater than that of large eels (mean &#177; SD = 30.9 &#177; 31.0 m, median = 20), but there was not a significant difference (Exact Wilcoxon-Mann-Whitney test, P = 0.262; Fig. <ns0:ref type='figure' target='#fig_10'>8B</ns0:ref>). There were no significant relationships between the probability of occurrence of eel movement and TL at initial capture before each recapture (GLM: P &gt; 0.05), irrespective of the possible distances at which the movement was observed (i.e., 10 and 20 m). The distance travelled of eels was significantly negatively related to TL at initial capture (GLM: coefficient &#177; SE =&#8722;0.003 &#177; 0.001, t =&#8722;2.376, P = 0.018), however, TL at initial capture was not statistically different between eels that moved and those that did not move (Exact Wilcoxon-Mann-Whitney test, P = 0.138; Fig. <ns0:ref type='figure' target='#fig_5'>S3A</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Growth rate</ns0:head><ns0:p>The GR of recaptured eels ranged from 0 to 163.2 mm/year with a mean &#177; SD of 31.8 &#177; 31.0 mm/year (median = 24.1 mm/year; n = 57) (Fig. <ns0:ref type='figure' target='#fig_10'>8C</ns0:ref>). The best GLM having the lowest AIC value showed that the GR was significantly higher for eels that moved &#8805;80 m (GLM: coefficient &#177; SE = 1.798 &#177; 0.528, t = 3.405, P = 0.001) than for eels that moved &lt;80 m (GLM: coefficient &#177; SE = 0.750 &#177; 0.320, t = 2.344, P = 0.023), both categories of eels that moved had significantly higher GR than the eels that did not move (Fig. <ns0:ref type='figure' target='#fig_5'>S3B</ns0:ref>); although it is still unclear whether eels that moved ended up growing faster or faster growing individuals decided to move more. GR also increased with TL at initial capture (GLM: coefficient &#177; SE = 0.004 &#177; 0.001, t = 3.856, P &lt; 0.001; Fig. <ns0:ref type='figure' target='#fig_6'>S4A</ns0:ref>). The GR of eels was lower for small eels than that of large eels (Fig. <ns0:ref type='figure' target='#fig_5'>S3C</ns0:ref>) and was different among the study periods (Fig. <ns0:ref type='figure' target='#fig_6'>S4B</ns0:ref>), but these variables were not selected by the best model. Similarly, the sampling section distance from the river mouth was not selected by the best model for affecting GR. The eels that showed no growth between marking and recapture included five eels that were captured 3 months after tagging, and two eels that were captured after 11 and 25 months (Fig. <ns0:ref type='figure' target='#fig_6'>S4A</ns0:ref>)</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head>Habitat preference</ns0:head><ns0:p>The RF models revealed that the distance from the river mouth was consistently the most important variable to explain density of A. marmorata irrespective of size of eels. Few small eels were caught in the upstream sections &gt; 300 m upstream and in sections &lt; 100 m from the river mouth where large eels were present. Eels of all sizes were present from 100-300 m. As anguillid eels recruit from the sea to rivers, it has been well known for temperate eels that the density of eels in rivers is strongly related with the distance from the river mouth <ns0:ref type='bibr' target='#b64'>(Smogor, Angermeier &amp; Gaylord, 1995;</ns0:ref><ns0:ref type='bibr' target='#b16'>Glova, Jellyman &amp; Bonnett, 1998;</ns0:ref><ns0:ref type='bibr' target='#b25'>Ibbotson et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b80'>Yokouchi et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b33'>Itakura et al., 2019)</ns0:ref>. For tropical eels, the abundance of A. marmorata was also significantly related with the distance from the river mouth when the species is highly dominant among anguillid species throughout rivers <ns0:ref type='bibr' target='#b61'>(Robinet et al., 2007;</ns0:ref><ns0:ref type='bibr'>Itakura et al., 2020b,a)</ns0:ref>, which is consistent with our findings. Therefore, the distance from the river mouth is likely one of the most common and important factors that determine the riverine distributions anguillid eel species.</ns0:p><ns0:p>The density of small A. marmorata was also negatively or positively related with water depth and velocity, respectively. Higher densities of small eels being present at shallower depths compared to in deeper areas was also found for temperate eels such as A. japonica <ns0:ref type='bibr' target='#b44'>(Kume et al., 2019)</ns0:ref>, A. anguilla <ns0:ref type='bibr' target='#b48'>(Laffaille et al., 2003)</ns0:ref>, A. rostrata <ns0:ref type='bibr' target='#b39'>(Johnson &amp; Nack, 2013)</ns0:ref>, and A. australis <ns0:ref type='bibr' target='#b16'>(Glova, Jellyman &amp; Bonnett, 1998)</ns0:ref>, and higher densities of small eels were also found in faster velocity waters for A. anguilla <ns0:ref type='bibr' target='#b48'>(Laffaille et al., 2003)</ns0:ref> and A. dieffenbachii <ns0:ref type='bibr' target='#b16'>(Glova, Jellyman &amp; Bonnett, 1998)</ns0:ref>. Small A. marmorata, therefore, seem to prefer shallow and fast-velocity waters (i.e., riffle or run, usually gravel or rocky sediments) rather than deep and slow-velocity areas (i.e., pools), although it should be noted that it is likely more difficult to collect small eels using electrofishing in deep areas than shallow areas, which could partly cause the difference of catchability between these areas. The distribution of small A. marmorata was biased toward habitats that consisted of gravel sediment, possibly because all tidal limit areas in the study river where almost all small eels were collected consisted of the gravel sediment. The grain size of gravel as a refuge seems better for small eels than others, and so the riffle or run habitats with gravel may provide suitable refuges and feeding area for small eels. Conversely, such riffle and run habitats with gravel were also present in the upper reaches of the river, but the distribution of small eels was biased toward the lower reaches, suggesting that they prefer such habitats in the lower reaches. Because sediment was not selected by the RF models as an important variable, these results imply that the effect of sediment was masked by the strong effect of distance from the river mouth. As shown by this study and previous studies, the distance from the river mouth strongly contributes to determine eel density, which may mask microhabitat effects, especially when the survey was only conducted in a river that includes one pattern of distribution of habitat variables in relation to the distance from the river mouth. Therefore, further surveys in multiple rivers that have diverse distribution patterns of habitat variables are required to clarify microhabitat effects on eel distribution without the effect of the distance from the river mouth.</ns0:p><ns0:p>In contrast with small eels, the density of large A. marmorata was not significantly related to the microhabitat environments except for riverbank type. This indicates that the relationship between the microhabitat environments and eel density disappeared as the eels grow. Indeed, large individuals were found in broader habitats with any depth, velocity, and sediment type, and these factors were not selected by the final RF models. A similar finding was found for A. japonica in which the density of large eels &#8805;240 mm TL was not correlated with any depth, velocity, or sediments <ns0:ref type='bibr'>(Ministry of Environment, 2016)</ns0:ref>. Such size-dependent changes in habitat use has also been reported for other anguillid species: large A. dieffenbachii are more uniformly spread across riffle, run, and pool habitats than small ones <ns0:ref type='bibr' target='#b16'>(Glova, Jellyman &amp; Bonnett, 1998)</ns0:ref>;</ns0:p><ns0:p>A. anguilla progressively shift to deeper habitats as they grow <ns0:ref type='bibr' target='#b48'>(Laffaille et al., 2003)</ns0:ref>; and small A. japonica used habitats near riverbanks, but large ones used habitats both near-riverbank and the center of rivers <ns0:ref type='bibr' target='#b43'>(Kume et al., 2020)</ns0:ref>. Our results and those of previous studies suggest that eels appear to be able to flexibly use habitats having a variety of environments as they grow, which allow eels to move into and utilize the entire range of continental waters from saline bays, to entire river systems up to the headwaters if there are no obstacles <ns0:ref type='bibr' target='#b53'>(Moriarty, 2003)</ns0:ref>.</ns0:p><ns0:p>Although A. marmorata seem to inhabit any habitat type as they grow, they appeared less likely to prefer habitats where the physical structure of the riverbank or riverbed was artificially altered by concrete. The RF models revealed that riverbank type also consistently contributed to explaining the density of eels as the second most important variable irrespective of size of eels.</ns0:p><ns0:p>While the models estimated the highest densities to occur when riverbanks consisted of vegetation, riverbanks consisting of concrete and sand were estimated to have the lowest densities. Moreover, eels were rarely found in sediment areas that consisted of concrete and no large eels were found there. It was reported that abundance of A. japonica was lower in areas that consisted of concrete revetment compared to those with vegetation or mud <ns0:ref type='bibr' target='#b27'>(Itakura et al., 2015)</ns0:ref>, which corresponds to our findings. Such habitat modifications often result in reduced abundance and diversity of freshwater animals due to loss of structural diversity along riverbanks or riverbeds <ns0:ref type='bibr' target='#b68'>(Taniguchi, Inoue &amp; Kawaguchi, 2001;</ns0:ref><ns0:ref type='bibr' target='#b78'>Wolter, 2001)</ns0:ref>. Thus, it is obvious that concrete does not provide suitable habitat for eels or their prey species because it is not possible to find shelter in concrete unless it is highly fractured, which may lead to the somewhat patchy distribution observed in this study. However, the density of eels was higher in sections that the riverbank consisted of concrete with boulders, vegetation, and gravel compared to that of concrete only. These combinations between concrete and the other materials made the density of eels almost identical to that in habitat consisting of vegetation. In addition, with regard to the combination between riverbank and sediment types, some eels were caught in the 110 and 120 m sections where the riverbank consisted of concrete with other types of sediments, while only one eel was caught in 320-350 m sections where both riverbank and sediment consisted of concrete.</ns0:p><ns0:p>These results suggest that the combination-habitats of concrete and other materials may provide Manuscript to be reviewed enough refuges for eels to inhabit the river at the current density levels.</ns0:p><ns0:p>However, habitat losses such as shoreline and riverbed modifications might cause higher densities of A. marmorata in the more suitable natural habitats by concentrating eels in those habitats. The resulting stronger intraspecific competition may lead to increased mortality or slower growth. A long life (mean &#177; SD = 12.8 &#177; 4.9 years; range = 3-30 on the study island: <ns0:ref type='bibr'>Wakiya, Itakura &amp; Kaifu, 2019)</ns0:ref> with very slow annual growth, strong site fidelity, and sizedependent habitat preference of A. marmorata imply that they may be impacted by the habitat modifications of rivers on small islands such as the Oganeku River. Therefore, it is important to have long-term maintenance of diverse riverine habitats to conserve this eel species.</ns0:p><ns0:p>The TL of A. marmorata observed in the study river (336.8 &#177; 153.0 mm with a range of 62-770 mm) did not clearly differ with that in other rivers on the same island (385.5 &#177; 172.6 mm with a range of 119-1320 mm; <ns0:ref type='bibr'>Wakiya, Itakura &amp; Kaifu, 2019)</ns0:ref>; however, larger eels &gt;800 mm in TL were absent in this study. It is well known that A. marmorata can frequently grow up to over a meter, but such larger eels are females only <ns0:ref type='bibr' target='#b21'>(Hagihara et al., 2018b)</ns0:ref>. <ns0:ref type='bibr'>Wakiya, Itakura &amp; Kaifu, (2019)</ns0:ref> reported that males are dominant in other rivers in same island and there were very few larger female eels &gt;800 mm. Although sex was not identified in this study, the majority of eels caught in the study river seems to be males that can start the spawning migration at &lt; 800 mm in TL, which may explain the absence of larger eels (females) there. The absence of the larger eels in the study river might be explained by the lack of much deeper pool waters that are preferred by larger eels, while rivers in <ns0:ref type='bibr'>Wakiya, Itakura &amp; Kaifu, (2019)</ns0:ref> have such deeper waters due to their larger river scale than the study river.</ns0:p></ns0:div> <ns0:div><ns0:head>Dispersal process after recruitment</ns0:head><ns0:p>The distributions of density and TL of A. marmorata provided interesting information about the dispersal process of the species after recruitment into the river. Eels that were &lt;100 mm TL were mostly found in the sections 100-200 m from the river mouth where the freshwater tidal limit was located (100-150 m), while small eels &lt;240 mm TL were found at a wider range of sections between 100-300 m. The GAM model showed that the TL of eels had a minimum peak at around the tidal limit of the 100-150 m sections, and increased with increasing distance from the tidal limit. Moreover, the RF models revealed that densities of all eels, small eels, and large eels peaked at around the tidal limit, and they decreased with increasing distance from the tidal limit.</ns0:p><ns0:p>These density and size gradients of eels in relation to the distance from the river mouth indicate that A. marmorata initially recruited to freshwater tidal limit areas after recruitment into the river and then dispersed in both downstream (&lt;75 m) and upstream directions as they grew. No glass eels and few smaller eels of A. marmorata were collected in this study, partly because it is difficult to capture them using electrofishing. Nevertheless, we collected small eels less than 100 mm TL with the smallest individual being 62 mm TL, which would likely be individuals that recruited to the river within the last year. Therefore, A. marmorata arriving from the sea into the river seem to initially settle in the tidal limit area. This type of dispersal process after recruitment may be common among anguillid eels because similar processes have been reported for temperate eels such as A. anguilla <ns0:ref type='bibr' target='#b14'>(Edeline et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b10'>Costa et al., 2008)</ns0:ref> and A. japonica <ns0:ref type='bibr' target='#b40'>(Kaifu et al., 2010;</ns0:ref><ns0:ref type='bibr'>Wakiya et al., 2019)</ns0:ref>. Glass eels and the subsequent smaller growth-phase eels are often abundant at the freshwater areas of the upper estuaries (tidal limit) of rivers and their sizes increase with increasing distance from the tidal limit, while their densities peaked at the tidal limit <ns0:ref type='bibr' target='#b23'>(Haro &amp; Krueger, 1991;</ns0:ref><ns0:ref type='bibr' target='#b13'>Daverat &amp; Tom&#225;s, 2006;</ns0:ref><ns0:ref type='bibr' target='#b0'>Aprahamian et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b14'>Edeline et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b10'>Costa et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b40'>Kaifu et al., 2010;</ns0:ref><ns0:ref type='bibr'>Wakiya et al., 2019)</ns0:ref>. Conversely, a more homogenous distribution of smaller growth-phase eels was found in an estuary compared to the glass eels <ns0:ref type='bibr' target='#b14'>(Edeline et al., 2007)</ns0:ref>. These size and density gradients of eels are thought to result from the dispersal behavior of eels, which shows that glass eel arriving from the sea accumulate at the freshwater tidal limit of an estuary and then disperse in both more downstream and upstream directions as they grow. Our first of their kind results for tropical eels are in agreement with these previous studies. The common point between A. marmorata in this study and these temperate eel species is that each eel species is highly dominant among anguillid species throughout the rivers in each distributional area. In our study river, only 7 Japanese eels were caught during the 4 sampling periods, so they are clearly not abundant compared to A. marmorata, or most do not survive very long. The dispersal process of A. marmorata shown in this study may change depending on whether sympatries of multiple eel species occur within same watersheds <ns0:ref type='bibr' target='#b49'>(Marquet &amp; Galzin, 1991;</ns0:ref><ns0:ref type='bibr' target='#b63'>Shiao et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b1'>Arai &amp; Abdul Kadir, 2017;</ns0:ref><ns0:ref type='bibr' target='#b20'>Hagihara et al., 2018a;</ns0:ref><ns0:ref type='bibr' target='#b24'>Hsu, Chen &amp; Han, 2019)</ns0:ref>. Therefore, future research conducted in regions with sympatries of multiple eel species will help to further understand how these sympatric eel species disperse to each habitat in river systems. This dispersal behavior might be an adaptive strategy to increase individual fitness by reducing intraspecific competition. The mortality of eels in freshwater may primarily be related to density-dependent factors such as intraspecific competition for resources or predation by eels <ns0:ref type='bibr' target='#b71'>(V&#248;llestad &amp; Jonsson, 1988)</ns0:ref>. Because higher density would lead to stronger intraspecific competition, the eel movements from the tidal limit to both downstream and upstream directions can be regarded as density-dependent dispersal that mitigates the competition <ns0:ref type='bibr' target='#b14'>(Edeline et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b40'>Kaifu et al., 2010)</ns0:ref>. Homogenous distribution of smaller growth-phase eels around the tidal limit also suggests density-dependent dispersal <ns0:ref type='bibr' target='#b14'>(Edeline et al., 2007)</ns0:ref>. As shown in this study, the growth-phase eels after dispersal and subsequent settlement in habitats exhibit strong sedentary behavior and limited movements <ns0:ref type='bibr' target='#b37'>(Jellyman &amp; Sykes, 2003;</ns0:ref><ns0:ref type='bibr' target='#b58'>Ovidio et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b28'>Itakura et al., 2017)</ns0:ref>. Accordingly, the dispersal-related movements may be one of the key elements to mitigate Manuscript to be reviewed the intra-interspecific competitions during their growth stage.</ns0:p></ns0:div> <ns0:div><ns0:head>Movements of eels</ns0:head><ns0:p>The mean distance travelled of the tagged large A. marmorata was 15.1 &#177; 26.5 m (median = 0 m), which is consistent with previous studies for temperate eels showing that most growth-phase anguillid eels have limited movements <ns0:ref type='bibr'>(Gunning &amp; Shoop, 1962;</ns0:ref><ns0:ref type='bibr' target='#b60'>Parker, 1995;</ns0:ref><ns0:ref type='bibr' target='#b37'>Jellyman &amp; Sykes, 2003;</ns0:ref><ns0:ref type='bibr' target='#b58'>Ovidio et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b28'>Itakura et al., 2017)</ns0:ref>. Half of the eels were recaptured from the original section of capture (i.e., distance travelled &lt; 10 m), suggesting strong fidelity of growthphase A. marmorata to 'familiar' habitats, as mentioned for A. japonica <ns0:ref type='bibr' target='#b28'>(Itakura et al., 2017)</ns0:ref>.</ns0:p><ns0:p>Furthermore, the distance travelled of small eels was greater than that of large eels, which is likely related to the upstream or downstream dispersal behavior after recruitment as discussed above, while large eels show sedentary behavior after they establish a home range <ns0:ref type='bibr' target='#b26'>(Imbert et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b76'>Wakiya, Kaifu &amp; Mochioka, 2016)</ns0:ref>.</ns0:p><ns0:p>Because we performed the sampling during daytime only, the short distance travelled reported here was limited to their movement between daytime refuges. Considering that anguillid eels are generally nocturnal <ns0:ref type='bibr' target='#b60'>(Parker, 1995;</ns0:ref><ns0:ref type='bibr' target='#b37'>Jellyman &amp; Sykes, 2003;</ns0:ref><ns0:ref type='bibr' target='#b58'>Ovidio et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b28'>Itakura et al., 2017)</ns0:ref>, it is likely that growth-phase A. marmorata move longer distances during night than observations in this study have indicated. In addition, the sampling events were conducted only four times over the 2-year study period, which make it difficult to estimate more exact distances travelled of eels or the sizes of their home ranges. Therefore, a mark-recapture experiment with more intensive sampling during both daytime and night or more continuous studies using methods such as biotelemetry are needed to further understand the movement ecology of this species.</ns0:p></ns0:div> <ns0:div><ns0:head>Growth</ns0:head><ns0:p>The direct measurement of individual growth by the mark-recapture experiment revealed that the A. marmorata in this river had a very wide range of annual GR among the 48 recaptured eels that ranged from 0 to 163.2 mm/year, with a mean &#177; SD of 31.8 &#177; 31.0 mm/year. This mean GR value is generally consistent with the otolith-based estimate value (25.9 &#177; 6.6 mm/year) obtained from other rivers on same island <ns0:ref type='bibr'>(Wakiya, Itakura &amp; Kaifu, 2019)</ns0:ref>. This indicates that otolithbased age estimates of this species in the previous study seem to be reasonable and that the otolith analysis method can be useful for the estimating age of A. marmorata. The range of GR from this study was much wider than the otolith-based estimate values (15.8-50.2 mm/year) from <ns0:ref type='bibr'>Wakiya, Itakura &amp; Kaifu, (2019)</ns0:ref>. Surprisingly, some individuals showed no (zero) or very high (&gt;100 mm/year) annual growth. Compared to our results, the mean GR of A. marmorata in an equatorial region (Sulawesi Island Indonesia) was three times higher than that in this study <ns0:ref type='bibr' target='#b21'>(Hagihara et al., 2018b)</ns0:ref>. As discussed by <ns0:ref type='bibr'>Wakiya, Itakura &amp; Kaifu, (2019)</ns0:ref>, the differences in GR of the species among latitudinally different regions may partly be explained the differences in annual water temperatures and productivity in the growth habitats. These results suggest that A. marmorata may accommodate any growth situations including extreme low and high growth conditions in response to a variety of environments. This diverse growth pattern of the species might allow eels to adapt to various habitats in continental waters in latitudinally expanded distributional regions from the equator to higher latitude regions such as southern Japan <ns0:ref type='bibr' target='#b52'>(Mizuno &amp; Nagasawa, 2010)</ns0:ref>.</ns0:p><ns0:p>In our study that extended across 2 years, there might have been seasonal and interannual differences in temperature and food availability that could have affected the GR of eels during each marked and recapture period that were of various durations, although study period was not selected by the best model. Temperature is one of the main seasonal and interannual effects on eel growth <ns0:ref type='bibr' target='#b11'>(Daverat et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b81'>Yokouchi &amp; Daverat, 2013)</ns0:ref>, but this may typically also be linked to seasonal cycles of prey availability. Eels that were caught in July 2017 and recaptured in September 2018 would have experienced an entire seasonal cycle in the river, and they had the highest GR among eels in this study. Conversely, eels that were caught in August 2016 and recaptured in November 2016 only experienced three months that did not include the spring season, and those eels had the lowest median GR and the highest range of GR values. Further research is required to examine the seasonal differences of growth of A. marmorata by conducting a mark-recapture experiment with seasonal intervals.</ns0:p><ns0:p>Another potential reason to explain the difference in GR of eels among the study periods is possible seasonal differences in food availability for the eels. Although we did not document the seasonal patterns of their species composition and abundance, a total of 33 diadromous fish and crustacean species was found in the study river during the sampling surveys, which are likely potential prey species for eels. In other rivers of the study island, the biomass of these fish and crustacean species accounted for more than 80% of stomach contents of A. marmorata <ns0:ref type='bibr'>(Wakiya et al., unpublished data)</ns0:ref>. These diadromous species can have seasonal patterns of recruitment into rivers with their own phenology <ns0:ref type='bibr' target='#b67'>(Tanaka et al., 2020)</ns0:ref>, so their recruitment dynamics might lead to seasonal and interannual differences in food availability in the river, which could affect the GR of eels. A greater diversity of fish and crustacean species and higher overall abundance appeared to be present in the lower river reaches below about 320 m from the river mouth (Table <ns0:ref type='table'>S1</ns0:ref>), which might be one reason why few eels were found in the more narrow upper reaches that likely have a lower carrying capacity for eels.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Our study is the first to provide information about several aspects of the riverine ecology of the spatial distribution, growth, and movement of the tropical eel A. marmorata in relation to environmental conditions, because we conducted a mark-recapture experiment across 2 years throughout the main reaches of the Oganeku River on Amami-Oshima Island, Japan, where it was the highly dominant anguillid species compared to small numbers of Japanese eels. This ecological information about A. marmorata in a small subtropical island river can be compared to future studies in different regions and will contribute to conservation and management efforts for anguillid eels in the Indo-Pacific. Manuscript to be reviewed ) was collected at boulder riverbank habitat in the section 60 m from the river mouth. Eels burrowed in boulder and vegetated riverbanks in the photos with some eels also burrowing in gaps in concrete riverbank. Moreover, large eels appeared to burrow under boulder or rocks, while small eels seemed to burrow in gravel. sections from the river mouth. The greatest number of large eels (n = 19) was collected at boulder riverbank habitat in the section 60 m from the river mouth. Eels burrowed in boulder and vegetated riverbanks in the photos with some eels also burrowing in gaps in concrete riverbank. Moreover, large eels appeared to burrow under boulder or rocks, while small eels seemed to burrow in gravel.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>46.5 &#177; 72.5 m (median = 20 m; n = 31). The distance travelled of recaptured large eels (TL &#8805; 240 PeerJ reviewing PDF | (2020:05:49339:1:2:NEW 10 Sep 2020) Manuscript to be reviewed mm) ranged from 0 m to 120 m with a mean &#177; SD of 15.1 &#177; 26.5 m (median = 0 m; n = 45), while that of small eels (TL&lt;240 mm) ranged from 0 m to 380 m with a mean &#177; SD of 63.3 &#177; 110.8 m (median = 20 m; n = 12).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49339:1:2:NEW 10 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49339:1:2:NEW 10 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure caption Figure 1</ns0:head><ns0:label>caption1</ns0:label><ns0:figDesc>Figure captionFigure1Locations of Amami-Oshima Island, Japan and the Oganeku River. The study on giant mottled eels Anguilla marmorata was conducted during 4 sampling periods throughout the entire river drainage.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 Photographs of representative study sections of the Oganeku River. (A) 50 m, (B) 60 m, (C) 130 m, (D) 170 m, (E) 230 m, (F) 290 m, (G) 310 m, (H) 440 m sections from the river mouth. The greatest number of large eels (n = 19) was collected at boulder riverbank habitat in the</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3 Total lengths (TL) frequency histogram of A. marmorata eels collected in the Oganeku River. TL of A. marmorata was separated into the 2 general size groups of large and small eels.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4 Distributions of (A) sediment, (B) riverbank types, and (C) individual Total lengths (TL) of A. marmorata eels in relation to distance from the river mouth in the Oganeku River. The line and shaded area in the right panel indicate the predictive value and 95% intervals of the generalized additive model, respectively. The open circles in the right panel show the capture locations and sizes of the 7 Japanese eels, A. japonica, that were captured during the surveys. TL of A. marmorata was separated into the 2 general size groups of large and small eels.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5 Relative importance scores of all predictor variables for density of A. marmorata in the Oganeku River. The blue and grey bars indicate finally selected or not selected by the random forest models as a significant importance variable, respectively.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6 Modelled relationships of selected predictor variables by the random forest models for density of A. marmorata in the Oganeku River. (A) Distance from the river mouth, (B) Riverbank type, (C) Depth (small eels), (D) Velocity (small eels). C, concrete.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 7</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7 Density of A. marmorata for each environmental variable in the Oganeku River. (A) Depth, (B) Velocity, (C) Sediment type, and (D) Riverbank type. In the boxplots, the middle lines indicate the median, the boxes represent the 0.25 and 0.75 quartiles, the whiskers are the values that are within 1.5 of the interquartile range, and the dots show outliers.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8 Movement and growth patterns of recaptured A. marmorata in the Oganeku River. (A) Capture and recapture locations during each sampling survey connected by lines for each eel. (B) Histogram of distance travelled of the recaptured eels. (C) Histogram of the annual growth rates of the eels.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='34,42.52,224.62,525.00,437.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='37,42.52,250.12,525.00,375.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='42,42.52,255.37,525.00,434.25' type='bitmap' /></ns0:figure> </ns0:body> "

"Response to reviewer’s comments: Editor’s comments: ●The reviewers have identified a number of issues that need to be addressed. Please indicate how you have addressed each reviewer comment in your reply. In addition to their comments, please consider how your statistical model confounds ‘distance from river mouth’ and environmental variables and whether there is an approach that could identify independent effects. >>Thank you for your review and helpful comments. We have revised the manuscript carefully to address you and reviewer’s concerns. Please see below for our responses to reviewer’s specific comments. Some specific comments follow: ●Line 131. Replace ‘throughout each river’ as ‘throughout the river network’ >> This was revised (L135). ●Line 142. Replace ‘have’ with ‘has’ >> This was revised (L146). ●Line 170. Replace ‘greatly changed’ to ‘transitioned’ >> This was revised (L174). ●Line 171. Delete ‘having a’ >> This was deleted (L175). ●Line 196. Replace ‘wooded’ with ‘wooden’ >> This was revised (L205). ●Line 314 and elsewhere. Avoid use of ‘respectively’. Reword to put number of individuals in parentheses after each year. Makes less work for the reader. >> This was revised here and elsewhere as possible (L 325–326 and elsewhere). ●Line 382. Delete ‘that’ >> This was deleted (L403). ●Line 389. Replace ‘regarded’ with ‘observed’ >> This was revised (L410). ●Lines 406-408. Sentence is not necessary. Consider deleting. >> We think that this information is important to tell readers the size characteristics of recapture eels. So, we retained this, but it was moved to the first paragraph of the result session (L337–339), Thanks. ●Lines 405-423. This paragraph uses many words to describe activities of a few eels. Consider condensing to key points. >> The sentences for the few eels have been moved to the caption of Fig. S3 (Supplemental materials)(L430). ●Line 427. To what extent is distance from the river mouth confounded with habitat variables? >> The purpose of the analyses of this study was to identify the relative importance of each variable, and the model used in this study can assess the relative importance between continuous and categorical variables, even if there were strong correlations among variables. Therefore, we think that we were able to fairly evaluate the relative importance of distance from the river mouth as well as other variables. Actually, since there is no strong correlations among continuous variables (the distance from the river mouth, depth, velocity) used in this study (coefficient of correlation < 0.5 and VIF <6; please see Fig. S1), these variables are not strongly confounded by each other at least. Perhaps, distributions of sediment and riverbank types (categorical variables) may relate to the distance from the river mouth (please see Fig. 4). For this, please see our response 1 as well. ●Line 438. Seemed like concrete was very important. Refer to previous comment. >> You are correct, concrete seems very important for eel distribution. Although this has been already mentioned in the fourth paragraph of the discussion, we have revised some sentences to emphasize that more as follows: “Thus, it is obvious that concrete does not provide suitable habitat for eels or their prey species because it is not possible to find shelter in concrete unless it is highly fractured, which may lead to the somewhat patchy distribution observed in this study.” (L500–503). ●Line 450. Similar issue as previous two comments. Need a statistical method that does not confound environmental variables with distance to river mouth. Consider separate analyses for distance to river mouth and the habitat variables. >>Response 1: Thank you for your thoughtful comment. You are correct, if our object was to test the effects of habitat variables on eel density without effects of distance from the river mouth, we may have to analyze by separating the effects of these factors. However, the purpose of the analyses of this study was to identify the relative importance of each variable (i.e., identify the most important variable) to explain the eel density. If we analyze the distance from the river mouth and other variables separately, it is difficult to evaluate the relative importance of each variable. Therefore, given both reviewers did not point out this as well, we think that the current analysis is not problematic for achieving the purpose of this study. As a result, the distance from the river mouth was selected by the model as the most important variable to explain eel density. Many previous studies have reported that eels recruit from the sea to the tidal limit areas of rivers and then disperse in both downstream and upstream directions, and thus the eel density in rivers is strongly related with the distance from the river mouth. Hence, the result of this study seems very reasonable. In contrast, as you mentioned (and we did in the discussion as well), this strong effect of the distance from the river mouth on eel density could mask effects of other factors. This is not big issue for the objective of this study, but now we have discussed about this more carefully and added the statement for a further work. In addition, we have moved a figure showing distributions of sediment, riverbank, and individual total length of eels in relation to distance from the river mouth, from the supplemental information to the main manuscript following reviewer1’s comment in order to make readers clearly understand their distribution-relationships. Hope this analysis is now more clear. In the discussion, we have revised a sentence to emphasize the effect of distance as follows: “Therefore, the distance from the river mouth is likely one of the most common and important factors that determine the riverine distributions anguillid eel species.” (L444–446), and sentences to mention about relationship between distance and other microhabitat variables as follows: “The distribution of small A. marmorata was biased toward habitats that consisted of gravel sediment, possibly because all tidal limit areas in the study river where almost all small eels were collected consisted of the gravel sediment. The grain size of gravel as a refuge seems better for small eels than others, and so the riffle or run habitats with gravel may provide suitable refuges and feeding area for small eels. Conversely, such riffle and run habitats with gravel were also present in the upper reaches of the river, but the distribution of small eels was biased toward the lower reaches, suggesting that they prefer such habitats in the lower reaches. Because sediment was not selected by the RF models as an important variable, these results imply that the effect of sediment was masked by the strong effect of distance from the river mouth. As shown by this study and previous studies, the distance from the river mouth strongly contributes to determine eel density, which may mask microhabitat effects, especially when the survey was only conducted in a river that includes one pattern of distribution of habitat variables in relation to the distance from the river mouth. Therefore, further surveys in multiple rivers that have diverse distribution patterns of habitat variables are required to clarify microhabitat effects on eel distribution without the effect of the distance from the river mouth.” (L457–472). ●Lines 480-489. This part is especially confusing. Consider rewriting to simplify. >> This was revised as follows: “Thus, it is obvious that concrete does not provide suitable habitat for eels or their prey species because it is not possible to find shelter in concrete unless it is highly fractured, which may lead to the somewhat patchy distribution observed in this study. However, the density of eels was higher in sections that the riverbank consisted of concrete with boulders, vegetation, and gravel compared to that of concrete only. These combinations between concrete and the other materials made the density of eels almost identical to that in habitat consisting of vegetation. In addition, with regard to the combination between riverbank and sediment types, some eels were caught in the 110 and 120 m sections where the riverbank consisted of concrete with other types of sediments, while only one eel was caught in 320–350 m sections where both riverbank and sediment consisted of concrete. These results suggest that the combination-habitats of concrete and other materials may provide enough refuges for eels to inhabit the river at the current density levels.” (L 500–512). ●Lines 550-560. This paragraph adds little to the discussion. Consider deleting. >> Now we have added one paragraph that discussed about eel movements following both reviewer’s comments. Hence, we retained this paragraph so that we compared the contents of this paragraph with contents of the new paragraph that was added (L598–607). Please see our responses 7 and 10. ●Line 568. Replace ‘seems with ‘seem’ >> This was revised (L615). ●Lines 582-591. Need to break growth rate estimates into seasonal components. >> It is difficult to break growth rate estimations into seasonal components, because the sampling was not conducted seasonally in this study. Therefore, we have added some words about possible future research on this in the discussion, following reviewer2’s comment (L712–724). Please see our response 9. ●Conclusion. This adds little new information. Consider deleting. >> Our understanding is that a conclusion section is necessary. So we retained this part, but we tried to substantially condense the section, as follows: “Our study is the first to provide information about several aspects of the riverine ecology of the spatial distribution, growth, and movement of the tropical eel A. marmorata in relation to environmental conditions, because we conducted a mark-recapture experiment across 2 years throughout the main reaches of the Oganeku River on Amami-Oshima Island, Japan, where it was the highly dominant anguillid species compared to small numbers of Japanese eels. This ecological information about A. marmorata in a small subtropical island river can be compared to future studies in different regions and will contribute to conservation and management efforts for anguillid eels in the Indo-Pacific.” (L656–663). Reviewer 1 Basic reporting This paper describes a 2-year mark-recapture study of juvenile and subadult Anguilla marmorata in a relatively small stream in southern Japan. The focus of the work is on distribution, preferred habitat, home range, and age and growth. The findings add to a growing body of ecological knowledge for this and other tropical species of Anguilla, which up to now have been little studied. ●The manuscript is relatively well researched and draws on an extensive list of references. Most references are more recent (post-2000); some older but relevant references on other species of Anguilla might be included, e.g. Gunning and Shoop 1962, Haro & Krueger 1991 (see citations in General Comments). The text contains few technical, grammatical, and stylistic errors, and I have relatively few comments/edits. The authors sufficiently review recent research with this and other subtropical Anguilla species. To my knowledge this research has not been published elsewhere. >>We would like to thank you for your review, with positive, constructive, and helpful advice. Please see our responses to your specific comments below. In addition, you can find the references that we cited here in the end of the letter. Experimental design The experimental design follows that for a standard mark-recapture study. Tag retention and fish catchability are not quantified, but the tagging methods have been used with juvenile Anguilla before and are probably appropriate. Some of the statistics employed are new to me (e.g. random forest models) but seem appropriate given limitations on sample size, non-normality of data, etc. The authors do a good job of justifying the specific analyses used. ●Catchability of eels using backpack electrofishing may be influenced by habitat (i.e., it is generally harder to detect and catch small eels in deep runs or areas with cover with electrofishing), which may have affected results somewhat (i.e., fewer small eels collected in deeper areas). However, there are no data to evaluate this potential effect. The recapture rate of eels in this small system, which seems to be easily comprehensively sampled, is quite small (48 of 339 fish = 14% recap rate; line 322). This might imply somewhat limited catchability using the electrofishing technique. Can the authors speak to this? >>Response 2: You are correct, there is a possibility that catchability of eels using electrofishing may be different between deep and shallow areas, and we did not evaluate this. Therefore, we have added a sentence in the discussion as follows: “Small A. marmorata, therefore, seem to prefer shallow and fast-velocity waters (i.e., riffle or run, usually gravel or rocky sediments) rather than deep and slow-velocity areas (i.e., pools), although it should be noted that it is likely more difficult to collect small eels using electrofishing in deep areas than shallow areas, which could partly cause the difference of catchability between these areas.” (L453–457). One potential reason to explain the observed low recapture rate of eels is that the environments of rivers in this small island have a higher level of habitat naturalness due to lower levels of habitat degradation, compared to other more developed regions like the mainland of Japan. There are a lot of diverse natural habitats in the study river, which provide refuges with structural complexity for eels. This can make it harder to recapture eels here than habitats where the structural complexity has been lost, because of river developments. Even though 15% of the recapture rate (38 of 252 fish) was observed for Japanese eels during past research (Yokouchi 2010) that conducted electrofishing monthly during 3 years in a small river (3 km) in the mainland of Japan, we can suggest the value (14%) observed here is not so low for mark and recapture studies on fishes. Validity of the findings ●The study was performed in a lower portion of a relatively small river system only 500 m long; how representative as a general habitat is this for this species? I would imagine larger/longer river systems might have different size/age distribution characteristics. Can the authors make any comparisons between this and other riverine habitats for this species? >>Response 3: We believe this study was performed in almost all mainstem areas of the study river. The distance above the waterfall in the river is unknow because (1) we cannot access to areas above the waterfall, and (2) we can see on maps if the river ends around the waterfall. Still, given that the river width at around the waterfall is much narrower (<1 m), it is unlikely that the river extends very far above the waterfall, and that abundant eels are present there, indicating that it is likely reasonable that the end of the study river is regarded as around the waterfall. Therefore, the sampling was able to be performed at diverse environments in almost all reaches of the study river that included lower to upper reach riverscapes. Indeed, we collected eels of a wide-range of total length (mean ± SD: 336.8 ± 153.0 mm; range: 62–770 mm), which did not differ greatly with eels caught in other rivers in same island (mean ± SD: 385.5 ± 172.6 mm; range: 119–1320 mm)(Wakiya et al. 2019), although larger eels >80 cm were absent (see our response 4 for reason). Therefore, we can deem the study river is quite small, but is not a specific habitat for this species. We have added the following sentences in the “Study area and sampling” in the M&M: “Because the river width around the waterfall is much narrower (<1m), the river flow may originate not far above the waterfall. Thus, our surveyed area was considered to cover almost all of the mainstem of the river.” (L178–180). ●Eel density ranged from 0 to almost 0.7 eels/m2. How does this compare to other studies of density of tropical and temperate eels? >> Density of A. marmorata observed in the study river (0.15 ± 0.13 eels m-2 with a range of 0.01– 0.69 eels m-2) is much higher than recent observations for the species in other rivers on same island (0.03 ± 0.03 eels m-2 with a range of 0.004–0.16 eels m-2) and for A. japonica in rivers in the mainland Japan (0.03 ± 0.04 eels m-2 with a range of 0.004–0.25 eels m-2)(Itakura et al. 2020). This difference could be explained by differences of recruitment, and numbers of predators or competitors for eels. Because it is challenging to directly compare eel densities between the study river and others due to different river scales or different species, we did not discuss that in the manuscript. ●My understanding is that adults of this species can grow to a very large size (2+ m total length), but few eels over 600 mm TL were collected. Why were larger/older eels absent from the system? Could the stream size have been too small to support them, or do larger eels prefer other habitat types (e.g., larger rivers)? >>Response 4: A previous study for this species in Indonesian waters showed that larger eels over 1 m are females only (Hagihara et at 2018). On the other hand, males are dominant in other rivers of the study island and thus larger female eels >80 cm in total length were rarely collected (Wakiya et al. 2019). Although sex was not identified in this study, the majority of eels caught in the study river was likely males. Because males start their spawning migration at < 80 cm, such large eels can be absent in the study river. The potential reason why few larger (female) eels > 80 cm were collected in other rivers by Wakiya et al. (2019), but were absent in the study river was that there was few deep pool waters that would be preferred by larger eels, while the rivers in Wakiya et al. (2019) have deeper waters due to their larger river scale. We have added one paragraph about this in the discussion as follows: “The TL of A. marmorata observed in the study river (336.8 ± 153.0 mm with a range of 62–770 mm) did not clearly differ with that in other rivers on the same island (385.5 ± 172.6 mm with a range of 119–1320 mm; Wakiya, Itakura & Kaifu, 2019); however, larger eels >800 mm in TL were absent in this study. It is well known that A. marmorata can frequently grow up to over a meter, but such larger eels are females only (Hagihara et al., 2018b). Wakiya, Itakura & Kaifu, (2019) reported that males are dominant in other rivers in same island and there were very few larger female eels >800 mm. Although sex was not identified in this study, the majority of eels caught in the study river seems to be males that can start the spawning migration at < 800 mm in TL, which may explain the absence of larger eels (females) there. The absence of the larger eels in the study river might be explained by the lack of much deeper pool waters that are preferred by larger eels, while rivers in Wakiya, Itakura & Kaifu, (2019) have such deeper waters due to their larger river scale than the study river.” (L521–532). ●The authors mention the potential for competition and habitat segregation of sizes in this river system (lines 436, 528). Is there any additional evidence for this? Are mottled eels the dominant fish species (in terms of number or biomass) in this system? If so, one might also look for evidence of cannibalism (which is common in Anguilla); the authors note that no glass eels and very few very small eels were collected throughout the 2 years of study.  >> Response 5: The cannibalism by eels may occur in the river despite a lack of evidence. However, we don’t think this cannibalism is the main reason to explain no glass eels and few smaller eels being caught in this study, because (1) if larger eels intensively and continuously feed on glass eels, there should be few larger eels as well, (2) although the giant mottled eels are dominate fish species in terms of both abundance and biomass in the river, we can see vast numbers of crustaceans (genes Macrobrachium) in the river, which would be sufficient prey items for eels. It is difficult to collect glass eels by electrofishing, which may partially explain the result. However, we don’t think we were not able to collect abundant eels >62 mm. Therefore, we have revised sentences as follows: “No glass eels and few smaller eels of A. marmorata were collected in this study, partly because it is difficult to capture them using electrofishing. Nevertheless, we collected small eels less than 100 mm TL with the smallest individual being 62 mm TL,..” (L546–548), and “The mortality of eels in freshwater may primarily be related to density-dependent factors such as intraspecific competition for resources or predation by eels…” (L575–577). ●Along these same lines, in temperate eels large runs of glass eels usually invade streams in the spring months and attempt to migrate as a far upstream as possible in their first year. If this is the case for mottled eels, one might expect large concentrations of glass eels accumulating below the waterfall 520 m from the river mouth (albeit perhaps during a very limited period of the year). Can small eels ascend this waterfall? If so, is there suitable habitat above the waterfall? If they cannot ascend, could they be consumed by larger eels or other predators? The authors make the claim that juvenile eels enter the river and establish themselves primarily in the riffle region 100-300 m above the river mouth but have no direct evidence of this. Because they were rarely observed, alternative routes and/or fates of glass eels entering from the ocean into this small stream should also be acknowledged. >> Although we think that eels have the ability to ascend this waterfall, there could be not enough suitable habitats above the waterfall as mentioned in response 3. According to a previous study performed on an island near the study river island, the recruitment of this species occurs from spring to fall with a peak in May and June (Yamamoto et al., 2001). So it is thought that large runs of glass eels in the study river may occur during summer to fall, which can be consistent with the study period. If so, we should find out glass eels and the subsequent smaller eels (i.e., large runs) at around areas below the waterfall, but we actually did not. Conversely, smaller eels (<100 mm) were only found at around the sections 100–200 m from the river mouth. This indirect evidence suggests that glass eels settle in around the sections 100–200 m rather than at around areas below the waterfall. For your perspective about the predation on glass eels by larger one, please see our response 5, thanks. Comments for the author ●Title: capitalize “island” if Amami-Oshima is indeed a specific named island >> This was revised (L4). ●Line 38: change “main reaches” to “mainstem reach” >> This was revised (L38). ●Line 57: change “is” to “was” >> This was revised (L59). ●Line 86: change “most species have not been studied for their freshwater ecology” to 'their freshwater ecology has not been studied' >> This was revised (L88). ●Line 131: “…A. marmorata is highly dominant…” - does this mean dominant among other Anguilla species or among other fishes in general? >> This means “among other Anguilla species”. We have revised here and elsewhere as follows: “A. marmorata is highly dominant among anguillid species” (L134). ●Line 160: provide latitude and longitude of study site >> This was added (L164). ●Line 169: sentence not clear; reword >> We have revised as follows: “The elevation of the river increases dramatically to >10 m from around the 320 m area from the river mouth where the riverscape transitioned to higher-gradient upstream environments.” (L173–175). ●Line 171: state (if known) whether the waterfall is passable by eels >> We think that some A. marmorata might be able to climb the waterfall, given that it’s been reported that the species were collected in waters above waterfalls with 12 and 30 m heights or above a 25 m dam in another river on the same island (Wakiya et al.,2019; Itakura et al.,2020). We have revised sentences as follows: “There is a waterfall >10 m height at 520 m from the river mouth (elevation = 50 m). Although some eels might be able to climb the waterfall, we surveyed…” (L175–176). ●Line 173: omit “to” >> This was omitted (L177). ●Line 173: how long is the total length of the mainstem, including the portion above the waterfall? >> Actually, this is unknown, but “approximately 0.5 km” seems correct. Please see our response 3 as well (L172). ●Line 179: change “was” to “were” >> This was revised (L186). ●Line 183: “entire river” – there was no sampling above the waterfall; reword >> Please see our response 3. This was revised here and elsewhere as follows: “all the main reaches of a river” (L191). ●Line 190: “uppermost reaches - there was no sampling above the waterfall; reword >> This was revised as follows: “We captured anguillid eels over almost the entire area of the river from the river mouth to the uppermost reaches of the river (below the waterfall) using…” (198–200). ●Line 192: omit 'of every sampling time' >> This was omitted (L201). ●Line 201: Few A. japonica were collected; does this imply habitat segregation of the two species? A. japonica is infrequently mentioned in the Discussion; habitat segregation (or not) of the two species could be discussed more there. >>Response 6: Yes, A. marmorata was found throughout the study river, while A. japonica was found only at the lower reaches of the river, possibly suggesting their habitat segregation, as previously reported. However, little evidence of habitat segregation was obtained by this study, and this is not the main focus of this study. Thus, we think that it is better that we don’t discuss about this here. Instead, we have moved a supplemental figure including distribution of A. japonica to the main manuscript following your suggestion (see our response 8). We hope this data will be useful for understanding of their habitat segregation in future studies. ●Line 233: change “detected” to “quantified” >> This was changed (L244). ●Line 367: change “was” to “were” >> This was changed (L387). ●Line 396: I assume the remaining sentences in this paragraph refer to the three eels that made the longest movements. >> The sentences for the three eels has been moved to the caption of Fig. S3 (Supplemental materials)(L414). ●Line 401: omit comma >> The sentences including the comma has been moved to the caption of Fig. S3 following your comment (L414). ●Discussion: The Discussion section is rather long, but still interesting. The authors speculate a bit, but perhaps are warranted in this given how little is known for this species. Editor’s call. >> Thank you so much. ●Line 467: change “range” to “range of” >> This was revised (L486). ●Line 551: A home range of 15.1 +/- 26.5 m is pretty small. The collections were made during daytime only, perhaps collecting eels only while in they were in their daytime refuges, which they may have had some fidelity to. Movements a night (e.g. ranging much farther from a daytime refuge) may be much more extensive; the authors should acknowledge this. >>Response 7: You are correct, so we have discussed this possibility. Moreover, now the phrase “home range” has not been used and it’s been replaced with “distance travelled” or “movement” throughout the manuscript, following reviewer 2’s comment. Please see our response 10 as well. We have added one paragraph as follows: “Because we performed the sampling during daytime only, the short distance travelled reported here was limited to their movement between daytime refuges. Considering that anguillid eels are generally nocturnal (Parker, 1995; Jellyman & Sykes, 2003; Ovidio et al., 2013; Walker et al., 2014; Itakura et al., 2017), it is likely that growth-phase A. marmorata move longer distances during night than observations in this study have indicated. In addition, the sampling events were conducted only four times over the 2-year study period, which make it difficult to estimate more exact distances travelled of eels or the sizes of their home ranges. Therefore, a mark-recapture experiment with more intensive sampling during both daytime and night or more continuous studies using methods such as biotelemetry are needed to further understand the movement ecology of this species.” (L598–607). ●Fig. 5; why are no large eel results shown in Figs. 6C and 6D? >> Because the depth (Fig. 6C) and velocity (Fig. 6D) were not selected by the random forest model for large eels as an important explanatory variable to predict density of large eels, they were not shown for large eels. The large eel results have been shown in Figs. 7C & 7D. ●Figures: In the interest of visualizing the data, it would be nice to include in the main manuscript a figure for density vs. distance, for both small and large eels, perhaps also showing sediment and bank type (i.e., Fig. S2). I would suggest breaking up Fig 3 and retain Fig.3A as a stand-alone figure, then add a new figure that emulates Fig. S2, adding the predictive value and 95% CI to the rightmost panel of S2. The open circles for A. japonica can be omitted. >>Response 8: Thank you for your suggestion. We have added the previous Fig. S2 as Fig. 4 in the main manuscript. We did not omit the plotted points for A. japonica, because we feel that the data for A. japonica will be useful for the understanding of habitat segregation of these two eel species in the future. Please see our response 6 as well. ●Suggested references: Gunning, G. E., and C. R. Shoop. 1962. Restricted movements of the American Eel, Anguilla rostrata (LeSueur) in freshwater streams, with comments on growth rate. Tulane Studies in Zoology 9:265-272. Haro, A. J., and W. H. Krueger. 1991. Pigmentation, otolith rings, and upstream migration of juvenile American Eels (Anguilla rostrata) in a coastal Rhode Island stream. Canadian Journal of Zoology 69:812-814. >> Thanks. Both references were cited in the manuscript (L106, 111, 556, 590). Reviewer 2 Basic reporting ●The manuscript is readable, and the study appears to be conducted by experts on the subject matter. >>We would like to thank you for your review and helpful advice. Please see below for our responses to your specific comments. Experimental design Methods are well described and statistical analyses appropriate. I have several major issues with the Methods section. ●(1) Growth: Given the irregular sampling intervals that range 3-14 months, it is challenging to interpret growth rate data. Authors wisely acknowledge the issue on line 582-591, and relegate data to Appendix Figure S5. On Figure S5, it seems growth rates appear to be higher when intervals contain spring, which I suspect may be the season with the highest growth rate. This is a major, if not fatal, shortcoming, which at this point is hard to offer a constructive suggestion. >>Response 9: You are correct. It is challenging to interpret the growth rate of eels based on the present data. We have added some words and mentioned future research perspectives as follows: “Conversely, eels that were caught in August 2016 and recaptured in November 2016 only experienced three months that did not include the spring season, and those eels had the lowest median GR and the highest range of GR values. Further research is required to examine the seasonal differences of growth of A. marmorata by conducting a mark-recapture experiment with seasonal intervals.” (L636–640). ●(2) Home range: I don't think that this phrase is used appropriately in this manuscript, as estimating home range requires location data at finer temporal scales (i.e., kernel density estimates). The phrase in fact is not defined clearly in the manuscript, but it is referred to as 'long-term linear home rage', which I take to mean cumulative distances for individuals recaptured more than once. Four recapture events over > 2 years are not simply sufficient for home range estimation, and I advise that authors refrain from using this phrase throughout. >>Response 10: Thank you for your suggestion. Following your suggestion, the phrase “long-term linear home range” has been replaced with “distance travelled” or “movement” throughout manuscript. In addition, we have added one paragraph to the discussion following your and another reviewer’s comments. Please see our response 7. ●(3) Movement: Authors conclude that movement is limited because 47.9% were recaptured in the same 10m section, but I wonder if the short study area (450m) provides a classic example of missing emigration from the area. The finding that smaller individuals traveled longer distances than larger individuals (Line 384-385) could just a symptom of the issue, where larger, mature individuals moved to the ocean. This would result in detecting only those that stayed in the study area (underestimating long-range movement). This potential criticism is further substantiated by the fact only 48 out of 396 individuals were recaptured, although it is possible that low recapture rates are due to other factors such as morality and detection rates by electrofishing. I suggest that authors discuss the potential impacts of the study design on underestimating movement, and even better, demonstrating why this would not be an issue in this study. >> This is a good point. It is known that some individuals of temperate eels utilize habitats out of rivers, but little is known for tropical eels. Generally, the area out of the river is beach (sand), which may be not suitable habitat for large eels. In order to examine if target eel species utilize the sea area out of the study river, we conducted environmental DNA (eDNA) based survey at two sea stations out of the river (10 m and 50 m distances from the river mouth; Itakura at al. unpublished) and all study sections within the river (Itakura et al. 2020). Results showed that mean eDNA concentration of eels at river stations was 883.974 copies/L, while eel eDNA concentration at the sea stations of 10 m and 50 m distances from the river mouth were 17.442 and 5.516 copies/L, respectively. This suggests that large portion of eels don’t inhabit the sea area. Therefore, eels in this river system are thought to basically utilize the river only. We believe that our recapture rate is not exceptionally low (please see our response 2). ●(4) Electrofishing: I wonder whether electrofishing was effective at capturing animals that burrow into substrates in brackish waters. I have a mixed experience with electrofishing when water conductivity is high, and species like juvenile eels and lamprey ammocetes appear quite elusive. It is particularly problematic when electrofishing capture probability varies by habitat. For example, on Figure 6(A), eel density decreases with depth. Is this because eels are harder to catch at deeper habitats? I suggest authors demonstrate that electrofishing capture probability is not habitat dependent (ideally) or at least report the range of conductivity along the study river. >> Electrofishing was performed during low tides at sampling sections below freshwater tidal limit of the river. At that time, we confirmed that all sampling sections were freshwater. For depth, please see our response 2. We have added sentences as follows: “Sampling was performed during low tides at sections below the freshwater tidal limit of the river in order to avoid the effect of salinity on the efficiency of electrofishing. As a result, we confirmed the sections were freshwater during low tides.” (L205–208). Validity of the findings ●The key take-home message of this manuscript is: 'Given the long life, slow growth, strong site fidelity, and size-dependent habitat preference of A. mamorate, the long-term maintenance of diverse natural riverine habitats are important to conserve this eel species (Line 64-66).' This blanket statement (sounds like a cliche) is likely right, but when examining data presented in the paper carefully, I wonder if the statement is sufficiently back up by data. - long life: true, but not a focus in this paper (no data presented). - slow growth: yes, there were a couple of individuals that did not grow at all for months, but there were others that grew much faster. What is striking seems growth variation among individuals, not necessarily slow growth. - strong site fidelity: this is questionable (see Comment 3 above) - size-dependent habitat preference: Given that large eels were habitat generalists, this applies more to small eels that occupied riffles/runs.  I wonder whether an alternative take-home message, supported more strongly by data in this paper, would be appropriate. For example, authors emphasize many similarities of the giant mottled eel to better-studied temperate eels. Would you be able to say that many conservation strategies that apply to temperate eels apply similarly to tropical eels, etc? >> Thank you for your suggestion. We have omitted this sentence and added another one to the end of abstract as follows: “This is the first clear detailed documentation of the spatial distribution, growth, and movements of tropical eels in a small river system in relation to environmental conditions that provides an example of how future studies can be conducted in other areas to understand how conservation efforts can be most efficiently targeted for maximum success.” (L64–68). Comments for the author A few other, more minor comments: ●- line 211: The total sample reported in Abstract (line 41) and Results (line 312) is 396 individuals. But here, 228 PIT tagged individuals + 105 VIE tagged individuals = 333 individuals? >> Sorry for the confusion. The 396 eels includes recaptured eels. In the results session, we have revised a sentence as follows: “A total of 396 growth-phase A. marmorata were collected in this study (this includes number of recaptured eels).” (L324–325). ●- line 219: Was there only a single measurement of depth and velocity per 10m section? This should have been taken at 3 or so points across multiple transects per section. At the least, you are measuring meso-habitat characteristics, instead of micro-habitat characteristics, because you cannot exactly know where eels were within a 10m section.  >> Yes, there was a single measurement per 10 m section. However, given the eel’s distance travelled and home range over several ten meters, our measurement can reflect their micro-habitat characteristics, rather than meso-habitat characteristics. ●- line 408-412: It is challenging to discern in this study (and many others) whether individuals that moved ended up growing faster, or faster growing individuals decided to move to different locations. >> You are correct. We acknowledged this, and added a sentence as follows: “…, both categories of eels that moved had significantly higher GR than the eels that did not move (Fig. S3B); although it is still unclear whether eels that moved ended up growing faster or faster growing individuals decided to move more.” (L421–424). Reference Yokouchi, K., 2010. Studies on phenotypic plasticity in catadromous life-histories of Japanese eel in the Hamana Lake system, Japan. Ph.D. thesis, The University of Tokyo, Tokyo. Wakiya R, Itakura H, Kaifu K. 2019. Age, growth, and sex ratios of the giant mottled eel, Anguilla marmorata, in freshwater habitats near its northern geographic limit: a comparison to tropical regions. Zoological Studies 58:34. DOI: 10.6620/ZS.2019.58-34. Itakura H, Wakiya R, Gollock M, Kaifu K. 2020. Anguillid eels as a surrogate species for conservation of freshwater biodiversity in Japan. Scientific reports. DOI: 10.1038/s41598-020-65883-4z. Hagihara S, Aoyama J, Limbong D, Tsukamoto K. 2018. Age and growth of migrating tropical eels, Anguilla celebesensis and Anguilla marmorata. Journal of Fish Biology 92:1526–1544. DOI: 10.1111/jfb.13608. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. Dispersal is an important process affecting population dynamics and connectivity. For marine direct developers, both adults and juveniles may disperse.</ns0:p><ns0:p>Although the distribution of juveniles can be initially constrained by their mothers' choice, they may be able to leave the parental habitat and colonize other habitats. We investigated the effect of habitat quality, patch size and presence of conspecific adults on the colonization of novel habitats by juveniles of the tube-dwelling amphipod Cymadusa filosa associated with the macroalgal host Sargassum filipendula. Methods. We tested the factors listed above on the colonization of juveniles by manipulating natural and artificial plants in both the field and laboratory. Results. In the laboratory, juveniles selected highquality habitats (i.e. natural alga), where both food and shelter are provided, when lowquality resources (i.e. artificial alga) were also available. In contrast, habitat quality and algal patch size did not affect the colonization by juveniles in the field. Finally, the presence of conspecific adults did not affect the colonization of juveniles under laboratory condition but had a weak effect in the field experiment. Our results suggest that C. filosa juveniles can select and colonize novel habitats, and that such process can be partially affected by habitat quality, but not by patch size. Also, the presence of conspecifics may affect the colonization by juveniles. Successful colonization by this specific developmental stage under different scenarios indicates that juveniles may act as a dispersal agent in this species.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Dispersal of individuals has important consequences for population dynamics, connectivity <ns0:ref type='bibr' target='#b30'>(Hansson, 1991;</ns0:ref><ns0:ref type='bibr' target='#b61'>Ronce, 2007;</ns0:ref><ns0:ref type='bibr' target='#b80'>White et al., 2019)</ns0:ref> and ecosystem function in aquatic environments <ns0:ref type='bibr' target='#b45'>(Little et al., 2019)</ns0:ref>. This process has been related to ultimate and proximate causes <ns0:ref type='bibr' target='#b5'>(Bowler &amp; Benton, 2005;</ns0:ref><ns0:ref type='bibr' target='#b11'>Burgess et al., 2016)</ns0:ref>, and also depends on organismal traits that often vary among individuals within a population, such as body size, sex, and developmental stage <ns0:ref type='bibr' target='#b39'>(Lawrence, 1987;</ns0:ref><ns0:ref type='bibr' target='#b54'>Munguia et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b53'>Munguia, 2015)</ns0:ref>. A variety of strategies related to dispersal are found among aquatic invertebrates, involving passive and/or active components and allowing the movement of these organisms across short and long distances <ns0:ref type='bibr' target='#b49'>(Martel &amp; Chia, 1991;</ns0:ref><ns0:ref type='bibr' target='#b56'>Palmer et al., 1996;</ns0:ref><ns0:ref type='bibr' target='#b36'>Kinlan &amp; Gaines, 2003;</ns0:ref><ns0:ref type='bibr' target='#b60'>Ptatscheck, 2020)</ns0:ref>. For many sessile and mobile benthic species, planktonic larvae represent the main dispersal stage, often exploiting resources in a habitat different from where adults are established <ns0:ref type='bibr' target='#b51'>(Mileikovsky, 1972;</ns0:ref><ns0:ref type='bibr' target='#b28'>Grantham et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b26'>Gaines et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b78'>Weersing &amp; Toonen, 2009)</ns0:ref>. However, dispersal during other life stages may have important implications for population dynamics <ns0:ref type='bibr'>(D`Aloia et al., 2017)</ns0:ref>, with juveniles and/or adults playing important roles on the dispersal process. For mobile benthic species with direct development (i.e. lacking a larval stage), such as amphipods and isopods, transport movements occur over both short and long distances during the whole lifespan <ns0:ref type='bibr' target='#b76'>(Waage-Nielsen et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b37'>Kumagai, 2006;</ns0:ref><ns0:ref type='bibr' target='#b21'>Davidson et al., 2008)</ns0:ref>. In this case, the spatial distribution of newborn juveniles can be initially constrained by the female's habitat choice <ns0:ref type='bibr' target='#b59'>(Poore &amp; Steinberg, 1999)</ns0:ref>, with individuals of different developmental stages often sharing the same habitat <ns0:ref type='bibr' target='#b73'>(Thiel, 1999;</ns0:ref><ns0:ref type='bibr' target='#b8'>Brooks &amp; Bell, 2001;</ns0:ref><ns0:ref type='bibr' target='#b57'>Poore, 2004;</ns0:ref><ns0:ref type='bibr' target='#b52'>Miranda &amp; Thiel, 2008)</ns0:ref>. The potential dispersal of direct developers may vary with age, with drastic consequences for population dynamics <ns0:ref type='bibr' target='#b54'>(Munguia et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b7'>Bringloe et al., 2013)</ns0:ref>. For some species, adults have an important role on the dispersal process, while juveniles can be the main dispersal stage for other direct developers <ns0:ref type='bibr' target='#b25'>(Franz &amp; Mohamed, 1989;</ns0:ref><ns0:ref type='bibr' target='#b10'>Bueno &amp; Leite, 2019)</ns0:ref>. Even when both developmental stages can disperse, adults and juveniles may be under different pressures to emigrate and colonize new patches <ns0:ref type='bibr' target='#b22'>(DeWitt, 1987;</ns0:ref><ns0:ref type='bibr' target='#b57'>Poore, 2004)</ns0:ref>. For instance, adults may be motivated to disperse in order to find mates to copulate <ns0:ref type='bibr' target='#b7'>(Bringloe et al., 2013)</ns0:ref> whereas distribution and dispersal of juveniles may be strongly affected by intraspecific competitive interactions. The presence of conspecifics in a patch may be indicative of habitat quality, attracting juveniles to settle <ns0:ref type='bibr' target='#b7'>(Bringloe et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b23'>Drolet et al., 2013)</ns0:ref>; alternatively, the highdensity of conspecific adults can inhibit the settlement of juveniles <ns0:ref type='bibr'>(Wilson, 1989;</ns0:ref><ns0:ref type='bibr' target='#b35'>Jensen &amp; Kristensen, 1990)</ns0:ref>. For some tube-dwelling amphipods, large individuals can also be aggressive towards smaller ones <ns0:ref type='bibr' target='#b17'>(Connell, 1963;</ns0:ref><ns0:ref type='bibr' target='#b6'>Brawley &amp; Adey, 1981)</ns0:ref>, probably forcing them to search for new sites <ns0:ref type='bibr' target='#b22'>(DeWitt, 1987)</ns0:ref>. Yet, juveniles and adults of brooding invertebrates may differ in their ability to exploit habitats with different qualities, resulting in distinct patterns of colonization among these developmental stages. For example, juveniles of the herbivorous amphipod Sunamphitoe parmerong (formerly Peramphithoe parmerong) mainly inhabit the high-quality algal food Sargassum linearifolium, while adults are able to occupy that host and also to colonize the poor-quality algal food Padina crassa <ns0:ref type='bibr' target='#b57'>(Poore, 2004)</ns0:ref>. Juveniles of the amphipod Pontogammarus robustoides consistently prefer inhabiting natural macrophytes over artificial ones, while adults do not distinguish among these habitat choices <ns0:ref type='bibr' target='#b19'>(Czarnecka et al., 2010)</ns0:ref>. These examples suggest that the colonization of juveniles may be affected by the habitat quality. Furthermore, large patches can attract more adult amphipods than small ones, while the colonization of juveniles may be unaffected by the patch size, probably because of the small size of these individuals <ns0:ref type='bibr' target='#b10'>(Bueno &amp; Leite, 2019)</ns0:ref>. In this sense, understanding the role of dispersal on the population dynamics and connectivity of direct developers requires investigating the factors driving the colonization of specific developmental stages. Marine macroalgae harbor a diverse fauna in shallow waters <ns0:ref type='bibr' target='#b14'>(Christie et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b27'>Gan et al., 2019)</ns0:ref>. Epifaunal assemblages are maintained through the developmental cycle of their hosts, which provide continuous renewal of the resource (i.e. food and/or shelter), allowing associated populations to thrive <ns0:ref type='bibr' target='#b66'>(Seed &amp; O'Connor, 1981)</ns0:ref>. Among mobile epifauna, amphipods are highly abundant on macroalgal beds and can show colonization within few days on defaunated algal thalli <ns0:ref type='bibr' target='#b72'>(Taylor &amp; Cole, 1994;</ns0:ref><ns0:ref type='bibr' target='#b71'>Tanaka &amp; Leite, 2004)</ns0:ref>. We selected that system to investigate the factors driving the colonization of novel habitats by juveniles. For that, we investigated the effect of habitat quality, algal patch size and presence of conspecific adults on the colonization of juveniles of the tube-dwelling amphipod Cymadusa filosa Savigny, 1816 (Amphipoda: Ampithoidae). We used this developmental stage because a previous investigation reported the important role of juveniles on the dispersal of amphipod species in the study system <ns0:ref type='bibr' target='#b10'>(Bueno &amp; Leite, 2019)</ns0:ref>. First, by manipulating natural and artificial plants in both laboratory and field, we tested if juveniles are able to select and colonize a new algal patch depending on the habitat quality. Because juveniles seem to be sensitive to the habitat quality (e.g. <ns0:ref type='bibr' target='#b57'>Poore, 2004;</ns0:ref><ns0:ref type='bibr' target='#b19'>Czarnecka et al., 2010)</ns0:ref>, we hypothesized that they would colonize high-quality habitats more frequently than low-quality habitats. Second, we tested if the algal patch size affects the colonization rate by juveniles in the field. Because of their small body size, we expected that juveniles would be indifferent to the algal patch size. Finally, under laboratory and field conditions, we tested if the presence of conspecific adults on algal patches affects the settlement of juveniles. We expected that colonization by juveniles would be negatively affected by the presence of adults as a result of intraspecific aggressive interactions <ns0:ref type='bibr' target='#b17'>(Connell, 1963;</ns0:ref><ns0:ref type='bibr' target='#b6'>Brawley &amp; Adey, 1981)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Organisms and study area</ns0:head><ns0:p>The tube-dwelling amphipod Cymadusa filosa is a mesograzer commonly found in association with a variety of macroalgae in marine shallow waters <ns0:ref type='bibr' target='#b70'>(Tanaka &amp; Leite, 2003;</ns0:ref><ns0:ref type='bibr' target='#b2'>Appadoo &amp; Myers, 2004;</ns0:ref><ns0:ref type='bibr' target='#b9'>Bueno et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b46'>Machado et al., 2019)</ns0:ref>. As a generalist herbivore, C. filosa is able to feed and survive on different algal diets <ns0:ref type='bibr' target='#b48'>(Machado et al., 2017;</ns0:ref><ns0:ref type='bibr'>2019)</ns0:ref>. This mesograzer often builds tubes on algal blades, with newborn juveniles settling in the vicinity of their mother's tube <ns0:ref type='bibr' target='#b1'>(Appadoo &amp; Myers, 2003)</ns0:ref>. Organisms used in the field and laboratory experiments were collected on a rocky shore (depth of 1-2 m) at Fortaleza Beach (23&#176;32'S, 45&#176;10'W), Ubatuba, S&#227;o Paulo State, Brazil (SISBIO/ICMBio # 51999-1). The brown alga Sargassum filipendula is abundant on the subtidal level of this rocky shore and shelters a highly diverse amphipod assemblage, including C. filosa <ns0:ref type='bibr' target='#b34'>(Jacobucci et al., 2009)</ns0:ref>.</ns0:p><ns0:p>Experiments: general procedures Field experiments were conducted during March 2017 (late summer). Natural Sargassum thalli used in the experiments were collected at the study area and cleaned of epibionts in the laboratory. For all field experiments, each experimental unit (EU) included one 70 cm iron stake (6 mm diameter) driven into the sediment to serve as a foundation for the whole unit. A squared plastic screen (8 cm X 8 cm) with 1 cm mesh size was attached to the iron stake with a long zip tie; it supported the algal patch, which was artificial or natural, according to the experiment. A small float was attached to the iron stick and the squared plastic screen by a rope to hold the whole unit erect (see Fig. <ns0:ref type='figure' target='#fig_5'>1</ns0:ref> and Bueno &amp; Leite, 2019 for further details). Algal substrates were attached to the plastic screen with nylon wires. We randomly deployed EUs parallel to shore ~ 1 m from the shoreline, leaving at least 2 m spacing between adjacent EUs. After 48 h, experimental algal thalli were placed in bags with mesh size of 200 &#181;m, transported to the laboratory and frozen. In the laboratory, samples were washed under freshwater to separate amphipods, which were preserved in ethanol 70%, counted under a stereomicroscope and identified to species level according to the literature (i.e., <ns0:ref type='bibr' target='#b62'>Ruffo, 1982;</ns0:ref><ns0:ref type='bibr' target='#b4'>Barnard &amp; Karaman, 1991;</ns0:ref><ns0:ref type='bibr' target='#b40'>LeCroy, 2000;</ns0:ref><ns0:ref type='bibr' target='#b41'>LeCroy, 2002;</ns0:ref><ns0:ref type='bibr' target='#b42'>LeCroy, 2004;</ns0:ref><ns0:ref type='bibr' target='#b43'>LeCroy, 2007;</ns0:ref><ns0:ref type='bibr' target='#b44'>LeCroy, 2011)</ns0:ref>. All laboratory experiments were performed in a climate-controlled room at 22&#176;C using a 12:12h photoperiod. Cymadusa filosa individuals were obtained from macroalgal hosts from the study area and, eventually, from other rocky shores nearby. After collection, epiphytes and associated fauna were carefully removed from algal fronds in the laboratory. Cymadusa individuals were kept in a stock culture (20 L plastic tank) with seawater and continuous aeration. We fed amphipods with fresh Sargassum every other day and changed the water once a week. For each experiment, juveniles were obtained from ovigerous females collected in the stock culture. Each replicate (a 20 L plastic tank with aerated seawater and algal thallus) was conducted with juveniles obtained from the same female. Ideally, the experiments should be conducted with females carrying juveniles in their marsupium, which would be released on the experimental habitats. However, incubation period is variable among females and juveniles can leave the marsupium at different times <ns0:ref type='bibr' target='#b67'>(Sheader &amp; Chia, 1970)</ns0:ref>. In this case, we attempted to minimize the difference in the size and age of juveniles within and among replicates by conducting the trials with the smallest individuals on the third day after the female had molted. For that, each ovigerous female was kept in a beaker with seawater (150 ml) until juveniles were released from the female's brood pouch (i.e. after the ovigerous female had molted). Then, newborn juveniles were assigned to a replicate.</ns0:p></ns0:div> <ns0:div><ns0:head>Habitat quality</ns0:head><ns0:p>Field and laboratory experiments were conducted to test the effect of habitat quality on the colonization of C. filosa juveniles. For that, we used natural Sargassum thalli as high-quality habitat, because it offers both food and shelter for C. filosa <ns0:ref type='bibr' target='#b46'>(Machado et al., 2019)</ns0:ref>, and artificial Sargassum thalli as low-quality habitat, because it could provide only a shelter for these herbivorous juveniles. Artificial Sargassum fronds (Bio Models Co.) were physically identical to Sargassum thalli in shape, size, branching and color and were arranged to have similar surface area to the natural algae. We estimated algal surface area by measuring the area of flattened branches with transparent adhesive tape in a PVC plate. We used the software Image-J to calculate area and duplicated the values to account for the front and back of branches. In the field, artificial (108.2&#177;3.0 cm 2 ) and natural (115.8&#177;25.8 cm 2 ) algae were attached to the squared plastic screen of the experimental structures (N=5). No difference in area was detected among artificial and natural algae (GLM, Gamma distribution, P = 0.518). The field experiment was performed as described above in general procedures. The number of C. filosa juveniles on each experimental algal thallus was used as the response variable. In the laboratory, besides manipulating the quality of the novel habitat, we also manipulated the quality of the source habitat (i.e. the habitat where juveniles were before the novel habitat was offered). For that, we used four levels of combination of source/novel habitats: natural/natural, natural/artificial, artificial/natural and artificial/artificial (N=6). For each replicate, we placed the first algal thallus (i.e. source habitat) in a 20 L plastic tank with aerated seawater and added the juveniles using a pipette. After 30 min of acclimatization, we added the second algal thallus (i.e. novel habitat). Both algal thalli were kept 5 cm apart and hold erect by using a fishing buoy at the top and a fishing rod at the bottom, both tied with nylon wires. We used similar number of juveniles in each replicate (18&#177;2 juveniles) to avoid confounding density-related factors. We counted the juveniles on each algal thallus after 24 h by carefully removing the algal fronds from the tank. We then calculated the proportion of juveniles that colonized the novel habitat (i.e. response variable). After each experimental run, we filtered all the water from the tanks and cleaned the algal fronds to ensure that there were no remaining juveniles.</ns0:p><ns0:p>Algal patch size A field experiment was performed to test the effect of algal patch size on the colonization of C. filosa juveniles. For that, the experiment consisted of two treatments representing algae with small (30.8&#177;13.8 cm 2 ) and large (115.8&#177;25.8 cm 2 ) surface area (N=5). Sargassum fronds with small and large surface area without any epibionts were attached to the square plastic screen on the experimental structures in the field, then the experiment was conducted as described above. The number of C. filosa juveniles on each experimental algal thallus was used as response variable. We estimated algal surface area applying the same methodology described above.</ns0:p></ns0:div> <ns0:div><ns0:head>Presence of conspecific adults</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:08:51640:1:0:NEW 17 Sep 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>To test the effect of conspecific adults on colonization by C. filosa juveniles, we performed field and laboratory experiments manipulating the abundance of adults on algal thalli. In both experiments, we used only male adults to avoid mating between males and females. For the field experiment, to test how the presence of C. filosa adults affects juveniles' colonization, we kept the algal thallus with adults inside of a 250 ml acrylic cup. We perforated the walls and the lid of the acrylic cups using a drill with a fine bit, producing 1 mm diameter orifices. The orifices allowed water and juveniles to pass (and perhaps small adults). In a laboratory pilot trial, we confirmed that C. filosa juveniles were able to pass through the wall of the cup through the orifices. To allow adult males to build tubes and settle in the Sargassum fronds, we kept them in cups with seawater and algal patches for 24 h in the laboratory before beginning the field experiment. Each experimental set was composed of one algal patch (~ 3.6 g of wet mass) with 0, 4 or 8 adult males within an acrylic cup (N=4 or N=5). We attached each experimental set to the squared plastic screens of the experimental structures in the field. The experiment was performed using the same methods described above. After the collection, experimental sets were transported to the laboratory and, before freezing these samples, cups were inspected for the presence of live C. filosa adults to assess if the number of active adult males inside the cups had changed throughout the experiment. After 48 h, for the treatments with 0, 4 and 8 male adults added initially, we found an average of 0, 3.6 (&#177;0.5) and 7.5 (&#177;0.6) adults inside the cups, respectively. As a response variable, we used the number of C. filosa juveniles in each experimental set.</ns0:p><ns0:p>In the laboratory, we tested whether the effect of adults on the colonization of natural algal patches by juveniles depends on the type of source habitat occupied by juveniles. For that, we manipulated the presence of adults on natural algal thallus (two levels: 0 or 4 adults) and the type of source habitat of juveniles (three levels: no algal thallus, artificial algal thallus and natural algal thallus) in an orthogonal design (N=6 for each level of combination). Considering in the field experiment there was no difference for both treatments with adults regarding their effects on juveniles' colonization (see Results), we decided to use only two levels for adult presence (i.e. 0 and 4 adults). Each replicate consisted of one plastic tank with a natural Sargassum patch with or without adult males. Cymadusa adult males (15.7&#177;1.6 mm of body size) were obtained from the stock culture, carefully placed on the algal frond using a delicate paintbrush and kept in the plastic tank for at least 6 h for acclimatization. Again, we used a similar number of juveniles in each replicate (16&#177;2 juveniles) to avoid confounding density-related factors. Juveniles were added to perforated acrylic cups similar to those used in the field experiment, placed on one of the types of source habitat. The cup with the juveniles was 5 cm away from the natural algal thallus with or without adults. After 24 h, we counted the number of juveniles and then calculated the proportion of juveniles that colonized the algal thalli outside the cups.</ns0:p></ns0:div> <ns0:div><ns0:head>Data analyses</ns0:head><ns0:p>We used general linear models (GLM) to analyze data from field and laboratory experiments. To compare the abundance of C. filosa juveniles among treatments of the field experiments, we used GLM with Poisson ('habitat quality' experiment), Quasi-poisson ('algal patch size' experiment) or Negative binomial ('presence of adults' experiment) distributions. For the field experiment testing the effect of presence of adults, algal wet mass (log-transformed) was used as an offset variable. For the laboratory experiments, we compared the proportion of juveniles that colonized a novel habitat among treatments using GLM with Quasi-binomial distribution. When the effect of a factor was detected, we used Tukey's test to explore possible differences among treatments.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Habitat quality A total of 37 juvenile amphipods colonized experimental algal thalli in the field. From this, 17 juveniles were identified as C. filosa. Although more individuals were found in natural algal patches, there was no difference in the abundance of C. filosa juveniles between artificial (1.2&#177;0.8 juveniles) and natural (2.2&#177;1.3 juveniles) algal thalli (GLM, Poisson distribution, P = 0.222). In contrast, in the laboratory experiment, the quality of source and novel habitats (i.e. artificial or natural alga) influenced the colonization rate by C. filosa juveniles (GLM, Quasibinomial distribution, P &lt; 0.001). The highest proportion of juveniles colonizing a novel habitat was found when the source was artificial, and the novel habitat was natural alga. In turn, the lowest proportion of juveniles colonizing a novel habitat occurred when the source and novel habitats were a natural and an artificial alga, respectively. Intermediate values of proportion of juveniles colonizing a novel habitat were found when novel and source habitats were of the same quality (Fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Algal patch size</ns0:head><ns0:p>Of 47 juvenile amphipods that colonized the experimental algal thalli, 12 were C. filosa juveniles. The abundance of C. filosa juveniles was similar between algal patches with small (1.2&#177;1.3 juveniles) and large (2.2&#177;1.3 juveniles) surface area (GLM, Quasi-poisson distribution, P = 0.277).</ns0:p></ns0:div> <ns0:div><ns0:head>Presence of adults</ns0:head><ns0:p>In the field experiment, 111 C. filosa juveniles (of 313 juvenile amphipods in total) colonized experimental algal thalli. Overall, the abundance of C. filosa juveniles had a tendency to increase with the density of adults (Fig. <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>). However, this effect was only marginally significant (GLM, Negative binomial distribution, P = 0.055). For the laboratory experiment, we found a significant interaction between the factors 'presence of adults' and 'type of source habitat' (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). Despite this, from the Tukey's test, we found that differences (or similarities) among levels of one factor did not depend on the levels of the other factor for the meaningful comparisons to this study. Cymadusa filosa juveniles without alga or with artificial alga colonized a novel habitat (with or without adults) in a higher proportion than juveniles with natural alga as source habitat (Fig. <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>). Within each level of source habitat, the presence of adults did not affect the colonization by juveniles (Fig. <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Habitat quality does not seem to affect colonization by juveniles of Cymadusa filosa on a local scale and under natural conditions (i.e. field experiment). However, on a smaller scale under controlled conditions (i.e. laboratory experiment), juveniles are able to optimize their habitat choice by selecting a high-quality resource (i.e. natural alga), where both food and shelter are provided, when low-quality resource (i.e. artificial alga) is available as a source or novel habitat. The colonization by juveniles did not depend on the algal patch size. The presence of conspecific adults does not affect the colonization of juveniles under controlled conditions but may be important under natural conditions. These findings suggest that, although very initially constrained by their mothers' choice, C. filosa juveniles can rapidly search, choose and colonize novel habitats, corroborating their previously reported dispersive potential <ns0:ref type='bibr' target='#b10'>(Bueno &amp; Leite, 2019)</ns0:ref>, and that such process can be partially affected by the habitat quality. In the laboratory, juveniles showed high colonization rates when going from artificial source habitats to natural novel habitats. In contrast, the lowest colonization rates were found when an artificial algal thallus was offered (i.e. novel habitat) for juveniles inhabiting a natural alga. In accordance, intermediate colonization rates were found when source and novel habitats were similar (i.e. both were natural or artificial algal thalli). These results suggest that C. filosa juveniles have a tendency to stay where they are, as expected since they are released from the mother brood pouch, unless a better-quality resource is available, corroborating the low mobility behavior often observed for tube-building amphipods <ns0:ref type='bibr' target='#b24'>(Duffy &amp; Hay, 1994;</ns0:ref><ns0:ref type='bibr' target='#b59'>Poore &amp; Steinberg, 1999)</ns0:ref>. Similar results were found in the laboratory experiment testing the effect of adult's presence. In this case, natural algal thalli (with or without adults) were offered as novel habitat in all treatments and juveniles with an artificial alga or without any alga (i.e. low-quality source habitats) showed higher colonization rates than those with a natural alga as source habitat. In this sense, our results corroborate the idea that the distribution of juvenile amphipods living on macroalgae is not restricted by the females' choice <ns0:ref type='bibr' target='#b58'>(Poore, 2005;</ns0:ref><ns0:ref type='bibr' target='#b10'>Bueno &amp; Leite, 2019)</ns0:ref> and that their colonization process is partially motivated by the habitat quality <ns0:ref type='bibr' target='#b57'>(Poore, 2004)</ns0:ref>. Sargassum is a high-quality food for C. filosa and, thus, is not only used for shelter by this herbivorous amphipod <ns0:ref type='bibr' target='#b48'>(Machado et al., 2017;</ns0:ref><ns0:ref type='bibr'>2019)</ns0:ref>. This role for Sargassum is supported by our results from laboratory experiments with artificial and natural algal thalli. Also, these results suggest that C. filosa juveniles can detect a suitable host to colonize. Similarly, the tube-building amphipod Jassa herdmani can discriminate between its host hydrozoan Tubularia indivisa and other artificial substrates, indicating this species may have a detection mechanism, although it is not fully understood <ns0:ref type='bibr' target='#b31'>(Havermans et al., 2007)</ns0:ref>. Moreover, the amphipod Incisocalliope symbioticus seems to use chemical cues to locate and colonize its host, the gorgonian octocoral Melithaea flabellifera, at short distances <ns0:ref type='bibr' target='#b37'>(Kumagai, 2006)</ns0:ref>. Chemical cues from Sargassum may Manuscript to be reviewed be an important mechanism for C. filosa juveniles detect a suitable and high-quality habitat and further studies are required to elucidate it. The ability to detect and colonize a suitable habitat should be advantageous for C. filosa juveniles when (1) there is a mismatch between feeding (or habitat) preference of adults and performance of juveniles (e.g. <ns0:ref type='bibr' target='#b18'>Cruz-Rivera &amp; Hay, 2001;</ns0:ref><ns0:ref type='bibr' target='#b50'>McDonald &amp; Bingham, 2010)</ns0:ref> and/or (2) the abundance of adults on high-quality food algae is constrained by extrinsic factors to the host, such as predation and wave action (e.g. <ns0:ref type='bibr' target='#b68'>Sotka, 2007;</ns0:ref><ns0:ref type='bibr' target='#b38'>Lasley-Rasher et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b46'>Machado et al., 2019)</ns0:ref>. The feeding behavior and its consequences for the survival, growth and reproduction of C. filosa are tightly linked, with adults preferring algal hosts that results in the highest performance of juveniles <ns0:ref type='bibr' target='#b48'>(Machado et al., 2017;</ns0:ref><ns0:ref type='bibr'>2019)</ns0:ref>. However, in the study area, C. filosa has been found on the red alga Dichotomaria marginata, which is a poor-quality food, in densities higher than on the high-quality food Sargassum filipendula <ns0:ref type='bibr' target='#b46'>(Machado et al., 2019)</ns0:ref>, suggesting a trade-off between food and shelter for this herbivorous amphipod. In this context, the ability of C. filosa juveniles to detect and colonize novel and suitable habitats, regardless their mothers' choice, should be advantageous for the success of this developmental stage and, consequently, for the species. Contrasting with our expectations and the results from the laboratory experiments, we did not find any effect of habitat quality on juveniles' colonization in the field experiment, suggesting other factors may influence the colonization of these amphipods under natural conditions. The similar abundance of C. filosa juveniles on artificial and natural algal thalli may suggest that the algal morphology per se has an important role regarding the host use by this amphipod in the field. Algal morphology mediates the vulnerability of associated fauna to predation <ns0:ref type='bibr' target='#b84'>(Zamzow et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b77'>Ware et al., 2019)</ns0:ref>. Also, structural and spatial traits of macroalgae affects the availability of space for the epifauna <ns0:ref type='bibr' target='#b29'>(Hacker &amp; Steneck, 1990;</ns0:ref><ns0:ref type='bibr' target='#b12'>Carvalho et al., 2018)</ns0:ref>. The colonization of artificial substrates mimicking natural plants by epifaunal species highlights the importance of the physical structure of macrophytes for the settlement of associated fauna <ns0:ref type='bibr' target='#b75'>(Virnstein &amp; Curran, 1986;</ns0:ref><ns0:ref type='bibr' target='#b55'>Norderhaug et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b76'>Waage-Nielsen et al., 2003)</ns0:ref>. Because artificial algal thalli in the field were rapidly colonized by juvenile amphipods, it is probably functioning as a suitable shelter, at least temporarily. The size of algal thalli available for colonization in the field experiment did not affect the number of C. filosa juveniles found on these substrates. In a previous laboratory experiment, C. filosa juveniles colonized small and large algal patches in similar proportions <ns0:ref type='bibr' target='#b10'>(Bueno &amp; Leite, 2019)</ns0:ref>. The availability of substrate is often related to the habitat complexity, thus is an important factor for the association of mobile fauna with macrophytes <ns0:ref type='bibr' target='#b69'>(Stoner, 1980;</ns0:ref><ns0:ref type='bibr' target='#b29'>Hacker &amp; Steneck, 1990)</ns0:ref>. For instance, as the surface area of a substrate increase, it can decrease the vulnerability of mobile fauna to predation <ns0:ref type='bibr' target='#b63'>(Russo, 1987)</ns0:ref>. However, prey size may also mediate the intensity of predation on amphipods. Predators may preferentially consume larger individuals (e.g. <ns0:ref type='bibr' target='#b69'>Sturaro et al., 2016)</ns0:ref> while smaller animals may be less vulnerable to detection and consumption by predators <ns0:ref type='bibr' target='#b64'>(Schlacher &amp; Wooldridge, 1996)</ns0:ref>. In this sense, although habitat size is important for the associated fauna, the surface area may be less crucial for the colonization of a Sargassum thallus by small bodied organisms, such as C. filosa juveniles. No effect of the presence of conspecific adults on the colonization of C. filosa juveniles was detected in the laboratory experiment. In contrast, we found a marginally significant trend of juveniles' abundance increasing with adult density. The effects of conspecifics on the recruitment and settlement of juvenile amphipods are variable. The presence of adults does not affect the habitat choice of juveniles of the amphipod Pontogammarus robustoides <ns0:ref type='bibr' target='#b19'>(Czarnecka et al., 2010)</ns0:ref>. For the tube-dwelling amphipod Corophium volutator, high densities of adults may negatively affect the settlement of conspecific juveniles, as a result of intraspecific competition <ns0:ref type='bibr'>(Wilson, 1989;</ns0:ref><ns0:ref type='bibr' target='#b35'>Jensen &amp; Kristensen, 1990)</ns0:ref>. The effects of intraspecific competition depend on the density of conspecifics and food concentration <ns0:ref type='bibr' target='#b32'>(Hill, 1992;</ns0:ref><ns0:ref type='bibr' target='#b79'>Wenngren &amp; &#211;lafsson, 2002;</ns0:ref><ns0:ref type='bibr' target='#b74'>Van Tomme et al., 2012)</ns0:ref>. In our field experiment, we used treatments with adults in densities (from ~1 to 2 ind/g of alga) that were much higher than that previously reported for C. filosa at same study site (~ 0.2 ind/g of alga; see <ns0:ref type='bibr' target='#b46'>Machado et al., 2019</ns0:ref>). Yet, the presence of adult conspecifics on algal patches did not negatively affect juveniles' colonization, suggesting that intraspecific competition for food and/or space is not an important factor for the colonization of C. filosa juveniles. In contrast, it is possible that C. filosa juveniles are attracted by the presence of adults, which could explain the increase of juveniles on intertidal soft-bottom habitats, which could be an indicative of habitat quality <ns0:ref type='bibr' target='#b7'>(Bringloe et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b23'>Drolet et al., 2013)</ns0:ref>. Further experiments with higher replication are necessary to confirm this hypothesis for C. filosa juveniles.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>By combining laboratory and field experiments, we found that the colonization of novel habitats by C. filosa juveniles can be affected by the habitat quality, but not by the patch size. Also, the presence of conspecifics may affect the colonization by juveniles. Contrasting results between laboratory and field experiments manipulating the habitat quality and the presence of conspecifics highlighted the importance of using different approaches to better understand the factors determining the host use by juvenile amphipods. In the present study, we used artificial algal thalli as a low-quality habitat; it would be interesting to investigate the behavior of C. filosa juveniles when they have more than one macroalgal host to select, since in the shallow subtidal areas they have a variety of biological substrates available for colonization <ns0:ref type='bibr' target='#b2'>( Appadoo &amp; Myers, 2004;</ns0:ref><ns0:ref type='bibr' target='#b9'>Bueno et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b46'>Machado et al., 2019)</ns0:ref>. Investigating dispersal patterns during specific life stages can greatly contribute to understand the movement paths during the lifespan of organisms <ns0:ref type='bibr' target='#b0'>(Allen et al., 2018)</ns0:ref>. After dispersing, the colonization of new substrates will set the distribution of populations among hosts <ns0:ref type='bibr' target='#b58'>(Poore, 2005;</ns0:ref><ns0:ref type='bibr' target='#b13'>Chapman, 2007)</ns0:ref>, contributing to the maintenance of populations at local and regional scales. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:51640:1:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure captions Figure 1 .</ns0:head><ns0:label>captions1</ns0:label><ns0:figDesc>Figure captions</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Proportion of Cymadusa filosa juveniles colonizing the novel habitat offered in the laboratory. Source and novel habitats are indicated as 'nat' when natural alga and as 'art' when artificial alga. Arrows indicate the colonization path. Bars represent standard error. Different letters indicate significant difference among combinations of source and novel habitats (Tukey test, p &lt; 0.05).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. Abundance of juveniles of Cymadusa filosa that colonized algal experimental patches in the field. Different numbers of conspecific adult males (0, 4 and 8) were established in the algal patches when they were deployed in the field. Bars represent standard error.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. Proportion of juveniles of Cymadusa filosa colonizing the novel habitat (natural alga with or without adults) when different source habitats (natural algal thallus, artificial algal and none) were provided to the juveniles in the laboratory. Bars represent standard error. Different letters indicate significant difference among juveniles' source habitats (Tukey test, p &lt; 0.05).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='21,42.52,70.87,285.08,672.95' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Analysis of Deviance for GLM with Quasi-binomial distribution fitted to the proportion of juveniles from different source habitats colonizing natural algal thallus with or without adults at the laboratory experiment.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Tables</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Source of variation</ns0:cell><ns0:cell cols='4'>df Deviance Residual df Residual deviance</ns0:cell><ns0:cell>F</ns0:cell><ns0:cell>p</ns0:cell></ns0:row><ns0:row><ns0:cell>NULL</ns0:cell><ns0:cell>---</ns0:cell><ns0:cell>---</ns0:cell><ns0:cell>35</ns0:cell><ns0:cell>20.423</ns0:cell><ns0:cell>---</ns0:cell><ns0:cell>---</ns0:cell></ns0:row><ns0:row><ns0:cell>Source habitat (SH)</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>12.181</ns0:cell><ns0:cell>33</ns0:cell><ns0:cell>8.242</ns0:cell><ns0:cell cols='2'>33.008 &lt; 0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Presence of adults</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>1</ns0:cell><ns0:cell>0.779</ns0:cell><ns0:cell>32</ns0:cell><ns0:cell>7.462</ns0:cell><ns0:cell>4.223</ns0:cell><ns0:cell>0.049</ns0:cell></ns0:row><ns0:row><ns0:cell>(PA)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SH X PA</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>1.699</ns0:cell><ns0:cell>30</ns0:cell><ns0:cell>5.763</ns0:cell><ns0:cell>4.605</ns0:cell><ns0:cell>0.018</ns0:cell></ns0:row></ns0:table></ns0:figure> </ns0:body> "

"September 17, 2020 Dr. Joseph Pawlik Academic Editor, PeerJ Dear Dr. Pawlik, Thank you for the opportunity to resubmit our manuscript ID 51640. We have carefully reviewed all issues pointed out by the reviewers. Their comments and suggestions were very valuable and significantly contributed to this new version. The corrections and changes made to the original manuscript are listed below. All sections of the manuscript were modified in accordance with the comments and suggestions made by the reviewers. Sincerely, Marilia Bueno Reviewer 1 Basic reporting COMMENT – The article is well written in general but can still use the help of a language editor. It also needs to update and broaden the literature cite. There is too much self citation. REPLY: We are grateful for the comments of the reviewer. The manuscript was revised in order to improve the language. Also, we included new references and removed others in order to avoid the excess of self-citation and update and broaden the literature cite. Experimental design COMMENT – The hypotheses make sense when the paper is read completely, but the experimental questions need to be stated more clearly. I have no issues with the experimental design or analysis other than some clarifications requested. I find the number of figures and their clarity appropriate. REPLY: We are grateful for the comments of the reviewer. We rewrote the hypotheses and their justifications to improve the clarity (see lines 137-145). Validity of the findings COMMENT – Only one of the conclusions (effects of adults) requires further discussion. However, overall, the conclusion will be improved if they are placed in a broader context than just the amphipod or marine literature. REPLY: Agreed. We have improved the discussion about the effects of adults (see lines 395-412). Also, we modified the conclusion in order to place it in a broader context (see lines 416-429). Comments for the author Review of Bueno et al. “Colonization of novel algal habitats…” PeerJ General comments:  1) Overall, this well written, but there are some slight mistakes in phrasing and the use of articles. A language editor should give this a reading. REPLY: The manuscript was revised in order to improve the language. 2) The authors are dealing with fundamental ecological issues such as the roles of dispersal and recruitment in population connectivity and community structure, age-related dispersal and other broader ecological questions. Most of the fundamental work on such questions has been done in terrestrial systems, especially with mammals and birds. It is surprising that so little of the relevant literature is cited. The manuscript will have broader appeal if the citations are less biased towards marine work in these fundamental issues.  REPLY: We are grateful for the comments of the reviewer. We have added more references in the manuscript, including those beyond marine context. 3) On a related issue, the literature cited is not current. For example, there are more recent reviews on the ecology of dispersal, including supply-side processes, than the ones cited here. In fact, all papers from 2015 on are from one of the coauthors. I think there is more recent relevant literature than this. REPLY: We are grateful for the comment. We included new references and removed others in order to avoid the excess of self-citation and update the literature cite. 4) Similarly, instances of repetitive citing should be avoided (see for example Mungia et al. 2007 in lines 97-99). REPLY: Agreed. We carefully reviewed the manuscript in order to avoid it. Specific comments: Lines 46-48: the methods are just a repetition of the background, please rephrase one or the other. Also “settlement” invokes a specific type of movement. Please use colonization or recruitment as these amphipods are likely crawling, rather than swimming. REPLY: Agreed. We modified this sentence according the reviewer’s suggestion (see lines 46-47). Also, we replaced “settlement” by colonization. Line 113: Eliminate “known as” REPLY: Agreed. Lines 131-145: The presentation of the hypotheses or experimental questions must be written more clearly. The authors use multiple vague statements and terms here that are not helpful (e.g., “the macroalgae-amphipod system”, “this early stage”). They also use several references when establishing their actual hypotheses, which is confusing. Are these hypotheses tested in those papers? The hypotheses and their justifications should be stated more directly. REPLY: We are grateful for the comments of the reviewer. We rewrote the hypotheses and their justifications (see lines 137-145). Also, we avoid terms like “the macroalgae-amphipod system” and “early stage” throughout the manuscript. Line 159: Deleted “the amphipod” and abbreviate the genus. REPLY: Agreed. Line 163: “thalli” should not be in italics REPLY: Agreed. Line 166: “Driven”, not “drove” REPLY: Agreed. Lines 165-170: The experimental units are difficult to visualize so I recommend adding a picture or diagram as supplementary material. Also, it is unclear what the components of the unit are for. Please explain. REPLY: We rewrote the description of the experimental units and we believe it is much clearer now. Also, we added a figure of the experimental unit. Line 172: Eliminate “of experiment” REPLY: Agreed. Line 180-181: This sentence is unclear. What epibionts? REPLY: We meant epiphytes and sessile and mobile fauna associated to macroalgal hosts. We rewrote this sentence (see lines 179-180). Line 184-194: Please eliminate superfluous details and explain more clearly. I am not sure what a replicate means from this REPLY: Agreed. We rewrote these sentences (see lines 184). Lines 319-320: I am not sure what this means. All amphipods are capable of colonizing substrates pending on circumstances. REPLY: We are grateful for this comment. We deleted this sentence. Lines 325-326: I am not convinced the presence of adults was irrelevant. The result of their analysis was borderline (p=0.055) and their replication was relatively low. The authors should comment on this. REPLY: We are grateful for the comment. We have improved the discussion about the effects of adults on the colonization of juveniles (see lines 395-412). Also, in this regard, we have modified some sentences in the Results section (see lines 306-308). Lines 366-368: I understand the trade-off but the role of juvenile mobility should be explained better in this context. REPLY: We are grateful for this comment. We have modified this sentence and explained better our ideas. Reviewer 2 Basic reporting No comment Experimental design No comment Validity of the findings 1- I have one comment on the statistics of the field experiment with the presence/absence of adults and its interpretation. There was a marginally-significant influence of adult male density and colonization rate (p=0.055); there was a 2-fold increase in juvenile recruits in cups with 8 adults relative to 0 adults (lines 306-309). The authors interpret this as no effect, but to me it is also possible, even likely, the experiment suffers from Type II error and low power. Id like the authors to mention this in either the results or Discussion. At the least, the Discussion should point out that the effect was marginally significant (e.g., paragraph starting line 392) - in fact, id suggest placing these results into a new figure. they are hard-fought data and deserve more attention. I'd also recommend the authors try a couple of analyses to pull out this effect. Does the analysis treat the male density as ordinal levels, or does it ignore the increasing levels of male density? Also, you might want to treat the levels as presence / absence (i.e., group 4 and 8 males), since that likely increases your power. REPLY: We are grateful for the reviewer’s comments. We agree with the reviewer about the marginally significant effect of adults on the colonization of juveniles from the field experiment. We have changed sentences in the Results and Discussion sections following this interpretation (see lines 306-308 and 395-412). Also, we have included a figure showing such results (see Figure 3). Regarding the alternative ways for analyzing the data as suggested by the reviewer, we tested all of them. In the first version of the manuscript, we considered the presence of adults as a factor, ignoring the increasing level of male density (GLM, Negative binomial distribution, P = 0.055). Also, we have re-run this analysis considering the same factor with ordinal levels (i.e. 0 < 4 < 8) and obtained the same result from the previous analysis (GLM, Negative binomial distribution, P = 0.055). Finally, we used the factor considering only two levels (i.e. presence and absence of adults) by grouping data from treatments with 4 and 8 adults in a single treatment. In this case, no effect was detected (GLM, Negative binomial distribution, P = 0.140) and P-value was no longer marginally significant. Because all analyses converged, we decided to keep the same analysis presented in first version of the manuscript. 2- a few issues with the artificial alga came to my head. Were artificial algae pre-treated in the water before any colonization experiments? If they were colonized by epibiota that can attract herbivorous amphipods (e.g., diatoms), then that would suggest they have both food and habitat quality. Also, microbial biofilms can generally influence invertebrate habitat choices. Finally, plastic can leach chemicals that can either repel or harm marine organisms. What precautions did you take to prevent this? REPLY: We appreciate the reviewer’s comment. No, we did not pre-treat artificial algae in the water before the colonization experiments. Such proceeding could have resulted in the establishment of microbial biofilms on artificial algae, what in turn could have been a problem since artificial algae were supposed to represent only shelter for juveniles (in contrast to natural algae, which offered both food and shelter). Also, because the artificial plants used in the experiments are of high quality and adequate for aquarium usage, we believe no harm was caused to the organisms. 3- there were substantial numbers of non-Cymadusa filosa juveniles in both field experiments. Were there any patterns between treatments in these other groups, or as a whole? If you know if any of these are competitors or predators, Id be particularly curious to know on this point, as it could help to explain the lack of field results. REPLY: We believe showing data on the whole amphipod assemblage would not add relevant information for our study. For the habitat quality experiment, we found similar abundances of Cymadusa filosa juveniles between natural and artificial algal patches. When analyzing all juvenile amphipods, we found higher abundance in natural algae. However, other tube-dwelling species were observed in very low numbers (Sunamphitoe pelagica (n=2), Aora spinicornis (n=4) and Ericthonius brasiliensis (n=4)) and 90% of those juveniles were exclusively inhabiting natural algal thalli. As C. filosa was better represented with more individuals (n=17) and it is the focal species in this study, we decided to show only the results of this species. Although C. filosa juveniles showed a different pattern of abundance, we are confident that our results are realistic based on our knowledge of the ecology of this particular species (very abundant in our study area, generalist, common in different substrates). For the experiment of presence of adults, when we accounted for all species, juveniles similarly colonized the algal patches without males, with 4 males and with 8 males. There wasn’t an increase in the abundance of juveniles towards the presence of conspecific adults, as observed for C. filosa, although marginally significant (p = 0.055). Also, we were interested in evaluating intraspecific competition, once conspecific adult males were added to the experiment. Analyzing all amphipod species would lead to different arguments concerning interspecific competition that were not on the scope of this study. Because of that, we decided not to show these results. Comments for the author This is a well-executed set of laboratory and field experiments exploring the ecology of juvenile colonization in a species of herbivorous amphipod. Overall, the experiments showed that these juveniles make explicit choice to colonize algal habitats over simple morphological structure, and that the effect of adult male presence on colonization rates was weaker. there was a marginally-significant increase in juvenile colonization in the field in the presence of adult males. REPLY: We are grateful for all comments of the reviewer. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Mesopontonia verrucimanus and Mesopontonia kimwoni sp. nov. are recorded from highlatitude temperate waters in Munseom Islet, Jejudo Island, Republic of Korea, with both species collected on gorgonians and sponges by trimix diving between 50 and 75 m depth.</ns0:p><ns0:p>Mesopontonia kimwoni sp. nov. is morphologically allied to M. brevicarpus, but can be distinguished by the cutting edges of the fingers of the first chela being entire. Significant morphological variation in the rostrum as well as the second pereiopods is documented in M. verrucimanus, although cytochrome c oxidase subunit I (COI) barcode analysis proves this to be infra-specific variation. A key to species of the genus Mesopontonia is provided.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The deep-sea palaemonid shrimp fauna of the Indo-West Pacific is relatively well documented, with to date 23 genera and about 84 species recorded from depths of more than 100m by trawling and dredging <ns0:ref type='bibr' target='#b7'>(Bruce 1991;</ns0:ref><ns0:ref type='bibr' target='#b22'>De Grave &amp; Fransen 2011;</ns0:ref><ns0:ref type='bibr' target='#b34'>Kou et al. 2016;</ns0:ref><ns0:ref type='bibr' target='#b42'>Li et al. 2008;</ns0:ref><ns0:ref type='bibr' target='#b45'>Marin &amp; Chan 2014;</ns0:ref><ns0:ref type='bibr' target='#b47'>Mitsuhashi &amp; Chan 2006;</ns0:ref><ns0:ref type='bibr' target='#b48'>Okuno 2017;</ns0:ref><ns0:ref type='bibr' target='#b58'>Wang et al. 2015</ns0:ref>). Among them is the rarely recorded genus, Mesopontonia <ns0:ref type='bibr' target='#b1'>Bruce, 1967</ns0:ref> which can be distinguished from related genera by the combination of the absence of both supraorbital and antennal teeth on the carapace, as well as the absence of an exopod on the third maxilliped <ns0:ref type='bibr' target='#b1'>(Bruce 1967;</ns0:ref><ns0:ref type='bibr' target='#b8'>Bruce 1995;</ns0:ref><ns0:ref type='bibr' target='#b13'>Chace &amp; Bruce 1993)</ns0:ref>.</ns0:p><ns0:p>The most recent classification of carideans by De Grave and Fransen (2011) listed six species in the genus, namely M. gorgoniophila <ns0:ref type='bibr'>Bruce, 1967 (type species)</ns0:ref>, M. gracilicarpus <ns0:ref type='bibr'>Bruce, 1990</ns0:ref>, M. brucei <ns0:ref type='bibr' target='#b11'>Burukovsky, 1991</ns0:ref><ns0:ref type='bibr'>, M. monodactylus Bruce, 1991</ns0:ref><ns0:ref type='bibr'>, M. verrucimanus Bruce, 1996</ns0:ref><ns0:ref type='bibr'>and M. brevicarpus Li &amp; Bruce, 2006</ns0:ref>. The type species was originally described from the <ns0:ref type='bibr'>Philippines (2018</ns0:ref><ns0:ref type='bibr'>-2019</ns0:ref><ns0:ref type='bibr'>), and Taiwan (2016)</ns0:ref>, organized by Academia Sinica, University of the Philippines Visayas (UPV), Korea Institute of Ocean Science &amp; Technology (KIOST), Marine Biodiversity Institute of Korea (MABIK), and SNU. All specimens were collected together with their host invertebrates and preserved in 80% ethanol. Specimens are deposited in the Marine Arthropod depository Bank of Korea, Seoul National University, Seoul (MADBK), Seoul National University, Seoul (SNU), National Institute of Biological Resources, Incheon (NIBR) and the Zoological Collections of the Oxford University Museum of Natural History, Oxford (OUMNH.ZC). Morphological examination. Shrimps were isolated from the host invertebrate using forceps, with their morphological characteristics observed using stereo microscopes (Leica M205C and M125, Germany) and a light microscope (Olympus BX51, Japan). Digital illustrations were done using a microscope digital camera (Leica MC170, Germany), Helicon focus software (Helicon focus 7.5.6, Ukraine) and drawing tablet (Wacom Intuos Pro PTH-660, China) with Adobe Illustrator software (Adobe Systems, USA), following <ns0:ref type='bibr' target='#b16'>Coleman (2006)</ns0:ref>. Molecular data and phylogenetic analysis. Molecular phylogenetic analyses were performed to understand the phylogenetic position of the new species, as well as the genus more broadly. Two species of Mesopontonia (M. verrucimanus and the new species) and 12 deep-sea species from the genera Altopontonia <ns0:ref type='bibr'>Bruce, 1990</ns0:ref><ns0:ref type='bibr'>, Anchistioides Paulson, 1875</ns0:ref><ns0:ref type='bibr'>, Bathymenes Kou, Li &amp; Bruce, 2016</ns0:ref><ns0:ref type='bibr'>, Cuapetes Clark, 1919</ns0:ref><ns0:ref type='bibr'>, Echinopericlimenes Marin &amp; Chan, 2014</ns0:ref><ns0:ref type='bibr'>, Lipkemenes Bruce &amp; Okuno, 2010</ns0:ref><ns0:ref type='bibr'>, Palaemonella Dana,1852</ns0:ref><ns0:ref type='bibr'>, Paraclimenes Bruce, 1995</ns0:ref><ns0:ref type='bibr'>, Periclimenes Costa, 1844</ns0:ref><ns0:ref type='bibr'>and Thaumastocaris Kemp, 1922</ns0:ref> were selected as the ingroup. Stenopus hispidus <ns0:ref type='bibr' target='#b49'>(Olivier, 1811)</ns0:ref> was used as an outgroup (Table <ns0:ref type='table'>1</ns0:ref>). Total genomic DNA was extracted from eggs or pleopod tissue using the QIAamp &#174; DNA Micro Kit (QIAGEN, Hilden, Germany), following the manufacturer's instructions. Partial sequences of the COI (~658bp) and 16S (~538bp) markers were amplified via polymerase chain reaction (PCR) with the primers jgHCO2198/jgLCO1490 <ns0:ref type='bibr' target='#b29'>(Geller et al. 2013</ns0:ref>) and 16S-ar/16S-1472 <ns0:ref type='bibr' target='#b17'>(Crandall &amp; Fitzpatrick 1996;</ns0:ref><ns0:ref type='bibr' target='#b50'>Palumbi et al. 2002)</ns0:ref>, respectively. PCR reactions and sequence data analysis were performed following <ns0:ref type='bibr' target='#b51'>Park et al. (2019a)</ns0:ref>. Zoobank registration. The electronic version of this article in Portable Document Format (PDF) will represent a published work according to the International Commission on Zoological Nomenclature (ICZN), and hence the new names contained in the electronic version are effectively published under that Code from the electronic edition alone. This published work and the nomenclatural acts it contains have been registered in ZooBank, the online registration system for the ICZN. The ZooBank LSIDs (Life Science Identifiers) can be resolved and the associated information viewed through any standard web browser by appending the LSID to the prefix http://zoobank.org/. The LSID for this publication is: urn:lsid:zoobank.org:pub:3CB43670-472F-49AE-80F2-EAE9597E12BD. The online version of this work is archived and available from the following digital repositories: PeerJ, PubMed Central and CLOCKSS. ovigerous females (pocl 1.5-3.7, R 1+8-9/0-1); Oct. 22, 2019; same location (33&#176;13'37'N 126&#176;34'11'E), 67m, on E. cf. limbaughi, leg. JH Park (NIBRIV0000862996-NIBRIV0000863001); 2 males, 1 female (pocl 2.4-3.7, R 1+8-9/0-2); Jan. 15, 2020; same location (33&#176;13'34'N 126&#176;33'45'E), 75m, on E. cf. limbaughi, leg. JH Park (MADBK 120533_007); 3 females (pocl 2.5-2.8, R 1+7-8/0); Jan. 15, 2020; same location (33&#176;13'34'N 126&#176;33'45'E), 75m, on C. anguina, leg. JH Park (SNU KR JH1100-1102); 1 male (pocl 2.5, R 2-8/1); Jan. 15, 2020; same location (33&#176;13'34'N 126&#176;33'45'E), 75m, on Raspailia sp., leg. JH Park (SNU KR JH1095); 1 female (pocl 2.3, R 1-8/0); Jan. 15, 2020; same location (33&#176;13'34'N 126&#176;33'45'E), 75m, on Raspailia sp., leg. JH Park (SNU KR JH1096); 1 female (pocl 2.9, R 1-9/0); Jan. 15, 2020; same location (33&#176;13'34'N 126&#176;33'45'E), 75m, on C. anguina, leg. JH Park (SNU KR JH1104). Description of Korean specimens. Body (Fig. <ns0:ref type='figure'>2</ns0:ref>) small-sized, subcylindrical form. Rostrum (Figs. 2 and 3A-D) straight, horizontal, almost as long as pocl, reaching or overreaching distal end of antennular peduncle, 6-9 dorsal teeth, spaced along entire length, 0-2 ventral teeth.</ns0:p><ns0:p>Carapace (Figs. 2 and 3A-D) smooth, glabrous, with epigastric tooth at anterior 0.3 of pocl; without supraorbital and antennal teeth; inferior orbital angle produced; hepatic tooth large, acute, extending to anterior margin of carapace; pterygostomial angle bluntly rounded.</ns0:p><ns0:p>Abdomen (Fig. <ns0:ref type='figure'>2</ns0:ref>) smooth; pleura of first five segments rounded; sixth pleura with pointed posterolateral angle, posteroventral angle subacute.</ns0:p><ns0:p>Telson (Figs. <ns0:ref type='figure' target='#fig_2'>2 and 3E</ns0:ref>, F) about 0.75 of pocl, 4.0 times as long as proximal width; two pairs of small dorsal spiniform setae at 0.4 and 0.65 of telson length respectively, with three pairs of posterior spiniform setae, lateral pair shortest, medial pair long and stout.</ns0:p><ns0:p>Eye (Figs. <ns0:ref type='figure' target='#fig_3'>2 and 4A</ns0:ref>) with hemispherical cornea, dorsolaterally with nebenauge, diameter about 0.20 of pocl.</ns0:p><ns0:p>Antennule (Figs. <ns0:ref type='figure' target='#fig_3'>2 and 4B</ns0:ref>) with proximal peduncle bearing distolateral tooth, with small acute tooth at ventromedial margin; stylocerite narrow, bearing sharp point, reaching to 0.45 times of proximal segment; intermediate segment short, 0.4 times of proximal segment length, 0.8 of distal segment; upper flagellum biramous, proximal five segments fused, lower flagellum slender, filiform.</ns0:p><ns0:p>Antenna (Figs. <ns0:ref type='figure' target='#fig_3'>2 and 4C</ns0:ref>) basicerite with sharp pointed distodorsal margin; ischiocerite and merocerite unarmed; carpocerite reaching to about 0.4 of scaphocerite length; scaphocerite 4 times as long as maximal width, lateral margin rounded, medial margin convex, distolateral tooth large, at 0.9 of lamella length.</ns0:p><ns0:p>Mouthparts typical for genus. Third maxilliped (Fig. <ns0:ref type='figure' target='#fig_3'>4D</ns0:ref>) without exopod, reaching to middle of carpocerite; ultimate segment about 0.4 of antepenultimate segment length, tapering distally, with transverse rows of setae; penultimate segment about 0.6 of antepenultimate segment length, with sparsely row of long setae ventromedially; ischiomerus completely fused to basis, antepenultimate segment feebly compressed distally, with long setae ventromedially; coxa with rounded medial lobe, with rounded lateral plate.</ns0:p><ns0:p>First pereiopod (Figs. 2, 5A and 5B) reaching to distal end of scaphocerite; fingers about 0.81 of palm length, tips hooked, cutting edge entire, with transverse row of setae and group of terminal setae; palm ventrolaterally with transverse row of serrulate setae; carpus 1.3 times length of chela with row of serrulate setae along distomesial margin; merus as long as carpus; ischium about 0.7 times length of merus; basis and coxa without special features.</ns0:p><ns0:p>Second pereiopods (Figs. 2A, 5C-G) well developed, dissimilar in shape, unequal in size. Major second pereiopod (Fig. <ns0:ref type='figure' target='#fig_4'>5C-E</ns0:ref>) overreaching distal end of rostrum by middle of propodus; chela about 0.63 of pocl, with group of terminal setae; fingers about 0.5 of palm length; dactylus slender, about 3.6 times longer than proximal depth, distally curved with acute tip, proximally with two acute teeth at 0.3 and 0.40, distally entire without dorsolateral flange; fixed finger with acute tip, proximally with two small teeth at 0.2 and 0.3, distally entire; palm subcylindrical, about 4.0 times longer than distal width, covered with minutely blunt tubercles and simple setae; carpus about 0.45 of palm length, about 2 times longer than distal width; merus about 2.0 times as long as carpus, as long as palm length, about 6.2 times longer than distal width; ischium as long as carpus length, about 6.0 times longer than distal width; basis and coxa without special features.</ns0:p><ns0:p>Minor second pereiopod (Fig. <ns0:ref type='figure' target='#fig_4'>5F, G</ns0:ref>) slightly overreaching distal end of scaphocerite; chela about 0.4 of pocl, 0.7 of major chela length, with group of terminal setae; fingers about 0.7 of palm length, distally curved with acute tips, cutting edge entire; palm subcylindrical, about 3 times longer than distal width, smooth slightly tapering proximally; carpus about 1.4 of palm length, about 0.9 of chela length, about 5.6 times longer than distal width; merus about 1.1 times as long as carpus length, about 7.8 times longer than distal width; ischium about 1.1 times as long as merus length, about 7.8 times longer than distal width; basis and coxa without special features.</ns0:p><ns0:p>Ambulatory pereiopods (Figs. <ns0:ref type='figure' target='#fig_5'>2 and 6</ns0:ref>) subequal in shape and size. Third pereiopod (Fig. <ns0:ref type='figure' target='#fig_5'>6A, B</ns0:ref>) overreaching distal end of rostrum by distal end of propodus; dactylus about 0.26 of propodus length, about 4.2 times longer than proximal width, not biunguiculate; propodus about 10 times longer than distal width, ventral border with four distolateral spiniform setae including pair distoventral one, with long setae distally, with distodorsal plumose setae and distal setae; carpus about 0.54 times length of propodus, unarmed; merus as long as carpus length, unarmed; ischium about 0.5 length of propodus, unarmed; basis and coxa without special features. Fourth and fifth pereiopods (Fig. <ns0:ref type='figure' target='#fig_5'>6C-F</ns0:ref>) similar to third pereiopod. Uropod (Figs. <ns0:ref type='figure' target='#fig_2'>2 and 3E</ns0:ref>) overreaching distal end of telson; exopod with distolateral tooth and movable acute tooth. Variation. <ns0:ref type='bibr' target='#b9'>Bruce (1996)</ns0:ref> described Mesopontonia verrucimanus based on a single specimen (holotype), with nine dorsal teeth, unarmed ventrally and markedly unequal, dissimilar second pereiopods. TheKorean specimens exhibit morphological variation in rostral dentition and the major second pereiopod. The number of dorsal and ventral rostral teeth (Figs. <ns0:ref type='figure' target='#fig_2'>2 and 3A-D</ns0:ref>) varies from 6-9 and 0-2 respectively. A single specimen (Fig. <ns0:ref type='figure' target='#fig_2'>3D</ns0:ref>) harbours two epigastric teeth on the carapace. Several specimens (Fig. <ns0:ref type='figure'>2B</ns0:ref>) bear two symmetrical second pereiopods, which are very similar to the minor second pereiopods in the original description and in other Korean specimens <ns0:ref type='bibr'>(Fig 2A)</ns0:ref>. Color in life. Whole body and appendages almost transparent with scattered emerald green chromatophores (Fig. <ns0:ref type='figure' target='#fig_6'>7</ns0:ref>); longitudinal pale red band along the ventral surface of the body from the carapace to the fifth abdominal somite. Geographical distribution. Presently known from the Tanimbar Islands (Indonesia) and Jejudo Island (Republic of Korea) (Fig. <ns0:ref type='figure'>1</ns0:ref>). Habitat and host. The present specimens were obtained from gorgonian and sponge colonies below 50 m (Fig. <ns0:ref type='figure' target='#fig_11'>14A, B</ns0:ref>), with the deepest samples from 75 m depth. The present specimens demonstrate a lack of host specificity and the species cannot be considered as restricted to gorgonians, as previously postulated. Most specimens were collected on the orange colored sea whip, Ellisella cf. limbaughi <ns0:ref type='bibr'>(Bayer &amp; Deichmann 1960)</ns0:ref>, with further specimens obtained on the white colored gorgonian, Cirrhipathes cf. anguina <ns0:ref type='bibr' target='#b18'>(Dana, 1846)</ns0:ref>, as well as the orange colored sponge, Raspailia (Raspaxilla) hirsuta Thiele, 1898. A single specimen was collected on the white colored antipatharian, Myriopathes lata <ns0:ref type='bibr' target='#b55'>(Silberfeld, 1909)</ns0:ref>.</ns0:p><ns0:p>Mesopontonia verrucimanus can be immediately separated from most other species in the genus which have a biunguiculate dactylus of ambulatory pereiopods, except M. monodactylus with which it shares a non-biunguiculate dactylus. M. monodactylus differs from M. verrucimanus primarily by having a distinct dorsolateral flange on the chela of the major second pereiopod <ns0:ref type='bibr' target='#b7'>(Bruce 1991;</ns0:ref><ns0:ref type='bibr' target='#b9'>Bruce 1996)</ns0:ref>. Mesopontonia kimwoni sp. nov. urn:lsid:zoobank.org:act:BBA317A3-7140-4D97-BCF4-DB6EEF6617F5 Figs. 8-12 Material examined. Type material. Holotype. 1 ovigerous female (pocl 2.5, R 1+8/2); Jun. 21, 2018; Munseom Islet, Jejudo Island (33&#176;13'31'N 126&#176;34'11'E), 55m, on Myriopathes lata <ns0:ref type='bibr' target='#b55'>(Silberfeld, 1909)</ns0:ref>, leg. JH Park (NIBRIV0000862985). Paratype. 1 ovigerous female (pocl 2.8, R 1+8/2); Aug. 16, 2019; same location (33&#176;13'41'N 126&#176;34'6'E), 53m, on M. lata, leg. JH Park (NIBRIV0000862994). Description. Body (Fig. <ns0:ref type='figure' target='#fig_7'>8</ns0:ref>) small-sized, subcylindrical form. Rostrum (Figs. <ns0:ref type='figure' target='#fig_8'>8 and 9A</ns0:ref>) straight, horizontal, almost as long as pocl, reaching or slightly beyond end of antennular peduncle, 8 dorsal teeth, along entire length, 2 subterminal ventral teeth.</ns0:p><ns0:p>Carapace (Fig. <ns0:ref type='figure' target='#fig_7'>8</ns0:ref>) smooth, glabrous, with epigastric tooth at anterior 0.3 of pocl; without supraorbital and antennal teeth; inferior orbital angle produced; hepatic tooth large, acute, extending to anterior margin of carapace; pterygostomial angle bluntly rounded.</ns0:p><ns0:p>Abdomen (Fig. <ns0:ref type='figure' target='#fig_7'>8</ns0:ref>) smooth; pleura of first five segments rounded; sixth pleura with pointed posterolateral angle, posteroventral angle subacute.</ns0:p><ns0:p>Telson (Figs. 8 and 9D) 0.8 of pocl, 4.0 times as long as proximal width; two pairs of small dorsal spiniform setae at 0.45 and 0.7 of telson length respectively, with three pairs of posterior spiniform setae, lateral pair shortest, medial pair long and stout.</ns0:p><ns0:p>Eye (Figs. 8 and 9B-C) with hemispherical cornea, dorsolaterally with nebenauge, diameter about 0.23 of pocl.</ns0:p><ns0:p>Antennule (Fig. <ns0:ref type='figure' target='#fig_8'>9B</ns0:ref>) with proximal peduncle bearing distolateral tooth, with small acute tooth at ventromedial margin; stylocerite narrow, bearing sharp point, reaching to 0.45 times of proximal segment; intermediate segment short, 0.3 times of proximal segment length, subequal to distal segment; upper flagellum biramous, proximal four segments fused, lower flagellum slender, filiform.</ns0:p><ns0:p>Antenna (Figs. <ns0:ref type='figure' target='#fig_8'>8 and 9B</ns0:ref>) basicerite with sharp pointed distodorsal margin; ischiocerite and merocerite unarmed; carpocerite reaching to about 0.4 of scaphocerite length; scaphocerite 4 times as long as maximal width, lateral margin rounded, medial margin convex, distolateral tooth large, at 0.9 of lamella length.</ns0:p><ns0:p>Mouthparts not dissected. Third maxilliped (Fig. <ns0:ref type='figure' target='#fig_8'>9F</ns0:ref>) without exopod, reaching to 0.7 of carpocerite; ultimate segment about 0.35 of antepenultimate segment length, tapering distally, with transverse rows of setae; penultimate segment about 0.7 of antepenultimate segment length, with sparsely row of long setae ventromedially; ischiomerus completely fused to basis, antepenultimate segment feebly compressed distally, with long setae ventromedially; coxa with rounded medial lobe, with rounded lateral plate.</ns0:p><ns0:p>First pereiopod (Figs. 8 and 9A, B) overreaching distal end of scaphocerite; fingers about 0.6 of palm length, tips hooked, cutting edge entire, with transverse row of setae and group of terminal setae; palm ventrolaterally with transverse row of serrulate setae; carpus 1.1 times length of chela with row of serrulate setae along distomesial margin; merus 1.1 times length of carpus; ischium about 0.5 times length of merus; basis and coxa without special features.</ns0:p><ns0:p>Second pereiopods (Figs. 8 and 10C-G) well developed, similar in shape, unequal in size. Major second pereiopod (Fig. <ns0:ref type='figure'>10C-E</ns0:ref>) overreaching distal end of rostrum by middle of propodus; chela about 1.3 times as long as pocl, with group of terminal setae; fingers about 0.4 of palm length; dactylus slender, about 3.8 times longer than proximal depth, distally curved with acute tip, proximally with two blunt teeth at proximal 0.3 and 0.4, distally entire without dorsolateral flange; fixed finger with distally curved with acute tip, proximally with single acute tooth at 0.4, distally entire; palm subcylindrical, about 4.2 times longer than distal width, covered with minutely blunt tubercles and short simple setae; carpus about 0.4 of palm length, about 2.8 times longer than distal width; merus about 2.1 times as long as carpus, about 0.8 of palm length, 7.0 times longer than distal width; ischium subequal to carpus length, about 7.0 times longer than distal width; basis and coxa without special features.</ns0:p><ns0:p>Minor second pereiopod (Fig. <ns0:ref type='figure'>10F, G</ns0:ref>) overreaching distal end of rostrum by end of carpus; chela about 0.7 of pocl, 0.7 of major chela length, with group of terminal setae; fingers about 0.7 of palm length, with distally curved with acute tips, cutting edge entire; palm subcylindrical, about 3.75 times longer than distal width, smooth, slightly tapering proximally; carpus about 1.3 of palm length, about 0.75 of chela length, about 7.2 times longer than distal width; merus about 1.1 times as long as carpus length, about 9 times longer than distal width; ischium about 0.9 of merus length, about 10 times longer than distal width; basis and coxa without special features.</ns0:p><ns0:p>Ambulatory pereiopods (Figs. 8 and 11) subequal in shape and size, only third pereiopod with distodorsal plumose setae and distal serrulate setae on propodus. Third pereiopod (Fig. <ns0:ref type='figure' target='#fig_9'>11A, B</ns0:ref>) overreaching distal end of rostrum by distal half of propodus; dactylus about 0.2 of propodus, about 4 times longer than proximal width, about 0.65 of corpus length, biunguiculate; propodus about 0.8 of pocl, 16 times longer than distal width, ventral border with four distolateral spiniform setae including single distoventral one, with long setae distally; carpus about 0.4 times length of propodus, unarmed; merus about 0.9 times length of propodus, unarmed; ischium about 0.5 length of propodus, unarmed; basis and coxa without special features.</ns0:p><ns0:p>Fourth pereiopod (Fig. <ns0:ref type='figure' target='#fig_9'>11C, D</ns0:ref>) with dactylus about 0.2 times length of propodus, about 4 times longer than proximal width, about 0.65 of corpus length, biunguiculate; propodus with four distolateral spiniform setae including single distoventral one, with long simple setae distally; carpus about 0.45 times length of propodus, unarmed; merus subequal to propodus length, unarmed; ischium about 0.46 length of propodus; basis and coxa without special feature. Fifth pereiopod (Fig. <ns0:ref type='figure' target='#fig_9'>11E</ns0:ref>) similar to fourth pereiopod.</ns0:p><ns0:p>Uropod (Figs. 11D) overreaching distal end of telson; exopod with distolateral tooth and movable acute tooth. Etymology. The specific name 'kimwoni' is in honor of Dr. Kim, Won, professor in the School of Biological Sciences, Seoul National University. He made a considerable contribution to the systematics of Korean crustaceans. Color in life. Whole body and appendages almost transparent (Figs. 12 and 13); longitudinal red bands along the ventral surface of the body from antennular peduncle to the fifth abdominal somite; tiny white and red chromatophore scattered along the dorsal surface of cornea of eyes, proximal segment of antennular peduncle and abdomen. Type locality. Munseom Islet, Jejudo Island, Korea Geographical distribution. Presently only known for the type locality. Habitat. The two specimens of M. kimwoni sp. nov. were collected from the gorgonian antipatharian, Myriopathes lata <ns0:ref type='bibr' target='#b55'>(Silberfeld, 1909)</ns0:ref> in 53-55 m (Fig. <ns0:ref type='figure' target='#fig_11'>14C</ns0:ref>). Remarks. Based on the presence of the biunguiculate dactyli of ambulatory pereiopods, the new species is morphologically allied to four species: M. brevicarpus <ns0:ref type='bibr' target='#b41'>Li &amp; Bruce, 2006</ns0:ref><ns0:ref type='bibr'>, M. brucei Burukovsky, 1991</ns0:ref><ns0:ref type='bibr'>, M. gorgoniophila Bruce, 1967</ns0:ref><ns0:ref type='bibr'>, and M. gracilicarpus Bruce, 1990</ns0:ref>; and can be easily separated from the remaining two species in the genus (M. monodactylus <ns0:ref type='bibr' target='#b7'>Bruce, 1991</ns0:ref><ns0:ref type='bibr'>, M. verrucimanus Bruce, 1996)</ns0:ref> which have simple dactyli. The new species differs from M. gorgoniophila by the straight distodorsal carina in the major second pereiopod (vs. oblique distodorsal carina in M. gorgoniophila), with two teeth on the cutting edge of dacytlus of major second pereiopod (vs. with single tooth in M. gorgoniophila), dorsolateral dactylar flange of major second pereiopod absent (vs. present in M. gorgoniophila), as well as the proportions of the carpus of the minor second pereiopod (about 1.3 time palm length in M. kimwoni sp. nov. vs. about 0.8 in M. gorgoniophila). The new species differs from M. gracilicarpus primarily by the relative short size of the carpus of the first pereiopods (about 1.1 times the chela length in M. kimwoni sp. nov., vs. about 1.4 in M. gracilicarpus), as well as the proportions of the carpus of the minor second pereiopod (0.8 times chela length in M. kimwoni sp. nov. vs. about 1.5 in M. gracilicarpus). The new species can be distinguished from M. brucei by the presence of a minute tubercle on the chela of the major second pereiopod (vs. absent in M. brucei), relatively long fingers of first pereiopod (about 0.6 of palm length in M. kimwoni sp. nov. vs. about 0.5 in M. brucei), relatively short carpus of major second pereiopod (about 0.4 of the palm length in M. kimwoni sp. nov. vs 0.6 in M. brucei) and the relatively long carpus of the minor second pereiopod (about 1.3 times the palm length in M. kimwoni sp. nov. vs. about 0.9 in M. brucei).</ns0:p><ns0:p>M. kimwoni sp. nov., appears most closely related to the west Indian species, M. brevicarpus, sharing a similar rostral formulation, a tuberculate major second pereiopod chela, as well as the ratio of the ambulatory pereiopods. Both species can be most easily distinguished on the basis of the combination of the following characters, 1) fingers of first chela with entire cutting edge (vs. fine pectinated serrations subapically on both fingers in M. brevicarpus); 2) hepatic tooth reaching to the anterior margin of the carapace (vs. reaching or extending to anterior margin of carapace in M. brevicarpus) and 3) the finger of minor chela being about 0.7 of the palm length (vs. fingers subequal to palm in M. brevicarpus). <ns0:ref type='bibr' target='#b9'>Bruce (1996)</ns0:ref> suggested two further new species may be present in the genus, one collected from Indonesia <ns0:ref type='bibr' target='#b9'>(Bruce, 1996)</ns0:ref>, as well as the juvenile specimen assigned to M. gorgoniophila in <ns0:ref type='bibr' target='#b4'>Bruce (1985)</ns0:ref>, both however were left unnamed. Given their incomplete or juvenile status these taxa are not considered herein, but are unlikely to be the same species as M. kimwoni, as the details of the first and second pereiopods are different.</ns0:p></ns0:div> <ns0:div><ns0:head>Molecular data analyses</ns0:head><ns0:p>Fragments of 658 and 462 bp were obtained for the COI and 16S markers, respectively. The multiple sequence alignment revealed that the K2P distance between the five specimens of M. verrucimanus which showed minor morphological variations in the dentition of the rostrum and proportions of the second pereiopods fall within an intraspecific range, being 0-0.5% (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>). The intraspecific divergence between both specimens of M. kimwoni sp. nov. was higher at 1.1% (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>).</ns0:p><ns0:p>To eludicate the phylogenetic position of the genus, an analysis was performed on 22 specimens of 16 species of 12 genera (Table <ns0:ref type='table'>1</ns0:ref>). The ML and BI analyses showed the same topology (Fig. <ns0:ref type='figure' target='#fig_12'>15</ns0:ref>), and the combined phylogenetic tree clearly demonstrated the monophyly of Mesopontonia with high support values (BP =100, PP=100). Furthermore, their distant relationship was supported by the K2P distance, which was 13.6% (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>).</ns0:p><ns0:p>From the concatenated tree in the present analysis,the genera Mesopontonia and Paraclimenes are postulated to be sister taxa with high support values (BP=100, PP=92), indicating that they are more genetically related to each other than the remaining analysed genera, supported by morphological similarities.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The present study explored the commensal palaemonid fauna of Jejudo Island, recording Mesopontonia kimwoni sp. nov. and M. verrucimanus at higher latitude temperate waters than the genus was previously known from. While the six species previously known in the genus had been reported from between 117 and 600 m depth by trawling and dredging <ns0:ref type='bibr' target='#b1'>(Bruce 1967;</ns0:ref><ns0:ref type='bibr' target='#b2'>Bruce 1979;</ns0:ref><ns0:ref type='bibr' target='#b3'>Bruce 1984;</ns0:ref><ns0:ref type='bibr' target='#b4'>Bruce 1985;</ns0:ref><ns0:ref type='bibr'>Bruce;</ns0:ref><ns0:ref type='bibr' target='#b5'>1990a;</ns0:ref><ns0:ref type='bibr' target='#b7'>Bruce 1991;</ns0:ref><ns0:ref type='bibr' target='#b9'>Bruce, 1996;</ns0:ref><ns0:ref type='bibr'>Burukovsy, 1991;</ns0:ref><ns0:ref type='bibr' target='#b41'>Li &amp; Bruce, 2006)</ns0:ref>, the present specimens were collected from shallower depths of less than 75 m. As they were directly collected with technical SCUBA diving equipment, more details are available on their habitat and ecology, whilst color patterns are recorded for the first time for the genus as a whole.</ns0:p><ns0:p>Mesopontonia kimwoni sp. nov. can be distinguished from all other Mesopontonia species by the combination of the biunguiculate dactylus of the ambulatory pereiopods, the lack of a dorsolateral dactylar flange on the major second chela, the relatively long carpus of the minor second pereiopod and the entire cutting edge of fingers of first chela. Specimens of M. verrucimanus exhibited minor morphological variation in rostral dentition and proportions of the major second pereiopod, but all specimens are clearly conspecific.</ns0:p><ns0:p>Due to its rarity, Mesopontonia had not been previously included in family level phylogenies (e.g. <ns0:ref type='bibr' target='#b33'>Kou et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b28'>Gan et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b30'>Hork&#225; et al. 2016)</ns0:ref>, but is herein shown to be phylogenetically close to Paraclimenes. This is also supported by a relatively similar morphology with both antennal and supraorbital teeth being absent; and the epigastric and hepatic teeth being present. Nevertheless, Paraclimenes can be readily distinguished from Mesopontonia by the presence of a well-developed exopod on the third maxilliped <ns0:ref type='bibr' target='#b8'>(Bruce 1995)</ns0:ref>. Table <ns0:ref type='table'>1</ns0:ref>: Species used in the phylogenetic analysis with GenBank accession numbers and source. Used symbols: N/A -not available. Pairwise distances of COI sequences and selected morphological characteristics for specimens used in the analysis. (P2 -second pereiopods). </ns0:p></ns0:div> <ns0:div><ns0:head>Key to species of</ns0:head></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Mesopontonia Bruce, 1967 (Adapted from Bruce, 1996; Li &amp; Bruce, 2006) 1. Dactylus of ambulatory pereiopods simple............................................................................2 -Dactylus of ambulatory pereiopods biunguiculate.......................................................................3 2. Major second pereiopod with dorsolateral dactylar flange ...........M. monodactylus Bruce, 1991 -Major second pereiopod without dorsolateral dactylar flange ......M. verrucimanus Bruce, 1996 3. Major second pereiopod with dorsolateral dactylar flange ..........M. gorgoniophila Bruce, 1967 -Major second pereiopod without dorsolateral dactylar flange ............................................4 4. Carpus of minor second pereiopod longer than chela ...................M. gracilicarpus Bruce, 1990 -Carpus of minor second pereiopod shorter than chela ........................................................5 5. Carpus of minor second pereiopod shorter than palm ....................M. brucei Burukovsky, 1991 -Carpus of minor second pereiopod longer than palm .................................................................6 6. Fingers of first chela with pectinated serrations, subapically..M. brevicarpus Li &amp; Bruce, 2006 -Fingers of first chela with clear entire cutting edge; R. 1+8/2 .....................M. kimwoni sp. nov. Abbreviations used in text, tables and figures PeerJ reviewing PDF | (2020:06:50042:2:0:NEW 19 Sep 2020) Manuscript to be reviewed BI Bayesian Inference BP Maximum likelihood bootstrap percentage K2P Kimura 2-parameter ML Maximum likelihood POCL postorbital carapace length PP Bayesian posterior probabilities R Rostrum formula; formulation of epigastric tooth and teeth on rostrum.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 Figure 2</ns0:head><ns0:label>12</ns0:label><ns0:figDesc>Figure 1 Map of Indo West Pacific Ocean (IWP). Map showing (A) distribution of Mesopontonia species, (B) location of Jejudo Island, and (C) the type locality of M. kimwoni sp. nov. Figure 2 Mesopontonia verrucimanus Bruce, 1996, habitus, lateral view. (A) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989); (B) male, pocl 3.2 mm (NIBRIV0000862991).Figure 3 Mesopontonia verrucimanus Bruce, 1996. (A) Frontal margin and rostrum, lateral view; (B, C) same, lateral view; (D) same, lateral view; (E) telson and uropods, dorso-lateral view; (F) distal end of telson, dorsal view. (A, E, F) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (B) Male, pocl 2.7 mm (NIBRIV0000862982); (C) Female, 2.78 mm (NIBRIV0000862978); (D) Male, pocl 2.5 mm (SNU KR JH1095).Figure 4 Mesopontonia verrucimanus Bruce, 1996. (A) Left eye, dorsal view; (B) left antennule, dorsal view; (C) left antenna, dorsal view; (D) left third maxilliped. (A-C) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (D) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989).Figure 5 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left first pereiopod. (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 6 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod; (F) same, dactylus and distal propodus.Figure 7 Mesopontonia verrucimanus Bruce, 1996 on Ellisella limbaughi Bayer &amp; Deichmann, 1960 from Munseom Islet, Jejudo Island. (A) Female specimen, pocl 2.5 mm (MADBK 120533_004); (B) male specimens, pocl 3.0 mm (MADBK 120533_003). Photographic Credits: (A) Jin-Ho Park, (B) Jong Moon Choi.Figure 8 Mesopontonia kimwoni sp. nov., habitus, lateral view. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985).Figure 9 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) frontal margin and rostrum, lateral view; (B) frontal region, dorsal view; (C) left eye, dorsal view; (D) left antenna, ventral view; (E) telson and uropod, dorsal view; (F) distal end of telson, dorsal view; (G) left third maxilliped, mesial view. Figure 10 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left first pereiopod; (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 11 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod. Figure 12 Mesopontonia kimwoni sp. nov. from Munseom Islet, Jejudo Island. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Photographic credit: Jin-Ho Park.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 1 Map of Indo West Pacific Ocean (IWP). Map showing (A) distribution of Mesopontonia species, (B) location of Jejudo Island, and (C) the type locality of M. kimwoni sp. nov. Figure 2 Mesopontonia verrucimanus Bruce, 1996, habitus, lateral view. (A) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989); (B) male, pocl 3.2 mm (NIBRIV0000862991).Figure 3 Mesopontonia verrucimanus Bruce, 1996. (A) Frontal margin and rostrum, lateral view; (B, C) same, lateral view; (D) same, lateral view; (E) telson and uropods, dorso-lateral view; (F) distal end of telson, dorsal view. (A, E, F) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (B) Male, pocl 2.7 mm (NIBRIV0000862982); (C) Female, 2.78 mm (NIBRIV0000862978); (D) Male, pocl 2.5 mm (SNU KR JH1095).Figure 4 Mesopontonia verrucimanus Bruce, 1996. (A) Left eye, dorsal view; (B) left antennule, dorsal view; (C) left antenna, dorsal view; (D) left third maxilliped. (A-C) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (D) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989).Figure 5 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left first pereiopod. (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 6 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod; (F) same, dactylus and distal propodus.Figure 7 Mesopontonia verrucimanus Bruce, 1996 on Ellisella limbaughi Bayer &amp; Deichmann, 1960 from Munseom Islet, Jejudo Island. (A) Female specimen, pocl 2.5 mm (MADBK 120533_004); (B) male specimens, pocl 3.0 mm (MADBK 120533_003). Photographic Credits: (A) Jin-Ho Park, (B) Jong Moon Choi.Figure 8 Mesopontonia kimwoni sp. nov., habitus, lateral view. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985).Figure 9 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) frontal margin and rostrum, lateral view; (B) frontal region, dorsal view; (C) left eye, dorsal view; (D) left antenna, ventral view; (E) telson and uropod, dorsal view; (F) distal end of telson, dorsal view; (G) left third maxilliped, mesial view. Figure 10 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left first pereiopod; (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 11 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod. Figure 12 Mesopontonia kimwoni sp. nov. from Munseom Islet, Jejudo Island. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Photographic credit: Jin-Ho Park.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 1 Map of Indo West Pacific Ocean (IWP). Map showing (A) distribution of Mesopontonia species, (B) location of Jejudo Island, and (C) the type locality of M. kimwoni sp. nov. Figure 2 Mesopontonia verrucimanus Bruce, 1996, habitus, lateral view. (A) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989); (B) male, pocl 3.2 mm (NIBRIV0000862991).Figure 3 Mesopontonia verrucimanus Bruce, 1996. (A) Frontal margin and rostrum, lateral view; (B, C) same, lateral view; (D) same, lateral view; (E) telson and uropods, dorso-lateral view; (F) distal end of telson, dorsal view. (A, E, F) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (B) Male, pocl 2.7 mm (NIBRIV0000862982); (C) Female, 2.78 mm (NIBRIV0000862978); (D) Male, pocl 2.5 mm (SNU KR JH1095).Figure 4 Mesopontonia verrucimanus Bruce, 1996. (A) Left eye, dorsal view; (B) left antennule, dorsal view; (C) left antenna, dorsal view; (D) left third maxilliped. (A-C) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (D) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989).Figure 5 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left first pereiopod. (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 6 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod; (F) same, dactylus and distal propodus.Figure 7 Mesopontonia verrucimanus Bruce, 1996 on Ellisella limbaughi Bayer &amp; Deichmann, 1960 from Munseom Islet, Jejudo Island. (A) Female specimen, pocl 2.5 mm (MADBK 120533_004); (B) male specimens, pocl 3.0 mm (MADBK 120533_003). Photographic Credits: (A) Jin-Ho Park, (B) Jong Moon Choi.Figure 8 Mesopontonia kimwoni sp. nov., habitus, lateral view. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985).Figure 9 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) frontal margin and rostrum, lateral view; (B) frontal region, dorsal view; (C) left eye, dorsal view; (D) left antenna, ventral view; (E) telson and uropod, dorsal view; (F) distal end of telson, dorsal view; (G) left third maxilliped, mesial view. Figure 10 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left first pereiopod; (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 11 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod. Figure 12 Mesopontonia kimwoni sp. nov. from Munseom Islet, Jejudo Island. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Photographic credit: Jin-Ho Park.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 1 Map of Indo West Pacific Ocean (IWP). Map showing (A) distribution of Mesopontonia species, (B) location of Jejudo Island, and (C) the type locality of M. kimwoni sp. nov. Figure 2 Mesopontonia verrucimanus Bruce, 1996, habitus, lateral view. (A) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989); (B) male, pocl 3.2 mm (NIBRIV0000862991).Figure 3 Mesopontonia verrucimanus Bruce, 1996. (A) Frontal margin and rostrum, lateral view; (B, C) same, lateral view; (D) same, lateral view; (E) telson and uropods, dorso-lateral view; (F) distal end of telson, dorsal view. (A, E, F) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (B) Male, pocl 2.7 mm (NIBRIV0000862982); (C) Female, 2.78 mm (NIBRIV0000862978); (D) Male, pocl 2.5 mm (SNU KR JH1095).Figure 4 Mesopontonia verrucimanus Bruce, 1996. (A) Left eye, dorsal view; (B) left antennule, dorsal view; (C) left antenna, dorsal view; (D) left third maxilliped. (A-C) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (D) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989).Figure 5 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left first pereiopod. (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 6 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod; (F) same, dactylus and distal propodus.Figure 7 Mesopontonia verrucimanus Bruce, 1996 on Ellisella limbaughi Bayer &amp; Deichmann, 1960 from Munseom Islet, Jejudo Island. (A) Female specimen, pocl 2.5 mm (MADBK 120533_004); (B) male specimens, pocl 3.0 mm (MADBK 120533_003). Photographic Credits: (A) Jin-Ho Park, (B) Jong Moon Choi.Figure 8 Mesopontonia kimwoni sp. nov., habitus, lateral view. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985).Figure 9 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) frontal margin and rostrum, lateral view; (B) frontal region, dorsal view; (C) left eye, dorsal view; (D) left antenna, ventral view; (E) telson and uropod, dorsal view; (F) distal end of telson, dorsal view; (G) left third maxilliped, mesial view. Figure 10 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left first pereiopod; (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 11 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod. Figure 12 Mesopontonia kimwoni sp. nov. from Munseom Islet, Jejudo Island. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Photographic credit: Jin-Ho Park.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 1 Map of Indo West Pacific Ocean (IWP). Map showing (A) distribution of Mesopontonia species, (B) location of Jejudo Island, and (C) the type locality of M. kimwoni sp. nov. Figure 2 Mesopontonia verrucimanus Bruce, 1996, habitus, lateral view. (A) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989); (B) male, pocl 3.2 mm (NIBRIV0000862991).Figure 3 Mesopontonia verrucimanus Bruce, 1996. (A) Frontal margin and rostrum, lateral view; (B, C) same, lateral view; (D) same, lateral view; (E) telson and uropods, dorso-lateral view; (F) distal end of telson, dorsal view. (A, E, F) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (B) Male, pocl 2.7 mm (NIBRIV0000862982); (C) Female, 2.78 mm (NIBRIV0000862978); (D) Male, pocl 2.5 mm (SNU KR JH1095).Figure 4 Mesopontonia verrucimanus Bruce, 1996. (A) Left eye, dorsal view; (B) left antennule, dorsal view; (C) left antenna, dorsal view; (D) left third maxilliped. (A-C) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (D) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989).Figure 5 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left first pereiopod. (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 6 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod; (F) same, dactylus and distal propodus.Figure 7 Mesopontonia verrucimanus Bruce, 1996 on Ellisella limbaughi Bayer &amp; Deichmann, 1960 from Munseom Islet, Jejudo Island. (A) Female specimen, pocl 2.5 mm (MADBK 120533_004); (B) male specimens, pocl 3.0 mm (MADBK 120533_003). Photographic Credits: (A) Jin-Ho Park, (B) Jong Moon Choi.Figure 8 Mesopontonia kimwoni sp. nov., habitus, lateral view. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985).Figure 9 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) frontal margin and rostrum, lateral view; (B) frontal region, dorsal view; (C) left eye, dorsal view; (D) left antenna, ventral view; (E) telson and uropod, dorsal view; (F) distal end of telson, dorsal view; (G) left third maxilliped, mesial view. Figure 10 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left first pereiopod; (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 11 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod. Figure 12 Mesopontonia kimwoni sp. nov. from Munseom Islet, Jejudo Island. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Photographic credit: Jin-Ho Park.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 7</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 1 Map of Indo West Pacific Ocean (IWP). Map showing (A) distribution of Mesopontonia species, (B) location of Jejudo Island, and (C) the type locality of M. kimwoni sp. nov. Figure 2 Mesopontonia verrucimanus Bruce, 1996, habitus, lateral view. (A) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989); (B) male, pocl 3.2 mm (NIBRIV0000862991).Figure 3 Mesopontonia verrucimanus Bruce, 1996. (A) Frontal margin and rostrum, lateral view; (B, C) same, lateral view; (D) same, lateral view; (E) telson and uropods, dorso-lateral view; (F) distal end of telson, dorsal view. (A, E, F) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (B) Male, pocl 2.7 mm (NIBRIV0000862982); (C) Female, 2.78 mm (NIBRIV0000862978); (D) Male, pocl 2.5 mm (SNU KR JH1095).Figure 4 Mesopontonia verrucimanus Bruce, 1996. (A) Left eye, dorsal view; (B) left antennule, dorsal view; (C) left antenna, dorsal view; (D) left third maxilliped. (A-C) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (D) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989).Figure 5 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left first pereiopod. (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 6 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod; (F) same, dactylus and distal propodus.Figure 7 Mesopontonia verrucimanus Bruce, 1996 on Ellisella limbaughi Bayer &amp; Deichmann, 1960 from Munseom Islet, Jejudo Island. (A) Female specimen, pocl 2.5 mm (MADBK 120533_004); (B) male specimens, pocl 3.0 mm (MADBK 120533_003). Photographic Credits: (A) Jin-Ho Park, (B) Jong Moon Choi.Figure 8 Mesopontonia kimwoni sp. nov., habitus, lateral view. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985).Figure 9 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) frontal margin and rostrum, lateral view; (B) frontal region, dorsal view; (C) left eye, dorsal view; (D) left antenna, ventral view; (E) telson and uropod, dorsal view; (F) distal end of telson, dorsal view; (G) left third maxilliped, mesial view. Figure 10 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left first pereiopod; (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 11 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod. Figure 12 Mesopontonia kimwoni sp. nov. from Munseom Islet, Jejudo Island. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Photographic credit: Jin-Ho Park.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 1 Map of Indo West Pacific Ocean (IWP). Map showing (A) distribution of Mesopontonia species, (B) location of Jejudo Island, and (C) the type locality of M. kimwoni sp. nov. Figure 2 Mesopontonia verrucimanus Bruce, 1996, habitus, lateral view. (A) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989); (B) male, pocl 3.2 mm (NIBRIV0000862991).Figure 3 Mesopontonia verrucimanus Bruce, 1996. (A) Frontal margin and rostrum, lateral view; (B, C) same, lateral view; (D) same, lateral view; (E) telson and uropods, dorso-lateral view; (F) distal end of telson, dorsal view. (A, E, F) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (B) Male, pocl 2.7 mm (NIBRIV0000862982); (C) Female, 2.78 mm (NIBRIV0000862978); (D) Male, pocl 2.5 mm (SNU KR JH1095).Figure 4 Mesopontonia verrucimanus Bruce, 1996. (A) Left eye, dorsal view; (B) left antennule, dorsal view; (C) left antenna, dorsal view; (D) left third maxilliped. (A-C) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (D) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989).Figure 5 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left first pereiopod. (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 6 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod; (F) same, dactylus and distal propodus.Figure 7 Mesopontonia verrucimanus Bruce, 1996 on Ellisella limbaughi Bayer &amp; Deichmann, 1960 from Munseom Islet, Jejudo Island. (A) Female specimen, pocl 2.5 mm (MADBK 120533_004); (B) male specimens, pocl 3.0 mm (MADBK 120533_003). Photographic Credits: (A) Jin-Ho Park, (B) Jong Moon Choi.Figure 8 Mesopontonia kimwoni sp. nov., habitus, lateral view. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985).Figure 9 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) frontal margin and rostrum, lateral view; (B) frontal region, dorsal view; (C) left eye, dorsal view; (D) left antenna, ventral view; (E) telson and uropod, dorsal view; (F) distal end of telson, dorsal view; (G) left third maxilliped, mesial view. Figure 10 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left first pereiopod; (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 11 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod. Figure 12 Mesopontonia kimwoni sp. nov. from Munseom Islet, Jejudo Island. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Photographic credit: Jin-Ho Park.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 9</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Figure 1 Map of Indo West Pacific Ocean (IWP). Map showing (A) distribution of Mesopontonia species, (B) location of Jejudo Island, and (C) the type locality of M. kimwoni sp. nov. Figure 2 Mesopontonia verrucimanus Bruce, 1996, habitus, lateral view. (A) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989); (B) male, pocl 3.2 mm (NIBRIV0000862991).Figure 3 Mesopontonia verrucimanus Bruce, 1996. (A) Frontal margin and rostrum, lateral view; (B, C) same, lateral view; (D) same, lateral view; (E) telson and uropods, dorso-lateral view; (F) distal end of telson, dorsal view. (A, E, F) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (B) Male, pocl 2.7 mm (NIBRIV0000862982); (C) Female, 2.78 mm (NIBRIV0000862978); (D) Male, pocl 2.5 mm (SNU KR JH1095).Figure 4 Mesopontonia verrucimanus Bruce, 1996. (A) Left eye, dorsal view; (B) left antennule, dorsal view; (C) left antenna, dorsal view; (D) left third maxilliped. (A-C) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (D) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989).Figure 5 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left first pereiopod. (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 6 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod; (F) same, dactylus and distal propodus.Figure 7 Mesopontonia verrucimanus Bruce, 1996 on Ellisella limbaughi Bayer &amp; Deichmann, 1960 from Munseom Islet, Jejudo Island. (A) Female specimen, pocl 2.5 mm (MADBK 120533_004); (B) male specimens, pocl 3.0 mm (MADBK 120533_003). Photographic Credits: (A) Jin-Ho Park, (B) Jong Moon Choi.Figure 8 Mesopontonia kimwoni sp. nov., habitus, lateral view. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985).Figure 9 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) frontal margin and rostrum, lateral view; (B) frontal region, dorsal view; (C) left eye, dorsal view; (D) left antenna, ventral view; (E) telson and uropod, dorsal view; (F) distal end of telson, dorsal view; (G) left third maxilliped, mesial view. Figure 10 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left first pereiopod; (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 11 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod. Figure 12 Mesopontonia kimwoni sp. nov. from Munseom Islet, Jejudo Island. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Photographic credit: Jin-Ho Park.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 11</ns0:head><ns0:label>11</ns0:label><ns0:figDesc>Figure 1 Map of Indo West Pacific Ocean (IWP). Map showing (A) distribution of Mesopontonia species, (B) location of Jejudo Island, and (C) the type locality of M. kimwoni sp. nov. Figure 2 Mesopontonia verrucimanus Bruce, 1996, habitus, lateral view. (A) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989); (B) male, pocl 3.2 mm (NIBRIV0000862991).Figure 3 Mesopontonia verrucimanus Bruce, 1996. (A) Frontal margin and rostrum, lateral view; (B, C) same, lateral view; (D) same, lateral view; (E) telson and uropods, dorso-lateral view; (F) distal end of telson, dorsal view. (A, E, F) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (B) Male, pocl 2.7 mm (NIBRIV0000862982); (C) Female, 2.78 mm (NIBRIV0000862978); (D) Male, pocl 2.5 mm (SNU KR JH1095).Figure 4 Mesopontonia verrucimanus Bruce, 1996. (A) Left eye, dorsal view; (B) left antennule, dorsal view; (C) left antenna, dorsal view; (D) left third maxilliped. (A-C) Ovigerous female, pocl 3.8 mm (NIBRIV0000862990); (D) Ovigerous female, pocl 3.7 mm (NIBRIV0000862989).Figure 5 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left first pereiopod. (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 6 Mesopontonia verrucimanus Bruce, 1996, ovigerous female, pocl 3.7 mm (NIBRIV0000862989). (A) Left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod; (F) same, dactylus and distal propodus.Figure 7 Mesopontonia verrucimanus Bruce, 1996 on Ellisella limbaughi Bayer &amp; Deichmann, 1960 from Munseom Islet, Jejudo Island. (A) Female specimen, pocl 2.5 mm (MADBK 120533_004); (B) male specimens, pocl 3.0 mm (MADBK 120533_003). Photographic Credits: (A) Jin-Ho Park, (B) Jong Moon Choi.Figure 8 Mesopontonia kimwoni sp. nov., habitus, lateral view. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985).Figure 9 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) frontal margin and rostrum, lateral view; (B) frontal region, dorsal view; (C) left eye, dorsal view; (D) left antenna, ventral view; (E) telson and uropod, dorsal view; (F) distal end of telson, dorsal view; (G) left third maxilliped, mesial view. Figure 10 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left first pereiopod; (B) same, chela; (C) major right second pereiopod; (D) same, chela and carpus; (E) same, fingers; (F) minor left second pereiopod; (G) same, chela.Figure 11 Mesopontonia kimwoni sp. nov., ovigerous female pocl 2.5 mm (NIBRIV0000862985), holotype. (A) left third pereiopod; (B) same, dactylus and distal propodus; (C) left fourth pereiopod; (D) same, dactylus and distal propodus; (E) left fifth pereiopod. Figure 12 Mesopontonia kimwoni sp. nov. from Munseom Islet, Jejudo Island. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Photographic credit: Jin-Ho Park.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 13</ns0:head><ns0:label>13</ns0:label><ns0:figDesc>Figure 13 Artistic interpretation of Mesopontonia kimwoni sp. nov. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Painting by Kyoung Kim. Figure 14 Habitat and host of Mesopontonia from Munseom Islet, Jejudo Island, Korea. Habitat and host specimens of M. verrucimanus (A, B) and M. kimwoni sp. nov. (C). (A) host sea whip, Ellisella cf. limbaughi and habitat in depth of 57 m; (B) host sponge Raspailia (Raspaxilla) hirsuta and habitat in depth of 55 m; (C) host black coral Myriopathes lata and habitat in depth of 55m. Photographic Credits: Jong Moon Choi.Figure 15 Phylogenetic tree obtained by the Maximum likelihood (ML) analysis based on the combined dataset for COI and 16S sequences. Numbers at nodes represent Maximum Likelihood bootstrap percentage (above) and Bayesian posterior probabilities (below), numbers less than 75% are not shown.Table1: Species used in the phylogenetic analysis with GenBank accession numbers and source. Used symbols: N/A -not available. Table2: Pairwise distances of COI sequences and selected morphological characteristics for specimens used in the analysis. (P2 -second pereiopods).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 14</ns0:head><ns0:label>14</ns0:label><ns0:figDesc>Figure 13 Artistic interpretation of Mesopontonia kimwoni sp. nov. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Painting by Kyoung Kim. Figure 14 Habitat and host of Mesopontonia from Munseom Islet, Jejudo Island, Korea. Habitat and host specimens of M. verrucimanus (A, B) and M. kimwoni sp. nov. (C). (A) host sea whip, Ellisella cf. limbaughi and habitat in depth of 57 m; (B) host sponge Raspailia (Raspaxilla) hirsuta and habitat in depth of 55 m; (C) host black coral Myriopathes lata and habitat in depth of 55m. Photographic Credits: Jong Moon Choi.Figure 15 Phylogenetic tree obtained by the Maximum likelihood (ML) analysis based on the combined dataset for COI and 16S sequences. Numbers at nodes represent Maximum Likelihood bootstrap percentage (above) and Bayesian posterior probabilities (below), numbers less than 75% are not shown.Table1: Species used in the phylogenetic analysis with GenBank accession numbers and source. Used symbols: N/A -not available. Table2: Pairwise distances of COI sequences and selected morphological characteristics for specimens used in the analysis. (P2 -second pereiopods).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 15</ns0:head><ns0:label>15</ns0:label><ns0:figDesc>Figure 13 Artistic interpretation of Mesopontonia kimwoni sp. nov. Holotype, ovigerous female, pocl 2.5 mm (NIBRIV0000862985). Painting by Kyoung Kim. Figure 14 Habitat and host of Mesopontonia from Munseom Islet, Jejudo Island, Korea. Habitat and host specimens of M. verrucimanus (A, B) and M. kimwoni sp. nov. (C). (A) host sea whip, Ellisella cf. limbaughi and habitat in depth of 57 m; (B) host sponge Raspailia (Raspaxilla) hirsuta and habitat in depth of 55 m; (C) host black coral Myriopathes lata and habitat in depth of 55m. Photographic Credits: Jong Moon Choi.Figure 15 Phylogenetic tree obtained by the Maximum likelihood (ML) analysis based on the combined dataset for COI and 16S sequences. Numbers at nodes represent Maximum Likelihood bootstrap percentage (above) and Bayesian posterior probabilities (below), numbers less than 75% are not shown.Table1: Species used in the phylogenetic analysis with GenBank accession numbers and source. Used symbols: N/A -not available. Table2: Pairwise distances of COI sequences and selected morphological characteristics for specimens used in the analysis. (P2 -second pereiopods).</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,229.87,525.00,283.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='38,42.52,204.37,525.00,371.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='45,42.52,204.37,525.00,360.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='46,42.52,204.37,525.00,355.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='49,42.52,250.12,525.00,242.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Pairwise distances of COI sequences and selected morphological characteristics for specimens used in the analysis. (P2 -second pereiopods).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>MT311972</ns0:cell><ns0:cell>Present study</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 : Pairwise distances of COI sequences and selected morphological characteristics for specimens used in the analysis. (P2 - second pereiopods).</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell>Species</ns0:cell><ns0:cell>Rostral</ns0:cell><ns0:cell>Shape and size of P2</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>6</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>formula</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='2'>1 M. kimwoni sp. nov.</ns0:cell><ns0:cell>1-8/2</ns0:cell><ns0:cell>Unequal and dissimilar</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>(1)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='2'>2 M. kimwoni sp. nov.</ns0:cell><ns0:cell>1-8/2</ns0:cell><ns0:cell>Unequal and dissimilar</ns0:cell><ns0:cell>0.011</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>(2)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell>M. verrucimanus (1)</ns0:cell><ns0:cell>1-8/1</ns0:cell><ns0:cell>Unequal and dissimilar</ns0:cell><ns0:cell>0.142</ns0:cell><ns0:cell>0.1360</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>4</ns0:cell><ns0:cell>M. verrucimanus (2)</ns0:cell><ns0:cell>1-8/0</ns0:cell><ns0:cell>Equal and similar</ns0:cell><ns0:cell>0.1380</ns0:cell><ns0:cell>0.1320</ns0:cell><ns0:cell>0.0030</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>5</ns0:cell><ns0:cell>M. verrucimanus (3)</ns0:cell><ns0:cell>1-9/0</ns0:cell><ns0:cell>Unequal and dissimilar</ns0:cell><ns0:cell>0.1380</ns0:cell><ns0:cell>0.1320</ns0:cell><ns0:cell>0.0030</ns0:cell><ns0:cell>0.0000</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>6</ns0:cell><ns0:cell>M. verrucimanus (4)</ns0:cell><ns0:cell>2-8/1</ns0:cell><ns0:cell>Unequal and dissimilar</ns0:cell><ns0:cell>0.1400</ns0:cell><ns0:cell>0.1340</ns0:cell><ns0:cell>0.0050</ns0:cell><ns0:cell>0.0020</ns0:cell><ns0:cell>0.0020</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>7</ns0:cell><ns0:cell>M. verrucimanus (5)</ns0:cell><ns0:cell>1-9/2</ns0:cell><ns0:cell>Equal and similar</ns0:cell><ns0:cell>0.1380</ns0:cell><ns0:cell>0.1320</ns0:cell><ns0:cell>0.0030</ns0:cell><ns0:cell>0.0000</ns0:cell><ns0:cell>0.0000</ns0:cell><ns0:cell>0.0020</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:06:50042:2:0:NEW 19 Sep 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:06:50042:2:0:NEW 19 Sep 2020)</ns0:note> <ns0:note place='foot' n='4'>PeerJ reviewing PDF | (2020:06:50042:2:0:NEW 19 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"18th September 2020 Dear Dr. Korakot Nganvongpanit, We are grateful to the editor and reviewer who have spent time and effort to review our manuscript. We have responded to reviewer and editorial requests, we would be greatly indebted if you could consider this manuscript for the publication in PeerJ. Sincerely, Taeseo Park, Ph.D. Senior Researcher of National Institute of Biological Resources. On behalf of all authors. National Institute of Biological Resources Ministry of Environment Hwangyeong-ro 42, Seo-gu Incheon, 22689, Republic of Korea Tel +82-32-590-7083 Fax +82-32-590-7250 [email protected] [email protected] A. Editor comments (Korakot Nganvongpanit) MINOR REVISIONS Thank you very much for your significantly improve this manuscript. However, I would like you to improve your figures; in figures 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 13. I need you to point the importance structure for the reader, better than figure without the label. I am looking for words to see your revision version. Rebuttal text: It is not standard practice in decapod taxonomy to add arrows (or similar annotations) to illustrations. This can be amply demonstrated by the following articles on decapod taxonomy, all of which have been published in PeerJ in the last 2-3 year (DOI links): 10.7717/peerj.9194 10.7717/peerj.9565 10.7717/peerj.9370 10.7717/peerj.8089 10.7717/peerj.7980 10.7717/peerj.6605 10.7717/peerj.5947 10.7717/peerj.5561 10.7717/peerj.5497. Whilst the editorial request of adding arrows many indeed be valid in other disciplines, such as anatomy or veterinary science, both disciplines we are not familiar with; we respectfully decline to add these to our own illustrations, as this is not the “norm” in our own discipline, and clearly has been acceptable to the journal in the past. As there are no other review or editorial requests to address, we look forward to the manuscript being accepted. B. Reviewer 1 (Anonymous) Basic reporting The authors has addressed major part of the comments and the MS can be accepted. Of course I agree the illustration is at the professional level. Whether the authors is encouraged to add in more ecological and illustration for non-specialists/beginner to understand is really depends the editor's decision on the scope of PeerJ - a really specialist taxonomy journal or a biodiversity, taxonomy and ecology journal for both specialists and general readers. Experimental design Addressed Validity of the findings Addressed Comments for the author The authors has addressed major part of the comments and the MS can be accepted. Of course I agree the illustration is at the professional level. Whether the authors is encouraged to add in more ecological and illustration for non-specialists/beginner to understand is really depends the editor's decision on the scope of PeerJ - a really specialist taxonomy journal or a biodiversity, taxonomy and ecology journal for both specialists and general readers. Rebuttal text: It is not standard practice in decapod taxonomy to add arrows (or similar annotations) to illustrations. This can be amply demonstrated by the following articles on decapod taxonomy, all of which have been published in PeerJ in the last 2-3 year (DOI links): 10.7717/peerj.9194 10.7717/peerj.9565 10.7717/peerj.9370 10.7717/peerj.8089 10.7717/peerj.7980 10.7717/peerj.6605 10.7717/peerj.5947 10.7717/peerj.5561 10.7717/peerj.5497. Whilst the editorial request of adding arrows many indeed be valid in other disciplines, such as anatomy or veterinary science, both disciplines we are not familiar with; we respectfully decline to add these to our own illustrations, as this is not the “norm” in our own discipline, and clearly has been acceptable to the journal in the past. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background: Grasshoppers are typical phytophagous pests, and they have large appetites with high utilization of plants fibers, the digestion of which may depend on the microorganisms in their intestines. Grasshoppers have the potential to be utilized in bioreactors, which could improve straw utilization efficiency in the future. In this study, we describe the gut microbiome in three species of grasshoppers, Oedaleus decorus asiaticus, Aiolopus tamulus and Shirakiacris shirakii, by constructing a 16S rDNA gene library and analyzed the digestibility of cellulose and hemicellulose in the grasshoppers by using moss black phenol colorimetry and anthrone colorimetry. Results:There were 509,436 bacterial OTUs (Operational Taxonomic Units) detected in the guts of all the grasshoppers sampled.</ns0:p><ns0:p>Among them, Proteobacteria and Firmicutes were the most common, Aiolopus tamulus had the highest bacterial diversity, and Shirakiacris shirakii had the highest bacterial species richness. The intestinal microflora structure varied between the different species of grasshopper, with Aiolopus tamulus and Shirakiacris shirakii being the most similar. Meanwhile, the time at which grasshopper specimens were collected also led to changes in the intestinal microflora structure in the same species of grasshoppers. Klebsiella may form the core elements of the microflora in the grasshopper intestinal tract. The digestibility of cellulose/hemicellulose among the three species grasshoppers varied (38.01/24.99%, 43.95/17.21% and 44.12/47.62%). LEfSe analysis and Spearman correlation coefficients showed that the hemicellulosic digestibility of Shirakiacris shirakii was significantly higher than that of the other two species of grasshopper, which may be related to the presence of Pseudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, and Brachybacterium in Shirakiacris shirakii intestinal tract.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion:</ns0:head><ns0:p>The intestinal microbial communities of the three grasshoppers species are similar on phylum level, but the dominant genera of different species grasshoppers are different. The cellulose digestibility of the three species of grasshoppers is relatively high, which may be correlated with the presence of some gut microbiome. Increasing the</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Grasshoppers (Orthoptera: Acridoidea) are the main pests in agriculture, cattle grazing and forestry.</ns0:p><ns0:p>Grasshoppers require a large quantity of gramineous plants to obtain the nutrients and water necessary for their survival, especially in their adult stage. The food selectivity of grasshoppers is affected by many factors. As far as plants themselves are concerned, the factors that affect grasshoppers' food selectivity include cellulose, water, carbohydrate and protein contents <ns0:ref type='bibr' target='#b17'>(Ibanez et al., 2013)</ns0:ref>. Wheat seedlings, which have a moisture content of 89.819%-93.326%, are rich in protein, vitamins, minerals, and other nutrients <ns0:ref type='bibr' target='#b28'>(Min et al., 2017)</ns0:ref> and are easy to cultivate, making them good fodder for grasshoppers bred in laboratories.</ns0:p><ns0:p>Cellulose and hemicellulose are the main components of plants. Previous studies have shown that the main components of corn straw are hemicellulose, cellulose and lignin <ns0:ref type='bibr' target='#b24'>(Liu &amp; Chen, 2007)</ns0:ref>. It is difficult to hydrolyze and utilize cellulose, so most of it is discarded. At present, cellulose and hemicellulose are increasingly widely used <ns0:ref type='bibr' target='#b53'>(Xiong et al., 2005)</ns0:ref>, and their efficient utilization is of great practical significance to reduce the burning of straw and promote the sustainable development of agriculture and animal husbandry.</ns0:p><ns0:p>The gut microbiome is a general term for all the microorganisms inhabiting the digestive tract of animals <ns0:ref type='bibr' target='#b33'>(Rangberg et al., 2012)</ns0:ref> and contains the most concentrated set of interactions among all symbiotic microorganisms in animals <ns0:ref type='bibr' target='#b15'>(Guo et al., 2015)</ns0:ref>. In the process of evolution, insects and intestinal microorganisms interact, cooperate and coevolve. Insects secrete digestive enzymes by means of symbiotic microorganisms in the body to better digest food and obtain energy needed for their own growth and development. Many phytophagous insects can effectively degrade and digest lignocellulose for their own use, including wood-eating insect, such as cockroaches, termites and wasps, and cereal-eating insects, such as beetles. The degradation of lignocellulose from food by these kinds of insects depends not only on themselves but also on the interaction of symbiotic microorganisms in their bodies. It is possible to contrive a species-wide metabolic interaction network of the termite gut-microbiome in order to have a system-level understanding of metabolic communication. <ns0:ref type='bibr' target='#b19'>Kundu et al.(2019)</ns0:ref> have elucidated 15 crucial hemicellulolytic microbes and their corresponding enzyme machinery <ns0:ref type='bibr' target='#b19'>(Kundu et al., 2019)</ns0:ref>. At present, no insect has been found to be able to completely digest lignocellulose food via cellulase and hemicellulase secreted by itself <ns0:ref type='bibr' target='#b40'>(Sun &amp; Chen, 2010)</ns0:ref>.</ns0:p><ns0:p>The digestive tract of grasshoppers is a complex ecosystem that is inhabited by a large number of microorganisms. These microorganisms play an important role in the grasshopper digestive tract. Studies have shown that changing the structure of the intestinal microbial community can affect the survival rate of grasshoppers <ns0:ref type='bibr' target='#b42'>(Tan et al., 2020)</ns0:ref>. At present, research on the intestinal microbial community of insects mainly focuses on certain economic insects, including silkworm, Ceroplastes japonica, and others, to improve the intestinal environment to reduce silkworm diseases or to increase the wax secretion of Ceroplastes japonica <ns0:ref type='bibr' target='#b54'>(Yi et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b1'>Bei et al., 2005)</ns0:ref>. In addition, other insects, such as ants and longicorn beetles, have been studied for their role in decomposing lignocellulose <ns0:ref type='bibr' target='#b57'>(Zhang et al., 2005)</ns0:ref>.</ns0:p><ns0:p>There are few studies on the composition of the grasshopper intestinal microflora structure, community diversity and functional bacteria. In addition, current research is based on traditional culture methods or traditional molecular biology techniques, and grasshopper intestinal microorganisms have not yet been thoroughly investigated. In this study, the intestinal bacterial community structures of three species grasshoppers were studied by constructing a 16S rDNA library technology, and the abundance and phylogenesis of these bacteria were analyzed to obtain better information on grasshopper intestinal microbial diversity, providing a theoretical basis for clarifying the mechanism of cellulose degradation in grasshopper, and further study the relationship between intestinal microorganisms and pest control. At the same time, the digestibility of cellulose and hemicellulose in the grasshoppers were determined by using moss black phenol colorimetry and anthrone colorimetry, providing basic data for the development of a cellulose and hemicellulose digestion bioreactor, as well as a feasible method for determining insects' cellulose and hemicellulose digestibility.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and methods</ns0:head></ns0:div> <ns0:div><ns0:head>Specimen collection</ns0:head><ns0:p>Adults of Oedaleus decorus asiaticus <ns0:ref type='bibr'>Bey-bienko, 1941</ns0:ref><ns0:ref type='bibr'>, Aiolopus tamulus Fabricius, 1789</ns0:ref><ns0:ref type='bibr'>and Shirakiacris shirakii Bol&#237;var, 1914</ns0:ref>, were collected from Baoding City, Hebei Province, China in July to November 2018 (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Intestinal microbial diversity of grasshoppers</ns0:head><ns0:p>Total DNA of the intestinal contents of the 3 species grasshoppers was extracted, with each species having 3 groups of samples, totaling 9 sample groups. The sample numbers are shown in Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>. Total DNA of the 9 sample groups was used as templates, and PCR was carried out with universal primers targeting the 16S rDNA V3+V4 region of prokaryotes. After the PCR products passed quality tests, they were detected by an Illumina HiSeq 2500 sequencer (at Biomarker Technologies Corporation), and the data were processed and analyzed by Uparse and QIIME software <ns0:ref type='bibr' target='#b7'>(Caporaso et al., 2010)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Sample treatment</ns0:head><ns0:p>The collected and classified living grasshoppers were placed in cages without access to food for 2 days to remove their intestinal contents. The grasshoppers to be tested were washed repeatedly with sterile water, placed in a 75% alcohol solution for 2 min, washed with sterile water, irradiated with ultraviolet light for 3-5 minutes, and dissected grasshoppers under sterile conditions. The entire intestinal tract was removed, and the midgut and hindgut parts were separated; placed in labeled, sterilized 1.5 mL centrifuge tubes; and kept at -80&#8451; for later use.</ns0:p></ns0:div> <ns0:div><ns0:head>Extraction of total DNA from the intestinal contents</ns0:head><ns0:p>Total DNA of the intestinal contents of grasshoppers was extracted using the PowerSoil DNA Isolation Kit according to the manufacturer's protocol, and the quality and quantity of DNA were evaluated by the 260 nm/280 nm and 260 nm/230 nm ratios, respectively. DNA was then stored at -80&#8451; until further processing.</ns0:p><ns0:p>For each individual sample, the 16s rDNA V 3 + V 4 region was amplified using the 338 F (5'-ACTCTACGGAGAGCA-3') and 806 R (5'-GGACTACHVGGGTWTCTAT-3') primers <ns0:ref type='bibr' target='#b29'>(Mori et al., 2014)</ns0:ref>. PCR was performed in a total reaction volume of 20 &#181;L: H 2 O ,13.25 &#181;L; 10&#215;PCR ExTaq Buffer, 2.0 &#181;L; DNA template (100 ng/mL), 0.5 &#181;L; primer1 (10 mmol/L), 1.0 &#181;L; primer2 (10 mmol/L) ,1.0 &#181;L; dNTP, 2.0 &#181;L; and ExTaq (5U/mL), 0.25 &#181;L. After an initial denaturation at 95&#8451; for 5 min, amplification was performed with 30 cycles of incubations for 30 sec at 95&#8451;, 20 sec at 58&#8451;, and 6 sec at 72&#8451;, followed by a final extension at 72&#8451; for 7 min. The amplified products were then purified and recovered using 1.0% agarose gel Manuscript to be reviewed electrophoresis. Finally, all the PCR products were quantified by Quant-iT TM dsDNA HS Reagent and pooled together. High-throughput sequencing analysis of bacterial rRNA genes was performed on the purified, pooled samples using the Illumina HiSeq 2500 platform (2&#215;250pairedends) at Biomarker Technologies Corporation, Beijing, China. Finally, library construction and sequencing were performed by Beijing Biomarker Technologies Co. Ltd.</ns0:p></ns0:div> <ns0:div><ns0:head>Bioinformatics analysis</ns0:head><ns0:p>Bioinformatics analysis in this study was completed on the Biomarker Cloud Platform (www.biocloud.org).</ns0:p><ns0:p>The original data obtained by sequencing were spliced by FLASH software. Then, raw tags were filtered and clustered. Sequences were removed from inclusion according to the following criteria: the average mass of bases was less than 20; the reads were low quality; the sequences contained primer mismatches; the sequences were less than 350 bp in length; and the sequences could not be spliced. UCHIME, a tool included in mothur (http://drive5.com/uchime), was used to remove chimeras and generate valid data. OTUs were taxonomically annotated based on the Silva (bacteria) and UNITE (fungi) taxonomic databases. The denoised sequences were clustered using USEARCH (version10.0), and tags with similarity &#8805; 97% were regarded as OTUs. Taxonomy was assigned to all OTUs by searching against the Silvadatabases (http://www.arb-silva.de.) using uclust within QIIME <ns0:ref type='bibr' target='#b11'>(Edgar, 2010)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Digestibility of wheat seedlings in grasshoppers Collection and treatment of samples</ns0:head><ns0:p>Grasshoppers collected in the field were separately packed in insect rearing cages, and each cage contained 10 individuals that were fed wheat seedlings (The wheat variety was Triticum aestivum Linnaeus,1753). After consecutively feeding for 3 days (no dung was collected during the period, and the wheat seedlings provided sufficient nutrition), grasshoppers were fasted for 2 days. A layer of white plastic foam was spread on the bottom of the cages to facilitate the collection of excrement <ns0:ref type='bibr' target='#b48'>(Wang et al., 2008)</ns0:ref>. During the experiment, the fresh weight of wheat seedlings fed each time was recorded, and the feces and residual wheat seedlings were dried to a constant weight at 70&#8451; and recorded (using an electrothermal constant temperature blast drying oven, Shanghai Flyover Experimental Instrument Co., Ltd. DGG-9030A). The dry-fresh ratio of wheat seedlings was determined to calculate the dry weight of the wheat seedlings before the experiment <ns0:ref type='bibr' target='#b45'>(Wang, 1997)</ns0:ref>. The collected feces were dried to a constant weight, pulverized, and filtered with a 40 mesh sieve.</ns0:p><ns0:p>The wheat seedlings were rapidly dehydrated by steam de-enzyming <ns0:ref type='bibr' target='#b41'>(Sun, 2014)</ns0:ref>, dried at 70&#8451; until a constant weight, crushed, and filtered with a 40 mesh sieve for later use.</ns0:p></ns0:div> <ns0:div><ns0:head>Determination of cellulose and hemicellulose content</ns0:head><ns0:p>Samples were prepared by weighing out 0.800 g of each sample, to which 8 mL 72% H 2 SO 4 was added, followed by shaking. Samples were placed in a water bath at 30&#8451; for 1 h, followed by the addition of 8 mL 4% H 2 SO 4 , and were then returned to the water bath for 45 min. Finally, 224 mL of distilled water was added, and the samples shaken well before being placed into conical flasks in an electric heating pressure steam sterilization pot (LS-30 type of Shanghai Bosun Industrial Co., Ltd.). Samples were then heated to a temperature of 121&#8451; for 1 h and filtered to obtain sample solutions.</ns0:p><ns0:p>One milliliter of this sample solution was diluted appropriately, and 1 mL of the diluted sample solution was added to 1 mL of anthrone reagent and 3 mL of 80% sulfuric acid, mixed well, and boiled at 100&#8451; for 5 min. Manuscript to be reviewed After cooling to room temperature, absorbance at 620 nm was measured, with the sugar concentration calculated according to the glucose standard regression equation and then multiplied by 0.9 <ns0:ref type='bibr' target='#b56'>(Zhang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>One milliliter of the sample solution was diluted appropriately, and 1 mL of the diluted sample solution was add to 2 mL of A reagent and 0.134 mL of B reagent and boiled at 100&#8451; for 20 min after fully mixing. Absorbance at 660 nm was measured after cooling to room temperature, with the sugar concentration calculated according to the xylose standard regression equation and then multiplied by 0.88 <ns0:ref type='bibr' target='#b56'>(Zhang et al., 2010)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Calculation of the decomposition rates of cellulose and hemicellulose</ns0:head><ns0:p>The decomposition rates of cellulose and hemicellulose were calculated after the cellulose and hemicellulose contents of the adult grasshopper feces were determined by the above methods. Statistical analysis of digestibility data was done in SPSS 21.0 software using T-test.</ns0:p><ns0:formula xml:id='formula_0'>&#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890;(&#8462;&#119890;&#119898;&#119894;&#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890;) = c * 240 * 10 -3 * 0.9(0.88) m * &#119889;&#119894;&#119897;&#119906;&#119905;&#119894;&#119900;&#119899; &#119898;&#119906;&#119905;&#119894;&#119901;&#119897;&#119890; * 100% &#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890; &#119889;&#119894;&#119892;&#119890;&#119904;&#119905;&#119894;&#119887;&#119894;&#119897;&#119894;&#119910; = &#119886;&#119898;&#119900;&#119906;&#119899;&#119905; &#119900;&#119891; &#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890; &#119891;&#119890;&#119889; &#119900;&#119899; &#119908;&#8462;&#119890;&#119886;&#119905; &#119904;&#119890;&#119890;&#119889;&#119897;&#119894;&#119899;&#119892;&#119904; -&#119891;&#119890;&#119888;&#119886;&#119897; &#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890; &#119888;&#119900;&#119899;&#119905;&#119890;&#119899;&#119905;</ns0:formula><ns0:p>&#119886;&#119898;&#119900;&#119906;&#119899;&#119905; &#119900;&#119891; &#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890; &#119891;&#119890;&#119889; &#119900;&#119899; &#119908;&#8462;&#119890;&#119886;&#119905; &#119904;&#119890;&#119890;&#119889;&#119897;&#119894;&#119899;&#119892;&#119904; * 100% Note: c is the sugar concentration (g/L) calculated according to the standard curve, m is the weighed sample mass (g).</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Intestinal microbes in grasshoppers Evaluation of sequencing quality</ns0:head><ns0:p>A total of 702,445 paired-end reads were obtained by sequencing the 9 pooled samples. and 512,109 clean tags were generated after splicing and filtering the paired-end reads. A minimum of 51,643 clean tags were generated for each sample, with an average of 56,901 clean tags. The proportion of effective sequences was 99.48%. The sequencing accuracy of the samples was high and met the standard requirements. Effective tags were the number of effective sequences after filtering chimeras from the clean tags. The number of sequences and the proportion for each sample are shown in Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref> below.</ns0:p></ns0:div> <ns0:div><ns0:head>OTU-Venn analysis</ns0:head><ns0:p>To identify the number of common and unique OTUs among samples, a Venn diagram was used, which intuitively reflects the coincidence of OTUs among samples. As shown in Figure <ns0:ref type='figure'>1</ns0:ref> (A), there were 37 species of bacteria in the intestinal tract common to the three species of grasshoppers. There were 6 species specific to Shirakiacris shirakii, 11 species specific to Oedaleus decorus asiaticus, and 13 species specific to Aiolopus tamulus. Further analysis of the identifies of the bacteria common to the three grasshopper species indicated that they were mainly composed of two families of Enterobacteriaceae and Enterococcaceae, as shown in Figure <ns0:ref type='figure'>1</ns0:ref>(B), with a relative abundance of 97.57%, indicating that these two families may form the core microflora in the grasshopper intestinal tract. <ns0:ref type='table' target='#tab_7'>PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head></ns0:div> <ns0:div><ns0:head>&#945;-diversity analysis</ns0:head><ns0:p>As shown in Figure <ns0:ref type='figure'>2</ns0:ref>(A), the rarefaction curves of 9 samples tended to be flat over an increasing number of sequences. The Shannon, Simpson, Chao1, and ACE indices, as well as others, were used to express the &#945;diversity of the microorganisms in the samples. As shown in Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, the coverage of the nine samples was relatively high, reaching 99.97%~99.99%. The above results show that the sequencing data were reasonable and that the vast majority of bacteria in the samples were detected. Different from the rarefaction curve, the species accumulation curve reflects whether the number of samples was sufficient and whether the information covered all the annotated species. As shown in Figure <ns0:ref type='figure'>2</ns0:ref>(B), as the sample number increased, the cumulative curve and the common quantity curve tended to be flat, which demonstrates that the new and common species detected in the sample were both approaching saturation, indicating that the sample size was sufficient and could be used for diversity and abundance analysis.</ns0:p><ns0:p>The &#945;-diversity of 9 samples varied according to the individual. In the three samples of Aiolopus tamulus, the Shannon index of At1 and At2 was much higher than that of At3, while the Simpson index of At3 was the opposite, indicating that the species diversity in samples At1 and At2 was higher than that in At3. Among the three samples of Oedaleus decorus asiaticus, the Shannon index of Od3 was much higher than that of Od1 and Od2, while the Simpson index of Od3 was much lower than that of the other two samples. For the three samples of Shirakiacris shirakii, the Shannon index and Simpson index were not significantly different, which may be related to the difference in the collection time (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>).</ns0:p><ns0:p>The average value of each index of three samples from the same species was calculated and then used to compare and analyze the &#945;-diversity among the different species. The Chao1 index (Figure <ns0:ref type='figure'>2C</ns0:ref>) of Shirakiacris shirakii was significantly higher than that of Oedaleus decorus asiaticus, and the ACE index (Figure <ns0:ref type='figure'>2D</ns0:ref>) was the highest in Shirakiacris shirakii, followed by Aiolopus tamulus, which demonstrates that among the three species grasshoppers, the abundance of species in the intestinal tract of Shirakiacris shiraki was significantly higher than that of Oedaleus decorus asiaticus, with Aiolopus tamulus in the middle. The Simpson index (Figure <ns0:ref type='figure'>2E</ns0:ref>) of Aiolopus tamulus was the smallest, while the index of Shirakiacris shiraki was the largest. The Shannon index (Figure <ns0:ref type='figure'>2F</ns0:ref>) followed the opposite trend to the Simpson index, which indicated that the species diversity in the intestinal tract of Aiolopus tamulus was the highest, followed by the Oedaleus decorus asiaticus, with Shirakiacris shiraki as the lowest.</ns0:p></ns0:div> <ns0:div><ns0:head>&#946;-Diversity analysis</ns0:head><ns0:p>Based on pyrosequencing data, PCoA and UPGMA clustering were carried out to determine &#946;-diversity. As shown in Supplementary figure <ns0:ref type='figure'>1</ns0:ref>, the smaller the distance between points in the figure, the smaller the difference in the intestinal flora structure, and vice versa. It can be seen from the figure that the difference in the intestinal microflora structure between the three samples of Shirakiacris shiraki and two of the samples of Aiolopus tamulus was relatively small, while difference in the intestinal microflora structure between one sample and the remaining two samples for both Oedaleus decorus asiaticus and Aiolopus tamulus was relatively large. The difference in the intestinal microflora structure among the three samples of Shirakiacris shiraki was not large. In addition, the hierarchical cluster tree (Figure <ns0:ref type='figure'>3A</ns0:ref>) shows that the microbial communities of the three species grasshoppers are divided into three groups: (1) group I includes samples A1 and A2 and sample O3, ( <ns0:ref type='formula'>2</ns0:ref> Manuscript to be reviewed the samples of Shirakiacris shiraki. In addition, the distance between group &#8545; and group &#8546; was closer, that is, the composition of the intestinal microflora is more similar between those two groups. Taken together, these results show that the intestinal microflora of different species of grasshoppers vary from one another. The intestinal microflora of Aiolopus tamulus and Shirakiacris shiraki are more similar. At the same time, different sampling times will also lead to the recombination of microbial communities. NMDS (Nonmetric Multidimensional Scaling) analysis can reflect the differences between groups or within groups according to the distribution of samples. As shown in Figure <ns0:ref type='figure'>3B</ns0:ref>, the stress value is less than 0.01, which indicates that the analysis result is extremely reliable. In the figure, it can be seen that there is a large difference in the intestinal community between one sample the remaining two samples for both Oedaleus decorus asiaticus and Aiolopus tamulus, which is related to the different collection times of the samples, indicating that a difference in collection time leads to changes in the microbial community structure of the same species. The three samples of Shirakiacris shiraki along with two samples of Aiolopus tamulus are almost coincident, which indicates that the similarity of the intestinal microflora structure between the two groups was relatively high.</ns0:p><ns0:p>As shown in Figure <ns0:ref type='figure'>3C</ns0:ref>, Ss1, Ss2 and Ss3 were grouped together; At1 and At2 were grouped together; and all (Ss1, Ss2, Ss3 and At2) were grouped with Od3. Od1 and Od2 were grouped with At3. The samples At1 and At2 of Aiolopus tamulus were relatively close to the three samples of Shirakiacris shiraki, which indicates that the intestinal community similarity between Aiolopus tamulus and Shirakiacris shiraki is high, that the difference of the microflora structure between them is relatively small, and that different collection times for the same species can lead to low similarity and large differences in the grasshopper intestinal microflora structure, which is consistent with the above results, indicating that a difference in collection time causes changes in the microbial community structure.</ns0:p></ns0:div> <ns0:div><ns0:head>Intestinal microflora structure of the three species grasshoppers</ns0:head><ns0:p>High-quality sequences obtained from 16S rDNA identification were compared with the database, and a total of 54 genera of 7 phyla, 12 classes, and 20 orders were identified. The composition of each sample is shown in Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>. Once the average relative abundance of different grasshoppers in the same treatment at each classification level is calculated, the average relative abundance can reflect the content of various intestinal microorganisms at the overall level.</ns0:p></ns0:div> <ns0:div><ns0:head>Intestinal microflora structure at the phylum level</ns0:head><ns0:p>The nine samples At1, At2, At3, Od1, Od1, Od2, Od3, Ss1, Ss2, and Ss3 contained 85.65%, 83.51%, 93.45%, 89.51%, 91.43%, 87.32%, 86.92%, 87.33%, and 87.35%, respectively, of the valid sequences that were able to be annotated at the phylum level. Seven phyla were detected in the nine samples. According to the annotation results of the samples at various classification levels (kingdom, phyla, class, order, family, genus and species), as shown in Figure <ns0:ref type='figure'>4A</ns0:ref>, Proteobacteria accounted for the highest relative abundance in the three species of grasshoppers, Aiolopus tamulus, Oedaleus decorus asiaticus, and Shirakiacris shiraki, at 94.10%, 90.72% and 93.94%, respectively. The second highest was Firmicutes, accounting for 5.72%, 8.94% and 5.31%, respectively.Actinobacteria accounted for a relatively high proportion of 0.52% in the intestinal tract of Shirakiacris shiraki, although less than 0.10% in the intestinal tracts of the other two species. Cyanobacteria was relatively abundant in the intestinal tract of Oedaleus decorus asiaticus, at 0.26%, while its abundance in the other two species was very small, accounting for 0.01%. Fusobacteria existed in the intestinal tracts of the three species grasshoppers in trace amounts, accounting for less than 0.10%. Bacteroidetes was found in trace amounts in Aiolopus tamulus and Oedaleus decorus asiaticus but was not detected in the intestinal tract of Shirakiacris shiraki. Tenericutes was only found in trace amount in the intestinal tract of Oedaleus decorus asiaticus, at 0.04%, but was not found in the intestinal tracts of the other two grasshoppers. Additionally, 0.20% unassigned microorganisms were present in the intestinal tract of Shirakiacris shiraki that have not previously been studied.</ns0:p><ns0:p>It is worth noting that the proportion of Firmicutes in At3 intestinal bacteria was 0.24%, which was much lower than that in At 1 (11.01%) and At2 (5.91%) treated with the same method. However, the proportion in sample Od3 (26.74%) was much higher than that in sample Od1 (0.03%) and sample Od2 (0.06%), while the proportion in the three samples Ss1 (3.72%), Ss2 (1.83%) and Ss3 (10.36%) of Shirakiacris shiraki was relatively constant, which could be related to their different collection times, indicating that the abundance of intestinal flora varied over different periods in the same species. Combined with &#945;-diversity analysis, these results show that the diversity and abundance of intestinal microflora varied over different periods in the same species.</ns0:p><ns0:p>Intestinal microflora structure at genus level At1, At2, At3, Od1, Od2, Od3, Ss1, Ss2 and Ss3 contained 54.57%, 68.35%, 93.40%, 89.35%, 90.93%, 87.31%, 86.08%, 85.45% and 87.30%, respectively, of the valid sequences that could be annotated at the genus level. A total of 54 bacterial genera were detected, of which 24 bacterial genera were common among the three species. As seen in Figure <ns0:ref type='figure'>4B</ns0:ref>, Klebsiella accounted for the highest proportion of the microbial community in the three grasshopper species. The top 10 abundant bacterial genera (by average relative abundance) for each of the three species of grasshoppers after data standardization are shown in Supplementary Tables 1, 2, and 3. In the three samples of Aiolopus tamulus, the average relative abundance of Klebsiella, Enterococcus and Enterobacter was greater than 1%, which identifies them as the primary bacteria in the Aiolopus tamulus intestinal tract. The primary bacteria of Oedaleus decorus asiaticus were Klebsiella, Enterococcus, Pantoea, Wolbachia, Enterobacter, and Lactococcus. Klebsiella, Lactococcus, and Staphylococcus were the primary genera of Shirakiacris shiraki. Five bacterial genera were detected only in the intestinal tract of Aiolopus tamulus, namely, Anaerotruncus, Diaphorobacter, Morganella, Proteiniclasticum, and Rikenellaceae_RC9_gut_ group. The proportion of these five bacterial genera in the intestinal tract was not more than 0.1%. Among them, Morganella was not detected in the At3 samples, but was detected in the At1 and At2 samples, and the remaining 4 genera were detected only in the At3 samples but not in the At1 and At2 samples, indicating that there were significant differences in the intestinal microflora diversity of the same species from different time periods. The genera Sphaerotilus and Spiroplasma were only detected in the intestinal tract of Oedaleus decorus asiaticus, and Cronobacter was only detected in Shirakiacris shiraki. Therefore, the diversity of the intestinal microorganisms varied by grasshopper species.</ns0:p></ns0:div> <ns0:div><ns0:head>Digestibility results</ns0:head><ns0:p>From Table <ns0:ref type='table' target='#tab_6'>4</ns0:ref>, the cellulose digestibility of the three species of grasshoppers were 43.95%, 38.01% and 44.12%, and there was no significant difference (P&gt;0.05) among the three groups. However, the hemicellulose digestibility in Shirakiacris shirakii at 47.65% was significantly higher (P&lt;0.05) than that in Aiolopus tamulus Manuscript to be reviewed (17.21%) and Oedaleus decorus asiaticus (24.99%). In addition, the cellulose digestibility in Aiolopus tamulus and Oedaleus decorus was significantly higher than that of hemicellulose, and there was no significant difference between the cellulose and hemicellulose digestibility in Shirakiacris shirakii.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between digestibility and microorganism abundance</ns0:head><ns0:p>In view of the fact that Shirakiacris shirakii can be distinguished from the other two species and that the digestibility of hemicellulose is significantly higher in that organism than in the other two species (P&lt;0.05), we conducted LEfSe analysis (Figure <ns0:ref type='figure'>5</ns0:ref>, Supplementary figure <ns0:ref type='figure'>2</ns0:ref>) on the three species and identified Pseudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, Brachybacterium and other bacteria genera as biomarkers of group difference. The relative abundance of these identified species in Shirakiacris shirakii is significantly higher than that in the other species, which may be related to the degradation of hemicellulose. To further screen out bacteria related to the degradation rate of cellulose and hemicellulose, we calculated the Spearman correlation coefficients (Figure <ns0:ref type='figure'>6</ns0:ref>) for the association between the degradation rate and microflora abundance and identified a number of bacteria whose abundance had a high correlation with the degradation rates of cellulose and hemicellulose. Some of the results highly overlap with the LEfSe analysis, suggesting that these bacteria can be used as candidate bacteria for cellulose and hemicellulose degradation.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>In this experiment, we constructed a 16S rRNA gene library via Illumina MiSeq sequencing and applied it to systematically study the intestinal microflora composition of three grasshopper species for the first time. Among the different grasshopper species, the abundance and diversity of intestinal microorganisms were varied. Through the analysis of &#945; and &#946; diversity, it was found that the diversity of the intestinal microflora in the same species was quite varied depending on the collection time. The grasshoppers in this study were collected from summer and autumn populations from the same location, which meant that there were changes in the host insect habitat. Previous studies have shown that the environmental conditions of the habitat of the host insect can affect the interaction between insects and their symbiotic microorganisms, as well as the species and distribution of symbiotic microorganisms <ns0:ref type='bibr' target='#b35'>(Schmid et al., 2015)</ns0:ref>, indicating that the diversity and function of microorganisms in the intestinal tract of insects are closely related to the habitat conditions in which the insects live. However, there are few reports on whether changes in the environment of host insects affects the species and community composition of intestinal microorganisms and the specific extent of that impact, which is a problem worthy of further study. There were differences in the primary intestinal bacteria among the different species of grasshopper, but the abundance of Proteobacteria was the highest in the intestinal bacteria of all three species of grasshopper, followed by Firmicutes. Bacteria of those two phyla accounted for more than 98% of the total intestinal bacteria of the three grasshopper species, which was consistent with previous reports on the primary species of insect microbiomes. Previous studies have shown that Proteobacteria are the primary bacteria in the intestinal tract of many insects: Schistocerca gregaria in Orthoptera <ns0:ref type='bibr' target='#b9'>(Dillon et al., 2010)</ns0:ref>, Acyrthosiphon pisum in Hemiptera, and Ectropis obliqua <ns0:ref type='bibr' target='#b12'>(Engel &amp; Moran, 2013)</ns0:ref> and Spodoptera frugiperda <ns0:ref type='bibr' target='#b14'>(Gichuhi et al., 2020)</ns0:ref> in Lepidoptera. Among the Lepidoptera insects studied, the primary bacteria in the intestinal tract of Lymantria dispar, Helicoverpa armigera, Bombyx mori and Plutella xylostella larvae are Proteobacteria and Firmicutes <ns0:ref type='bibr' target='#b60'>(Zhou et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b32'>Priya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b4'>Broderick et al., 2004)</ns0:ref>. There was variation in the primary genera in the intestinal tract of the grasshopper species. These primary genera and other less abundant genera all play important roles in the life activities of host insects. The content of Klebsiella in the intestinal tract of the three species grasshoppers in this study was very high, which was similar to the results of <ns0:ref type='bibr' target='#b22'>Liu (2012)</ns0:ref> on symbiotic bacteria in the intestinal tract of Locusta migratoria manilensis using DGGE <ns0:ref type='bibr' target='#b22'>(Liu, 2012)</ns0:ref>. The second most abundant bacteria in our study was Enterococcus. This result is consistent with the previous results where bacteria were found to be the most abundant in the microflora of Schistocerca gregaria. <ns0:ref type='bibr' target='#b20'>(Lavy et al., 2019)</ns0:ref>. In addition, previous studies have shown that Enterococcus can not only help degrade lignocellulose but can also produce biogenic amines, which have important physiological functions, such as promoting host growth and enhancing metabolism <ns0:ref type='bibr' target='#b38'>(Shu, Lu &amp; Xu, 2011;</ns0:ref><ns0:ref type='bibr' target='#b37'>Shil et al.,2014)</ns0:ref>. Enterococcus may encode 1,4-&#946;-cellobiosidase, endoglucanase and &#946;-glucosidase, which are involved in cellulose degradation, and 1,4-&#946;-xylosidase, which is involved in xylan degradation <ns0:ref type='bibr' target='#b51'>(Xia et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b31'>Potrikus &amp; Breznak, 1977;</ns0:ref><ns0:ref type='bibr' target='#b49'>Warnecke et al., 2007)</ns0:ref>; these factors have functions relating to food digestion and absorption. However, some other reported cellulose-degrading bacteria, such as Enterobacter and Pseudomonas <ns0:ref type='bibr' target='#b0'>(Bayer, Shoham &amp; Lamed, 2006;</ns0:ref><ns0:ref type='bibr' target='#b30'>Muhammad et al., 2017)</ns0:ref>, have no significant correlation with cellulose and hemicellulose degradation, and the presence of these bacteria may contribute to eliminating the differences in cellulose digestibility in this study. Acinetobacter participates in host food digestion, degrades harmful compounds, and plays a role in nitrogen transformation <ns0:ref type='bibr' target='#b2'>(Briones-Roblero et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b25'>Liu et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b26'>Mason et al., 2016)</ns0:ref>. Existing studies have shown that Wolbachia plays an important role in the reproductive ability of host insects <ns0:ref type='bibr' target='#b16'>(Hancock et al., 2011)</ns0:ref>, and whether this genus has an effect on the reproduction of grasshoppers requires further attention.</ns0:p><ns0:p>Since the main food source of grasshoppers is cellulose, it is speculated that the intestinal tract of grasshoppers may contain abundant microorganisms capable of degrading cellulose. <ns0:ref type='bibr' target='#b50'>Willis et al. (2010)</ns0:ref> isolated cellulase from the foregut and hindgut of the Carolina wasp Dissosteira carolina, which was highly similar to the &#946;-1,4-endonuclease of bacteria, fungi and invertebrates, including that secreted by the insects themselves <ns0:ref type='bibr' target='#b50'>(Willis et al., 2010)</ns0:ref>. <ns0:ref type='bibr' target='#b46'>Wang et al. (2010)</ns0:ref> isolated and screened 5 strains of bacteria with cellulose degradation function from the intestinal tract of Yunnanacris yunnaneus, including 4 strains of Bacillus and one strain of Pseudomonas, which had CMC and filter paper enzyme activities of 167 &#181;/mLand 9.8&#181;/mL, respectively <ns0:ref type='bibr' target='#b46'>(Wang et al., 2010)</ns0:ref>.The above studies show that grasshoppers have the ability to degrade cellulose efficiently. In this study, the contents of cellulose and hemicellulose in the wheat seedling and feces of three species of grasshoppers adults were detected by colorimetry, and the decomposition rates of cellulose and hemicellulose were calculated and analyzed. The cellulose digestibility in Aiolopus tamulus and Oedaleus decorus was significantly higher than that of hemicellulose. On one hand, this relates result to the structure and composition of cellulose and hemicellulose. Compared with cellulose, hemicellulose has a very complex structure and composition, including xylose, arabinose, mannose and galactose, etc. In the cell wall, hemicellulose is distributed among many celluloses, embedded in the surface of cellulose microfibers and mixed with cellulose. Therefore, only when cellulose is hydrolyzed can hemicellulose be completely hydrolyzed <ns0:ref type='bibr' target='#b43'>(Vargas, Weiss &amp; Mcclements, 2007)</ns0:ref>. On the other hand, the difference in cellulose and Manuscript to be reviewed hemicellulose digestibility relates to the type and quantity of microorganisms in the grasshopper's intestinal tract. Intestinal microorganisms can secrete a variety of cellulose digestive enzymes. The activities of cellulase and hemicellulase determine the grasshopper's ability to digest cellulose and hemicellulose.</ns0:p><ns0:p>The cellulose digestibility in the three species of grasshoppers was not significantly different, 43.95%, 38.01%, and 44.12%, respectively. In a previous study, <ns0:ref type='bibr' target='#b21'>Li et al. (2000)</ns0:ref> found that the digestibility of crude fiber in different components of corn straw fed to sheep varied from 34.21%-61.21% <ns0:ref type='bibr' target='#b21'>(Li et al.,2000)</ns0:ref>. <ns0:ref type='bibr' target='#b13'>Fang et al. (2009)</ns0:ref> studied the utilization rate of different straw diets in Xinjiang cattle and found that the digestibility of acid detergent fiber (ADF) and neutral detergent fiber (NDF) in wheat straw was 35.02% and 43.86%, respectively, and that the digestibility of ADF and NDF in corn straw was 44.26% and 51.91%, respectively <ns0:ref type='bibr' target='#b13'>(Fang et al., 2009)</ns0:ref>. Meanwhile, a study by <ns0:ref type='bibr' target='#b58'>Zhao (2015)</ns0:ref> found that the digestibility of cellulose in corn straw by Locusta migratoria manilensis was 15.10% <ns0:ref type='bibr' target='#b58'>(Zhao, 2015)</ns0:ref>. Our results showed that the cellulose digestibility in the three species grasshoppers was significantly higher than that of Locusta migratoria manilensis and was close to that of mammals. Whether this difference was related to a difference in the composition of the feeding material needs to be further studied. However, in terms of cellulose digestibility, the intestinal capacity of grasshoppers is very small compared with that of mammals, but their cellulose decomposition rate is close to that of mammals, which indicates that the ability of Aiolopus tamulus, Oedaleus decorus asiaticus and Shirakiacris shirakii to digest cellulose is indeed strong and that studying the cellulose decomposition rate of grasshoppers may be of great value to the development of a cellulose decomposition bioreactor.</ns0:p><ns0:p>Herbivorous insects usually do not directly digest cellulose, or minimally digest cellulose, but mainly digest starch, sugar and protein in food <ns0:ref type='bibr' target='#b10'>(Douglas, 2009)</ns0:ref>. Moreover, the honey bee gut microbiota digests complex carbohydrates, such as hemicellulose and pectin, thereby acquiring energy <ns0:ref type='bibr' target='#b59'>(Zheng et al, 2019)</ns0:ref>.These insects are mainly limited by nitrogen intake rather than carbon source <ns0:ref type='bibr' target='#b27'>(McNeil &amp; Southwood, 1978)</ns0:ref>. Klebisella plays an important role in ammonia assimilation into amino acids <ns0:ref type='bibr' target='#b36'>(Senior, 1975)</ns0:ref>, and its negative correlation with the digestion rate may be related to this. Similarly, <ns0:ref type='bibr' target='#b34'>San et al. (2011)</ns0:ref>also identified some other bacteria related to nitrogen metabolism, including Staphylococcus, <ns0:ref type='bibr'>Stenotrophomonas, etc (San et al., 2011)</ns0:ref>. However, it cannot be ignored that this study is consistent with previous studies, i.e., grasshoppers have a strong ability to digest cellulose <ns0:ref type='bibr' target='#b39'>(Su et al., 2014)</ns0:ref>, how much of which is due to the action of their own digestive enzymes and how much of which is due to the contribution of microorganisms needs to be further explored.</ns0:p><ns0:p>Yet, it remains to be seen whether cellulose/hemicellulose digestion in these grasshoppers is exclusively intrinsic or mediated by a combination of intrinsic and bacterial-mediated processes. Until now, there has been no direct evidence that grasshoppers rely entirely on gut microbes to break down cellulose and hemicellulose. For herbivorous insects, the efficiency of decomposition and utilization of cellulose and hemicellulose are largely dependent on gut microbes <ns0:ref type='bibr' target='#b18'>(Jehmlich et al., 2016)</ns0:ref>. Corynebacterium and Glutamicibacter have been identified from the intestinal bacteria of Shirakiacris shirakii. And Corynebacterium has been reported to be able to hydrolyze hemicellulose <ns0:ref type='bibr' target='#b5'>(Buschke, Schr&#246;der &amp; Wittmann, 2011)</ns0:ref>. Glutamicibacter isolated from the intestinal tract of Proisotoma ananevae has strong cellulose degradation ability <ns0:ref type='bibr' target='#b47'>(Wang et al., 2018)</ns0:ref>. Clavibacter produces cellulase <ns0:ref type='bibr' target='#b44'>(Waleron et al., 2010)</ns0:ref> and Brachybacterium can degrade cellulose <ns0:ref type='bibr' target='#b55'>(Zhang et al., 2007)</ns0:ref>, which supports the results of our correlation analysis. Many insects have intrinsic cellulases <ns0:ref type='bibr' target='#b8'>(Davison &amp; Blaxter, 2005)</ns0:ref>, and some insects belonging to Acrididae have cellulase that can break down plant cell </ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study analyzed the intestinal microbial diversity of 3 species of grasshoppers, using the method of 16S rDNA gene library construction. Proteobacteria and Firmicutes are the dominant bacteria in the intestinal microbial communities of the three grasshoppers species. However, the dominant genera of different species grasshoppers are different. Shirakiacris shirakii had the highest bacterial species richness, and Aiolopus tamulus had the highest bacterial diversity. The intestinal microflora structure varied between the different species of grasshoppers, with the intestinal microflora structure of Aiolopus tamulus and Shirakiacris shirakii being the most similar. Meanwhile, the time at which grasshopper specimens were collected also led to changes in the intestinal microflora structure in the same species of grasshoppers.</ns0:p><ns0:p>There was no significant difference in cellulose digestibility between the three species of grasshoppers (P&gt;0.05), while the hemicellulose digestibility of Shirakiacris shirakii was significantly higher than Aiolopus tamulus and Oedaleus decorus asiaticus (P &lt;0.05). In addition, the cellulose digestibility of Aiolopus tamulus and Oedaleus decorus asiaticus was significantly higher than the hemicellulose digestibility.</ns0:p><ns0:p>LEfSe analysis and Spearman correlation coefficients showed that the hemicellulosic digestibility of Shirakiacris shirakii was significantly higher than that of the other two species of grasshopper, which may be related to the presence of Pseudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, and Brachybacterium in Shirakiacris shirakii intestinal tract.</ns0:p><ns0:p>This study lays a foundation for the utilization of garsshoppers intestinal microorganisms in the future. Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head>Sequence and proportion results of each sample and bacterial identification results</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed 1 2 Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Digestibility of cellulose and hemicellulose in wheat seedlings in three species grasshoppers</ns0:p><ns0:p>The data in the table are expressed as the mean standard error, and the data in the same column with different lowercase letters show significant difference (P&lt;0.05).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed The data in the table are expressed as the mean standard error, and the data in the same column with different lowercase letters show significant difference (P&lt;0.05).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>) group II includes samples O1 and O2 and sample A3, and (3) group III includes all PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)Manuscript to be reviewed walls<ns0:ref type='bibr' target='#b6'>(Calderon-Cortes et al., 2012)</ns0:ref>.Combined with the results of this article, we can slate a new hypothesis: the intestinal microorganisms of grasshoppers have a great influence on the decomposition of cellulose/hemicellulose.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='24,42.52,199.12,525.00,273.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,255.37,525.00,186.00' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Information on the studied samples</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Species</ns0:cell><ns0:cell cols='2'>Sample code No. of specimens</ns0:cell><ns0:cell>Locality</ns0:cell><ns0:cell>Collection date</ns0:cell></ns0:row><ns0:row><ns0:cell>Aiolopus tamulus</ns0:cell><ns0:cell>At1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>July 15, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>At2</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>July 15, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>At3</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell>Oedaleus decorus asiaticus</ns0:cell><ns0:cell>Od1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Od2</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Od3</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>July 15, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell>Shirakiacris shirakii</ns0:cell><ns0:cell>Ss1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Ss2</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Ss3</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Sequence and proportion results of each sample and bacterial identification results</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='3'>Sample Clean tags Effective tags</ns0:cell><ns0:cell>Proportion</ns0:cell><ns0:cell>Identification result</ns0:cell></ns0:row><ns0:row><ns0:cell>At1</ns0:cell><ns0:cell>53704</ns0:cell><ns0:cell>53325</ns0:cell><ns0:cell>99.29%</ns0:cell><ns0:cell>4 phyla, 7 classes, 11 orders, 18 families, 26 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>At2</ns0:cell><ns0:cell>51643</ns0:cell><ns0:cell>51479</ns0:cell><ns0:cell>99.68%</ns0:cell><ns0:cell>5 phyla, 9 classes, 13 orders, 24 families, 31 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>At3</ns0:cell><ns0:cell>61063</ns0:cell><ns0:cell>61018</ns0:cell><ns0:cell>99.93%</ns0:cell><ns0:cell>5 phyla, 10 classes, 17orders, 28 families, 28 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Od1</ns0:cell><ns0:cell>61047</ns0:cell><ns0:cell>61024</ns0:cell><ns0:cell>99.96%</ns0:cell><ns0:cell>6 phyla, 9 classes, 12 orders, 18 families, 21 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Od2</ns0:cell><ns0:cell>72346</ns0:cell><ns0:cell>72296</ns0:cell><ns0:cell>99.93%</ns0:cell><ns0:cell>6 phyla, 9 classes, 16 orders, 23 families, 27 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Od3</ns0:cell><ns0:cell>53117</ns0:cell><ns0:cell>52034</ns0:cell><ns0:cell>97.96%</ns0:cell><ns0:cell>5 phyla, 7 classes, 11 orders, 17 families, 22 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss1</ns0:cell><ns0:cell>52796</ns0:cell><ns0:cell>52631</ns0:cell><ns0:cell>99.68%</ns0:cell><ns0:cell>5 phyla, 9 classes, 16 orders, 28 families, 32 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss2</ns0:cell><ns0:cell>53296</ns0:cell><ns0:cell>53144</ns0:cell><ns0:cell>99.71%</ns0:cell><ns0:cell>5 phyla, 8 classes, 15 orders, 25 families, 31 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss3</ns0:cell><ns0:cell>53097</ns0:cell><ns0:cell>52485</ns0:cell><ns0:cell>98.85%</ns0:cell><ns0:cell>5 phyla, 8 classes, 13 orders, 24 families, 30 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Tatal</ns0:cell><ns0:cell>512109</ns0:cell><ns0:cell>509436</ns0:cell><ns0:cell>99.48%</ns0:cell><ns0:cell>7 phyla, 12 classes, 20 orders, 42 families, 54 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>4</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Statistical results of the diversity index of the intestinal content samples of</ns0:figDesc><ns0:table /><ns0:note>grasshoppers PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Statistical results of the diversity index of the intestinal content samples of grasshoppers</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Simple ID</ns0:cell><ns0:cell>OTU</ns0:cell><ns0:cell>ACE</ns0:cell><ns0:cell>Chao1</ns0:cell><ns0:cell>Simpson</ns0:cell><ns0:cell>Shannon</ns0:cell><ns0:cell>Coverage</ns0:cell></ns0:row><ns0:row><ns0:cell>At1</ns0:cell><ns0:cell>37</ns0:cell><ns0:cell>41.5776</ns0:cell><ns0:cell>40.0000</ns0:cell><ns0:cell>0.3996</ns0:cell><ns0:cell>1.1721</ns0:cell><ns0:cell>0.9999</ns0:cell></ns0:row><ns0:row><ns0:cell>At2</ns0:cell><ns0:cell>47</ns0:cell><ns0:cell>48.7316</ns0:cell><ns0:cell>48.2000</ns0:cell><ns0:cell>0.5780</ns0:cell><ns0:cell>0.9800</ns0:cell><ns0:cell>0.9999</ns0:cell></ns0:row><ns0:row><ns0:cell>At3</ns0:cell><ns0:cell>41</ns0:cell><ns0:cell>48.9659</ns0:cell><ns0:cell>52.2500</ns0:cell><ns0:cell>0.9249</ns0:cell><ns0:cell>0.2079</ns0:cell><ns0:cell>0.9998</ns0:cell></ns0:row><ns0:row><ns0:cell>Od1</ns0:cell><ns0:cell>31</ns0:cell><ns0:cell>41.2173</ns0:cell><ns0:cell>38.2000</ns0:cell><ns0:cell>0.9211</ns0:cell><ns0:cell>0.2320</ns0:cell><ns0:cell>0.9998</ns0:cell></ns0:row><ns0:row><ns0:cell>Od2</ns0:cell><ns0:cell>40</ns0:cell><ns0:cell>49.3557</ns0:cell><ns0:cell>47.2000</ns0:cell><ns0:cell>0.7624</ns0:cell><ns0:cell>0.5464</ns0:cell><ns0:cell>0.9999</ns0:cell></ns0:row><ns0:row><ns0:cell>Od3</ns0:cell><ns0:cell>33</ns0:cell><ns0:cell>39.0695</ns0:cell><ns0:cell>37.6667</ns0:cell><ns0:cell>0.4783</ns0:cell><ns0:cell>1.0977</ns0:cell><ns0:cell>0.9998</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss1</ns0:cell><ns0:cell>50</ns0:cell><ns0:cell>51.9067</ns0:cell><ns0:cell>50.8571</ns0:cell><ns0:cell>0.8528</ns0:cell><ns0:cell>0.4748</ns0:cell><ns0:cell>0.9999</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss2</ns0:cell><ns0:cell>46</ns0:cell><ns0:cell>52.1871</ns0:cell><ns0:cell>51.6000</ns0:cell><ns0:cell>0.8964</ns0:cell><ns0:cell>0.3283</ns0:cell><ns0:cell>0.9998</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss3</ns0:cell><ns0:cell>44</ns0:cell><ns0:cell>62.0907</ns0:cell><ns0:cell>54.1111</ns0:cell><ns0:cell>0.7679</ns0:cell><ns0:cell>0.5609</ns0:cell><ns0:cell>0.9997</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 4 (on next page)</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Digestibility of cellulose and hemicellulose in wheat seedlings in three species grasshoppers Sample digestibility rate of cellulose digestibility rate of hemicellulose</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Aiolopus tamulus</ns0:cell><ns0:cell>43.95&#177;2.02a</ns0:cell><ns0:cell>17.21&#177;2.98b</ns0:cell></ns0:row><ns0:row><ns0:cell>Oedaleus decorus asiaticus</ns0:cell><ns0:cell>38.01&#177;3.96a</ns0:cell><ns0:cell>24.99&#177;4.80b</ns0:cell></ns0:row><ns0:row><ns0:cell>Shirakiacris shirakii</ns0:cell><ns0:cell>44.12&#177;3.60a</ns0:cell><ns0:cell>47.65&#177;3.37a</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49060:1:2:NEW 4 Sep 2020)</ns0:note> </ns0:body> "

"Dear Editors We thank the reviewers for their generous comments on the manuscript. In response to the questions raised by the reviewers, we revised them in sequence. We believe that our manuscript has made great progress with reviewers' suggestions. Dr. Xinjiang. Li Associate Professor of Zoology On behalf of all authors. Editor comments (Xiaolei Huang) MAJOR REVISIONS Although this paper presents some new information on the gut bacterial community of grasshoppers, I agree with the reviewers that several aspects need to be improved before the manuscript can be accepted. The authors should think about the review comments and revise the manuscript carefully. Especially, you should pay much attention to: 1) the clarity of your methods and experiments (as one reviewer suggested, you should make several places of the methods clearer); Agreed. We have added clearer instructions to some experimental methods. For example, the wheat variety is Triticum aestivum Linnaeus,1753, and we used the T test to complete the statistical analysis in SPSS 21.0 software. As for the feeding days of grasshoppers, it has been explained detailedly in line 113 and 153 of the manuscript. 2) the reliability of your claim and discussion (any discussion should be based on direct evidence); Thanks for your suggestion. We have added some literatures and combined the discussion with the results for analysis. Finally, the major results were summarized concisely and directly in the conclusions. 3) the presentation and language of the manuscript. Too many figures and tables are not good, instead, you need to assemble related figures into multiple-panel figures following a logical way, and some figures with less information can be provided as supplementary files. Actually separate tables can also be incorporated. We have assembled related figures into multiple-panel figures following a logical way. For example, We assemble the Venn diagram and the figure of composition of common OTUs at the family level into a multiple-panel figure in the OTU-Venn analysis results; the figures of rarefaction curves, species discovery curve, Chao1 index, ACE index, Simpson index and Shannon index were assembled a multiple-panel figure in the results of α-diversity analysis; the figures of UPGMA cluster analysis, NMDS analysis and Heatmap of each sample at the OTU classification level were assembled a multiple-panel figure in the results of β-Diversity analysis; the figures of diversity of the bacterial microbiota in the three species grasshoppers guts at the phylum level and genus level were assembled a multiple-panel figure and the figures of LEfSe analysis identifies biomarkers that cause differences between groups were assembled a multiple-panel figure. And some figures and tables with less information have been provided as supplementary files, such as the figure of analysis of the main principal component, the figure of abundance of the selected taxa (A) Pseudomonas, (B) Stenotrophomonas, (C) Glutamicibacter, (D) Corynebacterium, (E) Brachybacterium, the tables of top 10 bacteria genera in terms of average relative abundance in three samples of Aiolopus tamulus, Oedaleus decorus asiaticus, Shirakiacris shirakii. And, the language needs to be improved. Agreed. DBMediting provided us with professional English editing services and greatly improved the language of the manuscript. I suggest the authors revise the manuscript carefully. The decision of Major Revision can not guarantee future acceptance if you cannot handle the reviewers' comments in a proper way. You should also provide a file with point-to-point responses to the review comments when submitting revision files. We have revised the manuscript carefully and provided a file with point-to-point responses to the review comments. Reviewer 1 (Anonymous) Basic reporting Grasshoppers are the notorious pests for some agricultural crops. It is of great significance to determine the potential role of gut bacteria in the utilization of plant hosts for insect pests. Although the authors have presented some interesting findings here, this manuscript can not be accepted for publication now because of some visible defects. Firstly, the English language should be improved significantly because there are many grammar mistakes and awkward sentences. Agreed. DBMediting provided us with professional English editing services and greatly improved the language of the manuscript. Secondly, the results of this manuscript were not well summarized and presented. The data were described too generally, but the major results were not summarized concisely and directly. Therefore, it is very difficult to catch up what the major findings the authors presented here. We have made a concise and direct summary of the results in conclusions. This manuscript mainly talks about three contents: the first is the gut microbial diversity of the three species of grasshoppers; the second is the cellulose/hemicellulose digestibility of the three species of grasshoppers; the last is a conjecture about the connection between the first and second contents based on the correlation analysis and the previous literature achievement. Thirdly, some important progress has been done on the interactions between insect pests and their gut microbiota. However, the authors did not pay sufficient attention to these achievements on this topic in 2018-2020. There are some research results in recent years. We have cited some researches that are closely related to our subject in manuscript. For example, the honey bee gut microbiota digests complex carbohydrates, such as hemicellulose and pectin, thereby acquiring energy (Zheng et al., 2019); Kundu et al. found 15 hemicellulolytic microbes in the guts of termites (Kundu et al., 2019); Studies have shown that changing the structure of the intestinal microbial community can affect the survival rate of grasshoppers(Tan et al., 2020); Gichuhi et al. found that Proteobacteria are the primary bacteria in the intestinal tract of Spodoptera frugiperda in Lepidoptera (Gichuhi et al., 2020). Moreover, many sentences on describing experimental methods can be found in the section of results. It is better to remove them because this section should often focus on what you have found by your experiments. Agreed. We have removed these sentences. Finally, the authors did not present any direct evidence to support the cellulose digestibility of three grasshoppers was from their gut bacteria. But the authors did only do some correlation analysis and try to support their view. In my opinion, it is not enough to support this finding. It is better if the authors can isolate and identify some cultivable bacterial species from the guts of three grasshopper species. Agreed. There are few reports on the relationship between insect gut microbes and cellulose/hemicellulose digestibility. We tried to make a preliminary analysis about it. So we made a speculation that the hemicellulose digestibility of three species of grasshoppers may be from their gut bacteria based on the results of the correlation analysis. Thanks for your valuable advice. Our work now is to isolate and identify some cultivable cellulolytic bacteria in order to verify this relationship. Experimental design Some important experimental information missed in this manuscript. For example, the authors said they collected the adults of three grasshopper species in field and fed with wheat seedlings in lab. However, the authors did not introduce which wheat species or variety was used to feed these insects.  We have added the wheat variety, which is Triticum aestivum Linnaeus,1753. Furthermore, the authors did not tell how long these collected insects were fed in lab before the following experiments and the conditions that were used to rear these insects in lab. The grasshoppers used for the analysis of intestinal microbial diversity were fasted for two days and then dissected(This part of the content is in line 113 of the manuscript).And grasshoppers collected for digestibility analysis in the field were separately packed in insect rearing cages, and each cage contained 10 individuals that were fed wheat seedlings. After consecutively feeding for 3 days, grasshoppers were fasted for 2 days (This part of the content is in line 153 of the manuscript). Last, the authors did not tell the statistical method and how they complete the statistical analysis. We used the T test to complete the statistical analysis in SPSS 21.0 software. We have stated it in line 188 of the manuscript. Validity of the findings The major findings of this manuscript were not summarized and presented well. Because of the absence of some novel important publications, the findings of this manuscript were not well explained in the section of discussion. The authors should clearly present what great differences on gut microbiota among these three grasshopper species and what impact of these differences in their gut bacteria on the cellulose digestibility. Thanks for your advice. This part is explained in the conclusions. The dominant genera of different species are different. Shirakiacris shirakii had the highest bacterial species richness, and Aiolopus tamulus had the highest bacterial diversity. The intestinal microflora structure varied between the different species of grasshoppers, with the intestinal microflora structure of Aiolopus tamulus and Shirakiacris shirakii being the most similar. In view of the fact that Shirakiacris shirakii can be distinguished from the other two species and that the digestibility of hemicellulose is significantly higher in that organism than in the other two species (P<0.05), we conducted LEfSe analysis and Spearman correlation coefficients. The results showed that may be related to the presence of Pseudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, and Brachybacterium in Shirakiacris shirakii intestinal tract. Corynebacterium has been reported to be able to hydrolyze hemicellulose (Buschke, Schröder & Wittmann, 2011); Glutamicibacter isolated from the intestinal tract of Proisotoma ananevae has strong cellulose degradation ability (Wang et al., 2018). Moreover, there are some reports showing the connection between insect gut microbes and cellulose/hemicellulose digestibility, such as wasp (Willis et al., 2010), Yunnanacris yunnaneus (Wang et al., 2010) and termites (Kundu et al., 2019). The effect of grasshoppers gut bacteria on cellulose/ hemicellulosic digestibility needs further study. Comments for the Author Some format questions on reference can be easily found in the text and reference list of this manuscript. Therefore, the authors should correct these questions carefully. Thanks for your valuable suggestions. We have corrected these questions. Reviewer 2 (Anonymous) Basic reporting no comment Experimental design no comment Validity of the findings no comment Comments for the Author This paper describes the gut microbiome of three grasshopper species, and attempts to correlate the differences in microbiota structure with the ability of the host to digest cellulose and hemicellulose. The data is potentially interesting and should be useful for subsequent studies of grasshopper gut bacteria. However, it should be noted that this paper represents only very weak association between change in gut bacteria and the food digestion. Without further data showing the function of gut microbiota in helping digesting cellulose, it is difficult to justify the rational of the current study. Therefore, the authors need to do a better job with any claims that the difference in several bacterial species is actually causing the difference in host’s digestion. For example, the claim that the hemicellulose digestibility of Shirakiacris shirakii was significantly higher than that of the other two species of grasshopper DUE TO the presence of Psudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, and Brachybacterium in its intestinal tract, was not supported by the current analysis, and needs to be re-phrased. Agreed. Grasshoppers are the main pests in agriculture, cattle grazing and forestry. Grasshoppers require a large quantity of gramineous plants to obtain the nutrients and water necessary for their survival, especially in their adult stage. But, the mechanism of cellulose degradation in grasshopper is unclear. There are some reports showing the connection between insect gut microbes and cellulose/hemicellulose digestibility, such as wasp (Willis et al., 2010), Yunnanacris yunnaneus (Wang et al., 2010) and termites (Kundu et al., 2019). However, there are few reports on the mechanism which grasshoppers break down cellulose/ hemicellulosic at present. Moreover, there are few studies on the composition of the grasshopper intestinal microflora structure, community diversity and functional bacteria. Previous researches were based on traditional culture methods or traditional molecular biology techniques, and grasshopper intestinal microorganisms have not yet been thoroughly investigated. We analyzed the gut microbial diversity of the three species of grasshoppers and their cellulose digestibility and hemicellulosic digestibility. And we made a preliminary analysis of the relationship between gut microbes and digestibility. LEfSe analysis and Spearman correlation coefficients showed that the hemicellulosic digestibility of Shirakiacris shirakii was significantly higher than that of the other two species of grasshopper, which may be related to the presence of Pseudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, and Brachybacterium in Shirakiacris shirakii intestinal tract. Of course, this is only a preliminary result. The effect of their gut bacteria on cellulose/ hemicellulosic digestibility needs further study. Numerous language problems have to be fixed first to make the paper readable, probably by sending to a native English speaker to check. Agreed. DBMediting provided us with professional English editing services and greatly improved the language of the manuscript. Finally, It is strongly suggested that the authors assembly the figures into multiple-panel figures. Thanks. We have assembled related figures into multiple-panel figures following a logical way. For example, We assemble the Venn diagram and the figure of composition of common OTUs at the family level into a multiple-panel figure in the OTU-Venn analysis results; the figures of rarefaction curves, species discovery curve, Chao1 index, ACE index, Simpson index and Shannon index were assembled a multiple-panel figure in the results of α-diversity analysis; the figures of UPGMA cluster analysis, NMDS analysis and Heatmap of each sample at the OTU classification level were assembled a multiple-panel figure in the results of β-Diversity analysis; the figures of diversity of the bacterial microbiota in the three species grasshoppers guts at the phylum level and genus level were assembled a multiple-panel figure and the figures of LEfSe analysis identifies biomarkers that cause differences between groups were assembled a multiple-panel figure. In addition, a field permit was not required, and we explain why in the Notes to Staff ; we provide our raw numeric data for cellulose and hemicellulose digestibility; we upload a text-only manuscript with a separate file for each figure and table; We have re-edited affiliations in the system version; We submitted a complete manuscript including a discussion section and a conclusion section; We re-uploaded the figures measuring minimum 900 pixels and maximum 3000 pixels on all sides in PNG format; We replaced some of the red and green colors in Figures 2, 3, and 4 with color-blind friendly colors and reassembled. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background: Grasshoppers are typical phytophagous pests, and they have large appetites with high utilization of plants fibers, the digestion of which may depend on the microorganisms in their intestines. Grasshoppers have the potential to be utilized in bioreactors, which could improve straw utilization efficiency in the future. In this study, we describe the gut microbiome in three species of grasshoppers, Oedaleus decorus asiaticus, Aiolopus tamulus and Shirakiacris shirakii, by constructing a 16S rDNA gene library and analyzed the digestibility of cellulose and hemicellulose in the grasshoppers by using moss black phenol colorimetry and anthrone colorimetry. Results:There were 509,436 bacterial OTUs (Operational Taxonomic Units) detected in the guts of all the grasshoppers sampled.</ns0:p><ns0:p>Among them, Proteobacteria and Firmicutes were the most common, Aiolopus tamulus had the highest bacterial diversity, and Shirakiacris shirakii had the highest bacterial species richness. The intestinal microflora structure varied between the different species of grasshopper, with Aiolopus tamulus and Shirakiacris shirakii being the most similar. Meanwhile, the time at which grasshopper specimens were collected also led to changes in the intestinal microflora structure in the same species of grasshoppers. Klebsiella may form the core elements of the microflora in the grasshopper intestinal tract. The digestibility of cellulose/hemicellulose among the three species grasshoppers varied (38.01/24.99%, 43.95/17.21% and 44.12/47.62%). LEfSe analysis and Spearman correlation coefficients showed that the hemicellulosic digestibility of Shirakiacris shirakii was significantly higher than that of the other two species of grasshopper, which may be related to the presence of Pseudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, and Brachybacterium in Shirakiacris shirakii intestinal tract.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion:</ns0:head><ns0:p>The intestinal microbial communities of the three grasshoppers species are similar on phylum level, but the dominant genera of different species grasshoppers are different. The cellulose digestibility of the three species of grasshoppers is relatively high, which may be correlated with the presence of some gut microbiome. Increasing the</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Grasshoppers (Orthoptera: Acridoidea) are the main pests in agriculture, cattle grazing and forestry.</ns0:p><ns0:p>Grasshoppers require a large quantity of gramineous plants to obtain the nutrients and water necessary for their survival, especially in their adult stage. The food selectivity of grasshoppers is affected by many factors. As far as plants themselves are concerned, the factors that affect grasshoppers' food selectivity include cellulose, water, carbohydrate and protein contents <ns0:ref type='bibr' target='#b20'>(Ibanez et al., 2013)</ns0:ref>. Wheat seedlings, which have a moisture content of 89.819%-93.326%, are rich in protein, vitamins, minerals, and other nutrients <ns0:ref type='bibr' target='#b33'>(Min et al., 2017)</ns0:ref> and are easy to cultivate, making them good fodder for grasshoppers bred in laboratories.</ns0:p><ns0:p>Cellulose and hemicellulose are the main components of many biomass <ns0:ref type='bibr' target='#b35'>(Mueller-Hagedorn &amp; Bockhorn, 2007)</ns0:ref>. Due to the limitation of the lignin-hemicellulose, most of the biomass are difficult to be decomposed and utilized <ns0:ref type='bibr' target='#b50'>(Thompson et al., 2003)</ns0:ref>. Many factors, like lignin content, crystallinity of cellulose, and particle size, limit the digestibility of the hemicellulose and cellulose present in the lignocellulosic biomass <ns0:ref type='bibr' target='#b19'>(Hendriks &amp; Zeeman, 2009)</ns0:ref>. At present, cellulose and hemicellulose are increasingly widely used <ns0:ref type='bibr' target='#b62'>(Xiong et al., 2005)</ns0:ref>, and their efficient utilization is of great practical significance to reduce the burning of straw and promote the sustainable development of agriculture and animal husbandry.</ns0:p><ns0:p>The gut microbiome is a general term for all the microorganisms inhabiting the digestive tract of animals <ns0:ref type='bibr' target='#b40'>(Rangberg et al., 2012)</ns0:ref> and contains the most concentrated set of interactions among all symbiotic microorganisms in animals <ns0:ref type='bibr' target='#b17'>(Guo et al., 2015)</ns0:ref>. In the process of evolution, insects and intestinal microorganisms interact, cooperate and coevolve. Insects secrete digestive enzymes by means of symbiotic microorganisms in the body to better digest food and obtain energy needed for their own growth and development <ns0:ref type='bibr' target='#b31'>(Mason, Jones &amp; Felton, 2019)</ns0:ref>. It is possible to contrive a species-wide metabolic interaction network of the termite gutmicrobiome in order to have a system-level understanding of metabolic communication. <ns0:ref type='bibr' target='#b24'>Kundu et al.(2019)</ns0:ref> have elucidated 15 crucial hemicellulolytic microbes and their corresponding enzyme machinery <ns0:ref type='bibr' target='#b24'>(Kundu et al., 2019)</ns0:ref>. At present, no insect has been found to be able to completely digest lignocellulose food via cellulase and hemicellulase secreted by itself <ns0:ref type='bibr' target='#b47'>(Sun &amp; Chen, 2010)</ns0:ref>.</ns0:p><ns0:p>Compared with termites and cockroaches, grasshoppers have a very sparse microbiome <ns0:ref type='bibr' target='#b9'>(Dillon &amp; Dillon, 2004)</ns0:ref>. But these microorganisms play an important role in the grasshopper digestive tract. Studies have shown that changing the structure of the intestinal microbial community can affect the survival rate of grasshoppers <ns0:ref type='bibr' target='#b49'>(Tan et al., 2020)</ns0:ref>; <ns0:ref type='bibr' target='#b10'>Dillon et al. (2002)</ns0:ref> have discovered that locust gut bacteria were responsible for the production of components of the locust cohesion pheromone <ns0:ref type='bibr' target='#b10'>(Dillon, Vennard &amp; Charnley, 2002)</ns0:ref>. At present, research on the intestinal microbial community of insects mainly focuses on certain economic insects, including silkworm, Ceroplastes japonica, and others, to improve the intestinal environment to reduce silkworm diseases or to increase the wax secretion of Ceroplastes japonica <ns0:ref type='bibr' target='#b63'>(Yi et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b1'>Bei et al., 2005)</ns0:ref>. In addition, other insects, such as ants and longicorn beetles, have been studied for their role in decomposing lignocellulose <ns0:ref type='bibr' target='#b66'>(Zhang et al., 2005)</ns0:ref>.</ns0:p><ns0:p>There are few studies on the composition of the grasshopper intestinal microflora structure, community diversity and functional bacteria. In addition, current research is based on traditional culture methods or traditional molecular biology techniques, and grasshopper intestinal microorganisms have not yet been thoroughly investigated. In this study, the intestinal bacterial community structures of three species grasshoppers were studied by constructing a 16S rDNA library technology, and the abundance and phylogenesis of these bacteria were analyzed to obtain better information on grasshopper intestinal microbial diversity, providing a theoretical basis for clarifying the mechanism of cellulose degradation in grasshopper, and further study the relationship between intestinal microorganisms and pest control. At the same time, the digestibility of cellulose and hemicellulose in the grasshoppers were determined by using moss black phenol colorimetry and anthrone colorimetry, providing basic data for the development of a cellulose and hemicellulose digestion bioreactor, as well as a feasible method for determining insects' cellulose and hemicellulose digestibility.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and methods</ns0:head></ns0:div> <ns0:div><ns0:head>Specimen collection</ns0:head><ns0:p>Adults of Oedaleus decorus asiaticus <ns0:ref type='bibr'>Bey-bienko, 1941</ns0:ref><ns0:ref type='bibr'>, Aiolopus tamulus Fabricius, 1789</ns0:ref><ns0:ref type='bibr'>and Shirakiacris shirakii Bol&#237;var, 1914</ns0:ref>, were collected from Baoding City, Hebei Province, China in July to November 2018 (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Intestinal microbial diversity of grasshoppers</ns0:head><ns0:p>Total DNA of the intestinal contents of the 3 species grasshoppers was extracted, with each species having 3 groups of samples, totaling 9 sample groups. The sample numbers are shown in Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>. Total DNA of the 9 sample groups was used as templates, and PCR was carried out with universal primers targeting the 16S rDNA V3+V4 region of prokaryotes. After the PCR products passed quality tests, they were detected by an Illumina HiSeq 2500 sequencer (at Biomarker Technologies Corporation), and the data were processed and analyzed by Uparse and QIIME software <ns0:ref type='bibr' target='#b7'>(Caporaso et al., 2010)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Sample treatment</ns0:head><ns0:p>The collected and classified living grasshoppers were placed in cages without access to food for 2 days to remove their intestinal contents. The grasshoppers to be tested were washed repeatedly with sterile water, placed in a 75% alcohol solution for 2 min, washed with sterile water, irradiated with ultraviolet light for 3-5 minutes, and dissected grasshoppers under sterile conditions. The entire intestinal tract was removed, and the midgut and hindgut parts were separated; placed in labeled, sterilized 1.5 mL centrifuge tubes; and kept at -80&#8451; for later use.</ns0:p></ns0:div> <ns0:div><ns0:head>Extraction of total DNA from the intestinal contents</ns0:head><ns0:p>Total DNA of the intestinal contents of grasshoppers was extracted using the PowerSoil DNA Isolation Kit according to the manufacturer's protocol, and the quality and quantity of DNA were evaluated by the 260 nm/280 nm and 260 nm/230 nm ratios, respectively. DNA was then stored at -80&#8451; until further processing.</ns0:p><ns0:p>For each individual sample, the 16s rDNA V 3 + V 4 region was amplified using the 338 F (5'-ACTCTACGGAGAGCA-3') and 806 R (5'-GGACTACHVGGGTWTCTAT-3') primers <ns0:ref type='bibr' target='#b34'>(Mori et al., 2014)</ns0:ref>. PCR was performed in a total reaction volume of 20 &#181;L: H 2 O ,13.25 &#181;L; 10&#215;PCR ExTaq Buffer, 2.0 &#181;L; DNA template (100 ng/mL), 0.5 &#181;L; primer1 (10 mmol/L), 1.0 &#181;L; primer2 (10 mmol/L) ,1.0 &#181;L; dNTP, 2.0 &#181;L; and ExTaq (5U/mL), 0.25 &#181;L. After an initial denaturation at 95&#8451; for 5 min, amplification was performed with 30 cycles of incubations for 30 sec at 95&#8451;, 20 sec at 58&#8451;, and 6 sec at 72&#8451;, followed by a final PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020) extension at 72&#8451; for 7 min. The amplified products were then purified and recovered using 1.0% agarose gel electrophoresis. Finally, all the PCR products were quantified by Quant-iT TM dsDNA HS Reagent and pooled together. High-throughput sequencing analysis of bacterial rRNA genes was performed on the purified, pooled samples using the Illumina HiSeq 2500 platform (2&#215;250pairedends) at Biomarker Technologies Corporation, Beijing, China. Finally, library construction and sequencing were performed by Beijing Biomarker Technologies Co. Ltd.</ns0:p></ns0:div> <ns0:div><ns0:head>Bioinformatics analysis</ns0:head><ns0:p>Bioinformatics analysis in this study was completed on the Biomarker Cloud Platform (www.biocloud.org).</ns0:p><ns0:p>The original data obtained by sequencing were spliced by FLASH software. Then, raw tags were filtered and clustered. Sequences were removed from inclusion according to the following criteria: the average mass of bases was less than 20; the reads were low quality; the sequences contained primer mismatches; the sequences were less than 350 bp in length; and the sequences could not be spliced. UCHIME, a tool included in mothur (http://drive5.com/uchime), was used to remove chimeras and generate valid data. OTUs were taxonomically annotated based on the Silva (bacteria) and UNITE (fungi) taxonomic databases. The denoised sequences were clustered using USEARCH (version10.0), and tags with similarity &#8805; 97% were regarded as OTUs. Taxonomy was assigned to all OTUs by searching against the Silvadatabases (http://www.arb-silva.de.) using uclust within QIIME <ns0:ref type='bibr' target='#b13'>(Edgar, 2010)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Digestibility of wheat seedlings in grasshoppers Collection and treatment of samples</ns0:head><ns0:p>Grasshoppers collected in the field were separately packed in insect rearing cages, and each cage contained 10 individuals that were fed wheat seedlings (The wheat variety was Triticum aestivum Linnaeus,1753). After consecutively feeding for 3 days (no dung was collected during the period, and the wheat seedlings provided sufficient nutrition), grasshoppers were fasted for 2 days. A layer of white plastic foam was spread on the bottom of the cages to facilitate the collection of excrement <ns0:ref type='bibr' target='#b57'>(Wang et al., 2008)</ns0:ref>. During the experiment, the fresh weight of wheat seedlings fed each time was recorded, and the feces and residual wheat seedlings were dried to a constant weight at 70&#8451; and recorded (using an electrothermal constant temperature blast drying oven, Shanghai Flyover Experimental Instrument Co., Ltd. DGG-9030A). The dry-fresh ratio of wheat seedlings was determined to calculate the dry weight of the wheat seedlings before the experiment <ns0:ref type='bibr' target='#b53'>(Wang, 1997)</ns0:ref>. The collected feces were dried to a constant weight, pulverized, and filtered with a 40 mesh sieve.</ns0:p><ns0:p>The wheat seedlings were rapidly dehydrated by steam de-enzyming <ns0:ref type='bibr' target='#b48'>(Sun, 2014)</ns0:ref>, dried at 70&#8451; until a constant weight, crushed, and filtered with a 40 mesh sieve for later use.</ns0:p></ns0:div> <ns0:div><ns0:head>Determination of cellulose and hemicellulose content</ns0:head><ns0:p>Samples were prepared by weighing out 0.800 g of each sample, to which 8 mL 72% H 2 SO 4 was added, followed by shaking. Samples were placed in a water bath at 30&#8451; for 1 h, followed by the addition of 8 mL 4% H 2 SO 4 , and were then returned to the water bath for 45 min. Finally, 224 mL of distilled water was added, and the samples shaken well before being placed into conical flasks in an electric heating pressure steam sterilization pot (LS-30 type of Shanghai Bosun Industrial Co., Ltd.). Samples were then heated to a temperature of 121&#8451; for 1 h and filtered to obtain sample solutions.</ns0:p><ns0:p>One milliliter of this sample solution was diluted appropriately, and 1 mL of the diluted sample solution was Manuscript to be reviewed added to 1 mL of anthrone reagent and 3 mL of 80% sulfuric acid, mixed well, and boiled at 100&#8451; for 5 min. After cooling to room temperature, absorbance at 620 nm was measured, with the sugar concentration calculated according to the glucose standard regression equation and then multiplied by 0.9 <ns0:ref type='bibr' target='#b65'>(Zhang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>One milliliter of the sample solution was diluted appropriately, and 1 mL of the diluted sample solution was add to 2 mL of A reagent and 0.134 mL of B reagent and boiled at 100&#8451; for 20 min after fully mixing. Absorbance at 660 nm was measured after cooling to room temperature, with the sugar concentration calculated according to the xylose standard regression equation and then multiplied by 0.88 <ns0:ref type='bibr' target='#b65'>(Zhang et al., 2010)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Calculation of the decomposition rates of cellulose and hemicellulose</ns0:head><ns0:p>The decomposition rates of cellulose and hemicellulose were calculated after the cellulose and hemicellulose contents of the adult grasshopper feces were determined by the above methods. Statistical analysis of digestibility data was done in SPSS 21.0 software using T-test.</ns0:p><ns0:formula xml:id='formula_0'>&#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890;(&#8462;&#119890;&#119898;&#119894;&#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890;) = c * 240 * 10 -3 * 0.9(0.88) m * &#119889;&#119894;&#119897;&#119906;&#119905;&#119894;&#119900;&#119899; &#119898;&#119906;&#119905;&#119894;&#119901;&#119897;&#119890; * 100% &#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890; &#119889;&#119894;&#119892;&#119890;&#119904;&#119905;&#119894;&#119887;&#119894;&#119897;&#119894;&#119910; = &#119886;&#119898;&#119900;&#119906;&#119899;&#119905; &#119900;&#119891; &#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890; &#119891;&#119890;&#119889; &#119900;&#119899; &#119908;&#8462;&#119890;&#119886;&#119905; &#119904;&#119890;&#119890;&#119889;&#119897;&#119894;&#119899;&#119892;&#119904; -&#119891;&#119890;&#119888;&#119886;&#119897; &#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890; &#119888;&#119900;&#119899;&#119905;&#119890;&#119899;&#119905;</ns0:formula><ns0:p>&#119886;&#119898;&#119900;&#119906;&#119899;&#119905; &#119900;&#119891; &#119888;&#119890;&#119897;&#119897;&#119906;&#119897;&#119900;&#119904;&#119890; &#119891;&#119890;&#119889; &#119900;&#119899; &#119908;&#8462;&#119890;&#119886;&#119905; &#119904;&#119890;&#119890;&#119889;&#119897;&#119894;&#119899;&#119892;&#119904; * 100% Note: c is the sugar concentration (g/L) calculated according to the standard curve, m is the weighed sample mass (g).</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between digestibility and microorganism abundance</ns0:head><ns0:p>The LefSe analysis and Spearman analysis were performed using R and the Psych, Pheatmap and reshape2 package <ns0:ref type='bibr'>(Kostic et al., 2015)</ns0:ref> on the Biomarker Cloud Platform. The correlation between cellulose digestibility and intestinal microbial diversity of grasshoppers was established.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Intestinal microbes in grasshoppers Evaluation of sequencing quality</ns0:head><ns0:p>A total of 702,445 paired-end reads were obtained by sequencing the 9 pooled samples. and 512,109 clean tags were generated after splicing and filtering the paired-end reads. A minimum of 51,643 clean tags were generated for each sample, with an average of 56,901 clean tags. The proportion of effective sequences was 99.48%. The sequencing accuracy of the samples was high and met the standard requirements. Effective tags were the number of effective sequences after filtering chimeras from the clean tags. The number of sequences and the proportion for each sample are shown in Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref> below.</ns0:p></ns0:div> <ns0:div><ns0:head>OTU-Venn analysis</ns0:head><ns0:p>To identify the number of common and unique OTUs among samples, a Venn diagram was used, which intuitively reflects the coincidence of OTUs among samples. As shown in Figure <ns0:ref type='figure'>1</ns0:ref> (A), there were 37 species of bacteria in the intestinal tract common to the three species of grasshoppers. There were 6 species specific to PeerJ reviewing <ns0:ref type='table' target='#tab_6'>PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:ref> Manuscript to be reviewed Shirakiacris shirakii, 11 species specific to Oedaleus decorus asiaticus, and 13 species specific to Aiolopus tamulus. Further analysis of the identifies of the bacteria common to the three grasshopper species indicated that they were mainly composed of two families of Enterobacteriaceae and Enterococcaceae, as shown in Figure <ns0:ref type='figure'>1</ns0:ref>(B), with a relative abundance of 97.57%, indicating that these two families may form the core microflora in the grasshopper intestinal tract.</ns0:p></ns0:div> <ns0:div><ns0:head>&#945;-diversity analysis</ns0:head><ns0:p>As shown in Figure <ns0:ref type='figure'>2</ns0:ref>(A), the rarefaction curves of 9 samples tended to be flat over an increasing number of sequences. The Shannon, Simpson, Chao1, and ACE indices, as well as others, were used to express the &#945;diversity of the microorganisms in the samples. As shown in Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, the coverage of the nine samples was relatively high, reaching 99.97%~99.99%. The above results show that the sequencing data were reasonable and that the vast majority of bacteria in the samples were detected. Different from the rarefaction curve, the species accumulation curve reflects whether the number of samples was sufficient and whether the information covered all the annotated species. As shown in Figure <ns0:ref type='figure'>2</ns0:ref>(B), as the sample number increased, the cumulative curve and the common quantity curve tended to be flat, which demonstrates that the new and common species detected in the sample were both approaching saturation, indicating that the sample size was sufficient and could be used for diversity and abundance analysis.</ns0:p><ns0:p>The &#945;-diversity of 9 samples varied according to the individual. In the three samples of Aiolopus tamulus, the Shannon index of At1 and At2 was much higher than that of At3, while the Simpson index of At3 was the opposite, indicating that the species diversity in samples At1 and At2 was higher than that in At3. Among the three samples of Oedaleus decorus asiaticus, the Shannon index of Od3 was much higher than that of Od1 and Od2, while the Simpson index of Od3 was much lower than that of the other two samples. For the three samples of Shirakiacris shirakii, the Shannon index and Simpson index were not significantly different, which may be related to the difference in the collection time (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>).</ns0:p><ns0:p>The average value of each index of three samples from the same species was calculated and then used to compare and analyze the &#945;-diversity among the different species. The Chao1 index (Figure <ns0:ref type='figure'>2C</ns0:ref>) of Shirakiacris shirakii was significantly higher than that of Oedaleus decorus asiaticus, and the ACE index (Figure <ns0:ref type='figure'>2D</ns0:ref>) was the highest in Shirakiacris shirakii, followed by Aiolopus tamulus, which demonstrates that among the three species grasshoppers, the abundance of species in the intestinal tract of Shirakiacris shiraki was significantly higher than that of Oedaleus decorus asiaticus, with Aiolopus tamulus in the middle. The Simpson index (Figure <ns0:ref type='figure'>2E</ns0:ref>) of Aiolopus tamulus was the smallest, while the index of Shirakiacris shiraki was the largest. The Shannon index (Figure <ns0:ref type='figure'>2F</ns0:ref>) followed the opposite trend to the Simpson index, which indicated that the species diversity in the intestinal tract of Aiolopus tamulus was the highest, followed by the Oedaleus decorus asiaticus, with Shirakiacris shiraki as the lowest.</ns0:p></ns0:div> <ns0:div><ns0:head>&#946;-Diversity analysis</ns0:head><ns0:p>Based on pyrosequencing data, PCoA and UPGMA clustering were carried out to determine &#946;-diversity. As shown in Supplementary figure <ns0:ref type='figure'>1</ns0:ref>, the smaller the distance between points in the figure, the smaller the difference in the intestinal flora structure, and vice versa. It can be seen from the figure that the difference in the intestinal microflora structure between the three samples of Shirakiacris shiraki and two of the samples of Aiolopus tamulus was relatively small, while difference in the intestinal microflora structure between one sample and the remaining two samples for both Oedaleus decorus asiaticus and Aiolopus tamulus was relatively large. The difference in the intestinal microflora structure among the three samples of Shirakiacris shiraki was not large. In addition, the hierarchical cluster tree (Figure <ns0:ref type='figure'>3A</ns0:ref>) shows that the microbial communities of the three species grasshoppers are divided into three groups: (1) group I includes samples A1 and A2 and sample O3, (2) group II includes samples O1 and O2 and sample A3, and (3) group III includes all the samples of Shirakiacris shiraki. In addition, the distance between group &#8545; and group &#8546; was closer, that is, the composition of the intestinal microflora is more similar between those two groups. Taken together, these results show that the intestinal microflora of different species of grasshoppers vary from one another. The intestinal microflora of Aiolopus tamulus and Shirakiacris shiraki are more similar. At the same time, different sampling times will also lead to the recombination of microbial communities.</ns0:p><ns0:p>NMDS (Nonmetric Multidimensional Scaling) analysis can reflect the differences between groups or within groups according to the distribution of samples. As shown in Figure <ns0:ref type='figure'>3B</ns0:ref>, the stress value is less than 0.01, which indicates that the analysis result is extremely reliable. In the figure, it can be seen that there is a large difference in the intestinal community between one sample the remaining two samples for both Oedaleus decorus asiaticus and Aiolopus tamulus, which is related to the different collection times of the samples, indicating that a difference in collection time leads to changes in the microbial community structure of the same species. The three samples of Shirakiacris shiraki along with two samples of Aiolopus tamulus are almost coincident, which indicates that the similarity of the intestinal microflora structure between the two groups was relatively high.</ns0:p><ns0:p>As shown in Figure <ns0:ref type='figure'>3C</ns0:ref>, Ss1, Ss2 and Ss3 were grouped together; At1 and At2 were grouped together; and all (Ss1, Ss2, Ss3 and At2) were grouped with Od3. Od1 and Od2 were grouped with At3. The samples At1 and At2 of Aiolopus tamulus were relatively close to the three samples of Shirakiacris shiraki, which indicates that the intestinal community similarity between Aiolopus tamulus and Shirakiacris shiraki is high, that the difference of the microflora structure between them is relatively small, and that different collection times for the same species can lead to low similarity and large differences in the grasshopper intestinal microflora structure, which is consistent with the above results, indicating that a difference in collection time causes changes in the microbial community structure.</ns0:p></ns0:div> <ns0:div><ns0:head>Intestinal microflora structure of the three species grasshoppers</ns0:head><ns0:p>High-quality sequences obtained from 16S rDNA identification were compared with the database, and a total of 54 genera of 7 phyla, 12 classes, and 20 orders were identified. The composition of each sample is shown in Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>. Once the average relative abundance of different grasshoppers in the same treatment at each classification level is calculated, the average relative abundance can reflect the content of various intestinal microorganisms at the overall level.</ns0:p></ns0:div> <ns0:div><ns0:head>Intestinal microflora structure at the phylum level</ns0:head><ns0:p>The nine samples At1, At2, At3, Od1, Od1, Od2, Od3, Ss1, Ss2, and Ss3 contained 85.65%, 83.51%, 93.45%, 89.51%, 91.43%, 87.32%, 86.92%, 87.33%, and 87.35%, respectively, of the valid sequences that were able to be annotated at the phylum level. Seven phyla were detected in the nine samples. According to the annotation results of the samples at various classification levels (kingdom, phyla, class, order, family, genus and species), as shown in Figure <ns0:ref type='figure'>4A</ns0:ref>, Proteobacteria accounted for the highest relative abundance in the three species of grasshoppers, Aiolopus tamulus, Oedaleus decorus asiaticus, and Shirakiacris shiraki, at 94.10%, 90.72% and 93.94%, respectively. The second highest was Firmicutes, accounting for 5.72%, 8.94% and 5.31%, respectively.Actinobacteria accounted for a relatively high proportion of 0.52% in the intestinal tract of Shirakiacris shiraki, although less than 0.10% in the intestinal tracts of the other two species. Cyanobacteria was relatively abundant in the intestinal tract of Oedaleus decorus asiaticus, at 0.26%, while its abundance in the other two species was very small, accounting for 0.01%. Fusobacteria existed in the intestinal tracts of the three species grasshoppers in trace amounts, accounting for less than 0.10%. Bacteroidetes was found in trace amounts in Aiolopus tamulus and Oedaleus decorus asiaticus but was not detected in the intestinal tract of Shirakiacris shiraki. Tenericutes was only found in trace amount in the intestinal tract of Oedaleus decorus asiaticus, at 0.04%, but was not found in the intestinal tracts of the other two grasshoppers. Additionally, 0.20% unassigned microorganisms were present in the intestinal tract of Shirakiacris shiraki that have not previously been studied.</ns0:p><ns0:p>It is worth noting that the proportion of Firmicutes in At3 intestinal bacteria was 0.24%, which was much lower than that in At 1 (11.01%) and At2 (5.91%) treated with the same method. However, the proportion in sample Od3 (26.74%) was much higher than that in sample Od1 (0.03%) and sample Od2 (0.06%), while the proportion in the three samples Ss1 (3.72%), Ss2 (1.83%) and Ss3 (10.36%) of Shirakiacris shiraki was relatively constant, which could be related to their different collection times, indicating that the abundance of intestinal flora varied over different periods in the same species. Combined with &#945;-diversity analysis, these results show that the diversity and abundance of intestinal microflora varied over different periods in the same species.</ns0:p><ns0:p>Intestinal microflora structure at genus level At1, At2, At3, Od1, Od2, Od3, Ss1, Ss2 and Ss3 contained 54.57%, 68.35%, 93.40%, 89.35%, 90.93%, 87.31%, 86.08%, 85.45% and 87.30%, respectively, of the valid sequences that could be annotated at the genus level. A total of 54 bacterial genera were detected, of which 24 bacterial genera were common among the three species. As seen in Figure <ns0:ref type='figure'>4B</ns0:ref>, Klebsiella accounted for the highest proportion of the microbial community in the three grasshopper species. The top 10 abundant bacterial genera (by average relative abundance) for each of the three species of grasshoppers after data standardization are shown in Supplementary Tables <ns0:ref type='table' target='#tab_2'>1, 2</ns0:ref>, and 3. In the three samples of Aiolopus tamulus, the average relative abundance of Klebsiella, Enterococcus and Enterobacter was greater than 1%, which identifies them as the primary bacteria in the Aiolopus tamulus intestinal tract. The primary bacteria of Oedaleus decorus asiaticus were Klebsiella, Enterococcus, Pantoea, Wolbachia, Enterobacter, and Lactococcus. Klebsiella, Lactococcus, and Staphylococcus were the primary genera of Shirakiacris shiraki. Five bacterial genera were detected only in the intestinal tract of Aiolopus tamulus, namely, Anaerotruncus, Diaphorobacter, Morganella, Proteiniclasticum, and Rikenellaceae_RC9_gut_ group. The proportion of these five bacterial genera in the intestinal tract was not more than 0.1%. Among them, Morganella was not detected in the At3 samples, but was detected in the At1 and At2 samples, and the remaining 4 genera were detected only in the At3 samples but not in the At1 and At2 samples, indicating that there were significant differences in the intestinal microflora diversity of the same species from different time periods. The genera Sphaerotilus and Spiroplasma were only detected in the Manuscript to be reviewed intestinal tract of Oedaleus decorus asiaticus, and Cronobacter was only detected in Shirakiacris shiraki. Therefore, the diversity of the intestinal microorganisms varied by grasshopper species.</ns0:p></ns0:div> <ns0:div><ns0:head>Digestibility results</ns0:head><ns0:p>From Table <ns0:ref type='table' target='#tab_5'>4</ns0:ref>, the cellulose digestibility of the three species of grasshoppers were 43.95%, 38.01% and 44.12%, and there was no significant difference (P&gt;0.05) among the three groups. However, the hemicellulose digestibility in Shirakiacris shirakii at 47.65% was significantly higher (P&lt;0.05) than that in Aiolopus tamulus (17.21%) and Oedaleus decorus asiaticus (24.99%). In addition, the cellulose digestibility in Aiolopus tamulus and Oedaleus decorus was significantly higher than that of hemicellulose, and there was no significant difference between the cellulose and hemicellulose digestibility in Shirakiacris shirakii.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between digestibility and microorganism abundance</ns0:head><ns0:p>In view of the fact that Shirakiacris shirakii can be distinguished from the other two species and that the digestibility of hemicellulose is significantly higher in that organism than in the other two species (P&lt;0.05), we conducted LEfSe analysis (Figure <ns0:ref type='figure'>5</ns0:ref>, Supplementary figure <ns0:ref type='figure'>2</ns0:ref>) on the three species and identified Pseudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, Brachybacterium and other bacteria genera as biomarkers of group difference. The relative abundance of these identified species in Shirakiacris shirakii is significantly higher than that in the other species, which may be related to the degradation of hemicellulose. To further screen out bacteria related to the degradation rate of cellulose and hemicellulose, we calculated the Spearman correlation coefficients (Figure <ns0:ref type='figure'>6</ns0:ref>) for the association between the degradation rate and microflora abundance and identified a number of bacteria whose abundance had a high correlation with the degradation rates of cellulose and hemicellulose. Some of the results highly overlap with the LEfSe analysis, suggesting that these bacteria can be used as candidate bacteria for cellulose and hemicellulose degradation.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>In this experiment, we constructed a 16S rRNA gene library via Illumina MiSeq sequencing and applied it to systematically study the intestinal microflora composition of three grasshopper species for the first time. Among the different grasshopper species, the abundance and diversity of intestinal microorganisms were varied. Through the analysis of &#945; and &#946; diversity, it was found that the diversity of the intestinal microflora in the same species was quite varied depending on the collection time. The grasshoppers in this study were collected from summer and autumn populations from the same location, which meant that there were changes in the host insect habitat. Previous studies have shown that the environmental conditions of the habitat of the host insect can affect the interaction between insects and their symbiotic microorganisms, as well as the species and distribution of symbiotic microorganisms <ns0:ref type='bibr' target='#b42'>(Schmid et al., 2015)</ns0:ref>, indicating that the diversity and function of microorganisms in the intestinal tract of insects are closely related to the habitat conditions in which the insects live. However, there are few reports on whether changes in the environment of host insects affects the species and community composition of intestinal microorganisms and the specific extent of that impact, which is a problem worthy of further study. There were differences in the primary intestinal bacteria among the different species of grasshopper, but the abundance of Proteobacteria was the highest in the intestinal bacteria of all three species of grasshopper, followed by Firmicutes. Bacteria of those two phyla accounted for more than 98% of the total intestinal bacteria of the three grasshopper species, which was consistent with previous reports on the primary species of insect microbiomes. Previous studies have shown that Proteobacteria are the primary bacteria in the intestinal tract of many insects: Schistocerca gregaria in Orthoptera <ns0:ref type='bibr' target='#b11'>(Dillon et al., 2010)</ns0:ref>, Acyrthosiphon pisum in Hemiptera, and Ectropis obliqua <ns0:ref type='bibr' target='#b14'>(Engel &amp; Moran, 2013)</ns0:ref> and Spodoptera frugiperda <ns0:ref type='bibr' target='#b16'>(Gichuhi et al., 2020)</ns0:ref> in Lepidoptera. Among the Lepidoptera insects studied, the primary bacteria in the intestinal tract of Lymantria dispar, Helicoverpa armigera, Bombyx mori and Plutella xylostella larvae are Proteobacteria and Firmicutes <ns0:ref type='bibr' target='#b69'>(Zhou et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b39'>Priya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b4'>Broderick et al., 2004)</ns0:ref>. There was variation in the primary genera in the intestinal tract of the grasshopper species. These primary genera and other less abundant genera all play important roles in the life activities of host insects. The content of Klebsiella in the intestinal tract of the three species grasshoppers in this study was very high, which was similar to the results of <ns0:ref type='bibr' target='#b27'>Liu (2012)</ns0:ref> on symbiotic bacteria in the intestinal tract of Locusta migratoria manilensis using DGGE <ns0:ref type='bibr' target='#b27'>(Liu, 2012)</ns0:ref>. The second most abundant bacteria in our study was Enterococcus. This result is consistent with the previous results where bacteria were found to be the most abundant in the microflora of Schistocerca gregaria. <ns0:ref type='bibr' target='#b25'>(Lavy et al., 2019)</ns0:ref>. In addition, previous studies have shown that Enterococcus can not only help degrade lignocellulose but can also produce biogenic amines, which have important physiological functions, such as promoting host growth and enhancing metabolism <ns0:ref type='bibr' target='#b45'>(Shu, Lu &amp; Xu, 2011;</ns0:ref><ns0:ref type='bibr' target='#b44'>Shil et al.,2014)</ns0:ref>. Enterococcus may encode 1,4-&#946;-cellobiosidase, endoglucanase and &#946;-glucosidase, which are involved in cellulose degradation, and 1,4-&#946;-xylosidase, which is involved in xylan degradation <ns0:ref type='bibr' target='#b60'>(Xia et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b38'>Potrikus &amp; Breznak, 1977;</ns0:ref><ns0:ref type='bibr' target='#b58'>Warnecke et al., 2007)</ns0:ref>; these factors have functions relating to food digestion and absorption. However, some other reported cellulose-degrading bacteria, such as Enterobacter and Pseudomonas <ns0:ref type='bibr' target='#b0'>(Bayer, Shoham &amp; Lamed, 2006;</ns0:ref><ns0:ref type='bibr' target='#b36'>Muhammad et al., 2017)</ns0:ref>, have no significant correlation with cellulose and hemicellulose degradation, and the presence of these bacteria may contribute to eliminating the differences in cellulose digestibility in this study. Acinetobacter participates in host food digestion, degrades harmful compounds, and plays a role in nitrogen transformation <ns0:ref type='bibr' target='#b3'>(Briones-Roblero et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b29'>Liu et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b30'>Mason et al., 2016)</ns0:ref>. Existing studies have shown that Wolbachia plays an important role in the reproductive ability of host insects <ns0:ref type='bibr' target='#b18'>(Hancock et al., 2011)</ns0:ref>, and whether this genus has an effect on the reproduction of grasshoppers requires further attention.</ns0:p><ns0:p>Since the main food source of grasshoppers is cellulose, it is speculated that the intestinal tract of grasshoppers may contain abundant microorganisms capable of degrading cellulose. <ns0:ref type='bibr' target='#b59'>Willis et al. (2010)</ns0:ref> isolated cellulase from the foregut and hindgut of the Carolina wasp Dissosteira carolina, which was highly similar to the &#946;-1,4-endonuclease of bacteria, fungi and invertebrates, including that secreted by the insects themselves <ns0:ref type='bibr' target='#b59'>(Willis et al., 2010)</ns0:ref>. <ns0:ref type='bibr' target='#b55'>Wang et al. (2010)</ns0:ref> isolated and screened 5 strains of bacteria with cellulose degradation function from the intestinal tract of Yunnanacris yunnaneus, including 4 strains of Bacillus and one strain of Pseudomonas, which had CMC and filter paper enzyme activities of 167 &#181;/mLand 9.8&#181;/mL, respectively <ns0:ref type='bibr' target='#b55'>(Wang et al., 2010)</ns0:ref>.The above studies show that grasshoppers have the ability to degrade cellulose efficiently. In this study, the contents of cellulose and hemicellulose in the wheat seedling and feces of three species of grasshoppers adults were detected by colorimetry, and the decomposition rates of cellulose and hemicellulose were calculated and analyzed. The cellulose digestibility in Aiolopus tamulus and Oedaleus decorus was significantly higher than that of hemicellulose. On one hand, this relates result to the structure and PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020) composition of cellulose and hemicellulose. Compared with cellulose, hemicellulose has a very complex structure and composition, including xylose, arabinose, mannose and galactose, etc. In the cell wall, hemicellulose is distributed among many celluloses, embedded in the surface of cellulose microfibers and mixed with cellulose. Therefore, only when cellulose is hydrolyzed can hemicellulose be completely hydrolyzed <ns0:ref type='bibr' target='#b51'>(Vargas, Weiss &amp; Mcclements, 2007)</ns0:ref>. On the other hand, the difference in cellulose and hemicellulose digestibility relates to the type and quantity of microorganisms in the grasshopper's intestinal tract. Intestinal microorganisms can secrete a variety of cellulose digestive enzymes. The activities of cellulase and hemicellulase determine the grasshopper's ability to digest cellulose and hemicellulose.</ns0:p><ns0:p>The cellulose digestibility in the three species of grasshoppers was not significantly different, 43.95%, 38.01%, and 44.12%, respectively. In a previous study, <ns0:ref type='bibr' target='#b26'>Li et al. (2000)</ns0:ref> found that the digestibility of crude fiber in different components of corn straw fed to sheep varied from 34.21%-61.21% <ns0:ref type='bibr' target='#b26'>(Li et al.,2000)</ns0:ref>. <ns0:ref type='bibr' target='#b15'>Fang et al. (2009)</ns0:ref> studied the utilization rate of different straw diets in Xinjiang cattle and found that the digestibility of acid detergent fiber (ADF) and neutral detergent fiber (NDF) in wheat straw was 35.02% and 43.86%, respectively, and that the digestibility of ADF and NDF in corn straw was 44.26% and 51.91%, respectively <ns0:ref type='bibr' target='#b15'>(Fang et al., 2009)</ns0:ref>. Meanwhile, a study by <ns0:ref type='bibr' target='#b67'>Zhao (2015)</ns0:ref> found that the digestibility of cellulose in corn straw by Locusta migratoria manilensis was 15.10% <ns0:ref type='bibr' target='#b67'>(Zhao, 2015)</ns0:ref>. Our results showed that the cellulose digestibility in the three species grasshoppers was significantly higher than that of Locusta migratoria manilensis and was close to that of mammals. Whether this difference was related to a difference in the composition of the feeding material needs to be further studied. However, in terms of cellulose digestibility, the intestinal capacity of grasshoppers is very small compared with that of mammals, but their cellulose decomposition rate is close to that of mammals, which indicates that the ability of Aiolopus tamulus, Oedaleus decorus asiaticus and Shirakiacris shirakii to digest cellulose is indeed strong and that studying the cellulose decomposition rate of grasshoppers may be of great value to the development of a cellulose decomposition bioreactor.</ns0:p><ns0:p>Herbivorous insects usually do not directly digest cellulose, or minimally digest cellulose, but mainly digest starch, sugar and protein in food <ns0:ref type='bibr' target='#b12'>(Douglas, 2009)</ns0:ref>. Moreover, the honey bee gut microbiota digests complex carbohydrates, such as hemicellulose and pectin, thereby acquiring energy <ns0:ref type='bibr' target='#b68'>(Zheng et al, 2019)</ns0:ref>.These insects are mainly limited by nitrogen intake rather than carbon source <ns0:ref type='bibr' target='#b32'>(McNeil &amp; Southwood, 1978)</ns0:ref>. Klebisella plays an important role in ammonia assimilation into amino acids <ns0:ref type='bibr' target='#b43'>(Senior, 1975)</ns0:ref>, and its negative correlation with the digestion rate may be related to this. Similarly, San et al. ( <ns0:ref type='formula'>2011</ns0:ref>)also identified some other bacteria related to nitrogen metabolism, including Staphylococcus, <ns0:ref type='bibr'>Stenotrophomonas, etc (San et al., 2011)</ns0:ref>. However, it cannot be ignored that this study is consistent with previous studies, i.e., grasshoppers have a strong ability to digest cellulose <ns0:ref type='bibr' target='#b46'>(Su et al., 2014)</ns0:ref>, how much of which is due to the action of their own digestive enzymes and how much of which is due to the contribution of microorganisms needs to be further explored.</ns0:p><ns0:p>Yet, it remains to be seen whether cellulose/hemicellulose digestion in these grasshoppers is exclusively intrinsic or mediated by a combination of intrinsic and bacterial-mediated processes. Until now, there has been no direct evidence that grasshoppers rely entirely on gut microbes to break down cellulose and hemicellulose. For herbivorous insects, the efficiency of decomposition and utilization of cellulose and hemicellulose are largely dependent on gut microbes <ns0:ref type='bibr' target='#b21'>(Jehmlich et al., 2016)</ns0:ref>. Corynebacterium and Glutamicibacter have been identified from the intestinal bacteria of Shirakiacris shirakii. And Corynebacterium has been reported to be able to hydrolyze hemicellulose <ns0:ref type='bibr' target='#b5'>(Buschke, Schr&#246;der &amp; Wittmann, 2011)</ns0:ref>. Glutamicibacter isolated from the intestinal tract of Proisotoma ananevae has strong cellulose degradation ability <ns0:ref type='bibr' target='#b56'>(Wang et al., 2018)</ns0:ref>. Clavibacter produces cellulase <ns0:ref type='bibr' target='#b52'>(Waleron et al., 2010)</ns0:ref> and Brachybacterium can degrade cellulose <ns0:ref type='bibr' target='#b64'>(Zhang et al., 2007)</ns0:ref>, which supports the results of our correlation analysis. Many insects have intrinsic cellulases <ns0:ref type='bibr' target='#b8'>(Davison &amp; Blaxter, 2005)</ns0:ref>, and some insects belonging to Acrididae have cellulase that can break down plant cell walls <ns0:ref type='bibr' target='#b6'>(Calderon-Cortes et al., 2012)</ns0:ref>.Combined with the results of this article, we can slate a new hypothesis: the intestinal microorganisms of grasshoppers have a great influence on the decomposition of cellulose/hemicellulose.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study analyzed the intestinal microbial diversity of 3 species of grasshoppers, using the method of 16S rDNA gene library construction. Proteobacteria and Firmicutes are the dominant bacteria in the intestinal microbial communities of the three grasshoppers species. However, the dominant genera of different species grasshoppers are different. Shirakiacris shirakii had the highest bacterial species richness, and Aiolopus tamulus had the highest bacterial diversity. The intestinal microflora structure varied between the different species of grasshoppers, with the intestinal microflora structure of Aiolopus tamulus and Shirakiacris shirakii being the most similar. Meanwhile, the time at which grasshopper specimens were collected also led to changes in the intestinal microflora structure in the same species of grasshoppers.</ns0:p><ns0:p>There was no significant difference in cellulose digestibility between the three species of grasshoppers (P&gt;0.05), while the hemicellulose digestibility of Shirakiacris shirakii was significantly higher than Aiolopus tamulus and Oedaleus decorus asiaticus (P &lt;0.05). In addition, the cellulose digestibility of Aiolopus tamulus and Oedaleus decorus asiaticus was significantly higher than the hemicellulose digestibility.</ns0:p><ns0:p>LEfSe analysis and Spearman correlation coefficients showed that the hemicellulosic digestibility of Shirakiacris shirakii was significantly higher than that of the other two species of grasshopper, which may be related to the presence of Pseudomonas, Stenotrophomonas, Glutamicibacter, Corynebacterium, and Brachybacterium in Shirakiacris shirakii intestinal tract.</ns0:p><ns0:p>This study lays a foundation for the utilization of garsshoppers intestinal microorganisms in the future. Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head>Sequence and proportion results of each sample and bacterial identification results</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed 1 2 Manuscript to be reviewed Manuscript to be reviewed Digestibility of cellulose and hemicellulose in wheat seedlings in three species grasshoppers</ns0:p><ns0:p>The data in the table are expressed as the mean standard error, and the data in the same column with different lowercase letters show significant difference (P&lt;0.05).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed The data in the table are expressed as the mean standard error, and the data in the same column with different lowercase letters show significant difference (P&lt;0.05).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,199.12,525.00,273.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='26,42.52,255.37,525.00,186.00' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Information on the studied samples Species Sample code No. of specimens Locality Collection date</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Aiolopus tamulus</ns0:cell><ns0:cell>At1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>July 15, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>At2</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>July 15, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>At3</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell>Oedaleus decorus asiaticus</ns0:cell><ns0:cell>Od1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Od2</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Od3</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>July 15, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell>Shirakiacris shirakii</ns0:cell><ns0:cell>Ss1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Ss2</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Ss3</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>Baoding, China</ns0:cell><ns0:cell>October 1, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Sequence and proportion results of each sample and bacterial identification results</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='3'>Sample Clean tags Effective tags</ns0:cell><ns0:cell>Proportion</ns0:cell><ns0:cell>Identification result</ns0:cell></ns0:row><ns0:row><ns0:cell>At1</ns0:cell><ns0:cell>53704</ns0:cell><ns0:cell>53325</ns0:cell><ns0:cell>99.29%</ns0:cell><ns0:cell>4 phyla, 7 classes, 11 orders, 18 families, 26 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>At2</ns0:cell><ns0:cell>51643</ns0:cell><ns0:cell>51479</ns0:cell><ns0:cell>99.68%</ns0:cell><ns0:cell>5 phyla, 9 classes, 13 orders, 24 families, 31 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>At3</ns0:cell><ns0:cell>61063</ns0:cell><ns0:cell>61018</ns0:cell><ns0:cell>99.93%</ns0:cell><ns0:cell>5 phyla, 10 classes, 17orders, 28 families, 28 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Od1</ns0:cell><ns0:cell>61047</ns0:cell><ns0:cell>61024</ns0:cell><ns0:cell>99.96%</ns0:cell><ns0:cell>6 phyla, 9 classes, 12 orders, 18 families, 21 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Od2</ns0:cell><ns0:cell>72346</ns0:cell><ns0:cell>72296</ns0:cell><ns0:cell>99.93%</ns0:cell><ns0:cell>6 phyla, 9 classes, 16 orders, 23 families, 27 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Od3</ns0:cell><ns0:cell>53117</ns0:cell><ns0:cell>52034</ns0:cell><ns0:cell>97.96%</ns0:cell><ns0:cell>5 phyla, 7 classes, 11 orders, 17 families, 22 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss1</ns0:cell><ns0:cell>52796</ns0:cell><ns0:cell>52631</ns0:cell><ns0:cell>99.68%</ns0:cell><ns0:cell>5 phyla, 9 classes, 16 orders, 28 families, 32 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss2</ns0:cell><ns0:cell>53296</ns0:cell><ns0:cell>53144</ns0:cell><ns0:cell>99.71%</ns0:cell><ns0:cell>5 phyla, 8 classes, 15 orders, 25 families, 31 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss3</ns0:cell><ns0:cell>53097</ns0:cell><ns0:cell>52485</ns0:cell><ns0:cell>98.85%</ns0:cell><ns0:cell>5 phyla, 8 classes, 13 orders, 24 families, 30 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>Tatal</ns0:cell><ns0:cell>512109</ns0:cell><ns0:cell>509436</ns0:cell><ns0:cell>99.48%</ns0:cell><ns0:cell>7 phyla, 12 classes, 20 orders, 42 families, 54 genera</ns0:cell></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>4</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Statistical results of the diversity index of the intestinal content samples of</ns0:figDesc><ns0:table /><ns0:note>grasshoppers PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)Manuscript to be reviewed 1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Statistical results of the diversity index of the intestinal content samples of grasshoppers</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Simple ID</ns0:cell><ns0:cell>OTU</ns0:cell><ns0:cell>ACE</ns0:cell><ns0:cell>Chao1</ns0:cell><ns0:cell>Simpson</ns0:cell><ns0:cell>Shannon</ns0:cell><ns0:cell>Coverage</ns0:cell></ns0:row><ns0:row><ns0:cell>At1</ns0:cell><ns0:cell>37</ns0:cell><ns0:cell>41.5776</ns0:cell><ns0:cell>40.0000</ns0:cell><ns0:cell>0.3996</ns0:cell><ns0:cell>1.1721</ns0:cell><ns0:cell>0.9999</ns0:cell></ns0:row><ns0:row><ns0:cell>At2</ns0:cell><ns0:cell>47</ns0:cell><ns0:cell>48.7316</ns0:cell><ns0:cell>48.2000</ns0:cell><ns0:cell>0.5780</ns0:cell><ns0:cell>0.9800</ns0:cell><ns0:cell>0.9999</ns0:cell></ns0:row><ns0:row><ns0:cell>At3</ns0:cell><ns0:cell>41</ns0:cell><ns0:cell>48.9659</ns0:cell><ns0:cell>52.2500</ns0:cell><ns0:cell>0.9249</ns0:cell><ns0:cell>0.2079</ns0:cell><ns0:cell>0.9998</ns0:cell></ns0:row><ns0:row><ns0:cell>Od1</ns0:cell><ns0:cell>31</ns0:cell><ns0:cell>41.2173</ns0:cell><ns0:cell>38.2000</ns0:cell><ns0:cell>0.9211</ns0:cell><ns0:cell>0.2320</ns0:cell><ns0:cell>0.9998</ns0:cell></ns0:row><ns0:row><ns0:cell>Od2</ns0:cell><ns0:cell>40</ns0:cell><ns0:cell>49.3557</ns0:cell><ns0:cell>47.2000</ns0:cell><ns0:cell>0.7624</ns0:cell><ns0:cell>0.5464</ns0:cell><ns0:cell>0.9999</ns0:cell></ns0:row><ns0:row><ns0:cell>Od3</ns0:cell><ns0:cell>33</ns0:cell><ns0:cell>39.0695</ns0:cell><ns0:cell>37.6667</ns0:cell><ns0:cell>0.4783</ns0:cell><ns0:cell>1.0977</ns0:cell><ns0:cell>0.9998</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss1</ns0:cell><ns0:cell>50</ns0:cell><ns0:cell>51.9067</ns0:cell><ns0:cell>50.8571</ns0:cell><ns0:cell>0.8528</ns0:cell><ns0:cell>0.4748</ns0:cell><ns0:cell>0.9999</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss2</ns0:cell><ns0:cell>46</ns0:cell><ns0:cell>52.1871</ns0:cell><ns0:cell>51.6000</ns0:cell><ns0:cell>0.8964</ns0:cell><ns0:cell>0.3283</ns0:cell><ns0:cell>0.9998</ns0:cell></ns0:row><ns0:row><ns0:cell>Ss3</ns0:cell><ns0:cell>44</ns0:cell><ns0:cell>62.0907</ns0:cell><ns0:cell>54.1111</ns0:cell><ns0:cell>0.7679</ns0:cell><ns0:cell>0.5609</ns0:cell><ns0:cell>0.9997</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 4 (on next page)</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Digestibility of cellulose and hemicellulose in wheat seedlings in three species grasshoppers Sample digestibility rate of cellulose digestibility rate of hemicellulose</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Aiolopus tamulus</ns0:cell><ns0:cell>43.95&#177;2.02a</ns0:cell><ns0:cell>17.21&#177;2.98b</ns0:cell></ns0:row><ns0:row><ns0:cell>Oedaleus decorus asiaticus</ns0:cell><ns0:cell>38.01&#177;3.96a</ns0:cell><ns0:cell>24.99&#177;4.80b</ns0:cell></ns0:row><ns0:row><ns0:cell>Shirakiacris shirakii</ns0:cell><ns0:cell>44.12&#177;3.60a</ns0:cell><ns0:cell>47.65&#177;3.37a</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49060:2:0:NEW 19 Sep 2020)</ns0:note> </ns0:body> "

"Dear Editors We thank the reviewer and editor for their generous comments on the manuscript. We have made changes to address the questions raised by them. Dr. Xinjiang. Li Associate Professor of Zoology On behalf of all authors. Editor comments (Xiaolei Huang) MAJOR REVISIONS The authors have significantly improved the manuscript and addressed most of the concerns from reviewers. For example, they added rearing conditions and tests used in statistical analysis to make the Methods clearer, and they improved the presentation by adopting multiple-panel figures. However, some minor problems still remain to be addressed. 1. The title of the manuscript can be changed to 'Diversity of the gut microbiome in three grasshopper species using 16S rRNA and determination of cellulose digestibility'. Thanks. The title of the manuscript has been changed according to what you said. 2.The authors mentioned in the Results that Spearman correlation was calculated (Line 320-321), they should state how they did the correlation analysis in the Methods part. Agreed. The Spearman correlation was calculated on the Biomarker Cloud Platform (www.biocloud.org). We have state this detail in the Methods part in line 194 of the manuscript. 3. Currently, the content of the Introduction is suitable, but the authors should improve the diversity and representativeness of citations in the Introduction by citing more references from high-profile journals and international authors. Agreed. In the introduction we have added references from high-profile journals and international authors. In the second paragraph(in line 55), we add the following references: Mueller-Hagedorn, A. & Bockhorn, H. 2007. Pyrolytic behaviour of different biomasses (angiosperms) (maize plants, straws, and wood) in low temperature pyrolysis. Journal of Analytical and Applied Pyrolysis 79, 136-146 DOI 10.1016/j.jaap.2006.12.008 Thompson, D. N., Houghton, T. P., Lacey, J. A., Shaw, P. G., Hess, R. S. 2003. Preliminary investigation of fungal bioprocessing of wheat straw for production of straw-thermoplastic composites. Applied Biochemistry and Biotechnology 105, 423-436 DOI 10.1385/abab:106:1-3:423 Hendriks, A. T. W. M. & Zeeman, G. 2009. Pretreatments to enhance the digestibility of lignocellulosic biomass. Bioresource Technology 100, 10-18 DOI 10.1016/j.biortech.2008.05.027 In the third paragraph(in line 68), we add the following references: Mason, C. J., Jones, A. G. & Felton, G. W. 2019. Co-option of microbial associates by insects and their impact on plant-folivore interactions. Plant Cell and Environment 42, 1078-1086 DOI 10.1111/pce.13430. In the fourth paragraph(in line 74), we add the following references: Dillon, R. J. & Dillon, V. M. 2004. The gut bacteria of insects: Nonpathogenic interactions. Annual Review of Entomology 49, 71-92 DOI 10.1146/annurev.ento.49.061802.123416. Dillon, R. J., Vennard, C. T. & Charnley, A. K. 2002. A note: gut bacteria produce components of a locust cohesion pheromone. Journal of Applied Microbiology 92, 759-763 DOI 10.1046/j.1365-2672.2002.01581.x 4. There are still some minor format problems in the manuscript, for example in the reference list. Thanks. We have corrected these problems. Please see the manuscript for details. Reviewer 1 (Anonymous) Basic reporting Grasshoppers are the notorious pests for some agricultural crops.The authors presented some interesting findings on the gut microbiota of three grasshopper species and gut bacteria confer the cellulose digestibility to help the host to achieve nutrients. This manuscript has been improved significantly and it can be accepted for publication now. Comments for the Author This manuscript has been improved significantly and it can be accepted for publication now. However, there are still some small problems on the journal names in the reference list. Please corrected them before publication. Thanks. We have corrected these problems. Please see the manuscript for details. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. In seasonally breeding birds, the reproductive tract undergoes a dramatic circannual cycle of recrudescence and regression, with oviduct size increasing 5-220 fold from the non-breeding to the breeding state. Opportunistically breeding birds can produce multiple clutches sequentially across an extended period in response primarily to environmental rather than seasonal cues. In the zebra finch, it has been shown that there is a significant reduction in gonadal morphology in non-breeding females. However, the scale of recrudescence and regression of reproductive tissue within a single breeding cycle is unknown and yet important to understand the cost of breeding, and the physiological readiness to breed in such flexible breeders.</ns0:p><ns0:p>Methods. We examined the reproductive tissue of breeding female zebra finches at six stages in the nesting cycle from pre-breeding, to fledging offspring. We quantified the wet mass of the oviduct, the volume of the largest pre-ovulatory follicle, and the total number of pre-ovulatory follicles present on the ovary.</ns0:p><ns0:p>Results. Measures of the female reproductive tract were highest during nesting and laying stages and declined significantly in the later stages of the breeding cycle. Importantly, we found that the mass of reproductive tissue changes as much across a single reproductive event as that previously characterised between birds categorised as breeding and non-breeding. However, the regression of the ovary is less dramatic than that seen in seasonal breeders. This could reflect low-level maintenance of reproductive tissues in opportunistic breeders, but needs to be confirmed in wild non-breeding birds.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The avian reproductive system is typically viewed as a dynamic structure that exhibits dramatic changes in size and development across seasons <ns0:ref type='bibr' target='#b41'>(Williams 2012)</ns0:ref>. For example, in seasonally breeding birds, the reproductive tract undergoes a circannual cycle of regression and recrudescence <ns0:ref type='bibr' target='#b19'>(Johnson &amp; Woods 2007;</ns0:ref><ns0:ref type='bibr' target='#b20'>Keck 1934;</ns0:ref><ns0:ref type='bibr' target='#b44'>Wingfield &amp; Farner 1993)</ns0:ref>. In passerines, measurements taken during non-breeding and breeding periods show that oviductal wet mass increases by up to 220-fold during the breeding season, while the linear dimensions of the largest follicle have been shown to increase by up to 60-fold (see Table <ns0:ref type='table'>1</ns0:ref>). The reproductive cycle in seasonally breeding birds is primarily regulated by day length and, to a lesser extent, is finely tuned by environmental conditions such as rainfall, temperature, and access to nesting sites <ns0:ref type='bibr' target='#b4'>(Dawson et al. 2001;</ns0:ref><ns0:ref type='bibr' target='#b44'>Wingfield &amp; Farner 1993;</ns0:ref><ns0:ref type='bibr' target='#b46'>Wingfield et al. 1992)</ns0:ref>. In temperate environments with distinct seasons, day length is a reliable indicator of food availability.</ns0:p><ns0:p>Therefore, seasonal environments are thought to exert strong selective pressure on reproductive physiology that allows birds to time reproduction during peak seasonal food availability. However, not all bird species breed during discreet or predictable periods of time. Some species exhibit flexible breeding periods or breed opportunistically when conditions become favourable. In opportunistically breeding bird species, reproduction is timed primarily through non-photic cues such as food availability, temperature, and rainfall, and displays a dampened seasonal peak <ns0:ref type='bibr' target='#b6'>(Englert Duursma et al. 2019;</ns0:ref><ns0:ref type='bibr' target='#b12'>Hahn et al. 1997;</ns0:ref><ns0:ref type='bibr' target='#b13'>Hahn et al. 2008;</ns0:ref><ns0:ref type='bibr' target='#b14'>Hau et al. 2008)</ns0:ref>.</ns0:p><ns0:p>In contrast to seasonally breeding birds, opportunistically breeding species are hypothesised to maintain some degree of gonadal development year-round in order to rapidly initiate reproduction when ecological conditions become optimal <ns0:ref type='bibr' target='#b45'>(Wingfield 2008)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Compared to the well-established literature on seasonally breeding birds, relatively few studies have investigated variation in reproductive morphology in opportunistically breeding birds. The studies that have been conducted suggest that there is annual variation in gonad development, but full regression is not always evident <ns0:ref type='bibr' target='#b11'>(Hahn 1998;</ns0:ref><ns0:ref type='bibr' target='#b26'>Perfito et al. 2007</ns0:ref>). This supports the hypothesis that the there is some maintenance of gonads potentially allowing opportunistic breeders to rapidly exploit reproductive opportunities. For example, in wild zebra finches (Taeniopygia guttata), <ns0:ref type='bibr' target='#b26'>Perfito et al. (2007)</ns0:ref> reported a mean follicle size (for the largest follicle in each female) of 3mm 3 and 44mm 3 (early and late within a breeding season, respectively) and a mean follicle size (of the largest follicle) of around 5mm 3 in a non-breeding population (all values estimated from Fig. <ns0:ref type='figure' target='#fig_6'>2</ns0:ref> in <ns0:ref type='bibr' target='#b26'>Perfito et al. (2007)</ns0:ref>). These data suggest that the smallest values found in breeding birds are equivalent to those in non-breeding populations.</ns0:p><ns0:p>However, an important caveat is that the exact breeding status of the females studied by <ns0:ref type='bibr' target='#b26'>Perfito et al. (2007)</ns0:ref> was uncertain. In a laboratory study, <ns0:ref type='bibr' target='#b29'>Prior et al. (2013)</ns0:ref> used a water deprivation treatment to significantly inhibit reproduction in females. Specifically, <ns0:ref type='bibr' target='#b29'>Prior et al. (2013)</ns0:ref> reported that the largest follicle diameter in each female remained 1.8 mm on average. These data suggest follicle volume in water restricted non-breeding females averaged 3.05 mm 3 (using V=4/3&#960;a 3 where V= volume and a = radius of follicle), making them somewhat smaller than those reported by <ns0:ref type='bibr' target='#b26'>Perfito et al. (2007)</ns0:ref> in a non-breeding wild population in an unpredictable environment, but equivalent to late-breeding in a predictable environment. Importantly, however, these values are greater than the minimum size of the fully regressed follicles reported in seasonal breeders (see Supplemental Table <ns0:ref type='table'>S1</ns0:ref>). The significant shift in follicle volume and oviduct mass in water restricted zebra finches, did not coincide with a change in estradiol levels <ns0:ref type='bibr' target='#b29'>(Prior et al. 2013)</ns0:ref>. Further, in wild zebra Manuscript to be reviewed finches detectable estradiol was found in one of nine non-breeding birds in an unpredictable environment, but in none of the five birds tested when breeding in the predictable environment <ns0:ref type='bibr' target='#b26'>(Perfito et al 2007)</ns0:ref>. Both of these findings are surprising given that in birds, estradiol aids in regulating reproduction by stimulating the production of yolk precursors from the liver <ns0:ref type='bibr' target='#b37'>(Wallace 1985)</ns0:ref>, and stimulating oviduct development <ns0:ref type='bibr' target='#b28'>(Pollock &amp; Orosz 2002;</ns0:ref><ns0:ref type='bibr' target='#b39'>Williams 1999)</ns0:ref>. It is possible that changes in estradiol will only be seen during nesting and egg laying when it is stimulating yolk formation and oviduct growth and development <ns0:ref type='bibr' target='#b28'>(Pollock &amp; Orosz 2002;</ns0:ref><ns0:ref type='bibr' target='#b37'>Wallace 1985;</ns0:ref><ns0:ref type='bibr' target='#b39'>Williams 1999)</ns0:ref>. However, studies conducted thus far have not looked at estradiol production in zebra finches at this fine temporal resolution.</ns0:p><ns0:p>Although past studies have established that opportunistically breeding birds broadly maintain a degree of gonadal development when not breeding, no study to date has examined fine scale variation in gonad development within and between reproductive cycles. The average follicle sizes of the non-breeding zebra finches <ns0:ref type='bibr' target='#b26'>(Perfito et al. 2007;</ns0:ref><ns0:ref type='bibr' target='#b29'>Prior et al. 2013)</ns0:ref>, likely represent the minimal values for the largest follicle in each female in this species. However, they leave two important gaps in our knowledge. Neither study <ns0:ref type='bibr' target='#b26'>(Perfito et al. 2007;</ns0:ref><ns0:ref type='bibr' target='#b29'>Prior et al. 2013)</ns0:ref> characterised variation in oviduct tissue or tracked variation in follicle size of birds with known breeding status i.e. across different phases of active breeding such as egg-laying, incubation, offspring rearing etc. As such, the maximal size of both the oviduct and pre-ovulatory follicles is unclear. As a result, and also due to a lack of clarity over the breeding status of birds, it is not clear how quickly, and to what extent reproductive tissues cycle in this model opportunistic breeder. For example, as illustrated in Fig. <ns0:ref type='figure' target='#fig_5'>1</ns0:ref>, in comparison to seasonal breeders (Fig. <ns0:ref type='figure' target='#fig_5'>1A</ns0:ref>), females could regress their tissues within and between reproductive bouts to the same (Fig. <ns0:ref type='figure' target='#fig_5'>1B</ns0:ref>), or lesser extent (Fig. <ns0:ref type='figure' target='#fig_5'>1C</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Studies have suggested that zebra finches consistently maintain some level of gonad functionality, even within a reproductive cycle. For example, female zebra finches can lay eggs within five days of pairing <ns0:ref type='bibr' target='#b15'>(Haywood 1993;</ns0:ref><ns0:ref type='bibr' target='#b38'>Williams 1996)</ns0:ref>. Additionally, studies show that regression of the oviduct commences as females are laying their last egg <ns0:ref type='bibr' target='#b43'>(Williams &amp; Ames 2004</ns0:ref>) and that pairs frequently initiate a new clutch before the previous fledglings are fully independent <ns0:ref type='bibr' target='#b10'>(Griffith et al. 2017)</ns0:ref>. However, no study to date has quantified variation in reproductive tract morphology at different stages throughout the reproductive cycle in an opportunistically breeding bird. Further examination of the extent of variation in reproductive morphology in the zebra finch, as a model opportunistically breeding species, will help us to understand the costs and constraints involved in mounting a reproductive attempt in those birds that have highly flexible breeding times. This is of interest in the context of the rapidly changing ecological conditions that such opportunistically breeding species can face, and the ability of a male and female to physiologically coordinate their reproductive activity and investment <ns0:ref type='bibr' target='#b9'>(Griffith 2019</ns0:ref>).</ns0:p><ns0:p>Here, we investigated variation in female reproductive tissue morphology and circulating hormone levels (i.e. estradiol) across breeding stages of a single reproductive episode in the zebra finch. Given the ability of zebra finches to rapidly initiate reproduction, we predicted that females would maintain some level of gonadal development across a reproductive cycle.</ns0:p><ns0:p>Likewise, we predicted that females would maintain moderate levels of estradiol across most of the reproductive cycle, even when their reproductive development is significantly reduced <ns0:ref type='bibr' target='#b29'>(Prior et al. 2013)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Animals Thirty-six pairs of domestic zebra finch were force paired (i.e. we chose partners) into individual cages and allowed to lay at least one clutch of eggs together prior to the commencement of the study. All individuals were bred and maintained at Macquarie University (Sydney, Australia) and were between 18-24 months of age. Between February and May 2015, pairs were moved into one of 12 outdoor aviaries (L x W x H: 4.1 x 1.85 x 2.24 m, 3 pairs/aviary) that were physically, but not visually or vocally separated from other pairs. All procedures were conducted according to relevant national and international guidelines and were approved by the Macquarie University Animal Ethics Committee (Animal Research Authority 2013/29).</ns0:p></ns0:div> <ns0:div><ns0:head>Experimental design</ns0:head><ns0:p>Pairs were then randomly assigned to one of six sampling time points (n=6 per time point) across the breeding cycle: pre-breeding (paired, but without a nest for a total of four weeks including first two weeks considered acclimation), nesting (during nest building, once at least the bottom of the nestbox was lined with material), laying (day of laying third egg), incubation, posthatch (six days post hatching), and fledging (day after first fledgling was observed out of nest).</ns0:p><ns0:p>We chose not to sample on day one of egg laying or immediately post-hatch in order to ensure pairs were committed to the breeding stage (i.e. laying a full clutch and rearing nestlings). All birds were given two weeks to acclimate to the new aviary conditions, after which they were provided with nest boxes and nesting material (with exception of those birds in the pre-breeding group). All pairs were checked daily during acclimation and experimental time period to note change in breeding stage, and ensure no nest building or egg laying was occurring in acclimating or pre-breeding pairs.</ns0:p></ns0:div> <ns0:div><ns0:head>Blood and tissue collection</ns0:head><ns0:p>At the designated sampling time point, a whole blood sample was collected from each female within 5 minutes of initial disturbance, and the sample held on ice (for a maximum period of 1 hour) before plasma was separated from red blood cells and plasma stored at -80 &#186;C until later analysis of estradiol. Females were euthanised using deep anaesthesia with isoflurane. The oviduct was then dissected out (cut off at cloacal juncture) and weighed (after lightly blotting to remove any blood, and if present, eggs were removed prior to weighing). Next, the ovary was dissected out and photographed from two angles, which were then used to later assess the total number of pre-ovulatory follicles present. Finally, on the fresh ovary, the size of the largest preovulatory follicle was measured (three perpendicular measures) using digital callipers (to nearest 0.01mm). Follicular volumes were calculated using the formula for an ellipsoid, V =4/3&#960;abc, where the axes a, b, and c are equal to half of the value recorded for each of the three perpendicular measures, to account for deviations from a spheroid in large pre-ovulatory follicles. All nestlings and fledglings were successfully fostered to other pairs of zebra finch in the Macquarie University breeding colony.</ns0:p></ns0:div> <ns0:div><ns0:head>Plasma estradiol analysis</ns0:head><ns0:p>Plasma estradiol levels were quantified using a 17-&#946; estradiol high-sensitivity Enzyme Manuscript to be reviewed 200&#181;l and, following incubation and washing steps, sample absorbance measured at 405nm using a Varioskan LUX microplate reader (Thermo Scientific). All samples were measured in triplicate, and estradiol levels extrapolated from a ten-point standard curve ranging from 1.95 to 3,000 pg/ml, with a minimum detection limit of 0.8 pg/ml. The average intra-plate coefficient of variation was 9.99% and the inter-plate variation 6.55%. Samples were randomly distributed across plates. One pre-breeding sample was not run as it appeared dehydrated.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>All analysis was done with R v. 3.5.3 (R Core Team 2019) in the R package lme4 <ns0:ref type='bibr' target='#b1'>(Bates et al. 2015)</ns0:ref>. We used linear models to examine the effect of breeding stage on oviduct mass (log transformed) and volume of the largest pre-ovulatory follicle. Next, we examined the impact of breeding stage on the number of pre-ovulatory follicles using a Bayesian generalized linear model via Stan with negative binomial family function (to control for zero inflation) and breeding stage as a fixed effect using the R package rstanarm <ns0:ref type='bibr' target='#b8'>(Goodrich et al. 2018)</ns0:ref>. In these models, we included scaled mass index (SMI: using tarsus length and body mass, <ns0:ref type='bibr' target='#b25'>(Peig &amp; Green 2009)</ns0:ref> as a covariate, but when considered alone there was no significant difference in SMI between breeding stages (ANOVA; F 5,30 = 0.84, P = 0.53). We did not run a formal statistical analysis on estradiol data due to the low number of detectable samples (see below). Figures were constructed using the R package yarrr (Phillips 2017), and modelling assumptions (normality and heterogeneity of variance of residuals) were assessed visually (following <ns0:ref type='bibr' target='#b47'>Zuur et al. 2009</ns0:ref>).</ns0:p><ns0:p>All tests were two-tailed and considered significant at &#61537; &lt; 0.05, with significance estimates via lmerTest <ns0:ref type='bibr' target='#b21'>(Kuznetsova et al. 2016)</ns0:ref> for models, and emmeans <ns0:ref type='bibr' target='#b33'>(Russell 2019)</ns0:ref> for pairwise comparison of time points corrected for multiple testing using Tukey HSD p-value adjustment.</ns0:p><ns0:p>Data presented are mean &#61617; standard deviation unless otherwise noted.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Change in reproductive tissues</ns0:head><ns0:p>Oviduct mass declined significantly between laying (0.43 &#61617; 0.09 g) and incubation (0.06 &#61617; 0.03 g), reaching its lowest mass during the post-hatch period (0.03 &#61617; 0.01 g) and remaining low for the remainder of the breeding cycle (Table <ns0:ref type='table'>1</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_6'>2A</ns0:ref>). Similarly, following a peak in size during nesting (74.9 &#61617; 75.5 mm 3 ), follicle volume decreased significantly by incubation</ns0:p><ns0:p>(2.48 &#61617; 0.8 mm 3 ) before reaching its lowest volume during the post-hatch (2.45 &#61617; 1.0 mm 3 ) period (Table <ns0:ref type='table'>1</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_6'>2B</ns0:ref>). As expected, the number of ovarian pre-ovulatory follicles was highest during the pre-breeding and nesting stage. The number of follicles then declined during laying, before reaching zero during both the incubation and post-hatch period. The number of preovulatory follicles increased again during the fledgling period, albeit non-significantly and to a lesser degree than the number observed in the pre-breeding stage (Table <ns0:ref type='table'>2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_6'>2C</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Estradiol detection and levels</ns0:head><ns0:p>Estradiol levels were non-detectable in 22 of the 35 samples assayed (62.9%), although one detectable plasma sample appeared dehydrated and was therefore excluded. Of the remaining detectable samples (n = 13), there was a tendency for these samples to be present in the early stages of the breeding cycle and the highest average value was observed during the nesting stage (Fig. <ns0:ref type='figure'>3</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Across a single reproductive episode, from pre-breeding through to fledging of nestlings, female zebra finches showed dramatic variation in the size and development of their reproductive tract tissue (Fig. <ns0:ref type='figure' target='#fig_7'>4</ns0:ref>). Oviduct and ovary weight were highest during nesting and laying and regressed during the later stages of the breeding cycle. These results are generally consistent with other studies in this species <ns0:ref type='bibr' target='#b43'>(Williams &amp; Ames 2004</ns0:ref>) and a range of northern hemisphere, temperate zone birds <ns0:ref type='bibr' target='#b3'>(Dawson 2008;</ns0:ref><ns0:ref type='bibr' target='#b17'>Hurley et al. 2008;</ns0:ref><ns0:ref type='bibr' target='#b18'>Jacobs &amp; Wingfield 2000;</ns0:ref><ns0:ref type='bibr' target='#b31'>Ramenofsky 2011</ns0:ref>). Similar to the variation in ovary development that we described here, the length of the sperm storage tubules in females vary across a reproductive cycle <ns0:ref type='bibr'>(Pellatt, 1998)</ns0:ref> suggesting that the entire female reproductive changes in opportunistically breeding birds. We found that pre-ovulatory follicular development followed a similar pattern, though some females already possessed pre-ovulatory follicles when their first chicks fledged. Importantly, while the observed regression of the female reproductive tract in zebra finches is reminiscent of the regression of these tissues in temperate zone birds, the magnitude of these changes appears to be considerably lower in the zebra finch (Supplemental Table <ns0:ref type='table'>S1</ns0:ref>). As such, the reproductive tract regression observed in zebra finches can be considered more similar to the resting phase (e.g. the period between first phase differentiation and breeding when development can be suspended: <ns0:ref type='bibr' target='#b34'>(Sossinka 1980</ns0:ref>)) of a photosensitive seasonally breeding bird than to that of the fully regressed photorefractory state of such a species. It is widely held that the circannual recrudescence and regression cycle observed in seasonally breeding species mediates the energetic and physiological costs of egg production and the maintenance of reproductive tract tissues. These costs include protein depletion and compromised flight ability, as well as non-resource-based costs such as the negative pleiotropic rearing <ns0:ref type='bibr' target='#b36'>(V&#233;zina &amp; Williams 2003)</ns0:ref>. Given this, the semi-regressed 'resting phase' state we observed in female zebra finches would likely allow females to rapidly recommence breeding once their current brood is independent, whilst also allowing them to mitigate energetic costs of reproduction via the rerouting of energy from reproductive tissue investment to other activities such as chick rearing. Such rapid turnaround in breeding attempts is supported by our finding that some females exhibited pre-ovulatory follicles as early as the day after the first chick fledged, and is consistent with breeding observations in captive populations <ns0:ref type='bibr' target='#b10'>(Griffith et al. 2017)</ns0:ref>.</ns0:p><ns0:p>The variation between individuals with respect to the presence of pre-ovulatory follicles during the fledgling period could be considered surprising given that all birds were housed under identical conditions. However, zebra finch pairs frequently exhibit considerable variation in the number of days taken to initiate a new clutch, which would likely reflect underlying variation in the presence of pre-ovulatory follicles. In turn, this variation can be attributed to variation in breeding experience as a pair <ns0:ref type='bibr' target='#b16'>(Hurley et al. 2020</ns0:ref>) and variation in individual condition and lifehistory trade-offs <ns0:ref type='bibr' target='#b38'>(Williams 1996;</ns0:ref><ns0:ref type='bibr' target='#b40'>Williams 2005)</ns0:ref>. The observed variation in follicle development is broadly consistent with findings in wild zebra finches in unpredictable, arid</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed environments. Specifically, <ns0:ref type='bibr' target='#b26'>Perfito et al. (2007)</ns0:ref> reported a proportion of female birds were not completely regressed and had small follicles present when sampled despite an apparent absence of breeding within the population (49% in predictable temperate population during winter and 58% during a drought in late Spring in an unpredictable arid population).</ns0:p><ns0:p>Estradiol levels observed in this study were highly variable and a large proportion of the samples were below the detection level. Whilst it was disappointing that we were unable to assay the level of estradiol in so many of our samples, we feel that the data are worth publishing, and that, for the reasons discussed below, they are likely to reflect the underlying biology, and really low values, rather than methodological problems. Past studies have also reported large numbers of undetectable samples. For example, in a study of wild zebra finches using identical methods, estradiol was reported as non-detectable in 38.3% of samples <ns0:ref type='bibr' target='#b2'>(Crino et al. 2018)</ns0:ref>, and in an earlier study of another passerine, the Western scrub-jay (Aphelocoma californica) the authors were unable to detect estradiol levels in the majority of their samples using similar methods <ns0:ref type='bibr' target='#b32'>(Rensel et al. 2015)</ns0:ref>. The higher percentage of detectable samples in <ns0:ref type='bibr' target='#b2'>Crino et al. (2018)</ns0:ref> are likely explained by the use of gonadotropin-releasing hormone challenges to induce maximum estradiol release, whereas as our study examines natural endogenous levels. Finally, the peak in estradiol levels observed during the early stages of the reproductive episode, i.e. nesting and laying, is in line with the essential role estradiol plays in the growth and development of the oviduct <ns0:ref type='bibr' target='#b28'>(Pollock &amp; Orosz 2002;</ns0:ref><ns0:ref type='bibr' target='#b39'>Williams 1999)</ns0:ref>, as well as egg yolk and eggshell formation <ns0:ref type='bibr' target='#b23'>(Mishra et al. 2019)</ns0:ref>. This suggests that levels in the zebra finch are generally low, and in many individuals below the threshold of detectability, but that they do show the anticipated pattern of variation across the cycle.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Somewhat surprisingly, we found that ovary and oviduct development of females in the pre-breeding stage did not differ from those in the nesting stage. There are at least two plausible explanations for these results. First, domestic zebra finches are highly motivated to breed, and, when paired, females will frequently lay eggs on any suitable surface despite a lack of nest boxes and nesting material. Moreover, as oviduct and follicular development is sensitive to a change in circulating hormones, e.g. estrogen, lutenizing hormone, follicle stimulating hormone <ns0:ref type='bibr' target='#b19'>(Johnson &amp; Woods 2007;</ns0:ref><ns0:ref type='bibr' target='#b28'>Pollock &amp; Orosz 2002)</ns0:ref>, the still somewhat favourable conditions experienced by these birds (e.g. ad lib water and food) may have been sufficient to support elevated levels of hormones linked to reproductive tissue development. Thus it seems likely that females defined as pre-breeding in our study are functionally equivalent to seasonal breeders in a pre-laying state (when predictive cues have primed reproductive tissue), and not a completely non-breeding state.</ns0:p><ns0:p>It is unclear how long females will maintain readiness, especially in variable ecological condtions. In normal captive conditions, it can be very difficult to prevent birds from breeding due to the provision of relatively good resources <ns0:ref type='bibr' target='#b10'>(Griffith et al 2017)</ns0:ref>. Even though the females in our pre-breeding treatment were unable to physically breed due to the lack of a nest site, this is quite an unnatural constraint, that would not be encountered in the wild and it seems likely that physiologically these females were ready to breed. Second, we defined pairs as nesting once males were observed actively building nests. Thus, our distinction between pre-breeding and nesting stage may have been too coarse to detect differences between these stages. Pairs may have already established themselves into reproductive mode in the days before nest building started through the many subtle behaviours and forms of communication that we expect in such closely coordinated partners <ns0:ref type='bibr' target='#b9'>(Griffith 2019)</ns0:ref>. It is therefore very difficult in captivity to get zebra finches to a state where they can be confidently established to be in a stable and lengthy non- Manuscript to be reviewed breeding mode. It therefore remains to be checked in a wild population whether the gonadal and endocrine state that we have reported in the pre-breeding birds is truly reflective of non-breeding birds. To an extent however, we are reassured that the wild birds assessed by <ns0:ref type='bibr' target='#b26'>Perfito et al. (2007)</ns0:ref> as being in a non-breeding state had a range of folicle size that was similar to those found in our pre-breeding birds (Supplemental Table <ns0:ref type='table'>S1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>Detailed examination of the female reproductive tract of zebra finch across a single breeding episode revealed considerable variation in oviduct and ovary development, and a pattern of limited reproductive tract regression during the later stages of the reproductive cycle (i.e. incubation, post-hatch). We suggest the pattern of regression we observed is consistent with the lack of a photorefractory period with less regression than seen in another opportunistically breeding species <ns0:ref type='bibr' target='#b11'>(Hahn 1998)</ns0:ref> Manuscript to be reviewed hemisphere, and it is likely that quite different patterns will be seen in Australia and other ecologically unpredictable and aseasonal environments <ns0:ref type='bibr' target='#b0'>(Astheimer &amp; Buttemer 2002)</ns0:ref>. Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>Immunoassay (EIA) kit (Cat No. ADI 901-174, Enzo Life Sciences) following the standard protocol. Briefly, plasma samples (10-30&#181;l) were diluted in assay buffer to a final volume of PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)Manuscript to be reviewed effects of maintaining high hormone levels, e.g. immunosuppression (reviewed in<ns0:ref type='bibr' target='#b40'>Williams 2005)</ns0:ref>. The idea that such costs influence reproduction is further supported by the fact that seasonally breeding birds typically only engage in one energetically expensive life history stage (e.g. reproduction, moult, migration) at a time<ns0:ref type='bibr' target='#b7'>(Follett 2015;</ns0:ref><ns0:ref type='bibr' target='#b45'>Wingfield 2008)</ns0:ref>. Furthermore, a number of seasonally breeding species have been shown to shift their metabolic rates with reproductive state (e.g. great tit, Parus major<ns0:ref type='bibr' target='#b24'>(Nilsson &amp; R&#229;berg 2001)</ns0:ref>; European starlings, Sturnus vulgaris:<ns0:ref type='bibr' target='#b35'>(V&#233;zina &amp; Williams 2002</ns0:ref>)), with this change in metabolism being related to changing energetic demands of reproductive tissue, as well as the liver and gizzard during chick-</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>, and stands in stark contrast to observations in seasonally breeding birds. By dampening the degree of regression of the reproductive tract, female zebra finches might maintain a general state of reproductive readiness, whilst also mediating some of the energetic costs associated with reproduction. Future studies could test this hypothesis by examining the metabolic costs associated with partial reproductive regression in opportunistically breeding birds. Furthermore, future studies aimed at determining whether similar patterns of variation in female reproductive tract morphology are observed in the many other species that show a similar or greater extent of reproductive plasticity with respect to phenology (Englert Duursma et al. 2017) would be valuable. To date much of the focus on the extent of female reproductive tract variance has focused on seasonal breeders of the northern PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='27,42.52,70.87,525.00,393.75' type='bitmap' /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:06:50021:1:0:NEW 1 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Department of Biological Sciences Macquarie University Sydney, NSW, Australia 1 September 2020 Dear Editor Harrison We thank you for allowing us to address the thoughtful comments made by yourself and the two Reviewers and resubmit the manuscript. We have addressed all the comments and incorporated changes where appropriate, and feel it has helped focus the manuscript. In particular we have de-emphasised estradiol while further justified reporting it in the manuscript. We believe that the manuscript is now suitable for publication in PeerJ. Yours faithfully, Laura L. Hurley On behalf of all authors. Rebuttal to Editor and Reviewer comments Please note: Reviewer original comments are in normal type, Response to Reviewer comment is in bold type Editor comments (Xavier Harrison) Your manuscript has now been assessed by two expert reviewers, whose detailed comments are appended below. Both found your study interesting and agree it addresses an important question, but several issues require clarification in the revision. In particular I'd like to see some justification of the apparent disparity between the estradiol results and their relatively strong prominence in the title and abstract, as raised by rev. 1. We agree that there is a disparity in the emphasis put on estradiol, and have reduced the prominence of this in the revised manuscript. For Fig. 3, I commend the authors for providing raw data alongside summary statistics, but I'd argue the triple combo of quasi-boxplot, violin plot, and raw data points is a lot for the reader to take in visually. I'd be tempted to ditch the box plots, though a thin bar for the mean may still add value. We understand the figure label could have made this presentation of the data clearer. We have changed the style to make it more visually simple. I look forward to seeing a revision. Reviewer 1 (Nicola Hemmings) Basic reporting There are a few minor editorial changes required, as well as some more methodological detail. The title and abstract do not provide a totally accurate reflection of the results so require re-writing. There is too much focus on the estradiol part of the study (which ultimately didn't work) in the abstract and title. We agree that there is a disparity in the emphasis put on estradiol, and have reduced the prominence of this in the revised manuscript. The introduction would benefit with some more explanation of and justification for the estradiol question (and why other key reproductive hormones were not considered). We have provided greater clarity regarding the rationale for investigating estradiol and clarify that it was the only hormone assayed. A more detailed response to this issue is provided below to the detailed comment. Table 1 could arguably be a supplementary file/appendix. It also needs some more information to be useful in the context it is intended (specifically, information on when sampling was carried out in each study is important for comparison with the current study). Figure 3 requires a clearer legend and there are some conceptual issues with Figure 1. We agree with these comments and have put former Table 1 in the supplement, and provide more information on the timing in these other species (see detailed comment below). Figure 1 and 3 comments are addressed below in the detailed comments section. I'm not convinced the data obtained allow the hypotheses to be satisfactorily tested. We have dealt with this comment in the detailed comments section below. Experimental design Further data are required to fully answer the questions posed by this study. If this is not possible, the study's aims/scope need to be adjusted and interpretation of the results tempered. More detail is required in parts of the methods. These points are all expanded upon in my comments to authors. We agree that the framing of the study could be tempered slightly due to methodological limitations. These issues are addressed in detail where the specific comments are made below. Validity of the findings Further data are required to fully answer the questions posed by this study. If this is not possible, the study's aims/scope need to be adjusted and interpretation of the results tempered. These points are all expanded upon in my comments to authors. Again, we agree that the framing of the study should be tempered slightly due to certain limitations, and have now done so in the revision. We have also further addressed the comment in detail where the specific comments are made below. Comments for the Author This manuscript presents the interesting question of how the oviduct changes throughout a reproductive cycle in an opportunistically breeding bird, the zebra finch. Our current understanding of how the reproductive tissues of birds changes from nonbreeding to breeding state is largely limited to seasonal breeders such as temperate songbirds. In seasonal breeders, the oviduct in females (and testes in males) grows at the start of the breeding season in response to hormonal changes triggered by increasing day length, and regresses significantly after breeding, presumably as a cost-saving mechanism. This growth and regression take place over a relatively predictable and stable timeframe, allowing the timing of reproduction to be matched with environmental conditions. Opportunistic breeders, however, tend to breed in unpredictable environments, responding quickly to optimal breeding conditions. How they achieve this is poorly understood, despite the fact that in captivity, opportunistically breeding species like the zebra finch have been recorded to produce eggs less than a week after pairing with a male. How this rapid response happens at the mechanistic level, and what the costs might be, are fascinating questions. I was pleased to see a study focused on them. The manuscript is generally well written and straightforward, but I have some concerns about the methods and interpretation/presentation of the results. I also have some additional questions/ideas that I would like the authors to consider. The key issues are listed in order of importance here, but see also the specific comments afterwards for more minor comments and suggestions. Key concerns 1. The study doesn't explicitly measure 'non-breeding' state, so we do not know what the baseline values are for this species. The earliest sampling period is 'pre-breeding', which is before a nest site and material was provided. However, if I understand the methods correctly, females were already paired with a male that they had produced a clutch with previously, before they were moved to the experimental cage. It is therefore not clear that these females were in a 'baseline' reproductive condition (especially since some females of this species will lay on the cage floor if nesting sites are not available). The authors note this at the end of the discussion, but do not sufficiently deal with the implications of this in terms of their comparisons with seasonal breeders and their interpretation of patterns in Figure 1 (see specific comments below). It would be useful to have some measure of oviduct size from a group of females that haven't been paired, so that a true baseline state (and variation within) can be inferred. We agree that use of domesticated birds in this study can cause issues with the creation of a baseline reproductive condition, and have made sure to emphasis this caveats more specifically through out the manuscript. The issue is that, as an opportunistic breeder, the zebra finch is in breeding condition when the ecological conditions are right. In the wild there will be periods of austerity in which females may be in a non breeding state. However, in captivity, where good quality food is provided ad libitum females are likely always in breeding condition. We have clarified this logistical point in the discussion. We did not use any females that were unpaired because that is also not a natural state in the wild. We felt that leaving the female with the male for a pre-breeding sample and restricting nesting ability is appropriate baseline for this study. Due to the size of cages, we were able to monitor the production of eggs by these females and can ascertain that they weren’t actively laying at the time of the prebreeding sample, and have made a comment to this affect in the methods. We have noted that females from this flock when single sex housed will still lay eggs if nest boxes are provided. Therefore, we do recognise that to achieve true non- breeding state in these birds we would likely have to manipulate their situation further by restricting food, water, and potentially altering temperature. This was however beyond the scope of this study, and is actually quite difficult to achieve in the species. The key take away, even with these domesticated birds, is that we saw a rapid and dramatic change within the reproductive cycle that non- flexible breeders typically only show with seasonal/photorefractory shifts. This finding illustrates the importance of ascertaining the birds breeding state instead of trying to infer it indirectly from the state of reproductive tissue. Further, this demonstrates that even domestic zebra finch females are cycling the development of their reproductive system, and not keeping it at a constant ready state. It is likely that during extreme hot, cold, dry, or predictable seasonal periods wild birds will show a more complete regression of follicular development as with Perfito et al 2007’s predictable climate non-breeding sample. However, in the same study the non-breeding sample from the unpredictable climate suggests that maintaining low-level development may be a norm for this species in non-temperate areas. 2. The study explicitly aims to quantify how oviduct size changes throughout a reproductive cycle in an opportunistic breeder, for comparison with what is known about seasonal breeders. In this study, however, opportunistic breeding is confounded with domestication and captivity. It seems likely that the costs of maintaining reproductive tissue would be lower for captive birds with ad lib food etc, than it would be for wild birds. Moreover, domesticated strains may have been selected for high reproductive output and therefore more likely to be 'productive' (e.g. domestic chickens are an extreme example of this). These factors will surely influence oviduct condition (just as they do body condition), so it would have been ideal to have some wild comparison data (even just at one non-breeding and one breeding time point) to see if the patterns in captive birds are generally representative of wild birds. If it's not possible to add this, the possible effects of captivity/domestication should at least be discussed in the manuscript. We agree that to fully address this issue a comprehensive wild study tightly tracking the reproductive cycle is required, as selection for reproduction in domestic birds could complicate the degree to which these birds shut down their reproductive tissues. However, such a study is beyond the scope of the current study and we believe that the data are of value. Nonetheless, we have made sure to emphasis the domestic caveat more specifically throughout the manuscript. We also point out in the discussion that the low values of females in our study are very similar to those found by Perfito in their study of wild birds. 3. The estradiol part of the study largely failed. Because of this, the data obtained for this part of the study are very few and potentially not reliable. Yet, the estradiol 'result' is made to be a focal point of the manuscript via its inclusion in the title and coverage in the abstract (without any indication of the test failure). The emphasis needs to be taken off of the estradiol part of the study in the title and abstract. I support including information about the attempted trial and failures (as well as ideally some attempt to explain why), because it is useful for other researchers to be aware of potential methodological issues in the future. However, I do not think very much at all should be inferred from the data obtained. More generally, I also wonder why estradiol was focused on exclusively (especially given the poor performance of this test), in preference to other important reproductive hormones such as FSH or LH? We have reduced the emphasis on estradiol throughout the manuscript. We did not foresee having so many samples not returning results, given previous success with the same assay in zebra finches (Crino et al. 2018). We have left the results in as we think it is useful to document the trial and uneven success in results. Part of the issue of low detection could come from the fact that the estradiol test requires a large amount of plasma for the assay, but again given previous success we were confident in our handling of the samples. Given the amount of plasma used, only one hormone could be assayed from the single bleed taken before sacrifice to try to ensure we had enough plasma to run the assay. Estradiol was chosen because of the dramatic change in oviduct size seen, as it is known that Estradiol plays a key role in stimulating oviduct development. In my opinion, a revision of this manuscript should either (a) be rewritten to focus primarily on the oviduct size data alone, framed more simply and with the interpretation of the results somewhat tempered (i.e. taking into consideration the lack of a true 'baseline' measure and the confounding issue of captivity/domestication) OR (ideally) (b) include additional data to resolve these issues. While option (b) is obviously more time consuming and dependent on the availability of funds for further work, it would ultimately make this paper far more useful and interesting. We thank you for this suggestion and have tempered the framing of the paper in relation to domestic birds and estradiol. Taking further samples at this time is not possible. Below are some more specific comments on the manuscript (line numbers referred to), including some developments on the key points made above. I hope the authors find these comments useful when revising their manuscript. Abstract line 20 (and throughout MS): use of 'recrudescence'. This is a somewhat obscure word that I've never heard used in this context. When I looked it up, it seems to be most commonly used to describe disease relapse. I would personally prefer a more straightforward word, perhaps simply 'growth' or 're-growth' (as is typically used in similar studies). While we agree that the first Google hits for recrudescence are often related to disease reoccurrence, recrudescence in a common term used specifically to refer to the redevelopment of reproductive tissues in animals that undergo gonadal cycling. Its use in birds is not just limited to seasonal breeding birds, but also has been used in opportunistic breeders. Examples: Chmura, H.E., Wingfield, J.C. and Hahn, T.P., 2020. Non‐photic environmental cues and avian reproduction in an era of global change. Journal of Avian Biology, 51(3). Hahn, T.P., 1998. Reproductive seasonality in an opportunistic breeder, the red crossbill, Loxia curvirostra. Ecology, 79(7), pp.2365-2375. Perfito, N., Meddle, S.L., Tramontin, A.D., Sharp, P.J. and Wingfield, J.C., 2005. Seasonal gonadal recrudescence in song sparrows: response to temperature cues. General and comparative endocrinology, 143(2), pp.121-128. Urbanski, H.F., Doan, A. and Pierce, M., 1991. Immunocytochemical investigation of luteinizing hormone-releasing hormone neurons in Syrian hamsters maintained under long or short days. Biology of reproduction, 44(4), pp.687-692. Wingfield, J.C., Hahn, T.P., Levin, R. and Honey, P., 1992. Environmental predictability and control of gonadal cycles in birds. Journal of Experimental Zoology, 261(2), pp.214-231. line 27: ‘Physiological readiness’ rather than ‘physiologically readiness’ We have made this change line 33-35: the estradiol part of this study didn't really work and we can't infer much from the data obtained. But in the abstract it is presented as a straightforward result. I would remove this from the abstract (and remove the reference to estradiol from the title). We have removed estradiol from the title and the abstract, so that it isn’t emphasised as a clear-cut result. line 35-37: I think the abstract should include something about the regression being less dramatic in the zebra finch than has been previously found for seasonal breeders. To me, this is probably the most interesting and illuminating result (as you nicely explain at the end of your discussion). The caveat to this is, of course, if this is truly a consequence of being an opportunistic breeder, rather than just a consequence of captivity/domestication. Thank you for the suggestion, we have emphasised the findings in the abstract, with the caveat that it should be confirmed in wild birds. Introduction line 69-70: 'average' and 'mean' are used interchangeably here, which is a bit confusing and unclear. Presumably 'average' means 'mean'? If so, use 'mean' consistently We have changed both to mean to be consistent in meaning and with wording used by Perfito et al. 2007. line 72: remove the bracket around (Perfito et al. 2007) to read Perfito et al. (2007) since the study in question is being directly referred to. This correction has been made. line 76: it is not clear what 'maintained partially developed gonads when not breeding' means – partially developed compared to what? If all non-reproductive females have gonads that appear to be at the same level of development, presumably this is their baseline (i.e. undeveloped) state? Perhaps opportunistic breeders baseline is simply more developed than seasonal breeders (or to flip it round, seasonal breeders regress more dramatically than opportunistic breeders)? This also has implications for how the situation is depicted in Figure 1C (see later comment on this). This section has been more clearly worded to reflect that Prior et al. 2013 did not have a clear baseline, and their results are compared to Perfito et al. 2007 findings. This comparison is to show that the Prior et al. water restricted follicle volume is between the follicular volumes seen in non-breeding wild zebra finches in predictable and unpredictable environments (Perfito et al 2007). line 76: remove the bracket around (Prior et al. 2013) to read Prior et al. (2013) This correction has been made. line 80-81: (linked to previous comment) could there be something else about seasonal breeders (i.e. the environments they are typically found) that makes them need to regress more dramatically than opportunistic breeders would? I.e. it's not so much that opportunistic breeders are 'hanging on' to their reproductive capacity, but rather that seasonal breeders have to substantially pare back in order to survive. In seasonal breeders that have been studied the more dramatic reduction is seen regardless of environment life history (i.e. migratory vs. sedentary species). This can be seen by looking at the mix of songbird species in Table 1. Additionally, seasonal and opportunistic birds co-occur or experience environmental similar conditions. Therefore, it is not likely strictly a survival strategy, although regression of reproductive tissues is often linked to being an energetic savings strategy. line 101-103: the way this is written makes it sound like individuals will be followed through the reproductive cycle, which is slightly misleading. Could be reworded e.g. 'no study to date has quantified variation in reproductive tract morphology at different stages throughout the reproductive cycle in an opportunistically breeding bird.' We thank you for the suggestion in clarifying the intention of the study, it has been incorporated. line 111: the estradiol question feels a bit tagged on at the end of the introduction. If this is retained this as a focal part of the study (which it perhaps shouldn't be; see general comments), the introduction would benefit from a little bit more coverage of the role of estradiol earlier on e.g. when introducing about how tract growth and regression typically occur in seasonal breeders, the role of estradiol could be mentioned, and then as the manuscript goes on to introduce opportunistic breeders, it could highlight the fact that we don't really understand how estradiol works in this type of reproductive mode (which then sets up the question/hypothesis about estradiol and better integrates it into the overall biological background). Also, why just estradiol and not other important reproductive hormones such as FSH and LH? We agree that the last paragraph addition of estradiol had a tacked on feel. We have added a short paragraph in the introduction that explains other findings on estradiol and the need to look at it on a finer time scale. We picked estradiol because of its impact on both egg yolking and oviduct development, and variation (or lack of it) seen in previous studies (i.e. Perfito et al 2007 and Prior et al 2013) Methods line 121: 'thirty-sex' = 'thirty-six'? This typo has been corrected. line 121: 'force paired' meaning may not be clear to someone with no experience of bird breeding. Suggest replacing with 'were established in individual cages to prevent pairing or copulations with other birds' (or similar) We appreciate the suggestion, and we have changed the wording to indicate that pairs were housed individually. However, we have kept the ‘forced paired’ terminology as it is a common use term in bird breeding studies, but have clarified what it means in parentheses. line 121-122 'at least one clutch' – how much variation in prior breeding/laying experience was there between females? Might we expect oviduct size/flexibility to change with age and/or reproductive experience? I also wonder if there could be some sort of anticipatory effect here - if you have produced 3 clutches in a row are the perceived odds that you will be able to lay another higher? Could this influence retention of reproductive tissue? We agree that experience could impact retention of reproductive tissues, this is why we ensured that all birds had bred together at least once. 9 pairs had more than one breeding experience (~ 3 attempts, but not all resulted in the production of chicks as eggs were taken away from most pairs during incubation. These pairs were randomized across the six time points, and were given the same two week acclimation period (no nests or nesting material), which we feel would be sufficient to break any anticipatory effect. line 132 when is 'pre-breeding'? (precisely) This has now been defined. Pre-breeding birds were with out nest/nesting material for 4 weeks total when including the acclimation period. line 132 how is 'nesting' defined? (precisely) - is this nest-building? Also more generally, it would be helpful to use an easily differentiated word for either nesting or nestling to avoid confusion. This has now been defined to indicate it was during nest building, and that at least the bottom of the nest box was lined with building material. We have also changed nestling to “post-hatch” to reduce confusion. line 138: how often to females lay on the floor in this population (both non-breeders and those in pairs)? To produce an egg, females must have a functioning (i.e. developed) oviduct, and it seems this is quite common in captive populations of zebra finches even without the typical cues that induce breeding condition (i.e. pairing up with a male). Could this potential variation influence the interpretation of your results? In this study we did not have any birds lay on the floor of the aviary. However, some pairs were noted trying to build nests over the entry door where there was a small ledge. This was cleared daily to prevent egg laying during acclimation and during experiment. We have noted this lack of egg laying in these birds in the methods section. line 145-146: were the oviducts stripped of connective tissue and blotted first, before weighing? The oviduct was pulled free of connective tissue when removed so no excess was attached. If blood was evident it was lightly blotted off using a chemwipe. A note has been added about the blotting. Can you provide a bit more explanation about how follicle counts were done from photos? The ovary is three-dimensional so some follicles would be hidden in a twodimensional photo (evident from Figure 2)? Wouldn't it have been easier to preserve these and count directly? Yes we agree, in hindsight it would have been easier to preserve them for later counting. However, we instead photographed every ovary from two angles which was sufficient to allow us to visualize any yolking follicles. We have added this detail in the revised version. line 168: why mixed models? What was the random effect? Each female provides just one data point, right? Thank you for catching that, a bit of habit. Yes, it is just a linear model. There are no random effects as there was only one data point per bird. Results line 186-187: this first sentence is redundant, suggest omitting This statement is more of a discussion intro than results, and agree in the results it is redundant. line 193-194: isn't it obvious that follicle number and ovary mass will decline during this period? Not because of ovary 'regression', but simply because ova are being released? During and after laying follicles are releasing or have released their ova, respectively... not sure why these changes in the ovaries are particularly biologically interesting. The oviduct mass data seems more useful. Yes, we agree that ovary mass will reduce when the largest follicles are ovulated. The extent to which they are reduced is of value in the context of earlier studies of this and other species. line 200: do you have any idea what went wrong with the estradiol trials? Was it more likely a technical problem (if so, details of this might be important from a methodological perspective for other researchers) or could it be that the birds actually have very low estradiol levels? If the latter, could opportunistic breeders be fundamentally different to seasonal breeders in terms of their reproductive hormonal profiles? I.e. different proximate mechanisms for triggering oviduct growth and ovulation? Is anything known about this? We believe that the most likely explanation is that the levels of estradiol are very low, and at around the detection limit of the assay. In the earlier study in which we had used this assay (Crino et al 2018), the samples had been taken from birds that had been GnRH challenged. This stimulates a maximal release of reproductive hormones such as estradiol (receptor numbers can limit response). Given that our samples were looking at un-stimulated levels, it seems likely that the natural levels were just too low in many cases, and we have noted in the paper that other studies have had similar problems. Again, we feel that the data is worth reporting. Discussion line 211-212: over what timeframe do the changes in oviduct size occur in seasonal breeders previously studied? Does it take a much longer time? To me, this seems to be the interesting biological question - can opportunistic breeders do this far more quickly than seasonal breeders, and if so, how? We agree that it is interesting, but the small number of fine time scale studies songbirds (seasonal or opportunistic) makes conclusions hard. Starling’s oviducts do appear to start regression also appears to start with lay egg laid (regressing 42.5% of peak mass after clutch completion) (Vézina and Williams 2003). However, full regression is not tracked. In white crowned sparrows, the ovary weight and follicular size of brooding females (caring for nestlings) has only returned to pre-laying (just before lay) levels (Kern 1972). This is still about 6-7 times heavier (ovary) and 2.6x larger (Ovarian follicle) than winter measures. It is also clear that birds that do not lay eggs (in captivity) take longer to regress follicular development (Kern 1972, Hurley et al. 2008). line 217: it would be interesting to know if between-female variation depends on other maternal factors e.g. age/experience (see my similar earlier comment). We agree that age and experience – especially first breeding attempt and if previous attempt successfully produced fledglings. In this study we used birds that were within 6 months of age of one another to reduce age variation. Again, only 9 pairs had more than one breeding experience, and were spread across the 6 time points. With only 1-2 multi-experience pairs in each group, testing such effects is beyond the scope of this study. Importantly, we were aware of the possible potential confounding factor of the first breeding attempt, which is why we allowed each female to have one breeding experience before entering the study. line 246-248: this is a good point (and links to the above comment) – was there any variation like this within the study cohort e.g. previous breeding experience? E.g. as mentioned previously, the methods specifically state that birds were allowed to lay 'at least one' clutch (implying that some laid more). Is there any variation in this respect that could be informative? As above, we agree that this is an interesting question, but it is beyond the scope of this study to test impact of amount of previous breeding experience, given the relatively small number of individuals. line 254: how repeatable and reliable are these tests? Presumably not very, given the high failure rate. Are the detectable measures definitely reliable? The success of this assay appears to be variable based on plasma volume and handling technique, but is trustworthy. As mentioned the same process had a 38.3% non-detectable rate in GnRH challenged zebra finches, which should have higher levels of estradiol (Crino et al. 2018). As we have also indicated in the manuscript estradiol assays in songbirds have had mixed success rates, and have often been left unpublished without comment when poor. We feel that there is value in reporting the levels, but also highlighting the level of assay failure, for future work in this area. line 275: it would have been interesting to sample a random set of females before or very soon (i.e. one/two days) after pairing, to get an idea of what their baseline state is and therefore what the rate of oviduct regrowth is. I wonder if, under captive conditions, females are able to maintain their oviduct tissue more readily than a wild bird would be able to because living conditions are 'easy'? In this context, how representative are domesticated captive zebra finches likely to be of their wild counterparts? It may simply be easier to maintain oviduct tissue in captivity, so the effect we see here is actually a captivity effect, not an opportunistic breeder effect. Ideally, data from truly non-breeding females (to get real baseline data) and/or some comparison data from wild birds (even just non-breeding vs breeding time-points to get a rough idea of how comparable captive birds are to wild birds) would be added here to complete the puzzle. Currently, the existing data only really tell us is how the oviduct changes from after pairing (by which time changes may have already happened) through to chick-rearing, in a domesticated captive bird with (probably) limited costs associated with maintaining reproductive function outside of breeding. We agree that captivity does complicate the ability to reach baseline conditions, given that ad libitum food conditions represent good ecological conditions in the wild. As a result, it is very difficult to keep domesticated zebra finches in conditions under which they would not breed, and our ‘baseline’ birds are probably not physiologically equivalent to fully non reproductive state birds in the wild. We have now been clearer about this point in the introduction and discussion. line 277: definitions of what 'pre-breeding' and 'nesting' phases actually are need to be included in the methods, not just at the end of the discussion. These definitions have been clarified in the methods. line 278: change ‘destinction’ to ‘distinction’ Typo has been corrected. Fig 1C - this figure may be misleading. The data collected in this study don't allow us to infer reproductive tissue state outside of the breeding period (i.e. completely before and after the breeding cycle). This figure makes it look like the opportunistic breeder baseline is the same as it is in seasonal breeders outside the breeding season. However, it is possible that it never regresses to the same extent. Yes we agree that this is misleading. We have added a dashed line outside of the breeding periods to show that it is unclear how much the regress during the breeding season. We have also clarified this in the figure legend. Figure 3: figure legend could be clarified by changing ‘quantified variation in zebra finch female reproductive tract across and within…’ to ‘quantified variation in zebra finch reproductive tract tissue across and within…’ Thank you for the suggestion, it has been made. Table 1: while it's interesting to see these data and what is already known, it is not clear at what point in the reproductive cycle these traits were measured in other studies, which makes it difficult to draw comparisons with the current study. I also think this table probably isn't needed in the main text and should instead be in supplementary material. This table has been moved to supplemental and the sample times more clearly added to the table. Reviewer 2 (Anonymous) Basic reporting The manuscript is well written and easy to follow with appropriate figures. Data are shared. Overall, the literature is well referenced. However, I do have a couple of suggestions for improvement in this regard. In general, I think the characterization of our current understanding of opportunistic/flexible breeders is a bit of an oversimplification. For example, Ln 66 - I would disagree with the interpretation of the Hahn 1998 data as shown 'little annual variation'. Fig 2 shows females with an ovary score of 2 in late fall, which the Methods indicates reflects an absence of apparent follicles. Yes, we agree that there is more regression than we suggest. The wording had been clarified. The regression to score 2 means that there is some granulation to the ovary, but still is not considered entirely regressed (score 1). Related to the comment above, it isn't clear how data were selected for inclusion in this Table 1, as it does not appear to be comprehensive. For example, the Hahn data mentioned above are not included and it appears that only some species in the Wikelski et al. 2003 study are included. We can see that this seems like an omission. However, we only used those species reported in studies with actual measures of the oviduct mass or follicle volume to compare with the current study. Only those studies allowed proper calculation of the magnitude of change. The Hahn 1998 qualatativly scored ovary development, but did not measure follicle volume. We have now made this criteria clearer in the Table legend. Seasonal breeding is oversimplified in places as well. In particular, ln 48 - I suggest deleting 'much' from the statement, ln 52 - 'inflexible' is an overstatement as finetuning certainly occurs. We agree this wording is overly strong and have taken suggestion to reword these sentences. Minor comments Provide full references for studies in Table 1. I couldn't locate these. We have made certain that these references are now included in what is now supplemental Table 1 (Table S1). Experimental design Overall methods experimental design and methods are well defined and meaningful. However, further detail is needed in a few places. 1) More information is needed on how the 'pre-breeding' period was defined and the state of those birds. The authors note some difficulties with this category in the Discussion (and provide necessary caveats for interpreting the data), but it would be useful for readers to have more information about this categorization in the Methods. Is this defined purely on the fact that they did not have a nest-box and nesting materials? Was this period immediately following the 2 week acclimation? How long had it been since these birds had produced their last clutch? We have provided a clearer classification of pre-breeding and nesting have now been provided in methods section. Pre-breeding birds went 4 weeks total without nest-box or materials (which we now state). In terms of period since the pair’s last clutch: They were moved into the experiment after the last clutch produced. 2) It is stated that mixed models are used for statistical analysis, but it isn't clear what is the random term(s) in the models. Thank you for catching that, a bit of habit. Yes, it is just a linear model. There are no random effects as there was only one data point per bird. 3) No information is provided on priors used for Bayesian modeling. Were additional diagnostics performed for this modeling? The prior was estimated from the data by rstranarm model vs. being specified. All data was visualized explored and tested for over dispersion before modelling. Minor comments ln 144 - is 'deep anesthesia' really what is meant here given that birds are euthanized? Deep anaesthesia means that they are left in anaesthesia after they are no longer responsive and have stopped breathing. This means they are beyond the point of being able to recover. Validity of the findings Overall results and conclusions are well supported. But see comments below. 1) Ln 191 - the statement about a significant decrease between laying and incubation does not match statistical results presented in Table 2. Yes, you are correct. The wording has been corrected to state that it significantly decreased from high during nesting to incubation. 2) ln 286 - the conclusion that this reflects a lack of photo refractoriness is a bit of a leap. Perhaps this could be better supported with use of literature? This statement is made given the findings stated in the previous sentence that there was limited reproductive tract regression. However, we have now elaborated and added a citation. 3) ln 288 - reword to make clear this is a hypothesis (e.g., change 'can' to 'might') This change has been made. Minor comments Figure 4 legend use of the term 'bar' to describe both the black line showing mean and the boxes for counts is confusing. We agree this could be confusing. The symbol to denote mean has been changed to a black dot with standard error bars to match the new version of what was figure 3 (and is now figure 2), and the legend reworded. Figure 3. Is it possible to include letter labeling to indicate significant pairwise differences (from Table 2)? Yes, we agree this would improve clarity and have now done so. Comments for the Author Other minor suggestions ln 22 - 'seasonal' and 'environmental' cues are not necessarily alternatives. I suggest rewording. The word “primarily” has been added to shift the potential emphasis that these are alternatives. We aren’t suggesting they are alternatives per se, as it is well known that even strictly seasonal breeders used environmental cues to fine tune response. ln 48 - delete 'much' This has been deleted ln 221 - define what is meant by the resting phase. This definition has been elaborated on, so it is clear where in follicular development phases it exists. ln 285 - should 'nesting' be 'nestling'? Thank you for catching that. Yes, and nestling has been changed to post-hatch through out for clarity. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>As the world's economies come out of the lockdown imposed by the COVID-19 pandemic, there is an urgent need for technologies to mitigate COVID-19 transmission in confined spaces such as buildings. This feasibility study looks at one such technology, upper-room ultraviolet (UV) air disinfection, that can be safely used while humans are present in the room space, and which has already proven its efficacy as an intervention to inhibit the transmission of airborne diseases such as measles and tuberculosis. Using published data from various sources, it is shown that the SARS-CoV-2 virus, the causative agent of COVID-19, is highly likely to be susceptible to UV-C damage when suspended in air, with a UV susceptibility constant likely to be in the region 0.377 -0.590 m 2 /J, similar to that for other aerosolised coronaviruses. As such, the UV-C flux required to disinfect the virus is expected to be acceptable and safe for upper-room applications. Through analysis of expected and worst-case scenarios, the efficacy of the upper-room UV-C approach for reducing COVID-19 transmission in confined spaces (with moderate but sufficient ceiling height) is demonstrated. Furthermore, it is shown that with SARS-CoV-2, it should be possible to achieve high equivalent air change rates using upper-room UV air disinfection, suggesting that the technology might be particularly applicable to poorly ventilated spaces.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Since the emergence of COVID-19 in January 2020 there has been considerable interest in the use of ultraviolet (UV) light to disinfect blood plasma <ns0:ref type='bibr' target='#b15'>(Eickmann et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b28'>Keil et al. 2020b;</ns0:ref><ns0:ref type='bibr' target='#b46'>Ragan et al. 2020)</ns0:ref>, equipment <ns0:ref type='bibr' target='#b7'>(Card et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b13'>Derraik et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b21'>Hamzavi et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b22'>Heimbuch &amp; Harnish 2019)</ns0:ref> and air <ns0:ref type='bibr' target='#b37'>(Morawska et al. 2020)</ns0:ref>, in the hope that this might reduce transmission of the disease. In particular, upper-room ultraviolet germicidal irradiation (UVGI), a technology that disinfects room air, has been muted as a potential intervention that might prove effective against <ns0:ref type='bibr'>COVID-19 (Morawska et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b40'>Nardell &amp; Nathavitharana 2020;</ns0:ref><ns0:ref type='bibr' target='#b51'>Skorzewska 2020)</ns0:ref>. Upper-room UVGI utilizes UV-C light at wavelengths close to 254 nm to create an irradiation field above the heads of room occupants (Figure <ns0:ref type='figure'>1</ns0:ref>) that disinfects aerosolised bacteria and viruses suspended in the air <ns0:ref type='bibr' target='#b3'>(Beggs et al. 2006;</ns0:ref><ns0:ref type='bibr' target='#b4'>Beggs &amp; Sleigh 2002;</ns0:ref><ns0:ref type='bibr' target='#b45'>Noakes et al. 2015)</ns0:ref>. Because UV-C light is harmful to humans, such systems utilize louvres or shields that obscure the UV lamps from eyesight so that room occupants are kept safe. As such, upperroom UVGI is a well-established technology <ns0:ref type='bibr' target='#b17'>(First et al. 1999a;</ns0:ref><ns0:ref type='bibr' target='#b18'>First et al. 1999b</ns0:ref>) that has proven effective as a public health intervention to prevent the spread of airborne diseases such as measles <ns0:ref type='bibr' target='#b39'>(Nardell &amp; Nathavitharana 2019)</ns0:ref> and tuberculosis (TB) <ns0:ref type='bibr' target='#b16'>(Escombe et al. 2009;</ns0:ref><ns0:ref type='bibr' target='#b38'>Mphaphlele et al. 2015)</ns0:ref> in buildings.</ns0:p><ns0:p>Given that COVID-19 can be transmitted by the inhalation of aerosolised respiratory droplets containing the SARS-CoV-2 virus <ns0:ref type='bibr' target='#b2'>(Beggs 2020;</ns0:ref><ns0:ref type='bibr' target='#b36'>Miller et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b37'>Morawska et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b52'>Stadnytskyi et al. 2020)</ns0:ref>, and that several studies have recovered viral RNA from hospital air samples <ns0:ref type='bibr' target='#b10'>(Chia et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b20'>Guo et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b25'>Jiang et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b49'>Santarpia et al. 2020)</ns0:ref>, there is reason to believe that upper-room UVGI might be effective at 'killing' (inactivating) SARS-CoV-2 virions in the air, thus reducing the transmission of COVID-19 in buildings and other enclosed spaces. However, this presupposes that the technology is capable of delivering irradiation doses high enough to inactivate SARS-CoV-2 virions in respiratory droplets suspended in the air, something that has not yet been proven. Given this and the urgent need to develop interventions to break the chain of infection associated with COVID-19, we designed the short feasibility study reported here with the aim of evaluating whether or not upper-room UVGI might be an effective intervention against COVID-19.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Theory</ns0:head><ns0:p>At any point in time the amount of viral inactivation (disinfection) achieved for a given UV radiant flux (irradiance) can be described using the following first order decay equation <ns0:ref type='bibr' target='#b35'>(McDevitt et al. 2012)</ns0:ref>.</ns0:p><ns0:p>(1)</ns0:p><ns0:p>&#119873; &#119905; = &#119873; 0 &#215; &#119890; -&#119885;.&#119864;.&#119905;</ns0:p><ns0:p>Where: N 0 and N t are the number of viable viral particles (virions) at time zero and t seconds respectively; Z is the UV susceptibility constant for the virus (m 2 /J); E is the radiant (irradiation) flux (W/m 2 ); and t is time in seconds.</ns0:p><ns0:p>The UV irradiation dose received by the virus is simply:</ns0:p><ns0:p>(2)</ns0:p></ns0:div> <ns0:div><ns0:head>&#119867; = &#119864; &#215; &#119905;</ns0:head><ns0:p>Where: H is the observed UV irradiation dose (J/m 2 ).</ns0:p><ns0:p>By combining equations 1 and 2, and rearranging we can obtain a value for Z.</ns0:p><ns0:p>(</ns0:p><ns0:formula xml:id='formula_0'>) &#119885; =- 1 &#119867; &#215; &#119897;&#119899; ( &#119873; &#119905; &#119873; 0 ) =-1 &#119867; &#215; &#119897;&#119899; ( &#119891; )<ns0:label>3</ns0:label></ns0:formula><ns0:p>Where: f is the survival fraction.</ns0:p><ns0:p>Because the relationship between the UV dose and the natural logarithm of the survival fraction is broadly linear for most viral species, it means that the behaviour of any given virus exposed to UV-C light can be succinctly described by the value of Z, irrespective of the actual UV dose applied. As such, for any given viral species, if the value of Z is known, then it should be possible to predict with reasonable accuracy how the virus will behave when exposed to a given UV-C dose in any context. Microbes that exhibit larger Z values are more susceptible to UV damage, whereas those with small Z values are more difficult to inactivate.</ns0:p><ns0:p>UV inactivation plots for most viral species tend to be straight lines, although some might exhibit a curve <ns0:ref type='bibr' target='#b26'>(Kariwa et al. 2006)</ns0:ref>. Notwithstanding this, the model described in equation 1 is still a good approximation for most viral species <ns0:ref type='bibr' target='#b35'>(McDevitt et al. 2012</ns0:ref>) up until the point where the 'target' becomes saturated with UV photons. At this point, because all the virions have already been inactivated, increasing the UV dose further has no effect and so the linear relationship between UV dose and the log reduction become decoupled, with the result that the Z value no long applies.</ns0:p><ns0:p>Instead of quantifying UV inactivation in terms of survival fraction, many researchers, particularly those working in biology, describe the reduction in the microbial count in terms of log reduction, which can be converted to survival fraction as follows:</ns0:p><ns0:p>(4)</ns0:p><ns0:formula xml:id='formula_1'>&#119891; = 1 10 &#119860;</ns0:formula><ns0:p>Where: A is the log 10 reduction in the number of virions.</ns0:p><ns0:p>Specifically, with regard to upper-room UVGI, once the Z value has been obtained for the target microbe, it is then possible to determine the irradiation flux required to disinfect it, using the methodology described in Beggs and Sleigh <ns0:ref type='bibr' target='#b4'>(Beggs &amp; Sleigh 2002)</ns0:ref>. This method makes the assumption that the room air is well mixed, which is a reasonable approximation for most applications <ns0:ref type='bibr' target='#b4'>(Beggs &amp; Sleigh 2002)</ns0:ref>. If this is the case, then the average particle residence time, t res , (in seconds) in the room space will be:</ns0:p><ns0:p>(5)</ns0:p><ns0:formula xml:id='formula_2'>&#119905; &#119903;&#119890;&#119904; = 1 &#119899; &#215; 3600</ns0:formula><ns0:p>Where: n is the room ventilation rate in air changes per hour (AC/h).</ns0:p><ns0:p>From equation 5 it can be approximated that the average particle residence time in the upperroom UV field, t uv , (in seconds) will be: ( <ns0:ref type='formula'>6</ns0:ref>)</ns0:p><ns0:formula xml:id='formula_3'>&#119905; &#119906;&#119907; = &#119905; &#119903;&#119890;&#119904; &#215; &#8462; &#119906;&#119907; &#8462; &#119903;</ns0:formula><ns0:p>Where: h r is the floor-to-ceiling height (m), and h uv is the depth of the upper-room UV zone (m) (see Figure <ns0:ref type='figure'>1</ns0:ref>).</ns0:p><ns0:p>Because Z values are often determined experimentally using microbes suspended in liquids or on surfaces, it may be necessary to adjust the Z value for use with upper-room UVGI systems <ns0:ref type='bibr' target='#b3'>(Beggs et al. 2006;</ns0:ref><ns0:ref type='bibr' target='#b56'>Yang et al. 2017)</ns0:ref>, as follows:</ns0:p><ns0:p>(7)</ns0:p><ns0:formula xml:id='formula_4'>&#119885; &#119906;&#119903; = &#119885; &#215; &#119888; &#119906;&#119903;</ns0:formula><ns0:p>Where: Z ur is the effective upper-room Z value (m 2 /J), and c ur is a correction coefficient.</ns0:p><ns0:p>For practical purposes, Z ur can be assumed to be the same as the Z value achieved when a given microbe is irradiated in an aerosol.</ns0:p><ns0:p>So if we assume that the air in a room is well mixed, by combining equations 2, 3 and 6 it is possible to compute the average irradiation flux, E r , that is required to achieve a desired survival fraction, f r . ( <ns0:ref type='formula'>8</ns0:ref>)</ns0:p><ns0:formula xml:id='formula_5'>&#119864; &#119903; =- 1 (&#119885; &#119906;&#119903; &#215; &#119905; &#119906;&#119907; ) &#215; &#119897;&#119899;(&#119891; &#119903; )</ns0:formula><ns0:p>Alternatively, the disinfection achieved by an upper-room UVGI system can be thought of as being equivalent to additional air changes in the room space <ns0:ref type='bibr' target='#b34'>(McDevitt et al. 2008)</ns0:ref>. In this scenario, the UV rate constant, k uv , which can be thought of as the equivalent air change rate per second, can be determined using <ns0:ref type='bibr' target='#b3'>(Beggs et al. 2006</ns0:ref>): ( <ns0:ref type='formula'>9</ns0:ref>)</ns0:p><ns0:formula xml:id='formula_6'>&#119896; &#119906;&#119907; = &#119885; &#119906;&#119903; &#215; &#119864; &#215; &#8462; &#119906;&#119907; &#8462; &#119903;</ns0:formula><ns0:p>PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed So, in a ventilated room in which contamination ceases at time zero, we can utilize both the UV rate constant, k uv , and a rate constant, k v , for the ventilation (i.e. n &#61624; 3600), to produce a decay model for the room space.</ns0:p><ns0:p>&#119862; &#119905; = &#119862; 0 &#215; &#119890; -(&#119896; &#119907; + &#119896; &#119906;&#119907; + &#119896; &#119889; )&#119905; <ns0:ref type='bibr'>(10)</ns0:ref> Where; C 0 and C t are the concentrations of viable viral particles in the room space (virions/m 3 ) at time zero and t seconds respectively; k v is the ventilation rate constant; k d is the particulate deposition rate constant (e.g. 0.0014 s -1 <ns0:ref type='bibr' target='#b52'>(Stadnytskyi et al. 2020</ns0:ref>)); and t is time in seconds.</ns0:p></ns0:div> <ns0:div><ns0:head>Analysis of published data</ns0:head><ns0:p>A search of the relevant scientific literature (i.e. published literature, pre-prints and relevant websites) was undertaken to identify published data relating to the UV irradiation of the three closely related coronaviruses: SARS-CoV-2, the causative agent of COVID-19; SARS-CoV-1, the causative agent of severe acute respiratory syndrome (SARS); and MERS-CoV, the causative agent of middle east respiratory syndrome (MERS).</ns0:p><ns0:p>Because the experimental methods used in the various UV studies varied greatly, as did the level of detail reported, it was necessary to adopt a standardized approach so that valid comparisons could be made. It was therefore decided that, rather than estimating the Z value for a nominal log one reduction (i.e. D 90 ) as others have done <ns0:ref type='bibr' target='#b29'>(Kowalski 2010)</ns0:ref>, we would instead use the log reduction values and UV doses reported in the various studies to calculate the respective Z values using equation 3. In so doing, we were able to utilize the results from studies that would otherwise be excluded because the log reductions achieved were far in excess of one. Where researchers performed experiments using a range of UV doses, we calculated the Z value for two UV doses, one near the start of the inactivation process and the other just before the saturation point. So as to avoid bias due to pseudo-replication, when computing the average Z values for the respective viral species, we first aggregated the Z values reported for the various individual studies and then used the aggregated values to calculate the overall mean Z values for the respective viruses. <ns0:ref type='table' target='#tab_4'>PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head><ns0:p>In order to compare the Z values for the coronaviruses with those for influenza, we utilized experimental results produced by <ns0:ref type='bibr' target='#b22'>Heimbuch &amp; Harnish (Heimbuch &amp; Harnish 2019)</ns0:ref> who irradiated coupons of respirator material inoculated with SARS-CoV-1 and MERS-CoV, as well as four strains of influenza A, allowing direct comparisons to be made between the viral species.</ns0:p></ns0:div> <ns0:div><ns0:head>Estimating an effective upper-room Z value for aerosolised SARS-CoV-2</ns0:head><ns0:p>In order to evaluate how SARS-CoV-2 might behave in the presence of UV-C when aerosolised, we reviewed the available literature on the subject <ns0:ref type='bibr' target='#b24'>(Jensen 1964;</ns0:ref><ns0:ref type='bibr' target='#b29'>Kowalski 2010;</ns0:ref><ns0:ref type='bibr' target='#b30'>Kowalski et al. 2000;</ns0:ref><ns0:ref type='bibr' target='#b35'>McDevitt et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b53'>Walker &amp; Ko 2007)</ns0:ref> with the aim of estimating a value for the coefficient, c ur , in equation 7, which we then used to estimate the effective upper-room Z value, Z ur . In order to reflect the uncertainty associated with this, we compared effective Z values for aerosolised coronaviruses reported in the literature with values obtained for SARS-CoV-2 in liquids to obtain the range of possible values for c ur .</ns0:p></ns0:div> <ns0:div><ns0:head>Computation of required upper-room UV irradiation flux</ns0:head><ns0:p>Having estimated the value of Z ur for SARS-CoV-2 from the literature, we then used equations 6 and 8 to estimate the average upper-room irradiation flux that would be required to achieve a 50 -90% reduction in aerosolised SARS-CoV-2 virions (through the action of the UV-C alone) in a 4.2 &#61620; 4.2 &#61620; 2.5 m high room space for a range of ventilation rates. These dimensions were chosen because they are typical for an upper-room UVGI installation in which the lamp height is 2.1 m above the floor <ns0:ref type='bibr' target='#b18'>(First et al. 1999b</ns0:ref>). In the model we assumed that the air was completely mixed, which meant that according to equation 6, aerosol particles would spend on average 16% of their room residency time in the UV zone.</ns0:p><ns0:p>In addition to computing the required UV flux, we also wanted to know how a standard upperroom UV fitting might perform when challenged by SARS-CoV-2. In accordance with the guidelines stated by First <ns0:ref type='bibr' target='#b18'>(First et al. 1999b)</ns0:ref>, we assumed that the room contained a single 30 W (input) UV-C fitting capable of delivering an average upper-room flux of 50 &#956;W/cm 2 , and modelled its performance in terms of equivalent ventilation rate using equation 9. <ns0:ref type='table' target='#tab_4'>PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head></ns0:div> <ns0:div><ns0:head>Analysis of the published literature</ns0:head><ns0:p>The results of the literature search are summarized in Table <ns0:ref type='table'>1</ns0:ref>, which shows the UV-C (254 nm) doses applied and log reductions achieved in six studies investigating SARS-CoV-1 <ns0:ref type='bibr' target='#b11'>(Darnell et al. 2004;</ns0:ref><ns0:ref type='bibr' target='#b12'>Darnell &amp; Taylor 2006;</ns0:ref><ns0:ref type='bibr' target='#b14'>Duan et al. 2003;</ns0:ref><ns0:ref type='bibr' target='#b15'>Eickmann et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b22'>Heimbuch &amp; Harnish 2019;</ns0:ref><ns0:ref type='bibr' target='#b26'>Kariwa et al. 2006)</ns0:ref>, two studies investigating MERS-CoV <ns0:ref type='bibr' target='#b0'>(Bedell et al. 2016;</ns0:ref><ns0:ref type='bibr' target='#b22'>Heimbuch &amp; Harnish 2019)</ns0:ref>, and two studies investigating SARS-CoV-2 <ns0:ref type='bibr' target='#b5'>(Bianco et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b50'>Signify 2020)</ns0:ref>.</ns0:p><ns0:p>Table 1 also includes the results of one study that investigated the impact of deep-UV light at 280 nm (i.e. the boundary between UV-B and UV-C) on SARS-CoV-2 <ns0:ref type='bibr' target='#b23'>(Inagaki et al. 2020</ns0:ref>). In addition, three studies were found that used a combination of UV-A and UV-B light (270-360 nm), together with the photosensitiser, riboflavin, to disinfect SARS-CoV-2 <ns0:ref type='bibr' target='#b28'>(Keil et al. 2020b;</ns0:ref><ns0:ref type='bibr' target='#b46'>Ragan et al. 2020</ns0:ref>) and MERS-CoV <ns0:ref type='bibr' target='#b27'>(Keil et al. 2020a</ns0:ref>) in blood products (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Although these studies did not utilize UV-C light, it was nevertheless decided to report the results of these studies here so that direct comparisons could be made between SARS-CoV-2 and MERS-CoV.</ns0:p><ns0:p>The MERS-CoV irradiation study by <ns0:ref type='bibr' target='#b0'>Bedell et al. (Bedell et al. 2016</ns0:ref>) is included for completeness, even though the authors did not report the UV dose received by the virus, making it impossible to compute a Z value for this study.</ns0:p><ns0:p>The computed Z values for the respective experiments are shown in Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref> (UV-C and deep-UV) and Table <ns0:ref type='table'>4</ns0:ref> (UV-A/B plus riboflavin). From these it can be seen that the Z values for the MERS-CoV virus were similar in magnitude to those for both SARS-CoV-1 (UV-C) and SARS-CoV-2 (UV-A/B). With UV-C irradiation the mean Z value for SARS-CoV-1 was 0.00489 (SD = 0.00611) m 2 /J, whereas that for MERS-CoV was 0.00104 m 2 /J. Likewise, for UV-A/B plus riboflavin the corresponding Z values were 0.00020 (SD = 0.00009) m 2 /J and 0.00016 m 2 /J for SARS-CoV-2 and MERS-CoV respectively. However, by comparison SARS-CoV-2 appeared to be more susceptible to UV damage than either SARS-CoV-1 or MERS-CoV when irradiated with UV-C (mean Z = 0.14141 (SD = 0.09045) m 2 /J) and deep-UV light (mean Z = 0.03684 m 2 /J).</ns0:p></ns0:div> <ns0:div><ns0:head>The calculated Z values for influenza UV-C irradiation experiments undertaken by Heimbuch &amp;</ns0:head><ns0:p>Harnish <ns0:ref type='bibr' target='#b22'>(Heimbuch &amp; Harnish 2019</ns0:ref>) are presented in Table <ns0:ref type='table'>5</ns0:ref>. These experiments, which were carried out using inoculated coupons of respirator material, revealed that in this context the Z values for the various influenza A strains were of the same order of magnitude as those for SARS-CoV-1 and MERS-CoV. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Effective upper-room Z values for aerosolised SARS-CoV-2</ns0:head><ns0:p>A review of the literature revealed that relatively few experimental studies have been performed involving the UV irradiation of aerosolised viruses, with only three undertaken on a coronavirus <ns0:ref type='bibr' target='#b6'>(Buonanno et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b53'>Walker &amp; Ko 2007)</ns0:ref>. A summary of the findings of several key studies are presented in Table <ns0:ref type='table'>6</ns0:ref>, which reveals that most viral species appear to be relatively easy to disinfect when suspended in droplets in the air. In particular, aerosolised viruses appear to be more vulnerable to UV damage than when they are suspended in a liquid or on a substrate. For example, for the 24 irradiation experiments involving adenoviruses suspended in liquid, reported by Kowalski <ns0:ref type='bibr' target='#b29'>(Kowalski 2010)</ns0:ref>, the average Z value was 0.00586 m 2 /J, which is an order of magnitude less than the values of 0.0546 and 0.0390 m 2 /J for aerosolised adenoviruses, attributed to Jensen <ns0:ref type='bibr' target='#b24'>(Jensen 1964</ns0:ref>) and Walker and Ko <ns0:ref type='bibr' target='#b53'>(Walker &amp; Ko 2007)</ns0:ref> respectively.</ns0:p><ns0:p>Regarding coronaviruses, Walker and Ko <ns0:ref type='bibr' target='#b53'>(Walker &amp; Ko 2007</ns0:ref>) also performed experiments on aerosolised murine (mouse) hepatitis virus (MHV) coronavirus in a single pass test rig. This revealed a Z value of 0.377 &#61617; 0.119 m 2 /J for this virus. Buonanno et al. <ns0:ref type='bibr' target='#b6'>(Buonanno et al. 2020)</ns0:ref> also performed irradiation experiments on aerosolised coronaviruses, but using UV light at 222 nm (far-UV) rather than 254 nm. They found the Z values for human coronavirus 229E and human coronavirus OC43 to be 0.410 m 2 /J and 0.590 m 2 /J respectively. Collectively, these Z values are an order of magnitude greater than the values obtained for SARS-CoV-2 in liquid, implying that when aerosolised, coronaviruses in general and SARS-CoV-2 in particular, are much easier to disinfect compared with when they are presented in liquids or on surfaces.</ns0:p><ns0:p>Although we are comparing different species of coronavirus here, evidence from Bedell et al. <ns0:ref type='bibr' target='#b0'>(Bedell et al. 2016)</ns0:ref>, who irradiated MHV coronavirus and MERS-CoV in Petri dishes, suggests that it is nonetheless valid. They found that 5 minutes exposed to a UV-C light source resulted in a 2.71 log reduction for the MHV coronavirus, whereas the same exposure resulted in a 5.91 log reduction for MERS-CoV. This suggests that MHV coronavirus is actually more resistant to UV damage than MERS-CoV, and as such, supports Walker and Ko's <ns0:ref type='bibr' target='#b53'>(Walker &amp; Ko 2007)</ns0:ref> conclusion that coronaviruses are much easier to inactivate in the air compared with on surfaces and in liquids. Manuscript to be reviewed appear that irradiating the coronavirus in liquid requires a UV-C dose that is in the region 1.8 -6.0 times higher than that required when the virus is suspended in air. From this we estimated that the value of the adjustment coefficient c ur would be in a range 0.167 -0.545.</ns0:p></ns0:div> <ns0:div><ns0:head>Upper-room UVGI computation results</ns0:head><ns0:p>Because no UV irradiation experiments have to date been performed on aerosols containing the SARS-CoV-2 virus, it was necessary when undertaking the feasibility study to make assumptions regarding an appropriate value of Z ur to use in the upper-room UVGI analysis. With respect to this, because the published mean Z values for the aerosolised coronaviruses were all in the region 0.377 -0.590 m 2 /J, we felt that an assumed Z value in this range would be indicative of how airborne SARS-CoV-2 might behave in a UV-C field. A decision was therefore made to use Walker and Ko's Z value figure of 0.377 m 2 /J to evaluate the expected performance of the upper-room UVGI installation, because this was considered a conservative value. In addition, because of the uncertainty associated with this assumed value, we introduced a 'factor of safety' into our analysis by also modelling a worst-case scenario in which Z ur was 0.0377 m 2 /J. Table <ns0:ref type='table'>7</ns0:ref> presents the results of the room analysis using these two values for Z ur , for a range of ventilation rates. From this it can be seen that there is a direct inverse relationship between particle residence time in the UV field, t uv , and the required irradiation flux, E r , as predicted by equation 8. This means that for any given Z value, the value of E r will double as the room ventilation rate doubles. The table also reveals that there is a direct inverse relationship between Z ur and E r . From the calculated values in this table it can be seen that if Z ur , = 0.377 m 2 /J, then with an average UV flux of just 10 &#956;W/cm 2 it should be possible to achieve &gt;90% inactivation of SARS-CoV-2, even at a ventilation rate of 8 AC/h. However, if in reality, Z ur , is 0.0377 m 2 /J, then all the calculated fluxes would have to increase by a factor of ten to achieve the same results. Given that accepted guidelines <ns0:ref type='bibr' target='#b18'>(First et al. 1999b</ns0:ref>) recommend for a room 2.5 m high, one 30 W (input) UV lamp per 18.58 m 2 of floor area, which will produce an average flux in the region 50 &#956;W/cm 2 , this means that even under this worst-case scenario it should still be possible to achieve disinfection rates &gt;90% for all but the highest ventilation rates.</ns0:p><ns0:p>When we fixed the UV flux at an average of 50 &#956;W/cm 2 , we found that for Z ur , = 0.377 m 2 /J the upper-room UVGI installation produced an equivalent air change rate of 108.6 AC/h, whereas if Manuscript to be reviewed Z ur , = 0.0377 m 2 /J this fell to 10.9 AC/h. These values were constant and unaffected by the actual room ventilation rate.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Analysis of the literature relating to the UV irradiation of coronaviruses clearly reveals that SARS-CoV-2, when in a liquid assay, is relatively easily inactivated by UV light at both 254 nm <ns0:ref type='bibr' target='#b5'>(Bianco et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b50'>Signify 2020</ns0:ref>) and 280 nm <ns0:ref type='bibr' target='#b23'>(Inagaki et al. 2020)</ns0:ref>. Indeed, the results in Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref> suggest that the virus is likely to be more susceptible to UV-C damage than either SARS-CoV-1 or MERS-CoV. Furthermore, the results of the experiments were SARS-CoV-2 was exposed to UV-A/B and riboflavin, suggest that the virus is susceptible to damage, albeit to a lesser extent, caused by UV light at other wavelengths. As such, this appears to support the finding of Sagripanti and Lytle (Sagripanti &amp; Lytle 2020) that SARS-CoV-2 is vulnerable to sunlight.</ns0:p><ns0:p>One problem frequently encountered when comparing UV irradiation results from disparate researchers is that experimenters often utilize different methodologies to evaluate log reductions in microbial species, with varying doses of UV administered. In particular, the type of substrate or media used can greatly influence the outcome of the experiment. This is because the substrate or media can absorb the UV photons and shield the virus. Given this, it is important to compare like with like, if this is possible. For this reason we included the results of Heimbuch and Harnish <ns0:ref type='bibr' target='#b22'>(Heimbuch &amp; Harnish 2019)</ns0:ref> in Tables <ns0:ref type='table' target='#tab_4'>3 and 5</ns0:ref>, because they performed the same irradiation experiment on SARS-CoV-1 and MERS-CoV, as well as on four strains of influenza A, thus allowing direct comparisons to be made. From Tables <ns0:ref type='table' target='#tab_4'>3 and 5</ns0:ref> it can be seen that the Z values for the influenza strains are of a similar order of magnitude as those for the coronaviruses, implying that in this context SARS-CoV-1 and MERS-CoV were about as difficult to inactivate as influenza A. This is a surprising finding, because others have suggested that the UV dose required to inactivate SARS-CoV-2 might be lower than that required to disinfect influenza A <ns0:ref type='bibr' target='#b48'>(Sagripanti &amp; Lytle 2020)</ns0:ref>. This is because coronaviruses have genomes that are approximately twice as long as that of influenza A, making them in theory much more vulnerable to damage from UV-C <ns0:ref type='bibr' target='#b48'>(Sagripanti &amp; Lytle 2020)</ns0:ref>. Indeed, in a summary collated from hundreds of published studies by Kowalski <ns0:ref type='bibr' target='#b29'>(Kowalski 2010)</ns0:ref>, the Z values for influenza A in water were reported as being in the range 0.04800 -0.13810 m 2 /J, much higher than the values achieved by <ns0:ref type='bibr' target='#b22'>Heimbuch and Harnish (Heimbuch &amp; Harnish 2019)</ns0:ref>. As such, this suggests that the substrate or medium in which microbes are irradiated plays an important role in influencing the magnitude of the Z value achieved. Indeed, it is well known in other contexts that UV-C light can be attenuated as it passes through liquids <ns0:ref type='bibr' target='#b32'>(Mamane 2008)</ns0:ref>. When UV light passes through a suspension of particles in water, its intensity is reduced due to both scattering and absorption of the light <ns0:ref type='bibr' target='#b19'>(Gregory 2005)</ns0:ref>. Absorption occurs because the light beam interacts with atoms and molecules in the liquid to raise their energy level, with the result that energy is lost from the beam, whereas scattering occurs when particulates in the fluid interfere with the UV light making it more diffuse <ns0:ref type='bibr' target='#b32'>(Mamane 2008)</ns0:ref>. Particulates can also shield microbes from UV light. This means that UV inactivation of microbial suspensions in liquid films &gt;1.2 mm can be greatly inhibited, due to the low penetration depth of UV light through concentrated suspensions <ns0:ref type='bibr' target='#b9'>(Cheng et al. 2020)</ns0:ref>. Consequently, when interpreting the Z values for SARS-CoV-1, SARS-CoV-2 and MERS-CoV in Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>, it is important to view them as being strictly contextual.</ns0:p><ns0:p>With regard to UV irradiation of aerosolised viruses, very few published experimental studies exist, with only three specifically relating to coronaviruses <ns0:ref type='bibr' target='#b6'>(Buonanno et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b53'>Walker &amp; Ko 2007)</ns0:ref>. As a result there is a paucity of good quality data relating to UV-C irradiation of SARS-CoV-1, SARS-CoV-2 and MERS-CoV in the air. Consequently, we had to establish whether or not Walker and Ko's <ns0:ref type='bibr' target='#b53'>(Walker &amp; Ko 2007)</ns0:ref> published Z value of 0.377 m 2 /J was valid for SARS-CoV-2 in air. Comparison with the Z values presented in Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref> reveals that this value is considerably greater in magnitude than those achieved for the coronaviruses when they were irradiated in liquid or on equipment substrates. This however, is to be expected given that liquids attenuate UV penetration <ns0:ref type='bibr' target='#b32'>(Mamane 2008)</ns0:ref>. Also the finding appears to be broadly in keeping with the behaviour of adenoviruses when irradiated in air and in liquid. Furthermore, because Bedell et al. <ns0:ref type='bibr' target='#b0'>(Bedell et al. 2016)</ns0:ref> found MERS-CoV to be more susceptible to UV-C damage than MHV coronavirus, this strongly supports the use of Walker and Ko's <ns0:ref type='bibr' target='#b53'>(Walker &amp; Ko 2007</ns0:ref>) Z value for MHV coronavirus as a valid surrogate for SARS-CoV-2 in air. Having said this, because the UV susceptibility of the target microbe is crucial to the performance of any upperroom UVGI installation, our use of Walker and Ko's Z value for the MHV coronavirus to represent SARS-CoV-2 should be treated with caution. For this reason, when we assessed the performance of the upper-room UVGI in our hypothetical room, we used both 0.377 and 0.0377 m 2 /J in our simulations. In so doing, we effectively modelled both the expected and worst-case scenarios.</ns0:p><ns0:p>The results for the expected and worst-case scenarios in Table <ns0:ref type='table'>7</ns0:ref>, strongly suggest that upperroom UVGI, if applied correctly, should be effective at disinfecting SARS-CoV-2 virions suspended in respiratory droplets in the air. This finding is of course very much dependent on the surrogate Z ur value being truly representative for SARS-CoV-2. With respect to this, one limitation of our study is that we did not distinguish between the Z values achieved using a single-pass test rig, such as that used by Walker and Ko <ns0:ref type='bibr' target='#b53'>(Walker &amp; Ko 2007)</ns0:ref>, and those achieved in real-life by an upper-room UVGI system. With the latter, because the irradiation process is fragmented, compared with a single-pass system, it is thought that higher UV doses might be required to achieve equivalent levels of inactivation <ns0:ref type='bibr' target='#b3'>(Beggs et al. 2006;</ns0:ref><ns0:ref type='bibr' target='#b56'>Yang et al. 2017)</ns0:ref>. However, while this specifically applies to aerosolised bacteria that can rapidly repair UV damage when the irradiation process becomes fragmented <ns0:ref type='bibr' target='#b1'>(Beggs 2002)</ns0:ref>, it is not known to what extent this applies to viruses, which are not metabolically active, although it is known that through photoreactivation viruses can repair UV damage <ns0:ref type='bibr' target='#b54'>(Weinbauer et al. 1997)</ns0:ref>.</ns0:p><ns0:p>Notwithstanding this, because the Z values achieved for coronaviruses irradiated in air <ns0:ref type='bibr' target='#b6'>(Buonanno et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b53'>Walker &amp; Ko 2007)</ns0:ref> are very similar in magnitude to those exhibited by Mycobacterium tuberculosis (the causative agent of TB) in air (i.e. 0.33 -0.48 m 2 /J <ns0:ref type='bibr' target='#b47'>(Riley et al. 1976</ns0:ref>)), there is good reason to believe that upper-room UVGI might be effective at mitigating the spread of COVID-19 indoors.</ns0:p><ns0:p>Upper-room UVGI air disinfection is highly dependent on good air mixing occurring between the upper and lower portions of the room space <ns0:ref type='bibr' target='#b4'>(Beggs &amp; Sleigh 2002;</ns0:ref><ns0:ref type='bibr' target='#b41'>Nicas &amp; Miller 1999;</ns0:ref><ns0:ref type='bibr' target='#b43'>Noakes et al. 2004;</ns0:ref><ns0:ref type='bibr' target='#b57'>Zhu et al. 2013</ns0:ref>). In the study presented here we assumed that complete mixing occurred, which although a reasonable approximation in many instances, is not always the case because short circuiting can occur <ns0:ref type='bibr' target='#b4'>(Beggs &amp; Sleigh 2002)</ns0:ref>. If the room air mixing factor is low, say for example due stratification in a poorly ventilated space, then this can greatly impair the disinfection performance of an upper-room UVGI system <ns0:ref type='bibr' target='#b4'>(Beggs &amp; Sleigh 2002;</ns0:ref><ns0:ref type='bibr' target='#b43'>Noakes et al. 2004)</ns0:ref>. It is therefore important when designing such systems to carefully consider the air movement in the room space, in order to eliminate stagnant regions and maximize air movement through the UV field. In the context of COVID-19, this is particularly important because, unlike TB which is spread via the inhalation of droplet nuclei &lt;5 &#956;m in diameter, it is thought that COVID-19 can be transmitted through the exhalation of larger respiratory droplets &lt;100 &#956;m, which rapidly reduce in size due to evaporation <ns0:ref type='bibr' target='#b2'>(Beggs 2020;</ns0:ref><ns0:ref type='bibr' target='#b31'>Liu et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b55'>Xie et al. 2007</ns0:ref>) to become aerosols, say, &lt;50 &#956;m in diameter <ns0:ref type='bibr' target='#b42'>(Nicas et al. 2005)</ns0:ref>. These larger aerosol particles have settling velocities &lt;0.1 m/s and as such can readily be transported on convective room air currents, with the result that they can remain suspended in room air for many minutes.</ns0:p><ns0:p>However, if the velocities of the convection currents drop, then some of the larger aerosol particles may decouple from the air stream and settle out due to gravitational deposition, Manuscript to be reviewed potentially passing through the breathing zone where they can be inhaled by the room occupants. This is particularly the case if the air is poorly mixed and stagnant regions exist within the room space. Under such circumstances larger aerosol particles might be inhaled without being fully irradiated by the upper-room UV field, undermining the effectiveness of the whole UVGI installation. Consequently, if upper-room UVGI is to be effective against COVID-19, it is important to both promote good room air mixing and also ensure that larger aerosol particles (e.g.. &lt;50 &#956;m in diameter) receive the required UV irradiation dose. As such, this may require upper-room UVGI systems to be supplemented with ceiling mounted fans <ns0:ref type='bibr' target='#b57'>(Zhu et al. 2013)</ns0:ref> or other devices to promote the necessary air movement to ensure that larger aerosol particles are adequately irradiated.</ns0:p><ns0:p>One major advantage of upper-room UVGI is that it can be retrospectively fitted into buildings provided that the floor to ceiling height is large enough to ensure that the UV field does not impinge on room occupants <ns0:ref type='bibr' target='#b18'>(First et al. 1999b)</ns0:ref>. By installing such a system it is possible to effectively 'turbo-charge' the efficacy of the ventilation system. Indeed, in keeping with the findings of <ns0:ref type='bibr' target='#b34'>McDevitt et al. (McDevitt et al. 2008)</ns0:ref>, our analysis suggests that it is possible to achieve &gt;100 equivalent AC/h by installing upper-room UVGI. Using equation 9, we can calculate the UV rate constant, k uv , which can be thought of as the equivalent air change rate per second. Once known, this in turn can be used, together with the ventilation and particulate deposition rate constants, k v , and k d , in equation 10, to compute the concentration of viral partials in the room space at any point in time.</ns0:p><ns0:p>While our analysis has been able to show that upper-room UVGI has the potential to disinfect the SARS-CoV-2 virus when suspended in room air, we are nonetheless conscious of the limitations of the feasibility study. Chief among these is the fact that we had to assume the value of the upper-room UV susceptibility constant, Z ur , for SARS-CoV-2. Although the true value of this constant is likely to be similar to that exhibited by other aerosolised coronaviruses, we cannot know its exact magnitude without further experimental work. Consequently, the results of the study should be considered as indicative only. Also, in the study it was assumed that the room air is well mixed, which, as discussed above, may not necessarily be the case in some applications. In particular, because the model used was relatively simple, we were not able to assess how upper-room UVGI might perform in situations where aerosol particles decouple from the air stream due to gravitational deposition, or remain suspended in the breath zone. It is therefore recommended that future studies investigating the use of upper-room UVGI to prevent 3 * Estimated from plots and data presented in source material.</ns0:p><ns0:p>4 Legend: nr -not reported in source material.</ns0:p></ns0:div> <ns0:div><ns0:head>5</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed UV-A/B doses applied and log reductions achieved in the various studies relating to the disinfection of SARS-CoV-2 and MERS-CoV in blood products when riboflavin is used.</ns0:p><ns0:p>nr -not reported in source material 1 Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>. UV-A/B doses applied and log reductions achieved in the various studies relating to the 2 disinfection of SARS-CoV-2 and MERS-CoV in blood products when riboflavin is used. 3 Legend: nr -not reported in source material. Manuscript to be reviewed Calculated Z values for the UV-C irradiation experiments.</ns0:p><ns0:p>* Estimated from plots and data presented in source material. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>Comparing the computed Z values for UV-C irradiation experiments on the MHV coronavirus conducted in air (0.37700 m 2 /J (Walker &amp; Ko 2007)) with those for the SARS-CoV-2 virus in liquid ranging from 0.06280 m 2 /J (Signify 2020) to 0.20536 m 2 /J (Kariwa et al. 2006), it would PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>4</ns0:head><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='36,42.52,178.87,525.00,325.50' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>1</ns0:head><ns0:label /><ns0:figDesc>Table1. UV-C and deep-UV doses applied and log reductions achieved in various studies 2 relating to the SARS-CoV-1, MERS-CoV and SARS-CoV-2 viruses.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Virus</ns0:cell><ns0:cell>UV wave</ns0:cell><ns0:cell>Medium &amp;</ns0:cell><ns0:cell>Irradianc</ns0:cell><ns0:cell>Duratio</ns0:cell><ns0:cell>UV Dose</ns0:cell><ns0:cell>Inactivation</ns0:cell><ns0:cell>Reference</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>length</ns0:cell><ns0:cell>context</ns0:cell><ns0:cell>e</ns0:cell><ns0:cell>n</ns0:cell><ns0:cell>(mJ/cm 2 )</ns0:cell><ns0:cell>(log</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>(nm)</ns0:cell><ns0:cell /><ns0:cell>(&#956;W/cm 2</ns0:cell><ns0:cell>(min &amp;</ns0:cell><ns0:cell /><ns0:cell>reduction)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>)</ns0:cell><ns0:cell>sec)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell cols='2'>UV-C (nr) Liquid in well</ns0:cell><ns0:cell>&gt;90</ns0:cell><ns0:cell cols='2'>15 min &gt;81</ns0:cell><ns0:cell>&gt; log 0.602</ns0:cell><ns0:cell>Duan et al. [36]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>plate</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>254</ns0:cell><ns0:cell>Liquid in well</ns0:cell><ns0:cell>4016</ns0:cell><ns0:cell>1 min</ns0:cell><ns0:cell>241</ns0:cell><ns0:cell>log 1.4*</ns0:cell><ns0:cell>Darnell et al. [34]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>plate</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>254</ns0:cell><ns0:cell>Liquid in well</ns0:cell><ns0:cell>4016</ns0:cell><ns0:cell>6 min</ns0:cell><ns0:cell>1446</ns0:cell><ns0:cell>log 4.5*</ns0:cell><ns0:cell>Darnell et al. [34]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>plate</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>254</ns0:cell><ns0:cell>Liguid in well</ns0:cell><ns0:cell>4016</ns0:cell><ns0:cell cols='2'>20 min 4819</ns0:cell><ns0:cell>log 4.1*</ns0:cell><ns0:cell>Darnell &amp; Taylor</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>plate</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>[35]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell cols='2'>UV-C (nr) Liquid in well</ns0:cell><ns0:cell>134</ns0:cell><ns0:cell>5 min</ns0:cell><ns0:cell>40</ns0:cell><ns0:cell>log 3.2*</ns0:cell><ns0:cell>Kariwa et al. [27]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>plate</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell cols='2'>UV-C (nr) Liquid in well</ns0:cell><ns0:cell>134</ns0:cell><ns0:cell cols='2'>15 min 121</ns0:cell><ns0:cell>log 5.325</ns0:cell><ns0:cell>Kariwa et al. [27]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>plate</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>254</ns0:cell><ns0:cell>Respirator</ns0:cell><ns0:cell>2300</ns0:cell><ns0:cell>7.25</ns0:cell><ns0:cell>1000</ns0:cell><ns0:cell>&#61619;log 4.81</ns0:cell><ns0:cell>Heimbuch &amp;</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>surface</ns0:cell><ns0:cell /><ns0:cell>min</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Harnish [4]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>254</ns0:cell><ns0:cell>Platelet</ns0:cell><ns0:cell>nr</ns0:cell><ns0:cell>nr</ns0:cell><ns0:cell>50</ns0:cell><ns0:cell>log 3.05</ns0:cell><ns0:cell>Eickmann et al. [3]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>concentrates</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>254</ns0:cell><ns0:cell>Platelet</ns0:cell><ns0:cell>nr</ns0:cell><ns0:cell>nr</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>&#61619;log 3.5</ns0:cell><ns0:cell>Eickmann et al. [3]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>concentrates</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>MERS-CoV</ns0:cell><ns0:cell>254</ns0:cell><ns0:cell>Respirator</ns0:cell><ns0:cell>2300</ns0:cell><ns0:cell>7.25</ns0:cell><ns0:cell>1000</ns0:cell><ns0:cell>&#61619;log 4.5</ns0:cell><ns0:cell>Heimbuch &amp;</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>surface</ns0:cell><ns0:cell /><ns0:cell>min</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Harnish [4]</ns0:cell></ns0:row><ns0:row><ns0:cell>MERS-CoV</ns0:cell><ns0:cell cols='2'>UV-C (nr) Droplet on glass</ns0:cell><ns0:cell>nr</ns0:cell><ns0:cell>5 min</ns0:cell><ns0:cell>nr</ns0:cell><ns0:cell>&#61619;log 5.91</ns0:cell><ns0:cell>Bedell et al. [37]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>slip</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell>254</ns0:cell><ns0:cell>Liguid in well</ns0:cell><ns0:cell>1082</ns0:cell><ns0:cell>nr</ns0:cell><ns0:cell>3.7</ns0:cell><ns0:cell>log 3.3</ns0:cell><ns0:cell>Bianco et al. [38]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>plate</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell cols='2'>UV-C (nr) Inoculated</ns0:cell><ns0:cell>nr</ns0:cell><ns0:cell>6 sec</ns0:cell><ns0:cell>5.0</ns0:cell><ns0:cell>log 2.0</ns0:cell><ns0:cell>Signify [39]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>material</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell cols='2'>UV-C (nr) Inoculated</ns0:cell><ns0:cell>nr</ns0:cell><ns0:cell>25 sec</ns0:cell><ns0:cell>22.0</ns0:cell><ns0:cell>log 6.0</ns0:cell><ns0:cell>Signify [39]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>material</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell>280</ns0:cell><ns0:cell>Liquid in petri</ns0:cell><ns0:cell>3750</ns0:cell><ns0:cell>1 sec</ns0:cell><ns0:cell>3.75</ns0:cell><ns0:cell>log 0.9</ns0:cell><ns0:cell>Inagaki et al. [40]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>dish</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell>280</ns0:cell><ns0:cell>Liquid in petri</ns0:cell><ns0:cell>3750</ns0:cell><ns0:cell>10 sec</ns0:cell><ns0:cell>37.5</ns0:cell><ns0:cell>log 3.0</ns0:cell><ns0:cell>Inagaki et al. [40]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>dish</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Calculated Z values for the UV-C and deep-UV irradiation experiments.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Virus</ns0:cell><ns0:cell>UV Dose</ns0:cell><ns0:cell>Inactivation</ns0:cell><ns0:cell>UV</ns0:cell><ns0:cell>Reference</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>(mJ/cm 2 )</ns0:cell><ns0:cell>(log reduction)</ns0:cell><ns0:cell>susceptibility</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>constant , Z</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>(m 2 /J)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>&gt;81</ns0:cell><ns0:cell>&gt; log 0.602</ns0:cell><ns0:cell>0.00171</ns0:cell><ns0:cell>Duan et al. [36]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>241</ns0:cell><ns0:cell>log 1.4*</ns0:cell><ns0:cell>0.00134*</ns0:cell><ns0:cell>Darnell et al. [34]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>1446</ns0:cell><ns0:cell>log 4.5*</ns0:cell><ns0:cell>0.00072*</ns0:cell><ns0:cell>Darnell et al. [34]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>4819</ns0:cell><ns0:cell>log 4.1*</ns0:cell><ns0:cell>0.00020*</ns0:cell><ns0:cell>Darnell &amp; Taylor [35]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>40</ns0:cell><ns0:cell>log 3.2*</ns0:cell><ns0:cell>0.01833*</ns0:cell><ns0:cell>Kariwa et al. [27]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>121</ns0:cell><ns0:cell>log 5.325</ns0:cell><ns0:cell>0.01017</ns0:cell><ns0:cell>Kariwa et al. [27]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>1000</ns0:cell><ns0:cell>&#61619;log 4.81</ns0:cell><ns0:cell>0.00111</ns0:cell><ns0:cell>Heimbuch &amp; Harnish</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>[4]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>50</ns0:cell><ns0:cell>log 3.05</ns0:cell><ns0:cell>0.01405</ns0:cell><ns0:cell>Eickmann et al. [3]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-1</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>&#61619;log 3.5</ns0:cell><ns0:cell>0.00806</ns0:cell><ns0:cell>Eickmann et al. [3]</ns0:cell></ns0:row><ns0:row><ns0:cell>MERS-CoV</ns0:cell><ns0:cell>1000</ns0:cell><ns0:cell>&#61619;log 4.5</ns0:cell><ns0:cell>0.00104</ns0:cell><ns0:cell>Heimbuch &amp; Harnish</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>[4]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell>3.7</ns0:cell><ns0:cell>log 3.3</ns0:cell><ns0:cell>0.20536</ns0:cell><ns0:cell>Bianco et al. [38]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>log 2.0</ns0:cell><ns0:cell>0.09210</ns0:cell><ns0:cell>Signify [39]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>log 6.0</ns0:cell><ns0:cell>0.06280</ns0:cell><ns0:cell>Signify [39]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell>3.75**</ns0:cell><ns0:cell>log 0.9</ns0:cell><ns0:cell>0.05526</ns0:cell><ns0:cell>Inagaki et al. [40]</ns0:cell></ns0:row><ns0:row><ns0:cell>SARS-CoV-2</ns0:cell><ns0:cell>37.5**</ns0:cell><ns0:cell>log 3.0</ns0:cell><ns0:cell>0.01842</ns0:cell><ns0:cell>Inagaki et al. [40]</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>* Estimated from plots and data presented in source material.</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='2'>** Using deep-UV light at 222 nm.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot' n='4'>PeerJ reviewing PDF | (2020:07:51003:1:1:NEW 4 Sep 2020)</ns0:note> </ns0:body> "

" Reply to reviewers’ comments Upper-room ultraviolet air disinfection might help to reduce COVID-19 transmission in buildings: a feasibility study Clive B. Beggs and Eldad J. Avital We thank all three reviewers for the effort and comments that have improved the manuscript. We listed below our response and action (highlighted in red colour) to each of the comments. The modifications in the manuscript are also highlighted in red text colour. Reviewer 1 (Anonymous) Basic reporting The authors performed a literature review and summarized the reported inactivation “Z’ values of UVC light from different published experiments based on different pathogens in air and surface samples. The language is clear and the paper is well-written in English Experimental design Nevertheless, for the pathogen that causes COVID-19, tables 2 and 4 only provide data on UVA or UVB light in a Blood plasma sample from other published studies. The authors did not report the inactivation” z” values of airborne SARS-CoV-2 when exposed to UV-C light. Original or new experimental findings are expected. Reply: While we acknowledge the reviewer’s concerns about the lack of any new experimental findings, we have to respectfully point out that the article is a feasibility study (i.e. new and original analysis of existing published data) designed to evaluate whether or not upper-room UVGI might be helpful as an intervention against the transmission of Covid-19. Given the magnitude of the current Covid-19 pandemic and the urgent need for effective interventions, we felt that it was important that the potential efficacy of upper-room UVGI be rapidly evaluated (Reviewer 3 alludes to this), as it is one technology that might inhibit the spread of Covid-19 in buildings. Given the urgent situation and the fact that (to date) no experimental Z value results have been published on the aerosolised SARS-CoV-2 virus, all that can be done is to evaluate the likely impact of UV-C light on the virus through analysis of existing published data of closely related viruses – as we have done. So while it would be ideal to present new experimental data, we believe that under the circumstances our approach is valid (as well as being urgently required), as it is the first study of its kind to evaluate the potential efficacy of upper-room UVGI air disinfection against Covid-19. For this reason, we have changed the title of the paper and have added ‘a feasibility study’ to reinforce the exploratory nature of the work undertaken. We have also included a new paragraph in the discussion section specifically highlighting the limitations of the study (Lines 385-399). Notwithstanding the above comments, since the manuscript was first submitted, new experimental work has been undertaken which has conclusively demonstrated that SARS-CoV-2 is particularly vulnerable to UV-C light. Accordingly, we have incorporated the results from three new studies (Bianco et al., Inagaki et al., and experimental work reported by Signify) into our revised manuscript, all of which have enabled us to directly calculate Z values for SARS-CoV-2 (in liquid) irradiated by UV-C light (Lines 221-227). While these Z values do not relate to the behaviour of SARS-CoV-2 in aerosols, they do reveal that SARS-CoV-2 is more susceptible to UV-C damage than both SARS-CoV-1 and MERS-CoV, and strongly suggests that the Z value for the MHV coronavirus (one of only three coronavirus to be irradiated in an aerosol) is likely to be a valid surrogate for SARS-CoV-2 in aerosol form (Lines 276-283). Furthermore, in order to add a ‘factor of safety’ into our analysis we performed the upper-room UVGI feasibility calculations twice, once using Z = 0.377 m2/J (i.e. the measured Z value for the MHV coronavirus) and again using Z = 0.0377 m2/J (i.e. a highly conservative Z value) so that we could be confident of our findings (Lines 244-254) The simulation employed is a simple tool based on a well-mixed model. The equations are previously established and published in previous research. Reply: We agree that the well-mixed model is a relatively simple tool. However, we deliberately wished to keep the analysis simple because the article is a feasibility study, designed to appeal to a wide audience (including clinicians and public health professionals, as well as building engineers and indoor air scientists). As such, we did not want to over-complicate matters, because we did not want to obscure the central message that upper-room UVGI has the potential to be effective against Covid-19, see Lines 396-399 and revised conclusion section. Validity of the findings The z values used in the model are based on assumption and were NOT validated with real experimental data. Reply: We have now reported real experimental data directly relating to the irradiation of SARS-CoV-2 using UV-C light (see above). While the results reported relate to the SARS-CoV-2 in liquids and not in aerosols, because no such experimental data exists for UV-C irradiation of SARS-CoV-2 in aerosols, and given the current global emergency, we feel that the assumptions made are both conservative and justified (see above). Furthermore, because aerosol Z values for two additional coronaviruses (safe surrogates for SARS-CoV-2) have recently been reported (Buonanno et al. 2020) that are very close to the values obtained by Walker and Ko for the MHV coronavirus, it strongly implies that SARS-CoV-2 will also be sensitive to UV-C damage when aerosolised. Having said this, we have added a new limitations paragraph in the discussion section qualifying our findings as being indicative only given that to date no UV experiments have been performed directly on aerosols containing the SARS-CoV-2 virus (Lines 385-399). Comments for the Author see above ________________________________ Reviewer 2 (David Sykes) Basic reporting The reviewer considered the second paragraph of the abstract to be ”dense” and a little complex to read. If it is within the word count restriction and does not lead to lose of clarity of the main message, some further revision is suggested. Reply: We thank the reviewer for pointing this out. We have now revised the abstract in order to improve its clarity. Page 10, Section 4 Discussion – second line “highly lightly” – should be “highly likely” Reply: This has now been corrected. No further comments Experimental design no comment Validity of the findings Page 8, Section 3.1 Analysis – second paragraph “mean Z value for SARS-CoV-1 was 0.00489” – however, reviewer found the mean to be 0.00619, likely to be an interpreted or weighted mean? Please check with Authors, and ensure this is clear within the results. Reply: We thank the reviewer for pointing this out. The reported mean value is actually an adjusted mean designed to avoid bias due to pseudo-replication, which can occur because for some of the studies more than one Z value was reported. Accordingly, for those studies where two Z values were reported for different UV doses, we first aggregated the Z values reported for the various individual studies and then used the aggregated values to calculate the overall mean Z values for the respective viruses. We have now added a sentence in the methods section to make this point clear (lines 142-145) Page 9, Section 3.3 (Old version) Upper-room results – second paragraph. The main findings seem perfectly acceptable and indeed translate well from the table, to the results, discussion, conclusions and finally to the abstract. However, given this is the basis of the paper, the reviewer decided to try and replicate the results from the formula [8], using the data given in Table 7, as might reader of the paper. This proved difficult, and could be due to reviewer not fully understanding the maths, or a translation of units. Again as above, it is advised to check with Authors. Reply: We thank the reviewer for thoroughly checking our calculations and raising this point. We have checked our calculations and find them to be correct. Please see the sample calculation, which is provided below. Sample calculation Assumptions n = 2 # Air change rate per hour (AC/h) Zur = 0.377 # UV susceptibility constant for virus in air (m2/J) huv = 0.4 # Height of UV zone (m) hr = 2.5 # Floor to ceiling height (m) fs = 0.1 # Required survival fraction (e.g. 10% survival which is equivalent to a 90% kill) So, using equations 5 and 6: tres = (1/n)*60*60 # Average residence time of droplets in room space (sec) tres = 1800 sec tuv = tres*(huv/hr) # Average residence time of droplets in the upper-room UV zone (sec) tuv = 288 sec (i.e. 4.8 min) Now, using equation 8: E = -(1/(Zur*tuv))*ln(fs)) # UV irradiation flux in W/m2 E = 0.021207 W/m2 E = 2.1207 microW/cm2 To calculate equivalent air change rate generated by an average UV-C flux of 50 microW/cm2, we use equation 9: Euv = 50 # Average UV-C irradiance (microW/cm2) Euv1 = (Euv1/1000)*10 # UV irradiation flux (W/m2) Nuv = Zur*Euv1*(huv/hr)*3600 # Equivalent number of air changes (AC/h) Nu = 108.576 AC/h NB. These results are the same as those presented in Table 7 and elsewhere. No further comments Comments for the Author As the reviewer I am satisfied that the Authors have considered the how SARS-CoV-2 might be susceptible to UV-C light by analysing other viruses, trying to develop a UV-C susceptibility constant, Z. Then using this knowledge to investigate the efficacy of an upper-room reduction of the COVID-19 air transmission, and using the results generated to support their conclusions. Reply: We thank the reviewer for their kind words of support. ________________________________ Reviewer 3 (Huw Woodward) Basic reporting Typo in first sentence of Discussion. 'Lightly' should be 'likely'. Typo in first line of page 12 in Discussion. 'This finding is of course is'. Reply: We thank the reviewer for spotting these errors, which have now been corrected. Experimental design No comment Validity of the findings Covid-19 can be transmitted via droplets which may not be carried to the upper room zone by the indoor airflow. These larger droplets will eventually either deposit on surfaces or reduce in size due to evaporation, however there is a possibility that they could remain in the breathing zone for a significant period of time. Could the authors comment on this and its implications for the effectiveness of upper room UV? Reply: We thank the reviewer for raising this important issue. In response we have added a new paragraph in the discussion section raising this issue and highlighting the fact droplets can decouple from convective air streams and settle out due to gravitational deposition, with the result they may not be irradiated. This is something that is poorly understood and potentially could impair the performance of any upper-room UVGI system, especially if these un-irradiated droplets spend some time in the breathing zone. Accordingly, we have discussed this matter in a new limitations paragraph added to the discussion section (Lines 348-373). The analysis assumes a well mixed room. The authors acknowledge this and refer to a paper which illustrates that this is likely an acceptable assumption for most rooms (reference 11). However an expanded discussion of the limitations of this assumption would be of value. Are there occurrences when this may not be a valid assumption and therefore the effectiveness of upper room UV might be reduced? Reply: The reviewer makes an important point here. Upper-room UVGI air disinfection is highly dependent on good air mixing occurring between the upper and lower portions of the room. While the well-mixed model is applicable (i.e. a good approximation) to many contexts there are limits to the assumptions made in this model. Accordingly, we have added a new paragraph in the discussion section highlighting the importance of good air mixing with respect to upper-room UVGI. Furthermore, we have also commented on ventilation improvements that could be made to increase room air mixing and thus potentially increase the efficacy of the air disinfection process (Lines 378-392). Comments for the Author This is a very timely article by the authors as various control measures to mitigate the transmission rate of Covid-19 indoors are being considered. The authors make a convincing case that aerosolised SARS-CoV-2 is likely to be susceptible to UV-C irradiation using the evidence currently available in the literature. Their analysis demonstrates that high equivalent AC/H could be achieved by installing upper room UV. Reply: We thank the reviewer for their kind words of support. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Accurate knowledge of the spatial and temporal patterns of coral bleaching is essential both for understanding how coral reef ecosystems are changing today and forecasting their future states. Yet, in many regions of the world, the history of bleaching is poorly known, especially prior to the late 20 th century. Here, we use the information preserved within skeleton cores of long-lived Porites corals to reconstruct the past century of bleaching events in the Saudi Arabian central Red Sea. In these cores, skeletal 'stress bands'-indicative of past bleaching-captured known bleaching events that occurred in 1998 and 2010, but also revealed evidence of previously unknown bleaching events in 1931, 1978, and 1982. However, these earlier events affected a significantly lesser proportion of corals than 1998 and 2010. Therefore, coral bleaching may have occurred in the central Red Sea earlier than previously recognized, but the frequency and severity of bleaching events since 1998 on nearshore reefs is unprecedented over the past century.</ns0:p><ns0:p>Conversely, corals living on mid-to outer-shelf reefs have not been equally susceptible to bleaching as their nearshore counterparts, since stress bands were five times more prevalent nearshore. Whether this pattern of susceptible nearshore reefs and resistant outer-shelf reefs continues in the future remains a key question in forecasting coral reef futures in this region.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Reef-building corals thrive in the warm waters of the tropical oceans. Yet, despite their affinity for warm regions, anomalous increases in temperature of as little as 1 &#176;C can damage the symbiosis between the coral host and the photosynthetic algae that inhabit the host's tissues.</ns0:p><ns0:p>When summertime temperatures exceed typical levels, the endosymbiont photosystem is impaired and begins to produce more reactive oxygen species than the coral can tolerate, leading to the expulsion of the symbionts <ns0:ref type='bibr'>(Lesser, 1997;</ns0:ref><ns0:ref type='bibr' target='#b1'>Baker, Glynn &amp; Riegl, 2008)</ns0:ref>. Without their pigmented symbionts, corals turn white as their calcium carbonate skeletons become visible through their translucent tissues. Since the symbionts provide most of the energy that the coral needs to survive, bleaching causes reduced growth, fecundity, and lipid content, eventually leading to mortality if bleaching is prolonged <ns0:ref type='bibr' target='#b40'>(Mendes &amp; Woodley, 2002;</ns0:ref><ns0:ref type='bibr' target='#b24'>Grottoli, Rodrigues &amp; Juarez, 2004)</ns0:ref>. Coral bleaching was first observed by scientists in 1929 during the Great Barrier Reef Expedition on a shallow reef flat when calm weather led to localized heating of reef waters <ns0:ref type='bibr'>(Yonge &amp; Nicholls, 1931)</ns0:ref>. Other small-scale bleaching events were later observed due to localized disturbances such as freshwater <ns0:ref type='bibr' target='#b23'>(Goreau, 1964)</ns0:ref> or cold stress <ns0:ref type='bibr' target='#b45'>(Muscatine, Grossman &amp; Doino, 1991;</ns0:ref><ns0:ref type='bibr'>Saxby, Dennison &amp; Hoegh-Guldberg, 2003;</ns0:ref><ns0:ref type='bibr' target='#b29'>Hoegh-Guldberg &amp; Fine, 2004;</ns0:ref><ns0:ref type='bibr'>Paz-Garc&#237;a, Balart &amp; Garc&#237;a-De-L&#233;on, 2012)</ns0:ref>, with heat-induced, ocean basin-scale mass coral bleaching first observed in 1982/1983 <ns0:ref type='bibr' target='#b21'>(Glynn, 1983</ns0:ref><ns0:ref type='bibr' target='#b22'>(Glynn, , 1993;;</ns0:ref><ns0:ref type='bibr'>Coffroth, Lasker &amp; Oliver, 1990)</ns0:ref>, although other events may have occurred earlier <ns0:ref type='bibr'>(Cavole &amp; DeCarlo, 2020)</ns0:ref>. <ns0:ref type='bibr'>Since 1982, global</ns0:ref> PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed mass coral bleaching events have increased in frequency, most likely caused by more common heat stress due to global warming <ns0:ref type='bibr'>(Hughes et al., 2017</ns0:ref><ns0:ref type='bibr' target='#b38'>(Hughes et al., , 2018;;</ns0:ref><ns0:ref type='bibr'>Sully et al., 2019)</ns0:ref>.</ns0:p><ns0:p>The Red Sea is lined by thousands of kilometers of near-continuous, shallow-water coral reefs <ns0:ref type='bibr'>(Rowlands et al., 2012;</ns0:ref><ns0:ref type='bibr'>Churchill et al., 2019)</ns0:ref>. These reefs are mostly restricted to the continental shelf, ranging from fringing reefs along the coast to knoll reef platforms dotting the shelf until the slope break <ns0:ref type='bibr' target='#b43'>(Montaggioni et al., 1986)</ns0:ref>. Although the Red Sea is one of the warmest coral reef regions with summertime temperatures in the central and southern Red Sea routinely reaching 33 &#176;C, corals living there are not necessarily more prone to bleaching than conspecifics in cooler regions because they have acclimatized or adapted to their local environment. Experimental evidence suggests that corals in the far northern Red Sea, however, are currently living as much as 4 &#176;C below their thermal maximum, potentially a result of the south to north (i.e., warmer to cooler) migration of corals following the most recent glaciation <ns0:ref type='bibr' target='#b16'>(Fine, Gildor &amp; Genin, 2013;</ns0:ref><ns0:ref type='bibr'>Krueger et al., 2017)</ns0:ref>. This has led to suggestions that the far northern Red Sea could be a climate change refuge for at least some species <ns0:ref type='bibr' target='#b16'>(Fine, Gildor &amp; Genin, 2013;</ns0:ref><ns0:ref type='bibr'>Kleinhaus et al., 2020)</ns0:ref>, a hypothesis which-so far-has proven true since no bleaching has been observed there <ns0:ref type='bibr' target='#b48'>(Osman et al., 2018)</ns0:ref>. Conversely, the central Red Sea has experienced several bleaching events, which were directly observed in 1998 <ns0:ref type='bibr' target='#b13'>(Devantier &amp; Pilcher, 2000;</ns0:ref><ns0:ref type='bibr'>Devantier et al., 2000)</ns0:ref>, 2010 <ns0:ref type='bibr' target='#b19'>(Furby, Bouwmeester &amp; Berumen, 2013;</ns0:ref><ns0:ref type='bibr'>Pineda et al., 2013)</ns0:ref>, and 2015 <ns0:ref type='bibr' target='#b42'>(Monroe et al., 2018</ns0:ref>). Yet, there were few systematic reef surveys prior to 1998 in the Red Sea (but see <ns0:ref type='bibr' target='#b0'>Antonius, 1988)</ns0:ref>, leaving gaps in our knowledge of whether earlier bleaching events occurred in this region.</ns0:p><ns0:p>Although the surface waters of the Red Sea have warmed by ~0.8 &#176;C since 1900, in line with the global average for coral reef regions <ns0:ref type='bibr' target='#b38'>(Lough, Anderson &amp; Hughes, 2018)</ns0:ref>, the warming Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Bleaching histories from coral skeletal cores</ns0:head><ns0:p>Between August 2019 and January 2020, I drilled twenty-two skeletal cores from massive Porites spp. coral colonies near the Thuwal region of the central Red Sea (Fig. <ns0:ref type='figure'>1</ns0:ref>). The primary study location was a nearshore reef called Abu Shosha (11 cores), but I also collected cores at reefs across the shelf (1-2 cores per reef, 11 total cores). The cores were drilled downwards from the top of each colony using a pneumatic drill with either 3-or 5-cm diameter diamond-tipped bits. All cores were rinsed several times with fresh water, then with pure ethanol, and air dried.</ns0:p><ns0:p>To visualize density banding patterns within the cores, I scanned them with computerized tomography (CT) using a General Electric BrightSpeed machine. Scan settings included 100 kV Manuscript to be reviewed voltage, 9.6 cm field of view, and 1.25 mm pixel spacing (i.e., resolution). The CT scans were visualized using Osirix software, which enabled me to cut digital slices 3-5 mm thick along the primary growth axes <ns0:ref type='bibr'>(Carilli et al., 2009;</ns0:ref><ns0:ref type='bibr'>Cantin et al., 2010)</ns0:ref>. Annual density bands and anomalous high-density 'stress bands' were identified visually based on the banding pattern of each coral. Most of the cores had clear annual banding patterns with little ambiguity. Stress band identifications were based on their previously described appearances as sharply-defined bands that are anomalous relative to the regular annual banding pattern <ns0:ref type='bibr' target='#b32'>(Hudson et al., 1976;</ns0:ref><ns0:ref type='bibr'>Carilli et al., 2009;</ns0:ref><ns0:ref type='bibr'>Cantin &amp; Lough, 2014;</ns0:ref><ns0:ref type='bibr' target='#b3'>Barkley &amp; Cohen, 2016;</ns0:ref><ns0:ref type='bibr'>DeCarlo et al., 2017</ns0:ref><ns0:ref type='bibr'>DeCarlo et al., , 2019;;</ns0:ref><ns0:ref type='bibr' target='#b4'>Barkley et al., 2018)</ns0:ref>. The cores were not identified to species level, however there are only three possible species (lutea, lobata, and solida) with massive growth form in this region <ns0:ref type='bibr'>(Terraneo et al., 2019)</ns0:ref>, and a previous study found no effect of species on stress band prevalence <ns0:ref type='bibr' target='#b9'>(DeCarlo et al., 2020)</ns0:ref>. I followed the statistical approach of <ns0:ref type='bibr' target='#b27'>Hendy et al. (2003)</ns0:ref> to compare the prevalence of stress bands among years. Specifically, I calculated the probability of finding, per year, the number of observed stress bands or fewer based on bleaching events affecting a certain number of Porites corals. Determining these probabilities enables statistical testing of severity between events (e.g., whether the number of observed stress bands in a given year is statistical different from another year, or from zero). These calculations require three inputs: the number of replicates (i.e., the number of cores covering each year), the number of stress bands observed per year, and the severity of hypothetical bleaching events. Since the latter is arbitrary, I repeated the calculations using two severity levels: the proportion of Porites that were bleached on Abu Shosha (~1/3) during underwater surveys in 2015 <ns0:ref type='bibr' target='#b42'>(Monroe et al., 2018)</ns0:ref>, and the maximum proportion of stress bands observed in any one year (see Results).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed of observations in ICOADS corresponding to select bleaching years that fell within the HadISST and ERSSTv5 grid-boxes nearest to Abu Shosha. Wind speed data were acquired from the European Centre for Medium-Range Weather Forecasts ERA5 reanalysis product <ns0:ref type='bibr'>(Copernicus, 2017)</ns0:ref>. The data were downloaded as monthly means at 31-km resolution covering 1979-2019, and the average August-September wind speed anomalies were calculated per year for the grid-box nearest to Abu Shosha. August and September were selected because these are the months when coral bleaching has been observed in this region <ns0:ref type='bibr' target='#b13'>(Devantier &amp; Pilcher, 2000;</ns0:ref><ns0:ref type='bibr'>Pineda et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b42'>Monroe et al., 2018)</ns0:ref>.</ns0:p><ns0:p>Photosynthetically active radiation (PAR) data were acquired from the moderate resolution imaging spectroradiometer (MODIS) onboard the Terra satellite <ns0:ref type='bibr'>(2000)</ns0:ref><ns0:ref type='bibr'>(2001)</ns0:ref><ns0:ref type='bibr'>(2002)</ns0:ref><ns0:ref type='bibr'>(2003)</ns0:ref><ns0:ref type='bibr'>(2004)</ns0:ref><ns0:ref type='bibr'>(2005)</ns0:ref><ns0:ref type='bibr'>(2006)</ns0:ref><ns0:ref type='bibr'>(2007)</ns0:ref><ns0:ref type='bibr'>(2008)</ns0:ref><ns0:ref type='bibr'>(2009)</ns0:ref><ns0:ref type='bibr'>(2010)</ns0:ref><ns0:ref type='bibr'>(2011)</ns0:ref><ns0:ref type='bibr'>(2012)</ns0:ref><ns0:ref type='bibr'>(2013)</ns0:ref><ns0:ref type='bibr'>(2014)</ns0:ref><ns0:ref type='bibr'>(2015)</ns0:ref><ns0:ref type='bibr'>(2016)</ns0:ref><ns0:ref type='bibr'>(2017)</ns0:ref><ns0:ref type='bibr'>(2018)</ns0:ref> and from SeaWIFS (1998-1999) <ns0:ref type='bibr' target='#b17'>(Frouin, Franz &amp; Werdell, 2002)</ns0:ref>. Like the wind data, I averaged the August-September PAR anomalies per year for the grid-box nearest to Abu Shosha.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The oldest observable bands in the coral skeletal cores from Abu Shosha ranged from 1917 to 1986 with a median age of 1966 (Fig. <ns0:ref type='figure'>2</ns0:ref>), and those in cores from outside of Abu Shosha ranged from 1907 to 2010 with a median age of 1968 (Fig. <ns0:ref type='figure' target='#fig_11'>3</ns0:ref>). In total, Manuscript to be reviewed core. Most other identified stress bands fit within these same criteria, but with weaker anomalies than K24 and K2. Conversely, some stress bands (e.g., those in core K1) were identified based on anomalies to the normal banding pattern, but without exceptionally high density. Both the 1998 and 2010 stress bands in core K1 are characterized by distinct, thin bands that disrupt the regular, broad annual bands. Although this type of stress band was rare in the dataset, similar stress bands have been linked to directly-observed bleaching in other studies <ns0:ref type='bibr'>(DeCarlo &amp; Cohen, 2017)</ns0:ref>. In a few cases, stress bands appeared to result in multi-annual changes in density or banding patterns (e.g., <ns0:ref type='bibr'>K20 after 1998, and K13 after 1982)</ns0:ref>. Outside of Abu Shosha, I found only three stress bands among the 11 cores (two of which were in the same core), corresponding to <ns0:ref type='bibr'>1948</ns0:ref><ns0:ref type='bibr'>, 1978</ns0:ref><ns0:ref type='bibr'>, and 2010 (Fig. 3) (Fig. 3)</ns0:ref>. Details of all coral coring locations, as well as age and stress bands results, and listed in Supplemental Table <ns0:ref type='table'>S1</ns0:ref>. I calculated the probability of finding the observed number of stress bands or fewer for each year of the two time-series (Abu Shosha, and outside of Abu Shosha). These calculations were performed for a bleaching event affecting either 1/3 (as observed in benthic surveys of Abu Outside of Abu Shosha, cores were from younger corals, on average, compared to Abu Shosha, which limits the statistical power (Fig. <ns0:ref type='figure' target='#fig_12'>4B</ns0:ref>). Nevertheless, it is clear that the 1998 and 2010 events that affected most Porites at Abu Shosha did not similarly affect other reefs, and I can exclude that there were any events affecting 8 out of 11 Porites since 1949. The 2010 and 1978 stress bands found in cores K9 and K6, respectively, suggest that these bleaching events did have at least some influence on corals outside of Abu Shosha, though. Conversely, the 1948 stress band in core K6 is not replicated in either the two other cores from outside Abu Shosha, or in any of the four Abu Shosha cores, that extend that far back in time.</ns0:p><ns0:p>The four SST datasets used here show some similarities in heat stress during overlapping years, but with key differences (Fig. <ns0:ref type='figure' target='#fig_13'>5</ns0:ref>). According to HadISST, the greatest DHW was reached in 1931 (6.0 &#176;C-weeks), followed by 1998 (5.4 &#176;C-weeks) (Fig. <ns0:ref type='figure' target='#fig_13'>5A</ns0:ref>). <ns0:ref type='bibr'>, 1941, 1957, 1963, 2001, 2006, 2017)</ns0:ref>. Higher-resolution satellite SST datasets Manuscript to be reviewed highest DHW for this location of 5.3 &#176;C-weeks. During 2010, CRW displays highest DHW nearshore (e.g., Abu Shosha), but with at least 3 &#176;C-weeks on the mid-to outer-shelf reefs (Fig. <ns0:ref type='figure' target='#fig_14'>6</ns0:ref>). Thus, even though the lower spatial resolution of OI-SSTv2 means that it would average some of these spatial differences of DHW (Fig. <ns0:ref type='figure'>7D</ns0:ref>), this alone cannot explain the full difference between the two datasets. Overall, the correlation (r 2 ) between DHW calculated with the two longer-term datasets that are based primarily on shipboard measurements is only 0.16, and that between the two satellite-based datasets is even worse (0.13) (Fig. <ns0:ref type='figure' target='#fig_12'>4</ns0:ref>).</ns0:p><ns0:p>During August and September of 1931, there were 544 shipboard measurements in the central Red Sea, 274 of which were located within the ERSSTv5 grid-box, and only 1 of which was located within the HadISST grid-box (Fig. <ns0:ref type='figure'>7</ns0:ref>). By 1982, these numbers increased to 863, Manuscript to be reviewed been incorporated in a global assessment of spatial and temporal patterns of bleaching, is that no other bleaching events have occurred in this region, at least since 1980 <ns0:ref type='bibr' target='#b38'>(Hughes et al., 2018)</ns0:ref>. It should be noted that coral disease surveys began near Jeddah (~100 km to the south) in 1982 and continued for several years <ns0:ref type='bibr' target='#b0'>(Antonius, 1988)</ns0:ref>. In these surveys, 'frequent' coral bleaching was observed near Jeddah (13-25 colonies per 30-minute survey), although the year(s) in which this occurred is not stated <ns0:ref type='bibr' target='#b0'>(Antonius, 1988)</ns0:ref>. Since few colonies were affected and the author attributed the bleaching near Jeddah to a combination of pollution and freshwater run-off (albeit with no direct evidence to support this claim), subsequent studies have not considered these early observations to represent heat-induced coral bleaching <ns0:ref type='bibr' target='#b19'>(Furby, Bouwmeester &amp; Berumen, 2013;</ns0:ref><ns0:ref type='bibr' target='#b38'>Hughes et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b7'>Berumen et al., 2019)</ns0:ref>.</ns0:p><ns0:p>In this study, stress bands in long-lived Porites corals are broadly consistent with this current knowledge, except that I also found three stress bands corresponding to 1982 at a nearshore reef, Abu Shosha (Fig. <ns0:ref type='figure'>2</ns0:ref>). Thus, the cores show evidence of 1982 bleaching that may be concurrent with direct observations of bleaching near Jeddah, even though the cores were collected ~100 km from the pollution and freshwater sources. outside of the main shipping route where most pre-satellite measurements were made (Fig. <ns0:ref type='figure'>7</ns0:ref>).</ns0:p><ns0:p>Although ERSSTv2 grid-boxes are even larger, encompassing effectively the entire width of the Red Sea, the closest grid-box to Abu Shosha captures the main shipping route. The satellite products also differ in spatial resolution. OI-SSTv2 grid-boxes (0.25&#176;) near Abu Shosha either include a large portion of land or a combination of shelf and offshore waters, whereas CRW (5 km) grid-boxes are small enough to include only shelf areas (Fig. <ns0:ref type='figure'>7D</ns0:ref>). Temporally, the measurement intensity of surface water temperatures from ships increased dramatically over time (Fig. <ns0:ref type='figure'>7A-C</ns0:ref>), leaving greater uncertainty in earlier SST data. The satellite-based data suffer from a similar problem, as new satellites have come into operation over time. OI-SSTv2 attempts to minimize temporal biases by using only one type of sensor (the advanced very high resolution radiometer, AVHRR) at the expense of spatial resolution, whereas CRW uses more satellites to achieve greater spatial resolution at the expense of biases in some earlier years <ns0:ref type='bibr'>(Liu et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b2'>Banzon et al., 2016;</ns0:ref><ns0:ref type='bibr'>DeCarlo &amp; Harrison, 2019;</ns0:ref><ns0:ref type='bibr' target='#b9'>DeCarlo, 2020)</ns0:ref>. Thus, both have certain advantages, with OI-SSTv2 being more stable over time but CRW isolating shelf waters, making it difficult to conclude which is most accurate at a given time without validation against independent datasets. Discrepancies between DHW calculated from satellite-based SST datasets have also been reported for the Great Barrier Reef (GBR) of Australia <ns0:ref type='bibr'>(DeCarlo &amp; Harrison, 2019)</ns0:ref>, albeit to a</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed lesser degree than observed here in the central Red Sea. However, unlike the GBR, temperature logger data from Red Sea coral reefs are, to my knowledge, unavailable prior to 2009 <ns0:ref type='bibr'>(Davis et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b8'>Blythe, da Silva &amp; Pineda, 2011;</ns0:ref><ns0:ref type='bibr'>Pineda et al., 2013;</ns0:ref><ns0:ref type='bibr'>DeCarlo et al., 2016)</ns0:ref>, and intermittent since then. Testing the accuracy of different SST datasets during only the past decade is unlikely to resolve this problem because the differences are not stationary in time, meaning that accuracy in recent years does not necessarily translate to accuracy in previous decades <ns0:ref type='bibr'>(DeCarlo &amp; Harrison, 2019)</ns0:ref>. In addition to discrepancies between satellite SST datasets over broad spatial scales (kilometers), relatively large differences in temperature means and variances (of up to several &#176;C) can exist over just hundreds of meters within coral reef environments <ns0:ref type='bibr'>(Davis et al., 2011;</ns0:ref><ns0:ref type='bibr'>Pineda et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b49'>Palumbi et al., 2014;</ns0:ref><ns0:ref type='bibr'>DeCarlo et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The Abu Shosha cores were collected from the reef slope on the exposed side of the reef crest (Fig. <ns0:ref type='figure'>1</ns0:ref>), where diurnal cycles of heating and cooling are less than on top of the shallow reef flat Manuscript to be reviewed</ns0:p><ns0:p>In addition to temperature, other factors such as light and nutrients can modulate the bleaching susceptibility of corals <ns0:ref type='bibr'>(Brown, 1997;</ns0:ref><ns0:ref type='bibr' target='#b15'>Dunne &amp; Brown, 2001;</ns0:ref><ns0:ref type='bibr'>Wooldridge, 2009;</ns0:ref><ns0:ref type='bibr'>Cunning &amp; Baker, 2012;</ns0:ref><ns0:ref type='bibr'>Wiedenmann et al., 2013;</ns0:ref><ns0:ref type='bibr'>Vega Thurber et al., 2014;</ns0:ref><ns0:ref type='bibr'>Skirving et al., 2017;</ns0:ref><ns0:ref type='bibr'>DeCarlo &amp; Harrison, 2019;</ns0:ref><ns0:ref type='bibr' target='#b9'>DeCarlo et al., 2020)</ns0:ref>. I tested if wind speed or PAR anomalies correspond to bleaching events. Low-wind conditions can amplify heating on shallow reefs <ns0:ref type='bibr'>(Davis et al., 2011;</ns0:ref><ns0:ref type='bibr'>DeCarlo et al., 2017)</ns0:ref>, and unusually high PAR can exacerbate heat stress <ns0:ref type='bibr' target='#b15'>(Dunne &amp; Brown, 2001;</ns0:ref><ns0:ref type='bibr'>Skirving et al., 2017)</ns0:ref>. Although bleaching in this study tended to occur in low-wind years, wind speed is not a unique predictor of bleaching since there are several years with weaker winds than bleaching years (Fig. <ns0:ref type='figure' target='#fig_16'>8A</ns0:ref>). Additionally, low-wind conditions are likely responsible for some of the positive SST anomalies, making it difficult to treat these two factors as independent. Likewise, PAR anomalies do not seem to be a primary driver of bleaching here since there was only a modest positive anomaly in 2010 and a negative anomaly in 2015 (Fig. <ns0:ref type='figure' target='#fig_16'>8B</ns0:ref>). Yet, it is possible that the exceptionally high PAR in 1998 contributed, at least in part, to the severe bleaching response in that year. There are no continuous nutrient datasets available in this area, but a study of summertime upwelling ~300 km south in the Farasan Banks may offer some indication of upwelled nutrient supply <ns0:ref type='bibr' target='#b9'>(DeCarlo et al., 2020)</ns0:ref>. Upwelling of high-nutrient Gulf of Aden Intermediate Water (GAIW) in the Farasan Banks is one of the main sources of nutrients to Red Sea surface waters, and traces of GAIW (10-20%) have been identified at the shelf edge in the central Red Sea <ns0:ref type='bibr'>(Churchill et al., 2014)</ns0:ref>. Thus, it is conceivable that corals on Abu Shosha are occasionally exposed to elevated nutrients as traces of GAIW are mixed onto the shelf. Notably, June-August of 1982 and 2015 were among the strongest upwelling pulses in the Farasan Banks, both of which are bleaching years on Abu Shosha despite relatively low heat stress.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed this year lends support to this being a real bleaching event, it probably affected a relatively small proportion of corals, and the environmental driver of any bleaching in 1978 is unclear.</ns0:p><ns0:p>1982: This year marks the first occurrence of stress bands in multiple cores from one reef, similar to the results of a similar study on the northern GBR and in the Coral Sea <ns0:ref type='bibr'>(DeCarlo et al., 2019)</ns0:ref>. <ns0:ref type='bibr'>Likewise, 1982</ns0:ref><ns0:ref type='bibr'>Likewise, /1983</ns0:ref> is the first known large-scale bleaching event that stretched across the Pacific Ocean <ns0:ref type='bibr' target='#b21'>(Glynn, 1983;</ns0:ref><ns0:ref type='bibr' target='#b47'>Oliver, 1985)</ns0:ref>. Some bleaching was observed near Jeddah around this time, but key details such as specific times, places, and bleaching extent are lacking <ns0:ref type='bibr' target='#b0'>(Antonius, 1988)</ns0:ref>. SST datasets, including HadISST, ERSSTv5, and the satellite-based OI-SSTv2 all show no heat stress during this year. However, satellite-based SST also showed very little heat stress on the <ns0:ref type='bibr'>GBR in 1982</ns0:ref><ns0:ref type='bibr'>(DeCarlo &amp; Harrison, 2019)</ns0:ref> even though the majority of corals bleached, and more than half died, on most nearshore reefs that were monitored at the time <ns0:ref type='bibr' target='#b47'>(Oliver, 1985)</ns0:ref>. Furthermore, coral cores in the southern Red Sea show 1982 stress bands, albeit in &lt;15% of corals, despite similarly low heat stress, likely a result of nutrient-injection from the strong upwelling that preceded bleaching there <ns0:ref type='bibr' target='#b9'>(DeCarlo et al., 2020)</ns0:ref>. Therefore, I suggest that 1982 was probably a minor bleaching event on Abu Shosha even though heat stress was apparently either low or absent. This could be a result of either inaccuracies in the SST datasets and/or the exacerbation of minor heat stress by upwelled nutrients early in the summer. 1998: This is the only year that all four SST datasets agree that there was relatively high heat stress. Additionally, 1998 is the first time that mass coral bleaching in the central Red Sea was observed and recorded by scientists <ns0:ref type='bibr' target='#b13'>(Devantier &amp; Pilcher, 2000)</ns0:ref>. Although it is unclear if Abu Shosha itself was surveyed at this time, up to 65% of corals bleached on nearshore reefs around Rabigh, only 50 km to the north <ns0:ref type='bibr' target='#b13'>(Devantier &amp; Pilcher, 2000)</ns0:ref>. Consistent with the visual observations, coral cores from Abu Shosha reveal evidence of severe bleaching, with clear stress Manuscript to be reviewed Manuscript to be reviewed (cores K4 and K5) <ns0:ref type='bibr' target='#b42'>(Monroe et al., 2018)</ns0:ref>. As discussed previously <ns0:ref type='bibr' target='#b42'>(Monroe et al., 2018)</ns0:ref>, there was little heat stress in 2015, with only the low-resolution ERSSTv5 showing substantial DHW.</ns0:p><ns0:p>Like 1982, it is possible that minor heat stress was exacerbated by upwelled nutrients since 2015 was one of the strongest GAIW upwelling years of the satellite era <ns0:ref type='bibr' target='#b9'>(DeCarlo et al., 2020)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>Regardless of uncertainties in the precise DHW during each individual year, it is clear that heat stress events have become more common and of higher magnitude since 1998.</ns0:p><ns0:p>Likewise, the three bleaching events during this time <ns0:ref type='bibr'>(1998, 2010, and 2015)</ns0:ref> left signatures in the nearshore coral skeletal cores that, when viewed as a whole, are unprecedented in terms of frequency and severity since at least the mid-1930s. One potential glimmer of hope is that the results here suggest these corals may have acclimatized after 1998 and 2010, such that they were less affected by bleaching in 2015 (i.e., they may have bleached but not formed stress bands), consistent with signs of acclimatization in other regions <ns0:ref type='bibr'>(Vargas-&#193;ngel et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b25'>Guest et al., 2012;</ns0:ref><ns0:ref type='bibr'>Pratchett et al., 2013;</ns0:ref><ns0:ref type='bibr'>Putnam &amp; Gates, 2015;</ns0:ref><ns0:ref type='bibr' target='#b20'>Gintert et al., 2018;</ns0:ref><ns0:ref type='bibr'>Coles et al., 2018;</ns0:ref><ns0:ref type='bibr'>DeCarlo et al., 2019)</ns0:ref>. Additionally, mid-and outer-shelf reefs have been less sensitive to heat stress than those nearshore, with evidence of only minor bleaching events in the skeletal cores and no apparent increase in frequency or severity in recent decades. A similar pattern of highly susceptible nearshore corals and more resilient offshore corals has been reported in the Mesoamerican reef system <ns0:ref type='bibr' target='#b6'>(Baumann et al., 2019)</ns0:ref>. As sea surface temperatures increase in the Manuscript to be reviewed coming decades, the central Red Sea will be subjected to more frequent and intense heat stress events <ns0:ref type='bibr'>(Cantin et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b30'>van Hooidonk, Maynard &amp; Planes, 2013;</ns0:ref><ns0:ref type='bibr'>Hoegh-Guldberg et al., 2014)</ns0:ref>. Corals living on nearshore reefs of this region are therefore likely to experience more severe bleaching events with diminishing return times, unless they can acclimatize or adapt fast enough. On the other hand, corals on outer-shelf reefs of the Saudi Arabian central Red Sealike their counterparts in the northern Red Sea-have so far avoided severe bleaching, but we do not yet know whether this resistance will be maintained as the ocean continues to warm. Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 7</ns0:note><ns0:p>Historical shipboard SST measurements in the ICOADS database. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>trend has been punctuated by sporadic episodes of anomalously high temperatures and pulses of rapid warming(Raitsos et al., 2011; Krokos et al., 2019). In particular, two relatively warm intervals, one centered around the 1930s and the other around the 1970s, are superimposed on the centennial warming trend(Krokos et al., 2019). These warm periods result from the combination of climate teleconnections in the north Atlantic and equatorial Pacific(Karnauskas &amp; Jones, 2018; Krokos et al., 2019). Critically, since systematic surveys of coral health had not yet begun in the Red Sea, we do not know if these earlier warm periods were associated with coral bleaching events, or alternatively, if the recent bleaching events in the central Red Sea are unprecedented. Here, I use the stress history preserved within the skeletons of long-lived Porites spp. corals from the Saudi Arabian central Red Sea to reconstruct bleaching events over the past century, and I compare the presence of stress bands to a variety of ocean temperature and wind datasets.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>I counted 1,244 annual bands. At Abu Shosha, I identified high-density stress bands in 2015 (1/11 cores), 2010 (8/11 cores), 1998 (8/11 cores), 1982 (3/10 cores), 1978 (1/10 cores), and 1931 (1/2 cores) (Fig. 2). Only one core (K15) had no stress bands in any year. Most stress bands were distinct high-density anomalies, but their appearance varied among cores. For example, the 2010 stress bands in cores K24 and K2 were the most obvious because both the absolute density of the stress band, and the sharpness of the density gradient leading into the stress band, were exceptional relative to the rest of the PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Shosha in 2015) or 8/11 (the number of stress bands identified in Abu Shosha corals during 1998 and 2010) of Porites colonies (Fig.4). At Abu Shosha, I can exclude (with at least 95% confidence) that a comparable event to 1998/2010 occurred between 1934-2019 (Fig.4A). Even though stress bands were also present in1978, 1982, and 2015, the number of cores with stress bands in these years relative to the total number of cores was low enough that I could exclude an event affecting at least 8 out of 11 Porites. Conversely, even though only one stress band was associated with 1931, I cannot exclude that an event equivalent to 1998/2010 occurred in this year due to the small sample size. Detecting an event affecting 1/3 of Porites requires greater statistical power, and all years prior to 1970 cannot be excluded due to sample size. Additionally,PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020) Manuscript to be reviewed based on stress band counts, I cannot exclude with 95% confidence that bleaching in 1978, 1982, or 2015 affected 1/3 or fewer of Porites colonies.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>OI-SSTv2 and CRW) likewise show some agreement, but also key disparities in certain years (Fig. 5B). For example, both OI-SSTv2 and CRW show no heat stress in 1982, nearly the same DHW in 1998 (4.6 and 4.4 &#176;C-weeks, respectively), and relatively low DHW in 2015. However, the two depart during 2010, when OI-SSTv2 shows only 0.5 &#176;C-weeks while CRW reached its PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>535, and 26, respectively. Finally, in 1998, the sampling intensity was even greater, with 4,644 measurements in the central Red Sea, 2,466 in the ERSSTv5 grid-box, and 742 measurements in the HadISST grid-box.Wind speeds during August and September of years with observed bleaching or stress bands on Abu Shosha were all anomalously low, although not exceptionally so (Fig.8A). The lowest wind speeds between 1979 and 2018 occurred in 2003, followed by 1982. The years of highestPAR were 1998PAR were , 2002PAR were , and 2004 (Fig.8B). Although the bleaching year of 2010-like 1998-was also associated with a positive PAR anomaly, PAR during 2015 was unusually low.DiscussionScientists directly observed and reported coral bleaching in the central Red Sea during August-Septemberof 1998, 2010, and 2015<ns0:ref type='bibr' target='#b13'>(Devantier &amp; Pilcher, 2000;</ns0:ref><ns0:ref type='bibr' target='#b19'>Furby, Bouwmeester &amp; Berumen, 2013;</ns0:ref> Pineda et al., 2013;<ns0:ref type='bibr' target='#b42'>Monroe et al., 2018)</ns0:ref>. The current knowledge, which hasPeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>The 1982 event at Abu Shosha was significantly less severe than 1998/2010 (95% confidence), but I cannot exclude that minor bleaching of one third or fewer Porites corals occurred (Fig.4). Additionally, I found two stress bands in 1978, and single stress bands in each of 1948 and 1931. The 1978 event is also significantly less severe than 1998/2010, but the 1931 and 1948 events cannot be differentiated from 1998/2010 without more samples. However, while 1978 had no heat stress, 1931 was the summer with highest DHW according to HadISST (Fig.5). It is important to recognize that both the temperature and bleaching severity in 1931 are poorly constrained due to small sample sizes as I collected only three cores this old and there were far fewer shipboard temperaturePeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)Manuscript to be reviewed measurements in the 1930s than recent decades<ns0:ref type='bibr' target='#b12'>(Deser et al., 2010)</ns0:ref> (Fig.7). Nevertheless, even though each is sample-size limited, the correspondence between the clear 1931 stress band in core K13 and the exceptionally high heat stress during summer 1931 in HadISST leaves open the possibility that this was a bleaching event.Porites are generally considered to be relatively resistant to stress(Darling et al., 2012;<ns0:ref type='bibr' target='#b39'>McClanahan et al., 2020)</ns0:ref> and have shown evidence of acclimatization to repeated marine heatwaves (DeCarlo et al.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>Davis et al., 2011), but localized heating can still differentiate the water temperatures to which these corals were exposed from the larger-scale SST represented by satellite products(Pineda et al., 2013). Together, these issues present a fundamental limitation to understanding the drivers of coral bleaching in the central Red Sea, especially on shallow reef flats, because there is a low degree of confidence in the magnitudes of heat stress that have sparked bleaching. Corals themselves can shed light on past SST variability, though, since the trace-element geochemistry of their skeletons is sensitive to temperature(Corr&#232;ge, 2006;<ns0:ref type='bibr' target='#b46'>Nurhati, Cobb &amp; Di Lorenzo, 2011)</ns0:ref>. Previous analyses of temperature proxies in coral skeletal cores from Abu Shosha and Shi'b Nazar showed some of the highest summer temperature peaks in the early 2000s<ns0:ref type='bibr' target='#b11'>(D'Olivo et al., 2019</ns0:ref>; see also<ns0:ref type='bibr' target='#b44'>Murty et al., 2018)</ns0:ref>, broadly consistent with the satellite data, especially OI-SSTv2.PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>The past century of bleachingBelow, I summarize the bleaching history of the Saudi Arabian central Red Sea as inferred from coral cores and direct observations, in addition to the heat stress history during these bleaching years.1931: SST may have been anomalously high, especially in August, but HadISST and ERSSTv5 disagree on the magnitude of the heat stress (6.0 and 2.8 &#176;C-weeks, respectively). A single stress band was found corresponding to 1931, but only two cores from Abu Shosha extend this far back. Thus, 1931 is a potential bleaching year, but limitations in both the SST and stress band data prevent definitive conclusions. 1948: A single stress band was found in an outer-shelf core, but no other stress bands were found either in two other cores from mid-or outer-shelf reefs or in four cores from Abu Shosha. Neither HadISST nor ERSSTv5 show any heat stress at this time. Thus, 1948 is unlikely to have been a severe bleaching event, but rather was more likely to have been either a minor bleaching event or a non-temperature disturbance to this specific coral. 1978: Two stress bands were found in this year, one from an outer-shelf reef and another at Abu Shosha. The sample size of cores was sufficient to exclude that an event affecting 8 out of 11 Porites occurred from 1934 through 1978 at Abu Shosha, and from 1949 through 1978 outside of Abu Shosha. However, an event affecting 1 out of 3 Porites in 1978 could not be excluded, leaving open the possibility that a minor bleaching event affected reefs across the shelf. The 1978 stress bands in cores K6 and K14 are both clear, but there are no stress bands in the other 13 cores of this age (9 from Abu Shosha and 4 from other reefs). Both HadISST and ERSSTv5 show no heat stress as this time. Although the co-occurrence of two stress bands in PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>acclimatized following their previous exposure to heat stress, similar to results from the GBR (DeCarlo et al., 2019). No cores outside of Abu Shosha contained 2015 stress bands, although the outer-shelf reefs had &lt;10% bleaching at this time in benthic surveys, including Shi'b Nazar</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 3 CT</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>A-C) Locations and numbers of shipboard SST measurements inAugust and September of 1931, 1982, and 1998. Each measurement is plotted as a semi-transparent gray circle, such that darker gray coloring indicates multiple measurements in the same location. Numbers of measurements (n) are displayed for the central Red Sea (the area covered in the maps), and both the HadISST and ERSSTv5 grid-boxes nearest to Abu Shosha. (D) The size of grid-boxes in the OI-SSTv2 and CRW datasets. We use the OI-SSTv2 grid-box that covers Abu Shosha in our calculations, but the next grid-box to the west is also displayed to visualize its relation to shelf and offshore water, and both grid-boxes produce similar results such that the choice of grid-box does not affect our conclusions.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head>Figure 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='34,42.52,306.37,525.00,186.75' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head /><ns0:label /><ns0:figDesc>, 2019), meaning that they are not necessarily representative of entire It is important to recognize both the different spatial scales of the SST datasets and the potential for temporal biases due to changing measurement intensities. HadISST grid-boxes are 1&#176;x1&#176;, which is close to half the width of the Red Sea, and the grid-box closest to Abu Shosha is</ns0:figDesc><ns0:table><ns0:row><ns0:cell>single SST dataset's heat stress history accurately captures both the presence and absence of</ns0:cell></ns0:row><ns0:row><ns0:cell>bleaching events. HadISST shows highest DHW in 1931 and 1998, consistent with the bleaching</ns0:cell></ns0:row><ns0:row><ns0:cell>history, but 1978, 1982, 2010, and 2015 all have lower DHW than multiple non-bleaching years.</ns0:cell></ns0:row><ns0:row><ns0:cell>ERSSTv5, in contrast, shows highest DHW in 2010 and 2015, but fails to separate all other</ns0:cell></ns0:row><ns0:row><ns0:cell>bleaching years. OI-SSTv2 only shows relatively high DHW in 1998, but not 1982, 2010, or</ns0:cell></ns0:row></ns0:table><ns0:note>coral communities. It is also possible that some stress bands could arise from disturbances other than high temperatures, such as disease. Finally, Porites colonies could conceivably miss a bleaching event if calcification completely ceases. Nevertheless, Porites stress bands have captured known bleaching events across the Indo-Pacific(Cantin &amp; Lough, 2014;<ns0:ref type='bibr' target='#b3'>Barkley &amp; Cohen, 2016;</ns0:ref> DeCarlo et al., 2017 DeCarlo et al., , 2019<ns0:ref type='bibr' target='#b9'>DeCarlo et al., , 2020;;</ns0:ref><ns0:ref type='bibr' target='#b4'>Barkley et al., 2018)</ns0:ref>, and the presence of Porites stress bands has correlated with community-level bleaching responses<ns0:ref type='bibr' target='#b3'>(Barkley &amp; Cohen, 2016;</ns0:ref><ns0:ref type='bibr' target='#b41'>Mollica et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b9'>DeCarlo et al., 2020)</ns0:ref>. Thus, that the cores from Abu Shosha generally recorded the known bleaching events in 1998, 2010, and 2015 supports the accuracy of Porites stress bands for representing past bleaching events in this region.Heat stress in the central Red Sea is highly variable among SST datasets. Further, noPeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)Manuscript to be reviewed2015. Finally, CRW has its highest DHW in 1998 and 2010, but does not separate 1982 or 2015 from non-bleaching years.</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head /><ns0:label /><ns0:figDesc>bands in 8 out of 11 cores. I can conclude with 95% confidence that no prior event reached this severity since 1934. Skeletal geochemistry of Abu Shosha Porites was also perturbed during this event, indicative of disruptions to the normal calcification process<ns0:ref type='bibr' target='#b11'>(D'Olivo et al., 2019)</ns0:ref>. The complete absence of stress bands in cores outside of Abu Shosha suggests this event may have been restricted to nearshore environments. 2010: Similar to 1998, coral bleaching was observed directly on nearshore reefs in the central Red Sea in 2010, and this is corroborated by stress bands in 8 out of 11 cores at Abu Shosha. However, unlike 1998, not all SST datasets agree that there was substantial heat stress, with unprecedented DHW in ERSSTv5 and CRW, but relatively low DHW in HadISST and OI-SSTv2. Previous investigations of this bleaching event suggest that it arose from an eddy that constrained warm water near the coast (Pineda et al., 2013), which is only detectable in CRW.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Thus, this event likely rivalled 1998 in severity on Abu Shosha, but probably reached a lesser</ns0:cell></ns0:row><ns0:row><ns0:cell>extent of the Red Sea than previous bleaching events in 1982 and 1998 (Furby, Bouwmeester &amp;</ns0:cell></ns0:row><ns0:row><ns0:cell>Berumen, 2013). Only one core from outside Abu Shosha contained a 2010 stress band,</ns0:cell></ns0:row><ns0:row><ns0:cell>indicating that-like 1998-this event mostly affected nearshore reefs, but there may have been</ns0:cell></ns0:row><ns0:row><ns0:cell>minor effects on other reefs across the shelf.</ns0:cell></ns0:row><ns0:row><ns0:cell>2015: Coral bleaching was again directly observed in 2015, including approximately one</ns0:cell></ns0:row><ns0:row><ns0:cell>third of Porites colonies at Abu Shosha and Qita Al-Kirsh (Monroe et al., 2018), where cores</ns0:cell></ns0:row><ns0:row><ns0:cell>K11 and K12 were collected. However, the coral cores barely registered this event, with only 1</ns0:cell></ns0:row><ns0:row><ns0:cell>out of 11 Abu Shosha cores containing a faint stress band. Although this result is not</ns0:cell></ns0:row><ns0:row><ns0:cell>significantly different from expected if only 1/3 of Porites bleached, it represents a marked</ns0:cell></ns0:row><ns0:row><ns0:cell>difference in the Porites response compared to 1998 and 2010. This suggests that either</ns0:cell></ns0:row><ns0:row><ns0:cell>bleaching was more severe on Abu Shosha in 1998 and 2010 than 2015, or that these colonies</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:note></ns0:figure> <ns0:note place='foot' n='215'>215. DOI: 10.1007/s00338-003-0304-7. Hoegh-Guldberg O, Cai R, Poloczanska E, Brewer P, Sundby S, Helmi K, Fabry V, Jung S. PeerJ reviewing PDF | (2020:07:50935:1:1:NEW 4 Sep 2020)</ns0:note> </ns0:body> "

"Response to reviews (author responses in blue text, page numbers refer to “clean” document) Reviewer 1 Basic reporting The manuscript uses stress bands from massive Porites cores in the central Red Sea, along with climatology data, to identify past bleaching events in the area of the past 100+ years. The study complements more recent in situ observations of coral bleaching from the past ~ 20 years, and despite identifying possible undocumented bleaching events prior to the 1980s, concludes that the frequency and severity of bleaching events has increased in recent years. The manuscript is well-written and I feel is suitable for publication providing some minor comments (highlighted below under ‘general comments’) are addressed – these include some comments that are merely suggestions to be addressed at the author’s discretion. Overall, I think the manuscript is straightforward and will be a solid contribution to the field – I commend the author for their work. Experimental design The overall rational and design of the study are clear and sufficiently detailed. While the number of cores is limited, I recognise the difficulty and environmental impact of collecting a large number of cores. Additionally, the author seems to have used an appropriate statistical approach to account for this and, generally, interprets the results with this limitation in consideration – though there are a one or two sections, detailed below, where I think a more conservative interpretation may be more appropriate. Validity of the findings While I am not familiar with the technical aspects of using stress bands on coral cores to indentify past bleaching events, the author has previously published peer-reviewed work using this approach and cites past studies in support of the methodology. I therefore see little reason to doubt the validity of the approach unless another expert reviewer expresses concern. Comments for the author Line 15: Do you mean 20th century? Yes, thank you for catching that. Lines 31-32: It is my understanding that the term ‘zooxanthellae’ is colloquial and no longer appropriate. I would suggest removing it on line 31 and changing it to ‘endosymbiont photosystem’, or something similar, on the following line. Agreed, thank you. Line 61: ‘a’ hypothesis Corrected. Line 68: There is a paper by Raitsos et al. (2011) in Geophysical Research Letters that reports a considerable increase in temperature in the region since the mid-1990s – it may be relevant to refer to it here or elsewhere in the paper. Yes, the Raitsos et al. (2011) paper is relevant here and has been added to line 73. Line 75: not sure the ‘currently’ is necessary. This has been removed. Line 77-79: I think you should state here that you also analyse and compare long-term climatology datasets that include temperature and wind data - you don’t only use the coral cores to reconstruct the bleaching events. I added “and I compare the presence of stress bands to a variety of ocean temperature and wind datasets” to lines 82-83. However, I do not identify any potential bleaching events based on temperature alone. There are other studies that infer bleaching occurred based solely on temperature, which I think is problematic and I don’t want to suggest that this was done here. Line 84 and throughout: While I understand, and agree with, the benefit of using the active voice, I do think the use of ‘my’ often is not appropriate and could be replaced with ‘the’. Notably, on line 252, you say ‘my bleaching history’ when referring to the bleaching history reconstructed in the study – which I think is incorrect. This is a good point, and instances of awkward active voice have been revised throughout, such as the example mentioned by the reviewer and most instances of the word “my”. Line 86: I would suggest stating the total number of cores collected outside of Abu Shosha. This has been added (there were 11 cores from outside Abu Shosha) (line 90). Line 146: When you say ‘ranged in age’ do you mean that they dated as far back as the years stated? Thank you for point this out, the wording was not entirely clear. This has been revised to “The oldest observable bands in the coral skeletal cores from Abu Shosha…” (line 158). Line 148-150: I think it would be helpful to say how many of the 11 cores did or didn’t have bands here? Just to get an idea of the overall proportion of cores/colonies that did bleach. This a good suggestion, and I added “Only one core (K15) had no stress bands in any year” to clarify (line 163). Same for the non-Abu Shosha cores below (would be good to state many cores were taken in total and how many experienced bleaching). Lines 175-177 have been revised to: “Outside of Abu Shosha, I found only three stress bands among the 11 cores (two of which were in the same core), corresponding to 1948, 1978, and 2010 (Fig. 3).” Line 162: How many cores were these three bands found on? In just two out of 11 cores (this is clarified in the previous comment above). Line 205-206: Did this analysis yield a p-value regarding the significance (or non-significance) of these correlations? Yes, both are significant (p < 0.001). However, I chose to only include the simple r2 correlation statistic because the point is that the correlations are lower than might be expected, and the low correlations highlight the uncertainty of the SST history in this region. That the correlations are significant does not tell anything about the variability in heat stress between products, and thus the difference in heat stress history told depending on the choice of dataset. Line 249: I think this should toned down further considering the meagre evidence/data available - it leaves open the possibility that a bleaching event occurred in this year. There really isn’t any evidence to support the occurrence of a severe bleaching event. This is a good point, and the word “severe” has been deleted here. Line 300: You allude to it somewhat here, but I think a clear statement is missing in the discussion that indicates that the recorded stress bands may have been caused by something other than bleaching (even maybe disease or something else?), which may explain why you found stress bands on one or two colonies in years despite no evidence of high temperature/light or low wind in those years. This is a good suggestion, and I have added a paragraph discussing possible issues with stress bands (lines 268-280): “Porites are generally considered to be relatively resistant to stress (Darling et al., 2012; McClanahan et al., 2020) and have shown evidence of acclimatization to repeated marine heatwaves (DeCarlo et al., 2019), meaning that they are not necessarily representative of entire coral communities. It is also possible that some stress bands could arise from disturbances other than high temperatures, such as disease. Finally, Porites colonies could conceivably miss a bleaching event if calcification completely ceases. Nevertheless, Porites stress bands have captured known bleaching events across the Indo-Pacific (Cantin & Lough, 2014; Barkley & Cohen, 2016; DeCarlo et al., 2017, 2019, 2020; Barkley et al., 2018), and the presence of Porites stress bands has correlated with community-level bleaching responses (Barkley & Cohen, 2016; Mollica et al., 2019; DeCarlo et al., 2020). Thus, that the cores from Abu Shosha generally recorded the known bleaching events in 1998, 2010, and 2015 supports the accuracy of Porites stress bands for representing past bleaching events in this region.” Line 325-327: This really is a personal/stylistic thing, but I don’t personally agree with the approach to this section. I think the author could do without this statement and simply discuss the timeline of bleaching over the last century chronologically without separating it by year. E.g. ‘In 1931, SSTs appear to have…’ This is very much up to the discretion of the author, however. I too would generally prefer a narrative style, however, in this case I think it is best to provide a clear timeline. The first part of the discussion works in narrative form, but makes it more difficult to get just the information for a specific year, which may be the intent of some readers. The timeline makes a clear statement of the SST and stress band knowledge for each year. Line 328: Shouldn’t it be ‘SSTs appear’ rather than ‘SST appears’? There was more than one recording of SST this year, no? Thank you for pointing this out. Yes, there would be multiple measurements, but this is still generally referred to as “SST”. Nevertheless I changed the wording here to “SST may have been anomalously high” Figures: The figure legend for figure 3 could be written more formally – I would suggest something like ‘CT scans of coral skeletal cores collected outside of Abu Shosha. Refer to figure 2 legend for a full description of the figure.’ Revised as suggested, thank you. Reviewer 2 Basic reporting This is a well-written manuscript based on 22 Porites cores drilled out of long lived corals in the central Red Sea. This is a fortune when considering the amount of data recorded in these cores. I was excited and very curious reading the title of the ms and the abstract because the potential is huge. I was a bit disappointed when discovering that the bleaching record of the past century is not so straightforward and that the use of these cores was limited to tracking stress bands rather than supporting it with a stable isotopic work and densitometry. As is, it leaves many open questions and of course, the cores can be used for further analyses. Yet, the ms is informative and important for anyone working in this region. The title is a bit misleading because in fact we learn that beyond recent, observed bleaching events (1998, 2010, 2015) stress bands may not be the best proxy or, maybe there was only a minor, local bleaching event with only a few cores recording stress. so little do we learn about the bleaching events in the last century. proposed title: Can stress bands reliably report bleaching events in the Red Sea? Anyway, I enjoyed reading it. Thank you for the encouragement and enthusiasm. I certainly agree that much more can be done with these cores in the future (they are mostly sitting in a lab basement, by the way, but can be made available to the community). However, CT scanning for stress bands is really the most optimal technique for identifying past bleaching events in multiple cores. Isotope or element ratio measurements may capture bleaching events, and provide estimates of past temperature, but generating long geochemical time series from 22 cores would be an enormous undertaking. I also understand the suggestion for the revised title, but I don’t think it would be quite suitable because the study does not just test if stress bands work, but rather applies them to look further back in time prior to direct human observations. It is true that the data do not show an extensive history of bleaching in the earlier part of the past century, but nevertheless, describing “the past century of bleaching” is the purpose of the study and the goal that is addressed with the data. Experimental design No issues with the sampling procedure and analyses. L148- the author state the number of annual bands counted. Impressive but why is is this important or useful? This is not absolutely essential, but I think it’s best to state it briefly because some researchers may be interested in comparing stress band frequencies between regions (and one would need to know the total number of bands to do this). The Porites species issue: how many/which species were likely included in the study and what is known on the species sensitivity to thermal stress? This is a great question. I don’t want to use the coronavirus pandemic as an excuse, but unfortunately access to the lab prevented identification of the species and I have subsequently changed institution and am separated from the physical cores. However, I added to the manuscript that there are three potential species in this region, and a previous study found that there were no differences in stress band frequencies among species (lines 104-107). Is it possible to present the densitometric profile along the core and linear extension? I find it very interesting and I suppose the data for this exists? To clarify, the density data were collected with computerized tomography (CT), so densities are available for each entire core in 3-D. Subsets of these data are displayed (as images) in Figures 2 and 3. It would be possible to create virtual densitometer profiles by extracting density data along a line down each core. However, I do not think this would be very helpful here. The problem is that where one draws the line can completely change the density profile because of horizontal variations in the skeleton (particularly between dense thecal walls and porous corallite centers). I previously spent a long time attempting to do this effectively on a different set of cores, and I have concluded that 2-dimension images (like Figures 2-3) is the best and most representative way to display the data (these images are indeed density data, just displayed in grayscale across 2 dimensions). Linear extension data would require additional analysis, which is fine, but I also do not think this would add to the present manuscript. The main reason is that linear extension on its own is not a reliable proxy for bleaching (Hoegh-Guldberg et al., 2019; DeCarlo, 2020). Some stress bands are associated with lower linear extension, but others are not. Linear extension would mainly be useful to investigate whether growth rates have changed over the past century, which is really a separate question from bleaching and any extension changes may not be related to temperature. While I do plan to publish the linear extension data separately in a broader-scale compilation of Porites growth rates, I believe those data are too tangential to include in this manuscript. I'm not entirely sure I understood the need in calculating the probability of finding stress bands. maybe elaborate further on this. Thank you for pointing this out. The probability calculations are quite important, so it is good to know that the point of them was not made clear enough. I added the following sentence to lines 111-113 to explain their purpose: “Determining these probabilities enables statistical testing of severity between events (e.g., whether the number of observed stress bands in a given year is statistical different from another year, or from zero).” Good job comparing the different sources of temperature records for the region. Validity of the findings Findings are straightforward. Well presented and analyzed. Comments for the author As mentioned above, I like the study but would have liked to see more analyses to decipher the source of stress (temp, nutrients, light and interactions between these parameters). Thank you. There is an analysis of light, and its possible contribution to bleaching in 1998 in addition to temperature (lines 334-348). Nutrients are much more challenging since there are not gridded, time-resolved nutrient datasets. The potential role of nutrients is mentioned (lines 348-357), but I don’t think a quantitative analysis is possible to do retroactively in this case. Consider looking at cores (images in papers) from other regions in the Red Sea, can you detect some annual bands that might be stress bands? in some cases (Klein et al. 1997) these have also the isotopic signature to support thermal stress. This is a good suggestion. Indeed, both Cantin et al. (2010) and D’Olivo et al. (2019) include images of skeletal cores from this region, and both show evidence of stress in 1998 (lines 331-332). Conversely, Murty et al. (2018) conducted element ratio measurements in Porites across the Red Sea but they do not report any unusual results corresponding to bleaching events. Thank you for pointing out the Klein et al. (1997) paper, which I was previously unaware of. It is very interesting, especially because they have cores from a location that is virtually impossible to work in today. However, they do not seem to suggest any evidence of stress events in their data, and their cores were collected before the only known bleaching event in Eritrea during 1998 (Osman et al., 2018). Porties is considered thermally resilient and as such may be insensitive to high DHW. I think it is worth discussing it. is it possible that under severe stressful conditions, the more sensitive porites colony will miss a band? not calcify/grow at all? if so, maybe some 'missing stress bands' are the result of 0 growth? Both of these are great points, and they are now mentioned in a new paragraph about potential caveats in stress bands (lines 268-280). Regarding the potential for missed stress bands, while I agree it is worth mentioning as a possibility, this seems unlikely. It is true that Porites colonies may temporarily stop growing during bleaching, but they do not transition immediately from normal growth to no growth. Rather they gradually slow their growth, and it is during this time of declining growth that stress bands form (DeCarlo & Cohen, 2017). References Cantin NE, Cohen AL, Karnauskas KB, Tarrant AM, McCorkle DC. 2010. Ocean warming slows coral growth in the central Red Sea. Science 329:322. D’Olivo JP, Georgiou L, Falter J, DeCarlo TM, Irigoien X, Voolstra CR, Roder C, Trotter J, McCulloch MT. 2019. Long‐term impacts of the 1997‐1998 bleaching event on the growth and resilience of massive Porites corals from the central Red Sea. Geochemistry, Geophysics, Geosystems 20:2019GC008312. DOI: 10.1029/2019GC008312. DeCarlo TM. 2020. Commentary: Reconstructing Four Centuries of Temperature-Induced Coral Bleaching on the Great Barrier Reef. Frontiers in Marine Science 7:30. DOI: 10.3389/FMARS.2020.00030. DeCarlo TM, Cohen AL. 2017. Dissepiments, density bands and signatures of thermal stress in Porites skeletons. Coral Reefs 36:749–761. DOI: 10.1007/s00338-017-1566-9. Hoegh-Guldberg O, Skirving WJ, Lough JM, Liu C, Mann ME, Donner S, Eakin CM, Cantin N, Carilli J, Heron SF, Miller S, Dove S. 2019. Commentary: Reconstructing Four Centuries of Temperature-Induced Coral Bleaching on the Great Barrier Reef. Frontiers in Marine Science 6:86. DOI: 10.3389/fmars.2019.00086. Murty SA, Bernstein WN, Ossolinski JE, Davis RS, Goodkin NF, Hughen KA. 2018. Spatial and Temporal Robustness of Sr/Ca‐SST Calibrations in Red Sea Corals: Evidence for Influence of Mean Annual Temperature on Calibration Slopes. Paleoceanography and Paleoclimatology 33:443–456. DOI: 10.1029/2017PA003276. Osman EO, Smith DJ, Ziegler M, Kürten B, Conrad C, El-Haddad KM, Voolstra CR, Suggett DJ. 2018. Thermal refugia against coral bleaching throughout the northern Red Sea. Global Change Biology 24:e474–e484. DOI: 10.1111/gcb.13895. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Astrangia poculata is a temperate scleractinian coral that exists in facultative symbiosis with the dinoflagellate alga Breviolum psygmophilum across a range spanning the Gulf of Mexico to Cape Cod, Massachusetts. Our previous work on metabolic thermal performance of Virginia (VA) and Rhode Island (RI) populations of A. poculata revealed physiological signatures of cold (RI) and warm (VA) adaptation of these populations to their respective local thermal environments. Here, we used whole-transcriptome sequencing (mRNA-Seq) to evaluate genetic differences and identify potential loci involved in the adaptive signature of VA and RI populations. Sequencing data from 40 A. poculata individuals, including 10 colonies from each population and symbiotic state (VA-white, VA-brown, RIwhite, and RI-brown), yielded a total of 1,808 host-associated and 59 algal symbiontassociated single nucleotide polymorphisms (SNPs) post filtration. Fst outlier analysis identified 66 putative high outlier SNPs in the coral host and 4 in the algal symbiont.</ns0:p><ns0:p>Differentiation of VA and RI populations in the coral host was driven by putatively adaptive loci, not neutral divergence (Fst=0.16, p=0.001 and Fst=0.002, p=0.269 for outlier and neutral SNPs respectively). In contrast, we found evidence of neutral population differentiation in B. psygmophilum (Fst=0.093, p=0.001). Several putatively adaptive host loci occur on genes previously associated with the coral stress response. In the symbiont, three of four putatively adaptive loci are associated with photosystem proteins. The opposing pattern of neutral differentiation in B. psygmophilum, but not the A. poculata host, reflects the contrasting dynamics of coral host and algal symbiont population connectivity, dispersal, and gene by environment interactions.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head n='1.'>Introduction</ns0:head><ns0:p>Population connectivity in marine systems is shaped by a complex mixture of factors, including oceanographic currents <ns0:ref type='bibr' target='#b86'>(Selkoe et al. 2008)</ns0:ref>, planktonic larval durations and behavior <ns0:ref type='bibr' target='#b85'>(Selkoe &amp; Toonen 2011)</ns0:ref>, life history dynamics <ns0:ref type='bibr' target='#b17'>(Bradbury et al. 2008)</ns0:ref>, and environmentally driven selection <ns0:ref type='bibr' target='#b66'>(Limborg et al. 2012)</ns0:ref>, among others (reviewed in <ns0:ref type='bibr' target='#b85'>Selkoe &amp; Toonen 2011)</ns0:ref>. The result of these interacting forces can manifest in numerous ways, including wide-ranging panmixia across 1000s of kilometers (e.g. <ns0:ref type='bibr' target='#b26'>Dao et al. 2015)</ns0:ref>, extraordinarily fine-scaled neutral population structure across 10s of meters (e.g. <ns0:ref type='bibr' target='#b3'>Aurelle et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b23'>Costantini et al. 2007;</ns0:ref><ns0:ref type='bibr' target='#b63'>Ledoux et al. 2010)</ns0:ref>, or local adaptation over both small and large spatial scales (e.g. <ns0:ref type='bibr' target='#b10'>Bay &amp; Palumbi 2014;</ns0:ref><ns0:ref type='bibr' target='#b16'>Bradbury et al. 2010)</ns0:ref>. Patterns of population connectivity in marine systems are made only more complex when considering organisms as multi-organism symbiotic communities, or holobionts, and each member of the holobiont can be subject to opposing forces driving population structure.</ns0:p><ns0:p>In scleractinian corals, the holobiont consists of the coral host, algal symbiont (family Symbiodiniaceae; <ns0:ref type='bibr' target='#b58'>LaJeunesse et al. 2018)</ns0:ref>, and associated microbiota <ns0:ref type='bibr' target='#b55'>(Knowlton &amp; Rohwer 2003;</ns0:ref><ns0:ref type='bibr' target='#b82'>Rohwer et al. 2002)</ns0:ref>. While patterns are often complicated by species and location, population structure of the coral host is generally affected by reproductive strategy, with broad scale dispersal usually more common in broadcast spawning species compared to brooding species <ns0:ref type='bibr' target='#b4'>(Ayre &amp; Hughes 2000;</ns0:ref><ns0:ref type='bibr' target='#b19'>Coelho &amp; Lasker 2016)</ns0:ref>. Patterns of differential connectivity of coral hosts and symbionts has also been observed, with coral hosts generally exhibiting connectivity across larger scales compared to their hosted algal symbionts <ns0:ref type='bibr' target='#b9'>(Baums et al. 2014;</ns0:ref><ns0:ref type='bibr' target='#b74'>Pettay &amp; LaJeunesse 2013;</ns0:ref><ns0:ref type='bibr' target='#b75'>Pinzon &amp; LaJeunesse 2011)</ns0:ref>. This difference in dispersal among symbiotic partners could be influenced by distinct life history strategies and resulting dispersal</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed abilities, transmission strategy of symbionts (i.e. horizontal vs. vertical), and/or differential selection pressures <ns0:ref type='bibr' target='#b9'>(Baums et al. 2014</ns0:ref>).</ns0:p><ns0:p>Temperature is one environmental factor that can impose strong selection pressure on natural populations and therefore drive population differentiation <ns0:ref type='bibr' target='#b2'>(Angilletta 2009)</ns0:ref>, and is a common focus in the coral literature. Temperature gradients as drivers of selection and local adaptation have been demonstrated in corals, including Porites astreoides across nearshore and forereef environments on the Florida Keys Reef Tract <ns0:ref type='bibr' target='#b52'>(Kenkel et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b53'>Kenkel &amp; Matz 2016)</ns0:ref> and P. lobata inhabiting tidal pools in American Samoa with differing patterns of thermal variability <ns0:ref type='bibr' target='#b6'>(Barshis et al. 2018;</ns0:ref><ns0:ref type='bibr' target='#b8'>Barshis et al. 2010</ns0:ref>). While we are only beginning to understand these dynamics in tropical corals, comparatively little is known about the forces that shape population structure in temperate scleractinian corals, which exist across vastly wider environmental gradients. However, work in Oculina spp. has demonstrated genetic differentiation of the host did not correlate with Symbiodiniaceae community composition; instead, symbiont diversity and geographical structuring was shaped most strongly by sea surface temperature, particularly within the Mediterranean <ns0:ref type='bibr' target='#b64'>(Leydet &amp; Hellberg 2016)</ns0:ref>. Additionally, work on temperate octocorals in the Mediterranean has demonstrated local adaptation to distinct temperature regimes across depths <ns0:ref type='bibr' target='#b45'>(Haguenauer et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b62'>Ledoux et al. 2015)</ns0:ref> while highlighting genetic drift in limiting such phenotypic differentiation <ns0:ref type='bibr' target='#b24'>(Crisci et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b62'>Ledoux et al. 2015)</ns0:ref>.</ns0:p><ns0:p>Here, we consider patterns of neutral and adaptive differentiation in the northern star coral, Astrangia poculata (= A. danae; <ns0:ref type='bibr' target='#b73'>Peters et al., 1988)</ns0:ref>, and its algal symbiont Breviolum psygmophilum <ns0:ref type='bibr' target='#b59'>(LaJeunesse et al. 2012)</ns0:ref>. Astrangia poculata is facultatively symbiotic, meaning it can exist both with (symbiotic or brown) or without (aposymbiotic or white) B. psygmophilum across its range <ns0:ref type='bibr' target='#b14'>(Boschma 1925)</ns0:ref>. Therefore, the forces shaping host population structure may be decoupled from those shaping the algal symbiont. Our previous work <ns0:ref type='bibr' target='#b1'>(Aichelman et al. 2019)</ns0:ref> demonstrated physiological differentiation between a Virginia (VA) and Rhode Island (RI) population of A. poculata. Namely, the thermal optimum (T opt ) of respiration was elevated in VA corals compared to RI (3.8&#176;C and 6.9&#176;C greater in brown and white corals, respectively), corresponding with warmer in situ temperatures in the more southern population and suggestive of a signature of adaptation of VA and RI corals to their native thermal habitat.</ns0:p><ns0:p>Studies from Narragansett Bay, RI have demonstrated that A. poculata is a gonochoristic broadcast spawner that releases its gametes into the water column between early August and September <ns0:ref type='bibr' target='#b88'>(Szmant-Froelich 1980)</ns0:ref>. A. poculata horizontally transmits its symbionts, and recruits therefore acquire symbionts locally once they have settled in their new environment <ns0:ref type='bibr' target='#b88'>(Szmant-Froelich 1980)</ns0:ref>. Original studies on A. poculata life history observed the development of the planula larval stage 12 to 15 hours after fertilization, but researchers were unable to induce settlement <ns0:ref type='bibr' target='#b88'>(Szmant-Froelich 1980)</ns0:ref>. Achieving larval settlement in the lab remains challenging in this species today; however, larvae have been observed to remain swimming for at least 5 weeks in the lab (D. Wuitchik, personal communication), suggesting an extended pelagic larval duration (PLD).</ns0:p><ns0:p>In the current study, we characterized population structure of the A. poculata host and its symbiont (B. psygmophilum) both by population (VA vs. RI) and by symbiotic state (brown vs.</ns0:p><ns0:p>white) using SNPs derived from high-throughput mRNA-Seq data. Leveraging our previous work on physiological adaptation in these populations, we explore the relative strengths of neutral and adaptive divergence in this broadcast spawning, facultatively symbiotic, and extraordinarily thermally resilient species across the northern half of its range.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='2.'>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>Sample collection</ns0:head><ns0:p>Corals were collected from the same sites and using the same methods as previously described <ns0:ref type='bibr' target='#b1'>(Aichelman et al. 2019)</ns0:ref> Manuscript to be reviewed (i.e. putative genets) were fragmented into three pieces, so that a ramet from each genet was represented in each of the three temperature treatments (cold = 14&#176;C, control = 18&#176;C, and heat = 22&#176;C). Following fragmentation, all corals were allowed to recover at the holding conditions (18&#176;C and 35 ppt) for 20 days before the experiment began. While this experiment was designed to consider differential gene expression in A. poculata across temperatures and populations; here, we present sequencing data from this same experiment and resulting single nucleotide polymorphisms (SNPs) to consider population structure.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Temperature environment of coral populations</ns0:head><ns0:p>To compare long-term temperature trends across the two collection sites, sea surface temperature (SST) data was downloaded from the NOAA 1/4&#176; daily Optimum Interpolation Sea Surface Temperature dataset (OISST, dataset ID=ncdcOisst2Agg_LonPM180; Banzon et al.</ns0:p></ns0:div> <ns0:div><ns0:head>2020</ns0:head><ns0:p>) using the griddap function implemented in R (v3.5.2). Data was downloaded for the years 1982 to 2018 spanning the area 30 to 45&#176; latitude and -80 to -60&#176; longitude. Annual maximum temperature (Figure <ns0:ref type='figure' target='#fig_10'>1</ns0:ref>), annual mean (Figure <ns0:ref type='figure' target='#fig_10'>S1A</ns0:ref>), and annual minimum temperature (Figure <ns0:ref type='figure' target='#fig_10'>S1B</ns0:ref>) of each 1/4&#176; pixel were calculated from this dataset. The OISST temperature data were downloaded, compiled, and plotted with a high-resolution shoreline map layer <ns0:ref type='bibr' target='#b94'>(Wessel &amp; Smith 1996)</ns0:ref> using the method detailed in the GitHub repository associated with this publication.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Aquaria conditions</ns0:head><ns0:p>Similar to <ns0:ref type='bibr' target='#b1'>Aichelman et al. (2019)</ns0:ref>, following collection all experimental corals were maintained in a 325-gallon holding aquarium with artificial seawater mixed using Crystal Sea &#174; Bioassay salt (Marine Enterprises International, Baltimore, MD, USA) and deionized (DI) water.</ns0:p><ns0:p>Temperature was maintained using a temperature controller (AquaLogic, San Diego, CA, USA)</ns0:p><ns0:p>in combination with an in-line water chiller (Delta Star &#174; , AquaLogic, San Diego, CA, USA) and aquarium was equipped with a filter sock for mechanical filtration, protein skimmer for removal of organic material, and powerheads (Tunze &#174; Turbelle, Penzburg, Germany) to maintain flow.</ns0:p><ns0:p>All experimental corals were fed three times a week with freshly hatched Artemia sp. nauplii and maintained under approximately 200 &#956;mol photons m -2 s -1 of light supplied by 165 W LED aquarium lights (GalaxyHydro, Roleadro, Shenzhen, China).</ns0:p><ns0:p>The experiment was run in three separate aquaria, one for each temperature treatment (cold = 14&#176;C, control = 18&#176;C, and heat = 24&#176;C). As in the holding aquarium, artificial seawater was mixed to 35 ppt and each aquarium was equipped with a filter sock and protein skimmer. In the heat and cold aquaria, temperature was manipulated using a custom-programmed Arduino &#174; (code assembled by D. Barshis) connected to the same style heater and chiller as the holding aquarium (sensu <ns0:ref type='bibr' target='#b1'>Aichelman et al. 2019)</ns0:ref>. Temperature in the control experimental aquarium was maintained using a temperature controller as in the holding aquarium (AquaLogic, San Diego, CA, USA).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>Experimental design</ns0:head><ns0:p>At 08:00 on October 12, 2017, all corals were moved from the holding tank to one of the three experimental aquaria, such that each genotype was represented in each temperature treatment. Each experimental aquarium was maintained at conditions identical to the holding tank (salinity = 35 ppt, temperature = 18&#176;C). All corals were given 30 minutes of acclimation in the dark, after which the lights were turned on and a one hour hold at 18&#176;C began. At 09:30, temperature was increased (heat aquarium) and decreased (cold aquarium) at a rate of 4&#176;C hr -1 , and the target temperatures of 22&#176;C (heat) and 14&#176;C (cold) were reached at 10:30. The corals PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed were held at their respective target temperatures for another hour, and the experiment therefore ended at 11:30 (Figure <ns0:ref type='figure' target='#fig_11'>S2</ns0:ref>).</ns0:p><ns0:p>Immediately upon completion of the experiment, tissue samples of approximately 1 cm 2 were taken from each coral fragment and preserved in an RNAlater-like solution <ns0:ref type='bibr' target='#b32'>(De Wit et al. 2012)</ns0:ref>. RNA sampling took place between 11:30 and 13:10, and all fragments were maintained at their respective experimental condition until sampling occurred. The tissue samples were stored in RNALater at -80&#61616;C until RNA extraction.</ns0:p><ns0:p>Temperature was monitored throughout the experiment using Hobo Pendant &#174; Temperature Data Loggers (Onset Computer Corporation, Bourne, MA, USA; Figure <ns0:ref type='figure' target='#fig_11'>S2</ns0:ref>), which</ns0:p><ns0:p>recorded water temperature at one-minute intervals. Temperature loggers were calibrated with a NIST certified glass thermometer. Light levels in each experimental aquarium were maintained at 410 &#956;mol photons m -2 s -1 during the experiment, as measured in the center of each aquaria and supplied by a 165 W LED aquarium light (GalaxyHydro, Roleadro, Shenzhen, China). The light levels used here were based on an estimation of minimum saturating irradiance from our previously published photosynthesis vs. irradiance curve <ns0:ref type='bibr' target='#b1'>(Aichelman et al. 2019)</ns0:ref> as well as previous work by Jacques <ns0:ref type='bibr'>(1983)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>Library preparation and sequencing</ns0:head><ns0:p>RNA was extracted from all coral fragments between November 1 and 13, 2017 using Trizol (Invitrogen, Carlsbad, CA, USA). For each extraction, coral tissue samples were thawed, crushed with a sterile razor blade, combined with Trizol and sterile 0.5 mm zirconia/silica beads (BioSpec Products, Bartlesville, OK, USA) and bead beat on high for 2 minutes to break open cells. Following a 5-minute incubation at room temperature, samples were centrifuged for 10 minutes at 12,000 x g and 4&#61616;C to pellet the skeleton and beads. The supernatant was combined Any libraries that did not successfully amplify after the first attempt were prepped again using the same method listed above, except 25 &#61549;L of un-diluted RNA was used in the Illumina TruSeq mRNA prep kit. The 96 libraries were sequenced on 6 lanes of an Illumina HiSeq4000 (16 libraries per lane) at the University of California Berkeley Vincent J. Coates Genomics Sequencing Laboratory, which yielded single-end 50 base pair (bp) reads. All RNA sequences have been deposited in NCBI BioProject under accession number PRJNA614998.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>Processing sequences and transcriptome assembly</ns0:head><ns0:p>Detailed descriptions for all data analyses can be found on the electronic notebook associated with this publication (github.com/hannahaichelman/Astrangia_PopGen). Raw sequences were processed using the adapter trimming/quality filtering functions of the Fastx-Toolkit to remove adapter sequence contamination and reads with a quality score less than 33.</ns0:p><ns0:p>All sequences were then used as input for de novo transcriptome assembly using Trinity (version 2.0.6; <ns0:ref type='bibr' target='#b42'>Grabherr et al. 2011</ns0:ref>) and default parameters. Ribosomal RNA (rRNA) contamination of the reference was identified using nucleotide blast (blastn) against the Silva large subunit (LSU)</ns0:p><ns0:p>and small subunit (SSU) databases (http://www.arb-silva.de/). 'Good hits' to these rRNA databases were defined as matching at least 78% of the read over at least 100 bp, and once identified were removed from the reference assembly. A total of 1,273 matches to the LSU database and 688 matches to the SSU database were removed from the reference assembly.</ns0:p><ns0:p>Once rRNA contamination was removed from the reference assembly, it was filtered to include only sequences greater than 500 bp in length. Host and symbiont contigs in the reference assembly were differentiated and assigned as described previously <ns0:ref type='bibr' target='#b7'>(Barshis et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b29'>Davies et al. 2016;</ns0:ref><ns0:ref type='bibr'>Ladner &amp; Palumbi 2012)</ns0:ref>. Briefly, the reference assembly was blasted (using blastn) against four databases: 1) all available cnidarian data ('dirty coral'; n = 10 datasets), 2) all available Symbiodiniaceae data ('dirty sym'; n = 8 datasets), 3) aposymbiotic cnidarian data only ('clean coral'; n = 15 datasets), and 4) cultured Symbiodiniaceae data only ('clean sym'; n = 9 datasets). These four databases contained the same sequencing data used by Davies et al.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed (2016), plus an additional 16 datasets (summarized in Table <ns0:ref type='table'>S1</ns0:ref>). A contig was considered a host contig if it had a length overlap greater than 100 bp with a 60% identity cutoff to any cnidarian.</ns0:p><ns0:p>If the same contig was also assigned to a cultured (clean) symbiont read with the same length and cutoff identity, it was removed from the host contig list. Similarly, a contig was considered a symbiont contig if it had a length overlap greater than 100 bp with a 60% identity cutoff to any symbiont, and removed if it also assigned to a clean coral reference. Contigs identified as both coral and symbiont were also removed from the reference. Once contigs were designated as host or symbiont, the resulting Trinity-assembled reference was annotated by BLAST sequence homology searches against GenBank's nr protein database <ns0:ref type='bibr' target='#b22'>(Coordinators 2018</ns0:ref>) and UniProt's Swiss-Prot and TrEMBL databases <ns0:ref type='bibr' target='#b21'>(Consortium 2018)</ns0:ref> to create a consensus annotation using an e-value cutoff of 1e -4 using a custom annotation script <ns0:ref type='bibr' target='#b32'>(De Wit et al. 2012</ns0:ref>). Annotated sequences were then assigned to Gene Ontology (GO) categories <ns0:ref type='bibr' target='#b21'>(Consortium 2018)</ns0:ref>. Reference transcriptome size and contiguity was assessed using a custom python script (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>SNP calling and clone identification</ns0:head><ns0:p>To maximize the total reads per genotype for the population genetic analyses presented here, fastq files were combined by genotype. This reduced 84 libraries (7 genotypes x 4 populations x 3 temperature treatments) to 28 fastq files. These concatenated files, along with the 12 libraries originally intended for population genetic analyses, yielded a total of 40 libraries that were used for all downstream analyses. It should be noted that the dataset presented here had relatively low read counts, resulting from an error in the library preparation that led to sequencing of rRNA in addition to mRNA. The primary result of this error was a larger than usual percentage of sequence yield going to rRNA, which resulted in a lower read count on an</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed individual basis. To combat this, we have used conservative cut-off values at every step of the data analysis pipeline to address these issues and account for missing data.</ns0:p><ns0:p>The quality filtered reads were mapped to the de novo holobiont transcriptome using the 'very-sensitive' method of Bowtie2.2.4 <ns0:ref type='bibr' target='#b61'>(Langmead &amp; Salzberg 2012)</ns0:ref>. Single nucleotide polymorphisms (SNPs) were detected from the mapped reads using freebayes <ns0:ref type='bibr' target='#b40'>(Garrison &amp; Marth 2012)</ns0:ref>. The resulting unfiltered variant call file (vcf) was separated into 'good coral SNPs' and 'good symbiont SNPs' using the lists of coral and symbiont contigs in the reference transcriptome. These coral and symbiont vcf files were then separately filtered using vcftools (v0.1.12b) and utilizing scripts from the dDocent/2.24 pipeline <ns0:ref type='bibr' target='#b78'>(Puritz et al. 2014a;</ns0:ref><ns0:ref type='bibr' target='#b79'>Puritz et al. 2014b</ns0:ref>) to create a rigorously filtered set of variant sites. The filtering parameters were the same for the host and symbiont SNPs, and each file was filtered in four steps. First, vcftools was used to filter files to exclude individuals with more than 50% missing data, exclude sites with minor allele count (mac) greater than or equal to 3, only include sites with a quality score above 30, exclude genotypes with fewer than 5 reads, include only bi-allelic sites, and remove indels.</ns0:p><ns0:p>Second, the filter_missing_ind.sh script from dDocent was used to remove individuals with more than 85% missing data. Third, another round of vcftools filtering was conducted to exclude sites if they had more than 75% missing data, include sites with a minor allele frequency (maf) greater than or equal to 0.05, and include sites with mean depth values (across all included individuals) greater than or equal to 10. After these filters were executed, the fourth filtering step used the were determined to be clones using this method, and one was randomly removed for all downstream analyses (Figure <ns0:ref type='figure' target='#fig_12'>S3</ns0:ref>). To ensure that the clone identification was robust to other measures of genetic distance, this method was repeated with Prevosti distance <ns0:ref type='bibr' target='#b77'>(Prevosti et al. 1975</ns0:ref>) and Manhattan distance (using the vegdist function in the package vegan v2.4-2; Oksanen et al. 2011), and the same pair of clones was detected each time.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.8'>Outlier detection</ns0:head><ns0:p>Neutral and outlier SNPs were detected using BayPass3.04 <ns0:ref type='bibr' target='#b41'>(Gautier 2015)</ns0:ref> Manuscript to be reviewed create a neutral and a high outlier list of SNPs, and these two sets were analyzed separately for all downstream analyses. Total numbers of neutral and outlier SNPs are summarized in Table <ns0:ref type='table'>2</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.9'>Population structure and genetic diversity analyses</ns0:head><ns0:p>Following BayPass outlier detection, the coral and symbiont vcf files were each filtered to create separate files for neutral and high outlier SNPs. These separate vcf files were then randomly filtered to include only one SNP per contig using the Filter_one_random_snp_per_contig.sh script from the dDocent pipeline <ns0:ref type='bibr' target='#b78'>(Puritz et al. 2014a;</ns0:ref><ns0:ref type='bibr' target='#b79'>Puritz et al. 2014b</ns0:ref>). This was done to avoid potential bias of analyses due to non-independence of SNPs on the same contig. All analyses besides BayPass outlier detection used files that were first separated by neutral and outlier SNPs and then filtered to include only one SNP per contig.</ns0:p><ns0:p>Pairwise differentiation (Fst) calculations were conducted in GenoDive v3.04 <ns0:ref type='bibr' target='#b70'>(Meirmans &amp; Van Tienderen 2004)</ns0:ref> using the AMOVA Fs method and tested with 999 permutations.</ns0:p><ns0:p>AMOVA analyses were conducted in GenoDive using the infinite allele model (Fs-analog), a structure of allele nested within individual nested within population, and tested with 999 permutations. Measures of genetic diversity per population, including observed heterozygosity (Ho) and heterozygosity within subpopulations (i.e. expected heterozygosity; Hs) were calculated in GenoDive using default settings. To visualize population differentiation, Principal</ns0:p><ns0:p>Component Analysis (PCA) was conducted using the R (v3.5.2) package Adegenet (R Core Team 2017). STRUCTURE (v2.6), with a 100,000 burn-in period and 500,000 MCMC runs after burnin, was used to determine the number of distinct genetic groups in the coral host <ns0:ref type='bibr' target='#b38'>(Falush et al. 2007</ns0:ref>). The optimal number of genetic clusters (K) was assessed using the DeltaK method</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed <ns0:ref type='bibr' target='#b37'>(Evanno et al. 2005)</ns0:ref>, which was computed via the online program StructureSelector <ns0:ref type='bibr' target='#b65'>(Li &amp; Liu 2018)</ns0:ref> and plotted (Figure <ns0:ref type='figure'>S4</ns0:ref>) using the online program Clumpak <ns0:ref type='bibr' target='#b56'>(Kopelman et al. 2015)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.10'>Gene Ontology (GO) enrichment of outlier SNPs</ns0:head><ns0:p>A gene ontology (GO) Enrichment Analysis was conducted to determine if genes containing outlier SNPs were enriched for any particular GO categories. Each gene in the reference transcriptome received a binary indicator of whether it contained an outlier SNP or not, and a GO enrichment analysis based on Fisher's exact test was used to determine if these outlier SNPs were enriched for any GO categories. Results were plotted as a dendrogram (Figure <ns0:ref type='figure'>S5</ns0:ref>), which indicates gene sharing between GO categories and lists the number of genes in the module over the total number of genes assigned to each category in the entire SNP dataset (e.g. <ns0:ref type='bibr' target='#b29'>Davies et al. 2016;</ns0:ref><ns0:ref type='bibr' target='#b35'>Dixon et al. 2015)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.'>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>Mapping and SNP numbers</ns0:head><ns0:p>The total counts of A. poculata mapped reads/genet ranged from 9,340,966 to 167,484,549, and mapping efficiencies ranged from 45.96% to 54.10% (Table <ns0:ref type='table'>3</ns0:ref>). The unfiltered vcf file had a total of 1,214,003 variants, 432,676 of which were on host contigs and 16,417 of which were on symbiont contigs. After all filters were applied, there were a total of 1,808 coral SNPs, and 59 symbiont SNPs (2 populations including brown individuals only; Table <ns0:ref type='table'>2</ns0:ref>). After </ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>Significant neutral population structure in symbiont, but not host</ns0:head><ns0:p>For the coral host analysis, BayPass analyses identified 1,637 neutral and 84 high outlier SNPs, and further filtering for one SNP per contig left 279 neutral loci and 66 high outlier loci that were used in population differentiation analyses (Table <ns0:ref type='table'>2</ns0:ref>). Analysis of Molecular Variance (AMOVA) tests revealed no significant population structure at neutral loci (Fst = 0.002, AMOVA p = 0.269); however, there was significant population structure at high outlier loci (Fst = 0.16, AMOVA p = 0.001; Table <ns0:ref type='table' target='#tab_2'>4</ns0:ref>). Pairwise differentiation between the four populations reflects a similar pattern, with no significant population structure at neutral loci for most pairwise comparisons (Fst ranges between -0.007 to 0.012, all p &gt; 0.159; Table <ns0:ref type='table' target='#tab_2'>4</ns0:ref>) except between VA-B and RI-W (Fst = 0.012, p = 0.026). At high outlier loci, all pairwise Fst values were significant (Fst ranges between 0.079 to 0.213, all p &lt; 0.01; Table <ns0:ref type='table' target='#tab_2'>4</ns0:ref>). Principal components analysis (PCA)</ns0:p><ns0:p>further demonstrates that all four populations overlap at neutral loci (Figure <ns0:ref type='figure' target='#fig_11'>2A</ns0:ref>) but separate primarily by origin when including only putatively adaptive loci (Figure <ns0:ref type='figure' target='#fig_11'>2B</ns0:ref>).</ns0:p><ns0:p>For the symbiont analysis, BayPass analyses identified 52 neutral and 4 high outlier SNPs, and further filtering for one SNP per contig left 20 neutral loci and 4 high outlier loci that were used in population differentiation analyses (Table <ns0:ref type='table'>2</ns0:ref>). In contrast to the coral host population differentiation, symbiont SNPs showed significant population structure at neutral loci (Fst = 0.093, AMOVA p = 0.001; Figure <ns0:ref type='figure' target='#fig_12'>3</ns0:ref>). At the four high outlier symbiont SNPs identified, there was also significant differentiation (Fst = 0.965, AMOVA p = 0.001).</ns0:p><ns0:p>The coral host Fst results are reflected in the STRUCTURE analysis, with a pattern of admixture in all samples at neutral loci in the coral host, but two distinct clusters separating VA and RI individuals at high outlier loci (Figure <ns0:ref type='figure'>S4</ns0:ref>). The optimal K value for both neutral and outlier loci in the coral host was two.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>Genetic diversity</ns0:head><ns0:p>For the coral host analysis, at neutral loci there were no clear patterns for one population having higher observed (Ho) or expected (Hs) heterozygosity than another, with Ho ranging between 0.217 (RI-B) to 0.283 (RI-W) and Hs ranging between 0.224 (RI-B) and 0.267 (VA-W) (Table <ns0:ref type='table'>S2</ns0:ref>). At high outlier loci for the coral host, Ho and Hs was lower in VA populations (Ho:</ns0:p><ns0:p>VA-B = 0.121, VA-W = 0.097; Hs: VA-B = 0.168, VA-W = 0.171), than in RI (Ho: RI-B = 0.191, RI-W = 0.292; Hs: RI-B = 0.324, RI-W = 0.283; Table <ns0:ref type='table'>S2</ns0:ref>). For the neutral symbiont loci, Ho and Hs were higher in the VA-B population (0.575 and 0.385, respectively) than in the RI-B population (0.47 and 0.338, respectively). For the four high outlier symbiont SNPs, Ho and Hs were both 0.0 in VA-B population, and in the RI-B population Ho = 0.050 and Hs = 0.047 (Table <ns0:ref type='table'>S2</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head n='3.4'>Outlier SNP identities</ns0:head><ns0:p>Coral host contigs that contained more than one high outlier SNP (n = 13) were manually inspected to look for agreement with previous studies on coral adaptation to distinct temperature environments (Table <ns0:ref type='table'>S3</ns0:ref>). Some of these genes have been previously observed in coral transcriptomic studies in response to thermal stress, including 40S and 60S ribosomal proteins <ns0:ref type='bibr' target='#b33'>(DeSalvo et al. 2010;</ns0:ref><ns0:ref type='bibr' target='#b76'>Portune et al. 2010)</ns0:ref>, myosin heavy chain <ns0:ref type='bibr' target='#b96'>(Woo et al. 2010)</ns0:ref>, and ubiquitinlike protein FUBI <ns0:ref type='bibr' target='#b8'>(Barshis et al. 2010</ns0:ref>). Additionally, one gene (apolipoprotein B-100) was previously implicated in playing a role in the coral symbiosis <ns0:ref type='bibr' target='#b12'>(Bertucci et al. 2015)</ns0:ref>. Two other genes were highlighted in previous transcriptomic studies in corals, including the putative immune gene cyclic AMP-dependent transcription factor ATF-5 <ns0:ref type='bibr' target='#b39'>(Fuess et al. 2016</ns0:ref>) and two collagen chain proteins implicated in calcification and/or modified cell adhesion (DeSalvo et al.</ns0:p></ns0:div> <ns0:div><ns0:head>2010).</ns0:head><ns0:p>There were four high outlier SNPs in symbiont reads, three of which were annotated.</ns0:p><ns0:p>These SNPs are on genes annotated as photosystem II (PSII) CP43 reaction center protein, photosystem I (PSI) P700 chlorophyll a apoprotein A2, and PSII protein D1. A full summary of these contigs with multiple high outlier SNPs can be found in Table <ns0:ref type='table'>S3</ns0:ref>.</ns0:p><ns0:p>When analyzing the data as two populations separately for VA and RI to look for consistent high outlier SNPs that could be driving differentiation between brown and white morphs, 11 high outlier SNPs were identified as shared between VA and RI (Table <ns0:ref type='table'>S3</ns0:ref>), which independently had 49 and 47 high outlier SNPs, respectively. These shared high outlier SNPs include several previously mentioned genes (40S and 60S ribosomal proteins, cyclic AMPdependent transcription factor ATF-5, and a collagen chain protein), as well as Sequestosome-1, which is implicated in autophagy and immune system process (UniProtKB entry 008623;</ns0:p><ns0:p>Consortium 2018).</ns0:p></ns0:div> <ns0:div><ns0:head n='3.5'>High Outlier SNPs enriched for ribosome-associated GO Categories</ns0:head><ns0:p>Gene Ontology enrichment analyses showed that the coral host outlier SNPs detected in this study were enriched for 10 GO terms in the 'molecular function' category and 7 GO terms in the 'cellular components' category. The significant cellular components terms consisted of several ribosome-associated terms, including large ribosomal subunit, small ribosomal subunit, ribosome, and ribosomal subunit. The significant molecular function terms consisted of several ribosome-associated terms, including structural constituent of ribosome and rRNA binding, as well as several terms related to coral stress response, including ferric iron binding and oxidoreductase (Figure <ns0:ref type='figure'>S5</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head n='4.'>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head n='4.1'>Opposing patterns of differentiation in Astrangia poculata hosts and symbionts</ns0:head><ns0:p>Here, we find evidence of contrasting patterns of population structure between members of the holobiont in the temperate scleractinian coral Astrangia poculata. Between Virginia and Rhode Island, the coral host exhibited neutral panmixia, but adaptive divergence. While there was no significant population differentiation at putatively neutral loci in the host, there was evidence of neutral divergence in the algal symbiont. Astrangia poculata is a gonochoric broadcast spawning species that horizontally transmits its symbionts, a life history strategy that likely lends to the contrasting patterns of genetic differentiation in the host and symbiont observed here. Marine broadcast spawning species have extended pelagic larval durations (PLDs) of up to 244 days <ns0:ref type='bibr' target='#b43'>(Graham et al. 2008)</ns0:ref>, facilitating long-range dispersal and genetic connectivity <ns0:ref type='bibr' target='#b4'>(Ayre &amp; Hughes 2000;</ns0:ref><ns0:ref type='bibr' target='#b31'>Davies et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b71'>Nishikawa et al. 2003)</ns0:ref>. Combined with observations of A. poculata larvae swimming 5 weeks post-release in the lab (D. Wuitchik, personal communication), it is not unreasonable to expect that A. poculata larvae can remain in the water column for extended periods of time, facilitating larval connectivity across VA and RI.</ns0:p><ns0:p>Previous work in corals has demonstrated population connectivity across great distances.</ns0:p><ns0:p>For example, high genetic connectivity was found across 4,000 km in Micronesia for two acroporid corals <ns0:ref type='bibr' target='#b27'>(Davies et al. 2015)</ns0:ref>. In the Caribbean, models predict that the extended PLD Manuscript to be reviewed Symbiodiniaceae in comparison to the coral host is a commonly observed pattern. This suggests distinct micro-evolutionary processes (e.g. lower effective dispersal in the symbiont or stronger drift of symbiont genotypes within coral colonies) affect each symbiotic partner <ns0:ref type='bibr' target='#b9'>(Baums et al. 2014</ns0:ref>). Interestingly, our data confirm that pattern in a temperate coral species that is only facultatively associated with algal symbionts, thus the factors limiting dispersal of Symbiodiniaceae appear unrelated to the degree of host fidelity in the symbiosis.</ns0:p></ns0:div> <ns0:div><ns0:head n='4.2'>Physical patterns of water masses could contribute to the connectivity of A. poculata hosts</ns0:head><ns0:p>Population structure of organisms whose range spans the east coast of the United States is influenced by the physical properties of the ocean, where the warm waters of the Gulf Stream current meet the cooler, less-saline Labrador Current to create one of the steepest gradients in latitudinal temperature change in the world <ns0:ref type='bibr' target='#b15'>(Bower et al. 1985;</ns0:ref><ns0:ref type='bibr' target='#b20'>Conover et al. 2006;</ns0:ref><ns0:ref type='bibr' target='#b92'>Wares 2002)</ns0:ref>. Along this latitudinal gradient, Cape Hatteras and Cape Cod are sites of particularly stark environmental transitions <ns0:ref type='bibr' target='#b92'>(Wares 2002)</ns0:ref>. Cape Hatteras separates warmer waters in the south (the Carolinian Province) from more temperate and seasonally fluctuating waters to the north (Virginian Province; <ns0:ref type='bibr' target='#b67'>Mach et al. 2011)</ns0:ref>, while Cape Cod separates the Virginian Province from the consistently cooler waters of the Acadian Province <ns0:ref type='bibr' target='#b18'>(Briggs 1974;</ns0:ref><ns0:ref type='bibr' target='#b36'>Engle &amp; Summers 1999;</ns0:ref><ns0:ref type='bibr' target='#b67'>Mach et al. 2011)</ns0:ref>. Cape Cod also represents the upper range limit of A. poculata <ns0:ref type='bibr' target='#b73'>(Peters et al. 1988;</ns0:ref><ns0:ref type='bibr' target='#b89'>Thornhill et al. 2008)</ns0:ref>, where it is likely restricted by the colder waters to the north <ns0:ref type='bibr' target='#b34'>(Dimond et al. 2012)</ns0:ref>. Both VA and RI populations considered here lie within the Virginian Province and therefore between these stark environmental breaks (Figure <ns0:ref type='figure' target='#fig_10'>1</ns0:ref>). This likely facilitates dispersal of A. poculata larvae along the coast between sites, where they might</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed otherwise be prevented from dispersing by the Gulf Stream to the south or around Cape Cod to the north. These biogeographical provinces of the northwest Atlantic influence population structure not just of A. poculata, but of a diverse collection of organisms. For example, using RAD-seq <ns0:ref type='bibr' target='#b13'>Boehm et al. (2015)</ns0:ref> found two populations of the lined seahorse (Hippocampus erectus) within the Virginian Province to be connected and from an ancestral gene pool that diverged from populations south of Cape Hatteras in the Carolinian and Caribbean provinces. In contrast to panmixia within the Virginian Province, as we also observed in the A. poculata host, Zhang et al. Manuscript to be reviewed larval phase, likely contribute to the observed pattern <ns0:ref type='bibr' target='#b87'>(Strasser &amp; Barber 2009)</ns0:ref>. For these studies mentioned above, it is possible that differences in the genetic markers used to look for population structure also influenced the ability to detect differences (D'Aloia et al. 2020). In any case, this body of work highlights that oceanographic currents, planktonic larval durations and behavior, life history dynamics, and the environment are all important to consider when evaluating population structure in the sea.</ns0:p></ns0:div> <ns0:div><ns0:head n='4.3'>Temperature as a potential driver of adaptive population differentiation</ns0:head><ns0:p>Although there are no severe environmental breaks between VA and RI, as both sites lie within the Virginian Province, we have previously shown that there are indeed differences in the temperature environments at our collection sites, including warmer summers in VA and colder winters in RI <ns0:ref type='bibr' target='#b1'>(Aichelman et al. 2019)</ns0:ref>. These temperature differences are not restricted to the time frame of this study, but are consistent over the last ~40 years of SST data (Figure <ns0:ref type='figure' target='#fig_10'>1</ns0:ref>). These environmental differences could drive the subtle adaptive divergence we found in the A. poculata host as well as the B. psygmophilum symbiont. There is a large body of evidence demonstrating that differences in temperature contribute to adaptive population differentiation in marine organisms across a variety of spatial scales (reviewed in Sanford &amp; Kelly 2011). For example, <ns0:ref type='bibr' target='#b69'>Matz et al. (2018)</ns0:ref> found population differentiation of A. millepora on the Great Barrier Reef across over 1,200 km was associated with temperature. In a model simulation, this work showed that even high migration rates did not interfere with patterns of local thermal adaptation, and that the metapopulation could be able to adapt to predicted warming over the next 100 to 250 years <ns0:ref type='bibr' target='#b69'>(Matz et al. 2018)</ns0:ref>. Additionally, <ns0:ref type='bibr' target='#b45'>Haguenauer et al. (2013)</ns0:ref> Manuscript to be reviewed history. Namely, shallow-water corals that historically experienced warmer temperatures more strongly induced expression of HSP70 upon heat stress, and microsatellite loci showed that corals from the three depths were genetically differentiated across this steep environmental gradient <ns0:ref type='bibr' target='#b45'>(Haguenauer et al. 2013)</ns0:ref>.</ns0:p><ns0:p>Gradients in environmental parameters such as temperature also play an important role in </ns0:p></ns0:div> <ns0:div><ns0:head n='4.4'>Outlier SNPs related to coral stress response and energetics</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>It is important to distinguish between neutral and adaptive loci when considering population divergence. Namely, loci can still be under selection even in the face of extensive gene flow, and therefore populations can appear homogeneous at neutral loci but still exhibit local adaptation <ns0:ref type='bibr' target='#b20'>(Conover et al. 2006)</ns0:ref>. Adaptive (as opposed to neutral) genetic variation affects an organism's fitness <ns0:ref type='bibr' target='#b20'>(Conover et al. 2006</ns0:ref>). Here, we find evidence of A. poculata host connectivity at neutral loci despite evidence for adaptive divergence at several high outlier sites. Several of the putatively adaptive SNPs found here occur on genes that have been previously associated with the coral stress response. For example, two putatively adaptive SNPs were each found on genes annotated as 40S ribosomal protein S3 and 60S ribosomal protein L26.</ns0:p><ns0:p>Both 40S and 60S ribosomal proteins were shown to be downregulated in Acropora palmata after two days of thermal stress (~32&#176;C; <ns0:ref type='bibr' target='#b33'>DeSalvo et al. 2010)</ns0:ref>. Additionally, another four putatively adaptive SNPs were found on the gene annotated as myosin heavy chain. Myosin heavy chain is associated with the cytoskeleton and was previously reported to be upregulated after 24 hours of thermal stress (28&#176;C) in the octocoral Scleronephthya gracillimum <ns0:ref type='bibr' target='#b96'>(Woo et al. 2010)</ns0:ref>. Two more putatively adaptive SNPs were located on the gene annotated as ubiquitin-like protein FUBI. Ubiquitin binds to damaged proteins and marks them for degradation and reuse, and ubiquinated proteins are therefore thought to be a key marker for the physiological stress response <ns0:ref type='bibr' target='#b93'>(Weis 2010)</ns0:ref>. <ns0:ref type='bibr' target='#b8'>Barshis et al. (2010)</ns0:ref> found that ubiquitin-conjugated proteins were constitutively higher in a more thermally tolerant back reef population of Porites lobata in American Samoa. Lastly, although not related to coral response to thermal stress, two putatively adaptive SNPs were found on a gene annotated as apolipoprotein B-100, which Bertucci et al. Additionally, as there appears to be some differentiation between white and brown corals based on the PCA analysis (Figure <ns0:ref type='figure' target='#fig_11'>2B</ns0:ref>) and within population pairwise Fst calculations, it is tempting to speculate that there are factors driving genetic divergence between symbiotic states.</ns0:p><ns0:p>By considering each population separately and looking for consistent outlier SNP identities, we do not find compelling evidence to support this hypothesis as only 11 out of 49 (for VA) and 47</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed (for RI) outlier SNPs were shared between the two groups. Thus, we find it less parsimonious that each population has uniquely evolved genetic differentiation between symbiotic states, as we imagine a high degree of conservation/shared evolutionary history in this trait. However, there is one interesting high outlier SNP in both VA and RI, annotated as Sequestosome-1, that could potentially be related to differentiation between symbiotic state. For both the coral host and symbiont outlier loci, it is important to acknowledge the possibility that some of the SNPs we discuss above are false positives, and not true signatures of local adaptation. Additionally, it will be important to conduct deeper sequencing and analyze additional loci across multiple populations to have more confidence in the outlier loci driving differentiation across the range of A. poculata.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.'>Conclusions</ns0:head><ns0:p>Here, we found contrasting levels of genetic connectivity in the different partners of the Astrangia poculata holobiont, with neutral gene flow and adaptive divergence in the coral host </ns0:p></ns0:div> <ns0:div><ns0:head n='6.'>Acknowledgements</ns0:head><ns0:p>We extend appreciation to K. Sharp, R. Rotjan, S. Grace and the annual Astrangia Workshop hosted by Roger Williams University for fostering creative conversations and collaborations sites is approximately 630 km. Biogeographic province designations are from <ns0:ref type='bibr' target='#b18'>Briggs (1974)</ns0:ref> and <ns0:ref type='bibr'>Engle and Summers (2001)</ns0:ref>. Manuscript to be reviewed Pairwise differentiation (Fst) results from Genodive for the Astrangia poculata host.</ns0:p><ns0:p>Virginia = VA and Rhode Island = RI, B = symbiotic host, W = aposymbiotic host. The first number reported is the Fst value and the number following in parentheses is the p-value (significance was tested using 999 permutations in Genodive). Significant pairwise differentiation results are bolded. In each box, the results on the top are for putatively neutral loci, and the results underneath are for high outlier loci.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)Manuscript to be reviewed with 200 &#956;l of chloroform and mixed for 15 seconds. Following another 5-minute incubation, samples were spun for 15 minutes at 12,000 x g and 4&#61616;C, and the chloroform cleaning step was repeated. After the last centrifugation step, the supernatant was combined with an equal volume of 95% ethanol and all samples were immediately purified using a Direct-zol RNA MiniPrep Plus purification kit (Zymo Research, Irvine, CA, USA) according to manufacturer's instructions. The purified RNA was eluted in 50 &#61549;L of DNase/RNase-free water and immediately stored at -80&#61616;C for future library preparation. The concentration of all RNA extractions was assessed using a Qubit 2.0 Fluorometer (Invitrogen by Life Technologies) and diluted to 0.1-1 &#956;g total RNA before mRNA-Seq library preparation.Libraries (N = 96) were prepped using the Illumina TruSeq mRNA prep kit (San Diego, CA, USA) and half-sized reaction volumes. The 96 libraries consisted of 7 genotypes per population (RI-brown, RI-white, VA-brown, VA-white), with each genotype represented across all temperature treatments (7 genotypes x 4 populations x 3 temperature treatments = 84 libraries). These 84 libraries were intended for use in differential gene expression analysis. An additional 12 libraries, intended to increase the sample size for SNP analyses, were prepared from 3 additional genotypes per population (3 genotypes x 4 populations = 12 libraries), all of which were in the 18&#176;C control treatment.The quality and quantity of all mRNA-Seq libraries was assessed using both a fragment analyzer (DNF-910 dsDNA Reagent Kit, Advanced Analytical) and KAPA Library Quantification Kit for Illumina platforms (Roche Sequencing Solutions, Pleasanton, CA, USA).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>filter_hwe_by_pop.pl script from dDocent to remove sites out of Hardy-Weinberg equilibrium within each population (minimum Hardy-Weinberg p-value cutoff for SNPs = 0.01). This fourth filter resulted in no SNPs being removed from the symbiont file, but 11 SNPs being removed from the coral file. The filtered vcf files were converted to genepop format using a custom PeerJ reviewingPDF | (2020:04:47962:1:1:NEW 28 Aug 2020)Manuscript to be reviewed python script (written by D. Barshis). The coral host analysis was conducted considering the data as four populations (VA-B, VA-W, RI-B, and RI-W). The symbiont data only included brown hosts and was therefore analyzed as two populations (VA-B and RI-B). Additionally, to look for consistent loci driving patterns of differentiation between brown and white phenotypes within VA and RI, the coral host analysis was also conducted as two populations for each origin separately (VA-B and VA-W separately from RI-B and RI-W).Potential clones in the coral host data were assessed using the R package poppr (v2.8.5)<ns0:ref type='bibr' target='#b50'>(Kamvar et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b51'>Kamvar et al. 2014</ns0:ref>). The filtered vcf file was imported into R and converted into the genind format. Then, the diss.dist function was used to calculate a distance matrix based on relative dissimilarity (i.e. Hamming's distance;<ns0:ref type='bibr' target='#b46'>Hamming 1950;</ns0:ref><ns0:ref type='bibr' target='#b91'>Wang et al. 2015)</ns0:ref>, or the number of allelic differences between two individuals. The distance matrix was clustered with hclust and a dendrogram was plotted to identify clones. Two RI-B individuals</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>under the core model. Outlier SNPs under the core model were determined based on the XtX statistic (introduced by G&#252;nther &amp; Coop 2013), which is a SNP-specific Fst corrected for the scaled covariance of population allele frequencies (Gautier 2015). Outlier SNPs were defined as having XtX &gt; 0.5% FDR from a simulated dataset. The results of the BayPass analysis were used to PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>removing individuals with a high percentage of missing data from the coral vcf file (n = 2 RI-B, n = 2 RI-W, n = 1 VA-B) as well as removing one putative clone (RI-B), a total of 34 individuals remained in the coral analysis (n = 7 RI-B, n = 8 RI-W, n = 9 VA-B, n = 10 VA-W). For the symbiont analysis, two individuals with a high percentage of missing data (n = 2 VA-B) were PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020) Manuscript to be reviewed removed, leaving 38 individuals in the symbiont analysis (n = 10 RI-B, n = 10 RI-W, n = 8 VA-B, n = 10 VA-W).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>( 20 -</ns0:head><ns0:label>20</ns0:label><ns0:figDesc>120 days) of Orbicella franksi enables export of larvae from the Flower Garden Banks to more distant Caribbean reefs, including Broward and Palm Beach, Florida approximately 1,500 km away<ns0:ref type='bibr' target='#b31'>(Davies et al. 2017)</ns0:ref>. Additionally, across 10 Caribbean populations (bounded by Barbados in the east, Belize in the west, and the Flower Garden Banks in the north), O. faveolata exhibits strong overall connectivity (Fst = 0.038). However, this overall connectivity was complicated by regional patterns of genetic structure, including an east-west genetic barrier at Mona Passage and differentiation across only 470 km along the Mesoamerican Barrier Reef System<ns0:ref type='bibr' target='#b81'>(Rippe et al. 2017)</ns0:ref>.In addition to connectivity of the coral host, our results agree with previous work demonstrating greater genetic differentiation of symbiont populations. For example, population differentiation of algal symbionts of the genus Cladocopium (C3, C40) associated with A.hyacinthus and A. digifiera across Micronesia occurs across smaller scales compared to the coral animal (Davies et al. 2015; Davies et al. 2020). While the coral hosts exhibited gene flow across 4,000 km of the Pacific (Davies et al. 2015), the algal symbiont populations were often diverged between reefs within the same island (Davies et al. 2020). Pettay &amp; LaJeunesse (2013) found a similar pattern in Durusdinium glynni population structure sampled from Pocillopora (type 1) across the Eastern Tropical Pacific. In contrast to the host, which exhibited genetic connectivity over 3,400 km (Pinzon &amp; LaJeunesse 2011), a subtropical population of D. glynni in the Gulf of California was differentiated from all other populations, the closest being approximately 700 km away (Pettay &amp; LaJeunesse 2013). This pattern of limited symbiont population connectivity compared to its coral host has also been shown in A. palmata hosting Symbiodinium fitti in the Caribbean (Baums et al. 2014), symbionts of the genus Cladocopium hosted by the octocoral Sinularia flexibilis on the Great Barrier Reef (Howells et al. 2009), symbiont haplotypes B1/B184 associated with corals of the genus Montastraea (Thornhill et al. 2009), and in octocorals Gorgonia ventalina (Kirk et al. 2009) and Pseudopterogorgia elisabethae (Santos et al. 2003) associated with symbionts of the genus Breviolum. Taken together, these studies on both scleractinian and gorgonian tropical corals reveal that limited connectivity of PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>2014) sequenced two nuclear genes (ANT and H3) and found a break in structure in populations of the amethyst gem clam (Gemma gemma; no planktonic larval phase) around New Jersey, separating southern populations of Maryland, Virginia, and North Carolina from northern populations of Maine, Massachusetts, and Connecticut. Such divisions in population structure between what are called the Upper and Lower Virginian provinces (at ~39&#176;N latitude) correspond with a gradient in average SST and with population structure of several other species, including amphipods (Ampithoe longimana), killifish (Fundulus heteroclitus), polychaetes (Marenzellaria viridis), and copepods (Eurytemora affinis) (reviewed in Wares 2002). This division between Upper and Lower Virginian provinces is more consistent with what we observe in B. psygmophilum population structure. In contrast to a body of literature demonstrating marine species with phylogeographic structure in the northwest Atlantic, including those highlighted above, Strasser &amp; Barber (2009) found no evidence of genetic structure in the softshell clam (Mya arenaria) across the stark environmental differences between Maryland in the south and Nova Scotia in the north by sequencing the mitochondrial cytochrome oxidase I gene. The authors suggest that high levels of dispersal and gene flow, facilitated by a three week planktonic PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>found that populations of the Mediterranean octocoral Corallium rubrum from distinct thermal regimes across depth (5, 20, 40 m) differentially induced heat shock protein 70 (HSP70) expression as a function of thermal PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>local adaptation (Pettay &amp; LaJeunesse 2013) and genetic diversification (LaJeunesse et al. 2014) of Symbiodiniaceae. Pettay &amp; LaJeunesse (2013) showed differentiation of the subtropical population of D. glynni symbionts corresponds to environmental differentiation, including seasonal variation in temperature and light. It was hypothesized that connectivity in the Pocillopora coral host plus differentiation in the D. glynni symbiont resulted from larvae and associated symbionts arriving from more southern reefs to the Gulf of California being rapidly replaced by symbionts better adapted to the local temperate environment (Pettay &amp; LaJeunesse 2013). In contrast to A. poculata, Pocillopora maternally inherit their symbionts (vertical transmission). However it is possible that, similar to Pettay &amp; LaJeunesse (2013), differences in seasonal temperature (here between VA and RI; Aichelman et al. 2019) are driving local adaptation in the B. psygmophilum symbionts that A. poculata larvae acquire upon settling in their respective environments. Additionally, in the facultatively symbiotic coral Oculina patagonica,<ns0:ref type='bibr' target='#b64'>Leydet &amp; Hellberg (2016)</ns0:ref> show that distinct symbiont communities across the corals' Mediterranean range correlated with sea surface temperature rather than host genetic background, supporting our hypothesis that local environment also plays an important role in symbiont community structure of facultative corals.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>( 2015 )</ns0:head><ns0:label>2015</ns0:label><ns0:figDesc>photosystem II (psbA gene), a highly conserved region in dinoflagellates<ns0:ref type='bibr' target='#b48'>(Iida et al. 2008)</ns0:ref>. This</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)Manuscript to be reviewed versus neutral and adaptive divergence in the algal symbiont. This highlights how the interacting forces of oceanography, environmentally driven selection, local adaptation, and reproductive biology can manifest in differential connectivity of a marine holobiont system. Previously, we found physiological differentiation in coral host metrics (i.e. respiration rate and thermal optima), but not in symbiont physiology (i.e. photosynthesis rate and photochemical efficiency)<ns0:ref type='bibr' target='#b1'>(Aichelman et al. 2019)</ns0:ref>. Interestingly, here we find the opposite, namely a stronger signal of divergence in the algal symbiont. It is possible that our previous hypothesis regarding symbiont acclimation to aquarium light conditions accounts for this discrepancy, but future work should aim to disentangle the possibility for local adaptation acting at different levels of the A. poculata holobiont. Although A. poculata inhabits hard bottom communities throughout the mid-Atlantic, much remains to be learned about the physiological and molecular mechanisms that facilitate its persistence in such extreme temperature ranges, particularly outside the more northern range focus of this study. Future work should explore extended sampling, and include deeper sequencing to improve the search for potentially selected alleles, across the strong potential biogeographic break of the Gulf Stream at Cape Hatteras as well as increasing the spatial resolution to characterize the scale of connectivity in the weakly dispersing symbionts. Such work will help elucidate the potential role of temperature in driving local adaptation of A. poculata and B. psygmophilum, and could provide insights into how the population dynamics of this holobiont could change as temperatures continue to warm.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 2 Principal</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 3 Principal</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head /><ns0:label /><ns0:figDesc>. Here, in August and September, 2017, brown and white</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Astrangia poculata colonies were collected each from Virginia (VA) and Rhode Island (RI),</ns0:cell></ns0:row><ns0:row><ns0:cell>USA (populations will be referred to as VA-brown [n = 10], VA-white [n = 10], RI-brown [n =</ns0:cell></ns0:row><ns0:row><ns0:cell>10], and RI-white [n = 10]). All brown and white VA colonies were collected from the wreck of</ns0:cell></ns0:row><ns0:row><ns0:cell>ODU and maintained at a temperature of 18&#176;C ( 0.5&#176;C) and salinity of approximately 35 ppt &#177;</ns0:cell></ns0:row><ns0:row><ns0:cell>for a recovery period before fragmentation (5 days for VA corals, 48 days for RI corals). Corals</ns0:cell></ns0:row><ns0:row><ns0:cell>were fragmented over two days (September 20 -21, 2017) using a high-speed cut off tool</ns0:cell></ns0:row><ns0:row><ns0:cell>(Chicago Pneumatic, Rock Hill, SC, USA) fitted with a diamond tip circular blade (sensu</ns0:cell></ns0:row><ns0:row><ns0:cell>Aichelman et al. 2019), then affixed to labeled underwater paper using InstaCure ethyl</ns0:cell></ns0:row></ns0:table><ns0:note>the J.B. Eskridge (36&#176;53'57.1'N, 75&#176;43'20.6'W) on September 15, 2017 at 20 m depth (Figure1). All VA colonies were transported to the Old Dominion University (ODU) Aquatics Facility within 6 hours of collection. All brown and white RI colonies were collected from Fort Wetherill State Park (41&#176;28'38.7'N, 71&#176;21'36.3'W) on August 3, 2017 from a depth of 11 m (Figure1). RI colonies were maintained overnight submerged in Narragansett Bay and then transported by car in an aerated aquarium to ODU the next day. All VA and RI colonies were collected using a hammer and chisel and were separated by at least 0.5 m to ensure the collection of distinct individuals. VA corals were collected under Virginia Marine Resources Commission permit #17-017, while no permit was required for collection of RI corals.Following both collections, all A. poculata colonies were placed in a holding aquarium at cyanoacrylate gel (IC-Gel; Bob Smith Industries Inc., Atascadero, CA, USA). All individualsPeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 4 (on next page)</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:04:47962:1:1:NEW 28 Aug 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Editor’s Decision Two expert reviewers have evaluated your manuscript and their in-depth reviews can be seen below. Both reviewers are positive with respect to the relevance of this study, however, they also have made some important suggestions and comments. In particular, the materials and methods section should be more detailed and the limitations of the study should be addressed. These include the low SNP number, that corals were placed in one warm and one cold tank thus limiting replicates, and to answer whether the samples were tested for clones. Also, this dataset provides an excellent opportunity to discuss the brown and white morphs. Thank you for the opportunity to revise and resubmit our manuscript. We have thoroughly addressed each of the reviewer’s comments point by point below. As an overview, the comments of the two reviewers prompted us to re-analyze the dataset with more robust SNP filters and after removing one individual due to finding a pair of putative clones in our dataset. While our story stays almost entirely the same, as a result of this re-analysis we have updated all figures and tables associated with the SNP analyses. To add to the information we presented previously, we have added in analysis of heterozygosity, and an additional population differentiation analysis via STRUCTURE. Furthermore, we have made sure to emphasize the limitations of this study, including the lack of loci and the need to include additional populations in future studies. Finally, we added in an additional analysis and discussion of the potential genetic differentiation between brown and white morphs of Astrangia poculata. While we cannot provide a definitive answer to this question, we hope that this manuscript provides some insight and hypothesis generation for potential future areas of research. We hope that you will find this revision acceptable for publication in PeerJ and look forward to hearing from you. Additionally, please note throughout that this document the line numbers reported correspond to the version of the manuscript with track changes. Reviewer 1 Basic reporting In this manuscript (#47962), entitled “Adaptive divergence, neutral panmixia, and algal symbiont population structure in the temperate coral Astrangia poculata along the Mid-Atlantic United States”, Aichelman and Barshis aim to address a central question in marine molecular ecology: what are the forces shaping the pattern of genetic structure within species? Focusing of a temperate and facultative symbiotic coral, the northern star coral, Astrangia poculata (= A. danae), they “use high-throughput mRNA sequencing to consider patterns of neutral and adaptive differentiation” in the host and the symbiont, Breviolum psygmophilum (l.101-103). More particularly, they “characterized population structure of the A. poculata host and its symbiont (B. psygmophilum) both by population (VA vs. RI) and by symbiotic state (brown vs. white) using SNPs derived from mRNA-Seq data” (l.121-123). Interestingly, this work complements a recently published paper (Aichelman et al. 2019) suggesting the occurrence of adaption to local thermal conditions in this species. The Authors focused on symbiotic and asymbiotic individuals from two populations: “10 brown and 10 white Astrangia poculata colonies were collected each from Virginia (VA) and Rhode Island (RI), USA” (l. 130-131). These individuals were submitted to a common garden experiment (l.165-204) “designed to consider differential gene expression in A. poculata across temperatures and populations” (l.152-153). Here, the Authors present “the sequencing data from this experiment and the resulting single nucleotide polymorphisms (SNPs) to consider population structure” (l.153-155). The Authors sequenced 96 libraries (84 for gene expression analyses + 12 for population genetics analyses) from 10 symbiotic and 10 asymbiotic individuals from two localities. They conducted the de novo transcriptome assembly and SNP calling and filtering. They analyzed the population genetic structure contrasting the pattern between “neutral” and “outlier” loci in the host and the symbiont using an AMOVA, F-statistics and PCA (l.272-315). In addition to gene ontology analyses was conducted on outlier SNPs to “determine if genes containing outlier SNPs were enriched for any particular GO categories” (l.318). Based on these analyses, the Authors discuss: 1) the occurrence of contrasting patterns of genetic structure among the host and the symbiont; 2) the potential impact of physical barrier on connectivity among the two populations; 3) the influence of local temperature regime on the pattern of genetic differentiation; 4) identify putative genes that may be involved in adaptation to local thermal conditions. Basic reporting: The paper is well written (except some typos, eg. populationS on l. 332, 333). Thank you very much, we fixed the typos mentioned. Ideas are clear, reasoning is well exposed. The Introduction section gives an interesting perspective starting with general considerations on marine connectivity, issues linked to the study of holobionts and the potential role of temperature on the pattern of intra-specific diversity. The model and the objective of the study are well presented and described. One potential flaw may be the lack of reference to works already published in temperate corals (except Costantini et al. 2007). The Authors may consider the following papers focused: i) on the neutral genetic structure in temperate corals: Ledoux et al. 2010 Mol. Ecol., Ledoux et al. 2018 JBiogeo, Aurelle et al. 2011 Genetica, Arizmendi-Meija et al. 2015 Plos One, Masmoudi et al. 2016 EcolEvol; ii) on the potential for local adaptation to thermal conditions in temperate corals: Ledoux et al. 2015 Ecol Evol, Arizmendi-Meija et al. 2015 Coral Reefs, Haguenauer et al. 2013 JEMBE, Crisci et al. 2017 Scientific Rep. The Introduction and the Discussion sections may be strengthened by adding some of these references. We thank the reviewer for pointing out these relevant papers. We have clarified where we were explicitly referring to a lack of information on temperate scleractinian corals, and added in citations on the relevant work done in octocorals. The list of places where we added citations is as follows: • “…extraordinarily fine-scaled neutral population structure across 10s of meters (e.g. Aurelle et al. 2011; Costantini et al. 2007; Ledoux et al. 2010)…” (lines 86-88) • “While we are only beginning to understand these dynamics in tropical corals, comparatively little is known about the forces that shape population structure in temperate scleractinian corals, which exist across vastly wider environmental gradients…. Additionally, work on temperate octocorals in the Mediterranean has demonstrated local adaptation to distinct temperature regimes across depths (Haguenauer et al. 2013; Ledoux et al. 2015) while highlighting genetic drift in limiting such phenotypic differentiation (Crisci et al. 2017; Ledoux et al. 2015).” (lines 114-124) • “Additionally, Haguenauer et al. (2013) found that populations of the Mediterranean octocoral Corallium rubrum from distinct thermal regimes across depth (5, 20, 40 m) differentially induced heat shock protein 70 (HSP70) expression as a function of thermal history. Namely, shallow-water corals that historically experienced warmer temperatures more strongly induced expression of HSP70 upon heat stress, and microsatellite loci showed that corals from the three depths were genetically differentiated across this steep environmental gradient (Haguenauer et al. 2013).” (lines 745-755) In addition, one of the main originalities of the paper is to be focused on a facultative symbiotic coral species. Whether these models have been previously studied in the context of population genetics or local adaptation remain unclear based on the Introduction. This may be improved. Thanks to the reviewer for this suggestion, we found a relevant paper regarding this subject that we previously did not include in the manuscript. We have added the following text to the Introduction: “However, work in Oculina spp. has demonstrated genetic differentiation of the host did not correlate with Symbiodiniaceae community composition; instead, symbiont diversity and geographical structuring was shaped most strongly by sea surface temperature, particularly within the Mediterranean (Leydet & Hellberg 2016).” (lines 117-120) We also added the following text on the same topic to the Discussion: “Additionally, in the facultatively symbiotic coral Oculina patagonica, Leydet & Hellberg (2016) show that distinct symbiont communities across the corals’ Mediterranean range correlated with sea surface temperature rather than host genetic background, supporting our hypothesis that local environment also plays an important role in symbiont community structure of facultative corals.” (lines 768-772) Details on the previous work conducted by the Authors (Aichelman et al. 2019) may be mentioned in the Introduction instead of being presented in the Material and Methods. We feel that we have appropriately introduced our previous work (Aichelman et al. 2019) in the Introduction. We would like to point the reviewer to the points below. • “Our previous work (Aichelman et al. 2019) demonstrated physiological differentiation between a Virginia (VA) and Rhode Island (RI) population of A. poculata. Namely, the thermal optimum (Topt) of respiration was elevated in VA corals compared to RI (3.8°C and 6.9°C greater in brown and white corals, respectively), corresponding with warmer in situ temperatures in the more southern population and suggestive of a signature of adaptation of VA and RI corals to their native thermal habitat.” (lines 135-140) • “Leveraging our previous work on physiological adaptation in these populations, we explore the relative strengths of neutral and adaptive divergence in this broadcast spawning, facultatively symbiotic, and extraordinarily thermally resilient species across the northern half of its range.” (lines 153-156) We would like to highlight that the first point now includes an update and additional information on specific Topt differences between VA and RI corals as a result of a comment from Reviewer 2. The structure of the paper is conformed to PeerJ Standards. Figures and tables are relevant. I would suggest to complete the Figure 1 with the localities discussed from l. 428-468 (e.g. Cape cod, Virginia province). Thank you for this recommendation. We have updated Figure 1 and the Figure 1 legend as suggested to include these biogeographic provinces. I probably missed them but the raw data do not seem to be available (no depository number). The raw data is deposited in NCBI BioProject under accession number PRJNA614998. This information was in the original submitted version, and is currently reported in the Methods on line 286. Experimental design The issue addressed by the Authors perfectly fits the scope of PeerJ. The research questions are relevant. However, it would be nice to explain why do the Authors focused on the potential impact of temperature in this particular species (e.g. potential impact of climate change?). Thank you for this suggestion, we have clarified the potential impact of temperature in the Conclusion: “Such work will help elucidate the potential role of temperature in driving local adaptation of A. poculata and B. psygmophilum, and could provide insights into how the population dynamics of this holobiont could change as temperatures continue to warm.” (lines 891-894) Investigation is rigorous in line with high ethical and technical standard. The methods are sufficiently detailed in most of the manuscript. However, I have some minor concerns regarding the design of the common garden experiment as well as the filtering of molecular markers. In my understanding, the idea of common garden would be used to name the whole experimental design (e.g. Villemereuil et al. 2015 Heredity; Kawecki 2004 Ecology Letters) and not only the holding tank as did by the Authors. This may be confusing and should be rephrased. We agree that this could be confusing for the reader. We have therefore replaced all instances referencing the “common garden aquarium” with “holding aquarium”, including lines 174, 205, 212, 219, 222, and 224. The Authors did not replicate the experimental conditions (i.e. only one warm and one cold tank). Logistic may be a limiting factor for replication, however this lack of “experimental tank” replication and potential logistical limitations should be mentioned. While we agree with the reviewer that the lack of treatment replication would be an issue if we were considering gene expression or other phenotypic data, we maintain that this should not have affected the genotypes of the corals, which we consider here. Additionally, we combined the sequences across genotypes that were in different treatments in order to increase sequencing coverage for each genotype, making the separation of treatments even less of a factor. We present as much information as we do about the temperature aspects of the experimental set-up for the sake of transparency in how the samples were collected; however, we also understand that presenting the details of the temperature experiment when we are not considering gene expression in response to temperature (as the study was originally intended) can be confusing, though we have made our best attempt at describing the approach clearly. Did the Authors genetically confirm the individuals used in the experiment were not clone? We had not originally considered whether our dataset contained clones, so thank you to both reviewers for this suggestion. We have now updated the analysis and removed one individual due to the presence of a single pair of putative clones from the Rhode Island site. Details on the method to detect clones has been added to the Methods section (details below) and the code used has also been added to the Github page associated with this publication. Additionally, the dendrogram detailing the clone identification is included as a supplementary figure (Figure S3). Lines 376-386 now read as follows: “Potential clones in the coral host data were assessed using the R package poppr (v2.8.5) (Kamvar et al. 2015; Kamvar et al. 2014). The filtered vcf file was imported into R and converted into the genind format. Then, the diss.dist function was used to calculate a distance matrix based on relative dissimilarity (i.e. Hamming’s distance; Hamming 1950; Wang et al. 2015), or the number of allelic differences between two individuals. The distance matrix was clustered with hclust and a dendrogram was plotted to identify clones. Two RI-B individuals were determined to be clones using this method, and one was randomly removed for all downstream analyses (Figure S3). To ensure that the clone identification was robust to other measures of genetic distance, this method was repeated with Prevosti distance (Prevosti et al. 1975) and Manhattan distance (using the vegdist function in the package vegan v2.4-2; Oksanen et al. 2011), and the same pair of clones was detected each time.” Regarding the SNP markers, the Authors conducted the SNP filtering at two levels: considering two and four populations, respectively. It is not clear from the manuscript why the Authors choose this approach resulting in two different sets of SNPs, instead of considering the same set of SNPs for two and four populations and to what extend the SNPs that are not shared among the two levels influence the results of the analyses. This should be considered by the Authors. Originally, the goal of doing separate analyses considering the populations as just VA and RI (two populations) and then further subset by symbiotic state into VA-B, VA-W, RI-B, and RI-W (four populations) was to see if we could increase our power to detect population differentiation within neutral sites when doing the two-population analysis due to an increased sample size. However, we agree with the reviewer that this approach of analyzing the data as both two and four populations causes some confusion. We have therefore removed the two-population analysis from the manuscript and only include the analysis considering the corals as four populations, which we feel is the more relevant and interesting analysis. The Authors stated “It should be noted that the dataset presented here had relatively low read counts, resulting from an error in the library preparation that led to sequencing of rRNA in addition to mRNA. To combat this, we have used detailed screening methods at every step of the data analysis pipeline to address these issues” (l.277-280). While they mentioned “detailed screening methods”, I was not able to identify these particular screening methods in the present version of the MS. Moreover, the potential implications of the errors in library preparation should be explained. We agree with the reviewer that the way this was originally worded could be elaborated on further. The discussion referenced above (l. 328-333) now reads: “The primary result of this error was a larger than usual percentage of sequence yield going to rRNA, which resulted in a lower read count on an individual basis. To combat this, we have used conservative cut-off values at every step of the data analysis pipeline to address these issues and account for missing data.” Additionally, after receiving these reviews and re-visiting the data we decided to include additional SNP filters to more robustly filter the data. Specifically, the biggest change we made was to remove individuals with a high percentage of missing data from the analysis. Additionally, we now follow a multi-step process for SNP filtering, more similar to that outlined in the dDocent/2.24 tutorial than used previously. The total number of neutral and high outlier SNPs resulting from this updated analysis are similar to what was previously in the manuscript (see updated Table 2). All analyses in the manuscript have been updated to reflect these new SNP filters and slightly different SNP numbers, and lines 339-375 of the Methods now reads as follows: “These coral and symbiont vcf files were then separately filtered using vcftools (v0.1.12b) and utilizing scripts from the dDocent/2.24 pipeline (Puritz et al. 2014a; Puritz et al. 2014b) to create a rigorously filtered set of variant sites. The filtering parameters were the same for the host and symbiont SNPs, and each file was filtered in four steps. First, vcftools was used to filter files to exclude individuals with more than 50% missing data, exclude sites with minor allele count (mac) greater than or equal to 3, only include sites with a quality score above 30, exclude genotypes with fewer than 5 reads, include only bi-allelic sites, and remove indels. Second, the filter_missing_ind.sh script from dDocent was used to remove individuals with more than 85% missing data. Third, another round of vcftools filtering was conducted to exclude sites if they had more than 75% missing data, include sites with a minor allele frequency (maf) greater than or equal to 0.05, and include sites with mean depth values (across all included individuals) greater than or equal to 10. After these filters were executed, the fourth filtering step used the filter_hwe_by_pop.pl script from dDocent to remove sites out of Hardy-Weinberg equilibrium within each population (minimum Hardy-Weinberg p-value cutoff for SNPs = 0.01). This fourth filter resulted in no SNPs being removed from the symbiont file, but 11 SNPs being removed from the coral file. The filtered vcf files were converted to genepop format using a custom python script (written by D. Barshis). The coral host analysis was conducted considering the data as four populations (VA-B, VA-W, RI-B, and RI-W). The symbiont data only included brown hosts and was therefore analyzed as two populations (VA-B and RI-B).” The number of filtered SNPs is relatively low (1,506 and 1,562 considering 2 and 4 host populations, respectively and 68 for the symbiont). From these pools of SNPs and following the Baypass results, the analyses were conducted on 226 and 9 neutral and selected SNPs and 213 and 12 neutral and selected SNPs for the four and two populations analyses, respectively. The difference in the number of high-quality SNPs and the SNPs used for analyses should be explained both for the host and the symbiont. The difference in these SNP numbers is related to the difference between the files used to establish outliers (using the program BayPass), and the files used for all other analyses, which were filtered first for neutral and high outlier sites and then to include only 1 SNP per contig. We recognize that this was likely not effectively communicated in the manuscript, and we have therefore added information to the methods (lines 404-410) to clarify this point: “Following BayPass outlier detection, the coral and symbiont vcf files were each filtered to create separate files for neutral and high outlier SNPs. These separate vcf files were then randomly filtered to include only one SNP per contig using the Filter_one_random_snp_per_contig.sh script from the dDocent pipeline (Puritz et al. 2014a; Puritz et al. 2014b). This was done to avoid potential bias of analyses due to non-independence of SNPs on the same contig. All analyses besides BayPass outlier detection used files that were first separated by neutral and outlier SNPs and then filtered to include only one SNP per contig.” We would like to emphasize that Fst analyses and other population structure analyses would be unduly affected by multiple SNPs that are considered independent but linked on the same contig, hence why we did this 1 SNP per contig filter. It may have been interesting to consider the whole pool of SNPs first (neutral + selected) and then to conduct the analyses on neutral vs. potentially selected markers, separately. While we do not disagree that this could potentially be interesting, we are specifically interested in assessing the degree of neutral population structure separately from the pool of SNPs that are potentially under selection. This seems to be a common practice in the literature, please see several citations below that support this decision. • Hoban, S., Kelley, J. L., Lotterhos, K. E., Antolin, M. F., Bradburd, G., Lowry, D. B., ... & Whitlock, M. C. (2016). Finding the genomic basis of local adaptation: pitfalls, practical solutions, and future directions. The American Naturalist, 188(4), 379-397. • Milano, I., Babbucci, M., Cariani, A., Atanassova, M., Bekkevold, D., Carvalho, G. R., ... & Hansen, J. H. (2014). Outlier SNP markers reveal fine‐scale genetic structuring across European hake populations (Merluccius merluccius). Molecular Ecology, 23(1), 118-135. • Moore, J. S., Bourret, V., Dionne, M., Bradbury, I., O'Reilly, P., Kent, M., ... & Bernatchez, L. (2014). Conservation genomics of anadromous Atlantic salmon across its North American range: outlier loci identify the same patterns of population structure as neutral loci. Molecular Ecology, 23(23), 5680-5697. Additionally, we highlight our reasoning for this decision in the manuscript, on lines 777-782: “It is important to distinguish between neutral and adaptive loci when considering population divergence. Namely, loci can still be under selection even in the face of extensive gene flow, and therefore populations can appear homogeneous at neutral loci but still exhibit local adaptation (Conover et al. 2006). Adaptive (as opposed to neutral) genetic variation affects an organism’s fitness (Conover et al. 2006). Here, we find evidence of A. poculata host connectivity at neutral loci despite evidence for adaptive divergence at several high outlier sites.” The Authors mentioned “high-quality SNPs”. What do the “high-quality” refer to? We recognize that “high-quality” might not be the best adjective to use here, as we specifically mean to refer to the fact that the variant sites were rigorously filtered to remove noise from the dataset. We have updated lines 339-341 to reflect this: “These coral and symbiont vcf files were then separately filtered using vcftools (v0.1.12b) and utilizing scripts from the dDocent/2.24 pipeline (Puritz et al. 2014a; Puritz et al. 2014b) to create a rigorously filtered set of variant sites.” Additionally, we removed two references to “high-quality SNPs” in the Results, on lines 444 and 445. Moreover, considering the high dispersal capacity of Astrangia poculata, the expected level of genetic structure should be very low. Accordingly, the lack of significant genetic structure reported from neutral SNPs may potentially be linked to the low number of SNPs analyzed. Did the Authors consider this hypothesis? We acknowledge that the lack of structure that we observed in the A. poculata host could be potentially linked to low number of SNPs. However, even the 279 putatively neutral SNPs we have here is well above historical literature using 5-10 microsatellites to consider population genetics. More recently, Milano et al (2014) used only 299 putatively neutral SNPs and 17 outlier SNPs to consider genetic structure of European hake populations. • Milano, I., Babbucci, M., Cariani, A., Atanassova, M., Bekkevold, D., Carvalho, G. R., ... & Hansen, J. H. (2014). Outlier SNP markers reveal fine‐scale genetic structuring across European hake populations (Merluccius merluccius). Molecular Ecology, 23(1), 118-135. To fully address this comment, we have added a caveat to the Discussion as well as the Conclusion to address that future studies should focus on deeper sequencing to have more SNPs to consider population structure in Astrangia poculata and its symbiont: “Additionally, it will be important to conduct deeper sequencing and analyze additional loci across multiple populations to have more confidence in the outlier loci driving differentiation across the range of A. poculata.” (lines 869-871) “Future work should explore extended sampling, and include deeper sequencing to improve the search for potentially selected alleles, across the strong potential biogeographic break of the Gulf Stream at Cape Hatteras as well as increasing the spatial resolution to characterize the scale of connectivity in the weakly dispersing symbionts.” (Lines 888-891) Validity of the findings Validity of the finding: Overall, this is an interesting study focused on an original model (temperate facultative symbiotic coral). Conclusions are globally well supported by the analyses and fully linked to the research question. I would suggest the Authors to rephrase parts of the manuscript addressing the contrasted patterns of genetic differentiation among the host and the symbiont to better fit with the analyses and results. Indeed, the pattern of “selected” genetic structure was not characterized in the Symbiont. We believe that this comment is no longer relevant to the manuscript, as with the re-analysis of the data we are now able to discuss four high outlier SNPs in the symbiont dataset. The Authors may also consider to precise the type of genetic markers used when discussing the results of previous population genetics studies conducted in the same region (paragraph 4.2). Thank you for this suggestion. We added information about the type of genetic markers used in the studies we discuss in section 4.2, and added the following caveat at the end of the paragraph: “For these studies mentioned above, it is possible that differences in the genetic markers used to look for population structure also influenced the ability to detect differences (D’Aloia et al. 2020).” (lines 725-727) It would be interesting to develop the idea that selection may drive the pattern of differentiation at the neutral markers in the Symbiont (l.476). Please see our full response to Reviewer 2 below, who also felt that this point was unclear. In short, in reconsidering this statement, we realized that at neutral loci it is likely not temperature or light differences driving differentiation, but instead is more likely related to the dispersal barriers that we highlight in section 4.1 of the discussion. The Authors stated “Interestingly, the stronger signal of divergence in the algal symbiont is in contrast with our previous results demonstrating the strongest physiological population divergence in coral host respiration” on l. 541-543. In the present form, this sentence may appear a bit vague. The Authors should consider to develop a bit more this issue and its implication in term of local adaptation both at the symbiont and host levels. Thank you for this suggestion, as both reviewers felt this idea needed to be developed more, we have updated the conclusion and lines 878-885 now read as follows: “Previously, we found physiological differentiation in coral host metrics (i.e. respiration rate and thermal optima), but not in symbiont physiology (i.e. photosynthesis rate and photochemical efficiency) (Aichelman et al. 2019). Interestingly, here we find the opposite, namely a stronger signal of divergence in the algal symbiont. It is possible that our previous hypothesis regarding symbiont acclimation to aquarium light conditions accounts for this discrepancy, but future work should aim to disentangle the possibility for local adaptation acting at different levels of the A. poculata holobiont.” Comments for the author General comments: As mentioned, the study presented by Aichelman and Barshis is interesting and well written. In my opinion, it fits the standard of publication in PeerJ. However, I encourage the Authors to account for the comments previously made in order to clarify some parts of the paper. Reviewer 2 Basic reporting This article is clearly presented, and well organised. It is clearly written. Experimental design This article presents original results on the genetic structure of a temperate scleractinian coral and its associated dinoflagellate symbiont in two locations of western Atlantic. The research question is meaningful. The data come from mRNA sequencing which was initially performed for an experimental study of thermotolerance. The results are based on an analysis of potentially selected loci, on differentiation tests and Fst estimates, and on multivariate analyses. The results are interesting, but their interpretation is limited by the quite low final number of SNPs retained in the study, especially for the symbiont. This is a problem for the search of potentially selected alleles, and this point should be in the discussion: is it really meaningful to test for outlier loci with only 68 SNPs? The study is also based on the comparison of only two populations which also limits the conclusion about local adaptation, and replicates would be useful. I understand this is not possible for the present study, but this point should be discussed as well. We agree with the reviewer that we are limited in making conclusions about local adaptation because we only included corals from two sites (Virginia and Rhode Island). We have updated the last few sentences of the manuscript to state that expanded and deeper sequencing will be necessary in future studies: “Although A. poculata inhabits hard bottom communities throughout the mid-Atlantic, much remains to be learned about the physiological and molecular mechanisms that facilitate its persistence in such extreme temperature ranges, particularly outside the more northern range focus of this study. Future work should explore extended sampling, and include deeper sequencing to improve the search for potentially selected alleles, across the strong potential biogeographic break of the Gulf Stream at Cape Hatteras as well as increasing the spatial resolution to characterize the scale of connectivity in the weakly dispersing symbionts.” (lines 885-891) Therefore, we feel that we are leaving the readers with the impression that additional sampling is indeed necessary to make more robust conclusions about population genetic structure in Astrangia poculata. We recognize that this current study is not sufficient to make broad-scale claims about population structure across the entire range of A. poculata. To further drive this point home, we have added a similar caveat to the Discussion: “For both the coral host and symbiont outlier loci, it is important to acknowledge the possibility that some of the SNPs we discuss above are false positives, and not true signatures of local adaptation. Additionally, it will be important to conduct deeper sequencing and analyze additional loci across multiple populations to have more confidence in the outlier loci driving differentiation across the range of A. poculata.” (lines 867-871) Validity of the findings From a methodological point of view, the authors tested for outlier loci in their dataset. I wonder if this analysis can be biased for dinoflagellates considering their life cycle and ploidy? For the outlier analyses there was no filtering to keep one SNP per locus: why? We can see on line 357 that nine coral contigs contained more than one outlier: I wonder if this could have modified the analysis. The one SNP per contig analysis is specific to the population structure analyses that we conducted here, and is not necessary for the outlier analysis. Because linked loci are not independent, analyses that assume their independence (i.e. many population structure analyses) will be affected. To ensure we were thinking about this issue correctly, we wrote to several scientists working on population genetics in the ocean, including Dr. Malin Pinsky (Rutgers University, USA), Dr. Eric Anderson (NOAA), and Dr. Melissa Pespeni (University of Vermont, USA), and all agreed with the method of using all loci to look for outliers and then filter for one SNP per loci and for neutral and adaptive loci for downstream population genetic analyses. We have hopefully clarified the order of operations and our reasoning in the Methods: • “Following BayPass outlier detection, the coral and symbiont vcf files were each filtered to create separate files for neutral and high outlier SNPs. These separate vcf files were then randomly filtered to include only one SNP per contig using the Filter_one_random_snp_per_contig.sh script from the dDocent pipeline (Puritz et al. 2014a; Puritz et al. 2014b). This was done to avoid potential bias of analyses due to non-independence of SNPs on the same contig. All analyses besides BayPass outlier detection used files that were first separated by neutral and outlier SNPs and then filtered to include only one SNP per contig.” (lines 404-410) Regarding the concern about ploidy of dinoflagellates, there does not appear to be a consensus in the coral community on the best way to filter SNPs to address ploidy in Symbiodiniaceae. We communicated with Dr. Sarah Davies (Boston University, USA) and Dr. Mikhail Matz (University of Texas at Austin, USA) about this issue, as they are currently publishing a manuscript on population genetics of Symbiodiniaceae of the genus Cladocopium across the Pacific Ocean (we cite the biorxiv pre-print of their research in our manuscript; Davies et al. 2020). These authors confirmed that they have run into a similar issue, and attempted to analyze their data as diploid and haploid, without a change in results. Therefore, we left our symbiont data analyzed as a diploid, but recognize that as a community we have a lot left to learn about the basic reproduction and biology of Symbiodiniaceae before we can properly address this issue. More generally, in the SNP filtering the authors did not retain SNPs which were not in Hardy-Weinberg equilibrium: but for dinoflagellate, do we expect panmixia? To address the question of the Hardy-Weinberg filter, we included this filtering step in this dataset mostly as a way to remove additional erroneous variant calls. This logic is according to the dDocent SNP filtering tutorial (http://www.ddocent.com/filtering/). This filter is applied by population, as we don’t want to apply this filter across the board which could remove signals of population structure. Therefore, in this instance, we feel that this Hardy-Weinberg filter is more likely to aid in removing erroneous variant calls. Additionally, no SNPs were removed from the symbiont vcf file for the Hardy-Weinberg filter. For the outlier SNPs, both for coral and symbionts, do they correspond to non-synonymous mutations? And I think that analyses of outlier loci should include several different methods to check the robustness of the results. For both the coral host and the symbiont, outlier SNPs do not correspond to non-synonymous mutations. Rather, BayPass identifies outliers based on differentiation measured using the XtX statistic (additional information on this statistic below). A separate analysis would have been necessary to determine information about synonymous vs. non-synonymous sites, which we have not conducted here. We feel that a multi method approach to outlier detection is unnecessary to include here, as several recently published papers have included only one method for outlier detection. For example, van Boheemen et al. (2020) published using only Bayenv2 to detect outlier SNPs and Ketchum et al. (2020) used only a Mahalanobis distance-based approach implemented in the R package pcadapt. van Boheemen, L. A., & Hodgins, K. A. (2020). Rapid repeatable phenotypic and genomic adaptation following multiple introductions. Molecular Ecology. Ketchum, R. N., Smith, E. G., DeBiasse, M. B., Vaughan, G. O., McParland, D., Leach, W. B., ... & Reitzel, A. M. (2020). Population genomic analyses of the sea urchin Echinometra sp. EZ across an extreme environmental gradient. Genome Biology and Evolution. Regarding the coral samples, it would be necessary to indicate if putative clones were detected in the dataset (as this can bias the study of genetic structure). Thank you for this comment. Please see our response to Reviewer 1’s comment above regarding the same issue. In this revision we looked for and removed one of a pair of putative clones from the RI site. Apart from the genetic structure, the authors could give some estimates of genetic diversity such as expected heterozygosity. For this coral dataset, an analysis of genetic structure (with the software STRUCTURE or another similar method) would be interesting to estimate levels of admixture in individuals. Thank you for this suggestion, we have added estimates of heterozygosity to the manuscript, and these results are summarized in Table S2. We also added in a STRUCTURE analysis, reported in Supplementary Figure S4. The text below was specifically added to the manuscript: • Methods, lines 415-417: “Measures of genetic diversity per population, including observed heterozygosity (Ho) and heterozygosity within subpopulations (i.e. expected heterozygosity; Hs) was calculated in GenoDive using default settings.” • Methods, lines 420-428: “STRUCTURE (v2.6), with a 100,000 burn-in period and 500,000 MCMC runs after burn-in, was used to determine the number of distinct genetic groups in the coral host (Falush et al. 2007). The optimal number of genetic clusters (K) was assessed using the DeltaK method (Evanno et al. 2005), which was computed via the online program StructureSelector (Li & Liu 2018) and plotted (Figure S4) using the online program Clumpak (Kopelman et al. 2015).” • Results, lines 480-555: “The coral host Fst results are reflected in the STRUCTURE analysis, with a pattern of admixture in all samples at neutral loci in the coral host, but two distinct clusters separating VA and RI individuals at high outlier loci (Figure S4). The optimal K value for both neutral and outlier loci in the coral host was two.” • Results, lines 557-566: “For the coral host analysis, at neutral loci there were no clear patterns for one population having higher observed (Ho) or expected (Hs) heterozygosity than another, with Ho ranging between 0.217 (RI-B) to 0.283 (RI-W) and Hs ranging between 0.224 (RI-B) and 0.267 (VA-W) (Table S2). At high outlier loci for the coral host, Ho and Hs was lower in VA populations (Ho: VA-B = 0.121, VA-W = 0.097; Hs: VA-B = 0.168, VA-W = 0.171), than in RI (Ho: RI-B = 0.191, RI-W = 0.292; Hs: RI-B = 0.324, RI-W = 0.283; Table S2). For the neutral symbiont loci, Ho and Hs were higher in the VA-B population (0.575 and 0.385, respectively) than in the RI-B population (0.47 and 0.338, respectively). For the four high outlier symbiont SNPs, Ho and Hs were both 0.0 in VA-B population, and in the RI-B population Ho = 0.050 and Hs = 0.047 (Table S2).” There is also an interesting result of differentiation among white and brown coral morphs in Rhode Island (see Fst and PCA), but this is not discussed. More generally the white / brown differentiation is not discussed here, whereas this dataset is a very good opportunity to study this polymorphism. Thank you for pointing this out, we agree that this aspect of our work could be highlighted further. As a result of the new SNP filtering and re-analysis of the data, we now have significant pairwise Fst patterns between VA-B vs. VA-W and RI-B vs. RI-W at the coral host high outlier loci. Additionally, the PCA does still show patterns of differentiation between white and brown morphs at high outlier loci. In order to fully address this point, we conducted an analysis to look for consistent patterns of differentiation between brown and white morphs within each site. While we find equivocal evidence for shared high outlier loci that consistently drive differentiation between brown and white morphs, we have updated the manuscript with the text below to more fully address this point. • Methods, lines 372-375: “Additionally, to look for consistent loci driving patterns of differentiation between brown and white phenotypes within VA and RI, the coral host analysis was also conducted as two populations for each origin separately (VA-B and VA-W separately from RI-B and RI-W).” • Results, lines 589-596: “When analyzing the data as two populations separately for VA and RI to look for consistent high outlier SNPs that could be driving differentiation between brown and white morphs, 11 high outlier SNPs were identified as shared between VA and RI (Table S3), which independently had 49 and 47 high outlier SNPs, respectively. These shared high outlier SNPs include several previously mentioned genes (40S and 60S ribosomal proteins, cyclic AMP-dependent transcription factor ATF-5, and a collagen chain protein), as well as Sequestosome-1, which is implicated in autophagy and immune system process (UniProtKB entry 008623; Consortium 2018).” • Discussion, lines 830-866: “Additionally, as there appears to be some differentiation between white and brown corals based on the PCA analysis (Figure 2B) and within population pairwise Fst calculations, it is tempting to speculate that there are factors driving genetic divergence between symbiotic states. By considering each population separately and looking for consistent outlier SNP identities, we do not find compelling evidence to support this hypothesis as only 11 out of 49 (for VA) and 47 (for RI) outlier SNPs were shared between the two groups. Thus, we find it less parsimonious that each population has uniquely evolved genetic differentiation between symbiotic states, as we imagine a high degree of conservation/shared evolutionary history in this trait. However, there is one interesting high outlier SNP in both VA and RI, annotated as Sequestosome-1, that could potentially be related to differentiation between symbiotic state. Sequestosome-1 (UniProtKB entry 008623; Consortium 2018) is involved in autophagy, and may regulate the activation of NF-B1 (a conserved immune regulatory protein) by TNF-alpha. Previous work in a sea anemone model by Mansfield et al. (2017) suggested that NF-B levels were related to symbiotic state, and Symbiodiniaceae suppressed NF-B to establish symbiosis with Exaiptasia pallida. While it is possible that our results could signify a host-specific genotypic difference that is associated with being symbiotic or aposymbiotic, it is far from definitive. The environmental and/or genetic factors determining which A. poculata individuals are symbiotic and which are aposymbiotic therefore remains elusive, and certainly warrants further exploration.” Comments for the author Abstract : 'In the symbiont, the two putatively adaptive loci…' (there are only two candidate loci, right?) As a result of the slightly new SNP filters, there are now four putatively adaptive loci for the symbiont, and the abstract in addition to the rest of the manuscript has been updated as below to reflect this. “In the symbiont, three of four putatively adaptive loci are associated with photosystem proteins.” (lines 61-62) Introduction : line 69 : factors instead of forces Changed as suggested (line 81). line 78 : some organisms or all organisms? Great point, we have changed the sentence to read as follows: “Patterns of population connectivity in marine systems are made only more complex when considering organisms as multi-organism symbiotic communities, or holobionts…” (lines 89-91) line 94 : as drivers Changed as suggested (line 110). lines 95-97 : maybe give some species names We have added species names for both studies as suggested, and the sentence now reads: “Temperature gradients as drivers of selection and local adaptation have been demonstrated in corals, including Porites astreoides across nearshore and forereef environments on the Florida Keys Reef Tract (Kenkel et al. 2013, Kenkel & Matz 2016) and P. lobata inhabiting tidal pools in American Samoa with differing patterns of thermal variability (Barshis et al. 2010, Barshis et al. 2018).” (lines 110-114) lines 99-100 : you could check the literature on the thermotolerance of Mediterranean octocorals for example Thank you for this suggestion, Reviewer 1 agrees and we have added additional Mediterranean octocoral literature into the Introduction and Discussion. Please see our response to Reviewer 1 above for further details. line 103 : at the beginning of the sentence, write the full genus name Thank you for catching this mistake (line 127), we have changed throughout the manuscript. line 109 : give some numbers We have added the explicit difference in thermal optimum (Topt) that we report in our 2019 paper, and the sentence now reads: “Namely, the thermal optimum (Topt) of respiration was elevated in VA corals compared to RI (3.8°C and 6.9°C greater in brown and white corals, respectively)…” (lines 137-138) line 119 : five weeks in aquarium right ? Yes, this is correct. We have clarified this in text, which now reads: “…larvae have been observed to remain swimming for at least 5 weeks in the lab…” (lines 148-149) line 121 is similar to line 101 Thank you for pointing this out, we removed some information and changed around wording to make these two sentences less similar. Now lines 125 and 151. Materials and methods : lines 130-134 : were brown and white colonies sampled exactly at the same site and in the same ecological conditions ? Yes, the reviewer is correct. We clarified this point by adding the statement “All brown and white…” to the description of collection depth and date for the VA and RI sites (lines 164 and 167). line 132 : samples sizes are already given on line 130 Thank you, we have removed the first mention of the sample size and the sentence now reads: “Here, in August and September, 2017, brown and white Astrangia poculata colonies were collected each from Virginia (VA) and Rhode Island (RI), USA (populations will be referred to as VA-brown [n = 10], VA-white [n = 10], RI-brown [n = 10], and RI-white [n = 10]).” (lines 161-164) line 140 : is there a possibility to collect colonies issued from asexual propagation ? It is possible that we could have collected colonies that were clones as a result of asexual propagation. However, because of the clone analysis we have included, we have accounted for any error this could have introduced into the dataset. Please see our discussion of the new clone analysis above. lines 174-181 : what about light and food ? Did you use the same conditions for white and brown colonies ? Yes, all corals (both brown and white morphs) were maintained under the same conditions after they were collected, including light and food. We have now clarified this point on lines 215-217: “All experimental corals were fed three times a week with freshly hatched Artemia sp. nauplii and maintained under approximately 200 μmol photons m-2s-1 of light supplied by 165 W LED aquarium lights (GalaxyHydro, Roleadro, Shenzhen, China).” line 194: the experiment was a short stress, but the sampling lasted 1 h 40 min after the experiment : please explain this (e.g. what were the first and last samples?). Due to limited personnel during sampling, this is the amount of time that it took to sacrifice all coral fragments and put them into the RNAlater-like solution. While we recognize that this would not be ideal for a gene expression analysis, it should not have affected the genotype of the corals or downstream SNP calling. lines 254 – 255 : do the numbers refer to the number of species in the different databases ? Yes, the reviewer is correct that these numbers refer to the number of species in the different databases. We have clarified this in the text by adding “datasets” after each of the n’s, and lines 303-306 now read: “Briefly, the reference assembly was blasted (using blastn) against four databases: 1) all available cnidarian data (“dirty coral”; n = 10 datasets), 2) all available Symbiodiniaceae data (“dirty sym”; n = 8 datasets), 3) aposymbiotic cnidarian data only (“clean coral”; n = 15 datasets), and 4) cultured Symbiodiniaceae data only (“clean sym”; n = 9 datasets).” line 263 : this filtering seems logical, but then you can’t test here if there was some signals of dinoflagellate sequences in white morphs ? We apologize for the confusion, this was an error on our part. The reviewer correctly assesses that these filters are conservative and therefore do not account for ambiguously assigned contigs. Additionally, we found very few symbiont reads in the white colonies of A. poculata, making any analysis of symbiont reads from the white morphs difficult. This is why we did not address this question of signals of dinoflagellate sequences in white morphs. Ultimately, the goal of the filtering we are referring to here is to conservatively separate host and symbiont contigs in the reference transcriptome, and we are not able to effectively determine what is happening in the few symbionts within the white morphs. We have clarified a previous typo on this subject as follows: • “Similarly, a contig was considered a symbiont contig if it had a length overlap greater than 100 bp with a 60% identity cutoff to any symbiont, and removed if it also assigned to a clean coral reference.” (lines 310-312) line 296 : what is the meaning of 'h' in your Hardy-Weinberg filtering ? We have clarified this point in the text with the definition of this cutoff. Lines 350-352 now read: “After these filters were executed, the fourth filtering step used the filter_hwe_by_pop.pl script from dDocent to remove sites out of Hardy-Weinberg equilibrium within each population (minimum Hardy-Weinberg p-value cutoff for SNPs = 0.01).” lines 300-302 : give a brief explanation about how this method works. Why didn’t you filter for on SNP par locus here? And it would be necessary to test other methods to detect loci under selection We have added additional details on the XtX statistic on lines 389-392: “Outlier SNPs under the core model were determined based on the XtX statistic (introduced by Günther & Coop 2013), which is a SNP-specific Fst corrected for the scaled covariance of population allele frequencies (Gautier 2015). Outlier SNPs were defined as having XtX > 0.5% FDR from a simulated dataset.” We have previously addressed the reviewer’s concern about multiple methods to determine outliers above. line 303 : in table 3 you mention low and high outliers : please explain here. “Low outliers” are estimated by Baypass as SNPs that have lower than expected Fst based on the XtX statistic. Since we do not discuss these low outliers, we have removed them from Table 2 (previously Table 3). Results : line 330 : by 'sites' do you mean bp ? (because vcf files usually refer to variant sites) Thank you for pointing this out, we have changed “sites” to “variants” on line 443. lines 332-333 : recall here what are the two and four populations analyzes (and use plural for populations) We have removed the 2-population analysis from the manuscript (see full response to Reviewer 1 above), and have changed the wording to use the plural for populations (line 445). lines 344-345 :it would be interesting to analyse other axes in PCA (this can be in supplementary material) A preliminary examination of additional PCA axes did not reveal any additional patterns beyond those presented here. All data and analytical scripts are freely available so readers with specific hypotheses regarding additional differentiation can utilize the dataset. line 353 : ' a total of 19 sites were used' : because you test later if there are some outliers, you can’t say here that they are neutral This sentence is in fact referring to the Fst patterns of the sites that we have already determined to be neutral loci, and includes the filter for one SNP per contig. As this topic of number of SNPs used for outlier vs. population structure analyses (particularly the one SNP per contig filter) seems to have not been effectively communicated previously, we have attempted to clarify this point in the Results: • “For the coral host analysis, BayPass analyses identified 1,637 neutral and 84 high outlier SNPs, and further filtering for one SNP per contig left 279 neutral loci and 66 high outlier loci that were used in population differentiation analyses (Table 2).” (lines 462-464) • “For the symbiont analysis, BayPass analyses identified 52 neutral and 4 high outlier SNPs, and further filtering for one SNP per contig left 20 neutral loci and 4 high outlier loci that were used in population differentiation analyses (Table 2).” (lines 474-476) line 353-354 : indicate that the two outliers were not on the same contig (deduced from supplementary material but this should be mentioned here). And you could nevertheless do an Fst analysis on this SNPs. The new SNP filtering left us with 4 high outlier SNPs for the symbiont, therefore the comment above no longer applies to the analysis. Also, we have now included the Fst analyses for these SNPs in the manuscript. Discussion : line 388 (see also line 407) : you did not describe patterns of connectivity here but patterns of genetic differentiation. For the dinoflagellate, the genetic differentiation could also be driven by drift of different genotypes inside colonies which could lead to genetic differentiation among populations. This could also be driven by selection of different genotypes even if this was not detected by your outlier analysis because of a low number of SNPs. Thank you for bringing this to our attention, we have changed “connectivity” to “genetic differentiation” in both instances (now lines 634 and 654). We have also addressed the reviewer’s comment on the potential role of drift, and include a sentence on lines 675-678: “This suggests distinct micro-evolutionary processes (e.g. lower effective dispersal in the symbiont or stronger drift of symbiont genotypes within coral colonies) affect each symbiotic partner (Baums et al. 2014).” line 419 : Sinularia is an octocoral Changed from ‘coral’ to ‘octocoral’ (line 666). line 421 : I would suggest octocoral rather than soft coral Changed as suggested, line 669 now reads ‘octocorals’ instead of ‘soft corals’ line 449 : 'connected and isolated' ? I don’t understand We agree with the reviewer that this was previously unclear. Lines 700-703 now reads: “For example, using RAD-seq Boehm et al. (2015) found two populations of the lined seahorse (Hippocampus erectus) within the Virginian Province to be connected and from an ancestral gene pool that diverged from populations south of Cape Hatteras in the Carolinian and Caribbean provinces.” line 465 : what about the larval duration for the other species mentioned above ? We would like to point the reviewer to where we highlight that larval duration and reproductive mode play a role in the patterns we describe, on lines 727-730: • “In any case, this body of work highlights that oceanographic currents, planktonic larval durations and behavior, life history dynamics, and the environment are all important to consider when evaluating population structure in the sea.” To further elaborate on this point, we added information about the lack of a planktonic larval phase in Gemma gemma (lines 703-708): • “In contrast to panmixia within the Virginian Province, as we also observed in the A. poculata host, Zhang et al. (2014) sequenced two nuclear genes (ANT and H3) and found a break in structure in populations of the amethyst gem clam (Gemma gemma; no planktonic larval phase) around New Jersey, separating southern populations of Maryland, Virginia, and North Carolina from northern populations of Maine, Massachusetts, and Connecticut.” We had also previously included information about the 3-week planktonic larval phase of Mya arenaria, and point the reviewer to lines 718-725: • “The authors suggest that high levels of dispersal and gene flow, facilitated by a three week planktonic larval phase, likely contribute to the observed pattern (Strasser & Barber 2009).” Because we feel it is not the focus of this paragraph to add information about the life history of every organism mentioned, we have only included detailed information on G. gemma and M. arenaria larvae. line 475-476 : please explain how environmental differences could drive divergence in neutral loci. We thank the reviewer for bringing this to our attention. In reconsidering this statement, we realized that at neutral loci it is likely not temperature or light differences driving differentiation, but instead is more likely related to the dispersal barriers that we highlight in section 4.1 of the discussion. It is more likely that temperature/light differences are driving the Fst differentiation at outlier loci, as in the coral host. This agrees with the outliers that we find in the symbiont, namely the photosystem proteins. This sentence now reads: “These environmental differences could drive the subtle adaptive divergence we found in the A. poculata host as well as the B. psygmophilum symbiont.” (lines 736-738) line 482 : 'the metapopulation could be able' rather than 'was able' Changed as suggested (line 744). line 493 : 'similar differences' : similar to what ? Here we are referencing lines 758-760, which read: “Pettay and LaJeunesse (2013) showed differentiation of the subtropical population of D. glynni symbionts corresponds to environmental differentiation, including seasonal variation in temperature and light.” We have changed the sentence that was unclear to the reviewer, now on lines 765-768: “However it is possible that, similar to Pettay & LaJeunesse (2013), differences in seasonal temperature (here between VA and RI; Aichelman et al. 2019) are driving local adaptation in the B. psygmophilum symbionts that A. poculata larvae acquire upon settling in their respective environments.” lines 501-502 : for this kind of analysis it is also important to consider and discuss the possibility of false positives. We agree with the reviewer, this is an important caveat that we failed to include previously and have now added to the Discussion: “For both the coral host and symbiont outlier loci, it is important to acknowledge the possibility that some of the SNPs we discuss above are false positives, and not true signatures of local adaptation.” (lines 867-869) line 518 : response to which stress then ? You just mentioned copper. And you also mentioned a gene putatively involved in variation in symbiont density (so maybe not only coral response). We have clarified this sentence and also updated it based on the slightly new outlier SNPs that we found with the re-analysis and more strict SNP filtering. The sentence in question now reads: “It is therefore possible that adaptive differentiation between VA and RI A. poculata populations is occurring at loci related to the coral stress response and/or symbiosis.” (lines 798-813) lines 529-533 : it would be important to analyze more loci to get more confidence in outlier analysis We agree that this is an important caveat to make for this dataset. We have added this caveat to two places towards the end of the manuscript: • “Additionally, it will be important to conduct deeper sequencing and analyze additional loci across multiple populations to have more confidence in the outlier loci driving differentiation across the range of A. poculata.” (lines 869-871) • “Future work should explore extended sampling, and include deeper sequencing to improve the search for potentially selected alleles, across the strong potential biogeographic break of the Gulf Stream at Cape Hatteras as well as increasing the spatial resolution to characterize the scale of connectivity in the weakly dispersing symbionts.” (lines 888-891) Conclusion line 542 : why do you not discuss this ? We have elaborated on this point in the conclusion, as both reviewers felt that this comment was not given enough context: “Previously, we found physiological differentiation in coral host metrics (i.e. respiration rate and thermal optima), but not in symbiont physiology (i.e. photosynthesis rate and photochemical efficiency) (Aichelman et al. 2019). Interestingly, here we find the opposite, namely a stronger signal of divergence in the algal symbiont. It is possible that our previous hypothesis regarding symbiont acclimation to aquarium light conditions accounts for this discrepancy, but future work should aim to disentangle the possibility for local adaptation acting at different levels of the A. poculata holobiont.” (lines 878-885) References : check the bibliography format. For example some references use abbreviated journal name, and some others use full name Thank you for bringing this to our attention. We have updated the reference format to match PeerJ’s and have checked for consistency in journal naming scheme. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Introduction. The Norwegian regulations for nursing homes consider access to meaningful activities to be an indicator for the quality of nursing homes. Activities of daily living (ADL) provide important basic self-care skills for nursing home residents. Due to the physical changes caused by ageing and comorbidities, nursing home residents may experience functional decline over time, which may affect their ability to perform meaningful ADL, such as outdoor activity, which is considered a valuable and meaningful activity in Norwegian culture. This study aimed to investigate the association between ADL status, institution-dwelling and outdoor activity among nursing home residents.Methods.</ns0:p><ns0:p>This cross-sectional study included 784 residents aged &gt;67 years living in different nursing homes in 15 Norwegian municipalities between November 2016 and May 2018. The Barthel Index was used to assess the nursing home residents' ADL status. Other variables collected were age, gender, body weight and height, visits per month, institution, ward, and participation in weekly outdoor activities. Descriptive statistics were used to provide an overview of the residents' characteristics. A Poisson regression model was used to test the association between the outdoor activity level as a dependent variable and ADL score, institution, and other control variables as independent variables.Results. More than half (57%) of the nursing home residents in this sample did not go outdoors. More than 50% of the residents had an ADL score &lt;10, which indicates low performance status. Further, we found that residents' ADL status, institution, ward, and number of visits had an impact on how often the residents went outdoors.Discussion. The nursing home residents in this study rarely went outdoors, which is interesting because Norwegians appreciate this activity. Differences in the number of visits might explain why some residents went outdoors more often than other residents did. Our findings also highlight that the institution impacts the outdoor activity. How the institutions are organized and how important this activity is considered to be in the institutions obviously determine how often the activity is performed.Conclusion. The low frequency of the outdoor activities might be</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Norway is an example of the Nordic welfare model and its welfare state is characterized by public funding and service provision <ns0:ref type='bibr' target='#b12'>(Esping-Andersen et al. 2002)</ns0:ref>. Norwegian nursing homes are publicly financed, and the municipalities are responsible for providing this service. Access to meaningful activities is a reference for the quality of nursing homes as highlighted in Norwegian regulations for nursing homes (Forskr kvalitet i pleie-og omsorgstjenestene 2003). This regulation, with its specific recommendations, can be used as an indicator to assess the quality of care in nursing homes <ns0:ref type='bibr' target='#b25'>(Kirkevold &amp; Engedal 2006)</ns0:ref>. The regulations require the municipalities to ensure that each resident is offered varied and customised activities in line with other fundamentals of care (Forskr kvalitet i pleie-og omsorgstjenestene 2003).</ns0:p><ns0:p>The availability of activities for nursing home residents may contribute to their well-being and dignity <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b28'>Lampinen et al. 2006b;</ns0:ref><ns0:ref type='bibr' target='#b46'>Sletteb&#248; et al. 2016)</ns0:ref>. By contrast, according to <ns0:ref type='bibr' target='#b35'>N&#229;den et al. (2013)</ns0:ref>, the lack of participation in activities in nursing homes may be explained by the residents' physical impairments, e.g., some residents need to use wheelchairs. Up to 80% of nursing home residents experience cognitive impairment <ns0:ref type='bibr' target='#b43'>(Selbaek et al. 2007)</ns0:ref>, which may also limit their ability to participate in activities such as playing cards, bingo and reading groups <ns0:ref type='bibr' target='#b47'>(Str&#248;m et al. 2016)</ns0:ref>.</ns0:p><ns0:p>The outdoor lifestyle traditionally holds a prominent position in Norwegian culture <ns0:ref type='bibr' target='#b16'>(Gurholt &amp; Broch 2019)</ns0:ref> and is considered as a valuable and meaningful activity. Unfortunately, recent inspections undertaken by the authorities in nursing homes in Norway show a lack of activity offerings <ns0:ref type='bibr' target='#b21'>(Helsetilsynet 2018a;</ns0:ref><ns0:ref type='bibr' target='#b22'>Helsetilsynet 2018b;</ns0:ref><ns0:ref type='bibr' target='#b23'>Helsetilsynet 2018c</ns0:ref>). The limited activity options indicate that the government's current policy and new regulations to increase the level of activities in Norwegian nursing homes have not yet succeeded <ns0:ref type='bibr' target='#b21'>(Helsetilsynet 2018a;</ns0:ref><ns0:ref type='bibr' target='#b26'>Kj&#248;s &amp; Havig 2016;</ns0:ref><ns0:ref type='bibr' target='#b41'>Sandvoll et al. 2012)</ns0:ref>.</ns0:p><ns0:p>Despite the new regulations, changing nursing home practices is difficult <ns0:ref type='bibr' target='#b41'>(Sandvoll et al. 2012)</ns0:ref>. According to <ns0:ref type='bibr'>Palacios-Cena et al. (2015)</ns0:ref>, nursing homes should strive to develop meaningful activities for residents to occupy their time and to provide residents with a meaningful sense of purpose. However, low levels of activities of daily living (ADL) among the residents can affect their ability to participate in activities <ns0:ref type='bibr' target='#b4'>(B&#252;rge et al. 2012)</ns0:ref>. ADL are an important basic self-care skill for the general population as well as for nursing home residents.</ns0:p><ns0:p>Because of physical changes associated with ageing and comorbidities, nursing home residents may experience functional decline over time <ns0:ref type='bibr' target='#b9'>(Drageset et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b32'>Liu et al. 2015)</ns0:ref>. Reduced ADL status may impair the ability to perform ADL and can impact quality of life, social contact and loneliness <ns0:ref type='bibr' target='#b30'>(Liu et al. 2014b</ns0:ref>). Physical activity, rehabilitation or exercise may improve independence and prevent the decline in ADL in elderly residents in long-term care facilities <ns0:ref type='bibr' target='#b4'>(B&#252;rge et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b6'>Crocker et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b30'>Liu et al. 2014b)</ns0:ref>. It is unclear which interventions are most appropriate for slowing the decline in ADL <ns0:ref type='bibr' target='#b6'>(Crocker et al. 2013</ns0:ref>), but it has been suggested that health professionals should promote physical activities with the aim of improving ADL performance among older adults <ns0:ref type='bibr' target='#b4'>(B&#252;rge et al. 2012)</ns0:ref>. The loss of ADL independence is the strongest predictor of the need for institutionalization of the elderly <ns0:ref type='bibr' target='#b15'>(Gaugler et al. 2007</ns0:ref>).</ns0:p><ns0:p>Several factors might influence nursing home residents' ADL status. Previous research has investigated the importance of ADL related to different aspects, such as loneliness, less participation in activities and depression. <ns0:ref type='bibr' target='#b8'>Drageset (2004)</ns0:ref> has shown that dependence in ADL status is associated with a high level of social loneliness. <ns0:ref type='bibr' target='#b9'>Drageset et al. (2011)</ns0:ref> later showed that greater dependence in ADL was associated with more symptoms of depression. Poor balance, incontinence, impaired cognition, low body mass index (BMI), impaired vision, no daily contact with proxies, impaired hearing and the presence of depression were significant risk factors for nursing home residents who experienced a decline in ADL status <ns0:ref type='bibr' target='#b4'>(B&#252;rge et al. 2012)</ns0:ref>.</ns0:p><ns0:p>Few studies have focused on the relationships between ADL status and participation in different activities among nursing home residents. One study investigated physical and social aspects of residents' mobility level and reported that nursing home residents dependent on a wheelchair or elevator during care were less involved in physical and social activities compared with more-mobile residents <ns0:ref type='bibr' target='#b26'>(Kj&#248;s &amp; Havig 2016)</ns0:ref>. This study suggests that reduced mobility might influence participation in different activities offered in the nursing homes. The need for activities and engagement in nursing home residents is well known <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b26'>Kj&#248;s &amp; Havig 2016;</ns0:ref><ns0:ref type='bibr' target='#b27'>Lampinen et al. 2006a;</ns0:ref><ns0:ref type='bibr' target='#b37'>Palacios-Ce&#241;a et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b48'>Theurer et al. 2015)</ns0:ref>. More research is needed on residents' ADL status and its relationship with participation in different activities, such as going outdoors. Despite Norwegian regulations (Forskr kvalitet i pleie-og omsorgstjenestene 2003), the frequency and content of activities are very much up to each nursing home. Previous studies have shown differences between privately owned and government-owned facilities <ns0:ref type='bibr' target='#b29'>(Liu et al. 2014a)</ns0:ref>. Furthermore, previous studies have shown variations in practice regarding activities in Norwegian nursing homes <ns0:ref type='bibr' target='#b24'>(Isaksen et al. 2018)</ns0:ref>. To the best of our knowledge, however, little is known on differences between institutions regarding their outdoor activities.</ns0:p><ns0:p>The aim of this study was to investigate the association between nursing home residents ADL </ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head><ns0:p>A cross-sectional study was used to collect data <ns0:ref type='bibr' target='#b38'>(Polit &amp; Beck 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Variables</ns0:head><ns0:p>Outdoor activity is the dependent variable in our analysis. In this study, the residents either walked on their own or with assistance from staff or visitors. Some residents went outdoors with a walker or in a wheelchair. Some of the residents had an electric wheelchair and went outside on their own. However, the purpose was still the same: outdoor activity. The level of this activity was measured as the number of times the activity was performed during a specific week. We formulated a multivariate Poisson regression model to analyse the distribution of this activity. The independent variables or the regressors, along with their hypothesis, in the model are as follows: &#61623; ADL score. We expected increasing levels of outdoor activities, e.g., making trips outside the nursing home, with increasing ADL score because ADL is a measurement of physical capability (higher scores equal better function). &#61623; Institutions. We introduce nursing homes as random effects to allow for the fact that not all types of nursing homes are included. Our institutions represent a sample from a larger unknown population. The characteristics of that population is a latent, unmeasured factor accounted for by introducing institutions as random effects. &#61623; Ward type. We include a dummy variable for residing in a short-term/rehabilitation ward and one for residing in a long-term ward. The dementia ward is the reference case measured by the model's intercept. Long-term ward residents are expected to be older, frailer and in need of more care; thus, we expected these residents to have the lowest levels of making trips outside the nursing home.</ns0:p><ns0:p>PeerJ reviewing PDF | (2019:11:42775:1:1:NEW 9 Mar 2020)</ns0:p><ns0:p>Manuscript to be reviewed &#61623; Number of visits per month. The number of visits is interpreted as a proxy for less social isolation <ns0:ref type='bibr' target='#b8'>(Drageset 2004</ns0:ref>). We expected that more visits would lead to higher levels of outdoor activities. More visits may also mean that relatives engage in this activity, which increases the level of ADL. &#61623; Age. We expected decreasing levels of ADL with increasing age <ns0:ref type='bibr' target='#b13'>(Feng et al. 2017</ns0:ref>). &#61623; Gender. The gender dummy variable was coded as 1 for men and 0 for women. We had no specific expectations for a gender effect on making trips outside the nursing home. &#61623; BMI is an indication of the general health condition. A low BMI indicates that residents are not eating enough (or that they fail to maintain their body weight). We expected that low BMI would be associated with fewer trips outside the nursing home. Using a Poisson model allowed us to control for other regressors when assessing the effect of ADL score or institution. That is, we could compare residents in the same ward and with the same age, gender, number of visits per month and BMI, but with different ADL scores. Thus, we were able to quantify the direct, independent effect of ADL score or institution on activity levels.</ns0:p><ns0:p>Our responses were collected from 21 different nursing institutions. These institutions differ because they have different combinations of ward types and may have different attitudes towards outdoor activity. Clustering occurs when entities are distributed on several levels. When this is the case, error terms within a cluster will not be independent of error terms in another cluster <ns0:ref type='bibr' target='#b49'>(Trutschel et al. 2017</ns0:ref>). In our design, this means that error terms between nursing homes will not be independent because their differences are not considered in the regression model. We have already considered different ward types because the chance of a resident performing the activity may be affected by the ward type in which the resident lives. Nursing homes (institutions) and ward types are two cluster types; therefore, we should also consider differences between nursing homes in the regression model. We believe that the chance of the activity being performed will be affected by what nursing home a resident lives in. The distribution of wards in nursing homes may also differ. Some nursing homes may have a short-term ward combined with a dementia ward, while others may have a long-term ward combined with a short-term ward. This unequal distribution of ward type combinations may affect the chance of the activity being performed. The nursing homes may have different resources, or they may have different organizations depending on the mix of ward types. There may even be different 'cultures', i.e., the nursing home personnel's attention and attitudes towards outdoor activity may differ.</ns0:p><ns0:p>All of the nursing homes in this study except for one are financed and operated by the municipality. The single private nursing home is not run by a commercial actor, but by the parish associated with the Bergen Cathedral in Bergen, the second largest city and municipality in Norway. Nursing homes all share the same national financing system; therefore, they are in a certain sense not independent of each other because they share the same state budget.</ns0:p><ns0:p>Ideally, the selection criteria for different ward types are identical for all nursing homes and the Norwegian authorities have a set of criteria, which includes the patient's ADL status.</ns0:p><ns0:p>Therefore, the chance of one resident being located in the same ward should be identical between nursing homes. The allocation of residents to ward types should be based on objective rules and not on the discretion of the nursing home, which may differ between municipalities. Uniform standards should be implemented in each nursing home; however, application of the criteria depends on clinical judgment, which might vary between homes. If equal consideration of the patients' condition is not the case, discretion applied at the municipal and institutional level may affect the selection criteria. This may imply that characteristics, such as physical capabilities and need for care, vary between nursing homes and may affect the chance of an activity being performed. Again, this means that institutions should be included in the model. One might argue that the differences between nursing homes are better considered at the municipal level because some nursing homes are located in the same municipality. We have decided to include institutions instead of municipalities because we expect organizational practices and discretion at the institutional level to impact outdoor activity.</ns0:p></ns0:div> <ns0:div><ns0:head>Sample</ns0:head><ns0:p>This cross-sectional study included 784 residents aged &gt;67 years living in 17 nursing homes in 15 Norwegian municipalities. The inclusion criteria were all residents aged &gt;67 years living in the selected nursing homes, while the exclusion criteria were residents receiving palliative care, related to ethical considerations, to protect them from harm related to the completion of questionnaires in their presence. In addition, residents in the palliative phase may be unable to take part in the outdoor activities described in this paper. Five of the nursing homes were located Manuscript to be reviewed in rural areas, while others were located in small villages. The nursing homes were not selected completely at random because the selection was partially determined by what nursing homes that the nursing students attended during their practice period. Therefore, the sample is a convenient sample with limited possibilities for generalization.</ns0:p></ns0:div> <ns0:div><ns0:head>Data collection</ns0:head><ns0:p>The data were collected by first-year nursing students during their placement in nursing homes</ns0:p><ns0:p>between November 2016 and May 2018. The placement was either during the autumn semester, i.e., 8 weeks from the middle of October until the middle of December, or 8 weeks during the spring semester, from the middle of April until the middle of June. The data were collected during the daytime. The process of data collection was discussed and secured by the university teacher and the nurses working at the different nursing homes.</ns0:p></ns0:div> <ns0:div><ns0:head>Instruments</ns0:head><ns0:p>The students observed the residents using the method described in the Barthel Index for measuring performance in ADL, as translated and revised by <ns0:ref type='bibr' target='#b39'>Saltvedt et al. (2008)</ns0:ref>. Each performance item is rated on this scale with a given number of points assigned to each level, related to how dependent or independent the resident is, with maximum of 20 points (20 = totally dependent). The ten variables with possible scores in the Barthel scale are: help needed with eating (0-2), help needed with bathing (0-1), help needed with personal hygiene (0-1), help needed with dressing (0-2), presence or absence of faecal incontinence (0-2), presence or absence of urinary incontinence (0-2), help needed with toilet use (0-2), help needed with transfers (0-3), help needed with walking/mobility (0-3), and help needed with climbing stairs (0-2). The Barthel Index is a standardized, validated and psychometric-tested instrument widely used in the context of elderly care <ns0:ref type='bibr' target='#b32'>(Liu et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b33'>Mahoney &amp; Barthel 1965)</ns0:ref> </ns0:p></ns0:div> <ns0:div><ns0:head>Limitations</ns0:head><ns0:p>There are some limitations in using this approach. Firstly, we did not secure complete randomization in selecting the residents for observation. The students may understand the concept differently or they did not apply it consistently. Secondly, a detailed protocol must be provided to the students so that their observations are made consistently. For instance, what date format should be used, and age and length of stay should be integer numbers. We could not eliminate ambivalence in the data collection completely, but we believe that the sample is a simple, random sample of residents in Norwegian nursing homes and that errors in the data collection were corrected to secure reliability.</ns0:p></ns0:div> <ns0:div><ns0:head>Analysis</ns0:head><ns0:p>We assume that outdoor activity is the dependent variable and that ADL status is an independent variable affecting the level of this activity. In addition, we control for several variables that may have an influence on both activity level and ADL scores, thereby eliminating possible spurious causal factors. We also included institutions as an independent variable, assuming they are random effects, which allows the coefficients to vary between institutions. Descriptive statistics were used to give an overview of the demographic and clinical characteristics of the participants, including age, gender, BMI, ADL status, institution and the prevalence of residents' outdoor activities. We sorted the informants into different groups according to the quartiles from the distribution of ADL scores. We then analysed the levels of the outdoor activities between these groups. To examine the association between ADL score and outdoor activity, we included age, BMI, gender, visits per month, type of ward and ADL score as well as institution in a multivariate Poisson regression model, which allowed us to estimate the independently controlled effect of ADL score and institutions on the level of outdoor activities.</ns0:p><ns0:p>The data were analysed using a Poisson regression model, which was estimated using the SAS GLIMMIX procedure with a Poisson log-link function. In case of over-dispersion in the Poisson models, we used a negative binomial regression model instead. The two-sided significance level was set to 0.05. We assume that institutions (nursing homes) represent several unmeasured characteristics that vary between them. These characteristics may be different service quality, different organizations, different informal routines established between staff, different efficiency in using resources, or different resident characteristics. These characteristics are not measured and probably cannot be measured; thus, it may be better to include the latent variable as random effects in the regression model. Consequently, we estimated a model using institutions as random effects; therefore, the estimated coefficients are allowed to vary between nursing homes. The fixed effects are the effects of different ward types, which are common for all institutions. Each nursing home has an individual-specific random effect in addition to this fixed effect (SAS Institute 2019).</ns0:p><ns0:p>When we introduce institutions as random effects, we also allow for the fact that not all types of nursing homes are included. Our institutions represent a sample from a larger population of unknown size and characteristics. We do not know the defining characteristics for the population of nursing homes; therefore, the institution is not a level variable, such as ward types, where there is a predefined set of possible values. We understand this to be the main difference between using nursing homes as dummy variables or introducing them as random effects. When we use dummy variables, we only include the nursing homes for which we have data. When we introduce them as random effects, we acknowledge that the observed institutions are only a random sample of the wider population and that the population characteristics are a latent, unmeasured factor that should be considered. All statistical analyses were performed using SAS software (University Edition; SAS Institute, Cary, NC, USA).</ns0:p></ns0:div> <ns0:div><ns0:head>Ethics</ns0:head><ns0:p>The </ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The sample (n = 784), presented in table 1, included more women (69%) than men (31%), , which is consistent with the population distribution in this age group <ns0:ref type='bibr' target='#b44'>(Sentralbyr&#229; 2016)</ns0:ref>. Most residents in our sample (55%) resided in a long-term facility, 26% resided in a dementia ward Manuscript to be reviewed and 19% resided in a short-term ward (table <ns0:ref type='table'>1</ns0:ref>). The mean ADL score was 10.1. We distributed residents into groups according to their ADL score using the quartiles from the ADL distribution, which resulted in about the same number of residents in each group. Twenty-eight per cent of the residents had an ADL score of 0-6 points as measured by the Barthel Index, 24% had an ADL score of 7-10 points, 26% had an ADL score of 11-14 points and 23% had an ADL score &gt;15 points.</ns0:p><ns0:p>Table <ns0:ref type='table'>1</ns0:ref> Sample, gender, mean age and ward.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1 Histogram of the distribution of outdoor activities in the preceding week</ns0:head><ns0:p>Figure <ns0:ref type='figure'>1</ns0:ref> shows the distribution of outdoor activities in the preceding week, i.e., trips outside the nursing home. The residents rarely went outdoors: e.g., 57.3% of residents never went outside during the week, while one resident made 14 trips. A few residents went outdoors more often than did the majority, which skewed the distribution to the right.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 2 Association between ADL score and mean participation in outdoor activities</ns0:head><ns0:p>Table <ns0:ref type='table'>2</ns0:ref> shows the participation levels for the outdoor activities in the different ADL groups divided into quartiles from the ADL distribution. Participation is relatively stable; however, it decreased in the lowest two ADL groups.</ns0:p><ns0:p>We estimated a Poisson regression model to analyse the association between outdoor activity, nursing home residents' ADL status and institution. The regression coefficient in a Poisson or negative binomial regression model measures the change in the logarithm of the rate of occurrence for an activity caused by a unit change in a specific independent variable. For example, if the coefficient for a unit change in the ADL score is 0.052, the anti-log of this value is about 1.054, which means that the level of activity has increased by this factor or 5.4%.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 3 Model statistics for Poisson regression model for outdoor activities in the preceding week as a dependent variable</ns0:head><ns0:p>Table <ns0:ref type='table'>3</ns0:ref> shows the goodness-of-fit values for the regression model with trips outside the nursing home in the preceding week as the dependent variable. Institutions are represented as random effects. This means that each institution is allocated an intercept in addition to the model intercept. The dispersion criteria &#61539; 2 /df has a value &lt;2. Therefore, we assume no overdispersion in the Poisson regression model. <ns0:ref type='table' target='#tab_3'>4 and 5</ns0:ref> show the results of the model estimation with outdoor activities in the preceding week as the dependent variable. Long-term ward type is the reference case for ward types and its effect is measured by the model's general intercept. The ADL score has a significant effect on the activity. An increase in the ADL score of 1 was expected to give an increase in the rate of activity level of 1.05. We show this effect by considering two residents, both women aged 85 years, living in a long-term ward, receiving 6 visits per month and having a BMI of 23.8 kg/m 2 (the last two numbers are median values). Both women live in institution number 1. Resident A had an ADL score of 10, while resident B had an ADL score of 15. From our model, we expected resident A to take 0.43 trips outside the nursing home in the preceding week and resident B to take 0.56 trips. Accordingly, we expected that 16 days would be needed for resident A to take one trip outdoors and 13 days would be needed for resident B. Had the two residents lived in institution number 7, the expected number of trips would have been 1.3 and 1.7 trips outdoors, assuming values for age, number of visits, BMI and gender are the same and ADL score is 10 and 15, respectively, as above. In other words, both residents A and B would have three times more outdoor activities if they had been living in institution 7 instead of 1. This result shows that institutions have an effect. All in all, eight institutions have significant effects, while four of them are positive. Table <ns0:ref type='table' target='#tab_3'>4</ns0:ref> also shows that age, visits per month and ward type had significant effects on the number of outdoor activities during the week. All effects were as expected: i.e., increasing age was associated with a lower activity level, whereas an increasing number of visits were associated with more trips outside the nursing home. The effects of short-term wards were negative, indicating that residents in that ward type took significantly fewer trips outside the nursing home than did residents in the long-term ward. Residents in dementia wards took significantly more trips outdoors than residents in long-term wards. BMI had no significant effect on the number of outdoor activities.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Our findings show that 57% of the nursing home residents in this sample did not go outdoors. This is consistent with other studies showing that the activities offered in nursing homes are limited <ns0:ref type='bibr' target='#b26'>(Kj&#248;s &amp; Havig 2016)</ns0:ref> and that the residents often are inactive <ns0:ref type='bibr' target='#b18'>(Harper Ice 2002)</ns0:ref>. Recent inspections of nursing homes undertaken by the Norwegian authorities confirm the lack of activity offerings <ns0:ref type='bibr' target='#b21'>(Helsetilsynet 2018a;</ns0:ref><ns0:ref type='bibr' target='#b22'>Helsetilsynet 2018b;</ns0:ref><ns0:ref type='bibr' target='#b23'>Helsetilsynet 2018c)</ns0:ref>.</ns0:p><ns0:p>The findings of our study might be explained by the residents' ADL score, which was low:</ns0:p><ns0:p>i.e., 50% of the residents had an ADL score between 0 and 10. Increased age was associated with lower activity levels. This low ADL score indicates that these residents had a low ability to go outdoors. This is consistent with national health policies in Norway, which emphasize that the frailest elderly should receive care in nursing homes. It is also in line with previous research that shows that the frailest residents might not be able to go outdoors because of their old age, fatigue, frailty or illness <ns0:ref type='bibr' target='#b35'>(N&#229;den et al. 2013</ns0:ref>). However, <ns0:ref type='bibr' target='#b2'>Bj&#246;rk et al. (2017)</ns0:ref> performed a similar study in Sweden and reported that 60% of the nursing home residents had gone outdoors during the data collection period (November 2013-September 2014). The differences in going outside the nursing home in these similar studies from the Scandinavian health-care context are interesting. Weather and the need for appropriate clothing or equipment can impede the ability of residents to go outdoors. If <ns0:ref type='bibr' target='#b2'>Bj&#246;rk et al. (2017)</ns0:ref> collected data during the summer, it might explain some of these differences. Our data were collected either during autumn or spring. In Norway the temperature and weather conditions often are warmer and contains less rain during July and August, and the residents is more likely to go outdoors. This might explain why the residents in the Swedish study went outside more often <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017</ns0:ref>). Further, our data were collected in the western part of Norway, which experiences weather conditions with more rain compared to the eastern parts of Manuscript to be reviewed</ns0:p><ns0:p>Norway. In addition, these residents might not have proper clothing like raincoats, warm jackets, appropriate shoes or hats suitable for the different weather conditions. The British Broadcasting Corporation (BBC 2018) has shown how the use of a rickshaw with a roof and cover may be an alternative for helping frail elderly people to perform outdoor activities despite their loss in ADL status. The concept of outdoor life, in particular hiking, has a prominent position in the Norwegian culture <ns0:ref type='bibr' target='#b16'>(Gurholt &amp; Broch 2019)</ns0:ref>. In addition, most of the older population in Norway grew up after the last world war; therefore, many have received basic socialization in outdoor life and have maintained their association with outdoor activities throughout their lives <ns0:ref type='bibr' target='#b36'>(Odden 2008)</ns0:ref>.</ns0:p><ns0:p>Our findings highlight that what institution the residents live in has an impact how often they go outdoors. Based on these findings, we present empirical evidence for suggesting that organizational differences impact outdoor activity. How the institutions are organized and how importantly they consider this activity obviously determine how often it is performed. These findings are in line with <ns0:ref type='bibr' target='#b24'>Isaksen et al. (2018)</ns0:ref>, who found that only four of 17 nursing homes had activity plans for the wards. Further, they found variations in staff who had participated in training program regarding activities for the residents <ns0:ref type='bibr' target='#b24'>(Isaksen et al. 2018</ns0:ref>). Physical activity is important for mental well-being among elderly people <ns0:ref type='bibr' target='#b28'>(Lampinen et al. 2006b</ns0:ref>). However, our findings show that increasing age was associated with lower activity levels, which is also in line with <ns0:ref type='bibr' target='#b13'>Feng et al. (2017)</ns0:ref>. This might imply a natural change from being active to being less active and in need for assistance in performing ADL, which corresponds with the process of disengagement described by Cumming and Henry in 1961 <ns0:ref type='bibr' target='#b10'>(Daatland &amp; Solem 2011)</ns0:ref>. When people get older, it is natural for them to gradually withdraw from their social roles and the activities they used to perform. This is in line with Adams et al. Manuscript to be reviewed newspapers or medicines <ns0:ref type='bibr' target='#b3'>(Board &amp; McCormack 2018)</ns0:ref>. Nursing home residents who are no longer capable or do not want to go outside might appreciate a nice view <ns0:ref type='bibr' target='#b11'>(Eijkelenboom et al. 2017)</ns0:ref>. Activities are a basic need and participation in activities might contribute to the wellbeing and dignity experienced by nursing home residents <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b28'>Lampinen et al. 2006b;</ns0:ref><ns0:ref type='bibr' target='#b46'>Sletteb&#248; et al. 2016)</ns0:ref>. Such activities should be organized by the staff in close cooperation with relatives because they are familiar with the residents' needs <ns0:ref type='bibr' target='#b41'>(Sandvoll et al. 2012</ns0:ref>).</ns0:p><ns0:p>Previous research shows that nursing home staff are committed to routines, such as helping residents with personal care, practical help, nutrition and toileting <ns0:ref type='bibr' target='#b17'>(Harnett 2010;</ns0:ref><ns0:ref type='bibr' target='#b41'>Sandvoll et al. 2012</ns0:ref>), but do not always take a person-centred approach (McCormack 2016) in terms of their activities. Nursing homes often lack the opportunity and time to offer activities for all residents and their staff recognize that some residents may spend time sitting alone even though staff members know that they might have preferred to join in activities <ns0:ref type='bibr' target='#b40'>(Sandvoll et al. 2015)</ns0:ref>. Could the lack of staff explain our study results? Our findings show that visits per month and ward type had a significant association with the number of outdoor activities during the week. An increasing number of visits were associated with more trips outside the nursing home. The association with short-term ward type was negative, indicating that the residents in that ward type took significantly fewer trips outside the nursing home than did residents in the long-term ward. Our findings show that the number of visits and ward types had significant effects on the number of trips outside the nursing home during the week. Residents in dementia wards had more visits and took significantly more trips outdoor than did residents in long-term wards. This shows that the visits (from family or volunteers) have an impact on resident's level of activities Manuscript to be reviewed resources to organize individual, person-centred and customized activities for all residents and to co-ordinate voluntary contributions (e.g., from family members and elderly that want to participate in activities). This is consistent with a recent study by <ns0:ref type='bibr' target='#b45'>Skinner et al. (2018)</ns0:ref>, who found that the voluntary, unpaid contribution took place within cultural, social and other activities aimed at promoting mental stimulation and well-being. Furthermore, they suggested that the staff in government nursing homes should consider voluntary contributions when they plan the care of residents in long-term care <ns0:ref type='bibr' target='#b45'>(Skinner et al. 2018</ns0:ref>). To offer a variety of activities for nursing home residents, activities should be offered both inside and outside the nursing home.</ns0:p><ns0:p>We also encourage the national authorities to specify in white papers that activities for Norwegian nursing home residents should take place both indoors and outdoors. For residents who are unable to go outdoors on their own, rickshaws might serve as an alternative way of enabling them to go outdoors. Our findings show that nursing home residents rarely engage in outdoor activities, even though the need for activities and engagement for nursing home residents is well known internationally <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b26'>Kj&#248;s &amp; Havig 2016;</ns0:ref><ns0:ref type='bibr' target='#b27'>Lampinen et al. 2006a;</ns0:ref><ns0:ref type='bibr' target='#b37'>Palacios-Ce&#241;a et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b48'>Theurer et al. 2015)</ns0:ref>. Therefore, a greater focus on activities for elderly nursing home residents should be increased and customized in line with each resident's individual needs and wishes. Finally, our results show that the institution that the residents live in has an important association with outdoor activity. This implies that organizational differences in nursing homes might have an impact on outdoor activity, which is an important implication for further research, health policy and practice.</ns0:p></ns0:div> <ns0:div><ns0:head>Strengths and weaknesses</ns0:head><ns0:p>The strength of this study is the systematic use of standardized, psychometric-tested instruments and measures <ns0:ref type='bibr' target='#b33'>(Mahoney &amp; Barthel 1965)</ns0:ref>. One weakness is related to the nursing students' observations used to rate ADL. One obligation of research is not to harm participations; i.e., even though self-report is recommended as the gold standard for gathering data <ns0:ref type='bibr' target='#b38'>(Polit &amp; Beck 2017)</ns0:ref>, self-report was considered to be inappropriate for assessing the ADL of these residents. The students' involvement in research might contribute to mutually strengthening research and education. In addition, the process of data collection was discussed and secured by the university teacher and nurses working at the different nursing homes. This might be a bias in this study because the involvement might serve as a Hawthorne effect <ns0:ref type='bibr' target='#b38'>(Polit &amp; Beck 2017)</ns0:ref>. Another possible weakness is that we did not test for inter-rater bias. Nevertheless, the teacher and the nurse supervisors were available to the students and a lecture given immediately before this clinical placement highlighted the potential pitfalls.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>More than half (57%) of the participants in this study did not go outdoors during the preceding week. Their ADL status might explain this pattern because more than 50% of the residents had an ADL score &lt;10, which indicates low performance status. The institution that the residents live in has an effect on outdoor activity, which suggests that organizational differences might have an impact on residents' activities, which is an important implication for further research, health policy and practice. Planning for nursing home residents' activities requires staff competence in assessing the capacity and needs of all residents. Those residents with few family members or friends might benefit from visits from volunteers taking on an important function in collaboration with the nursing staff in managing different kind of activities, such as outdoor activities. Our findings show that residents rarely engage in outdoor activities, even though the need for activities and engagement for nursing home residents is well known. Therefore, a greater focus on activities for elderly nursing home residents should be increased and customized in line with each resident's individual needs and wishes.</ns0:p><ns0:note type='other'>Figure 1</ns0:note><ns0:p>Figure <ns0:ref type='figure'>1</ns0:ref> </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2019:11:42775:1:1:NEW 9 Mar 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2019:11:42775:1:1:NEW 9 Mar 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>2011), who found that activity participation in late life changed from an active social life with creative activities to an increased participation in passive social and spiritual activities. Nursing homes must consider this and meet their residents' individual needs and interests. According to the Norwegian quality regulations, nursing home residents should be offered varied and customized activities (Forskr kvalitet i pleie-og omsorgstjenestene 2003). Nursing homes need to facilitate activities that are suitable for each resident's ADL status and individual wishes. For example, it might be important for residents to have their own personal things near their own chair. A nearby table might contain personal important objects, such as magazines, books, PeerJ reviewing PDF | (2019:11:42775:1:1:NEW 9 Mar 2020)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 4 Model estimates of outdoor activities in the preceding week: Poisson regression Table 5 Model estimates of outdoor activities in the preceding week: random effects Tables</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2019:11:42775:1:1:NEW 9 Mar 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Dear Editor in Chief Peer J March 2 th 2020 Thank you for your comments and reviews of our manuscript: Nursing home residents ADL-status and its association with going outdoors. We have considered the reviewers comments, the paper has been revised (major revision), and are pleased to make a new submission of the paper, entitled: Nursing home residents ADL-status, institution-dwelling and its association with outdoor activity, with the following changes marked in red, which provide a point-by-point response (in red) to the reviewers suggestions. Please also see the revised version of the paper with track changes. The paper have been edited by online English before submission. On behalf of the authors, best regards Anne Marie Sandvoll Reviewer: Rebecca Palm Basic reporting The structure of the article needs to be improved. Especially the method section is confusing to the reader, as details on measurement and data collection are given quite late in the manuscript, but which is needed earlier to understand everything that follows properly. Details on the statistics are given in the 'Design' section that need to be placed in the 'Analysis' section. These are just examples. I commented the structure in the pdf to make clear where improvement is needed. We have performed a major revision and structured the paper in line with your suggestions. In the results the authors come up with a result that was not part of the research questions and theoretical assumptions: the influence of the institution. If this result is presented it needs to be included in the research question, theoretically reasoned why the authors included this variable and discussed properly regarding the impact that this result has. Please also see my comments in the pdf. We have revised the paper in line with these suggestions, and added the institution to the research question. The tables and ficures need to be revised (the number of tables shouls be reduced, captions added). Figure 1 need axis labels and a caption. We have revised the figure. Experimental design The meaningfulness of the original research question may be a bit questionable, as the investigated association is quite self-evident. This is also a reason why I recommend to include the influence the instituion has as a research question, as this is not so obvious and also not often investigated. Valuable comment, thank you. We have revised the whole paper in line with this comment. Validity of the findings The discussion and the conclusion need to be broadened with respect to the finding that the institution has an effect on the dependent variable. We have revised the discussion and the conclusion in line with the finding that the institution has an effect. Reviewer 2 Basic reporting Some sentence structure and American English issues in sentence structure remain. Literature sources are provided except where noted. The article is more cohesive with this review, however, major flaws remain.  The paper have beed edited by Online English The paper is unorganized. Adding a full literature review would be helpful. We have made a major revision of the paper, and hopefully it is bette organised now. We have performed a litteraturereview, although the instiutions association on going outdoor is little investigated. See comments to reviewer 1. A description of the variables should be consistent and located in the methods section We have added description of all variables in the method section under the heading variables. Content provided under the methods heading is unclear The paper have been revised in line with this comment. Experimental design The design of the study is stated as cross sectional with randomized selection of homes. No description of how the randomization was conducted is provided. As these homes are locations where nursing students perform clinical, the reader feels the randomization may have been somewhat biased. A full description of how the randomization was done should be included. For example, were all homes in a specifed area able to participate? You were required to obtain consent from all resients, however, a cross sectional study implies all residents in every home (except those who were exclused due to exclusion criteria) participate. Not knowing how many declined is a major flaw in this study design.  A description of radomization have been added. You have one variable ADL as measured by the Barthel Index is valid and reliable (although those validity and reliability statistics were not provided). No other variables are. Your description of the variables is unclear and presented in two locations which is confusing. Your description of the variable 'visits' 'going outside' and 'activity' are believed to be the same variable, however, it is unclear.  We have added information about this variable, hopefully its more clear now. The analysis is described as Poisson model or a multivariate model, then stated that you chose to use a negative binomial regression model instead. You should consistently describe what method of analysis you use. In addition, you have different homes with different ward types and different Norwegian municipalities. Each home is nested within each Norwegian municipalities. You need to review your analysis. We have revised the analysis part in the paper. Validity of the findings Parts of the discussion are overstated, stated incorrectly, or have English language wording issues that may help to confuse the meaning. See comments in paper. The paper have been edited by Online English before submission Suggestions are provided to strengthen the strengths and limitations of this paper. Expand on strengths, there are more than one strrength. Weakness can be more clear and could include:  This weakness needs to be addressed as potential research bias. Measurement bias arises from a potential error the data collection and the process of measuring.You are trying to say that the students might not have assessed residents accurately. There are ways to address this in your data collection, but you did not so address as possible research bias.  How were the activities residents participated in counted. Just going outdoors is difficult to count unless you have someone outside to track 24/7 for the entire period, this is also a measurement bias Did anyone decide not to participate or is it expected in this culture to participate in research activities. This may be a bias as well. Your homes were randomly selected but were the residents? Inclusive bias occurs when samples are selected for convenience. Participants might be biased as well. Any self-reported data could be provided in a way the participant believed the students wanted to hear. response bias is a type of bias where the subject consciously, or subconsciously, gives response that they think that the interviewer wants to hear. We have performed a major revison in line with your comments, and hopefully its more clear now. Comments for the author Thank you for the opportunity to review this paper. The authors have conducted a major revision of this paper and as a result, a new manuscript has been submitted. The authors would benefit from some guidance on research methodology and English language prior to the next submission. Please see comments above and in the paper itself. We have perfomed a major revision and the paper have beed edited by Online English https://www.oleng.com.au before submission. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Introduction. The Norwegian regulations for nursing homes consider access to meaningful activities to be an indicator for the quality of nursing homes. Activities of daily living (ADL) provide important basic self-care skills for nursing home residents. Due to the physical changes caused by ageing and comorbidities, nursing home residents may experience functional decline over time, which may affect their ability to perform meaningful ADL, such as outdoor activity, which is considered a valuable and meaningful activity in Norwegian culture. This study aimed to investigate the association between ADL status, institution-dwelling and outdoor activity among nursing home residents.Methods. This cross-sectional study included 784 residents aged &gt;67 years living in 21 nursing homes in 15 Norwegian municipalities between November 2016 and May 2018. The Barthel Index was used to assess the nursing home residents' ADL status. Other variables collected were age, gender, body weight and height, visits per month, institution, ward, and participation in weekly outdoor activities. Descriptive statistics were used to provide an overview of the residents' characteristics. A Poisson regression model was used to test the association between the outdoor activity level as the dependent variable and ADL score, institution, and other control variables as independent variables.Results. More than half (57%) of the nursing home residents in this sample did not go outdoors. More than 50% of the residents had an ADL score &lt;10, which indicates low performance status. Further, we found that residents' ADL status, institution, ward, and number of visits had an impact on how often the residents went outdoors.Discussion. The nursing home residents in this study rarely went outdoors, which is interesting because Norwegians appreciate this activity. Differences in the number of visits might explain why some residents went outdoors more often than other residents did. Our findings also highlight that the institutions impact the outdoor activity. How the institutions are organized and how important this activity is considered to be in the institutions determine how often the</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Norway is an example of the Nordic welfare model and its welfare state is characterized by public funding and service provision <ns0:ref type='bibr' target='#b12'>(Esping-Andersen et al. 2002)</ns0:ref>. Norwegian nursing homes are publicly financed, and the municipalities are responsible for providing this service. Access to meaningful activities is a reference for the quality of nursing homes as highlighted in Norwegian regulations for nursing homes (Forskr kvalitet i pleie-og omsorgstjenestene 2003). This regulation, with its specific recommendations, can be used as an indicator to assess the quality of care in nursing homes <ns0:ref type='bibr' target='#b26'>(Kirkevold &amp; Engedal 2006)</ns0:ref>. The regulations require the municipalities to ensure that each resident is offered varied and customised activities in line with other fundamentals of care (Forskr kvalitet i pleie-og omsorgstjenestene 2003).</ns0:p><ns0:p>The availability of activities for nursing home residents may contribute to their well-being and dignity <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b29'>Lampinen et al. 2006b;</ns0:ref><ns0:ref type='bibr' target='#b50'>Sletteb&#248; et al. 2016)</ns0:ref>. By contrast, according to <ns0:ref type='bibr' target='#b38'>N&#229;den et al. (2013)</ns0:ref>, the lack of participation in activities in nursing homes may be explained by the residents' physical impairments, e.g., some residents need to use wheelchairs. Up to 80% of nursing home residents experience cognitive impairment <ns0:ref type='bibr' target='#b48'>(Selbaek et al. 2007)</ns0:ref>, which may also limit their ability to participate in activities such as playing cards, bingo and reading groups <ns0:ref type='bibr' target='#b52'>(Str&#248;m et al. 2016)</ns0:ref>.</ns0:p><ns0:p>The outdoor lifestyle traditionally holds a prominent position in Norwegian culture <ns0:ref type='bibr' target='#b16'>(Gurholt &amp; Broch 2019)</ns0:ref> and is considered as a valuable and meaningful activity. Unfortunately, recent inspections undertaken by the authorities in nursing homes in Norway show a lack of activity offerings <ns0:ref type='bibr' target='#b22'>(Helsetilsynet 2018a;</ns0:ref><ns0:ref type='bibr' target='#b23'>Helsetilsynet 2018b;</ns0:ref><ns0:ref type='bibr' target='#b24'>Helsetilsynet 2018c</ns0:ref>). The limited activity options indicate that the government's current policy and new regulations to increase the level of activities in Norwegian nursing homes have not yet succeeded <ns0:ref type='bibr' target='#b22'>(Helsetilsynet 2018a;</ns0:ref><ns0:ref type='bibr' target='#b27'>Kj&#248;s &amp; Havig 2016;</ns0:ref><ns0:ref type='bibr' target='#b43'>Sandvoll et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b46'>Sandvoll et al. 2012)</ns0:ref>.</ns0:p><ns0:p>Despite the new regulations, changing nursing home practices is difficult <ns0:ref type='bibr' target='#b46'>(Sandvoll et al. 2012)</ns0:ref>. According to <ns0:ref type='bibr'>Palacios-Cena et al. (2015)</ns0:ref>, nursing homes should strive to develop meaningful activities for residents to occupy their time and to provide residents with a meaningful sense of purpose. However, low levels of activities of daily living (ADL) among the residents can affect their ability to participate in activities <ns0:ref type='bibr' target='#b5'>(B&#252;rge et al. 2012)</ns0:ref>. ADL are an important basic self-care skill for the general population as well as for nursing home residents.</ns0:p><ns0:p>Because of physical changes associated with ageing and comorbidities, nursing home residents may experience functional decline over time <ns0:ref type='bibr' target='#b9'>(Drageset et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b33'>Liu et al. 2015)</ns0:ref>. Reduced ADL status may impair the ability to perform activities and can impact quality of life, social contact and loneliness <ns0:ref type='bibr' target='#b32'>(Liu et al. 2014b</ns0:ref>). Physical activity, rehabilitation or exercise may improve independence and prevent the decline in ADL in elderly residents in long-term care facilities <ns0:ref type='bibr' target='#b5'>(B&#252;rge et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b6'>Crocker et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b32'>Liu et al. 2014b)</ns0:ref>. It is unclear which interventions are most appropriate for slowing the decline in ADL <ns0:ref type='bibr' target='#b6'>(Crocker et al. 2013</ns0:ref>), but it has been suggested that health professionals should promote physical activities with the aim of improving ADL performance among older adults <ns0:ref type='bibr' target='#b5'>(B&#252;rge et al. 2012)</ns0:ref>. The loss of ADL independence is the strongest predictor of the need for institutionalization of the elderly <ns0:ref type='bibr' target='#b15'>(Gaugler et al. 2007</ns0:ref>).</ns0:p><ns0:p>Several factors might influence nursing home residents' ADL status. Previous research has investigated the importance of ADL related to different aspects, such as loneliness, less participation in activities and depression. <ns0:ref type='bibr' target='#b8'>(Drageset 2004</ns0:ref>) has shown that dependence in ADL status is associated with a high level of social loneliness. <ns0:ref type='bibr' target='#b9'>(Drageset et al. 2011</ns0:ref>) later showed that greater dependence in ADL was associated with more symptoms of depression. Poor balance, incontinence, impaired cognition, low body mass index (BMI), impaired vision, no daily contact with proxies, impaired hearing and the presence of depression were significant risk factors for nursing home residents who experienced a decline in ADL status <ns0:ref type='bibr' target='#b5'>(B&#252;rge et al. 2012)</ns0:ref>.</ns0:p><ns0:p>Few studies have focused on the relationships between ADL status and participation in different activities among nursing home residents. One study investigated physical and social aspects of residents' mobility level and reported that nursing home residents dependent on a wheelchair or elevator during care were less involved in physical and social activities compared with more-mobile residents <ns0:ref type='bibr' target='#b27'>(Kj&#248;s &amp; Havig 2016)</ns0:ref>. This study suggests that reduced mobility might influence participation in different activities offered in the nursing homes. The need for activities and engagement in nursing home residents is well known <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b27'>Kj&#248;s &amp; Havig 2016;</ns0:ref><ns0:ref type='bibr' target='#b28'>Lampinen et al. 2006a;</ns0:ref><ns0:ref type='bibr' target='#b40'>Palacios-Ce&#241;a et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b53'>Theurer et al. 2015)</ns0:ref>. More research is needed on residents' ADL status and its relationship with participation in different activities, such as going outdoors. Despite Norwegian regulations (Forskr kvalitet i pleie-og omsorgstjenestene 2003), the frequency and content of activities are very much up to each nursing home. Previous studies have shown differences between privately owned and government-owned facilities <ns0:ref type='bibr' target='#b31'>(Liu et al. 2014a)</ns0:ref>. Furthermore, previous studies have shown variations in practice regarding activities in Norwegian nursing homes <ns0:ref type='bibr' target='#b25'>(Isaksen et al. 2018)</ns0:ref>. To the best of our knowledge, however, little is known on differences between institutions regarding their outdoor activities.</ns0:p><ns0:p>The aim of this study was to investigate the association between nursing home residents ADL </ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head><ns0:p>A cross-sectional design was used.</ns0:p></ns0:div> <ns0:div><ns0:head>Setting</ns0:head><ns0:p>The data were collected by first-year nursing students during their placement in nursing homes</ns0:p><ns0:p>between November 2016 and May 2018. The placement was either during the autumn semester, i.e., 8 weeks from the middle of October until the middle of December, or 8 weeks during the spring semester, from the middle of April until the middle of June. The data were collected during the daytime by means of a study manual, which the students had been presented in lectures at the university. For standardized instruments and questionnaires, we used the connected manual, procedure or protocol. The process of data collection was supervised by the university teacher and the nurses working at the different nursing homes. </ns0:p></ns0:div> <ns0:div><ns0:head>Participants</ns0:head><ns0:p>The study included 784 residents aged &gt;67 years living in 21 nursing homes in 15 Norwegian municipalities. The inclusion criteria were all residents aged &gt;67 years living in the selected nursing homes, while the exclusion criteria were residents receiving palliative care, related to ethical considerations, to protect them from harm related to the completion of questionnaires in their presence. In addition, residents in the palliative phase may be unable to take part in the outdoor activities described in this paper. Five of the nursing homes were located in rural areas, while others were located in small villages. The nursing homes were not selected completely at random because the selection was partially determined by what nursing homes the nursing students attended during their practice period.</ns0:p></ns0:div> <ns0:div><ns0:head>Variables</ns0:head><ns0:p>We expected increasing levels of outdoor activities, e.g., making trips outside the nursing home, with increasing ADL score because ADL is a measurement of physical capability (higher scores mean better capabilities).We observed the residents by using the method described in the Barthel Index for measuring performance in ADL, as translated and revised by <ns0:ref type='bibr' target='#b42'>Saltvedt et al. (2008)</ns0:ref>.</ns0:p><ns0:p>Each performance item is rated on this scale with a given number of points assigned to each level, related to how dependent or independent the resident is, with maximum of 20 points (20 = totally dependent). The Barthel Index is a standardized, validated and psychometric-tested instrument widely used in the context of elderly care <ns0:ref type='bibr' target='#b33'>(Liu et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b34'>Mahoney &amp; Barthel 1965)</ns0:ref>.</ns0:p><ns0:p>Outdoor activity is the dependent variable in our analysis. In this study, the residents either walked on their own or with assistance from staff or visitors. Some residents went outdoors with a walker or in a wheelchair. Some of the residents had an electric wheelchair and went outside on their own. However, the purpose was still the same: outdoor activity. The level of this activity was measured and documented as the number of times the activity was performed during a week.</ns0:p><ns0:p>Further, we introduce nursing homes as random effects to allow for the fact that not all types of nursing homes are included. Our nursing homes or institutions represent a sample from a larger unknown population. The characteristics of that population is a latent, unmeasured factor accounted for by introducing institutions as random effects. These effects will tell us whether activity levels vary between institutions. We included a dummy variable for residing in a shortterm/rehabilitation ward and one for residing in a dementia ward. Long-term ward residents are expected to be older, frailer and in need of more care; thus, we expected these residents to have the lowest levels of making trips outside the nursing home.</ns0:p><ns0:p>PeerJ reviewing PDF | ( <ns0:ref type='table' target='#tab_22'>2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:ref> Manuscript to be reviewed</ns0:p><ns0:p>The number of visits (per week) is interpreted as a proxy for less social isolation <ns0:ref type='bibr' target='#b8'>(Drageset 2004</ns0:ref>). We expected that more visits would lead to higher levels of outdoor activities. More visits may also mean that relatives engage in this activity, which increases the level of ADL.</ns0:p><ns0:p>Further, we expected decreasing levels of activity with increasing age <ns0:ref type='bibr' target='#b13'>(Feng et al. 2017)</ns0:ref>.</ns0:p><ns0:p>The gender dummy variable was coded as 1 for men and 0 for women. We had no specific expectations for a gender effect on making trips outside the nursing home.</ns0:p><ns0:p>BMI is an indication of the general health condition. A low BMI indicates that residents are not eating enough (or that they fail to maintain their body weight). We expected that low BMI would be associated with fewer trips outside the nursing home. </ns0:p></ns0:div> <ns0:div><ns0:head>Bias</ns0:head><ns0:p>There are some limitations in using this approach. Firstly, we did not secure complete randomization in selecting the residents for observation. The students may understand the concept differently or they did not apply it consistently. Secondly, a detailed protocol was provided to the students so that their observations were made consistently. For instance, what date format should be used, and age and length of stay should be integer numbers. We could not eliminate ambivalence in the data collection completely.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical methods</ns0:head><ns0:p>We designed a model with outdoor activity as the dependent variable and ADL status as an explanatory variable affecting the level of this activity. In addition, we controlled for several other explanatory variables that may have an influence on both activity level and ADL scores, thereby eliminating possible spurious factors. We also included institutions as an independent variable, assuming they are random effects, which allows the coefficients to vary between institutions.</ns0:p><ns0:p>Descriptive statistics were used to give an overview of the demographic and clinical characteristics of the participants, including age, gender, BMI, ADL status, institution and the prevalence of residents' outdoor activities. We sorted the informants into different groups according to the quartiles from the distribution of ADL scores. We then analysed the levels of the outdoor activities between these groups. Clustering occurs when entities are distributed on several levels. When this is the case, error terms within a cluster will not be independently distributed of error terms in another cluster <ns0:ref type='bibr' target='#b54'>(Trutschel et al. 2017</ns0:ref>). In our design, this means that error terms between nursing homes will be biased if they are not acounted for in the regression model. We have already considered different ward types because the chance of a resident performing the activity may be affected by the ward type in which the resident lives. Nursing homes (institutions) and ward types are two cluster types; therefore, we should also consider differences between nursing homes in the regression model. </ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The sample (n = 784), presented in table 2, included more women (69%) than men (31%), , which is consistent with the population distribution in this age group <ns0:ref type='bibr' target='#b51'>(Statistisk Sentralbyr&#229; 2016)</ns0:ref>. Most residents in our sample (55%) resided in a long-term facility, 26% resided in a dementia ward and 19% resided in a short-term ward (table <ns0:ref type='table' target='#tab_7'>2</ns0:ref>). The mean ADL score was 10.1.</ns0:p><ns0:p>We distributed residents into groups according to their ADL score using the quartiles from the ADL distribution, which resulted in about the same number of residents in each group. Twentyeight per cent of the residents had an ADL score of 0-6 points as measured by the Barthel Index, 24% had an ADL score of 7-10 points, 26% had an ADL score of 11-14 points and 23% had an ADL score &gt;15 points.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_9'>3</ns0:ref> shows the participation levels for the outdoor activity in the different ADL groups divided into quartiles from the ADL distribution. Participation is relatively stable; however, it decreased in the lowest two ADL groups.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_13'>4</ns0:ref> shows descriptive statistics for the dependent variable, trip outdoors last week. Table <ns0:ref type='table' target='#tab_14'>5</ns0:ref> shows descriptive statistics for numeric variables used as independent variables while Table <ns0:ref type='table' target='#tab_17'>6</ns0:ref> shows descriptive statistics for categorical variables used as independent variables. Tables <ns0:ref type='table' target='#tab_22'>7 and 8</ns0:ref> show the results of the model estimation with outdoor activities in the preceding week as the dependent variable. Long-term ward type is the reference case for ward types and its effect is measured by the model's general intercept. The ADL score has a significant impact on the activity. An increase in the ADL score of 1 was expected to give an increase in the rate of activity level of 1.05. We show this effect by considering two residents, both women aged 85 years, living in a long-term ward, receiving 6 visits per month and having a BMI of 23.8 kg/m 2 (the last two numbers are median values). Both women live in institution number 1. Resident A had an ADL score of 10, while resident B had an ADL score of 15. From our model, we expected resident A to take 0.43 trips outside the nursing home in the preceding week and resident B to take 0.56 trips. Accordingly, we expected that 16 days would be needed for resident A to take one trip outdoors and 13 days would be needed for resident B. Had the two residents lived in institution number 7, the expected number of trips would have been 1.3 and 1.7 trips outdoors, assuming values for age, number of visits, BMI and gender stay the same and ADL score is 10 and 15, respectively, as above. In other words, both residents A and B would have three times more outdoor activities if they had been living in institution 7 instead of 1. This result shows that institutions have an impact on activity level. This is confirmed by estimation of institutional random effects in Table <ns0:ref type='table' target='#tab_22'>8</ns0:ref> where eight institutions have significant effects, four of them are positive. Table <ns0:ref type='table' target='#tab_20'>7</ns0:ref> also shows that age, visits per month and ward type had significant effects on the number of outdoor activities during the week. All effects were as expected: i.e., increasing age was associated with a lower activity level, whereas an increasing number of visits were associated with more trips outside the nursing home. The effects of short-term wards were negative, indicating that residents in that ward type took significantly fewer trips outside the nursing home than did residents in the long-term ward. Residents in dementia wards took significantly more trips outdoors than residents in long-term wards. BMI had no significant effect on the number of outdoor activities.</ns0:p><ns0:p>We also estimated a zero-inflated Poisson model to account for the large number of observations with zero trips outdoors. The model was designed as a mixed model with nursing homes as random effects. The model estimates zero outcomes separately using ADL scores as predictor variable. This was done in SAS according to the algorithm described by Institute for Digital Research &amp; Education (UCLA 2020). There was little difference compared to the model estimated in Table <ns0:ref type='table' target='#tab_20'>7</ns0:ref> and Table <ns0:ref type='table' target='#tab_22'>8</ns0:ref>. The same independent variables had significant impacts and there was no substantial change in coefficient values.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Our findings show that 57% of the nursing home residents in this sample did not go outdoors. This is consistent with other studies showing that the activities offered in nursing homes are limited <ns0:ref type='bibr' target='#b27'>(Kj&#248;s &amp; Havig 2016)</ns0:ref> and that the residents often are inactive (Harper Ice 2002). Recent inspections of nursing homes undertaken by the Norwegian authorities confirm the lack of activity offerings <ns0:ref type='bibr' target='#b22'>(Helsetilsynet 2018a;</ns0:ref><ns0:ref type='bibr' target='#b23'>Helsetilsynet 2018b;</ns0:ref><ns0:ref type='bibr' target='#b24'>Helsetilsynet 2018c</ns0:ref>).</ns0:p><ns0:p>The findings of our study might be explained by the residents' ADL score, which was low:</ns0:p><ns0:p>i.e., 50% of the residents had an ADL score between 0 and 10. These low ADL scores indicate that these residents had a low ability to go outdoors. This is consistent with national health policies in Norway, which emphasize that the frailest elderly should receive care in nursing homes. It is also in line with previous research that shows that the frailest residents might not be able to go outdoors because of their old age, fatigue, frailty or illness <ns0:ref type='bibr' target='#b38'>(N&#229;den et al. 2013</ns0:ref>). However, <ns0:ref type='bibr' target='#b2'>Bj&#246;rk et al. (2017)</ns0:ref> performed a similar study in Sweden and reported that 60% of the nursing home residents had gone outdoors during the data collection period (November 2013-September 2014). The differences in going outside the nursing home in these similar studies from the Scandinavian health-care context are interesting. Weather and the need for appropriate clothing or equipment can impede the ability of residents to go outdoors. If <ns0:ref type='bibr' target='#b2'>Bj&#246;rk et al. (2017)</ns0:ref> collected data during the summer, it might explain some of these differences. Our data were collected either during autumn or spring. In Norway the temperature and weather conditions often are warmer and contain less rain during July and August, and the residents are more likely to go outdoors. This might explain why the residents in the Swedish study went outside more often <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017</ns0:ref>). Further, our data were collected in the western part of Norway which has more rain compared to the eastern parts of Norway where most people live.</ns0:p><ns0:p>In addition, these residents might not have proper clothing like raincoats, warm jackets, appropriate shoes or hats suitable for the different weather conditions. The British Broadcasting Corporation (BBC 2018) has shown how the use of a rickshaw with a roof and cover may be an alternative for helping frail elderly people to perform outdoor activities despite their loss in ADL status. The concept of outdoor life, in particular hiking, has a prominent position in the Norwegian culture <ns0:ref type='bibr' target='#b16'>(Gurholt &amp; Broch 2019)</ns0:ref>. In addition, most of the older population in Norway grew up after the last world war; therefore, many have received basic socialization in outdoor life and have maintained their association with outdoor activities throughout their lives <ns0:ref type='bibr' target='#b39'>(Odden 2008)</ns0:ref>.</ns0:p><ns0:p>Our findings highlight that institutions have an impact on how often residents go outdoors.</ns0:p><ns0:p>These findings suggest that organizational differences impact outdoor activity. How the institutions are organized and the importance they give this activity obviously determine how often it is performed. These findings are in line with <ns0:ref type='bibr' target='#b25'>Isaksen et al. (2018)</ns0:ref>, who found that only four of 17 nursing homes had activity plans for the wards. Further, they found variations in staff who had participated in training program regarding activities for the residents <ns0:ref type='bibr' target='#b25'>(Isaksen et al. 2018)</ns0:ref>. Even if the service going outdoor is regulated by national regulations (Forskr kvalitet i pleie-og omsorgstjenestene 2003), there is considerable room for adaption in each nursing home. The variation in service provision between nursing homes comes from different cultures, organizational practices and plainly the priority the service gets when set against other services the nursing homes are obliged to provide <ns0:ref type='bibr' target='#b37'>(Nakrem 2015)</ns0:ref>. To increase the level of activity, students should be given more information about the benefits of the activity for nursing home residents as well as the legal rights of this activity. Physical activity is important for mental well-being among elderly people <ns0:ref type='bibr' target='#b29'>(Lampinen et al. 2006b</ns0:ref>). However, our findings show that increasing age was associated with lower activity levels, which is also in line with <ns0:ref type='bibr' target='#b13'>Feng et al. (2017)</ns0:ref>. This might imply a natural change from being active to being less active and in need for assistance, which corresponds with the process of disengagement described by Cumming and Henry in 1961 <ns0:ref type='bibr' target='#b10'>(Daatland &amp; Solem 2011)</ns0:ref>. When people get older, it is natural for them to gradually withdraw from their social roles and the activities they used to perform. This is in line with <ns0:ref type='bibr' target='#b0'>Adams et al. (2011)</ns0:ref>, who found that activity participation in late life changed from an active social life with creative activities to an increased participation in passive social and spiritual activities. Nursing homes must consider this and meet their residents' individual needs and interests. According to the Norwegian quality regulations, nursing home residents should be offered varied and customized activities (Forskr kvalitet i pleie-og omsorgstjenestene 2003). Nursing homes need to facilitate activities that are suitable for each resident's ADL status and individual wishes. For example, it might be important for residents to have their own personal things near their own chair. A nearby table might contain personal important objects, such as magazines, books, newspapers or medicines <ns0:ref type='bibr' target='#b4'>(Board &amp; McCormack 2018)</ns0:ref>. Nursing home residents who are no longer capable or do not want to go outside might appreciate a nice view <ns0:ref type='bibr' target='#b11'>(Eijkelenboom et al. 2017)</ns0:ref>. Activities are a basic need and participation in activities might contribute to the well-being and dignity experienced by nursing home residents <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b29'>Lampinen et al. 2006b;</ns0:ref><ns0:ref type='bibr' target='#b50'>Sletteb&#248; et al. 2016)</ns0:ref>. Such activities should be organized by the staff in close co-operation with relatives because they are familiar with the residents' needs <ns0:ref type='bibr' target='#b46'>(Sandvoll et al. 2012</ns0:ref>).</ns0:p><ns0:p>Previous research shows that nursing home staff are committed to routines, such as helping residents with personal care, practical help, nutrition and toileting <ns0:ref type='bibr' target='#b17'>(Harnett 2010;</ns0:ref><ns0:ref type='bibr' target='#b46'>Sandvoll et al. 2012</ns0:ref>), but do not always take a person-centred approach (McCormack 2016) in terms of their activities. Nursing homes often lack the opportunity and time to offer activities for all residents and their staff recognize that some residents may spend time sitting alone even though staff members know that they might have preferred to join in activities <ns0:ref type='bibr' target='#b44'>(Sandvoll et al. 2015)</ns0:ref>. Could the lack of staff explain our study results? Our findings show that visits per month and ward type had a significant effect on number of outdoor activities during the week. An increasing number of visits were associated with more trips outside the nursing home. This shows that the visits (from family or volunteers) have an impact on resident's level of activities regarding outdoor activity. In Norway, the government has addressed new ideas to solve the staff challenges and suggests that voluntary contributions by relatives and organizations should be included as a way of providing activities for nursing home residents (Det kongelige kulturdepartement 2018; Helseog omsorgsdepartementet 2013).</ns0:p><ns0:p>A reform to improve elderly care was introduced in a recent white paper from the Norwegian government. One of the main areas that need improvement in elderly care is activities for elderly people living in nursing homes and the white paper suggests that they should participate in one hour of activity every day (Helse-og omsorgsdepartementet 2018). To provide more activities for nursing home residents, particularly outdoor activities, nursing home staff should be given resources to organize individual, person-centred and customized activities for all residents and to co-ordinate voluntary contributions (e.g., from family members and elderly that want to participate in activities). This is consistent with a recent study by <ns0:ref type='bibr' target='#b49'>Skinner et al. (2018)</ns0:ref>, who found that the voluntary, unpaid contribution took place within cultural, social and other activities aimed at promoting mental stimulation and well-being. Furthermore, they suggested that the staff in government nursing homes should consider voluntary contributions when they plan the care of residents in long-term care <ns0:ref type='bibr' target='#b49'>(Skinner et al. 2018</ns0:ref>). To offer a variety of activities for nursing home residents, activities should be offered both inside and outside the nursing home.</ns0:p><ns0:p>We also encourage the national authorities to specify in white papers that activities for Norwegian nursing home residents should take place both indoors and outdoors. For residents who are unable to go outdoors on their own, rickshaws might serve as an alternative way of enabling them to go outdoors. Our findings show that nursing home residents rarely engage in outdoor activities, even though the need for activities and engagement for nursing home residents is well known internationally <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b27'>Kj&#248;s &amp; Havig 2016;</ns0:ref><ns0:ref type='bibr' target='#b28'>Lampinen et al. 2006a;</ns0:ref><ns0:ref type='bibr' target='#b40'>Palacios-Ce&#241;a et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b53'>Theurer et al. 2015)</ns0:ref>. Therefore, a greater focus on activities for elderly nursing home residents should be increased and customized in line with each resident's individual needs and wishes. Finally, our results show that the institution that the residents live in has an important association with outdoor activity. This implies that organizational differences in nursing homes might have an impact on outdoor activity, which is an important implication for further research, health policy and practice.</ns0:p></ns0:div> <ns0:div><ns0:head>Strengths and weaknesses</ns0:head><ns0:p>The strength of this study is the systematic use of standardized, psychometric-tested instruments and measures <ns0:ref type='bibr' target='#b34'>(Mahoney &amp; Barthel 1965)</ns0:ref>. One weakness is related to the nursing students' observations used to rate ADL. One obligation of research is not to harm participations; i.e., even though self-report is recommended as the gold standard for gathering data <ns0:ref type='bibr' target='#b41'>(Polit &amp; Beck 2017)</ns0:ref>, self-report was considered to be inappropriate for assessing the ADL of these residents. The Manuscript to be reviewed is an advantage, particularly since the lecture was given immediately before clinical placement.</ns0:p><ns0:p>The data collection was supervised by the university teacher and nurses working at the different nursing homes. This might, on the other side, be a bias in this study because the involvement might serve as a Hawthorne effect <ns0:ref type='bibr' target='#b41'>(Polit &amp; Beck 2017)</ns0:ref>. The participants represent a convenient sample from clinical placements where the university has contracts educating students. In such a way, it might be limited possibilities for generalization of the results to all nursing homes.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>More than half (57%) of the participants in this study did not go outdoors during the preceding week. Their ADL status might explain this pattern because more than 50% of the residents had an ADL score &lt;10, which indicates low performance status. The institutions that the residents live in have an impact on outdoor activity, which suggests that organizational differences matter.</ns0:p><ns0:p>This is an important implication for further research, health policy and practice. Planning for nursing home residents' activities requires staff competence in assessing the capacity and needs of all residents. Those residents with few family members or friends might benefit from visits from volunteers taking on an important function in collaboration with the nursing staff in managing different kind of activities, such as outdoor activities. Our findings show that residents rarely engage in outdoor activities, even though the need for activities and engagement for nursing home residents is well known. Therefore, a greater focus on activities for elderly nursing home residents should be increased and customized in line with each resident's individual needs and wishes. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Descriptive statistics for numeric independent variables Manuscript to be reviewed Manuscript to be reviewed Descriptive statistics for categorical variables used as independent variables Manuscript to be reviewed Manuscript to be reviewed Model estimates of outdoor activities in the preceding week: Poisson regression Tables <ns0:ref type='table' target='#tab_22'>7 and 8</ns0:ref> show the results of the model estimation with outdoor activities in the preceding week as the dependent variable. Long-term ward type is the reference case for ward types and its effect is measured by the model's general intercept. The ADL score has a significant impact on the activity.</ns0:p><ns0:p>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed Model estimates of outdoor activities in the preceding week: random effects Tables <ns0:ref type='table' target='#tab_22'>7 and 8</ns0:ref> show the results of the model estimation with outdoor activities in the preceding week as the dependent variable. Long-term ward type is the reference case for ward types and its effect is measured by the model's general intercept. The ADL score has a significant impact on the activity.</ns0:p><ns0:p>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>students' involvement in research might contribute to mutually strengthening research and education. The students used a predefined manual or standardized protocol to assess data, which PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head /><ns0:label /><ns0:figDesc>All variables were registered in a form and documented in Excel version16.16.19 (Microsoft, </ns0:figDesc><ns0:table /><ns0:note>Redmond, WA, USA).</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head /><ns0:label /><ns0:figDesc>Poisson log-link function. The two-sided significance level was set to 0.05.We assume that institutions (nursing homes) represent several unmeasured characteristics that vary between them. These characteristics may be different service quality, different organizations, different informal routines established among staff, different efficiency in using resources, or different resident characteristics. These characteristics are not measured and probably cannot be measured. Therefore, we introduced nursing homes as random effects in the</ns0:figDesc><ns0:table /><ns0:note>To further examine the association between ADL score and outdoor activity, we included age, BMI, gender, visits per month, type of ward and ADL score as well as institutions in a multivariate Poisson regression model. The data were analysed using the SAS GLIMMIX procedure with a regression model to account for these variations. Consequently, the estimated coefficients are allowed to vary between nursing homes. The impacts of different ward types are fixed effects since ward types have the same definition for all nursing homes and therefore do not measure any latent characteristics. Thus, each nursing home has an individual-specific random effect in addition to this fixed effect of ward type (SAS Institute 2019). A mixed model with both fixed and random effects designed to capture variations between clusters is called a conditional model<ns0:ref type='bibr' target='#b36'>(Muff et al. 2016)</ns0:ref>. The clusters in the estimated model consist of nursing homes.The model allowed us to control for other regressors when assessing the effect of ADL score or institutions on outdoor activity. Thus, we could compare activity level between residents in the same ward and with the same age, gender, number of visits per month and BMI, but with different ADL scores in different institutions.</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>shows the goodness-of-fit values for the regression model with trips outside the nursing home in the preceding week as the dependent variable. The dispersion criteria &#61539; 2 /df has a value &lt;2. Therefore, we assumed no overdispersion in the model and we continued with a</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Poisson model rather than substituting it with a model correcting for overdispersion such as a</ns0:cell></ns0:row><ns0:row><ns0:cell>negative-binomial model.</ns0:cell></ns0:row><ns0:row><ns0:cell>All statistical analyses were performed using SAS software (University Edition; SAS</ns0:cell></ns0:row><ns0:row><ns0:cell>Institute, Cary, NC, USA).</ns0:cell></ns0:row><ns0:row><ns0:cell>Ethics</ns0:cell></ns0:row><ns0:row><ns0:cell>The Regional Medical Ethics Committee REK West, University of Bergen (2015/2030 REK</ns0:cell></ns0:row></ns0:table><ns0:note>WEST, University of Bergen) and the Norwegian Social Science Data Services (46303) approved the study, which was endorsed by all nursing homes. Voluntary, written informed consent was obtained from all participants. In situations where the resident was not able to give consent related to e.g., dementia or cognitive impairment, either the resident's relatives or the department manager gave consent.</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Model statistics for Poisson regression model for outdoor activities in the preceding week as a dependent variableTable1shows the goodness-of-fit values for the regression model with trips outside the nursing home in the preceding week as the dependent variable. The dispersion criteria c</ns0:figDesc><ns0:table><ns0:row><ns0:cell>2 /df</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 1 Model statistics for Poisson regression model for outdoor activities in the preceding week as a dependent variable</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Goodness-of-fit criteria</ns0:cell><ns0:cell>df</ns0:cell><ns0:cell>&#61539; 2</ns0:cell><ns0:cell>&#61539; 2 /df</ns0:cell></ns0:row><ns0:row><ns0:cell>Generalized chi-square</ns0:cell><ns0:cell>774</ns0:cell><ns0:cell>1216.3</ns0:cell><ns0:cell>1.57</ns0:cell></ns0:row><ns0:row><ns0:cell>Number of observations</ns0:cell><ns0:cell /><ns0:cell>784</ns0:cell><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Sample</ns0:cell></ns0:row><ns0:row><ns0:cell>The sample (n = 784), included more women (69%) than men (31%), , which is consistent</ns0:cell></ns0:row><ns0:row><ns0:cell>with the population distribution in this age group. Most residents in our sample (55%) resided</ns0:cell></ns0:row><ns0:row><ns0:cell>in a long-term facility, 26% resided in a dementia ward and 19% resided in a short-term ward</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_8'><ns0:head>Table 2 Sample, gender, mean age and ward Variable Value Frequency Relative frequency (%) Mean age (years)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Gender</ns0:cell><ns0:cell>Female</ns0:cell><ns0:cell>541</ns0:cell><ns0:cell>69.0</ns0:cell><ns0:cell>87.1</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Male</ns0:cell><ns0:cell>243</ns0:cell><ns0:cell>31.0</ns0:cell><ns0:cell>84.7</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Total</ns0:cell><ns0:cell>784</ns0:cell><ns0:cell>100.0</ns0:cell><ns0:cell>86.3</ns0:cell></ns0:row><ns0:row><ns0:cell>Ward</ns0:cell><ns0:cell>Dementia</ns0:cell><ns0:cell>200</ns0:cell><ns0:cell>26</ns0:cell><ns0:cell>84.8</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Short term</ns0:cell><ns0:cell>152</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>83.7</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Long term</ns0:cell><ns0:cell>432</ns0:cell><ns0:cell>55</ns0:cell><ns0:cell>87.9</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Total</ns0:cell><ns0:cell>784</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>86.3</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_9'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_10'><ns0:head>Table 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_11'><ns0:head>Table 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>shows the participation levels for the outdoor activity in the different ADL groups divided into quartiles from the ADL distribution. Participation is relatively stable; however, it decreased in the lowest two ADL groups.</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_12'><ns0:head>Table 3 Association between ADL score and mean participation in outdoor activities</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell cols='2'>ADL groups</ns0:cell><ns0:cell>Total</ns0:cell></ns0:row><ns0:row><ns0:cell>0-6</ns0:cell><ns0:cell>7-10</ns0:cell><ns0:cell>11-14</ns0:cell><ns0:cell>Over</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>15</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_13'><ns0:head>Table 4 Descriptive statistics for dependent variable, trips outdoors last week Trip outdoors last week</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Min</ns0:cell><ns0:cell>0</ns0:cell></ns0:row><ns0:row><ns0:cell>Median</ns0:cell><ns0:cell>0</ns0:cell></ns0:row><ns0:row><ns0:cell>Max</ns0:cell><ns0:cell>14</ns0:cell></ns0:row><ns0:row><ns0:cell>Number of observations</ns0:cell><ns0:cell>788</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_14'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_15'><ns0:head>Table 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>shows descriptive statistics for numeric variables used as independent variables.</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_16'><ns0:head>Table 5 Descriptive statistics for numeric independent variables Mean Standard deviation</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Number of</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>observations</ns0:cell></ns0:row><ns0:row><ns0:cell>ADL score</ns0:cell><ns0:cell>10.1</ns0:cell><ns0:cell>5.2</ns0:cell><ns0:cell>787</ns0:cell></ns0:row><ns0:row><ns0:cell>Age</ns0:cell><ns0:cell>86.3</ns0:cell><ns0:cell>7.2</ns0:cell><ns0:cell>786</ns0:cell></ns0:row><ns0:row><ns0:cell>Visits per month</ns0:cell><ns0:cell>8.9</ns0:cell><ns0:cell>8.8</ns0:cell><ns0:cell>787</ns0:cell></ns0:row><ns0:row><ns0:cell>Body mass index</ns0:cell><ns0:cell>24.2</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>785</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_17'><ns0:head>Table 6 (on next page)</ns0:head><ns0:label>6</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_18'><ns0:head>Table 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>shows descriptive statistics for categorical variables used as independent variables.</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_19'><ns0:head>1 Table 6 Descriptive statistics for categorical variables used as independent variables</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell>N</ns0:cell><ns0:cell>% of total</ns0:cell></ns0:row><ns0:row><ns0:cell>Ward type</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Short term/rehab</ns0:cell><ns0:cell>153</ns0:cell><ns0:cell>19.4</ns0:cell></ns0:row><ns0:row><ns0:cell>Long term</ns0:cell><ns0:cell>434</ns0:cell><ns0:cell>55.1</ns0:cell></ns0:row><ns0:row><ns0:cell>Dementia</ns0:cell><ns0:cell>200</ns0:cell><ns0:cell>25.4</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>787</ns0:cell><ns0:cell>99.9</ns0:cell></ns0:row><ns0:row><ns0:cell>Gender</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Female</ns0:cell><ns0:cell>543</ns0:cell><ns0:cell>69</ns0:cell></ns0:row><ns0:row><ns0:cell>Male</ns0:cell><ns0:cell>244</ns0:cell><ns0:cell>31</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>787</ns0:cell><ns0:cell>100</ns0:cell></ns0:row><ns0:row><ns0:cell>Nursing home</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>InstId 1</ns0:cell><ns0:cell>74</ns0:cell><ns0:cell>9.4</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 2</ns0:cell><ns0:cell>43</ns0:cell><ns0:cell>5.5</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 3</ns0:cell><ns0:cell>60</ns0:cell><ns0:cell>7.6</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 4</ns0:cell><ns0:cell>37</ns0:cell><ns0:cell>4.7</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 5</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>1.3</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 6</ns0:cell><ns0:cell>39</ns0:cell><ns0:cell>5</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 7</ns0:cell><ns0:cell>52</ns0:cell><ns0:cell>6.6</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 8</ns0:cell><ns0:cell>43</ns0:cell><ns0:cell>5.5</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 9</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>2.8</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 10</ns0:cell><ns0:cell>123</ns0:cell><ns0:cell>15.6</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 11</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 12</ns0:cell><ns0:cell>45</ns0:cell><ns0:cell>5.7</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 13</ns0:cell><ns0:cell>25</ns0:cell><ns0:cell>3.2</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 15</ns0:cell><ns0:cell>96</ns0:cell><ns0:cell>12.2</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 16</ns0:cell><ns0:cell>26</ns0:cell><ns0:cell>3.3</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 17</ns0:cell><ns0:cell>15</ns0:cell><ns0:cell>1.9</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 19</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>3.4</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 20</ns0:cell><ns0:cell>18</ns0:cell><ns0:cell>2.3</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 21</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 22</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.9</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 23</ns0:cell><ns0:cell>15</ns0:cell><ns0:cell>1.9</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>787</ns0:cell><ns0:cell>100</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_20'><ns0:head>Table 7 (on next page)</ns0:head><ns0:label>7</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_21'><ns0:head>1 Table 7 Model estimates of outdoor activities in the preceding week: Poisson regression</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Effect</ns0:cell><ns0:cell>Estimate</ns0:cell><ns0:cell>Standard error</ns0:cell><ns0:cell>df</ns0:cell><ns0:cell>t value</ns0:cell><ns0:cell>Pr &gt; |t|</ns0:cell></ns0:row><ns0:row><ns0:cell>Intercept</ns0:cell><ns0:cell>0.941</ns0:cell><ns0:cell>0.590</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>1.59</ns0:cell><ns0:cell>0.127</ns0:cell></ns0:row><ns0:row><ns0:cell>ADL</ns0:cell><ns0:cell>0.052</ns0:cell><ns0:cell>0.008</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>6.72</ns0:cell><ns0:cell>&lt;.0001</ns0:cell></ns0:row><ns0:row><ns0:cell>Gender (1 = Male)</ns0:cell><ns0:cell>0.102</ns0:cell><ns0:cell>0.086</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>1.19</ns0:cell><ns0:cell>0.236</ns0:cell></ns0:row><ns0:row><ns0:cell>Age</ns0:cell><ns0:cell>&#8722;0.024</ns0:cell><ns0:cell>0.006</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;4.18</ns0:cell><ns0:cell>&lt;.0001</ns0:cell></ns0:row><ns0:row><ns0:cell>Visit Pr month</ns0:cell><ns0:cell>0.030</ns0:cell><ns0:cell>0.004</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>7.74</ns0:cell><ns0:cell>&lt;.0001</ns0:cell></ns0:row><ns0:row><ns0:cell>BMI</ns0:cell><ns0:cell>&#8722;0.005</ns0:cell><ns0:cell>0.008</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;0.61</ns0:cell><ns0:cell>0.545</ns0:cell></ns0:row><ns0:row><ns0:cell>Dementia</ns0:cell><ns0:cell>0.463</ns0:cell><ns0:cell>0.116</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>4.01</ns0:cell><ns0:cell>&lt;.0001</ns0:cell></ns0:row><ns0:row><ns0:cell>Short-term rehabilitation ward</ns0:cell><ns0:cell>&#8722;0.309</ns0:cell><ns0:cell>0.135</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;2.29</ns0:cell><ns0:cell>0.022</ns0:cell></ns0:row></ns0:table><ns0:note>2PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_22'><ns0:head>Table 8 (on next page)</ns0:head><ns0:label>8</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_23'><ns0:head>1 Table 8 Model estimates of outdoor activities in the preceding week: random effects Institution Estimate Std Err Pred df t value Pr &gt; |t|</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>InstId 1</ns0:cell><ns0:cell>&#8722;0.451</ns0:cell><ns0:cell>0.191</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;2.36</ns0:cell><ns0:cell>0.019</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 2</ns0:cell><ns0:cell>0.583</ns0:cell><ns0:cell>0.177</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>3.28</ns0:cell><ns0:cell>0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 3</ns0:cell><ns0:cell>&#8722;0.2667</ns0:cell><ns0:cell>0.170</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;1.57</ns0:cell><ns0:cell>0.116</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 4</ns0:cell><ns0:cell>&#8722;0.047</ns0:cell><ns0:cell>0.219</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;0.21</ns0:cell><ns0:cell>0.831</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 5</ns0:cell><ns0:cell>&#8722;0.155</ns0:cell><ns0:cell>0.313</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;0.5</ns0:cell><ns0:cell>0.620</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 6</ns0:cell><ns0:cell>&#8722;0.475</ns0:cell><ns0:cell>0.226</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;2.11</ns0:cell><ns0:cell>0.036</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 7</ns0:cell><ns0:cell>0.674</ns0:cell><ns0:cell>0.152</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>4.42</ns0:cell><ns0:cell>&lt;.0001</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 8</ns0:cell><ns0:cell>&#8722;0.593</ns0:cell><ns0:cell>0.266</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;2.23</ns0:cell><ns0:cell>0.026</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 9</ns0:cell><ns0:cell>0.084</ns0:cell><ns0:cell>0.216</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.39</ns0:cell><ns0:cell>0.698</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 10</ns0:cell><ns0:cell>&#8722;0.055</ns0:cell><ns0:cell>0.151</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;0.36</ns0:cell><ns0:cell>0.718</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 11</ns0:cell><ns0:cell>0.641</ns0:cell><ns0:cell>0.312</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>2.06</ns0:cell><ns0:cell>0.040</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 12</ns0:cell><ns0:cell>0.406</ns0:cell><ns0:cell>0.174</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>2.33</ns0:cell><ns0:cell>0.020</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 13</ns0:cell><ns0:cell>0.141</ns0:cell><ns0:cell>0.224</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.63</ns0:cell><ns0:cell>0.529</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId15</ns0:cell><ns0:cell>&#8722;0.040</ns0:cell><ns0:cell>0.154</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;0.26</ns0:cell><ns0:cell>0.796</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 16</ns0:cell><ns0:cell>&#8722;0.305</ns0:cell><ns0:cell>0.241</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;1.27</ns0:cell><ns0:cell>0.206</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 17</ns0:cell><ns0:cell>0.468</ns0:cell><ns0:cell>0.255</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>1.84</ns0:cell><ns0:cell>0.066</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 19</ns0:cell><ns0:cell>&#8722;0.542</ns0:cell><ns0:cell>0.248</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;2.18</ns0:cell><ns0:cell>0.029</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 20</ns0:cell><ns0:cell>0.135</ns0:cell><ns0:cell>0.245</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.55</ns0:cell><ns0:cell>0.581</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 21</ns0:cell><ns0:cell>&#8722;0.396</ns0:cell><ns0:cell>0.341</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>&#8722;1.16</ns0:cell><ns0:cell>0.247</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 22</ns0:cell><ns0:cell>0.011</ns0:cell><ns0:cell>0.311</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.04</ns0:cell><ns0:cell>0.971</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 23</ns0:cell><ns0:cell>0.181</ns0:cell><ns0:cell>0.244</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.74</ns0:cell><ns0:cell>0.460</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2019:11:42775:2:1:NEW 8 Jul 2020)</ns0:note> </ns0:body> "

"Dear editor PeerJ June 2020 Thank you for your valuable comments to our paper. We have now revised the paper according to the reviewer comments. We reply to the comments in red. On behalf of the authors, Sincerely, Anne Marie Sandvoll Overall the paper has improved substantially. However, it still requires more work to be considered for publication. The two main points are the presentation of the results (tables, figures) and the organization of the text.  Major comments: 1) The method section is disorganized. Please use a structure like provided in the STROBE guideline. (https://www.equator-network.org/wp-content/uploads/2015/10/STROBE_checklist_v4_cross-sectional.pdf) Thank you for this valuable comment. The method section has been organized in line with the STROBE guidelines. 2) Please provide a clear account of the variables used in the analysis. Provide them in one section. I am still not sure how outdoor activities were measures. Please keep description of data collection, analysis and your suspected theoretical considerations separate. For instance line 129 – the variable section is not for described suspected associations between variables. Thank you for this comment. We have now described the variables in one section. 3) There is too much redundancy in the text. For instance, Lines 129-151 and 213-227. Please organize the text accordingly.  The text has been revised, please see previous comment (2). 4) The descriptive reporting is not yet optimal. Please use one descriptive table, which contains all variables used in the model. For numeric variables with means and sd, for categories n (%). For the outdoor activities I would suggest using the median and min, max values. This should also replace figure 1.  We have added descriptive tables and removed figure 1. Please see tables 4, 5 and 6. 5) Methods: Please provide the intraclass correlation based on the unconditional random effect model (ICC1). This will be above 0.05 and will strengthen your argument. A requirement for estimation of this effect is that the same item or subject is rated between at least two judges or raters. The rating is based on replication; without it, there is nothing common to rate. In our design, items are registered by students in one institution but this registration or rating is not replicated by other students or judges. Therefore, we believe that estimation of inter-rater reliability is not relevant in our project. In our view, the random effects of institution are also covering reliability of rating. The students followed a predefined protocol when registrering the activity but the importance of this activity and the attention it receives among management and students are among the unmeasured features we include in the latent attributes which the random effects are assumed to capture. 6) Methods: There is a high number of zeros. Did you consider a zero-inflated Poisson regression model? We also estimated a zero inflated Poisson mixed model with institutions as random effects. It did not show any difference to the model estimated without separate estimation of zero outcomes. This is commented in the text. 7) Discussion: Please make sure you compare apples with apples, is the sampling and the instruments between your study and Björk 2017 comparable? This is a lengthy argument about the weather, and it is outside the data you collected. All in all, I am not convinced this is driving the observed data. Please assess again whether this is really comparable. Thank you for this comment. We have considered this again and we find these studies comparable. Bjørk et al 2017 registered how often the residents in their study went outside the nursing home last week. The same variable was measured in our study. Further, we have discussed the different weather conditions in our part (western) of Norway compared to (southern) parts of Norway and Sweden. Minor comments: 8) Line 119 remove reference. It is to generic to be useful. This sentence has been removed. 9) Line 240 “spurious causal factors” – this does not exist either it is a spurious association or a causal factor, but not both… Thank you for this comment, we have revised this particular part. 10)Line 265-274 Remove this section. I don’t think that this argument holds, since you do not have a random sample. Thank you, this section has been removed. 11)Line 309-312: This belongs if at all in the methods section, it’s pretty much redundant and I would suggest removing table 3. Thank you, we have considered this, and chosen to keep the table as we consider it a relevant table. 12)Line 315-321: Move this to the methods section, this is part of the model specification. Thank you, this has been moved to methods.   13) Table 4: Please limit to three digits after the comma, do it consistently. Please no vertical lines, only one horizontal line under the header… (applies for table 1 too) Thank you for this comment, the table has been revised. 14)Line 283-285: Remove sentence As recommended, we have removed this sentence. Reviewer 2 15) The section „Limitations“ that is now placed in the Method section of the text should rather be placed in the “Strength and weaknesses” section. As recommended by the reviewer we have placed limitations under the strengths and weaknesses section. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Introduction. The Norwegian regulations for nursing homes consider access to meaningful activities to be an indicator for the quality of nursing homes. Activities of daily living (ADL) provide important basic self-care skills for nursing home residents. Due to the physical changes caused by ageing and comorbidities, nursing home residents may experience functional decline over time, which may affect their ability to perform meaningful ADL, such as outdoor activity, which is considered a valuable and meaningful activity in Norwegian culture. This study aimed to investigate the association between ADL status, institution-dwelling and outdoor activity among nursing home residents.</ns0:p><ns0:p>Methods. This cross-sectional study included 784 residents aged &gt;67 years living in 21 nursing homes in 15 Norwegian municipalities between November 2016 and May 2018. The Barthel Index was used to assess the nursing home residents' ADL status. Other variables collected were age, gender, body weight and height, visits per month, institution, ward, and participation in weekly outdoor activities. Descriptive statistics were used to provide an overview of the residents' characteristics. A Poisson regression model was used to test the association between the outdoor activity level as the dependent variable and ADL score, institution, and other control variables as independent variables.</ns0:p><ns0:p>Results. More than half (57%) of the nursing home residents in this sample did not go outdoors. More than 50% of the residents had an ADL score &lt;10, which indicates low performance status. Further, we found that residents' ADL status, institution, ward, and number of visits had an impact on how often the residents went outdoors.</ns0:p><ns0:p>Discussion. The nursing home residents in this study rarely went outdoors, which is interesting because Norwegians appreciate this activity. Differences in the number of visits might explain why some residents went outdoors more often than other residents did. Our findings also highlight that the institutions impact the outdoor activity. How the institutions are organized and how important this activity is considered to be in the institutions determine how often the activity is performed.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion.</ns0:head><ns0:p>The low frequency of the outdoor activities might be explained by a low ADL score. More than 50% of the residents had an ADL score &lt;10, which indicates low performance status. Despite regulations for nursing home quality in Norway, this result suggests that organizational differences matter, which is an important implication for further research, health policy and practice.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Norway is an example of the Nordic welfare model and its welfare state is characterized by public funding and service provision <ns0:ref type='bibr' target='#b11'>(Esping-Andersen et al. 2002)</ns0:ref>. Norwegian nursing homes are publicly financed, and the municipalities are responsible for providing this service. Access to meaningful activities is a reference for the quality of nursing homes as highlighted in Norwegian regulations for nursing homes (Forskr kvalitet i pleie-og omsorgstjenestene 2003). This regulation, with its specific recommendations, can be used as an indicator to assess the quality of care in nursing homes <ns0:ref type='bibr' target='#b26'>(Kirkevold &amp; Engedal 2006)</ns0:ref>. The regulations require the municipalities to ensure that each resident is offered varied and customised activities in line with other fundamentals of care (Forskr kvalitet i pleie-og omsorgstjenestene 2003).</ns0:p><ns0:p>The availability of activities for nursing home residents may contribute to their well-being and dignity <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b29'>Lampinen et al. 2006b;</ns0:ref><ns0:ref type='bibr' target='#b51'>Sletteb&#248; et al. 2016)</ns0:ref>. By contrast, according to <ns0:ref type='bibr' target='#b39'>N&#229;den et al. (2013)</ns0:ref>, the lack of participation in activities in nursing homes may be explained by the residents' physical impairments, e.g., some residents need to use wheelchairs. Up to 80% of nursing home residents experience cognitive impairment <ns0:ref type='bibr' target='#b49'>(Selbaek et al. 2007)</ns0:ref>, which may also limit their ability to participate in activities such as playing cards, bingo and reading groups <ns0:ref type='bibr' target='#b53'>(Str&#248;m et al. 2016)</ns0:ref>.</ns0:p><ns0:p>The outdoor lifestyle traditionally holds a prominent position in Norwegian culture <ns0:ref type='bibr' target='#b16'>(Gurholt &amp; Broch 2019)</ns0:ref> and is considered as a valuable and meaningful activity. Unfortunately, recent inspections undertaken by the authorities in nursing homes in Norway show a lack of activity offerings <ns0:ref type='bibr' target='#b22'>(Helsetilsynet 2018a;</ns0:ref><ns0:ref type='bibr' target='#b23'>Helsetilsynet 2018b;</ns0:ref><ns0:ref type='bibr' target='#b24'>Helsetilsynet 2018c</ns0:ref>). The limited activity options indicate that the government's current policy and new regulations to increase the level of activities in Norwegian nursing homes have not yet succeeded <ns0:ref type='bibr' target='#b22'>(Helsetilsynet 2018a;</ns0:ref><ns0:ref type='bibr' target='#b27'>Kj&#248;s &amp; Havig 2016;</ns0:ref><ns0:ref type='bibr' target='#b45'>Sandvoll et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b47'>Sandvoll et al. 2012)</ns0:ref>.</ns0:p><ns0:p>Despite the new regulations, changing nursing home practices is difficult <ns0:ref type='bibr' target='#b47'>(Sandvoll et al. 2012)</ns0:ref>. According to <ns0:ref type='bibr'>Palacios-Cena et al. (2015)</ns0:ref>, nursing homes should strive to develop meaningful activities for residents to occupy their time and to provide residents with a meaningful sense of purpose. However, low levels of activities of daily living (ADL) among the residents can affect their ability to participate in activities <ns0:ref type='bibr' target='#b4'>(B&#252;rge et al. 2012)</ns0:ref>. ADL are an important basic self-care skill for the general population as well as for nursing home residents.</ns0:p><ns0:p>Because of physical changes associated with ageing and comorbidities, nursing home residents may experience functional decline over time <ns0:ref type='bibr' target='#b8'>(Drageset et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b32'>Liu et al. 2015)</ns0:ref>. Reduced ADL status may impair the ability to perform activities and can impact quality of life, social contact and loneliness <ns0:ref type='bibr' target='#b31'>(Liu et al. 2014b</ns0:ref>). Physical activity, rehabilitation or exercise may improve independence and prevent the decline in ADL in elderly residents in long-term care facilities <ns0:ref type='bibr' target='#b4'>(B&#252;rge et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b5'>Crocker et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b31'>Liu et al. 2014b)</ns0:ref>. It is unclear which interventions are most appropriate for slowing the decline in ADL <ns0:ref type='bibr' target='#b5'>(Crocker et al. 2013</ns0:ref>), but it has been suggested that health professionals should promote physical activities with the aim of improving ADL performance among older adults <ns0:ref type='bibr' target='#b4'>(B&#252;rge et al. 2012)</ns0:ref>. The loss of ADL independence is the strongest predictor of the need for institutionalization of the elderly <ns0:ref type='bibr' target='#b15'>(Gaugler et al. 2007</ns0:ref>).</ns0:p><ns0:p>Several factors might influence nursing home residents' ADL status. Previous research has investigated the importance of ADL related to different aspects, such as loneliness, less participation in activities and depression. <ns0:ref type='bibr' target='#b7'>(Drageset 2004</ns0:ref>) has shown that dependence in ADL status is associated with a high level of social loneliness. <ns0:ref type='bibr' target='#b8'>(Drageset et al. 2011</ns0:ref>) later showed that greater dependence in ADL was associated with more symptoms of depression. Poor balance, incontinence, impaired cognition, low body mass index (BMI), impaired vision, no daily contact with proxies, impaired hearing and the presence of depression were significant risk factors for nursing home residents who experienced a decline in ADL status <ns0:ref type='bibr' target='#b4'>(B&#252;rge et al. 2012)</ns0:ref>.</ns0:p><ns0:p>Few studies have focused on the relationships between ADL status and participation in different activities among nursing home residents. One study investigated physical and social aspects of residents' mobility level and reported that nursing home residents dependent on a wheelchair or elevator during care were less involved in physical and social activities compared with more-mobile residents <ns0:ref type='bibr' target='#b27'>(Kj&#248;s &amp; Havig 2016)</ns0:ref>. This study suggests that reduced mobility might influence participation in different activities offered in the nursing homes. The need for activities and engagement in nursing home residents is well known <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b27'>Kj&#248;s &amp; Havig 2016;</ns0:ref><ns0:ref type='bibr' target='#b28'>Lampinen et al. 2006a;</ns0:ref><ns0:ref type='bibr' target='#b42'>Palacios-Ce&#241;a et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b54'>Theurer et al. 2015)</ns0:ref>. More research is needed on residents' ADL status and its relationship with participation in different activities, such as going outdoors. Despite Norwegian regulations (Forskr kvalitet i pleie-og omsorgstjenestene 2003), the frequency and content of activities are very much up to each nursing home. Previous studies have shown differences between privately owned and government-owned facilities <ns0:ref type='bibr' target='#b30'>(Liu et al. 2014a)</ns0:ref>. Furthermore, previous studies have shown variations in practice regarding activities in Norwegian nursing homes <ns0:ref type='bibr' target='#b25'>(Isaksen et al. 2018)</ns0:ref>. To the best of our knowledge, however, little is known on differences between institutions regarding their outdoor activities.</ns0:p><ns0:p>The aim of this study was to investigate the association between nursing home residents ADL </ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head><ns0:p>A cross-sectional design was used.</ns0:p></ns0:div> <ns0:div><ns0:head>Setting</ns0:head><ns0:p>The data were collected by first-year nursing students during their placement in nursing homes</ns0:p><ns0:p>between November 2016 and May 2018. The placement was either during the autumn semester, i.e., 8 weeks from the middle of October until the middle of December, or 8 weeks during the spring semester, from the middle of April until the middle of June. The data were collected during the daytime by means of a study manual, which the students had been presented in lectures at the university. For standardized instruments and questionnaires, we used the connected manual, procedure or protocol. The process of data collection was supervised by the university teacher and the nurses working at the different nursing homes. </ns0:p></ns0:div> <ns0:div><ns0:head>Participants</ns0:head><ns0:p>The study included 784 residents aged &gt;67 years living in 21 nursing homes in 15 Norwegian municipalities. The inclusion criteria were all residents aged &gt;67 years living in the selected nursing homes, while the exclusion criteria were residents receiving palliative care, related to ethical considerations, to protect them from harm related to the completion of questionnaires in their presence. In addition, residents in the palliative phase may be unable to take part in the outdoor activities described in this paper. Five of the nursing homes were located in rural areas, while others were located in small villages. The nursing homes were not selected completely at random because the selection was partially determined by what nursing homes the nursing students attended during their practice period.</ns0:p></ns0:div> <ns0:div><ns0:head>Variables</ns0:head><ns0:p>We expected increasing levels of outdoor activities, e.g., making trips outside the nursing home, with increasing ADL score because ADL is a measurement of physical capability (higher scores mean better capabilities).We observed the residents by using the method described in the Barthel Index for measuring performance in ADL, as translated and revised by <ns0:ref type='bibr' target='#b44'>Saltvedt et al. (2008)</ns0:ref>.</ns0:p><ns0:p>Each performance item is rated on this scale with a given number of points assigned to each level, related to how dependent or independent the resident is, with maximum of 20 points (20 = totally dependent). The Barthel Index is a standardized, validated and psychometric-tested instrument widely used in the context of elderly care <ns0:ref type='bibr' target='#b32'>(Liu et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b35'>Mahoney &amp; Barthel 1965)</ns0:ref>.</ns0:p><ns0:p>Outdoor activity is the dependent variable in our analysis. In this study, the residents either walked on their own or with assistance from staff or visitors. Some residents went outdoors with a walker or in a wheelchair. Some of the residents had an electric wheelchair and went outside on their own. However, the purpose was still the same: outdoor activity. The level of this activity was measured and documented as the number of times the activity was performed during a week.</ns0:p><ns0:p>Further, we introduce nursing homes as random effects to allow for the fact that not all types of nursing homes are included. These effects will tell us whether activity levels vary between institutions. We included a dummy variable for residing in a short-term/rehabilitation ward and one for residing in a dementia ward. Long-term ward residents are expected to be older, frailer and in need of more care; thus, we expected these residents to have the lowest levels of making trips outside the nursing home.</ns0:p><ns0:p>The number of visits (per week) is interpreted as a proxy for less social isolation <ns0:ref type='bibr' target='#b7'>(Drageset 2004</ns0:ref>). We expected that more visits would lead to higher levels of outdoor activities. More visits may also mean that relatives engage in this activity, which increases the level of ADL.</ns0:p><ns0:p>Further, we expected decreasing levels of activity with increasing age <ns0:ref type='bibr' target='#b12'>(Feng et al. 2017</ns0:ref>).</ns0:p><ns0:p>The gender dummy variable was coded as 1 for men and 0 for women. We had no specific expectations for a gender effect on making trips outside the nursing home.</ns0:p><ns0:p>BMI is an indication of the general health condition. A low BMI indicates that residents are not eating enough (or that they fail to maintain their body weight). We expected that low BMI would be associated with fewer trips outside the nursing home. </ns0:p></ns0:div> <ns0:div><ns0:head>Bias</ns0:head><ns0:p>There are some limitations in using this approach. The sample is not completely randomized since the nursing homes were not selected at random, neither were the residents in the nursing homes. The students may also understand the concept differently or they did not apply it consistently. However, a detailed protocol was provided to the students so that their observations were made consistently. For instance, what date format should be used, and age and length of stay should be integer numbers. We could not eliminate ambivalence in the data collection completely.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical methods</ns0:head><ns0:p>Descriptive statistics were used to give an overview of the demographic and clinical characteristics of the participants, including age, gender, BMI, ADL status, institution and the prevalence of residents' outdoor activities. We sorted the informants into different groups according to the quartiles from the distribution of ADL scores. We then analysed the levels of the outdoor activities between these groups. Manuscript to be reviewed thereby eliminating possible spurious factors. We also included institutions as an independent variable, assuming they are random effects, which allows the coefficients to vary between institutions.</ns0:p><ns0:p>We assume that institutions (nursing homes) represent several unmeasured characteristics that vary between them. These characteristics may be different service quality, different Clustering occurs when entities are distributed on several levels. When this is the case, error terms within a cluster will not be independently distributed of error terms in another cluster <ns0:ref type='bibr' target='#b55'>(Trutschel et al. 2017</ns0:ref>). In our design, this means that error terms between nursing homes will be biased if they are not accounted for in the regression model. We have already considered different ward types because the chance of a resident performing the activity may be affected by the ward type in which the resident lives. Nursing homes (institutions) and ward types are two cluster types; therefore, we should also consider differences between nursing homes in the regression model. The table A1 (appendix A) shows the goodness-of-fit values for the regression model with trips outside the nursing home in the preceding week as the dependent variable. The dispersion criteria &#61539; 2 /df has a value &lt;2. Therefore, we assumed no overdispersion in the model.</ns0:p><ns0:p>Further, we computed the intraclass correlation (ICC1) from the estimated model. This was performed by using a function in R, since SAS does not provide this statistic (L&#252;decke 2020a).</ns0:p><ns0:p>The correlation is calculated as the random effect variance divided by the sum of this variance plus the residual variance. The conditional ICC1 takes the fixed effects into consideration as well as the random effects <ns0:ref type='bibr' target='#b34'>(L&#252;decke 2020b</ns0:ref>). The estimated conditional ICC1 is 0,145 which means the cluster effects account for almost 15% of the variation in dependent variable making trips outdoors. The model estimated in R (function glmer) gives the same results as with the GLIMMIX procedure in SAS using the Laplace maximum likelihood method.</ns0:p><ns0:p>Except for the ICC1, all statistical analyses were performed using SAS software (University Edition; SAS Institute, Cary, NC, USA).</ns0:p></ns0:div> <ns0:div><ns0:head>Ethics</ns0:head><ns0:p>The Regional Medical Ethics Committee (REK West), University of Bergen (2015/2030 REK WEST, University of Bergen) and the Norwegian Social Science Data Services (46303) approved the study, which was endorsed by all nursing homes. Voluntary, written informed consent was obtained from all participants. In situations where the resident was not able to give consent related to e.g., dementia or cognitive impairment, either the resident's relatives or the department manager gave consent.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The sample (n = 784), included more women (69%) than men (31%), , which is consistent with the population distribution in this age group <ns0:ref type='bibr' target='#b52'>(Statistisk Sentralbyr&#229; 2016)</ns0:ref>. Most residents in our sample (55%) resided in a long-term facility, 26% resided in a dementia ward and 19% resided in a short-term ward. The mean ADL score was 10.1. We distributed residents into groups according to their ADL score using the quartiles from the ADL distribution, which resulted in about the same number of residents in each group. Twenty-eight per cent of the residents had an ADL score of 0-6 points as measured by the Barthel Index, 24% had an ADL score of 7-10 points, 26% had an ADL score of 11-14 points and 23% had an ADL score &gt;15 points.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_5'>1</ns0:ref> shows descriptive statistics for the dependent variable, trip outdoors last week. Table <ns0:ref type='table'>2</ns0:ref> shows descriptive statistics for the continuous independent variables while Table <ns0:ref type='table'>3</ns0:ref> shows descriptive statistics for categorical independent variables. Manuscript to be reviewed</ns0:p><ns0:p>Nursing homes are used as cluster variables for estimating random effects. The range is from 5 to 123 registrations per nursing home. The average was 37 registrations while the standard deviation was 31, suggesting high variation in registrations. The nursing homes also vary considerably in size which explains some, but not all of this variation Table <ns0:ref type='table'>4</ns0:ref> show the results of the model estimation with outdoor activities in the preceding week as the dependent variable. The table shows the fixed effects in the model. The random effects are available in appendix B (table <ns0:ref type='table'>A2</ns0:ref>). These are obtained by using a random intercept model, one for each nursing home, which implies that the fixed effects are assumed to be constant over all nursing homes. Long-term ward type is the reference case for ward types and its effect is measured by the model's general intercept.</ns0:p><ns0:p>The ADL score has a significant impact on the activity. An increase in the ADL score of 1 was expected to give an increase in the rate of activity level of 1.05. We show this effect by considering two residents, both women aged 85 years, living in a long-term ward, receiving 6 visits per month and having a BMI of 23.8 kg/m 2 (the last two numbers are median values). Both women live in institution number 1. Resident A had an ADL score of 10, while resident B had an ADL score of 15. From our model, we expected resident A to take 0.43 trips outside the nursing home in the preceding week and resident B to take 0.56 trips. Accordingly, we expected that 16 days would be needed for resident A to take one trip outdoors and 13 days would be needed for resident B. Had the two residents lived in institution number 7, the expected number of trips would have been 1.3 and 1.7 trips outdoors, assuming values for age, number of visits, BMI and gender stay the same and ADL score is 10 and 15, respectively, as above. In other words, both residents A and B would have three times more outdoor activities if they had been living in institution 7 instead of 1. This result shows that institutions have an impact on activity level. This is confirmed by estimation of institutional random effects (table <ns0:ref type='table'>A2</ns0:ref>) where eight institutions have significant effects, four of them are positive. Table <ns0:ref type='table'>4</ns0:ref> also shows that age, visits per month and ward type had significant effects on the number of outdoor activities during the week. All effects were as expected: i.e., increasing age was associated with a lower activity level, whereas an increasing number of visits were associated with more trips outside the nursing home. The relative risk factor for age shows that a resident with 80 years is assumed to have 0.8 less trips outdoors previous week compared to a resident with 70 years, assuming all other variables are held constant and that they reside in the same institution. Also, with the same assumptions, a resident receiving 10 visits per month is expected to have 1.3 more trips outdoors compared to a resident receiving only one visit per month.</ns0:p><ns0:p>The effects of short-term wards were negative, indicating that residents in that ward type took significantly fewer trips outside the nursing home than did residents in the long-term ward. On the other hand, residents in dementia wards took significantly more trips outdoors than residents in long-term wards. Based on the assumptions outlined above, the risk factors show that a resident in the dementia ward had almost 1.6 more trips outdoors in the previous week compared to a resident in the long-term ward. A resident in the short-term ward had 0.7 less trips. Gender and BMI had no significant effect on the number of outdoor activities.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Our findings show that institutions are important predictors for the level of trips made outdoors by residents. Age and BMI index had significant effects, both negative since increasing age and BMI led to fewer trips outdoors. Visits per month had a significant positive effect, more visits led to more trips outdoors. In addition, ADL-score had a significant effect on the activity, the lower the score, the lower the activity level. Further, our findings show that 57% of the nursing home residents in this sample did not go outdoors. This is consistent with other studies showing that the activities offered in nursing homes are limited <ns0:ref type='bibr' target='#b27'>(Kj&#248;s &amp; Havig 2016)</ns0:ref> and that the residents often are inactive <ns0:ref type='bibr' target='#b18'>(Harper Ice 2002)</ns0:ref>. Recent inspections of nursing homes undertaken by the Norwegian authorities confirm the lack of activity offerings <ns0:ref type='bibr' target='#b22'>(Helsetilsynet 2018a;</ns0:ref><ns0:ref type='bibr' target='#b23'>Helsetilsynet 2018b;</ns0:ref><ns0:ref type='bibr' target='#b24'>Helsetilsynet 2018c)</ns0:ref>.</ns0:p><ns0:p>The findings of our study might be explained by the residents' ADL score, which was low:</ns0:p><ns0:p>i.e., 50% of the residents had an ADL score between 0 and 10. These low ADL scores indicate that these residents had a low ability to go outdoors. This is consistent with national health policies in Norway, which emphasize that the frailest elderly should receive care in nursing homes. It is also in line with previous research that shows that the frailest residents might not be able to go outdoors because of their old age, fatigue, frailty or illness <ns0:ref type='bibr' target='#b39'>(N&#229;den et al. 2013</ns0:ref>).</ns0:p><ns0:p>However, <ns0:ref type='bibr' target='#b2'>Bj&#246;rk et al. (2017)</ns0:ref> performed a similar study in Sweden and reported that 60% of the nursing home residents had gone outdoors during the data collection period (November 2013-September 2014). The differences in going outside the nursing home in these similar studies from the Scandinavian health-care context are interesting. Weather and the need for appropriate clothing or equipment can impede the ability of residents to go outdoors. If <ns0:ref type='bibr' target='#b2'>Bj&#246;rk et al. (2017)</ns0:ref> collected data during the summer, it might explain some of these differences. Our data were collected either during autumn or spring. In Norway the temperature and weather conditions often are warmer and contain less rain during July and August, and the residents are more likely to go outdoors. This might explain why the residents in the Swedish study went outside more often <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017</ns0:ref>). Further, our data were collected in the western part of Norway which has more rain compared to the eastern parts of Norway where most people live.</ns0:p><ns0:p>In addition, these residents might not have proper clothing like raincoats, warm jackets, appropriate shoes or hats suitable for the different weather conditions. The British Broadcasting Corporation (BBC 2018) has shown how the use of a rickshaw with a roof and cover may be an alternative for helping frail elderly people to perform outdoor activities despite their loss in ADL status. The concept of outdoor life, in particular hiking, has a prominent position in the Norwegian culture <ns0:ref type='bibr' target='#b16'>(Gurholt &amp; Broch 2019)</ns0:ref>. In addition, most of the older population in Norway grew up after the last world war; therefore, many have received basic socialization in outdoor life and have maintained their association with outdoor activities throughout their lives <ns0:ref type='bibr' target='#b40'>(Odden 2008)</ns0:ref>. Our findings highlight that institutions have an impact on how often residents go outdoors.</ns0:p><ns0:p>These findings suggest that organizational differences impact outdoor activity. How the institutions are organized and the importance they give this activity obviously determine how often it is performed. These findings are in line with <ns0:ref type='bibr' target='#b25'>Isaksen et al. (2018)</ns0:ref>, who found that only four of 17 nursing homes had activity plans for the wards. Further, they found variations in staff who had participated in training program regarding activities for the residents <ns0:ref type='bibr' target='#b25'>(Isaksen et al. 2018)</ns0:ref>. Even if the service going outdoor is regulated by national regulations (Forskr kvalitet i pleie-og omsorgstjenestene 2003), there is considerable room for adaption in each nursing home. The variation in service provision between nursing homes comes from different cultures, organizational practices and plainly the priority the service gets when set against other services the nursing homes are obliged to provide <ns0:ref type='bibr' target='#b38'>(Nakrem 2015)</ns0:ref>. To increase the level of activity, Manuscript to be reviewed</ns0:p><ns0:p>students should be given more information about the benefits of the activity for nursing home residents as well as the legal rights of this activity. Physical activity is important for mental well-being among elderly people <ns0:ref type='bibr' target='#b29'>(Lampinen et al. 2006b</ns0:ref>). However, our findings show that increasing age was associated with lower activity levels, which is also in line with <ns0:ref type='bibr' target='#b12'>Feng et al. (2017)</ns0:ref>. This might imply a natural change from being active to being less active and in need for assistance, which corresponds with the process of disengagement described by Cumming and Henry in 1961 <ns0:ref type='bibr' target='#b9'>(Daatland &amp; Solem 2011)</ns0:ref>. When people get older, it is natural for them to gradually withdraw from their social roles and the activities they used to perform. This is in line with <ns0:ref type='bibr' target='#b0'>Adams et al. (2011)</ns0:ref>, who found that activity participation in late life changed from an active social life with creative activities to an increased participation in passive social and spiritual activities. Nursing homes must consider this and meet their residents' individual needs and interests. According to the Norwegian quality regulations, nursing home residents should be offered varied and customized activities (Forskr kvalitet i pleie-og omsorgstjenestene 2003). Nursing homes need to facilitate activities that are suitable for each resident's ADL status and individual wishes. For example, it might be important for residents to have their own personal things near their own chair. A nearby table might contain personal important objects, such as magazines, books, newspapers or medicines <ns0:ref type='bibr' target='#b3'>(Board &amp; McCormack 2018)</ns0:ref>. Nursing home residents who are no longer capable or do not want to go outside might appreciate a nice view <ns0:ref type='bibr' target='#b10'>(Eijkelenboom et al. 2017)</ns0:ref>. Activities are a basic need and participation in activities might contribute to the well-being and dignity experienced by nursing home residents <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b29'>Lampinen et al. 2006b;</ns0:ref><ns0:ref type='bibr' target='#b51'>Sletteb&#248; et al. 2016)</ns0:ref>. Such activities should be organized by the staff in close co-operation with relatives because they are familiar with the residents' needs <ns0:ref type='bibr' target='#b47'>(Sandvoll et al. 2012)</ns0:ref>.</ns0:p><ns0:p>Previous research shows that nursing home staff are committed to routines, such as helping residents with personal care, practical help, nutrition and toileting <ns0:ref type='bibr' target='#b17'>(Harnett 2010;</ns0:ref><ns0:ref type='bibr' target='#b47'>Sandvoll et al. 2012</ns0:ref>), but do not always take a person-centred approach (McCormack 2016) in terms of their activities. Nursing homes often lack the opportunity and time to offer activities for all residents and their staff recognize that some residents may spend time sitting alone even though staff members know that they might have preferred to join in activities <ns0:ref type='bibr' target='#b46'>(Sandvoll et al. 2015)</ns0:ref>. Could the lack of staff explain our study results? Our findings show that visits per month and ward type had a significant effect on number of outdoor activities during the week. An increasing number Manuscript to be reviewed of visits were associated with more trips outside the nursing home. This shows that the visits (from family or volunteers) have an impact on resident's level of activities regarding outdoor activity. In Norway, the government has addressed new ideas to solve the staff challenges and suggests that voluntary contributions by relatives and organizations should be included as a way of providing activities for nursing home residents (Det kongelige kulturdepartement 2018; Helseog omsorgsdepartementet 2013).</ns0:p><ns0:p>A reform to improve elderly care was introduced in a recent white paper from the Norwegian government. One of the main areas that need improvement in elderly care is activities for elderly people living in nursing homes and the white paper suggests that they should participate in one hour of activity every day (Helse-og omsorgsdepartementet 2018). To provide more activities for nursing home residents, particularly outdoor activities, nursing home staff should be given resources to organize individual, person-centred and customized activities for all residents and to co-ordinate voluntary contributions (e.g., from family members and elderly that want to participate in activities). This is consistent with a recent study by <ns0:ref type='bibr' target='#b50'>Skinner et al. (2018)</ns0:ref>, who found that the voluntary, unpaid contribution took place within cultural, social and other activities aimed at promoting mental stimulation and well-being. Furthermore, they suggested that the staff in government nursing homes should consider voluntary contributions when they plan the care of residents in long-term care <ns0:ref type='bibr' target='#b50'>(Skinner et al. 2018</ns0:ref>). To offer a variety of activities for nursing home residents, activities should be offered both inside and outside the nursing home.</ns0:p><ns0:p>We also encourage the national authorities to specify in white papers that activities for Norwegian nursing home residents should take place both indoors and outdoors. For residents who are unable to go outdoors on their own, rickshaws might serve as an alternative way of enabling them to go outdoors. Our findings show that nursing home residents rarely engage in outdoor activities, even though the need for activities and engagement for nursing home residents is well known internationally <ns0:ref type='bibr' target='#b2'>(Bj&#246;rk et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b27'>Kj&#248;s &amp; Havig 2016;</ns0:ref><ns0:ref type='bibr' target='#b28'>Lampinen et al. 2006a;</ns0:ref><ns0:ref type='bibr' target='#b42'>Palacios-Ce&#241;a et al. 2015;</ns0:ref><ns0:ref type='bibr' target='#b54'>Theurer et al. 2015)</ns0:ref>. Therefore, a greater focus on activities for elderly nursing home residents should be increased and customized in line with each resident's individual needs and wishes. Finally, our results show that the institution that the residents live in has an important association with outdoor activity. This implies that organizational differences in nursing homes might have an impact on outdoor activity, which is an important implication for further research, health policy and practice. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Strengths and weaknesses</ns0:head><ns0:p>The strength of this study is the systematic use of standardized, psychometric-tested instruments and measures <ns0:ref type='bibr' target='#b35'>(Mahoney &amp; Barthel 1965)</ns0:ref>. One weakness is related to the nursing students' observations used to rate ADL. One obligation of research is not to harm participations; i.e., even though self-report is recommended as the gold standard for gathering data <ns0:ref type='bibr' target='#b43'>(Polit &amp; Beck 2017)</ns0:ref>, self-report was considered to be inappropriate for assessing the ADL of these residents. The students' involvement in research might contribute to mutually strengthening research and education. The students used a predefined manual or standardized protocol to assess data, which is an advantage, particularly since the lecture was given immediately before clinical placement.</ns0:p><ns0:p>The data collection was supervised by the university teacher and nurses working at the different nursing homes. This might, on the other side, be a bias in this study because the involvement might serve as a Hawthorne effect <ns0:ref type='bibr' target='#b43'>(Polit &amp; Beck 2017)</ns0:ref>. The participants represent a convenient sample from clinical placements where the university has contracts educating students. In such a way, it might be limited possibilities for generalization of the results to all nursing homes.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>More than half (57%) of the participants in this study did not go outdoors during the preceding week. Their ADL status might explain this pattern because more than 50% of the residents had an ADL score &lt;10, which indicates low performance status. The institutions that the residents live in have an impact on outdoor activity, which suggests that organizational differences matter.</ns0:p><ns0:p>This is an important implication for further research, health policy and practice. Planning for nursing home residents' activities requires staff competence in assessing the capacity and needs of all residents. Those residents with few family members or friends might benefit from visits from volunteers taking on an important function in collaboration with the nursing staff in managing different kind of activities, such as outdoor activities. Our findings show that residents rarely engage in outdoor activities, even though the need for activities and engagement for nursing home residents is well known. Therefore, a greater focus on activities for elderly nursing home residents should be increased and customized in line with each resident's individual needs and wishes. Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2019:11:42775:3:1:NEW 3 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2019:11:42775:3:1:NEW 3 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2019:11:42775:3:1:NEW 3 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2019:11:42775:3:1:NEW 3 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2019:11:42775:3:1:NEW 3 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head /><ns0:label /><ns0:figDesc>All variables were registered in a form and documented in Excel version 16.16.19 (Microsoft, Redmond, WA, USA).</ns0:figDesc><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head /><ns0:label /><ns0:figDesc>To further examine the association between ADL score and outdoor activity, we included age, BMI, gender, visits per month, type of ward and ADL score as well as institutions in a multivariate Poisson regression model. The data were</ns0:figDesc><ns0:table><ns0:row><ns0:cell>analysed using the SAS GLIMMIX procedure with a Poisson log-link function. The two-sided</ns0:cell></ns0:row><ns0:row><ns0:cell>significance level was set to 0.05.</ns0:cell></ns0:row><ns0:row><ns0:cell>We designed a model with outdoor activity as the dependent variable and ADL status as an</ns0:cell></ns0:row></ns0:table><ns0:note>explanatory variable affecting the level of this activity. In addition, we controlled for several other explanatory variables that may have an influence on both activity level and ADL scores,PeerJ reviewing PDF | (2019:11:42775:3:1:NEW 3 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head /><ns0:label /><ns0:figDesc>organizations, different informal routines established among staff, different efficiency in using resources, or different resident characteristics. These characteristics are not measured and probably cannot be measured. Institutions are clusters therefore we include them as random effects in the regression model to account for these variations. On the other hand, the impacts of different ward types are fixed effects since ward types have the same definition for all nursing</ns0:figDesc><ns0:table /><ns0:note>homes and therefore do not measure any latent characteristics. The model is estimated as random intercept model, each institution has an individual-specific random effect in addition to the fixed effects of all other independent variables (SAS Institute 2019). A mixed model with both fixed and random effects that is designed to capture variations between clusters is called a conditional model<ns0:ref type='bibr' target='#b37'>(Muff et al. 2016)</ns0:ref>.The model allowed us to control for other regressors when assessing the effect of ADL score or institutions on outdoor activity. Thus, we could compare activity level between residents in the same ward and with the same age, gender, number of visits per month and BMI, but with different ADL scores in different institutions.</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 1 Descriptive statistics for dependent variable, trips outdoors last week Trips outdoors last week</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Min</ns0:cell><ns0:cell>0</ns0:cell></ns0:row><ns0:row><ns0:cell>25 th percentile</ns0:cell><ns0:cell>0</ns0:cell></ns0:row><ns0:row><ns0:cell>Median</ns0:cell><ns0:cell>0</ns0:cell></ns0:row><ns0:row><ns0:cell>75 th percentile</ns0:cell><ns0:cell>1</ns0:cell></ns0:row><ns0:row><ns0:cell>95 th percentile</ns0:cell><ns0:cell>4</ns0:cell></ns0:row><ns0:row><ns0:cell>Max</ns0:cell><ns0:cell>14</ns0:cell></ns0:row><ns0:row><ns0:cell>Number of observations</ns0:cell><ns0:cell>784</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table A2 Model estimates of outdoor activities in the preceding week: random effects</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Institution</ns0:cell><ns0:cell>Estimate</ns0:cell><ns0:cell>Standard Error</ns0:cell><ns0:cell>df</ns0:cell><ns0:cell cols='2'>t value Pr &gt; |t|</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 1</ns0:cell><ns0:cell>-0.430</ns0:cell><ns0:cell>0.1896</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-2.27</ns0:cell><ns0:cell>0.0236</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 2</ns0:cell><ns0:cell>0.595</ns0:cell><ns0:cell>0.1793</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>3.32</ns0:cell><ns0:cell>0.0009</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 3</ns0:cell><ns0:cell>-0.247</ns0:cell><ns0:cell>0.1671</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-1.48</ns0:cell><ns0:cell>0.139</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 4</ns0:cell><ns0:cell>-0.031</ns0:cell><ns0:cell>0.2164</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-0.14</ns0:cell><ns0:cell>0.8872</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 5</ns0:cell><ns0:cell>-0.140</ns0:cell><ns0:cell>0.3083</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-0.45</ns0:cell><ns0:cell>0.6499</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 6</ns0:cell><ns0:cell>-0.453</ns0:cell><ns0:cell>0.2255</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-2.01</ns0:cell><ns0:cell>0.0451</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 7</ns0:cell><ns0:cell>0.689</ns0:cell><ns0:cell>0.1519</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>4.54</ns0:cell><ns0:cell>&lt;.0001</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 8</ns0:cell><ns0:cell>-0.567</ns0:cell><ns0:cell>0.2713</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-2.09</ns0:cell><ns0:cell>0.0371</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 9</ns0:cell><ns0:cell>0.099</ns0:cell><ns0:cell>0.2133</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.46</ns0:cell><ns0:cell>0.6441</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 10</ns0:cell><ns0:cell>-0.036</ns0:cell><ns0:cell>0.1487</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-0.24</ns0:cell><ns0:cell>0.8068</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 11</ns0:cell><ns0:cell>0.630</ns0:cell><ns0:cell>0.3366</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>1.87</ns0:cell><ns0:cell>0.0615</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 12</ns0:cell><ns0:cell>0.420</ns0:cell><ns0:cell>0.1742</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>2.41</ns0:cell><ns0:cell>0.0161</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 13</ns0:cell><ns0:cell>0.155</ns0:cell><ns0:cell>0.2227</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.69</ns0:cell><ns0:cell>0.4881</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 14</ns0:cell><ns0:cell>-0.022</ns0:cell><ns0:cell>0.1521</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-0.14</ns0:cell><ns0:cell>0.8866</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 15</ns0:cell><ns0:cell>-0.284</ns0:cell><ns0:cell>0.2389</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-1.19</ns0:cell><ns0:cell>0.2343</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 16</ns0:cell><ns0:cell>0.472</ns0:cell><ns0:cell>0.2612</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>1.81</ns0:cell><ns0:cell>0.0713</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 17</ns0:cell><ns0:cell>-0.518</ns0:cell><ns0:cell>0.2509</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-2.06</ns0:cell><ns0:cell>0.0395</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 18</ns0:cell><ns0:cell>0.146</ns0:cell><ns0:cell>0.243</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.6</ns0:cell><ns0:cell>0.5478</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 19</ns0:cell><ns0:cell>-0.372</ns0:cell><ns0:cell>0.3453</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>-1.08</ns0:cell><ns0:cell>0.2821</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 20</ns0:cell><ns0:cell>0.021</ns0:cell><ns0:cell>0.3065</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.07</ns0:cell><ns0:cell>0.9453</ns0:cell></ns0:row><ns0:row><ns0:cell>InstId 21</ns0:cell><ns0:cell>0.191</ns0:cell><ns0:cell>0.2434</ns0:cell><ns0:cell>756</ns0:cell><ns0:cell>0.79</ns0:cell><ns0:cell>0.4322</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2019:11:42775:3:1:NEW 3 Sep 2020)</ns0:note> <ns0:note place='foot' n='3'>PeerJ reviewing PDF | (2019:11:42775:3:1:NEW 3 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Dear editor PeerJ August 2020 Thank you again for your valuable comments to our paper. We have now revised the paper according to your comments. We reply to the comments in red. On behalf of the authors, Sincerely, Anne Marie Sandvoll Editor comments (Michael Simon) Minor revisions The paper has improved, yet authors did not adequately respond to some of the remarks. Therefore, please be careful in your response to the comments.  1. Please provide the ICC1. You are right that the ICC1 is used for reliability assessment – but it is also a key indicator for clustering in multilevel models (1-4). This is very important in the context of your analysis as nursing home is a relevant factor.  Thank you for this comment. We have provided the ICC1, please see page 10. The regression model has been re-estimated in this version using the METHOD=laplace option in SAS GLIMMIX. The previous version used METHOD=rspl which is the default. This option is a quasi-maximum-likelihood algorithm, which does not provide the AIC value. The laplace option will provide that value and is a more proper maximum-likelihood algorithm. The differences in parameter estimates between options laplace and rspl is negligible. For the fix effects there is no difference at all except for the intercept. For the random effects, the same institutions have significant effects except for institution #11 whose effect is no longer significant. The signs are the same for all random effects and the size of the effects have roughly the same magnitude using the two method options. We used R for calculating the ICC1 value. R uses the laplace method and the fixed and random effects are exactly the same as for SAS GLIMMIX with laplace option. R does not give p-values for the random effects so GLIMMIX is still the best choice if ICC1 values can be calculated additionally using R. We have used this procedure for the updated version of the article. 2. Please organize statistics section as descriptive and inferential analysis. Specify all variable included in the model as part of the description of the model. Move Table 1 to appendix. Thank you for this comment. The statistic section has been revised and the tables are modified. Table 1 has been moved to appendix A. 3. For the results section please follow the same order as outlined in the statistics section. Tables 2-6 are very disorganized. Please clean up – two tables should be enough. For instance, why do you report gender twice (table 2 and 6)? In table 6 – better report the range of responses (n) and response rates across nursing homes in a narrative. For table 7 – please also report relative risk ratios since these are easier to interpret. Furthermore, provide a short narrative eluding to the size of the found effects Please move table 8 to the appendix, the estimates are not much  informative. Thank you for this comment. The result section has been revised, and the tables are modified, se tables 1-4. Table 8 has been moved to appendix B. 4. The discussion should start with a clear summary of the main results -descriptive and inferential. Thank you for this comment. The discussion has been revised according to your comment. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Households are known to be high-risk locations for the transmission of communicable diseases. Numerous modelling studies have demonstrated the important role of households in sustaining both communicable diseases outbreaks and endemic transmission, and as the focus for control efforts. However, these studies typically assume that households are associated with a single dwelling and have static membership. This assumption does not appropriately reflect households in some populations, such as those in remote Australian Aboriginal and Torres Strait Islander communities, which can be distributed across more than one physical dwelling, leading to the occupancy of individual dwellings changing rapidly over time. In this study, we developed an individual-based model of an infectious disease outbreak in communities with demographic and household structure reflective of a remote Australian Aboriginal community. We used the model to compare the dynamics of unmitigated outbreaks, and outbreaks constrained by a household-focused prophylaxis intervention, in communities exhibiting fluid versus stable dwelling occupancy. We found that fluid dwelling occupancy can lead to larger and faster outbreaks in modelled scenarios, and may interfere with the effectiveness of householdfocused interventions. Our findings suggest that while short-term restrictions on movement between dwellings may be beneficial during outbreaks, in the longer-term, strategies focused on reducing household crowding may be a more effective way to reduce</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>INTRODUCTION</ns0:head><ns0:p>For many infectious diseases, it is assumed that the risk of transmission within households exceeds that in the wider community due to the increased opportunity they provide for repeated and prolonged close contact between the people who live in them <ns0:ref type='bibr' target='#b11'>(Goeyvaerts et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b9'>Endo et al., 2019)</ns0:ref>. Due to this increased risk, households are often the focus of infectious disease control strategies. For example, household contacts of invasive Group A Streptococcus cases are estimated to have a 2000-fold increased risk of developing the disease themselves <ns0:ref type='bibr' target='#b17'>(Oliver et al., 2019)</ns0:ref>. For Meningococcal disease, the equivalent increase in risk is estimated to be between 500-800-times <ns0:ref type='bibr' target='#b7'>(De Wals et al., 1981)</ns0:ref>. As such, prophylaxis of household contacts of cases for both of these infectious diseases is recommended to prevent further spread <ns0:ref type='bibr' target='#b17'>(Oliver et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b7'>De Wals et al., 1981)</ns0:ref>.</ns0:p><ns0:p>Much of our understanding of household structure, and hence its representation in mathematical models of disease transmission comes from descriptions of census data. However, these descriptions frequently rely on the notion of a stable 'nuclear household' (i.e., comprising two parents and their children). This notion may fail to capture the complexities and nuances of populations with very different household structure and dynamics. In many settings, households differ in their composition-the people they contain and their relationships to each other. Households may contain extended family members, multiple family units, and unrelated people. For example, in Thailand, the proportion of households not considered to be 'nuclear' is estimated at close to 50% <ns0:ref type='bibr' target='#b8'>(Dommaraju and Tan, 2014)</ns0:ref>. In Vietnam, this proportion is estimated to be one third, the majority of which are so-called 'stem households' which include adults, their parents, and possibly their children <ns0:ref type='bibr' target='#b8'>(Dommaraju and Tan, 2014)</ns0:ref>. The proportion of households where there is co-residence of children under 15 years of age with older people over 60 differs greatly throughout the world-in Senegal it is 37% , but just 0.2% in the Netherlands (United Nations, Department of <ns0:ref type='bibr'>Economic and Social Affairs, Population Division, 2017)</ns0:ref>.</ns0:p><ns0:p>Patterns of membership of households may also vary over time. People may spend time in multiple housing units, blurring the relationship between the household as a unit of social organisation and the physical dwelling <ns0:ref type='bibr' target='#b18'>(Smith, 1992)</ns0:ref>. For example, a study in Northern Malawi found that households were distributed across between one and twelve dwellings (mean of 1.7 dwellings per household), with between one and nineteen persons occupying each dwelling per night (mean 3.0) <ns0:ref type='bibr' target='#b10'>(Fine et al., 1997)</ns0:ref>. Australian Aboriginal and Torres Strait Islander households can also be distributed across more than one physical dwelling. One study of the occupancy of a single dwelling in a remote Australian Aboriginal community over time revealed that in addition to core residents, the dwelling was also regularly occupied (although less frequently) by an extended household compromising other relatives and close associates <ns0:ref type='bibr' target='#b16'>(Musharbash, 2008)</ns0:ref>. Over the course of just over a year, more than 100 unique people were observed to stay at the dwelling for at least one night. The flux in occupancy of individual dwellings potentially results in an increased risk of introduction into dwellings, and a continually changing population at risk of householdlevel infection transmission, particularly if there is also high rates of overcrowding (27.3% of Indigenous Australians living in remote communities live in households requiring at least one additional bedroom, based on the Canadian National Occupancy Standard for Housing Appropriateness, compared to 5.5% for non-Indigenous Australians, AIHW (2017)). The implications of this type of fluid dwelling occupancy on infectious disease transmission and control are unknown.</ns0:p><ns0:p>In this study, we introduce an individual-based model incorporating a more flexible representation of household membership distributed across multiple dwellings. We calibrate our model to a remote Australian Aboriginal community to capture observed demographic, household and mobility characteristics of the population. We then use the model to simulate unmitigated and mitigated (through a household-focused prophylaxis intervention) outbreaks of an influenza-like illness where the risk of infection transmission between contacts residing in the same dwelling is greater than those in the wider community. Model outputs are compared to those from a more traditional household model assuming stable dwelling occupancy, to quantify the impact of distributed households and fluid dwelling occupancy on the dynamics and control of communicable diseases outbreaks.</ns0:p></ns0:div> <ns0:div><ns0:head>2/12</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:07:50684:1:1:NEW 16 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>MATERIALS AND METHODS</ns0:head></ns0:div> <ns0:div><ns0:head>Individual-based model of population and infection dynamics</ns0:head><ns0:p>Population structure.</ns0:p><ns0:p>Our individual-based model tracks the age and current residence of individuals in a community over time.</ns0:p><ns0:p>The community is comprised of N individuals and H physical dwellings. An individual's age is updated each day, and individuals are lost due to natural death at an age-dependent rate. When a death occurs, a new individual aged zero is born into the population so that the population size N is constant.</ns0:p></ns0:div> <ns0:div><ns0:head>Population mobility.</ns0:head><ns0:p>The mobility model is based on the Australian Indigenous mobility framework proposed in <ns0:ref type='bibr' target='#b16'>(Musharbash, 2008)</ns0:ref>. This study tracked the number of people that stayed at least one night in a particular dwelling in the remote Australian Aboriginal community, Yuendumu during the 221 nights for which this data was recorded (these 221 nights were not continuous, but occurred during the 467 day study period). The cumulative number of nights stayed by each person was reported. The authors identified four types of residents, based on the amount of time spent in the dwelling: so called core residents, who were present 60-100% of the time, regular residents, who were present 20-34% of the time, other residents who stayed less frequently on an on-and-off basis and were present 4-16% of the time, and many sporadic short-term visitors who stayed for between 1-6 nights.</ns0:p><ns0:p>In line with this framework, individuals in our model are assigned (uniformly at random) to a fixed set of three dwellings within their community, which we assume remain fixed over the time frames we are considering in this study (less than one year), and which we refer to as their dwelling set. These dwellings represent their core residence, where they spend most nights, a regularly-visited residence, and an on-off residence, where they stay less frequently on an on-and-off basis (see Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). We refer to individuals who have the same core residence as a core household, while an individual's extended household consists of all core, regular and on-off residents of their dwelling set. An individual's current residence can change due to population mobility. We have two types of mobility in the model: between-dwelling mobility (intra-community); and between-community mobility (inter-community).</ns0:p><ns0:p>Within the community, each day, an individual's current residence is chosen to be either their core, regular or on/off residence with respective probabilities p c , p r and p o , where p c &gt; p r &gt; p o . There is also a small probability p s , where p s &lt; p o and &#8721; i p i = 1, that their current residence will be a dwelling chosen uniformly at random.</ns0:p><ns0:p>To capture inter-community mobility, each day, A individuals (where A is a Poisson distributed random variable with mean &#945;N, and &#945; is the mean per capita migration rate) are chosen uniformly at random to be replaced by immigrants (thus ensuring that community size remains constant). Immigrants are assumed to have a similar age to individuals in the population. This is implemented by specifying that an immigrant will have the same age as an individual selected uniformly at random from the population. Immigrants are assigned a current residence chosen uniformly at random from all dwellings in the community, as are the dwellings which make up their dwelling set (their core, regular and on/off residences). All immigrants are assumed to be susceptible to infection.</ns0:p><ns0:p>In an extended version of the model (described in the supplementary material) we consider an additional type of mobility -the regular influx of temporary visitors into the community due to two types of events: funerals (which take place after the death of a community resident) and reoccurring events, such as sporting matches or festivals. This type of mobility leads to temporary changes in the community size.</ns0:p></ns0:div> <ns0:div><ns0:head>Infection dynamics.</ns0:head><ns0:p>We use an SEIR (Susceptible-Exposed-Infectious-Recovered) transmission model to simulate an outbreak of an influenza-like illness in the community (see Figure <ns0:ref type='figure' target='#fig_0'>1c</ns0:ref>). Individuals in the community are classified according to their infection status: they are either susceptible to infection (i.e., they can acquire the infection from an infectious contact), exposed (i.e., they have a latent infection and are not infectious), infectious (i.e., they have an active infection and can infect susceptible contacts), or recovered (i.e., they have recovered from the infection and are protected from re-infection). This infection status can change over time due to a transmission event, the progression to infectiousness, or due to the clearance of an infection (detailed below).</ns0:p></ns0:div> <ns0:div><ns0:head>3/12</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:07:50684:1:1:NEW 16 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed (b) Individuals identify with three dwellings in their community: their core residence, where they spend most nights, a regularly-visited residence, and an on-off residence, where they stay less frequently on an on-and-off basis. Individuals may also sporadically stay in a dwelling chosen uniformly at random from all dwellings in the community. (c) SEIR outbreak model. Individuals are born susceptible to infection, can become exposed to infection through contact with an infectious person, before progressing to infectiousness, and then become immune to re-infection following recovery from infection.</ns0:p><ns0:p>Each day, individuals with the same current residence make contact with each other (we refer to these contacts as household contacts), and we simulate daily contacts that occur between individuals in the wider community (i.e., between individuals with different current residences, which we refer to as community contacts). These community contacts occur at age-dependent rates c u,v , where c u,v is the daily rate of contact of an individual in age-category u with individuals in age category v. Community contacts are chosen uniformly at random from the pool of individuals in the relevant age category.</ns0:p><ns0:p>If a susceptible person makes contact with an infected individual with a different current residence, the susceptible person becomes infected (entering the exposed class) with probability q. Household contacts (between individuals with the same current residence) are assumed to be more intense than community contacts. We translate this increased intensity into a probability of transmission per contact that is higher by a factor of q &#8805; 1 for these household contacts, compared to community contacts. The duration of latent and active infection are assumed to be exponentially distributed with respective mean duration of 1/&#963; and 1/&#947;. Once an individual clears an infection (and enters the recovered class), they can no longer be infected.</ns0:p><ns0:p>Simulated outbreaks were seeded with one infectious individual (chosen uniformly at random), and with the rest of the population in the susceptible class, and were run until the end of the outbreak (when there were zero infected individuals left in the population).</ns0:p></ns0:div> <ns0:div><ns0:head>Dynamics of a core household-focused prophylaxis intervention.</ns0:head><ns0:p>Finally, we also consider outbreaks where a prophylaxis intervention is administered to the core household members of an infectious person.</ns0:p><ns0:p>We assume that this prophylaxis intervention is administered once an infected person enters the infectious state. We do not explicitly model the onset of symptoms in the model. However, if symptom onset corresponds to the onset of infectiousness, then the timing of this intervention corresponds to there being no delay in the core household receiving prophylaxis from symptom onset of the index case.</ns0:p><ns0:p>We consider outbreak scenarios where the intervention is 100% and 50% effective at protecting the core household from contracting the infection, if they hadn't been previously infected and/or recovered.</ns0:p></ns0:div> <ns0:div><ns0:head>Model parameterisation and description of outbreak simulation scenarios</ns0:head><ns0:p>We parameterised the model to be consistent with demography and mobility in remote Australian Aboriginal and Torres Strait Islander communities.</ns0:p></ns0:div> <ns0:div><ns0:head>4/12</ns0:head><ns0:p>We considered outbreaks in communities of size N = 2500 and N = 500 individuals, with respective number of dwellings H = 358 and H = 80, that are reflective of a large and small-medium community in the NT (Australian Bureau of Statistics, 2018a). With these values, the mean number of core residents per house was 7 and 6.3, respectively. We also explored scenarios in populations with lower numbers of core residents per house (i.e., with either (N, H) = (2500, 833) or (N, H) = (500, 160), so that the mean number of core residents per house was 3 and 3.1, respectively), to explore the impact of fluid dwelling occupancy in less-crowded communities.</ns0:p><ns0:p>Mortality rates and the initial age distribution were taken from the most recent census data of Aboriginal and Torres Strait Islander Australians in the Northern Territory (NT), Australia (Australian Bureau of Statistics, 2018b) (see Figure <ns0:ref type='figure' target='#fig_3'>2(a)</ns0:ref>). We set the intra-community mobility probabilities to be (p c , p r , p o , p s ) = (0.66, 0.23, 0.09, 0.02) based on data (summarised above) of house occupancy over time in a single household from the remote Australian Aboriginal mobility study in Yuendumu <ns0:ref type='bibr' target='#b16'>(Musharbash, 2008)</ns0:ref>. Inter-community mobility patterns are not described in this setting although, anecdotally, Aboriginal Australians are described as having a higher than average rate of mobility compared to non-Aboriginal Australians <ns0:ref type='bibr' target='#b15'>(Morphy, 2007)</ns0:ref>. We set the per capita expected migration rate &#945; to be between [0.002, 0.004] per day, which corresponds to, on average, between [5, 10] migration events per week when the population size N = 2500.</ns0:p><ns0:p>To date, there have been no studies measuring contact patterns outside of households in remote Indigenous Australian communities. Age-dependent contact data that differentiates between household and non-household contacts is available for rural populations in Kenya <ns0:ref type='bibr' target='#b12'>(Kiti et al., 2014)</ns0:ref>, and we used this to specify the age-dependent community contact rates c u,v in our model.</ns0:p><ns0:p>Infection parameters were chosen to be consistent with influenza-like illness: the mean duration of latency 1/&#963; was set to between [1, 3] days, as was the duration of infectiousness 1/&#947;. We do not have data to inform the within-house transmission factor q. Therefore, we considered two different scenarios: a high household-infection risk scenario where q is set between [3, 5], and a medium household-infection risk scenario where q is set between [1, 3]. We set the community transmission probability q to be between [0.002, 0.004] which, in the high household-infection risk scenario, led to outbreaks where greater than 50% of the population became infected, when the outbreaks took off. Results are also provided in the supplementary material where we assumed a higher transmissibility of the infection with q set to be between [0.004, 0.006].</ns0:p><ns0:p>To account for uncertainty in the model parameters, for each population and infection scenario considered, we generated 1000 samples from the parameter space using Latin Hypercube Sampling <ns0:ref type='bibr' target='#b6'>(Blower and Dowlatabadi, 1994)</ns0:ref>. The parameters &#945;, 1/&#963; , 1/&#947;, q, and q were sampled from uniform distributions with upper and lower bounds as described above. All other parameters were held constant.</ns0:p><ns0:p>All outbreak scenarios were re-run in a population assuming stable dwelling occupancy (i.e., with the intra-community mobility probabilities set to (p c , p r , p o , p s ) = (1, 0, 0, 0), and again in populations where the core household-focused prophylaxis interventions, described above, were implemented, to understand the implications of fluid dwelling occupancy on outbreak dynamics and control.</ns0:p><ns0:p>The model is implemented in MATLAB and the code needed to regenerate all figures and tables is available at https://github.com/rhchisholm/transmission-complex-households.</ns0:p></ns0:div> <ns0:div><ns0:head>RESULTS</ns0:head></ns0:div> <ns0:div><ns0:head>Population mobility model leads to dwelling occupancy distributions consistent with observations in a remote Australian Aboriginal community</ns0:head><ns0:p>To determine whether our model leads to dwelling occupancy distributions that are consistent with that observed in Yuendumu, we first set up our model population to have similar characteristics to this community. According to the most recent census data, Yuendumu has a population size N = 759, an average household size of 4.3 (which we used to estimate the number of dwellings H = 176), and people have a median age of 28 (Australian Bureau of Statistics, 2016). We then simulated population and mobility dynamics using our model, collecting occupancy data from all dwellings over 221 nights (randomly selected during a 467 day period), and compared this to the occupancy distribution from the Yuendumu study (data was extracted from Figure <ns0:ref type='figure' target='#fig_0'>10</ns0:ref> in <ns0:ref type='bibr' target='#b16'>(Musharbash, 2008)</ns0:ref> Manuscript to be reviewed which is consistent with other studies reporting household size in remote communities <ns0:ref type='bibr' target='#b14'>(McDonald et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b20'>Vino et al., 2017)</ns0:ref>. There are clear steps in the distribution of the cumulative number of nights stayed by different resident types (panels d-h), as was observed in the original study (panel i). We found that the widths of these occupancy steps were a reflection of the number of residents of each type (core, regular, on/off and sporadic visitors) associated with a dwelling, which differed between dwellings (panel e). The observed cumulative occupancy in the Yuendumu dwelling <ns0:ref type='bibr' target='#b16'>(Musharbash, 2008)</ns0:ref> largely matched the distribution of model occupancy from a dwelling with the same number of core, regular and on/off residents as this dwelling (panel i). There was limited overlap of the observed data with the distribution of cumulative occupancy for all houses in the population (comparing panels d and i). However, this was expected, given the difference in the number of residents in the Yuendumu dwelling, compared to the population average in the model (which was much lower). The greatest discrepancy between the observed and model occupancy for the single dwelling with the same number of residents related to the most regularly occupying core residents, with the model consistently underestimating the nights stayed by these residents. This was also the case when we considered the extended model with event migration (Figure <ns0:ref type='figure' target='#fig_0'>S1</ns0:ref>). Nevertheless, both models qualitatively capture the fluid dwelling occupancy observed in a remote Australian Aboriginal community.</ns0:p></ns0:div> <ns0:div><ns0:head>Fluid dwelling occupancy leads to faster, and more-intense outbreaks</ns0:head><ns0:p>We then used our model to simulate outbreaks of an influenza-like illness in communities with a population size and core dwelling size distributions reflective of large and small-medium remote Aboriginal communities in the NT, Australia (the population sizes were 2500 and 500, and the mean number of core residents per dwelling was 7 and 6.3, respectively) (Australian Bureau of Statistics, 2018a). Key model outputs are shown in the main manuscript for large communities, and the analogous outputs for the small-medium communities are provided in the electronic supplementary material. All outbreaks were seeded with a single infectious person, and model outputs (summarised in Tables <ns0:ref type='table' target='#tab_0'>1 and S1</ns0:ref>) were compared to those from equivalent simulations in communities assuming stable dwelling occupancy.</ns0:p><ns0:p>We found that infection introductions were just as likely to lead to outbreaks in communities with fluid dwelling occupancy as they were in communities with stable dwelling occupancy. However, for outbreaks which did take off, those which occurred in communities with fluid dwelling occupancy were consistently more intense than those in communities with stable dwelling occupancy (Figure <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>(a)). That is, in communities with fluid dwelling occupancy, outbreaks were typically larger in overall size (the total number of people infected during outbreaks), had a higher, and earlier peak (the time in the outbreak when the number of infectious people was highest), and had a shorter duration than those in communities with stable dwelling occupancy.</ns0:p><ns0:p>These differences in outbreak intensity were less noticeable when we considered outbreak scenarios (i) with a lower increased risk of infection transmission between contacts residing in the same dwelling compared to those in the wider community (Figure <ns0:ref type='figure' target='#fig_4'>3</ns0:ref> The n th unit of the horizontal axis represents the n th -most regular occupant of a dwelling, and the vertical axis represents the median (black line) and 95%CI (grey shading) for the cumulative number of nights stayed by this occupant; (e-h) The cumulative dwelling occupancy over 221 nights for four exemplar dwellings. Each bar represents a unique individual (coloured according to resident type: core, purple; regular, green; on/off, blue; white, sporadic visitor) who stayed at the dwelling for at least one night, and the height of the bar represents the cumulative number of nights the individual was present (note, a log scale is used). Individuals are shown in order of decreasing occupancy, and the title of each subplot shows the number of (core, regular, on/off) residents for that dwelling at the end of the simulation; (i) Observed occupancy (red dots) vs model occupancy (median and 95%CI from 100 simulations) for a dwelling with 11 core, 12 regular, and 36 on/off residents. Higher outbreak intensity is driven by an increased number of unique, and higher-risk, household contacts.</ns0:p><ns0:p>To understand why communities with fluid dwelling occupancy experienced more intense outbreaks, we inspected the number and types of contacts of infectious people over the course of outbreaks (Figure <ns0:ref type='figure' target='#fig_5'>4</ns0:ref> and S6). We found that the greatest relative difference between the contact patterns of infectious people between the fluid occupancy model (with and without event-based migration) and stable occupancy model was in relation to the number of unique individuals they contacted within dwellings, which was much greater in communities assuming fluid dwelling occupancy compared to stable dwelling occupancy, independent of the community size considered. Neither the number of unique community contacts, nor the total number of contacts of infectious people within or outside of dwellings were as affected by the type of dwelling occupancy model assumed, which suggests that the higher outbreak intensity observed in model communities with fluid versus stable dwelling occupancy was driven by the increased number of unique, and higher-risk, household contacts.</ns0:p></ns0:div> <ns0:div><ns0:head>Fluid dwelling occupancy decreases the impact of a core household-focused prophylaxis intervention</ns0:head><ns0:p>Finally, we explored the effect of fluid dwelling occupancy on the impact of a core household-focused prophylaxis intervention that could be implemented during outbreaks. This intervention was administered to an infected person's core household at the time of infectiousness onset (which was, on average, between 1-3 days post exposure), which protected the core household from contracting the infection, if they hadn't previously been infected and/or recovered.</ns0:p><ns0:p>In all scenarios considered, the intervention reduced outbreak size (Tables <ns0:ref type='table' target='#tab_1'>2, S2 and S3</ns0:ref>), although this occurred to a lesser extent in communities with less crowding in dwellings (likely because the average population coverage of the intervention per treated core household was reduced) (Figures <ns0:ref type='figure' target='#fig_6'>5 and S7</ns0:ref>), or when we considered either a more transmissible pathogen, or a pathogen with a higher relative risk of infection transmission within dwellings (Figures <ns0:ref type='figure' target='#fig_0'>S11(c</ns0:ref>),(d)). In scenarios where we assumed the intervention was 100% effective at protecting a case's core household from contracting the infection, the intervention had a greater impact on outbreak size in communities with stable dwelling occupancy, compared to those with fluid dwelling occupancy (Figures <ns0:ref type='figure' target='#fig_6'>5 and S7</ns0:ref>). In scenarios where we assumed the intervention was 50% effective, there was little to no difference in the impact of the intervention between communities with fluid versus stable dwelling occupancy, unless household crowding was reduced. In this latter case, the 50% effective intervention had a greater impact in communities with stable vs fluid dwelling occupancy (Figures <ns0:ref type='figure' target='#fig_6'>5(c</ns0:ref>),(f)). Again, these results were robust to the sizes of the communities considered (Figure <ns0:ref type='figure'>S8</ns0:ref>), and to the inclusion of event-based mobility in the fluid-household membership model (Figure <ns0:ref type='figure'>S9</ns0:ref>-S10). In some scenarios where we assumed the intervention was 50% effective, the duration of the outbreak was increased by the intervention, although the total size was</ns0:p></ns0:div> <ns0:div><ns0:head>8/12</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:07:50684:1:1:NEW 16 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed medium-level, of increased risk of transmission from household contacts compared to community contacts; and (c) less crowding in dwellings. Each disk with error bars shows the mean of means &#177; one pooled standard deviation of either the total number of contacts, or the total number of unique individuals contacted (as indicated in the plots) during the infectious period of infected individuals, when there is fluid dwelling occupancy (red, solid lines); fluid dwelling occupancy with event-based migration (blue, dotted lines); compared to when there is stable dwelling occupancy (black, dash-dot lines). reduced <ns0:ref type='bibr'>(Figures 5(a)</ns0:ref>,(d), S7(a),(c),(d),(f), S8(g),(i),(j),(l), S9(a),(d),(g),(i),(j),(l) and S10(g),(j)). This occurred more frequently in communities of size 2500, and when we considered a more transmissible pathogen. </ns0:p></ns0:div> <ns0:div><ns0:head>DISCUSSION</ns0:head><ns0:p>It is generally assumed that households are associated with a single physical dwelling which is considered to be a high-risk location for the transmission of many infectious diseases. However, the assumption of a one-to-one correspondence between households and dwellings does not appropriately reflect households in some populations, such as the Australian Aboriginal and Torres Strait Islander communities considered here, where households can extend across multiple physical dwellings leading to fluid groups of people occupying individual dwellings. In this study, we showed that communities made up of such extended households have the potential to experience larger and more intense outbreaks of infectious diseases spread by close contact, particularly when there are high levels of household crowding. In our model with fluid dwelling occupancy, the extended household of an individual does not, in general, overlap with that of others in their extended household. Thus, multiple extended households can be connected via shared members, leading to large pools of individuals at greater risk of quickly contracting an infection and spreading it to other extended households, and to faster and larger outbreaks. For pathogens where there is even greater relative risk of infection transmission between household contacts compared to between community contacts, the risk of onward transmission beyond an extended household is amplified further, leading to even larger discrepancies in outbreak intensity between model communities characterised by fluid versus stable dwelling occupancy.</ns0:p><ns0:p>These reflections also help to explain why smaller discrepancies in outbreak intensity were observed between communities with different dwelling occupancy models when either household crowding was reduced or a more-transmissible pathogen was considered. In both of these scenarios, the lower-risk community contacts contributed much more to widespread transmission because, in the first scenario, the number of household contacts was significantly reduced, and in the latter scenario, the overall risk of infection transmission from the more-frequent community contacts had increased.</ns0:p></ns0:div> <ns0:div><ns0:head>Implications for infectious disease control</ns0:head><ns0:p>Our findings contribute to the evidence base that supports reducing household overcrowding as an effective strategy to decrease the risk of severe outbreaks in populations with fluid dwelling occupancy <ns0:ref type='bibr'>(World Health Organization, 2018)</ns0:ref>. They also highlight the limitations of household-focused interventions in these settings, which suggests that such interventions should be scaled up to reflect the interconnectedness of households. Our findings also suggest that an intervention that reduces the number of unique household contacts during an outbreak by, for example, limiting the amount of movement between dwellings, may </ns0:p></ns0:div> <ns0:div><ns0:head>Model limitations</ns0:head><ns0:p>Our study of the impact of a household-focused intervention considered scenarios where the intervention could be implemented at the time of infectiousness onset (on average 1-3 days post exposure). This may not be possible for Australian Aboriginal and Torres Strait Islander people living in remote communities, where access to health care services can be more challenging compared to people living in regional areas or major cities (AIHW, 2018). Given the higher intensity of outbreaks in communities with fluid vs stable dwelling occupancy, we expect that longer delays in implementation would further reduce the ability of household-focused interventions to constrain outbreaks in these settings.</ns0:p><ns0:p>The mechanistic model of intra-community mobility proposed in this study was based on data describing the cumulative occupancy over a period of time of a single dwelling in one remote Australian Aboriginal community <ns0:ref type='bibr' target='#b16'>(Musharbash, 2008)</ns0:ref> </ns0:p></ns0:div> <ns0:div><ns0:head>CONCLUSIONS</ns0:head><ns0:p>Our study highlights why accounting for correct household structure and dynamics in models of infectious diseases that spread through close contacts can be important when analysing outbreaks and the effects </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Population, mobility and infection model. (a) Intra-and inter-community mobility resultsin the movement of infectious (I) and non-infectious individuals (S,E,R) within and between communities. (b) Individuals identify with three dwellings in their community: their core residence, where they spend most nights, a regularly-visited residence, and an on-off residence, where they stay less frequently on an on-and-off basis. Individuals may also sporadically stay in a dwelling chosen uniformly at random from all dwellings in the community. (c) SEIR outbreak model. Individuals are born susceptible to infection, can become exposed to infection through contact with an infectious person, before progressing to infectiousness, and then become immune to re-infection following recovery from infection.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>using the open-source tool, Engauge Digitizer Version 12.1). A sample of these model outputs is shown in Figure 2. The median of the distribution of the number of current residents over time closely matches the average household size observed in Yuendumu (panel c), and the maximum occupancy in the model fluctuates between 9-22, 5/12 PeerJ reviewing PDF | (2020:07:50684:1:1:NEW 16 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>(b) and Figure S11(a),(b)); (ii) in communities with a lower extent of household overcrowding (Figure 3(c)); and/or (iii) with a more transmissible pathogen (Figure S2(a),(c) and Figure S11(a),(b)). These results were robust to the sizes of the communities considered (Figure S3), and to the inclusion of event-based mobility in the fluid dwelling-occupancy model (Figures S4 and S5).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Population and mobility model outputs from (a-h) one simulation; and (i) 100 simulations, for a community with similar characteristics to Yuendumu (NT, Australia). (a) Age distribution of the population in years; (b) Number of nights that core (purple), regular (green) and on/off (blue) residents occupied their core, regular and on/off dwellings, respectively, over 221 nights; (c) The distribution of the number of current residents in each dwelling over 5 years, showing the median (black line), maximum (blue line), and 95%CI (grey shading); (d) The distribution of cumulative dwelling occupancy over 221 nights for all dwellings.The n th unit of the horizontal axis represents the n th -most regular occupant of a dwelling, and the vertical axis represents the median (black line) and 95%CI (grey shading) for the cumulative number of nights stayed by this occupant; (e-h) The cumulative dwelling occupancy over 221 nights for four exemplar dwellings. Each bar represents a unique individual (coloured according to resident type: core, purple; regular, green; on/off, blue; white, sporadic visitor) who stayed at the dwelling for at least one night, and the height of the bar represents the cumulative number of nights the individual was present (note, a log scale is used). Individuals are shown in order of decreasing occupancy, and the title of each subplot shows the number of (core, regular, on/off) residents for that dwelling at the end of the simulation; (i) Observed occupancy (red dots) vs model occupancy (median and 95%CI from 100 simulations) for a dwelling with 11 core, 12 regular, and 36 on/off residents.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure3. The impact of fluid dwelling occupancy on influenza-like outbreaks in a population of size N = 2500 assuming (a) a high-level; (b) a medium-level, of increased risk of transmission from household contacts compared to community contacts; and (c) less crowding in dwellings. The lines and shading show the median and interquartile ranges of the population prevalence of infection over time when there is fluid dwelling occupancy (red solid line, red shading); compared to when there is stable dwelling occupancy (black dashed line and grey shading).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. The impact of fluid dwelling occupancy on the distribution of the number of contacts of infectious people during outbreaks in a population of size N = 2500 assuming (a) a high-level; (b) a medium-level, of increased risk of transmission from household contacts compared to community contacts; and (c) less crowding in dwellings. Each disk with error bars shows the mean of means &#177; one pooled standard deviation of either the total number of contacts, or the total number of unique individuals contacted (as indicated in the plots) during the infectious period of infected individuals, when there is fluid dwelling occupancy (red, solid lines); fluid dwelling occupancy with event-based migration (blue, dotted lines); compared to when there is stable dwelling occupancy (black, dash-dot lines).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure5. The impact of fluid dwelling occupancy on the effect of a household-focused prophylaxis intervention that is 50% effective and 100% effective in a population of size N = 2500 assuming (a,d) a high-level; and (b,e) a medium-level, of increased risk of transmission from household contacts compared to community contacts; and (c,f) less crowding in dwellings. The lines and shading show the median and interquartile ranges of the population prevalence of infection over time when there is (a-c) fluid dwelling occupancy (unmitigated outbreak: red solid line and shading; with 50% effective intervention: blue dotted line and shading; with 100% effective intervention: magenta dash-dot line and shading); compared to when there is (d-f) stable dwelling occupancy (unmitigated outbreak: black dashed line and shading; with 50% effective intervention: blue dotted line and shading; with 100% effective intervention: magenta dash-dot line and shading).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50684:1:1:NEW 16 Sep 2020) Manuscript to be reviewed reduce outbreak intensity for certain pathogens. Further work could explore the effectiveness of such interventions.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head /><ns0:label /><ns0:figDesc>of interventions. Our analysis suggests that in populations with fluid dwelling occupancy, short-term restrictions on movement between dwellings may be beneficial during outbreaks, and possibly improve the effectiveness of household-focused prophylaxis interventions. However, in the longer-term, pre-emptive strategies focused on reducing household crowding may be a more effective way to reduce the risk of severe outbreaks occurring in such populations. Pathogens which do not spread via close contacts, for example, those which spread via vectors or which are sexually transmitted, may not necessarily have different outbreak dynamics and responses to interventions in communities with fluid versus stable dwelling occupancy. Further work could explore the implications of complex household structure and mobility for such pathogens, as well as those which are endemic in populations.</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Statistics from model scenarios of unmitigated outbreaks in communities of size 2500, including percentage of simulations that led to an outbreak (take off %), and the median (50%CIs) of the outbreak duration and final size.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Scenario</ns0:cell><ns0:cell>Dwelling occupancy</ns0:cell><ns0:cell cols='2'>Take off (%) Duration (days)</ns0:cell><ns0:cell>Final size</ns0:cell></ns0:row><ns0:row><ns0:cell>Baseline</ns0:cell><ns0:cell>fluid</ns0:cell><ns0:cell>52.8</ns0:cell><ns0:cell>112 (91,136)</ns0:cell><ns0:cell>1760 (1304,2040)</ns0:cell></ns0:row><ns0:row><ns0:cell>Baseline</ns0:cell><ns0:cell>stable</ns0:cell><ns0:cell>52.3</ns0:cell><ns0:cell>129 (105,160)</ns0:cell><ns0:cell>1494 (1073,1789)</ns0:cell></ns0:row><ns0:row><ns0:cell>Lower q</ns0:cell><ns0:cell>fluid</ns0:cell><ns0:cell>37.7</ns0:cell><ns0:cell>139 (104,179)</ns0:cell><ns0:cell>1051 (507,1414)</ns0:cell></ns0:row><ns0:row><ns0:cell>Lower q</ns0:cell><ns0:cell>stable</ns0:cell><ns0:cell>34.3</ns0:cell><ns0:cell>141 (112,183)</ns0:cell><ns0:cell>995 (473,1319)</ns0:cell></ns0:row><ns0:row><ns0:cell>Less crowded</ns0:cell><ns0:cell>fluid</ns0:cell><ns0:cell>33.8</ns0:cell><ns0:cell>147 (117,184)</ns0:cell><ns0:cell>910 (446,1276)</ns0:cell></ns0:row><ns0:row><ns0:cell>Less crowded</ns0:cell><ns0:cell>stable</ns0:cell><ns0:cell>33</ns0:cell><ns0:cell>140 (88,181)</ns0:cell><ns0:cell>725 (118,1070)</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Statistics from model scenarios of mitigated outbreaks in communities of size 2500, including the percentage reduction in the median value of the outbreak duration and final size, compared to the equivalent unmitigated scenarios, for 100% and 50% effective interventions.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Scenario</ns0:cell><ns0:cell>Dwelling occupancy</ns0:cell><ns0:cell cols='2'>Median duration reduction (%) with intervention effect 100% 50%</ns0:cell><ns0:cell cols='2'>Median final size reduction (%) with intervention effect 100% 50%</ns0:cell></ns0:row><ns0:row><ns0:cell>Baseline</ns0:cell><ns0:cell>fluid</ns0:cell><ns0:cell>29</ns0:cell><ns0:cell>-4</ns0:cell><ns0:cell>87</ns0:cell><ns0:cell>48</ns0:cell></ns0:row><ns0:row><ns0:cell>Baseline</ns0:cell><ns0:cell>stable</ns0:cell><ns0:cell>55</ns0:cell><ns0:cell>-2</ns0:cell><ns0:cell>97</ns0:cell><ns0:cell>49</ns0:cell></ns0:row><ns0:row><ns0:cell>Lower q</ns0:cell><ns0:cell>fluid</ns0:cell><ns0:cell>45</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>87</ns0:cell><ns0:cell>61</ns0:cell></ns0:row><ns0:row><ns0:cell>Lower q</ns0:cell><ns0:cell>stable</ns0:cell><ns0:cell>59</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>94</ns0:cell><ns0:cell>61</ns0:cell></ns0:row><ns0:row><ns0:cell>Less crowded</ns0:cell><ns0:cell>fluid</ns0:cell><ns0:cell>35</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>77</ns0:cell><ns0:cell>39</ns0:cell></ns0:row><ns0:row><ns0:cell>Less crowded</ns0:cell><ns0:cell>stable</ns0:cell><ns0:cell>37</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell>85</ns0:cell><ns0:cell>54</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head /><ns0:label /><ns0:figDesc>. While the occupancy distributions generated from our model do resemble this data, it remains an open question whether our model is an accurate reflection of the mechanisms which led to these cumulative patterns. It is also an open question how generalisable this model is to other dwellings in the same community in which the data was collected, to other remote Australian Aboriginal and Torres Strait Islander communities, and to other population settings where households are distributed across multiple dwellings. Longitudinal data of intra-community mobility from multiple dwellings, in multiple communities, and from different populations could help to inform these open questions.</ns0:figDesc><ns0:table /></ns0:figure> <ns0:note place='foot' n='6'>/12 PeerJ reviewing PDF | (2020:07:50684:1:1:NEW 16 Sep 2020)</ns0:note> <ns0:note place='foot' n='7'>/12 PeerJ reviewing PDF | (2020:07:50684:1:1:NEW 16 Sep 2020)</ns0:note> <ns0:note place='foot' n='9'>/12 PeerJ reviewing PDF | (2020:07:50684:1:1:NEW 16 Sep 2020)</ns0:note> <ns0:note place='foot' n='12'>/12 PeerJ reviewing PDF | (2020:07:50684:1:1:NEW 16 Sep 2020)</ns0:note> </ns0:body> "

"‘A model of population dynamics with complex household structure and mobility: implications for transmission and control of communicable diseases’ Response of the authors to the Reviewers We thank the Reviewers for their comments, all of which are addressed below. Quotations from the Reviewers’ reports are coloured blue. A revised version of the paper is appended, with changes in response to Reviewer comments highlighted such that any removed sections are crossed out with a single line and coloured red, and any additions are underlined and coloured blue. Reviewer 1 1. Dwelling occupancy was randomly chosen according to the set of probability pi ’s, which means some dwellings may have an extraordinary number of occupants due to randomness. However, this might not happen in reality because people may avoid already occupied dwellings or make arrangements when to use them. In that case, the number of occupants in each dwelling would be more evened out than under the random-allocation assumption. We agree with the reviewer that there is a small probability that some dwellings could have all of their core, regular and on/off residents present at the one time, with some sporadic visitors. However, in remote communities it is not uncommon to have > 20 people in houses at one time. For example, Vino et al., PeerJ 5:e3958, 2017, found a range of 1–23 people per dwelling, while McDonald et al., Epidemiol. Infect. 136:529-539, 2008, found a median of 17 people per dwelling with IQR 14-21. To illustrate how the distribution of the number of current residents of dwellings changes over time in the model, we now plot the median, 95% CI and maximum number of current residents over time for the Yuendumu-like populations in Figure 2c and Figure S1c. It shows that the maximum number of residents fluctuates between 9–22 in these simulations, and that these fluctuations reduce in size over time and stabilise around 10–15. For scenarios with a higher level of crowding (such as those shown in Figure 3a), the fluctuations in the maximum number of current residents stabilise around 15–22 (these results not shown in the manuscript). We now include the following description of these dynamics in the main manuscript, lines 228–232: “The median of the distribution of the number of current residents over time closely matches the average household size observed in Yuendumu (panel c), and the maximum occupancy in the model fluctuates between 9–22, which is consistent with other studies reporting household size in remote communities (McDonald et al., 2008; Vino et al., 2017).” 2. As the authors adopted LHS, it may be informative to show correlations between the parameter values and the outcome (final size/effectiveness) to assess the sensitivity of the results to the parameter assumptions. 1 In the supplementary material (Figure S11), we now show correlations between the LHS parameter values q̂ and q and the final size, outbreak duration, and percentage reduction in final size due to the two interventions. The relationships between these parameters and outputs are consistent with the other results shown in the manuscript and supplementary material. Results are not shown for the other LHS parameters, but are described in the figure caption of Figure S11: “Similar output for the other parameters sampled via LHS are not shown, but are briefly described here. The migration rate, α, showed no relationship with these outcome variables over the explored range of sampled values. Higher values of the duration of latency 1/σ were associated with a longer outbreak duration, but showed no relationship with other outcome variables. And higher values of the duration of infectiousness 1/γ were associated with a larger final size, a smaller reduction in final size due to both prophylaxis interventions, and showed no relationship with outbreak duration.” 3. L79: please add context of citation. Does Morphy 2007 suggest there is overcrowding (what is definition?) in Aboriginal population? We cited Morphy 2007 in error here. We have included the correct citation, clarifying the context of the citation, and including the definition of overcrowding in lines 81–84: “(27.3% of Indigenous Australians living in remote communities live in households requiring at least one additional bedroom, based on the Canadian National Occupancy Standard for Housing Appropriateness, compared to 5.5% for non-Indigenous Australians, AIHW (2017))” 4. L172-173: I think the representation using a set notation {} here is unclear (a set is usually not ordered). How about explicitly presenting scenarios as a combination of N and H, for example, (N, H) = (2500, 358), (500, 80),. . . ? - L182: ditto; () instead of {} We have removed the use of set notation throughout. For example, in lines 177–183 we have, “We considered outbreaks in communities of size N = 2500 and N = 500 individuals, with respective number of dwellings H = 358 and H = 80, that are reflective of a large and small-medium community in the NT. With these values, the mean number of core residents per house was 7 and 6.3, respectively. We also explored scenarios in populations with lower numbers of core residents per house (i.e., with either (N, H) = (2500, 833) or (N, H) = (500, 160), so that the mean number of core residents per house was 3 and 3.1, respectively), to explore the impact of fluid dwelling occupancy in less-crowded communities.” 5. - Fig2: The readers cannot assess if this is consistent with the observed data in Musharbash 2008. Could there be a comparison between simulated and observed distributions (e.g., bars vs 2 red lines)? In Figures 2 and S1, we now include a comparison between the observed cumulative occupancy data (shown in red in panel i) and the distribution of model occupancy data (the median and 95% CI is shown from 100 simulations) from a house with initially the same number of core, regular and on/off residents as the house where the real data was collected. 6. - Fig2c: The x-scales seem random: I would suggest to use the consistent scale as much as possible for comparability. The x and y scales of plots of the cumulative occupancy for single dwellings shown in Figure 2e–h and S1e–h now have the same scale. Also, only 4 dwellings are now shown, instead of 12, to accommodate the additional plots now included in figure 2. One of these extra plots (panel d) is of the distribution of the cumulative occupancy of all dwellings in the simulation, to illustrate the variability among all dwellings. 7. - Fig5: The 4 curves and shades overlapping each other makes the figure very difficult to read. Could there be any alternative way, e.g., separating fluid and stable occupancy curves in different panels? We have now separated all plots showing the effect of the interventions into those showing scenarios assuming fluid occupancy and those showing scenarios assuming stable occupancy. Now each subplot only has 3 curves: the unmitigated scenario, the 50% effective intervention scenario, and the 100% effective intervention scenario 8. - L269-271, 274-276: I would say there was a slight difference with 100% effectiveness and not difference with 50% for Baseline and Lower q scenarios according to Table 2. Also, 100% effectiveness may be rather unrealistic given that timely prophylaxis at time of infection of an idex case would be rarely possible, especially when the model considers a remote population where medical resource might not be fully available. We agree with the reviewer on the first point, and have changed the wording in the section describing these results. It now reads, lines 291–302, “In all scenarios considered, the intervention reduced outbreak size (Tables 2, S2 and S3), although this occurred to a lesser extent in communities with less crowding in dwellings (likely because the average population coverage of the intervention per treated core household was reduced) (Figures 5 and S7), or when we considered either a more transmissible pathogen, or a pathogen with a higher relative risk of infection transmission within dwellings (Figures S11(c),(d)). In scenarios where we assumed the intervention was 100% effective at protecting a case’s core household from contracting the infection, the intervention had a slightly greater impact on outbreak size in communities with 3 stable dwelling occupancy, compared to those with fluid dwelling occupancy (Figures 5 and S7). In scenarios where we assumed the intervention was 50% effective, there was little to no difference in the impact of the intervention between communities with fluid versus stable dwelling occupancy, unless household crowding was reduced. In this latter case, the 50% effective intervention had a greater impact in communities with stable vs fluid dwelling occupancy (Figures 5(c),(f)).” Regarding the second point, we model the implementation of the intervention at the time of infectiousness onset, rather than the time of infection, as described in lines 168–171, “We assume that this prophylaxis intervention is administered once an infected person enters the infectious state. We do not explicitly model the onset of symptoms in the model. However, if symptom onset corresponds to the onset of infectiousness, then the timing of this intervention corresponds to there being no delay in the core household receiving prophylaxis from symptom onset of the index case.” We now provide a short discussion on the limitations of this assumption in the discussion, lines 344–350, “ Our study of the impact of a household-focused intervention considered scenarios where the intervention could be implemented at the time of infectiousness onset (on average 1–3 days post exposure). This may not be possible for Australian Aboriginal and Torres Strait Islander people living in remote communities, where access to health care services can be more challenging compared to people living in regional areas or major cities (AIHW (2018)). Given the higher intensity of outbreaks in communities with fluid vs stable dwelling occupancy, we expect that longer delays in implementation would further reduce the ability of household-focused interventions to constrain outbreaks in these settings. ” Reviewer 2 1. An improvement is recommended for figures 2c, S1c . The plot titles indicate the final numbers of core, regular, and on/off residents, but the distribution of cumulative nights stayed for each class would be more interesting. Since each bar represents a unique individual, I suggest colour-coding and grouping according to residential class within each plot. In figures 2 and S1 we have replaced the distributions for the number of core, regular and on/off residents in dwellings with the distribution of the cumulative number of nights stayed by core, regular and on/off residents in their respective core, regular and on/off dwellings. We also colour code the bars in the plots of the cumulative occupancy (for four exemplar dwellings) according to resident type, as suggested by the reviewer. 2. Findings appear sound except for figure 2 and figure S1. 1. Figures 2a and 2b seem identical to figures S1a and S1b, respectively. This is strange since figures 2c and S1c are mutually distinct 4 although still very similar. If this is accurate then it requires comment or explanation, and if it is to be expected from the model then displaying figures S1a, S1b is redundant and they should be removed. Similarly, the plot titles in figures 2c and S1c are surprisingly matched even though the plots are not quite. This requires explanation or comment. The similarity between these subplots in the two figures is expected as both simulations were initialised with exactly the same population. In panels a and b, only the permanent residents of the population were represented in these plots, although this was not made clear in the original manuscript. We have since replaced the distributions for the number of core, regular and on/off residents in dwellings (panel b) with the distribution of the cumulative number of nights stayed by core, regular and on/off residents in their respective core, regular and on/off dwellings, as described above. In panel c (now panel e–h), the titles are the same between figures as the occupancy from the same set of households was chosen to be displayed. To clarify these points, we have added the following explanations in the figure caption of Figure S1: “All simulations presented here were initialised with the same population as those presented in Figure 2 in the main text.” “(a) Age distribution of the population (of permanent residents only) in years;” “Note that the same dwellings are presented here as in Figure 2e–h in the main text which allows them to have the same number of residents of each type, as indicated in the subplot tiles” 3. The tick-labels on the y-axes vary inexplicably between plots in figure S1c. Every multiple of 50 should be indicated on every y-axis, as they are in figure 2c. The ticks and scale of all y axes in panel e in both figures are now the same 4. Page 8/11, line 275, “protected” should be “protecting”, “the core household of a case” would read better as “a case’s core household”. Page 10/11, line 13, “finding” should be “findings”. These have been rectified 5 "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Triploid Chinese white poplar (Populus tomentosa Carr., Salicaceae) has stronger advantages in growth and better stress resistance and wood quality than diploid P. tomentosa. Using transcriptome sequencing technology to identify candidate transcriptome-based markers for growth vigor in young tree tissue is of great significance for the breeding of P. tomentosa varieties in the future. In this study, the cuttings of diploid and triploid P. tomentosa were used as plant materials, transcriptome sequencing was carried out, and their tissue culture materials were used for RT-qPCR verification of the expression of genes. The results showed that 12,240 differentially expressed genes in diploid and triploid P. tomentosa transcripts were annotated and enriched into 135 metabolic pathways. The top six pathways that enriched the most significantly different genes were plant-pathogen interaction, phenylpropanoid biosynthesis, MAPK signalling pathway-plant, ascorbate and aldarate metabolism, diterpenoid biosynthesis, and betalain biosynthesis pathway. Ten growth-related genes were selected from pathways of plant hormone signal transduction and carbon fixation in photosynthetic organisms for RT-qPCR verification. The expression levels of MDH and CYCD3 in tissue-cultured and greenhouse planted triploid P. tomentosa were higher than those in tissue-cultured diploid P. tomentosa, which was consistent with the TMM values calculated by transcriptome.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>redundant protein sequences, NR; NCBI nucleotide sequences, NT; A manually annotated and reviewed protein sequence database, SwissProt; Protein family, PFAM; and Clusters of Orthologous Groups of proteins, KOG) were performed on the assembled unigenes. BLAST was used for functional annotation of NT, Diamond was used for NR, KOG, SwissProt and KEGG, Hmmscan for PFAM and Blast2GO for GO, with the e-value of 1e&#8722; <ns0:ref type='bibr'>10 (Feng et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>Detection of differentially expressed genes (DEGs)</ns0:head><ns0:p>Using the transcriptome data of D1, D2, D3 &amp; T1, T2, T3, DESeq2 software <ns0:ref type='bibr' target='#b1'>(Anders and Huber, 2010)</ns0:ref> were employed to screen DEGs with parameters of Fold Change &#8807; 2 and adjusted P-value &#8804; 0.001. The genes with a fold of more than twice in triploid P. tomentosa compared to diploid P. tomentosa and Q-value &#8804; 0.001 were screened as differentially expressed genes. QUANT (https://www.quantsoftware.com/) was used to normalize and reduce the variance and help detect DEGs. The transcripts were filtered for minimum count prior to assessing differential expression. TMM values were calculated by using the edgeR software <ns0:ref type='bibr'>(Maza, 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>Analysis of Gene Ontology (GO) function and KEGG function of DEGs</ns0:head><ns0:p>GO annotations were performed using nucleotide data. According to the GO annotation and KEGG annotation results, as well as the functional annotation, the differential genes were functionally classified. Detection of transcription factor families is based on the annotations. Meanwhile, the phyper function <ns0:ref type='bibr'>(Evans et al., 2000)</ns0:ref> in R software was used for enrichment analysis, the p-values were calculated and then corrected by False Discovery Rate (FDR) <ns0:ref type='bibr'>(Burger, 2018)</ns0:ref>. Finally, the function with Q-value &#8804;0.05 was deemed significant enrichment. The test conducted was one tailed for enrichment.</ns0:p><ns0:p>GetORF was used to detect the ORF of Unigene, and HMMER 3.0 hmmsearch was used to compare ORF, and then the characteristics of the transcription factor family were analyzed by PlantTFDB <ns0:ref type='bibr' target='#b6'>(Sanseverino et al., 2010)</ns0:ref>. The gene alignments were annotated into the plant disease resistance gene database PRGdb by using DIAMOND (https://github.com/bbuchfink/diamond) v0.8.31 software <ns0:ref type='bibr'>(Buchfink et al., 2015)</ns0:ref>.</ns0:p><ns0:p>The candidate coding region in Unigenes was identified by TransDecoder v2.0.1 software, and then the PFAM protein homologous sequence was searched by Blast alignment SwissProt database and Hmmscan 3.0</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed ( http://hmmer.org), thus the coding region CDSs were predicted. MISA (http://pgrc.ipk-gatersleben.de/misa) was used to detect simple sequence repeat (SSR) in Unigene, the parameters were set as default <ns0:ref type='bibr' target='#b9'>(Sen et al., 2018)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>Tissue culture of diploid and triploid P. tomentosa</ns0:head><ns0:p>The leaves of diploid and triploid P. tomentosa were inoculated on a callus induction medium (MS+1.2 mg/l 6-BA+0.6 mg/l NAA) for 15 days. They were transferred to an aseptic differentiation medium (MS+1.0 mg/l 6-BA+0.4 mg/l NAA) for 28 days. Then the adventitious buds were moved to a rooting medium (1/2 MS + 0.4mg/L IBA), after they grew to 2 to 3cm. After the adventitious roots growing to 2 to 3 cm, the seedlings were moved to a greenhouse.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>Real-time quantitative polymerase chain reaction (RT-qPCR) validation</ns0:head><ns0:p>To verify the reliability of transcriptome sequencing results and the expression of key genes, diploid and triploid</ns0:p><ns0:p>Chinese white poplar tissue culture seedlings of the same age and growth conditions, which were derived from the same trees used for transcriptome, tissue culture plants and planted in the greenhouse, at 1 month, 4 months, 7 months, 10 months and 13 months old plants, were used for RT-qPCR validation. As in transcriptome sequencing, stem segments under the fifth leaf down from the tip of a branch were selected for validation. The method of tissue culture was carried out according to the method reported by <ns0:ref type='bibr'>Hu et al. (2005)</ns0:ref>. The stem cuttings were sampled at 9 o'clock in the morning. Ten growth-related genes were selected from the pathway of plant hormone signal transduction (Ko04075), carbon fixation in photosynthetic organisms (Ko00710), nitrogen metabolism (Ko00910) and tryptophan metabolism (Ko00380) for RT-qPCR validation. These genes were up-regulated in triploid P. tomentosa compared to diploid P. tomentosa, and taken as candidate markers for plant breeders in the future. Using the EF1a as an internal reference gene, and using the gene sequences of the transcriptome, the primers were designed using Primer primer 5 <ns0:ref type='bibr'>(Lalitha 2000)</ns0:ref>, as listed in Table <ns0:ref type='table'>1</ns0:ref>. The RT-qPCR processes were described according to Manuscript to be reviewed qPCR reactions. The data were normalized with housekeeping gene EF1&#945;, and the 2 (-&#9651;&#9651;Ct) method was employed according to the previous study <ns0:ref type='bibr'>(Liu et al., 2018)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3'>Results and Analysis</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>Unigene function annotations</ns0:head><ns0:p>The length distribution of unigenes is shown in Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>. The unigenes were annotated with seven major functional database annotations (KEGG, GO, NR, NT, SwissProt, Pfam, and KOG). Finally there were 6,554 </ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>Transcription factor (TF) prediction</ns0:head><ns0:p>The TF prediction results showed that the genes belonged to a total of 55 transcription factor families, of which, with the largest number of genes, was the MYB gene family, with a total of 438 genes involved in the expression, followed by the AP2-EREBP gene family with 290 genes, and finally the bHLH gene family with 239 genes (see Figure <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). Among these transcription factor families, both the MYB family and the WRKY family (including 208 genes) are involved in plant growth and development processes, which can provide relevant information for our subsequent screening of growth-related genes.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>Cluster analysis and GO classification of DEGs</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The number of up-regulated genes in diploid P. tomentosa compared with triploid P. tomentosa was 15,690 and the down-regulated gene was 16,971. The scatter plot of DEGs showed that the difference of transcriptional profiles between triploid and diploid samples was obvious (see Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>). The GO function was divided into three branches: molecular function, cellular component, and biological process. Figure <ns0:ref type='figure'>4</ns0:ref> shows the functional classification based on differential gene detection. A total of 22,375 differentially expressed genes that had GO annotations were obtained in GO classification entries by using the classification of 32,661 common differential genes. There were 13,720 DEGs in biological processes, including 6,481 up-regulated genes and 6,879 down-regulated genes; 15,963 DEGs in cell composition, including 7,687 up-regulated genes and 8,276 down-regulated genes; and 1,092 DEGs in molecular function, including 8,553 up-regulated genes and 9,539 down-regulated genes.</ns0:p><ns0:p>Among the three branches of GO function entries, the number of DEGs of binding was the largest in molecular function, the number of DEGs of the cell and cell part was the largest in the cellular component, and the number of DEGs of the cellular process was the largest in the biological process. There are 44 DEGs that belonged to lignin production related transcripts (see Table <ns0:ref type='table'>2</ns0:ref>), which are important for tree breeders. A total of 38 entries were enriched in GO function (Q &#8804; 0.05) (see Table <ns0:ref type='table'>3</ns0:ref>). Biological processes accounted for 36.8% of the total, of which catalytic activity accounted for the largest proportion of biological processes, at 42.86%; cell components accounted for 18.5% of the total, of which cell accounted for 42.85%; and molecular functions accounted for 44.7% of the total, of which catalytic activity accounted for 47.05%.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.4'>Analysis of pathway function of DEGs</ns0:head><ns0:p>Using Q-value &#8804; 0.05 as the standard, 32,661 differential genes were separately analysed by pathway enrichment using the KEGG database. There were 16 significantly enriched KEGG metabolic pathways. Among them, the most frequently occupied pathways were the metabolism branch, with 13, and a total of 19,469 DEGs involved;</ns0:p><ns0:p>the second was the biological system branch, with two, and a total of 1,447 DEGs involved; and finally, the environmental information process branch, with one, with 868 DEGs involved.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The results showed that there were 12,240 significantly different genes annotated in the KEGG pathways of diploid and triploid samples. The top differentially expressed genes significantly enriched six pathways were as follows: 1,115 differential gene expression in the plant-pathogen interaction (KO: ko04626) pathway; 396 differential genes in the phenylpropane biosynthesis (KO: ko00940) pathway; 868 differential genes in the mitogen-activated protein kinase (MAPK) plant signaling pathway (KO: ko04016); 170 differential genes expression in the ascorbate and aldarate metabolism pathway (KO: ko00053); 64 differential genes in the diterpenoid biosynthesis pathway (KO: ko00904); and 43 differential genes in the beets red pigment biosynthesis pathway (KO: ko00965). All differentially expressed genes significantly enriched pathways were shown in Table <ns0:ref type='table'>4</ns0:ref>. The results showed there were 496 DEGs up-regulated and 619 down-regulated in the plant-pathogen interaction pathway, and there were 864 DEGs enriched in the organismal systems category of GO annotations, 217 DEGs in environmental information processing, 25 DEGs in genetic information processing, 9 DEGs in metabolism.</ns0:p><ns0:p>In the process of analysing the growth-related pathways, it was found that the growth-related genes were up-regulated and down-regulated, so it was difficult to explain the difference between diploid and triploid samples. The NCBI database was used for gene information annotation; the details are shown in Table <ns0:ref type='table'>5</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.5'>RT-qPCR validation</ns0:head><ns0:p>Genes related to growth which up-regulated in the triploid P. tomentosa compared to diploid P. tomentosa, as candidate markers for plant breeders in the future, were selected for RT-qPCR validation. There was no peak in the dissolution curves of RT-qPCR products of GH3, CA, and A-ARR gene. And the other seven genes showed a single peak curve, indicating that their amplification products did not contain primer dimers or nonspecific amplification products, and each primer PCR reaction was specific. The results of comparison of the transcriptome analysis and the RT-qPCR analysis are shown in Figure <ns0:ref type='figure' target='#fig_6'>5A</ns0:ref>. In diploid plants, the expression levels of the SAUR, FDP, ALDH, AUX1 and ABF in RT-qPCR analysis were significantly higher than those in the transcriptome analysis. In triploid plants, the expression levels of the ALDH and AUX1 in RT-qPCR analysis were significantly lower than those in the transcriptome analysis; the expression levels of the MDH and CYCD3</ns0:p><ns0:p>in RT-qPCR analysis were significantly higher than those in the transcriptome analysis. The expression levels</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed of AUX1, CYCD3, and MDH in tissue-cultured triploid poplar were higher than those of tissue-cultured diploid samples, which were consistent with the changes of TMM values calculated by transcriptome. Among them, the expression levels of the AUX1 gene in triploid samples were significantly higher than those in diploid samples (about 6.88 times, logFC value). However, the expression of the ABF gene in diploid samples was higher than that of triploid samples, which was not in accordance with the TMM values. In further experiments, the expression levels of MDH and CYCD3 in tissue-cultured and greenhouse planted triploid poplar were significantly higher than those of tissue-cultured and greenhouse planted diploid samples. And the expression levels of MDH and CYCD3 increased with the age gradually (Figure <ns0:ref type='figure' target='#fig_6'>5, B and C</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head n='4'>Discussion</ns0:head><ns0:p>The transcriptome analysis of the new rooting stem segments of diploid and triploid P. tomentosa showed that most of the significantly different genes were concentrated in plant-pathogen interaction, phenylpropane biosynthesis pathway, and MAPK signaling pathway-plant. Under the condition of comprehensive screening of the GO function enrichment and KEGG function analysis of transcriptome data, it is difficult to determine the expression of specific genes when the genes associated with plant growth appear up-regulated and downregulated. <ns0:ref type='bibr'>Huang et al (1990)</ns0:ref> have demonstrated larger branches, leaves and fruits in the triploid variety of pear compared to the diploid variety. And the production of tetraploid radish is 20% higher than that of ordinary diploids <ns0:ref type='bibr'>(Liu et al., 2003)</ns0:ref>. <ns0:ref type='bibr'>Zhu et al. (1995)</ns0:ref> reported that allotriploidy of P. tomentosa had greater values than diploidy under the same growth conditions in tree height, diameter at breast height, and single plant volume at the age of eight years.</ns0:p><ns0:p>It is interesting that although the transcriptome of the diploidy and triploidy of P. tomentosa was analyzed here, according to the specific species distribution chart of the annotations, only 3.26% was annotated by P.</ns0:p><ns0:p>tomentosa. It may be partly due to that the triploid materials used in this study were obtained by the hybridized with P. bolleana, and some of the mRNA does not belong to P. tomentosa. Of course, it may also partly due to that the plant materials were annual stems in this study, which was different from previous studies on P.</ns0:p><ns0:p>tomentosa. Previous studies of transcriptome analysis on P. tomentosa were mostly based on aseptic seedlings, PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed root, one-month-old stem and leaf samples materials <ns0:ref type='bibr' target='#b0'>(An et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b15'>Wang et al., 2018)</ns0:ref>, and the expression of mRNA is organ-specificity <ns0:ref type='bibr'>(Ohtsuki et al., 2005)</ns0:ref>.</ns0:p><ns0:p>The phytohormone signal transduction pathway controls plant cell division, cell elongation, cell enlargement, and stem elongation, which is closely related to plant growth and development <ns0:ref type='bibr'>(Guo et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Compared with previous data of transcriptome analysis on phytohormone signal transduction, we selected AUX1, GH3, A-ARR, CYCD3, ABF and five other genes for the RT-qPCR validation. Huge differences were found between the expression levels of the selected genes in the RT-qPCR analysis and those of the transcriptome analysis, and we inferred that it might be due to the different growth stages of the experiment's materials.</ns0:p><ns0:p>Photosynthesis is an important metabolic process in plants, and its strength has an important effect on plant growth, development, and stress resistance. <ns0:ref type='bibr'>Li and Zhang (2006)</ns0:ref> found that the lower leaves of the fast-growing triploid P. tomentosa clones could maintain a higher photosynthetic rate when measuring the leaf net photosynthetic rate of diploid and triploid P. tomentosa. Photosynthesis includes a series of complex reactions in which carbon fixation is a central link in the regulation of photosynthesis <ns0:ref type='bibr'>(Feng et al., 2006)</ns0:ref>. We compared the data of carbon fixation pathways in previous photosynthetic organism kiwifruit <ns0:ref type='bibr'>(Li et al., 2019b)</ns0:ref> and selected the up-regulated malate dehydrogenase (MDH) for the RT-qPCR validation, and the expression levels of MDH gene were up-regulated in triploid P. tomentosa plants, compared to the diploid ones. With the possible exception of the stomatal dimension, the response to polyploidy can be very variable and complex. It has been proved in oilseed rape <ns0:ref type='bibr' target='#b2'>(Bancroft et al., 2011)</ns0:ref>, sugarcane (Manners and Casu, 2011), cotton <ns0:ref type='bibr' target='#b5'>(Rambani et al., 2014</ns0:ref><ns0:ref type='bibr'>), wheat (Leach et al., 2014</ns0:ref><ns0:ref type='bibr'>), kiwifruit (Li et al., 2019b)</ns0:ref>, rice <ns0:ref type='bibr' target='#b10'>(Shenton et al., 2020)</ns0:ref> and numerous studies in Arabidopsis species, some of which specifically consider triploidy <ns0:ref type='bibr'>(Fort et al., 2016;</ns0:ref><ns0:ref type='bibr'>2017;</ns0:ref><ns0:ref type='bibr'>Pacey et al., 2019)</ns0:ref>. Related to the phenomenon, the gene expression levels were not up-regulated in all polyploid plants, and over-, under-or mixed expression of genes were found in the polyploid plant <ns0:ref type='bibr'>(Osborn et al., 2003;</ns0:ref><ns0:ref type='bibr'>Gutierrez-Gonzalez and Garvin, 2017;</ns0:ref><ns0:ref type='bibr'>Li et al., 2019b)</ns0:ref>. And this phenomenon was also found in this study. It illustrated that the allopolyploidy in particular in P. tomentosa also alter the gene expression profile and levels as well as those in autopolyploid plants, compared to their diploid relatives. In this study, the expression levels that related to the growth genes such as MDH and CYCD3 in triploid P. tomentosa were higher than those of diploid P. tomentosa.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Malate dehydrogenase (MDH) is mainly involved in plant photosynthesis metabolism <ns0:ref type='bibr' target='#b8'>(Sawada et al., 2002)</ns0:ref>.</ns0:p><ns0:p>The main function of the protein encoded by the MDH gene is to fix carbon dioxide in the photosynthesis <ns0:ref type='bibr' target='#b8'>(Sawada et al., 2002)</ns0:ref>. Higher expression levels of MDH gene was proved to be related to higher rates of photosynthesis <ns0:ref type='bibr'>(Kandoi et al., 2018)</ns0:ref>, which in turn contributes to higher timber yield. CYCLIN D3 (CYCD3) is a member of cell-cycle genes, and Overexpression of CYCLIN D3;1 (CYCD3;1) in transgenic plants can increase mitotic cycles and reduces endocycles <ns0:ref type='bibr'>(Menges et al., 2006)</ns0:ref>. CYCD3 was found to regulate cambial cell proliferation and secondary growth, and the protein encoded by the CYCD3 gene is required for normal vascular development in <ns0:ref type='bibr'>Arabidopsis (Collins et al., 2015)</ns0:ref>. These previous studies indicated a relationship between faster growth and the increased expression of the CYCD3 gene. Hence, the upregulation of MDH and CYCD3 in the triploids is biologically meaningful. There were many DEGs between the diploid and triploid poplar plants that were enriched for plant-pathogen interaction pathway, stress resistance and several growth related transcripts too. Genes in the plant-pathogen interaction pathway are known to be diverse and large in plants and are known to be involved in reproduction isolation across Arabidopsis and Poplars too <ns0:ref type='bibr'>(Liao et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b4'>Qian et al., 2018)</ns0:ref>. Further, the enrichment of differential expression transcripts in this category could provide useful information to tree breeders intending to generate heterotic F1s. The pathway enrichment approach also shows several other interesting candidates that would be worth future elaborating on and relating to studies demonstrating higher stress resistance in the triploid poplar.</ns0:p></ns0:div> <ns0:div><ns0:head n='5'>Conclusion</ns0:head><ns0:p>A total of 32,661 DEGs were identified in triploid and diploid Chinese white poplar, of which 15,690 were upregulated and 16,971 were down-regulated in triploidy compared to diploidy. Through the comprehensive analysis of GO functional enrichment analysis and the pathway functional annotation of transcriptome data of diploid and triploid P. tomentosa, no significantly enriched entries and pathways related to growth were found.</ns0:p><ns0:p>Compared to diploidy, the growth-related genes were found to be up-regulated and down-regulated in the natural diploid and triploid P. tomentosa trees. Although the expression levels of genes were unstable in the different environments and different growth stages, the expression levels of MDH and CYCD3 in triploid P. tomentosa</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed were higher than those of diploid P. tomentosa in young tree tissue, which was consistent with the values calculated using the transcriptome data.</ns0:p></ns0:div> <ns0:div><ns0:head>Availability of data and material</ns0:head><ns0:p>All data generated or analyzed during this study are included in this published article. RNA-Seq data were presented at the Genome Sequence Archive of the Beijing Institute of Genomics (BIG) Data Center (accession number Manuscript to be reviewed Figure <ns0:ref type='figure'>4</ns0:ref> GO secondary node annotation statistics of differential expression genes.</ns0:p><ns0:p>Note: The abscissa was the number of genes and the left side of the ordinate was the GO classification. 4,10 months old; 5, 13 months old. **, the difference is very significant (P-value&lt;0.01). RT-qPCR was performed on 3 diploid and 3 triploid plants, which were driven from the same tree used for transcriptome analysis, normalized with housekeeping gene EF1&#945;, repeated 3 times. The 2 (-&#9651;&#9651;Ct) method was utilized to process the data <ns0:ref type='bibr'>(Liu et al., 2018)</ns0:ref>. Because the difference of the values in Figure <ns0:ref type='figure' target='#fig_6'>5A</ns0:ref> was too big, the y-axis of Figure Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 3</ns0:note><ns0:note type='other'>Figure 4</ns0:note><ns0:p>Figure <ns0:ref type='figure'>4</ns0:ref> GO secondary node annotation statistics of differential expression genes.</ns0:p><ns0:p>Note: The abscissa was the number of genes and the left side of the ordinate was the GO classification.</ns0:p><ns0:p>Figure </ns0:p><ns0:note type='other'>5</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Li et al. (2019b) on a Bio-Rad CFX96TM Real-time PCR Detection System (Bio-Rad, California, USA), with a final volume of 25.0 &#956;l, containing 2.5 units of Taq DNA polymerase, 0.4 mM deoxyribonucleotides (dNTPs), 20 &#956;l of ddH 2 O, 1 &#956;l of cDNA, and 500 nM of each primer. Each sample was carried out in triplicate for the RT-PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1 Length distribution of unigenes.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 Classification of the family of transcription factors.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3 Scatter plot of log diploid and triploid expression data.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5 Comparison of the transcriptome analysis and the RT-qPCR analysis.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3 Scatter plot of log diploid and triploid expression data.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5 Comparison of the transcriptome analysis and the RT-qPCR analysis.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,178.87,525.00,315.00' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head /><ns0:label /><ns0:figDesc>PRJCA002269, https://bigd.big.ac.cn/search?dbId=biosample&amp;q=PRJCA002269). Liu B, Sun G. Transcriptome and miRNAs analyses enhance our understanding of the evolutionary advantages of polyploidy. Liu XP, Zhang ZM, Sang M, Sun XD, He CZ, Xin PY &amp; Zhang HY. Functional analysis of the FZF1 genes of Saccharomyces uvarum. Frontiers in Microbiology, 2018, 9: 96.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Critical</ns0:cell><ns0:cell>Reviews</ns0:cell><ns0:cell>in</ns0:cell><ns0:cell>Biotechnology,</ns0:cell><ns0:cell>2019,</ns0:cell><ns0:cell>39(2):173-180.</ns0:cell><ns0:cell>doi:</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>10.1080/07388551.2018.1524824.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='7'>Liu W, Wang M, Yan Z. Advances in polyploid breeding of vegetable crops. Changjiang vegetables, 2003 (01):</ns0:cell></ns0:row><ns0:row><ns0:cell>29-33. in Chinese</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='7'>Liu XZ, Manners, JM, Casu, RE (2011) Transcriptome analysis and functional genomics of sugarcane. Trop Plant</ns0:cell></ns0:row><ns0:row><ns0:cell>Biology, 4: 9-21.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='7'>Ohtsuki T, Otsuki M, Murakami Y, Maekawa T, Yamamoto T, Akasaka K, Takeuchi S, Takahashi S. Organ-</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>specific and age-dependent expression of insulin-like growth factor-I (IGF-I) mRNA variants: IGF-IA</ns0:cell></ns0:row><ns0:row><ns0:cell cols='6'>and IB mRNAs in the mouse. Zoological Science, 2005, 22(9):1011-21. doi: 10.2108/zsj.22.1011.</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='7'>Osborn TC, Pires JC, Birchler JA, Auger DL, Chen ZJ, Lee HS, Comai L, Madlung A, Doerge RW, Colot V,</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>Martienssen RA.. Understanding mechanisms of novel gene expression in polyploids. Trends in Genetics,</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>2003, 19:141-147. doi:10.1016/S0168-9525(03)00015-5.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='7'>Pacey EK, Maherali H, Husband BC. The influence of experimentally induced polyploidy on the relationships</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>between endopolyploidy and plant function in Arabidopsis thaliana. Ecology Evolution, 2019,</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>10(1):198-216. doi: 10.1002/ece3.5886.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>Maza E. In Papyro comparison of TMM (edgeR), RLE (DESeq2), and MRN normalization methods for a simpletwo-conditions-without-replicates RNA-Seq experimental design. Frontiers in Genetics, 2016, 7: 164. doi: 10.3389/fgene.2016.00164. Menges M, Samland AK, Planchais S, Murray JA. The D-type cyclin CYCD3;1 is limiting for the G1-to-Sphase transition in Arabidopsis. Plant Cell. 2006,18(4):893-906. doi:10.1105/tpc.105.039636. PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table . 1</ns0:head><ns0:label>.</ns0:label><ns0:figDesc>The primers used in the RT-qPCR analysis.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell>F&#65306;TGCTGGTGGACTTGAGGATT</ns0:cell><ns0:cell>168</ns0:cell></ns0:row><ns0:row><ns0:cell>1</ns0:cell><ns0:cell>ALDH</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;ATCAAAGAAATGGAGAATAGGCAGA</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Gene Symbol</ns0:cell><ns0:cell>Upstream and Downstream primer sequence(5&#8594;3)</ns0:cell><ns0:cell>Product length</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;GGCAAGGAGAAGGTACACAT</ns0:cell><ns0:cell>204</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>EF1a</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;CAATCACACGCTTGTCAATA</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;TGGATCTGTCATTCAACTTATTGCT</ns0:cell><ns0:cell>143</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>AUX1</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;AAATACGGTAGTTATGAAAAGAGGGTAT</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;GGACACCGGAAAGAAGAAGGT</ns0:cell><ns0:cell>211</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>GH3</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;CCCTGAAACATCCTAATCAAGCTAC</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;AAATCAGGGGGAGCTCTCTT</ns0:cell><ns0:cell>100</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>A-ARR</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;TTCTACACTTCTGTTGAGCCTGT</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;TGCTCTGCTCTCTCTTTGTTCG</ns0:cell><ns0:cell>216</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>CYCD3</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;CCACTGAAAATCTCACGCCAATC</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;TGGAAAGTGGCAAGTGGGAA</ns0:cell><ns0:cell>134</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>ABF</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;TCAAGACACTGGCAAAGGCA</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;CCGGCTTCATCCACTAGACTC</ns0:cell><ns0:cell>153</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>MDH</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;GAAGGGAAGGGGTGATACCG</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;AGAGATTATAATGGCCAGCACCAG</ns0:cell><ns0:cell>178</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>CA</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;TGGCCCTTTTCCAGTTCCTT</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;ACTCCCAAACACCAAACGAGA</ns0:cell><ns0:cell>136</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>FDP</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;AGCCCACTTGGTATTGGAGC</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;TGCCAAGCAAATTTTCCGCC</ns0:cell><ns0:cell>105</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>SAUR</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;ACTGGAACCACAAATCGCTTC</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)Manuscript to be reviewed</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table . 3</ns0:head><ns0:label>.</ns0:label><ns0:figDesc>Entries were enriched in GO function.</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='2'>DNA binding</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='4'>GO:0046658 Anchored component of</ns0:cell><ns0:cell>Cellular component</ns0:cell><ns0:cell>Cell</ns0:cell><ns0:cell>0.565 0.002</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>GO Term ID GO Term plasma membrane</ns0:cell><ns0:cell /><ns0:cell>Level 1 a</ns0:cell><ns0:cell>Level 2 b</ns0:cell><ns0:cell>Rich</ns0:cell><ns0:cell>Q-value</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Ratio</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>GO:0009611 Response to wounding</ns0:cell><ns0:cell /><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Response to stimulus</ns0:cell><ns0:cell>0.613 0.002</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>GO:0043531 ADP binding</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Molecular function</ns0:cell><ns0:cell>Binding</ns0:cell><ns0:cell>0.649 5.07E-40</ns0:cell></ns0:row><ns0:row><ns0:cell>GO:0048046 Apoplast</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Cellular component</ns0:cell><ns0:cell cols='2'>Extracellular region</ns0:cell><ns0:cell>0.609 0.002</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>GO:0007165 Signal transduction</ns0:cell><ns0:cell /><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Biological regulation</ns0:cell><ns0:cell>0.607 1.54E-32</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:2000022 Regulation of jasmonic acid</ns0:cell><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Biological regulation</ns0:cell><ns0:cell>0.625 0.002</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0006952 Defense response mediated signaling pathway</ns0:cell><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Response to stimulus</ns0:cell><ns0:cell>0.613 2.75E-24</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0046914 Transition metalion binding GO:1903507 Negative regulation of</ns0:cell><ns0:cell>Molecular function Biological process</ns0:cell><ns0:cell cols='2'>Binding Biological regulation</ns0:cell><ns0:cell>0.675 1.49E-09 0.629 0.003</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0046916 Cellular transition metalion nucleic acid-templated</ns0:cell><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Biological regulation</ns0:cell><ns0:cell>0.677 1.49E-09</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>homeostasis transcription</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>GO:0030001 Metalion transport GO:0000977 RNA polymerase</ns0:cell><ns0:cell>II</ns0:cell><ns0:cell>Biological process Molecular function</ns0:cell><ns0:cell>Localization Binding</ns0:cell><ns0:cell>0.644 2.10E-08 0.570 0.003</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>regulatory region sequence-</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>GO:0005886 Plasma membrane specific DNA binding</ns0:cell><ns0:cell /><ns0:cell>Cellular component</ns0:cell><ns0:cell>Cell</ns0:cell><ns0:cell>0.494 1.64E-06</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0016021 Integral GO:0003700 DNA binding transcription component of</ns0:cell><ns0:cell>Cellular component Molecular function</ns0:cell><ns0:cell>Membrane part Transcription</ns0:cell><ns0:cell>regulator</ns0:cell><ns0:cell>0.461 3.73E-06 0.497 0.003</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>membrane factor activity</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>activity</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0007205 Protein kinase C-activating GO:0003839 Gamma-</ns0:cell><ns0:cell>Biological process Molecular function</ns0:cell><ns0:cell cols='2'>Biological regulation Catalytic activity</ns0:cell><ns0:cell>0.8 0.941 0.004 9.92E-05</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>G-protein coupled receptor glutamylcyclotransferase</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>signaling pathway activity</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='4'>GO:0031347 Regulation GO:0006979 Response to oxidative stress of defense</ns0:cell><ns0:cell>Biological process Biological process</ns0:cell><ns0:cell cols='2'>Biological regulation Response to stimulus</ns0:cell><ns0:cell>0.618 9.92E-05 0.596 0.006</ns0:cell></ns0:row><ns0:row><ns0:cell>response</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>GO:0005576 Extracellular region</ns0:cell><ns0:cell /><ns0:cell>Cellular component</ns0:cell><ns0:cell cols='2'>Extracellular region</ns0:cell><ns0:cell>0.541 0.006</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>GO:0004143 Diacylglycerol</ns0:cell><ns0:cell cols='2'>kinase</ns0:cell><ns0:cell>Molecular function</ns0:cell><ns0:cell>Catalytic activity</ns0:cell><ns0:cell>0.8</ns0:cell><ns0:cell>9.99E-05</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>activity GO:0016298 Lipase activity</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Molecular function</ns0:cell><ns0:cell>Catalytic activity</ns0:cell><ns0:cell>0.698 0.006</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>GO:0006351 Transcription, GO:0016020 Membrane</ns0:cell><ns0:cell cols='2'>DNA-</ns0:cell><ns0:cell>Biological process Cellular component</ns0:cell><ns0:cell>Cellular process Membrane</ns0:cell><ns0:cell>0.491 0.001 0.501 0.007</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>templated GO:0006629 Lipid metabolic process</ns0:cell><ns0:cell /><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Metabolic process</ns0:cell><ns0:cell>0.550 0.010</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>GO:0001228 Transcriptional GO:0016747 Transferase</ns0:cell><ns0:cell cols='2'>activator activity,</ns0:cell><ns0:cell>Molecular function Molecular function</ns0:cell><ns0:cell>Transcription Catalytic activity</ns0:cell><ns0:cell>regulator</ns0:cell><ns0:cell>0.592 0.002 0.578 0.012</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>activity, RNA polymerase II transferring acyl groups</ns0:cell><ns0:cell /><ns0:cell>activity</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>transcription other than</ns0:cell><ns0:cell cols='2'>regulatory amino-acyl</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>region groups</ns0:cell><ns0:cell cols='3'>sequence-specific</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:48280:1:2:NEW 7 Aug 2020)Manuscript to be reviewed</ns0:note></ns0:figure> </ns0:body> "

"Dear editor and reviewers, We have revised the manuscript according to the reviewers comments. Following are the answers to the reviewers concerns: Overall, this manuscript describes patterns of gene expression in the diploid and triploid species of poplar. However, I think because the authors were very focussed on finding growth related transcripts being upregulated in the triploid, they have missed the opportunity to explore certain pathways that may not directly be related to growth and superior performance but can have key implications for tree breeders. Besides, superior growth in the triploid poplar need not always be related to upregulation of growth related transcripts across all developmental stages. With regard to exploring other pathways, their study shows the plant-pathogen interaction pathway to be enriched among sets of transcripts that were DE. Genes in this pathway are known to be diverse and large in plants and are known to be involved in reproduction isolation across Arabidopsis and Poplars too. While investigating neo-functionalisation and sub-functionalisation of genes belonging to this pathway in the triploid Poplar maybe beyond the scope of this work, it would be useful to speculate on this in the discussion. Answer: We have done a speculation in the discussion in the last paragraph. A simple summary of how many genes in this pathway have zero expression in the triploid poplar or are associated with different GO node terms relative to the diploid would be good. Answer: We got 1115 DEGs, since they are DEGs, so no Zero expression DEGs in the triploid poplar were found. However, the results showed there were 496 DEGs up-regulated and 619 down-regulated in the plant-pathogen interaction pathway, and there were 864 DEGs enriched in organismal systems category of GO annotations, 217 DEGs in environmental information processing, 25 DEGs in genetic information processing, 9 DEGs in metabolism. Further, the enrichment of DE transcripts in this category could provide useful information to tree breeders intending to generate heterotic F1s. The pathway enrichment approach also shows several other interesting candidates that would be worth future elaborating on and relating to previous studies demonstrating higher stress resistance noted in the triploid poplar. Answer: We had added these information in the discussion section. Another place to elaborate would be the DE of MDH & CYCD3 genes as evaluated using qRT-PCR. I think it would be useful to relate their finding of higher expression levels to higher rates of photosynthesis which in turn contributes to higher timber yield. Maybe relate to other studies that have demonstrated a relationship between the rate of photosynthesis and faster growth and higher timber yield or have evaluated the rate of growth in mutants of MDH and CYCD3. Answer: We had added these information in the discussion section. I would also have liked to see a qRT-PCR on lignin production related transcripts since it is a key trait used by tree breeders. If that is not possible, evaluating patterns of DE for some of the lignin production related transcripts using the RNAseq data would also be useful. Answer: We did not do additional experiments of qRT-PCR on lignin production related transcripts. However, we added some information on the DEGs for some of the lignin production related transcripts using the RNAseq data, please see Table 2. Specific and minor comments: Line 49: this sentence seems incomplete, should it be a continuation of the previous sentence and not a new sentence. Answer: Done. Line 58: please provide a reference for genome duplication due to hybridization. Consider changing line 73 to read as : RNA was extracted using the Tiagen kit. Answer: Done. Line 74: change “performed” to “generated”. Answer: Done. Please provide the settings used while running Trimmomatic and Soapnuke. For instance, was trimming of polyA tails conducted, what was Q score cutoff, length cutoff etc. in Trimmomatic. Answer: Done. Line 114: This is the first instance where the authors talk about CDS & SSR, please mention in the methods section how these were detected. Answer: The methods to detect CDS & SSR were added in the M & M section. The candidate coding region in Unigenes were identified by TransDecoder software, and then the Pfam protein homologous sequence were searched by Blast alignment SwissProt database and Hmmscan, thus the coding region CDSs were predicted. MISA (http://pgrc.ipk-gatersleben.de/misa) was used to detect simple sequence repeat (SSR) in Unigene, the parameters were default. Were the GO annotations performed using protein sequences or using nucleotide? I am assuming protein sequences were used for this. Answer: GO annotations were performed using nucleotide. Please see “Seven major functional database annotations (KEGG, GO, NR, NT, Swissprot, Pfam, and KOG) were performed on the assembled unigenes.” in the “2.3 Gene annotation” section. Line 124: Detection of transcription factor families is not mentioned in the methods. Is this based on the annotations, if so please clarify. Answer: Detection of transcription factor families is based on the annotations. It is unclear to me what the authors mean by “involved in the transcriptome” mentioned at line 126. Answer: It should be “involved in the expression”, and because it is redundant, it is deleted in the revised manuscript. Line 137: This sentence is unclear. Does 22k refer to the set of DE transcripts that had GO annotations, or does it refer to the set that was not DE? Please clarify. Answer: They refer to the set of DE transcripts that had GO annotations. Line 150-153: Not clear. Answer: Deleted. Line 159: This is confusing. Earlier you mention that there are in total 32k DE transcripts, so what does this 12k refer to? Answer: This 12K refer to the transcripts enriched in KEGG pathways. Line 177-178: Please elaborate what you mean by “was obviously different from transcriptome analyses”. Answer: We have deleted “The expression levels of the selected genes in RT-qPCR analysis were obviously different from those of the transcriptome analysis.” and changed it into “In diploid plants, the expression levels of the SAUR, FDP, ALDH, AUX1 and ABF in RT-qPCR analysis were significantly higher than those in the transcriptome analysis. In triploid plants, the expression levels of the ALDH and AUX1 in RT-qPCR analysis were significantly lower than those in the transcriptome analysis; the expression levels of the MDH and CYCD3 in RT-qPCR analysis were significantly higher than those in the transcriptome analysis.” Line 193: Please provide a citation for this statement. Answer: We cited a refference (Huang et al.,1990) here. Please rewrite line 193 to 196. In line 193 it is not clear whether the authors are referring to larger leaf sizes for polyploid plants. Similarly for line 194, consider rewriting to:Huang et al (1990) have demonstrated larger branches, leaves and fruits in the triploid variety of pear compared to the diploid variety. Answer: Thanks a lot. We have revised it into “Huang et al (1990) have demonstrated larger branches, leaves and fruits in the triploid variety of pear compared to the diploid variety.” Line 202: what are the authors comparing to? Answer: Compared with previous data of transcriptome analysis on phytohormone signal transduction. Line 214-217: These sentences as written are not clear. Please consider elaborating what you mean by cryptic. Answer: Deleted. It is also not clear how the various studies listed here are related to gene expression differences noted in your study. Answer: The various studies listed here were used to illustrated the phenomenon of polyploidy were various and the expression levels of the genes in polyploidy were not meant to be up-regulated as ploidy increase, because “Related to the phenomenon, the gene expression levels were not up-regulated in all polyploid plants (Li et al., 2019b). Some genes in polyploidy were up-regulated and some were down-regulated compared to the diploidy”. Table 2 & 3 needs to be formatted correctly. Also consider using superscripts to describe what level1 and level2 are. Answer: Table 2 & 3 were reformatted. We used superscripts to describe what level1 and level2. a, large categories only includs Biological Process, Cellular Component, Molecular Function; b, subcategories under each large category. Please check if fig 3 is representing Up and down regulated transcripts after FDR. Answer: Fig 3 is representing non-DEGs, Up and down regulated transcripts after FDR. Fig 6: It is very difficult to see the bars for expression levels using the transcriptome dataset, which is expected given the higher sensitivity of qRT-PCR. I would suggest changing the y-axis to a log scale or presenting these as two separate panels. Answer: We used a log scale in Fig 6 A. The y-axis is also not labelled. Answer: The y-axis is labelled -5,0,5,10,15,20, and 25. Experimental design Are D1, D2, D3 & T1, T2, T3 representing biological replicates or technical replicates? Please clarify at the first mention and also in the methods for DE. Answer: They represented biological replicates. There are also several other aspects of the methods that need to be elaborated on and I have listed them above under 'specific & minor comments'. Answer: Thank you. We have revised them. Validity of the findings --FPKM not ideal for across sample comparisons (unless the cross sample scaling was performed prior to getting FPKM). FPKM is ok to compare gene expression within the same sample. I would suggest using TMM which is easy to implement and robust. See: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3608160/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5411036/ https://genomebiology.biomedcentral.com/articles/10.1186/gb-2010-11-3-r25 Answer： We have used the edgeR software to calculate the TMM values. --Please provide more details for the DE section of the methods. It is important to mention that the data was normalised and the approach used for normalisation and whether the transcripts were filtered for minimum count prior to assessing differential expression. Answer: QUANT was used to normalise and reduce the variance and help detect DEGs. The transcripts were filtered for minimum count prior to assessing differential expression. --I am curious as to why the authors decided to use phyper against several other methods specifically designed for conducting GO category enrichment. But more importantly, please mention whether the test conducted was two tailed or one tailed for enrichment. Based on the figure, it seems the test was one tailed. Answer: We only known how to use the phyper for GO category enrichment. And we don’t known how to conducting other software. The test conducted was one tailed for enrichment. Reviewer 2 (Anonymous) Basic reporting Although the authors used a proofreading service, this manuscript could benefit from another proofreading by someone familiar with the field. The English used in the article is, in general, good. However, there are enough instances where the meaning of the authors is ambiguous that the overall clarity should be addressed. Answer: Thank you. We have revised the manuscript according to the reviewers’ comment. The places which were ambiguous had been clarified. The authors primarily focus on the need for better approaches to crop improvement of tree species from an applied point of view (i.e. discussing the superiority of triploid P. tomentosa for timber qualities and growth vigor). Given that PeerJ has a relatively broad audience, the authors may need to explain some assertions they currently take for granted. What defines good wood quality? Answer: With long fiber and white wood. Fast growth and long life as compared to what? Other trees in northern China? Trees worldwide? Commercial trees? Answer: Compared to other trees in northern China. The second paragraph of the introduction does a better job of describing the difficulties of performing genetic improvement of tree crop species, but I think it would benefit from a considerably more comprehensive literature search. Answer: We have rewritten the second paragraph of the introduction and cited more references. In general, there is not sufficient background provided in the introduction, and references are sparse. Additional scholarship should be done, particularly focused on diploid vs polyploid traits in crop species. The third paragraph describes differences between triploid and diploid P. tomentosa, but misses an opportunity to better motivate their work. There is a wide literature comparing diploid and polyploid individuals for a variety of crop species that would be relevant here, but the authors choose to focus on P. tomentosa alone. A broader discussion of why polyploid plants often exhibit traits that are commercially beneficial, especially with respect to differences in gene expression, would be beneficial here. Answer: We have added an paragraph focused on diploid vs polyploid traits in crop species, and a broader discussion of why polyploid plants often exhibit traits that are commercially beneficial, especially with respect to differences in gene expression. Minor comments/suggestions: Line 35: Briefly explain what good wood quality is. Answer: Done. Line 45: 'the tree transcriptome' or 'tree transcriptomes' . Answer: revised. Line 51: omit ploidy Answer: Deleted. Line 52 and line 182: although not exactly wrong, 'obviously' is not a commonly-used word in most scientific literature (generally one's data should make something obvious). I would omit this. Answer: Deleted. Line 57-58: 'the transcriptome analysis was subjected to an analysis of the differences between diploid and triploid P. tomentosa' is a bit awkward and unclear. Differences in what? Answer: The differences in gene expression. Line 68: 'o'clock' Answer: Done. Line 195: 'found to be huge in triploids on branches' this is unclear. Answer: revised. Line 197: 'allotriploidy of P. tomentosa was better than diploidy' It would be better to say that the triploid had greated values of these traits. 'better' implies a value judgment. Answer: revised. It is definitely possible that I did something incorrectly, because I'm not very familiar with the BIG database, but I could not download the raw data. However, I can see that this project is listed in the database. Someone with greater familiarity may be able to pull down the raw reads. Answer: It had set a reveal date, before that it can not be download. Experimental design The methods as written are rather sparse, and it is difficult to get a good idea of what was done, or to understand if the protocols used are appropriate. As currently written, they would not be sufficient to replicate the experiment. Answer: We have rewritten the methods and tried to describe more details. Where the trees native to the area sampled, or where they planted? Answer: They were planted in Kunming World Horticultural Expo Park which are and the campus of Southwest Forestry University, these two planted sites are adjacent. Diploidy are native to the area. If planted, is there any way to determine where these genetic stocks originally come from? Answer: Triploidy are introduced from Beijing Forestry University (Zhang et al., 2008), please see the M&M section. Are the trees precisely one-year-old, or is there variability in their ages (and if so, how much?). Answer: Not precisely one-year-old. There variability in their ages about one month. How much material was sampled from each individual? Answer: 1g. The methods also appear in some cases to be out of order. Was RNA extraction done by the authors? Answer: No, RNA was extracted by Wuhan Huada Gene Company. What were the operating parameters used for data filtering and analysis? Answer: Trimming of polyA tails was conducted, and a cut-off threshold of Q-score 30 was chosen and bases with Q-score less than 30 were trimmed. How was annotation performed? Answer: BLAST was used for functional annotation of Nt, Diamond was used for Nr, KOG, Swissprot and KEGG, Hmmscan for Pfam and Blast2GO for GO, with the e-value of 1e−10. What pipeline was used (and if none was used, how was annotation done)? Answer: KEGG, GO, NR, NT, Swissprot, Pfam, and KOG were used to annotation perform. Four kinds of software were used for functional annotation with the e-value of 1e−10, including BLAST for Nt, Diamond for Nr, KOG, Swissprot and KEGG, Hmmscan for Pfam and Blast2GO for GO. How was tissue culture performed on plants to be used for RT-qPCR? Answer: The leaves of diploid and triploid P. tomentosa were inoculated on a callus induction medium (MS+1.2 mg/l 6-BA+0.6 mg/l NAA) for 15 days. They were transferred to an aseptic differentiation medium (MS+1.0 mg/l 6-BA+0.4 mg/l NAA) for 28 days. Then the adventitious buds were moved to a rooting medium (1/2 MS + 0.4mg/L IBA), after they were grew to 2 to 3cm. After the adventitious roots growing to 2 to 3 cm, the seedlings were moved to a greenhouse. Although the authors do refer to other papers for some methods, a brief description of the methods (RNA extraction, RT-qPCR protocol, data processing). Answer: RNA was extracted using the Tiagen kit (TIANGEN Biotech Beijing Co., Ltd.) by Wuhan Huada Gene Company, sorry, we can not provided more information. More details were provided in RT-qPCR protocol and data processing. The RT-qPCR processes were described according to Li et al. (2019b) on a Bio-Rad CFX96TM Real-time PCR Detection System (Bio-Rad, California, USA), with a final volume of 25.0 μl, containing 2.5 units of Taq DNA polymerase, 0.4 mM deoxyribonucleotides (dNTPs), 20 μl of ddH2O, 1 μl of cDNA, and 500 nM of each primer. Each sample was carried out in triplicate for the RT-qPCR reactions. The data were normalized with housekeeping gene EF1α, and the 2(-△△Ct) method was employed according to the previous study (Liu et al., 2018). Line 69: 'top-to-bottom fifth leaf'. This phrase is somewhat confusing, and if I am interpreting it correctly, raises a question about the protocol. Does this mean the fifth leaf down from the tip of a branch, or the fifth leaf up the stem from the base? Answer: The fifth leaf down from the tip of a branch. If it means the fifth leaf down from the top, are the authors certain they sampled analogous leaves from each individual? Answer: Not analogous leaves from each individual, but stem segments under the fifth leaf down from the tip of a branch. Generally, similar experiments count leaves or nodes from the base of the plant, but it's not entirely clear what the authors did and if it was appropriate. Answer: We choose the stems from the fifth leaf down from the tip of a branch, and it was appropriate because secondary growth is began at the the stems from the fifth leaf down from the tip of a branch. At this place we may find the genes related to the secondary growth (Ye et al., 2020). Ye Q, Liu X, Bian W, Zhang Z, Zhang H. Over-expression of transcription factor ARK1 gene leads to down-regulation of lignin synthesis related genes in hybrid poplar ‘717’. Scientific Reports, 2020, 10: 8549. https://doi.org/10.1038/s41598-020-65328-y. Line 210-213: 'We compared the data of carbon fixation pathways in previous photosynthetic organisms and selected the up-regulated malate dehydrogenase (MDH) for the RT-qPCR validation, and the expression levels of MDH gene were up-regulated in triploid P. tomentosa plants, compared to the diploid ones.' Which photosynthetic organisms? Answer: kiwifruit , please see Li et al., 2019b. Li S, Liu X, Liu H, Zhang X, Ye Q, Zhang H. Induction, identification and genetics analysis of tetraploid Actinidia chinensis. Royal Society Open Science, 2019b, 6: 191052. Validity of the findings The discussion and conclusions, as with the rest of the paper, are quite short, and do not spend enough time discussing the results of the experiments and how they fit into the broader literature. For example, it seems unusual that P. tomentosa would match the assembled transcriptome to such a low degree (3.26%) given that the individuals studied are supposedly P. tomentosa. The authors do not mention this in their discussion, but I feel it merits pointing out and explaining. Answer: We have discussed in the discussion section. Although the authors do spend some time mentioning previous work on polyploids, they mainly list species on which similar studies have been done. A more thorough description of which studies found over-, under- or mixed expression would be nice, as would some discussion and speculation on the role of allopolyploidy in particular in P. tomentosa. Some discussion on if the authors think upregulation of MDH and CYCD3 in the triploids is biologically meaningful, or simply due to chance would be useful in the discussion. Answer: We have added some discussion on MDH and CYCD3. Comments for the Author This work is interesting, and will be useful to tree geneticists and tree crop specialists, and shows how variable gene expression can be in young tree tissues. However, the brevity of the manuscript means that a lot of useful detail and important scholarship is missing. I encourage the authors to add additional detail to the methods section in particular. Answer: Thank you. We have revised the manuscript, and added additional detail to the methods section. Thanks for your help. Cheers, Yours sincerely, Hanyao Zhang Professor of Molecular Genetics Southwest Forestry University "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Triploid Chinese white poplar (Populus tomentosa Carr., Salicaceae) has stronger advantages in growth and better stress resistance and wood quality than diploid P. tomentosa. Using transcriptome sequencing technology to identify candidate transcriptome-based markers for growth vigor in young tree tissue is of great significance for the breeding of P. tomentosa varieties in the future. In this study, the cuttings of diploid and triploid P. tomentosa were used as plant materials, transcriptome sequencing was carried out, and their tissue culture materials were used for RT-qPCR verification of the expression of genes. The results showed that 12,240 differentially expressed genes in diploid and triploid P. tomentosa transcripts were annotated and enriched into 135 metabolic pathways. The top six pathways that enriched the most significantly different genes were plant-pathogen interaction, phenylpropanoid biosynthesis, MAPK signalling pathway-plant, ascorbate and aldarate metabolism, diterpenoid biosynthesis, and betalain biosynthesis pathway. Ten growth-related genes were selected from pathways of plant hormone signal transduction and carbon fixation in photosynthetic organisms for RT-qPCR verification. The expression levels of MDH and CYCD3 in tissue-cultured and greenhouse planted triploid P. tomentosa were higher than those in tissue-cultured diploid P. tomentosa, which was consist ent with the TMM values calculated by transcriptome.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>modern breeding techniques represented by genomics is the main trend in the field of forest breeding in the future <ns0:ref type='bibr' target='#b11'>(Harfouche et al., 2012)</ns0:ref>. Combining conventional breeding methods with transcriptome sequencing technology to screen tree growth-related genes is not only a breakthrough in variety selection but also a new field of exploration, and to identify candidate transcriptome-based markers for growth vigor in young tree tissue is very important <ns0:ref type='bibr' target='#b10'>(Hao et al., 2011;</ns0:ref><ns0:ref type='bibr'>Sun et al., 2019)</ns0:ref>.</ns0:p><ns0:p>Polyploidy is important for the evolution of plants <ns0:ref type='bibr'>(Sattler et al., 2016;</ns0:ref><ns0:ref type='bibr'>Liu and Sun, 2019)</ns0:ref>. RNA interference and dosage compensation in a polyploid cell often leads to epigenetic changes as it alters the gene expression levels <ns0:ref type='bibr'>(Osborn et al., 2003;</ns0:ref><ns0:ref type='bibr'>Soltis et al., 2004)</ns0:ref>. Many studies have found significant differences between the expression levels of genes in diploid and polyploid plants <ns0:ref type='bibr'>(Osborn et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b9'>Gutierrez-Gonzalez and Garvin, 2017;</ns0:ref><ns0:ref type='bibr'>Li et al., 2019b)</ns0:ref>. Polyploid plants often exhibit commercially beneficial qualities, e.g. increased vigour, improved product quality, enlarged organs, enhanced tolerance to both biotic and abiotic stresses and increased heterozygosity and heterosis, in contrast to their diploid relatives <ns0:ref type='bibr'>(Sattler et al., 2016;</ns0:ref><ns0:ref type='bibr'>Liu and Sun, 2019)</ns0:ref>. Polyploidy often results in downregulated fertility because the expression of fertility-related genes is lower than that of compared to their diploid relatives <ns0:ref type='bibr'>(Li et al., 2019b)</ns0:ref>. Developing polyploidy in plants has been the focus of many plant breeders for some time <ns0:ref type='bibr' target='#b13'>(Huang et al., 1990;</ns0:ref><ns0:ref type='bibr' target='#b2'>Bancroft et al., 2011;</ns0:ref><ns0:ref type='bibr'>Rambani et al., 2014;</ns0:ref><ns0:ref type='bibr'>Li et al., 2019b;</ns0:ref><ns0:ref type='bibr'>Shenton et al., 2020)</ns0:ref>.</ns0:p><ns0:p>There are many advantages of triploid P. tomentosa plants compared with diploid ones <ns0:ref type='bibr'>(Zhu et al., 1995;</ns0:ref><ns0:ref type='bibr' target='#b6'>Chen et al., 2017)</ns0:ref>. Studies have shown that triploid P. tomentosa is superior to diploid P. tomentosa in both volumes per plant and papermaking <ns0:ref type='bibr' target='#b6'>(Chen et al., 2017;</ns0:ref><ns0:ref type='bibr'>Li and Zhang, 2000)</ns0:ref>. P. tomentosa has a great advantage in the construction of shelterbelt and fast-growing and high-yield forest <ns0:ref type='bibr'>(Li et al., 2019a)</ns0:ref>. However, the related studies on the differences in growth between diploid and triploid P. tomentosa are mostly focused on phenotypic studies, while there are few studies on the genes that control the differences in their growth characteristics. In this study, the transcriptome analysis was subjected to an analysis of the differences in gene expression between diploid and triploid P. tomentosa, which derived from genome doubling and hybridization with different genotypes <ns0:ref type='bibr' target='#b23'>(Zhang et al., 2008)</ns0:ref>, and RT-qPCR analysis was used for verification of the results of the transcriptome analysis. It would lay a foundation to screen growth-related genes for providing high-quality, fastgrowing industrial timber and speeding up the genetic improvement of forest trees.</ns0:p><ns0:p>3.0 ( http://hmmer.org), thus predicting the coding region CDSs. MISA (http://pgrc.ipk-gatersleben.de/misa) was used to detect simple sequence repeats (SSR) in UniGene with the parameters set as default <ns0:ref type='bibr'>(Sen et al., 2018)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>Tissue culture of diploid and triploid P. tomentosa</ns0:head><ns0:p>The leaves of diploid and triploid P. tomentosa were inoculated on a callus induction medium (MS+1.2 mg/l 6-BA+0.6 mg/l NAA) for 15 days. After which, they were transferred to an aseptic differentiation medium (MS+1.0 mg/l 6-BA+0.4 mg/l NAA) for 28 days. Once the adventitious buds had grown by 2 to 3 cm, they were moved to a rooting medium (1/2 MS + 0.4mg/L IBA). After the adventitious roots had grown by 2 to 3 cm, the seedlings were then moved to a greenhouse.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>Real-time quantitative polymerase chain reaction (RT-qPCR) validation</ns0:head><ns0:p>To verify the reliability of transcriptome sequencing results and the expression of key genes, diploid and triploid</ns0:p><ns0:p>Chinese white poplar tissue culture seedlings of the same age and growth conditions, which were derived from the same trees used for transcriptome, tissue culture plants and planted in the greenhouse, at 1 month, 4 months, 7 months, 10 months and 13 months old plants, were used for RT-qPCR validation. As in transcriptome sequencing, stem segments under the fifth leaf down from the tip of a branch were selected for validation. The method of tissue culture was carried out according to the method reported by <ns0:ref type='bibr' target='#b12'>Hu et al. (2005)</ns0:ref>. The stem cuttings were sampled at 9 o'clock in the morning.</ns0:p><ns0:p>Ten growth-related genes were selected from the pathway of plant hormone signal transduction (Ko04075), carbon fixation in photosynthetic organisms (Ko00710), nitrogen metabolism (Ko00910) and tryptophan metabolism (Ko00380) for RT-qPCR validation. These genes were up-regulated in triploid P. tomentosa compared to diploid P. tomentosa, and taken as candidate markers for plant breeders in the future. Using the EF1a as an internal reference gene, and using the gene sequences of the transcriptome, the primers were designed using Primer primer 5 <ns0:ref type='bibr' target='#b17'>(Lalitha 2000)</ns0:ref>, as listed in Table <ns0:ref type='table'>1</ns0:ref>. The RT-qPCR processes were described according to Manuscript to be reviewed line with the previous study <ns0:ref type='bibr' target='#b29'>(Liu et al., 2018)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3'>Results and Analysis</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>Unigene function annotations</ns0:head><ns0:p>The length distribution of unigenes is shown in Figure <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>. The unigenes were annotated with seven major functional database annotations (KEGG, GO, NR, NT, SwissProt, Pfam, and KOG). Finally there were 6,554 </ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>Transcription factor (TF) prediction</ns0:head><ns0:p>The TF prediction results showed that the genes belonged to a total of 55 transcription factor families, of which, with the largest number of genes, was the MYB gene family, with a total of 438 genes involved in the expression, followed by the AP2-EREBP gene family with 290 genes, and finally the bHLH gene family with 239 genes (see Figure <ns0:ref type='figure' target='#fig_4'>2</ns0:ref>). Among these transcription factor families, both the MYB family and the WRKY family (including 208 genes) are involved in plant growth and development processes, which can provide relevant information for our subsequent screening of growth-related genes.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>Cluster analysis and GO classification of DEGs</ns0:head><ns0:p>The number of up-regulated genes in diploid P. tomentosa compared with triploid P. tomentosa was 15,690 and Manuscript to be reviewed the down-regulated gene was 16,971. The scatter plot of DEGs showed that the difference of transcriptional profiles between triploid and diploid samples was obvious (see Figure <ns0:ref type='figure' target='#fig_5'>3</ns0:ref>). The GO function was divided into three branches: molecular function, cellular component, and biological process. Figure <ns0:ref type='figure' target='#fig_6'>4</ns0:ref> shows the functional classification based on differential gene detection. A total of 22,375 differentially expressed genes that had GO annotations were obtained in GO classification entries by using the classification of 32,661 common differential genes. There were 13,720 DEGs in biological processes, including 6,481 up-regulated genes and 6,879 down-regulated genes; 15,963 DEGs in cell composition, including 7,687 up-regulated genes and 8,276 down-regulated genes; and 1,092 DEGs in molecular function, including 8,553 up-regulated genes and 9,539 down-regulated genes.</ns0:p><ns0:p>Among the three branches of GO function entries, the number of DEGs of binding was the largest in molecular function, the number of DEGs of the cell and cell part was the largest in the cellular component, and the number of DEGs of the cellular process was the largest in the biological process. There are 44 DEGs that belonged to lignin production-related transcripts (see Table <ns0:ref type='table'>2</ns0:ref>), which are important for tree breeders. A total of 38 entries were enriched in GO function (Q &#8804; 0.05) (see Table <ns0:ref type='table'>3</ns0:ref>). Biological processes accounted for 36.8% of the total, of which catalytic activity accounted for the largest proportion of biological processes, at 42.86%; cell components accounted for 18.5% of the total, of which cell accounted for 42.85%; and molecular functions accounted for 44.7% of the total, of which catalytic activity accounted for 47.05%.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.4'>Analysis of pathway function of DEGs</ns0:head><ns0:p>Using Q-value &#8804; 0.05 as the standard, 32,661 differential genes were separately analysed by pathway enrichment using the KEGG database. There were 16 significantly enriched KEGG metabolic pathways. Among them, the most frequently occupied pathways were the metabolism branch, with 13, and a total of 19,469 DEGs involved;</ns0:p><ns0:p>the second was the biological system branch, with two, and a total of 1,447 DEGs involved; and finally, the environmental information process branch, with one, with 868 DEGs involved.</ns0:p><ns0:p>The results showed that there were 12,240 significantly different genes annotated in the KEGG pathways of diploid and triploid samples. The top differentially expressed genes significantly enriched six pathways were</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed as follows: 1,115 differential gene expression in the plant-pathogen interaction (KO: ko04626) pathway; 396 differential genes in the phenylpropane biosynthesis (KO: ko00940) pathway; 868 differential genes in the mitogen-activated protein kinase (MAPK) plant signalling pathway (KO: ko04016); 170 differential genes expression in the ascorbate and aldarate metabolism pathway (KO: ko00053); 64 differential genes in the diterpenoid biosynthesis pathway (KO: ko00904); and 43 differential genes in the beets red pigment biosynthesis pathway (KO: ko00965). All differentially expressed genes significantly enriched pathways were shown in Table <ns0:ref type='table'>4</ns0:ref>. The results showed that there were 496 DEGs upregulated and 619 downregulated in the plant-pathogen interaction pathway, and that there were 864 DEGs enriched in the organismal systems category of GO Manuscript to be reviewed addition, there were 104 differential genes in the plant-pathogen interaction pathway that had zero expression in the triploid poplar.</ns0:p><ns0:p>In the process of analysing the growth-related pathways, it was found that the growth-related genes were up-regulated and down-regulated, so it was difficult to explain the difference between diploid and triploid samples. The NCBI database was used for gene information annotation; the details are shown in Table <ns0:ref type='table'>5</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.5'>RT-qPCR validation</ns0:head><ns0:p>Genes related to growth which up-regulated in the triploid P. tomentosa compared to diploid P. tomentosa, as candidate markers for plant breeders in the future, were selected for RT-qPCR validation. There was no peak in the dissolution curves of RT-qPCR products of GH3, CA, and A-ARR gene. And the other seven genes showed a single peak curve, indicating that their amplification products did not contain primer dimers or nonspecific amplification products, and each primer PCR reaction was specific. The results of comparison of the transcriptome analysis and the RT-qPCR analysis are shown in Figure <ns0:ref type='figure' target='#fig_7'>5A</ns0:ref>. In diploid plants, the expression levels of the SAUR, FDP, ALDH, AUX1 and ABF in the RT-qPCR analysis were significantly higher than those in the transcriptome analysis. In triploid plants, the expression levels of the ALDH and AUX1 in the RT-qPCR analysis were significantly lower than those in the transcriptome analysis, whereas the expression levels of the malate dehydrogenase (MDH) and CYCD3 in the RT-qPCR analysis were significantly higher than those in the transcriptome analysis. The expression levels of AUX1, CYCD3, and MDH in tissue-cultured triploid poplar were higher than those of tissue-cultured diploid samples, which were consistent with the changes of TMM values calculated by transcriptome. Among them, the expression levels of the AUX1 gene in triploid samples were significantly higher than those in diploid samples (about 6.88 times, logFC value). However, the expression of the ABF gene in diploid samples was higher than that of triploid samples, which was not in accordance with the TMM values. In further experiments, the expression levels of MDH and CYCD3 in tissue-cultured and greenhouse planted triploid poplar were significantly higher than those of tissue-cultured and greenhouse planted diploid samples. And the expression levels of MDH and CYCD3 increased with the age gradually (Figure <ns0:ref type='figure' target='#fig_7'>5</ns0:ref>, B and C).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='4'>Discussion</ns0:head><ns0:p>The transcriptome analysis of the new rooting stem segments of diploid and triploid P. tomentosa showed that most of the significantly different genes were concentrated in plant-pathogen interaction, phenylpropane biosynthesis pathway, and MAPK signalling pathway-plant. Under the condition of comprehensive screening of the GO function enrichment and KEGG function analysis of transcriptome data, it is difficult to determine the expression of specific genes when the genes associated with plant growth appear up-regulated and downregulated. <ns0:ref type='bibr' target='#b13'>Huang et al (1990)</ns0:ref> shown there to be larger branches, leaves and fruits in the triploid variety of pear when compared to the diploid variety. And the production of tetraploid radish is 20% higher than that of ordinary diploids <ns0:ref type='bibr'>(Liu et al., 2003)</ns0:ref>. <ns0:ref type='bibr'>Zhu et al. (1995)</ns0:ref> reported that allotriploidy of P. tomentosa had greater values than diploidy under the same growth conditions in tree height, diameter at breast height, and single plant volume at the age of eight years.</ns0:p><ns0:p>It is interesting that although the transcriptome of the diploidy and triploidy of P. tomentosa was analysed here, according to the annotations of the specific species distribution chart, only 3.26% was annotated by P.</ns0:p><ns0:p>tomentosa. This may partly be due to the fact that the triploid materials used in this study were obtained by the hybridised P. bolleana, and some of the mRNAs did not belong in P. tomentosa. Of course, it may also partly be due to the fact that the plant stems were taken from annual plants in this study, which is different to previous studies on P. tomentosa. Previous studies on the transcriptome analysis of P. tomentosa were mostly based on aseptic seedlings, root one-month-old stem and leaf sample materials <ns0:ref type='bibr' target='#b0'>(An et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b21'>Wang et al., 2018)</ns0:ref>, and the expression of mRNA was organ-specific <ns0:ref type='bibr'>(Ohtsuki et al., 2005)</ns0:ref>. The phytohormone signal transduction pathway controls plant cell division, cell elongation, cell enlargement, and stem elongation, which is closely related to plant growth and development <ns0:ref type='bibr'>(Guo et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Compared with previous data of transcriptome analysis on phytohormone signal transduction, we selected AUX1, GH3, A-ARR, CYCD3, ABF and five other genes for the RT-qPCR validation. Huge differences were found between the expression levels of the selected genes in the RT-qPCR analysis and those of the transcriptome analysis, and we inferred that it might be due to the different growth stages of the experiment's materials.</ns0:p><ns0:p>Photosynthesis is an important metabolic process in plants, and its strength has an important effect on plant</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed growth, development, and stress resistance. Li and <ns0:ref type='bibr'>Zhang (2006)</ns0:ref> found that the lower leaves of the fast-growing triploid P. tomentosa clones could maintain a higher photosynthetic rate when measuring the leaf net photosynthetic rate of diploid and triploid P. tomentosa. Photosynthesis includes a series of complex reactions in which carbon fixation is a central link in the regulation of photosynthesis <ns0:ref type='bibr'>(Feng et al., 2006)</ns0:ref>. We compared the data of carbon fixation pathways in previous photosynthetic organism kiwifruit <ns0:ref type='bibr'>(Li et al., 2019b)</ns0:ref> and selected the up-regulated malate dehydrogenase (MDH) for the RT-qPCR validation, and the expression levels of MDH gene were up-regulated in triploid P. tomentosa plants, compared to the diploid ones.</ns0:p><ns0:p>With the possible exception of the stomatal dimension, the response to polyploidy can be very variable and complex. It has been proved in oilseed rape <ns0:ref type='bibr' target='#b2'>(Bancroft et al., 2011</ns0:ref><ns0:ref type='bibr'>), sugarcane (Manners and Casu, 2011</ns0:ref><ns0:ref type='bibr'>), cotton (Rambani et al., 2014)</ns0:ref>, wheat <ns0:ref type='bibr' target='#b18'>(Leach et al., 2014</ns0:ref><ns0:ref type='bibr'>), kiwifruit (Li et al., 2019b</ns0:ref><ns0:ref type='bibr'>), rice (Shenton et al., 2020)</ns0:ref> and numerous studies in Arabidopsis species, some of which specifically consider triploidy <ns0:ref type='bibr'>(Fort et al., 2016;</ns0:ref><ns0:ref type='bibr'>2017;</ns0:ref><ns0:ref type='bibr'>Pacey et al., 2019)</ns0:ref>. Related to the phenomenon, the gene expression levels were not upregulated in any polyploid plant, and over-, under-or mixed-expression of genes were found in the polyploid plant <ns0:ref type='bibr'>(Osborn et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b9'>Gutierrez-Gonzalez and Garvin, 2017;</ns0:ref><ns0:ref type='bibr'>Li et al., 2019b)</ns0:ref>. Some genes in polyploid plants were upregulated while others were downregulated compared to diploid plants, which was also found in this study. It illustrated that the allopolyploidy -in particular in P. tomentosa -also alter the gene expression profile and levels as well as those in autopolyploid plants, compared to their diploid relatives. In this study, the expression levels that related to the growth genes such as MDH and CYCD3 in triploid P. tomentosa were higher than those of diploid P. tomentosa. MDH is mainly involved in the metabolism of plant photosynthesis <ns0:ref type='bibr'>(Sawada et al., 2002)</ns0:ref>. The main function of the protein encoded by the MDH gene is to control the carbon dioxide levels during photosynthesis <ns0:ref type='bibr'>(Sawada et al., 2002)</ns0:ref>. Higher expression levels of the MDH gene was proved to be related to higher rates of photosynthesis <ns0:ref type='bibr' target='#b16'>(Kandoi et al., 2018)</ns0:ref>, which in turn contributes to higher timber yield. CYCLIN D3 (CYCD3) is a cell-cycle gene, and overexpression of CYCLIN D3;1 (CYCD3;1) in transgenic plants can increase mitotic cycles and reduce endocycles <ns0:ref type='bibr'>(Menges et al., 2006)</ns0:ref>. Manuscript to be reviewed meaningful. There were many DEGs between the diploid and triploid poplar plants that were enriched for a plantpathogen interaction pathway, stress resistance and several growth-related transcripts too. Genes in the plantpathogen interaction pathway are known to be diverse and large in plants and are known to be involved in reproduction isolation across Arabidopsis and Poplars too <ns0:ref type='bibr'>(Liao et al., 2014;</ns0:ref><ns0:ref type='bibr'>Qian et al., 2018)</ns0:ref>. In this study, one differential gene of the developmental process involved in reproduction was also found in the plant-pathogen interaction pathway. Further, the enrichment of differential expression transcripts in this category could provide useful information to tree breeders who intend to generate heterotic F1s. The pathway enrichment approach also shows several other interesting candidates that would be worth elaborating on in the future relating to studies demonstrating higher stress resistance in the triploid poplar.</ns0:p></ns0:div> <ns0:div><ns0:head n='5'>Conclusion</ns0:head><ns0:p>A total of 32,661 DEGs were identified in triploid and diploid Chinese white poplar, of which 15,690 were upregulated and 16,971 were down-regulated in triploidy compared to diploidy. Through the comprehensive analysis of GO functional enrichment analysis and the pathway functional annotation of transcriptome data of diploid and triploid P. tomentosa, no significantly enriched entries and pathways related to growth were found.</ns0:p><ns0:p>Compared to diploidy, the growth-related genes were found to be up-regulated and down-regulated in the natural diploid and triploid P. tomentosa trees. Although the expression levels of genes were unstable in the different environments and different growth stages, the expression levels of MDH and CYCD3 in triploid P. tomentosa were higher than those of diploid P. tomentosa in young tree tissue, which was consistent with the values calculated using the transcriptome data.</ns0:p></ns0:div> <ns0:div><ns0:head>Availability of data and material</ns0:head><ns0:p>All data generated or analyzed during this study are included in this published article. RNA-Seq data were presented at the Genome Sequence Archive of the Beijing Institute of Genomics (BIG) Data Center (accession number PRJCA002269, https://bigd.big.ac.cn/search?dbId=biosample&amp;q=PRJCA002269).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed preprocessing of high-throughput sequencing data.</ns0:p><ns0:p>Gigascience, 2018,7(1):1-6. doi: 10.1093/gigascience/gix120. Ci D, Tian M, Song Y, Du Q, Quan M, Xuan A, Yu J, Yuan Z, Manuscript to be reviewed Manuscript to be reviewed TP, triploid plants. These plants were tissue culture plants and planted in greenhouse. 1, 1 month old; 2, 4 months old; 3, 7 months old; 4,10 months old; 5, 13 months old. **, the difference is very significant (P-value&lt;0.01). RT-qPCR was performed on 3 diploid and 3 triploid plants, which were driven from the same tree used for transcriptome analysis, normalized with housekeeping gene EF1&#945;, repeated 3 times. The 2 <ns0:ref type='bibr'>(-&#9651;&#9651;Ct)</ns0:ref> method was utilized to process the data <ns0:ref type='bibr' target='#b29'>(Liu et al., 2018)</ns0:ref>. Because the difference of the values in Figure <ns0:ref type='figure' target='#fig_7'>5A</ns0:ref> was too big, the y-axis of Figure <ns0:ref type='figure' target='#fig_7'>5A</ns0:ref> was changed to a log scale. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Li et al. (2019b) on a Bio-Rad CFX96TM Real-time PCR Detection System (Bio-Rad, California, USA), with a final volume of 25.0 &#956;l, containing 2.5 units of Taq DNA polymerase, 0.4 mM deoxyribonucleotides (dNTPs), 20 &#956;l of ddH 2 O, 1 &#956;l of cDNA, and 500 nM of each primer. Each sample was carried out in triplicate for the RT-qPCR reactions. The data were normalised with the housekeeping gene EF1&#945;, and the method was employed in PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>CYCD3 was found to regulate cambial cell proliferation and secondary growth, and the protein encoded by the CYCD3 gene is required for normal vascular development in Arabidopsis (Collins et al., 2015). Previous studies have indicated a relationship between faster growth and the increased expression of the CYCD3 gene. Hence, the upregulation of MDH and CYCD3 in the triploids is biologically PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1 Length distribution of unigenes.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 Classification of the family of transcription factors.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3 Scatter plot of log diploid and triploid expression data.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4 GO secondary node annotation statistics of differential expression genes.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure5Comparison of the transcriptome analysis and the RT-qPCR analysis.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 1 Figure 1 2 Figure 2</ns0:head><ns0:label>1122</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 3 Figure 3 4 Figure 4</ns0:head><ns0:label>3344</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 5 Figure 5</ns0:head><ns0:label>55</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head /><ns0:label /><ns0:figDesc>acid has long-term effects on long non-coding RNA gene methylation and growth in Populus tomentosa.Statistical Distributions, New York: Wiley-Interscience, Third edition, 2000. Fan B, Li X, Zhang J, Chen W, Dong H. Decomposition of triploid populus tomentosa fine root and Lolium multiflorum grass root in a composite ecosystem and their nutrient dynamics. Ying Yong Sheng Tai Xue Bao, 2005, 16(11):2030-4. in Chinese.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Molecular Genetics</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='6'>and Genomics, 2019, 294(6):1511-1525. doi: 10.1007/s00438-019-01593-5.</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>Collins C, Maruthi NM, Jahn CE. CYCD3 D-type cyclins regulate cambial cell proliferation and secondary</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='6'>growth in Arabidopsis. Journal of Experimental Botany, 2015, 66(15):4595-606. doi: 10.1093/jxb/erv218.</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>Evans M, Hastings N, Peacock B. Feng X, Jia Y, Zhu R, Chen K, Chen Y. Characterization and analysis of the transcriptome in Gymnocypris</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='6'>selincuoensis on the Qinghai-Tibetan Plateau using single-molecule long-read sequencing and RNA-</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='6'>seq, DNA Research, 2019, 26(4): 353-363. https://doi.org/10.1093/dnares/dsz014.</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>Feng Y, Chen X, Shi D, Wang Q. Expression of rice cytoplasmic FBA gene in Anabaena 7120 and its regulation</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='5'>on photosynthesis. Plant Research, 2006 (06): 691-698. in Chinese</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='7'>Fort A, Ryder P, McKeown PC, Wijnen C, Aarts MG, Sulpice R, Spillane C. Disaggregating polyploidy,</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='6'>parental genome dosage and hybridity contributions to heterosis in Arabidopsis thaliana. New</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='6'>Phytologist, 2016, 209(2):590-9. doi: 10.1111/nph.13650. Epub 2015 Sep 23.</ns0:cell></ns0:row><ns0:row><ns0:cell>Fort</ns0:cell><ns0:cell>A, Tuteja</ns0:cell><ns0:cell>R, Braud</ns0:cell><ns0:cell>M, McKeown</ns0:cell><ns0:cell>PC, Spillane</ns0:cell><ns0:cell>C.</ns0:cell><ns0:cell>Parental-genome dosage effects on</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='6'>the transcriptome of F1 hybrid triploid embryos of Arabidopsis thaliana. Plant Journal, 2017, 92(6):1044-</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='4'>1058. doi: 10.1111/tpj.13740. Epub 2017 Nov 28.</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='5'>PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table . 1</ns0:head><ns0:label>.</ns0:label><ns0:figDesc>The primers used in the RT-qPCR analysis.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell>F&#65306;TGCTGGTGGACTTGAGGATT</ns0:cell><ns0:cell>168</ns0:cell></ns0:row><ns0:row><ns0:cell>1</ns0:cell><ns0:cell>ALDH</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;ATCAAAGAAATGGAGAATAGGCAGA</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Gene Symbol</ns0:cell><ns0:cell>Upstream and Downstream primer sequence(5&#8594;3)</ns0:cell><ns0:cell>Product length</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;GGCAAGGAGAAGGTACACAT</ns0:cell><ns0:cell>204</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>EF1a</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;CAATCACACGCTTGTCAATA</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;TGGATCTGTCATTCAACTTATTGCT</ns0:cell><ns0:cell>143</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>AUX1</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;AAATACGGTAGTTATGAAAAGAGGGTAT</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;GGACACCGGAAAGAAGAAGGT</ns0:cell><ns0:cell>211</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>GH3</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;CCCTGAAACATCCTAATCAAGCTAC</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;AAATCAGGGGGAGCTCTCTT</ns0:cell><ns0:cell>100</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>A-ARR</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;TTCTACACTTCTGTTGAGCCTGT</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;TGCTCTGCTCTCTCTTTGTTCG</ns0:cell><ns0:cell>216</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>CYCD3</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;CCACTGAAAATCTCACGCCAATC</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;TGGAAAGTGGCAAGTGGGAA</ns0:cell><ns0:cell>134</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>ABF</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;TCAAGACACTGGCAAAGGCA</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;CCGGCTTCATCCACTAGACTC</ns0:cell><ns0:cell>153</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>MDH</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;GAAGGGAAGGGGTGATACCG</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;AGAGATTATAATGGCCAGCACCAG</ns0:cell><ns0:cell>178</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>CA</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;TGGCCCTTTTCCAGTTCCTT</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;ACTCCCAAACACCAAACGAGA</ns0:cell><ns0:cell>136</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>FDP</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;AGCCCACTTGGTATTGGAGC</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>F&#65306;TGCCAAGCAAATTTTCCGCC</ns0:cell><ns0:cell>105</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>SAUR</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>R&#65306;ACTGGAACCACAAATCGCTTC</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)Manuscript to be reviewed</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table . 3</ns0:head><ns0:label>.</ns0:label><ns0:figDesc>Entries were enriched in GO function.</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='2'>DNA binding</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='4'>GO:0046658 Anchored component of</ns0:cell><ns0:cell>Cellular component</ns0:cell><ns0:cell>Cell</ns0:cell><ns0:cell>0.565 0.002</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>GO Term ID GO Term plasma membrane</ns0:cell><ns0:cell /><ns0:cell>Level 1 a</ns0:cell><ns0:cell>Level 2 b</ns0:cell><ns0:cell>Rich</ns0:cell><ns0:cell>Q-value</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Ratio</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>GO:0009611 Response to wounding</ns0:cell><ns0:cell /><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Response to stimulus</ns0:cell><ns0:cell>0.613 0.002</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>GO:0043531 ADP binding</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Molecular function</ns0:cell><ns0:cell>Binding</ns0:cell><ns0:cell>0.649 5.07E-40</ns0:cell></ns0:row><ns0:row><ns0:cell>GO:0048046 Apoplast</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Cellular component</ns0:cell><ns0:cell cols='2'>Extracellular region</ns0:cell><ns0:cell>0.609 0.002</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>GO:0007165 Signal transduction</ns0:cell><ns0:cell /><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Biological regulation</ns0:cell><ns0:cell>0.607 1.54E-32</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:2000022 Regulation of jasmonic acid</ns0:cell><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Biological regulation</ns0:cell><ns0:cell>0.625 0.002</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0006952 Defense response mediated signaling pathway</ns0:cell><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Response to stimulus</ns0:cell><ns0:cell>0.613 2.75E-24</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0046914 Transition metalion binding GO:1903507 Negative regulation of</ns0:cell><ns0:cell>Molecular function Biological process</ns0:cell><ns0:cell cols='2'>Binding Biological regulation</ns0:cell><ns0:cell>0.675 1.49E-09 0.629 0.003</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0046916 Cellular transition metalion nucleic acid-templated</ns0:cell><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Biological regulation</ns0:cell><ns0:cell>0.677 1.49E-09</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>homeostasis transcription</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>GO:0030001 Metalion transport GO:0000977 RNA polymerase</ns0:cell><ns0:cell>II</ns0:cell><ns0:cell>Biological process Molecular function</ns0:cell><ns0:cell>Localization Binding</ns0:cell><ns0:cell>0.644 2.10E-08 0.570 0.003</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>regulatory region sequence-</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>GO:0005886 Plasma membrane specific DNA binding</ns0:cell><ns0:cell /><ns0:cell>Cellular component</ns0:cell><ns0:cell>Cell</ns0:cell><ns0:cell>0.494 1.64E-06</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0016021 Integral GO:0003700 DNA binding transcription component of</ns0:cell><ns0:cell>Cellular component Molecular function</ns0:cell><ns0:cell>Membrane part Transcription</ns0:cell><ns0:cell>regulator</ns0:cell><ns0:cell>0.461 3.73E-06 0.497 0.003</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>membrane factor activity</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>activity</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>GO:0007205 Protein kinase C-activating GO:0003839 Gamma-</ns0:cell><ns0:cell>Biological process Molecular function</ns0:cell><ns0:cell cols='2'>Biological regulation Catalytic activity</ns0:cell><ns0:cell>0.8 0.941 0.004 9.92E-05</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>G-protein coupled receptor glutamylcyclotransferase</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>signaling pathway activity</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='4'>GO:0031347 Regulation GO:0006979 Response to oxidative stress of defense</ns0:cell><ns0:cell>Biological process Biological process</ns0:cell><ns0:cell cols='2'>Biological regulation Response to stimulus</ns0:cell><ns0:cell>0.618 9.92E-05 0.596 0.006</ns0:cell></ns0:row><ns0:row><ns0:cell>response</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>GO:0005576 Extracellular region</ns0:cell><ns0:cell /><ns0:cell>Cellular component</ns0:cell><ns0:cell cols='2'>Extracellular region</ns0:cell><ns0:cell>0.541 0.006</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>GO:0004143 Diacylglycerol</ns0:cell><ns0:cell cols='2'>kinase</ns0:cell><ns0:cell>Molecular function</ns0:cell><ns0:cell>Catalytic activity</ns0:cell><ns0:cell>0.8</ns0:cell><ns0:cell>9.99E-05</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>activity GO:0016298 Lipase activity</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Molecular function</ns0:cell><ns0:cell>Catalytic activity</ns0:cell><ns0:cell>0.698 0.006</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>GO:0006351 Transcription, GO:0016020 Membrane</ns0:cell><ns0:cell cols='2'>DNA-</ns0:cell><ns0:cell>Biological process Cellular component</ns0:cell><ns0:cell>Cellular process Membrane</ns0:cell><ns0:cell>0.491 0.001 0.501 0.007</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>templated GO:0006629 Lipid metabolic process</ns0:cell><ns0:cell /><ns0:cell>Biological process</ns0:cell><ns0:cell cols='2'>Metabolic process</ns0:cell><ns0:cell>0.550 0.010</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>GO:0001228 Transcriptional GO:0016747 Transferase</ns0:cell><ns0:cell cols='2'>activator activity,</ns0:cell><ns0:cell>Molecular function Molecular function</ns0:cell><ns0:cell>Transcription Catalytic activity</ns0:cell><ns0:cell>regulator</ns0:cell><ns0:cell>0.592 0.002 0.578 0.012</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>activity, RNA polymerase II transferring acyl groups</ns0:cell><ns0:cell /><ns0:cell>activity</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>transcription other than</ns0:cell><ns0:cell cols='2'>regulatory amino-acyl</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>region groups</ns0:cell><ns0:cell cols='3'>sequence-specific</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:48280:2:0:CHECK 31 Aug 2020)Manuscript to be reviewed</ns0:note></ns0:figure> </ns0:body> "

"Responce Thank you for the revisions. The manuscript is indeed improved. I would encourage you to read through carefully (or hire a service to do so) for grammar -- in several places the grammar still leads to ambiguous sentences that are difficult to understand. Answer: Thanks. We have asked a service ( Proofed Inc.(UK)) to read through carefully. I'm not sure why you can't answer the reviewer question about genes with zero expression in the triploid? Surely some of the DEGs must have zero expression in triploid? I also may have missed it but don't see the reviewer's request to include different GO terms between the diploid and triploid? Answer: The reviewer have asked us to get a simple summary of how many genes in plant-pathogen interaction pathway have zero expression in the triploid poplar or are associated with different GO node terms relative to the diploid. Hence, we summarized the genes in plant-pathogen interaction pathway have zero expression in the triploid poplar and the genes associated with different GO node terms relative to the diploid (see below). The differential genes in the plant-pathogen interaction (KO: ko04626) pathway could be enriched in 46 GO function entries. These GO function entries are integral components to fungus and ribosome biogenesis in the following components: the membrane, signal transduction, defence response, DNA-templated transcription, calcium ion binding, ADP binding, regulation of membrane potential, cell surface receptor signalling pathway, abscisic acid-activated signalling pathway, protein phosphorylation, peptidyl-serine phosphorylation, lipid metabolic process, intracellular signal transduction, proteolysis, protein autophosphorylation, ATP binding, plasma membrane, mRNA transcription, protein folding, 2-alkenal reductase [NAD(P)] activity, activation of protein kinase activity, kinase activity, regulation of mitotic cell cycle, calcium ion homeostasis, signal transduction by protein phosphorylation, intracellular, response to stress, membrane, extracellular region, metal ion transport, primary miRNA processing, stress-activated protein kinase signalling cascade, cellular transition metal ion homeostasis, response to temperature stimulus, calmodulin-dependent protein kinase activity, mitochondrion, endosome, protein kinase activity, developmental process involved in reproduction, DNA-templated regulation of transcription, plant-type hypersensitive response, defence response to bacterium, incompatible interaction, lipid catabolic process, pre-miRNA processing and defence response. Among them, the top five entries were 184 differential genes in the integral component of membrane, 174 in the signal transduction, 145 in defence response, 128 in DNA-templated transcription and 53 in calcium ion binding. In addition, there were 104 differential genes in the plant-pathogen interaction pathway that had zero expression in the triploid poplar. Please be sure your plots include information on what the whiskers represent (standard errors? deviation? confidence interval?). Answer: The whiskers are standard deviation bars. We had added the information into the text. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The perception of facial attractiveness is a complex phenomenon which depends on how the observer perceives not only individual facial features, but also their mutual influence and interplay. In the machine learning community, this problem is typically tackled as a problem of regression of the subject-averaged rating assigned to natural faces. However, it has been conjectured that this approach does not capture the complexity of the phenomenon. A recent original experiment (Ib&#225;&#241;ez-Berganza et al., Scientific Reports 9, 8364, 2019) allowed different human subjects to navigate the face-space and 'sculpt' their preferred modification of a reference facial portrait. Here we present an unsupervised inference study of the set of sculpted facial vectors in this experiment. We first infer minimal, interpretable and accurate probabilistic models (through Maximum Entropy and artificial neural networks) of the preferred facial variations, that encode the inter-subject variance. The application of such generative models to the supervised classification of the gender of the subject that sculpted the face reveals that it may be predicted with astonishingly high accuracy. We observe that the classification accuracy improves by increasing the order of the non-linear effective interaction. This suggests that the cognitive mechanisms related to facial discrimination in the brain do not involve the positions of single facial landmarks only, but mainly the mutual influence of couples, and even triplets and quadruplets of landmarks. Furthermore, the high prediction accuracy of the subjects' gender suggests that much relevant information regarding the subjects may influence (and be elicited from) their facial preference criteria, in agreement with the multiple motive theory of attractiveness proposed in previous works.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head n='1'>INTRODUCTION</ns0:head><ns0:p>Human facial perception (of identity, emotions, personality dimensions, attractiveness) has been the subject of intense and multidisciplinary research in the last decades <ns0:ref type='bibr' target='#b50'>(Walker and Vetter (2016)</ns0:ref>; <ns0:ref type='bibr' target='#b24'>Little et al. (2011)</ns0:ref>; <ns0:ref type='bibr' target='#b22'>Leopold and Rhodes (2010)</ns0:ref>). In particular, facial attractiveness is a research topic that involves many different disciplines, from evolutionary biology and psychology to neuroscience <ns0:ref type='bibr' target='#b7'>(Bzdok et al. (2011)</ns0:ref>; <ns0:ref type='bibr' target='#b15'>Hahn and Perrett (2014)</ns0:ref>; <ns0:ref type='bibr' target='#b21'>Laurentini and Bottino (2014)</ns0:ref>; <ns0:ref type='bibr' target='#b25'>Little (2014)</ns0:ref>; <ns0:ref type='bibr' target='#b45'>Thornhill and Gangestad (1999)</ns0:ref>). Furthermore, it is an interesting case of study in the machine learning research community, as a paradigm of a complex cognitive phenomenon, ruled by complex and difficult to infer criteria. Indeed, the rules according to which a facial image will probably result pleasant are poorly known <ns0:ref type='bibr' target='#b24'>(Little et al. (2011)</ns0:ref>). The most relevant face-space variables in terms of which such rules should be inferred remain elusive as well <ns0:ref type='bibr' target='#b21'>(Laurentini and Bottino (2014)</ns0:ref>).</ns0:p><ns0:p>Many works have discussed, in the context of evolutionary biology, the validity of the so called natural selection hypothesis <ns0:ref type='bibr' target='#b24'>(Little et al. (2011)</ns0:ref>; <ns0:ref type='bibr' target='#b39'>Rhodes (2006)</ns0:ref>), according to which the traits that we recognise as attractive are markers of a good phenotypic condition. Along with natural selection, also sexual selection and the handicap principle are known to play a role in facial attractiveness <ns0:ref type='bibr'>(Thornhill</ns0:ref> PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed and Gangestad (1999)).</ns0:p><ns0:p>The evolutionary approach explains several aspects of the phenomenon, such as the impact in facial attractiveness of facial traits that are known to covary with a good phenotypic condition (averageness, symmetry, secondary sexual traits). Despite the success of the evolutionary approach, it is known that there are aspects of facial attractiveness which elude an evolutionary explanation. The natural selection hypothesis implies that the perception of attractiveness is mainly universal, species-typical. While a certain degree of universality has been assessed in many references, cultural and inter-person differences definitely play a role, beyond the species-typical criterion <ns0:ref type='bibr' target='#b25'>(Little (2014)</ns0:ref>). Several factors are known to influence the single subject idiosyncrasies, such as the subject's self-and other-rated attractiveness, genetic propensity, sexual orientation, and the menstrual cycle (see references in <ns0:ref type='bibr' target='#b37'>Oh et al. (2019b)</ns0:ref>).</ns0:p><ns0:p>Recently, many works have argued (the multiple motive hypothesis) that the evaluation of facial attractiveness is a complex process, influenced by the prior inference of semantic personality traits (such as dominance, extroversion or trustworthiness) that we consensually attribute to specific shape and luminance patterns in others' face <ns0:ref type='bibr'>(Oh et al. (2019a,b)</ns0:ref>; <ns0:ref type='bibr' target='#b0'>Abir et al. (2017)</ns0:ref>; <ns0:ref type='bibr' target='#b50'>Walker and Vetter (2016)</ns0:ref>; <ns0:ref type='bibr' target='#b1'>Adolphs et al. (2016)</ns0:ref>; <ns0:ref type='bibr' target='#b14'>Galantucci et al. (2014)</ns0:ref>; <ns0:ref type='bibr' target='#b25'>Little (2014)</ns0:ref>; <ns0:ref type='bibr' target='#b47'>Todorov and Oosterhof (2011)</ns0:ref>; <ns0:ref type='bibr' target='#b38'>Oosterhof and Todorov (2008)</ns0:ref>; <ns0:ref type='bibr' target='#b12'>Edler (2001)</ns0:ref>; <ns0:ref type='bibr' target='#b11'>Cunningham et al. (1995)</ns0:ref>). According to this scenario, facial attractiveness is influenced by the single-subject relative inclination towards some fundamental personality traits. In the word of <ns0:ref type='bibr' target='#b36'>Oh et al. (2019a)</ns0:ref>, individuals who highly value a personality trait, such as dominance, are likely to perceive faces that appear to possess the trait as attractive. This implies, in particular, that (A) the single subject preferred faces are expected to be, to some extent, distinguishable if characterised or inferred with sufficient accuracy, and (B) they are expected to reflect meaningful information regarding the subject.</ns0:p><ns0:p>The assessment of the validity of these hypotheses is, arguably, strongly influenced by the experimental precision with which the individuals' preferred faces can be characterised. While the natural selection hypothesis explains general aspects of facial attractiveness, if the experiments allow to resolve the single subjects' idiosyncrasies, more complex aspects and a strong subjectivity emerge <ns0:ref type='bibr' target='#b18'>(H&#246;nekopp (2006);</ns0:ref><ns0:ref type='bibr' target='#b37'>Oh et al. (2019b)</ns0:ref>). In particular, the subjectivity of facial attractiveness has been proven to be underestimated by the common experimental method from which most of the works draw their conclusions: the subjectaveraged rating assigned to several natural facial images <ns0:ref type='bibr' target='#b18'>(H&#246;nekopp (2006)</ns0:ref>). Moreover, it has been argued that the average rating may suffer, as an experimental technique, the curse of dimensionality (the face-space being highly dimensional) and may consequently hinder the complexity and subjectivity of the phenomenon <ns0:ref type='bibr' target='#b21'>(Laurentini and Bottino (2014)</ns0:ref>; <ns0:ref type='bibr' target='#b49'>Valentine et al. (2016)</ns0:ref>; <ns0:ref type='bibr' target='#b19'>Ib&#225;&#241;ez-Berganza et al. (2019)</ns0:ref>).</ns0:p><ns0:p>Roughly half of the variance in attractiveness ratings has been attributed to idiosyncratic preferences, the other half to shared preferences <ns0:ref type='bibr' target='#b18'>(H&#246;nekopp (2006)</ns0:ref>). It is a natural question whether such idiosyncratic proportion would result more prominent using an experimental method that bypasses the use of ratings. This motivates the search for alternative experimental approaches. <ns0:ref type='bibr' target='#b19'>Ib&#225;&#241;ez-Berganza et al. (2019)</ns0:ref> investigated the question (A) by means of an innovative experimental technique which permits the sampling of a single subject's preferred region in the face-space. 1 As a matter of fact, the method allows the sampling of the subjects' preferred facial modifications with high precision. It is observed that, within the experimental precision (limited by the time that the subjects dedicate to the experiment), different subjects 'sculpt' distinguishable facial modifications. Indeed, when repeating the experiment, they tend to sculpt facial modifications which are more similar to the ones that they already sculpted than to those sculpted by others, in &#8764; 82% of the cases.</ns0:p><ns0:p>In the present work we present an inference analysis of the data collected in reference <ns0:ref type='bibr' target='#b19'>(Ib&#225;&#241;ez-Berganza et al. (2019)</ns0:ref>), developing data-driven probabilistic generative models that describe the intersubject fluctuations around the average landmark positions. As previously stated, such fluctuations are expected to reflect and encode meaningful differences among experimental subjects. Indeed, we thereafter apply such models to the investigation of the aforementioned prediction (B); that is, whether we could elicit meaningful information regarding the subject from her/his preferred facial modifications. In particular, we address whether one may correctly predict the gender of the sculpting subject from such data. Many references have reported quantitative differences between male and female perception of 1 The alternative experimental technique allows a given subject to seek her/his preferred variation of a reference facial portrait. Such variations differ only in a low-dimensional face-space of essential facial features. It is arguably the introduction of these two ingredients: the reduction of facial degrees of freedom and the possibility to efficiently explore the face-space (rather than rating facial images differing in many facial dimensions) that allows for a significant experimental distinction of different subject's criteria (see the SI for further details).</ns0:p></ns0:div> <ns0:div><ns0:head>2/14</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed facial attractiveness. Generally, males prefer smaller lower face area, higher cheekbones, larger mouths and eyes (see references in <ns0:ref type='bibr' target='#b24'>Little et al. (2011)</ns0:ref>; <ns0:ref type='bibr' target='#b39'>Rhodes (2006)</ns0:ref>; <ns0:ref type='bibr' target='#b45'>Thornhill and Gangestad (1999)</ns0:ref>). These facts are compatible with the results of <ns0:ref type='bibr' target='#b19'>Ib&#225;&#241;ez-Berganza et al. (2019)</ns0:ref>. In the present work we go one step further and demonstrate that gender, besides having an impact on the subject-averaged facial sculptures, can actually be predicted with almost certainty for single subjects, based on their facial modifications.</ns0:p><ns0:p>Our inference protocol allows the assessment of the relative influence of linear and non-linear correlations among facial coordinates in the classification, hence overcoming the black-box issue. In particular, we infer, in an unsupervised way, a collection of probabilistic generative models from the database of sculpted facial modifications S = {f (s) } S s=1 (where s is the subject index). Afterwards we assess the predictive power of the models, in two ways. (1) We evaluate the consistency of the simplest of such models, in order to ensure that all of them provide a faithful and economic description of the data.</ns0:p><ns0:p>(2)</ns0:p><ns0:p>The models are applied, when inferred from male/female data separately, to the supervised classification of the subject gender of a test-set and the results are compared with a powerful, specific algorithm for supervised classification, the random forest algorithm.</ns0:p><ns0:p>We infer, in particular, probabilistic models, L (f|&#952; &#952; &#952; ), representing the probability density of a facial image with face-space vector f to be sculpted by any subject (given the reference facial portrait and the sculpture protocol). We have considered three generative models of unsupervised learning: two Maximum Entropy (MaxEnt) models, with linear and non-linear interactions among the facial coordinates, and the Gaussian Restricted Boltzmann Machine (GRBM) model of Artificial Neural Network (ANN). 2</ns0:p><ns0:p>The models presented here are interpretable: the model parameters &#952; &#952; &#952; provide information regarding the relative importance of the various facial distances and their mutual influence in the cognitive process of face perception, which are fundamental questions in the specific literature <ns0:ref type='bibr' target='#b21'>(Laurentini and Bottino (2014)</ns0:ref>). In particular, a comparison of the various models' efficiency highlights the relevance of the nonlinear influence (hence beyond proportions) of facial distances. Finally, this work provides a novel case of study, in the field of cognitive science, for techniques and methods in unsupervised inference and, in particular, a further application of the MaxEnt method <ns0:ref type='bibr' target='#b20'>(Jaynes (1957)</ns0:ref>; <ns0:ref type='bibr' target='#b3'>Berg (2017)</ns0:ref>; Nguyen et al. The structure of the article is as follows. The inference models will be presented in sec. 2, along with some key methodological details. In sec. 3 we analyse the results following our objectives (1,2) described above: we first evaluate the quality of our models as generative models of the set of facial modifications in <ns0:ref type='bibr' target='#b19'>(Ib&#225;&#241;ez-Berganza et al. (2019)</ns0:ref>). Afterwards, we perform a further assessment in which we apply the generative models to the classification of the gender of the subjects from their sculpted facial vectors, and compare the results with that of a purely supervised learning algorithm. We draw our conclusions in sec.</ns0:p><ns0:p>4.</ns0:p></ns0:div> <ns0:div><ns0:head n='2'>MATERIALS AND METHODS</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>Description of the database</ns0:head><ns0:p>We analyse the dataset S described by <ns0:ref type='bibr' target='#b19'>Ib&#225;&#241;ez-Berganza et al. (2019)</ns0:ref>. In such experiments, each subject was allowed to sculpt her/his favorite deformation of a reference portrait (through the interaction with an software which combines image deformation techniques with a genetic algorithm for the efficient search in the face-space). The set of selected images are, hence, artificial, though completely realistic, variations of a common reference portrait (corresponding to a real person). In such a way, only the geometric positions of the landmarks are allowed to vary, the texture degrees of freedom are fixed (and correspond to the reference portrait RP1 (taken from the Chicago database, see <ns0:ref type='bibr' target='#b26'>(Ma et al. (2015)</ns0:ref>) and fig. <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>). This representation of the face is, hence, rooted on a decoupling of geometric (also called shape) and texture (also called reflectance) degrees of freedom <ns0:ref type='bibr' target='#b21'>(Laurentini and Bottino (2014)</ns0:ref>). <ns0:ref type='formula'>2019</ns0:ref>)) (signaled with red points in figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>). We will also refer to the 2D Cartesian vector of the i-th landmark as r i = (x i , y i ), and define the fluctuations of the landmark positions with respect to their average value as</ns0:p><ns0:formula xml:id='formula_0'>&#8710; i = r i &#8722; r i , where &#8226; denotes the experimental average, &#8226; = (1/S) &#8721; s &#8226;. Analogously, &#8710; &#8710; &#8710; (s) = r (s) &#8722; r . An important aspect of</ns0:formula><ns0:p>the dataset is that even the coordinates of the restricted set of n = 8 landmarks, r (s) , are redundant and 3 Many works exploit the geometric/texture decoupling in artificial facial images to study separately the effect of both kinds of coordinates. It is also a natural strategy of dimensionality reduction of the human face, that has been observed to be implemented in both the neural code for facial identification in the brain and by artificial neural networks <ns0:ref type='bibr' target='#b9'>(Chang and Tsao (2017)</ns0:ref>; <ns0:ref type='bibr' target='#b16'>Higgins et al. (2020)</ns0:ref>). In (Ib&#225;&#241;ez-Berganza et al. ( <ns0:ref type='formula'>2019</ns0:ref>)), we combine this separation with the use of completely realistic images, thus eliminating the bias that artificial images are known to induce in experiments <ns0:ref type='bibr' target='#b2'>(Balas and Pacella (2015)</ns0:ref>; <ns0:ref type='bibr' target='#b37'>Oh et al. (2019b)</ns0:ref>). 4 Actually, the database S = {r (v,i) } is composed by S = n s &#215; N facial vectors labelled by a single index s = 1, . . . , S or, alternatively, by a tuple of indices (v, i) (v = 1, . . . , n s , i = 1, . . . , N , n s = 95, N = 28) referring to the i-th facial vector sculpted by the v-th subject (in a single genetic experiment, see <ns0:ref type='bibr' target='#b19'>(Ib&#225;&#241;ez-Berganza et al. (2019)</ns0:ref>)). In the SI we present a detailed analysis of the error estimation over the dataset, distinguishing inter-and intra-subject fluctuations. The last ones are, in principle, an artifact of the sculpting process, but they may encode part of the subject's idiosyncrasy. Similarly, the inferred models may be conceived to account for intra-and inter-subject, or only for inter-subject correlations (see the SI).</ns0:p></ns0:div> <ns0:div><ns0:head>4/14</ns0:head><ns0:p>PeerJ reviewing <ns0:ref type='table'>PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:ref> Manuscript to be reviewed depend on 10 coordinates only, due to the presence of 2n &#8722; 10 = 6 constraints that result from the very definition of the face-space. Such constraints are described in detail in the SI.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Unsupervised inference</ns0:head><ns0:p>We now present some non-technical notion of unsupervised learning. In the next subsection we will describe the probabilistic models with which we describe the dataset. These are generative models that induce a likelihood probability density L (&#8226;|&#952; &#952; &#952; ) over the space of facial vectors &#8710; &#8710; &#8710;. The meaning of L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; ) is that the probability of finding a facial vector in an interval of facial vectors I is given by I L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; )d&#8710; &#8710; &#8710;. The probabilistic model L represents a generalisation of the database, from which it is not unambiguously elicited. Indeed, a probabilistic model of the data depends both on the functional form of L (often called simply the model), and on the learning algorithm, or the protocol with which its parameters &#952; &#952; &#952; are inferred form the data.</ns0:p><ns0:p>For the learning algorithm, in the present work we adopt the Maximum Likelihood principle. We fix the parameters to the value that maximises the database likelihood:</ns0:p><ns0:formula xml:id='formula_1'>&#952; &#952; &#952; * = arg max &#952; &#952; &#952; &#8719; s L (&#8710; &#8710; &#8710; (s) |&#952; &#952; &#952; )</ns0:formula><ns0:p>, where the product is over all the samples in the database (please, see Inter-and intra-subject correlations and errors in the SI for further information at this regard).</ns0:p><ns0:p>The functional form is given by the kind of unsupervised model. In this article we will consider three models (2-and 3-MaxEnt, GRBM), that will be described in the following subsections. The 2-and 3-MaxEnt models follows from the Maximum Entropy principle <ns0:ref type='bibr' target='#b20'>(Jaynes (1957)</ns0:ref>; <ns0:ref type='bibr' target='#b3'>Berg (2017)</ns0:ref>; <ns0:ref type='bibr' target='#b35'>Nguyen et al. (2017)</ns0:ref>; <ns0:ref type='bibr' target='#b28'>Martino and Martino (2018)</ns0:ref>), which provides the functional form of the probability distribution L (&#8226;|&#952; &#952; &#952; ) that exhibits maximum entropy and, at the same time, is consistent with the average experimental value of some observables of the data, &#931; , that will be called sufficient statistics. L must satisfy &#931; L = &#931; , where &#8226; L refers to the expected value according to L . In other words, L is the most general probability distributions constrained to exhibit a fixed expectation value of &#931; L (and this value, under the Maximum Likelihood prescription, is given by the corresponding experimental value).</ns0:p><ns0:p>The precise choice of the sufficient statistics determines the functional form of L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; ). A more detailed description is given in the next section and in section Introduction to the Maximum Entropy principle:</ns0:p><ns0:p>Correlations vs effective interactions of the SI.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>The Maximum Entropy models</ns0:head><ns0:p>We propose two MaxEnt probabilistic generative models of the set of selected faces, inferred from the dataset S . In the case of the Gaussian or 2-MaxEnt model, the sufficient statistics is given by the 2n averages &#8710; &#181; and by the 2n &#215; 2n matrix of horizontal, vertical and oblique correlations among couples of vertical and horizontal landmark coordinates, whose components are C &#181;&#957; = &#8710; &#181; &#8710; &#957; . In these equations, the 2n Greek indices &#181; = i, c i denote the c i = x, y coordinates of the i-th landmark. The 2-MaxEnt model probability distribution takes the form (see the SI) of a Maxwell-Boltzmann distribution,</ns0:p><ns0:formula xml:id='formula_2'>L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; ) = 1 Z exp (&#8722;H(&#8710; &#8710; &#8710;|&#952; &#952; &#952; )).</ns0:formula><ns0:p>In this equation, Z is a normalising constant (the partition function, in the language of statistical physics) depending on &#952; &#952; &#952; , and H = H 2 (the Hamiltonian) is the function:</ns0:p><ns0:formula xml:id='formula_3'>H 2 (&#8710; &#8710; &#8710;|&#952; &#952; &#952; 2 ) = 1 2 &#8710; &#8710; &#8710; &#8224; &#8226; J &#8226; &#8710; &#8710; &#8710; + h &#8224; &#8226; &#8710; &#8710; &#8710;.<ns0:label>(1)</ns0:label></ns0:formula><ns0:p>The model depends on the parameters &#952; &#952; &#952; 2 = {J, h}, or the 2n &#215; 2n matrix of effective interactions J and the 2n vector of effective fields, h. Due to the symmetry of matrix J, the number of independent parameters in the 2-MaxEnt model is D + D(D + 1)/2, where D = 2n is the dimension of the vectors of landmark coordinates &#8710; &#8710; &#8710;. The value of these parameters is such that the equations</ns0:p><ns0:formula xml:id='formula_4'>&#8710; &#8710; &#8710; = &#8710; &#8710; &#8710; L and &#8710; &#181; &#8710; &#957; L = C &#181;&#957;</ns0:formula><ns0:p>are satisfied. This is equivalent to require that &#952; &#952; &#952; 2 are those that maximise the likelihood of the joint L over the database S (the Maximum Likelihood condition). The solution of such an inverse problem is (see</ns0:p><ns0:formula xml:id='formula_5'>SI): J = C &#8722;1 , h = J &#8226; &#8710; &#8710; &#8710; , and Z = (2&#960;) n exp(h &#8224; &#8226; J &#8722;1 &#8226; h/2)(det J) &#8722;1/2</ns0:formula><ns0:p>, where the &#8722;1 power in equation J = C &#8722;1 denotes the pseudo-inverse operation, or the inverse matrix disregarding the null eigenvalues induced by the database constraints (see SI). The 2-MaxEnt model is equivalent in the present case, in which the coordinates &#8710; &#181; are real numbers, to a Principal Component Analysis and L is in this case a multi-variate Normal distribution.</ns0:p><ns0:p>We will define as well the 3-MaxEnt model. In this case, the sufficient statistics is given by averages &#8710; &#181; , pairwise correlations C &#181;&#957; , and correlations among 3-landmark coordinates, C</ns0:p><ns0:p>(3)</ns0:p><ns0:formula xml:id='formula_6'>&#181;&#957;&#954; = &#8710; &#181; &#8710; &#957; &#8710; &#954; . The</ns0:formula></ns0:div> <ns0:div><ns0:head>5/14</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed 3-MaxEnt model probability distribution function takes the form of a Maxwell-Boltzmann distribution multiplied by a regularisation term ensuring that it is normalisable:</ns0:p><ns0:formula xml:id='formula_7'>L (&#8226;|h, J, Q) = 1 Z 3 e &#8722;[H 2 (&#8226;|&#952; &#952; &#952; 2 )+H 3 (&#8226;|Q)] H(&#8226;|B) (2)</ns0:formula><ns0:p>where H(&#8226;|B) is a multivariate Heaviside function, equal to one for vectors &#8710; &#8710; &#8710; lying in the hypercube &#8722;B &#8804; &#8710; &#181; &#8804; B for all &#181; and zero otherwise; Z 3 is the normalising factor, and the Hamiltonian is</ns0:p><ns0:formula xml:id='formula_8'>H = H 2 + H 3 ,</ns0:formula><ns0:p>where H 2 given by equation ( <ns0:ref type='formula' target='#formula_3'>1</ns0:ref>) and H 3 by:</ns0:p><ns0:formula xml:id='formula_9'>H 3 (&#8710; &#8710; &#8710;|Q) = 1 6 &#8721; &#181;&#957;&#954; &#8710; &#181; &#8710; &#957; &#8710; &#954; Q &#181;&#957;&#954; (3)</ns0:formula><ns0:p>Besides h and J, the non-linear MaxEnt model depends on a further tensor of three-wise interaction constants among triplets of landmark coordinates. Consequently, the number of independent parameters</ns0:p><ns0:formula xml:id='formula_10'>is [D] + [D(D + 1)/2] + [(D 3 &#8722; D 2 )/6 + D] = D 3 /6 + D 2 /3 + 5D/2.</ns0:formula><ns0:p>The solution of the inverse problem for the non-linear MaxEnt model does not take a closed analytic form. The maximum likelihood value of the parameters (h, J, Q) is numerically estimated by means of a deterministic gradient ascent algorithm (see <ns0:ref type='bibr' target='#b30'>Monechi et al. (2020)</ns0:ref>). A detailed explanation of the learning protocol may be found in the SI (see Learning in the non-linear MaxEnt model). Before inferring the data with the non-linear models (3-MaxEnt and GRBM) we have eliminated a subset of 6 redundant coordinates from the original 2n coordinates. The data has been standardised in order to favor the likelihood maximisation process. The value of B has been chosen to be B = 6, so that the probability distribution function is nonzero only in an hypercube whose side is six times the standard deviation of each standardised variable.</ns0:p></ns0:div> <ns0:div><ns0:head>2.4</ns0:head><ns0:p>The Restricted Boltzmann Machine model for unsupervised inference.</ns0:p><ns0:p>We have learned the data with the (Gaussian-Binary) Restricted Boltzmann Machine (GRBM) model of unsupervised inference <ns0:ref type='bibr' target='#b51'>(Wang et al. (2012</ns0:ref><ns0:ref type='bibr' target='#b52'>(Wang et al. ( , 2014))</ns0:ref>). It is a 2-layer unsupervised ANN, a variant, processing input real vectors, of the binary-binary RBM model. The model induces a probability distribution L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; ) = &#8721; h p(&#8710; &#8710; &#8710;, h|&#952; &#952; &#952; ) which is obtained by the marginalisation, over a set of N h binary hidden variables (or hidden neurons), h j &#8712; {0, 1}, j = 1, . . . , N h , of a joint probability distribution p:</ns0:p><ns0:formula xml:id='formula_11'>L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; ) = &#8721; h p(&#8710; &#8710; &#8710;, h|&#952; &#952; &#952; ), p(v, h|&#952; &#952; &#952; ) = 1 Z &#952; &#952; &#952; e &#8722;E(v,h|&#952; &#952; &#952; )<ns0:label>(4)</ns0:label></ns0:formula><ns0:p>The interaction among visible and hidden variables, and the dependence of p(&#8710; &#8710; &#8710;, h|&#952; &#952; &#952; ) on all its arguments is described by an energy function E that couples hidden to visible neurons. E is defined in terms of a set of parameters &#952; &#952; &#952; consisting, among others, on the D &#215; N h matrix of synaptic weights among visible (input)</ns0:p><ns0:p>and hidden variables. Although E presents only a linear coupling among v and h, the marginalisation over binary hidden neurons actually induce nonlinear effective couplings at all orders among the visible variables v (or &#8710; &#8710; &#8710;), couplings that may be accessed from the network parameters &#952; &#952; &#952; (MacKay (2003);</ns0:p><ns0:p>Cossu et al. ( <ns0:ref type='formula'>2019</ns0:ref>)).</ns0:p><ns0:p>We have employed the open-source software <ns0:ref type='bibr' target='#b29'>(Melchior (2017)</ns0:ref>) for the efficient learning of GRBM.</ns0:p><ns0:p>The learning protocol and parameters are described in detail, along with an introduction to the GRBM model, in the SI, see: Learning the database with the Gaussian Restricted Boltzmann Machine.</ns0:p></ns0:div> <ns0:div><ns0:head n='3'>RESULTS</ns0:head><ns0:p>We will now present an assessment of the description of the database according to the inference models described in the precedent section. In sec. 3.1 we will argue that the 2-MaxEnt model is a faithful representation of the dataset, and that only the nonlinear models predict the subject's gender when applied to such supervised inference task. Finally, in subsection 3.2, we will argue that the matrix of effective interactions J provides interpretable information, beyond the raw information present in the raw experimental measure C.</ns0:p></ns0:div> <ns0:div><ns0:head>6/14</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed i of the i-th landmark along an axes which subtends an angle &#966; &#8712; (&#8722;&#960;, &#960;) with the horizontal axis. These histograms are presented for all the landmarks also in fig. <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>, under the form of polar histograms. h (i) t (&#966; ) is the theoretical prediction of the same quantity, obtained by sampling data from the inferred L (&#8226;|&#952; &#952; &#952; ). The i-th landmark coordinates &#8710; i tend to fluctuate in the database with respect their average position &#8710; i = 0. As a nonlinear observable O we will consider the angle that the i-th landmark fluctuation &#8710; i forms with the x-axis. This quantity will be referred to as &#966;</ns0:p></ns0:div> <ns0:div><ns0:head n='3.1'>Quality of the MaxEnt models as generative models</ns0:head><ns0:formula xml:id='formula_12'>(s) i = arctan(&#8710; (s) i,y /&#8710; (s) i,x</ns0:formula><ns0:p>). In figs. 1,2, we report the empirical histogram of angles, h(&#966; i ) for some landmarks i. Remarkably, some landmarks' angle distribution exhibit local maxima, probably reflecting their tendency to follow the direction of some inter-landmark segments (as it is apparent for the 3-rd and 6-th landmark's in figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>). 5 We have compared the empirical histograms with the theoretical &#966; i distributions according to the model. These have been obtained as the angle histograms of a set of S vectors &#8710; &#8710; &#8710; sampled from the inferred distribution L (&#8226;|&#952; &#952; &#952; ) (see fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). The 2-MaxEnt model satisfactorily reproduces most of the landmark angle distributions. The empirical angle distribution, in other words, is reasonably well reproduced by the</ns0:p><ns0:formula xml:id='formula_13'>theoretical distribution h t (&#981;) = d&#8710; &#8710; &#8710; L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; )&#948; (&#966; (&#8710; &#8710; &#8710;) &#8722; &#981;).</ns0:formula><ns0:p>It is important to remark that the model-data agreement on h(&#966; i ) is observed also for large values of |&#966; i | &#8712; (0, &#960;) (see fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>), and not only for small values of |&#966; i |, for which it approximately becomes |&#8710; i,y /&#8710; i,x | (whose average is related to the correlation C &#945;&#946; , see SI).</ns0:p><ns0:p>We conclude that, very remarkably, a highly non-linear observable as &#966; is well described by the 2-MaxEnt model, albeit it has been inferred from linear (pairwise) correlations only. In this sense, the 2-MaxEnt model is a faithful and economic description of the dataset. This picture is confirmed by the results of the following section which suggest, however, that a description of the gender differences in the dataset require taking into account effective interactions of order p &gt; 2.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.1.2'>Performance of the MaxEnt model in a classification task</ns0:head><ns0:p>We now further evaluate the quality of the 2-and 3-MaxEnt models by assessing their efficiency to classify a test database of vectors in two disjoint subsets S = S A &#8746; S B corresponding to the gender of the subject that sculpted the facial vector in (Ib&#225;&#241;ez-Berganza et al. ( <ns0:ref type='formula'>2019</ns0:ref>)). We compare such efficiency with that of the GRBM model of ANN (see <ns0:ref type='bibr' target='#b51'>Wang et al. (2012</ns0:ref><ns0:ref type='bibr' target='#b52'>Wang et al. ( , 2014))</ns0:ref>, sec. 2 and the SI). This comparison allows to assess the relative relevance of products of p-facial coordinates &#8710; &#945; in the classification task: averages (p = 1), pairwise correlations (p = 2), and non-linear correlations of higher, p &gt; 2 order (modelled by the 3-MaxEnt and GRBM models only). </ns0:p></ns0:div> <ns0:div><ns0:head>8/14</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed non-linear effective interactions at least of fourth order are necessary for a complete description of the database. For completeness, we have included a comparison with the Random Forest (RF) algorithm <ns0:ref type='bibr' target='#b33'>(Murphy (2012)</ns0:ref>). As shown in fig. <ns0:ref type='figure' target='#fig_5'>3</ns0:ref>, RF achieves the highest classification accuracy (auROC= 0.995, see SI). We notice that this does not imply that the unsupervised models are less accurate: the RF algorithm is advantaged, being a specific model trained to classify at best the A, B partitions, not to provide a generative model of the A and B partitions separately.</ns0:p><ns0:p>We report the maximal accuracy scores for all the algorithms: RF (0.971); GRBM (0.952); 3-MaxEnt (0.865); 2-MaxEnt (0.764); 1-MaxEnt (0.680). The 2-MaxEnt model efficiency is, as expected, compatible with that of a t-Student test regarding the differences in the principal component values of A and B vectors, see fig. <ns0:ref type='figure' target='#fig_5'>3</ns0:ref>. See the auROC scores of all the algorithms in the SI.</ns0:p><ns0:p>We conclude that, on the one hand, the subjects' gender strikingly determines her/his preferred set of faces, to such an extent that it may be predicted from the sculpted facial modification with an impressively high accuracy score <ns0:ref type='bibr' target='#b33'>(Murphy (2012)</ns0:ref>): a 97.1% of correct classifications. On the other hand, the relative efficiency of various models highlights the necessity of non-linear interactions for a description of the differences among male and female facial preference criterion in this database. Arguably, such nonlinear functions play also a role in the cognitive process of facial perception. The criterion with which the subjects evaluate and discriminate facial images seems to involve not only proportions r &#945; /r &#946; (related to the pairwise correlations C &#945;&#946; , see SI), but also triplets and quadruplets of facial coordinates influencing each other (yet, see the SI for an alternative explanation) 7 .</ns0:p><ns0:p>It is believed that the integration of different kinds of facial variables (geometric, feature-based versus texture, holistic, see <ns0:ref type='bibr' target='#b48'>(Trigueros et al. (2018)</ns0:ref>; <ns0:ref type='bibr' target='#b49'>Valentine et al. (2016)</ns0:ref>)) improve the attractiveness inference results, suggesting that both kinds mutually influence each other in attractiveness <ns0:ref type='bibr' target='#b13'>(Eisenthal et al. (2006)</ns0:ref>; <ns0:ref type='bibr' target='#b54'>Xu et al. (2017)</ns0:ref>; <ns0:ref type='bibr' target='#b21'>Laurentini and Bottino (2014)</ns0:ref>; Ib&#225;&#241;ez-Berganza et al. ( <ns0:ref type='formula'>2019</ns0:ref>)). The present results indicate that, even restricting to geometric coordinates (at fixed texture degrees of freedom), it is necessary a holistic approach, in the sense that it considers the mutual influence of many geometric coordinates.</ns0:p><ns0:p>Actually, our results indicate that pairwise influence of geometric coordinates are enough for a fair and economic description of the database (the 2-MaxEnt model predicts nonlinear observables, beyond the empirical information with which it has been fed). However, the differences among the facial vectors sculpted by males and females are not only encoded in pairwise correlations among geometric coordinates.</ns0:p><ns0:p>Facial vectors reveal the gender of the sculpting subject with almost certainty only when non-linear models are used.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>Analysis of the matrix of effective interactions</ns0:head><ns0:p>We now show that the generative models may provide directly interpretable information. This is an advantage of the MaxEnt method, whose parameters, the effective interaction constants, may exhibit an interpretable significance. We prove, in particular, that at least the matrix of effective interactions J admits an interpretation in terms of 'resistance' (elastic constant) of inter-landmark segment distances and angles to differ with respect to their average or preferred value.</ns0:p><ns0:p>The 2-MaxEnt model admits an immediate interpretation. The associated probability density L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; ) = exp (&#8722;H 2 (&#8710; &#8710; &#8710;|&#952; &#952; &#952; )) /Z formally coincides with a Maxwell-Boltzmann probability distribution of a set of n interacting particles in the plane (with positions &#8710; i , i = 1, . . . , n), subject to the influence of a thermal bath at constant temperature. Each couple i, j of such fictitious set of particles interacts through an harmonic coupling that corresponds to a set of three effective, virtual springs with non-isotropic elastic constants, J (xx) i j , J (yy) i j , J (xy) i j corresponding (see equation 1) to horizontal, vertical and oblique displacements,</ns0:p><ns0:formula xml:id='formula_14'>&#8710; i,x &#8722; &#8710; j,x , &#8710; i,y &#8722; &#8710; j,y</ns0:formula><ns0:p>, and &#8710; i,x &#8722; &#8710; j,y , respectively.</ns0:p><ns0:p>The inferred effective interactions are more easily interpretable if one considers, rather than their xx, yy and xy components, the longitudinal and torsion effective interactions, J i j and J &#8869; i j , respectively. The longitudinal coupling |J i j | may be understood (see the SI for a precise definition) as the elastic constant corresponding to the virtual spring that anchors the inter-i j landmark distance to its average value, r i j (where r i j = r j &#8722; r i ). In its turn, the torsion interaction |J &#8869; i j | is the elastic constant related to fluctuations of 7 As we explain in the SI, the non-Gaussian correlations of order 3 present in the dataset are, at least partially, not of cognitive origin, but due to an artifact of the numerical algorithm allowing subjects to sculpt their preferred facial vectors. However, we believe that the non-linear effective interactions that we infer do reflect the existence of non-linear operations playing a role in the cognitive process of facial evaluation. This is suggested by the fact that the introduction of non-linear effective interactions drastically improves the gender classification.</ns0:p></ns0:div> <ns0:div><ns0:head>9/14</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed r i j along the direction normal to r i j or, equivalently, to fluctuations of the i j-segment angle, with respect to its average value that we will call &#945; i j = arctan( r i j,y / r i j,x ).</ns0:p><ns0:p>In fig. <ns0:ref type='figure' target='#fig_8'>4-A</ns0:ref>,B we show the quantities |J i j | and |J &#8869; i j | for those couples i, j presenting a statistically significant value (for which the t&#8722;value t i j = |J i j |/&#963; J i j &gt; 1 (a description of the calculation protocol of the bootstrap error &#963; i j may be found in the SI). The width of the colored arrow over the i, j segment is proportional to |J i j | (blue arrows in fig. <ns0:ref type='figure' target='#fig_8'>4-A</ns0:ref>) and |J &#8869; i j | (red arrows in fig. <ns0:ref type='figure' target='#fig_8'>4-B</ns0:ref>). We notice that there exist inter-landmark segments for which |J i j | is significant while |J &#8869; i j | is not (as the 0, 4 or the 5, 6 segments)</ns0:p><ns0:p>and vice-versa (as the 6, 7 and 2, 5). This suggests that |J i j |, |J &#8869; i j | actually capture the cognitive relative relevance of distance fluctuations around r i j , and of angle fluctuations around &#945; i j .</ns0:p><ns0:p>We remark that the prominent importance of the inter-segment angles i j highlighted in fig. <ns0:ref type='figure' target='#fig_8'>4</ns0:ref>-B is fully compatible with the analysis presented in (Ib&#225;&#241;ez-Berganza et al. ( <ns0:ref type='formula'>2019</ns0:ref>)) at the level of the oblique correlation matrix C (xy) , and it goes beyond, as far as it quantitatively assess their relative relevance. As we will see in the next subsection, such information cannot be retrieved from the experimental matrix C only.</ns0:p><ns0:p>In the SI we explain in more detail the analogy with the system of particles. We also analyse the dependence of the torsion and longitudinal effective interactions, |J i j | and |J &#8869; i j |, with the average distance and angle of the i j inter-landmark segment, showing that there is a moderate decreasing trend of |J i j | with r i j . This fact admits an interpretation: large inter-landmark distances are less 'locked' to their preferred value with respect to shorter distances. Very interestingly, such trend is less evident for |J &#8869; i j |: the relative relevance of the inter-landmark angles according to J is not lower for farther away landmarks. This confirms the holistic nature of facial perception. The mutual influence among landmarks is not among nearby landmarks only, but over the scale of the entire face.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2.1'>Extra information retrieved with effective interactions</ns0:head><ns0:p>A relevant question is to what extent the inferred effective interactions J provide interpretable information, inaccessible from the raw experimental correlations C. In the general case, couples of variables may be statistically correlated through spurious correlations, even in the absence of a causal relation among them The differences among C and J matrices are apparent from fig. <ns0:ref type='figure' target='#fig_8'>4-C</ns0:ref>, where the arrows represent the absolute value of the raw experimental matrix elements C i j . Remarkably, all but two of the matrix elements result statistically significant (t-value &gt; 1): matrix C can be hardly used to assess the relative relevance of various inter-landmark segments. The effective interaction matrix J disambiguates the correlations propagated by the constraints, attributing them to the effect of a reduced set of elastic constants, in the particle analogy. Such attribution is not unambiguous, but the result of the inference procedure.</ns0:p><ns0:p>In other words, the inferred matrix J provides interpretable results, beyond the less-interpretable empirical information present in matrix C. Indeed, matrix C is dense, in the sense that almost all its elements are statistically significant (see fig. <ns0:ref type='figure' target='#fig_8'>4-C</ns0:ref>). Matrix C is, however, exactly explained by the 2-MaxEnt model, defined by the sparser matrix J of effective interactions, such that only some matrix elements are statistically significant (see figs. <ns0:ref type='figure' target='#fig_8'>4-A,B</ns0:ref>).</ns0:p><ns0:p>An in-depth comparison among C and J is presented in the SI, where we consider also the alternative method of avoiding the constraints, consisting in inferring from a non-redundant set of coordinates. We conclude that, in the general case, and for the sake of the interpretation of the effective interactions, it may be convenient to infer from a database of redundant variables, eliminating a posteriori the influence of the null modes associated to the constraints (and, perhaps, of low-variant modes associated to quasi-constraints or to non-linear constraints).</ns0:p></ns0:div> <ns0:div><ns0:head>10/14</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed The width of the arrow joining the i-th and j-th landmarks is proportional to |A i j |, where A is the corresponding matrix. Matrices J and J &#8869; represent, respectively, the longitudinal and torsion elastic constants of the correspondent inter-landmark segments. They indicate, respectively, the segment's distance and angle 'resistance' to differ in the database with respect to their average (preferred) values, reported in the image. Only significant matrix elements have been plotted: only those exhibiting a t-value larger than one:</ns0:p><ns0:formula xml:id='formula_15'>t i j = |A i j |/&#963; A i j &gt; 1. Matrix C (right) is less interpretable than J (left).</ns0:formula></ns0:div> <ns0:div><ns0:head n='4'>CONCLUSIONS</ns0:head><ns0:p>We have performed an unsupervised inference study of the database of preferred facial modifications presented in reference <ns0:ref type='bibr' target='#b19'>(Ib&#225;&#241;ez-Berganza et al. (2019)</ns0:ref>). Much work has been devoted to the regression of the average rating in face-space, specially in the machine learning community. Such supervised inference approach indirectly allows for an assessment of the relative impact of various facial traits on perceived attractiveness. This point, however, remains poorly understood <ns0:ref type='bibr' target='#b21'>(Laurentini and Bottino (2014)</ns0:ref>). Furthermore, some authors have argued that the subjective nature of facial attractiveness has been overlooked and underestimated, and that the subject-averaged rating presents several limitations as an experimental method <ns0:ref type='bibr' target='#b18'>(H&#246;nekopp (2006)</ns0:ref>; <ns0:ref type='bibr' target='#b21'>Laurentini and Bottino (2014)</ns0:ref>; <ns0:ref type='bibr' target='#b37'>Oh et al. (2019b)</ns0:ref>). As a novel experimental tool for the investigation of the nature of facial attractiveness and its subjectivity, we here propose an alternative inference scheme in which the variability to be inferred is the inter-subject variability of preferred modifications in a subspace of the face-space (in which only the geometric positions of some landmarks are allowed to vary), rather than the average rating assigned to different natural faces.</ns0:p><ns0:p>The present work is probably the first unsupervised inference approach in facial preference research.</ns0:p><ns0:p>Our models induce a probabilistic representations of a set of facial modifications (corresponding to the whole set of subjects or to the set of male or female subjects only, in secs. 3.1.1,3.1.2 respectively, or to the single subject). Such models avoid the use of ratings; account for nonlinear influence of p&#8722;plets of facial features, hence beyond a principal component analysis; their parameters are in principle interpretable since they involve 'physical' facial coordinates only.</ns0:p><ns0:p>Our approach allows to clarify several aspects regarding facial preference. First, that the cognitive mechanisms related to facial discrimination in the brain mainly involves proportions, or pairwise influence of couples of landmarks, more than the positions of single landmarks. Indeed, the 2-MaxEnt model, equivalent to a description in terms of principal components, is enough to describe also non-linear features of the database (see sec. Second, and rather remarkably, the introduction of non-linear effective interactions, beyond the influence of proportions, allows for an astonishingly high classification efficiency of the facial vectors according the subject's gender. Indeed, the random forest algorithm, a highly nonlinear supervised algorithm for classification, provides a 97% of correct classifications. The most non-linear of the probabilistic models, the GRBM, provides a slightly lower accuracy: 95%. This implies that the subject's gender strikingly determines her/his facial preference criteria and that the sculpted facial modifications, as a sample of the subjects idiosyncratic criterion, are accurate enough to allow to predict such impact.</ns0:p><ns0:p>The impact of the gender is consistent with the sexual selection hypothesis <ns0:ref type='bibr' target='#b24'>(Little et al. (2011)</ns0:ref>; <ns0:ref type='bibr' target='#b39'>Rhodes (2006)</ns0:ref>; <ns0:ref type='bibr' target='#b45'>Thornhill and Gangestad (1999)</ns0:ref>). However, since the sculpted vectors partially capture the subjects' idiosyncrasy, such a result is also consistent with the multiple motive hypothesis, assuming that the gender strongly influences the subjects' idiosyncratic preferences for personality traits (in the language of <ns0:ref type='bibr' target='#b37'>Oh et al. (2019b)</ns0:ref>).</ns0:p><ns0:p>In summary, we have presented probabilistic generative models of the database of preferred facial variations, describing the inter-subject fluctuations around the average modification (given a reference background portrait). The simplest of these models, characterised by pairwise correlations among facial distances, already provides a faithful description of the database. Afterwords, we demonstrate that such fluctuations encode, and may accurately reveal when introducing non-linearity, the subjects' gender. According to the multiple motive hypothesis, many other subject attributes and distinguishing psychological traits may influence, beyond the gender, the preferences in the face-space. The present results suggest that such attributes could be retrieved from the subject sculpted facial vectors.</ns0:p><ns0:p>Finally, we have demonstrated that the data elicited with the method in (Ib&#225;&#241;ez-Berganza et al. ( <ns0:ref type='formula'>2019</ns0:ref>)) represents a novel case of study for the application of statistical learning methods, in particular the assessment of the relevant order of interaction by comparison with an ANN model, and the comparison among various strategies of inference in the presence of constraints.</ns0:p><ns0:p>The introduction of texture degrees of freedom in the sculpting process is a possible development of the empirical technique of <ns0:ref type='bibr' target='#b19'>Ib&#225;&#241;ez-Berganza et al. (2019)</ns0:ref>, that would allow to quantify the extent to which texture and geometric facial features (and which ones) influence each other in attractiveness perception (a debated question, see <ns0:ref type='bibr' target='#b21'>Laurentini and Bottino (2014)</ns0:ref>). Further possible extensions are: the generalisation to different datasets and facial codification methods allowing, for example, landmark asymmetry (see also Generality of the unsupervised inference models in the SI); the classification of different subject's features from her/his set of sculpted faces.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>2017)), otherwise extensively used in physics, systems neuroscience and systems biology (Lezon et al. (2006); Schneidman et al. (2006); Shlens et al. (2006); Bialek and Ranganathan (2007); Tang et al. (2008); Weigt et al. (2009); Roudi et al. (2009); Tkacik et al. (2009); Stephens and Bialek (2010); Mora et al. (2010); Morcos et al. (2011); Bialek et al. (2012); Martino and Martino (2018)).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Facial landmarks i = 0, . . . , 7 whose 2D coordinates r i constitute the face space (signaled with black circles). Their position in the figure correspond to the average position, r i . The background image corresponds to the texture degrees of freedom of the reference portrait. The blue lines are polar histograms h(&#966; ) (the radius is proportional to h(&#966; )) corresponding to the experimental distribution of angle landmark fluctuations around their average position.</ns0:figDesc><ns0:graphic coords='5,269.53,110.89,166.72,289.22' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Comparison among empirical (h (i) (&#966; )) and theoretical (h</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>)) histograms of angle landmark fluctuations, for several landmarks, i = 1, 5, 6, 7, see fig.1(from left to right, from top to bottom). The empirical histograms h (i) (&#966; ) represent the probability density of empirical displacements &#8710; (s)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>of single landmark-angle fluctuations The quality of the 2-MaxEnt generative model as a faithful description of the database may be evaluated by the extent to what the model L reproduces observables O that it is not required to reproduce by construction. In other words, observables that cannot be written in terms of couples and triplets of coordinates &#8710; &#945; . The model is faithful in the extent to what O &#8771; O L .</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. True Positive Rate (TPR) versus False Positive Rate (FPR) corresponding to the Receiver Operating Characteristic (ROC) curves associated to the gender classification. Different ROC curves correspond to different algorithms. PC's refers to a t-Student test of the difference in the principal components of a vector with respect to their average value in the A, B sets.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>The dataset is divided in two disjoint classes S A , S B . Afterwards, both S A,B are divided in trainingand test-sets (20% and 80% of the elements of S A,B , respectively), and inferred the A and B training sets separately, with the MaxEnt and GRBM models. This results in six ({2, 3, G} &#215; {A, B}) sets of parameters&#952; &#952; &#952; 2,3,G A,B, where the super-index refers to the model. Given a vector &#8710; &#8710; &#8710; belonging to the A or B test set, thescore s(&#8710; &#8710; &#8710;) = ln L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; A ) &#8722; ln L (&#8710; &#8710; &#8710;|&#952; &#952; &#952; B) is taken as the estimation of the model prediction for &#8710; &#8712; S A .The resulting Receiver Operating Characteristic (ROC) curves<ns0:ref type='bibr' target='#b33'>(Murphy (2012)</ns0:ref>) are shown in fig.3for the various models considered.6 Considering only the averages &#8710; &#8710; &#8710; as sufficient statistics (or, equivalently, inferring only the fields h and setting J i j = &#963; &#8722;2 i &#948; i j in equation 1) results in a poor, near-casual classification (specially in the most interesting region of the ROC curve, for small FPR and large TPR), see figure3. The 2-MaxEnt model allows, indeed, for a more efficient classification. Rather remarkably, with the 3-MaxEnt and GRBM models the classification accuracy gradually increases. We interpret this as an indication of the fact that 6 These consist in a scatter plot with the fraction of true positive classifications (TPR) in the S A test-set versus the fraction of false positive classifications (FPR) in the S B test-set, where each point corresponds to a different soil &#948; over the estimator s(&#8710; &#8710; &#8710;) &#8822; &#948; that we use to assign whether the model predicts that &#8710; &#8710; &#8710; belongs to A or B. The curve is invariant under reparametrizations of s &#8594; f (s) defined by any monotone function f .</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>see the Introduction to the Maximum Entropy principle in the SI). In the present case, the main source of spurious correlations is the presence of the constraints among various landmark coordinates. The MaxEnt inference eventually subtracts (through the pseudo-inverse operation) the influence of the constraints from matrix J, which describes the essential effective mutual influence among pairs of coordinates of prominent relative importance (see Two ways of inferring with constraints in the database of facial modifications in the SI).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. Modulus of the matrices J (left), J &#8869; (center), C (right). The width of the arrow joining the i-th and j-th landmarks is proportional to |A i j |, where A is the corresponding matrix. Matrices J and J &#8869; represent, respectively, the longitudinal and torsion elastic constants of the correspondent inter-landmark segments. They indicate, respectively, the segment's distance and angle 'resistance' to differ in the database with respect to their average (preferred) values, reported in the image. Only significant matrix elements have been plotted: only those exhibiting a t-value larger than one: t i j = |A i j |/&#963; A i j &gt; 1. Matrix C (right) is less interpretable than J (left).</ns0:figDesc><ns0:graphic coords='12,144.71,63.80,133.99,231.70' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>3.1.1). Moreover, the results suggest as well that non-linear operators of the 11/14 PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020) Manuscript to be reviewed geometrical facial coordinates may play a non-negligible role in the cognitive process (see sec. 3.1.2). Further research is needed to clarify this point (see also Cognitive origin of non-linear correlations in the SI). 8</ns0:figDesc></ns0:figure> <ns0:note place='foot' n='2'>This inference scheme differs from the common one found in the facial attractiveness literature, specially in the machine learning papers. In these papers the main goal is the automatic rating of facial images, considered as a supervised inference problem<ns0:ref type='bibr' target='#b21'>(Laurentini and Bottino (2014)</ns0:ref>). The facial image is parametrised in a face-space vector f, the inference goal consists in the regression R(f) that reproduces at best the subject-averaged ratings R s s of a database {f s , R s }. In the case of deep, hierarchical networks, which automatically perform feature selection, the raw image is used as an input to the learning algorithm instead of a face-space parametrisation f. The resulting relevant features are, however, not immediately accessible.3/14PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:note> <ns0:note place='foot' n='5'>Interestingly, such local maxima seem to be oriented along inter-landmark segments eventually involving landmarks which are not described in the facial vectors &#8710;: the landmarks &#8467; 0 and &#8467; 18 , see the SI.7/14PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot' n='8'>The recent de-codification of the neural code for facial recognition in the primate brain<ns0:ref type='bibr' target='#b9'>(Chang and Tsao (2017)</ns0:ref>) has revealed that recognition is based on linear operations (or projections in the geometric and texture principal axes) in the face-space.12/14PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)</ns0:note> <ns0:note place='foot' n='14'>/14 PeerJ reviewing PDF | (2020:03:47277:1:1:NEW 22 Aug 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Dear Prof. Edward Vessel, dear Editors of PeerJ, On behalf of my coauthors, I thank you very much for yours and the referees’ comments. Your criticisms have helped and motivated us to perform a profound rewriting of the manuscript, mainly of sections 1 and 4. In its present version, the motivation and scientific question, as well as the results and their interpretation are explained in a more straightforward fashion. We believe that the manuscript is now more self-contained, more understandable for non-technical readers, more fluent and clear to the reader. We have framed the scientific question in a more complete description of the state of the art, adding twelve references. The figures and the results are unchained. Our modifications have been guided by the referees’ criticisms. We have implemented most of your suggestions, adding clarifying paragraphs to the main text or to the figure captions when necessary. The new manuscript comes with further improvements. For example, we have carefully described the experiment presented in [Ibáñez-Berganza et al, 2019] (task, stimuli and subjects). We have added a non-technical section with a gentle description of unsupervised, Maximum Entropy and GRBM inference. Finally, the manuscript has been carefully copyedited and the spelling errors corrected (it had, indeed, been revised by a native person in its first form, the errors that you noticed are last-minute spelling mistakes). Please, see the detailed differences among the old and new documents in the trackedchanges manuscript, and our answers to your questions below, in which we also refer to the changes that we have performed. We hope to have provided exhaustive and convincing explanations, and that in its present form our manuscript can be published in PeerJ. Best regards, Miguel Ibáñez-Berganza, on behalf of Ambra Amico, Gian Luca Lancia, Federico Maggiore, Bernardo Monechi and Vittorio Loreto. Università degli Studi di Roma “La Sapienza” CF 80209930587 PI 02133771002 Dipartimento di Fisica Edificio Marconi - P.le Aldo Moro n. 2, 00185 Roma www.phys.uniroma1.it/DipWeb/home.html Pag !2 Answer to the Editor’s comments: Figure 3: please include full labels for TPR or FPR in the figure legend. Done. The sentence is now: <<True Positive Rate (TPR) versus False Positive Rate (FPR) corresponding to the Receiver Operating Characteristic (ROC) curves associated to the gender classification.>> ln 225-227: I think this calls for reference to the large literature on “holistic” facial representations. We agree with the Editor that the mutual influence of p-plets of geometric coordinates in the perceived attractiveness implies that this phenomenon would be better studied in terms of holistic facial representations, rather than by regression methods that accounts for the impact of each facial coordinate separately (as, indeed, some articles do). Nevertheless, by holistic in this sentence we mean that each holistic coordinate is a general (perhaps linear) combination of all the geometric quantities (the landmark positions). This is precisely what we do in this article in the 2-MaxEnt model, the simplest of the inferred models. The non-linear models perform an even “more holistic” description in terms of nonlinear combination of facial variables which are, however, only landmark (i.e., geometric, or shape) coordinates. Indeed, the term holistic normally refers to facial representation methods (as the eigenfaces) whose coordinates involves the whole facial image, comprising also the texture degrees of freedom, that in our work are not free to vary since the background image is common in all the images and deformed with image deformation algorithms defined by the geometric ccordinates. In terms of holistic variables, the geometric quantities are normally coupled to the texture degrees of freedom. Hence, the term holistic should be used with care to avoid confusion at this point. For the sake of clarity, we have summarised this digressions in two paragraphs in the Introduction. These are: >> It is believed that the integration of different kinds of facial variables (geometric, featurebased versus texture, holistic, see [Trigueros et al 2018]) improves the attractiveness inference results [Eisenthal et al 2006, Xu, J. et al 2017, Laurentini & Bottino 2014, Ibáñez-Berganza et al 2019], suggesting that both kinds mutually influence each other in attractiveness. The present results indicate that, even restricting to geometric coordinates (at fixed texture degrees of freedom), it is necessary a holistic approach, in the sense that it considers the mutual influence of many geometric coordinates. Pag !3 >> Actually, our results indicate that pairwise mutual influences of geometric coordinates are enough for a fair and economic description of the database (the 2-MaxEnt model predicts nonlinear observables, beyond the empirical information with which it has been fed). However, the differences among the facial vectors sculpted by males and females are not only encoded in pairwise correlations among geometric coordinates. Facial vectors reveal the gender of the sculpting subject with almost certainty only when non-linear models are used. We have consequently added the following reference: [Trigueros et al 2018] Trigueros, Daniel Sáez, Li Meng, and Margaret Hartnett. 'Face recognition: From traditional to deep learning methods.' arXiv:1811.00116 (2018). Fig. 4: 3rd panel is not very interpretable We thank the Editor for this question, that gives us the possibility to clarify this important point. We have deliberately presented the non-interpretable 3rd panel of fig. 4 to demonstrate that the information present in matrix C is less interpretable than that in matrix J (1st and 2nd panels of fig. 4). In other words, we wanted to illustrate the fact that the inference procedure provides interpretable results, beyond the less interpretable raw empirical information present in C. Still in other terms: the “dense” matrix C, in which almost all elements are statistically significant, may be exactly explained by a model (the 2-MaxEnt model) defined by a sparser matrix of interactions, J, in which only some matrix elements (the most relevant ones) are statistically significant. These are not deduced straightforwardly by the raw experimental C but have to be inferred (the inference depending on the model, say 2MaxEnt, and on the learning protocol, say, maximum likelihood). J subtracts from C the spurious correlations. In the SI we attribute such difference in sparseness to the presence of the artifact constraint among the coordinates, and we explain in detail the two ways in which the presence of a constraint may be handled in the inference procedure. This is mentioned in the article, in subsection 3.2.1 Extra information retrieved with effective interactions, where we say: <<Remarkably, all but two of the matrix elements result statistically significant (t-value > 1): matrix C∥ can be hardly used to assess the relative relevance of various inter-landmark segments. The effective interaction matrix J disambiguates the correlations propagated by the constraints, attributing them to the Pag !4 effect of a reduced set of elastic constants, in the particle analogy.>> We have further clarified this point in a new paragraph that reads: >> In other words, the inferred matrix J provides interpretable results, beyond the lessinterpretable raw empirical information present in matrix C. Indeed, matrix C is dense, in the sense that almost all its elements are statistically significant (see fig. 4-C). Matrix C is, however, exactly explained by the 2-MaxEnt model, defined by the sparser matrix J of effective interactions, such that only some matrix elements are statistically significant (see figs. 4-A,B). The caption of Fig. 4 has been also consequently changed: >> Figure 4. Modulus of the matrices J∥ (left), J⊥ (center), C∥ (right). The width of the arrow joining the i-th and j-th landmarks is proportional to |Aij|, where A is the corresponding matrix. Matrices J∥ and J⊥ represent, respectively, the longitudinal and torsion elastic constants of the correspondent inter-landmark segments. They indicate, respectively, the segment’s distance and angle “resistance” to differ in the database with respect to their average (preferred) values, reported in the image. Only significant matrix elements have been plotted: only those exhibiting a t -value larger than one: ti j = |Ai j |/σAi j > 1. Matrix C∥ (right) is, consequently, less interpretable than J∥ (left). Moreover, we have added a further paragraph an interpretation of the dependence of matrix J with the inter-landmark distance <r_ij>. As it is evident from our interpretation: >> In the SI we explain in more detail the analogy with the system of particles. We also analyse the dependence of the torsion and longitudinal effective interactions, |J∥ | and |J⊥|, with the average distance and angle of the i j inter-landmark segment, showing that there is a moderate decreasing trend of |J∥ | with ⟨ri j ⟩. This fact admits an interpretation: large inter-landmark distances are less “locked” to their preferred value with respect to shorter distances. Very interestingly, such trend is less evident for |J⊥|: the relative relevance of the inter-landmark angles according to J is not lower for farther away landmarks. This confirms the holistic nature of facial perception. The mutual influence among landmarks is not among nearby landmarks only, but over the scale of the entire face. matrix J actually provides meaningful cognitive information regarding the holistic nature of facial perception. Finally, we have added a new section 2.2 Unsupervised inference where we mention that the inference procedure depends on both the model and the learning protocol. For clarity, we also specify in the (new) section 2.3 that the 2-MaxEnt model is equivalent to Principal Component Analysis. Pag !5 ln 325-327: It is not clear to me that the manuscript benefits from mentioning the possible security or forensic applications of the results. I would consider cutting. We have followed the Editor’s suggestion, eliminating the incriminated paragraph in section 4. Pag !6 Answer to Referee #1 comments: Overall, this is an interesting approach. I appreciate the earlier authors’ development of a new method to extract human preference behavior in relation to faces. It’s a clever and fairly naturalistic approach. In the current work, the predictability of gender difference is an interesting and significant addition. However, I see issues with the interpretation of the present results, and also underlying issues and lacunae in the psychophysical procedure. We are glad that Referee #1 appreciates our previous work, considering it a clever approach to extract human preference behavior in relation to faces. Motivated by her/his criticisms, we have rewritten the interpretation of our results in section 4, and clarified the experimental procedure in various respects, that we now describe along with our answers. 1. The model introduces symmetry to otherwise asymmetrical faces by applying the same transform to both sides of the face. This is somewhat unavoidable but it has yet to be shown that, given freedom to manipulate both sides of the face, people don’t introduce small asymmetries, if only to make a face less “uncanny.” In any case, the present method does not help disentangle the influence of symmetry. In the experiments that we presented in 2019, the right landmark positions were, indeed, symmetrical to the left ones. Consequently, we agree with the Referee #1 that these experiments do not allow to assess to what extent the subjects would tend to slightly desymmetrise the face in geometric coordinates. This is, in my opinion, an interesting point for further investigations, along with other improvements of the experiment. In our opinion, the most fundamental of them is to allow the subjects to sculpt also texture degrees of freedom, not only geometrical. Perhaps the point raised by the referee could be the subject of a dedicated study, we would be glad if our experimental software could be used to investigate it. The 2019 experiments aimed to clarify two points that are, in our opinion, somehow more fundamental: 1) whether the subjects were consistent in their sculpted vectors, and consistently distinguishable from other subjects (i.e., whether attractiveness is subjective in this scheme), and 2) whether the texture influenced the single and average sculpted vectors (i.e., whether texture and geometry influence each other in attractiveness). In the spirit of solving progressively one question at once, the demand to address these two questions excluded the possibility to address other questions. Pag !7 Indeed, the genetic algorithm scheme used in 2019 is such that, for computational complexity reasons, adding more degrees of freedom to the face-space actually compromise the efficiency of the sculpting process (the number of binary choices to be perform by the subject before arriving to pseudo-convergence). As a final remark, let me say that faces in our experiment are actually asymmetric in the texture degrees of freedom, since the texture image corresponds to a real person. My guess is that, if subjects were allowed to introduce asymmetry in the landmark positions, they would not do it (beyond the sensibility limit). Although, as pointed out by Referee #1, too much texture symmetry may seem “uncanny”, any perceptible degree of geometric asymmetry (i.e. asymmetry in the fundamental Cartesian landmark positions) may be perceived as unattractive. In any case, that this discussion regards the experiments in [Ibáñez-Berganza et al 2019], and not the results of the present article, in which we do not perform any experiment but draw our conclusions from the 2019 data as they are. We have, however, added the referee’s idea in the list of future work: >> Further possible extensions are: the generalisation to different datasets and facial codification methods allowing, for example, landmark asymmetry (see also Generality of the unsupervised inference models in the SI); the classification of different subject's features from her/his set of sculpted faces; the analysis of medical imaging data characterised by the 3D position of landmark points. Nor is it clear that people really “like” the sculpted faces they make. I would have had users compare each user-sculpted face to a symmetrized version of the same (unaltered) face—individuals should prefer the face they sculpted (maybe with some control for familiarity). If this is not the case, the MaxEnt models for individuals aren’t very meaningful. The point raised by the referee is a natural question. There are actually many evidences that the subjects actually “like” the facial vectors that they sculpted. The most overwhelming of them is the result of the self-consistency experiment (E2) in [I-B et al 2019]: when repeating the experiment, the subjects tend to sculpt facial vectors which are more similar to the ones that they already sculpted than to other’s facial vectors (the average “self-consistency” distance is lower than than the average “inter-subject distance”, with a p-value lower than 10-10). This is a very strong evidence. A natural alternative is the one proposed by the referee: a test in which the subject compares his/her sculpted facial vector with those sculpted by Pag !8 other volunteers. Such a test, however, could be subject to several kinds of bias (a subject could be biased towards the face he/she has sculpted), of which the selfconsistency test is less affected (because it depends, indirectly, on many choices). The MaxEnt models for individuals are totally meaningful. We remark, in any case, that this discussion do not regard the results of the present paper since in the present work we do not present results for the single-individual MaxEnt models: for the reproduction of the histograms of landmark-angle fluctuations in section 3.1.1 we use a generative model inferred from the hole collection of subjects, while for the subject gender classification in section 3.1.2 we infer two separated generative models from the whole set of female and male subjects, respectively. We have stressed this point in section 4: >>Our models present a probabilistic representations of a set of facial modifications (corresponding to the whole set of subjects or to the set of male or female subjects only, in secs. 3.1.1,3.1.2 respectively, or to the single subject). For details regarding the differences among single and collective inferred models, you can consult section Inter- and intra-subject correlations and errors in the SI. 2. Also it is not clear that people can see the changes they make in the sculpted faces. We acknowledge the referee for this important observation. There are several evidences that the subjects actually notice the changes they make in the sculpted faces. The stronger evidence is perhaps given by the intra-population distance among the facial vectors sculpted by single subjects at equal “times” (generations in the genetic algorithm) (see fig. 2 of [Ibáñez-Berganza et al 2019]). The typical trend for humans is a faster decrease of the intra-population distance, followed by a slower decrease, or by a pseudo-plateau. In a null model consisting in random pairwise choices a very slow decreasing trend with constant slope is observed instead. The interpretation of these results is that, when starting from a random initial condition composed by very deformed, grotesque images, the subjects sculpt using a well determined criterion, fast towards the commonly preferred, realistic area in the face space (with size \vec\sigma, in the 2019 notation). Once the subjects have “left” the grotesque zone, the slope of the intra-population distance gradually decreases, indicating that they tend to be less determined. At even larger times, some subjects Pag !9 reach a proper plateau (of intra-population distance), indicating that the intra-population distance is lower than their sensitivity (typically, 4/1000 of the facial height): they cannot distinguish the facial vectors within a population. In summary, the decreasing not only of the intra-population distance, but also of its slope are an indication of the fact that the nearer the subject is to her/his preferred attractor, the larger the choice uncertainty. Subjects notice the differences in the faces they sculpt, until they do not want to change them any more. These facts are also confirmed by the statistics of response times (which become larger the nearest are the faces to the “final sculpture”) and by informal questions (not tracked) that we performed to several volunteers: they recognised to be more and more “proud” of the resulting face. a. Stimuli are B/W (compressed?) 300x400 pixels, shown at unreported viewing distance, and there seems to be no control for individuals’ optical errors (corrected to normal?). Maybe people selected preferred images in each pair based on visibility of difference compared to the previous trial. In any case, no one would confuse these small, low-res images for real faces. First, motivated by the Referee’s criticism, and in order to make the manuscript more self-consistent and independent on the 2019 article, we have reported an exhaustive description in a novel sub-section, Description of the E1 experiment in the SI, and refer to this section in the main text when needed. Along with the main details of the experiment, we also report the resolution of the reference portrait (72 pix/inch) and viewing distance to the computer screen in E1 (65(10) cm). Second, the faces sculpted by the subjects are under all respects realistic images, impossible to distinguish from real images (see, for example, fig. 1, which corresponds to the texture that every subject sculpted in real time, using the average vector of landmark positions). The image resolution (72pix/inch) is below the human sensitivity in the sense that doubling such resolution does not result in any appreciable difference in the image. We have discussed the realistic nature of the facial images that we used in 2019, adding further references: >>Many works exploit the geometric/texture decoupling in artificial facial images to study separately the effect of both kinds of coordinates. It is also a natural strategy of dimensionality reduction of the human face, that has been observed to be implemented in both the neural code for facial identification in the brain and by artificial neural networks (Chang and Tsao (2017); Pag !10 Higgins et al. (2020)). In (Ibanez-Berganza et al. (2019)), we combine this separation with the use of completely realistic images, thus eliminating the bias that artificial images are known to induce in experiments (Balas and Pacella (2015); Oh et al. (2019b)). [Balas and Pacella 2015] Balas, B. and Pacella, J. (2015). Artificial faces are harder to remember. Computers in human behavior, 52:331–337. [Oh et al 2019a] Oh, D., Dotsch, R., and Todorov, A. (2019a). Contributions of shape and reflectance information to social judgments from faces. Vision research, 165:131–142. [Oh et al 2019b] Oh, D., Grant-Villegas, N., and Todorov, A. (2019b). The eye wants what the heart wants: Female face preferences track partner personality preferences. [Chang and Tsao 2017] Chang, L. and Tsao, D. Y. (2017). The code for facial identity in the primate brain. Cell, 169(6):1013– 1028.e14. [Higgins et al 2020] Higgins, I., Chang, L., Langston, V., Hassabis, D., Summerfield, C., Tsao, D., and Botvinick, M. (2020). Unsupervised deep learning identifies semantic disentanglement in single inferotemporal neurons. The resolution with which the image is shown in the monitor is roughly R~27 pix/cm. Rather remarkably, the self-consistency distance is only ~3R. This means that the resolution with which we determine the “taste” of the single subject in different realisations of the experiment is not much larger than the minimum distance that can be implemented in the monitor (say, 1 pixel). This, despite of the fact that the images are perfectly realistic. We believe that accurate analysis/checks as the two proposed by the referee (control for optical errors / discard that selected preferred images in each pair based on visibility of difference compared to the previous trial) are interesting possible refinements of the technique, albeit clearly out of the scope of the present work, which is not experimental. Such refinements would probably result in even lower empirical errors and even higher statistical significance of the present results. b. Subjects were apparently uncompensated and mostly undergraduates so it’s not clear how careful or motivated they were. Pag 1 ! 1 The subjects were volunteers, motivated only by their own curiosity and enthusiasm. They were ready to spend more than one hour (20 min. only for E1) in a computer room. They had to book their place in the computer room and come at the appointed day and hour. This may be understood already as a demonstration of motivation. On a more quantitative basis, our database allows us with heuristic evidences of the “care”: the consistency and the sensitivity with which each subject performed the experiment (reaction times, intra-population distance vs time…). As said before, eliminating the less consistent (perhaps less motivated?) subjects from the database would probably result in higher statistical significance of the results. We would be happy to furnish our software for this kind of evolutions of the experiments. Also, what were the instructions? Choose the face you like best? Or the “choose the most attractive face”? These might be different: the first question is about personal preference while the second could be about cultural norms. (also how is gender assessed? Again there are culturally normative effects possible here). We thank the referee for this important point. Subjects were asked to choose the most attractive face. This point is specified in the novel section Description of the E1 experiment. 3. With the generative models, why not generate new sculpted faces tailored for each subject and have that subject choose between that face and, e.g., a face sculpted from the preferences of someone else of the same gender? The subject should choose the face sculpted from their own preferences. As it is, the generative model could just be overfitting an individual’s idiosyncracies of adjustment rather than preference (except for the gender difference). The fact that the self-consistency distance is clearly lower than the inter-subject is an overwhelming evidence that the sculpted faces does consistently represent, and in some cases, actually characterises, the single subject’s taste. As we said before, <<A natural alternative is the one proposed by the referee: a test in which the subject compares his/her sculpted facial vector with those sculpted by other volunteers. This test, however, could be subject to several kinds of bias (a subject could be unconsciously biased towards the face he/she has sculpted), of which the selfconsistency test is free (because it depends, indirectly, on many choices).>> Pag !12 4. Showing model accuracy for gender of the observer doesn’t really follow or support the premise of the work, which is that individual preferences are systematic. I would refocus on the gender result rather than claiming that you are modeling individual preference. This observation gives us the opportunity to clarify this point. That <<individual preferences are systematic>> is, roughly speaking, the question that reference [I-B et al 2019] aimed to address. We obtained, within the experimental limits, a positive answer. The present article does not aim to address such question. Instead, we ask ourselves: 1. to what extent a linear model may infer efficiently the database (i.e., to what extent the database properties may be explained in terms of average positions of the landmarks and pairwise correlations —related to proportions— among them) 2. to what extent one may predict the subjects’ gender from the sculpted facial vector using linear and nonlinear models. The second question does not coincide with <<individual preferences being systematic>> since it is nor a necessary nor a sufficient condition for it. In the new version of section 1, we have rephrased our objectives and motivation in a more clear fashion, following the structure of the 1.,2. points above: >> Our inference protocol allows to assess the relative influence of linear and non-linear correlations among facial coordinates in the classification, hence overcoming the black-box issue. In particular, we infer, in an unsupervised way, a collection of probabilistic generative models from the database of sculpted facial modifications S = {f(s)} (where s is the subject index). Afterwards we assess the predictive power of the models, in two ways. (1) We perform a consistency assessment of the simplest of such models, in order to ensure that all of them provide a faithful and economic description of the data. (2) The models are applied, when inferred from male/female data separately, to the supervised classification of the subject gender of a test-set and the results are compared with a powerful algorithm for supervised classification, the random forest algorithm. Minor comments. Lots of grammar issues. A non-exhaustive list: Citations should be in parentheses. Line 40: Grammar/typo Line 45: What phenomenon? Unclear sentence Line 47: Not sure what “On the other hand” refers to. Line 161: precedent: preceding We thank the referee for these observations. We have put parenthesis in the references. Pag !13 In line 47, “On the other hand” referred to “In the context of evolutionary biology, on the one hand”. We have rephrased the sentences in lines 40 45, and 47 (old numeration): >> Many works have discussed, in the context of evolutionary biology, the validity of the so called natural selection hypothesis (Little et al. (2011); Rhodes (2006)), according to which the traits that we recognise as attractive are markers of a good phenotypic condition. Along with natural selection, also sexual selection and the handicap principle are known to play a role in facial attractiveness (Thornhill and Gangestad (1999)). The mention to the computer-science papers in facial attractiveness has been moved to the Discussion: >>Much work has been devoted to the regression of the average rating in face-space, specially in the machine learning community. Such supervised inference approach indirectly allows for an assessment of the relative impact of various facial traits on perceived attractiveness. This point, however, remains poorly understood (Laurentini and Bottino 386 (2014)). Furthermore, some authors have argued that subjectivity of facial attractiveness has been overlooked and underestimated and that the supervised inference of the rating presents several limitations as an experimental method (Honekopp (2006); Laurentini and Bottino (2014); Oh et al. (2019b)). As a novel experimental tool to the investigation of the nature of facial attractiveness and its subjectivity, we here propose an alternative inference scheme in which the variability to be inferred is the inter-subject variability of preferred modifications in a subspace of the face-space (in which only the geometric position of some landmarks are allowed to vary), rather than the average rating assigned to different natural faces. Finally, we have spell-checked the whole manuscript. Pag !14 Answer to Referee #2 comments: I find the manuscript to be interesting, but the motivation murky and findings are a bit unclear. The manuscript can use a bit more editing. I found a misspelling of gender 'genender' that should have been picked up by spell checker. We thank the Referee #2 for her/his observations. We have tried to express the motivations and conclusions in a more transparent and direct way. We have, in particular, presented a more exhaustive introduction, based on our answers to Referee #2, see below. We discuss the natural selection hypothesis in facial attractiveness, their predictions and limitations, the modern hypotheses involving inference of personality traits. We present a motivation of the article in light of the methodological limitations of supervised inference schemes (the rating regression) as a methodological technique to assess the relative validity of these hypothesis. Such limitations have been already carefully discussed in references that we have added: >>Recently, many works have argued (the multiple motive hypothesis) that the evaluation of facial attractiveness is a complex process, influenced by the prior inference of semantic personality traits (as dominance, extroversion or trustworthiness) that we consensually attribute to specific shape and luminance patterns in others’ face (Oh et al. (2019a,b); Abir et al. (2017); Walker and Vetter (2016); Adolphs et al (2016); Galantucci et al. (2014); Little (2014); Todorov and Oosterhof (2011); Oosterhof and Todorov (2008); Edler (2001); Cunningham et al. (1995)). According to this scenario, facial attractiveness is influenced by the single-subject relative inclination for some fundamental personality traits. In Oh et al. (2019a) words, individuals who highly value a personality trait, such as dominance, are likely to perceive faces that appear to possess the trait as attractive. This implies, in particular, that (A) the single subject preferred faces are expected to be, to some extent, distinguishable if characterised or inferred with sufficient accuracy, and (B) they are expected to reflect meaningful information regarding the subject. >>The assessment of the validity of these hypothesis is, arguably, strongly influenced by the experimental precision with which the individuals’ preferred faces can be characterised. While the natural selection hypothesis explain general aspects of facial attractiveness, if the experiments allow to resolve the single subjects’ idiosyncrasies, more complex aspects and a strong subjectivity emerge (Ho ̈ nekopp (2006); Oh et al. (2019b)). In particular, the subjectivity of facial attractiveness has been proven to be underestimated by the common experimental method from which most of the works regarding facial attractiveness draw their conclusions: the subject-averaged rating assigned to several natural facial images (Honekopp(2006)). Moreover, it has been argued that the average rating may suffer, as an experimental technique, the curse of dimensionality (the face-space being highly dimensional) and may consequently hinder the complexity and subjectivity of the phenomenon (Laurentini and Bottino (2014); Valentine et al. (2016); Ibanez-Berganza et al. (2019)). Roughly half of the variance in attractiveness ratings has been attributed to idiosyncratic preferences, the other half to shared preferences (Ho ̈ nekopp (2006)). It is a natural question whether such idiosyncratic proportion Pag !15 would result more prominent using an experimental method that bypasses the use of ratings. Afterwards, we motivate the two precise and natural questions/objectives that our work aims to address: 1. to what extent a linear model may infer efficiently the database of facial modifications (i.e., to what extent the database properties may be explained in terms of average positions of the landmarks and pairwise correlations —related to proportions— among them) 2. to what extent one may predict the subjects’ gender from the sculpted facial vector using linear and nonlinear models. In the novel version of section 4 we present in a clearer way our results, providing a answers to the two questions above, and interpreting it in terms of the above mentioned hypotheses: >>The present approach allows to clarify several aspects regarding facial preference. First, that the cognitive mechanisms related to facial discrimination in the brain mainly involves proportions, or pairwise influence of couples of landmarks, more than the positions of single landmarks. Indeed, the 2-MaxEnt model, equivalent to a description in terms of principal components, is enough to describe also non-linear features of the database (see sec. 3.1.1). Moreover, the results suggest as well that non-linear operators of the geometrical facial coordinates may play a non-negligible role in the cognitive process (see sec. 3.1.2). Further research is needed to clarify this point (see also Cognitive origin of non-linear correlations in the SI).8 >> Second, and rather remarkably, the introduction of non-linear effective interactions, beyond the influence of proportions, allows for an astonishingly high classification efficiency of the facial vectors according the subject’s gender. Indeed, the random forest algorithm, a highly nonlinear supervised algorithm for classification, provides a 97% of correct classifications. The most non-linear of the probabilistic models, the GRBM, provides a slightly lower accuracy: 95%. This implies that the subject’s gender strikingly determines her/his facial preference criteria and that the sculpted facial modifications, as a sample of the subjects idiosyncratic criterion, are accurate enough to allow to predict such impact. While the impact of the gender is consistent with the sexual selection hypothesis (Little et al. (2011); Rhodes (2006); Thornhill and Gangestad (1999)), it is also consistent in this framework with the gender strongly influencing the subjects’ preferences for personality traits, in the language of Oh et al. (2019b). Further work is needed to clarify this relevant issue. We are confident that, in its new version, sec. 4 express more clearly our findings. Pag !16 The research question itself is somewhat interesting, but on the whole I don't understand why there would be an expectation that facial deformations would be preferred across people or not. I don't understand why there is a clear gender difference, or what the difference is. The theoretical motivation is lacking. Charles Darwin first exposed a concept called sexual selection, providing an explanation for sexual dimorphism in secondary sexual characteristics, (say, for “beauty” traits in animals, such as the ornate plumage of peacocks, or the deers’ antlers). Such traits are deleterious for surviving, but functional to mate with members of the opposite sex. This is the evolutionary origin of the development of “beautiful” traits: these are those that may be recognised as markers of the individual’s good phenotypic condition (“beauty as a health certificate”). The more complex mechanism of Fisherian runaway implies a co-evolution of the development of certain traits in the male, and the development of the ability to recognise these traits as attractive in the female, in a feedback mechanism that is believed to lead to ornate plumages in birds. Still different theoretical mechanisms of sexual selection and modern formulations of Fisherian runaway have been proposed to exist in animals: the sensory bias hypothesis, the compatibility hypothesis and the handicap principle. Despite there are controversies regarding the sexual selection hypothesis and the evolutive origin of secondary sexual traits, it has an extraordinary importance in genetics and in biology, and has been observed in many animals, even in plants and fungi (see, for example, Wikipedia). For what concerns human faces, however, the question is particularly debated. The sexual selection hypothesis implies that the perception of beauty is mainly universal, species-typical. While a partial universality has been assessed, it is known that it is also culturally influenced, and that there even exist observable inter-subject differences in the perception of attractiveness. Recently, it has been argued that the evaluation of facial attractiveness is a much complex process, influenced by the semantical personality traits that we attribute to specific shape and luminance patterns in others’ face [Oh et al 2019]. It is actually believed that facial attractiveness is based on the prior inference of personality traits from the face (as dominance, extroversion and trustworthiness, among others), such inference being consensual or universal. Afterwards, the individual unconsciously forms an evaluation of the attractiveness of a face based on her/his personal inclination for each of these personality traits. In this way, this scenario predicts that, (A)within a sufficiently high “resolution” of each persons’ taste, beauty is subjective. Afterwards, it predicts as well that Pag !17 (B) the criterion of an individual, if accurately inferred, may reveal relevant information regarding the individuals’ psychology and, in general, a lot of information regarding the individual. However, it has been observed that the supervised regression of the rating may pose several limitations in the assessment of the A,B predictions of such hypothesis. In particular, several authors have explained that the idiosyncrasy and the complexity of the facial perception are hindered by the arbitrariness of the rating and by the course of dimensionality associated with the rating of (high-dimensional) natural images. In [I-B et al 2019] and in the present work we have addressed, respectively, the predictions (A) and (B), within a novel method of facial attractiveness assessment at a personal level. We have rewritten the Introduction according to this structure. This research topic, the assessment of the validity of the natural selection hypothesis in the perception of the human face, and of its consequences (universality, impact of symmetry, averageness and sexual dimorphism in facial attractiveness), has been one of the most intense intense objects of study in evolutionary psychology since the eighties, with several hundreds of relevant publications at this regard (please see the reviews [Little et al 2011, Thornhill & Gangestad 1999, Laurentini and Bottino 2014]). Since the first decades of the XIX century, and with the advent of the deep learning, the supervised regression of facial attractiveness ratings is also a standard benchmark for deep and machine learning algorithms, being the subject of many publications (see references in [Ibáñez-Berganza et al 2019]). The question of the subjectivity/objectivity of facial beauty is, hence, of undiscussed interest. There are hundreds of references that have assessed the partial universality of facial attractiveness and the relative impact on it of various facial traits (texture, symmetry, averageness, sexually dimorphic traits, single distances, principal components of texture/geometry… ). The novelty of our approach is the method, with which one can accurately sample a subset of the face-space which is representative of the single individual’s taste. This allows to explore somehow the opposite, disregarded “limit”: the assessment of the extent to which facial attractiveness is subjective, not the extent to which it is objective. Pag !18 The impact of the subjects’ gender in the perceived attractiveness is one of the most investigated questions in this context. On the one hand, it is a consequence of the sexual selection hypothesis. On the other hand, it is compatible with the hypothesis that we judge on the basis of consensually inferred personality traits from others’ faces (since males and females tend to prefer different personality traits, as has been recently proved). Many references have reported the quantitative differences among males and females perception of facial beauty. On general grounds, males prefer smaller lower face area, higher cheekbones, larger mouths and eyes, some of these properties may be interpreted in terms of sexual selection, and have been confirmed in [Ibáñez-Berganza et al 2019]. To the best of our knowledge, the possibility of predicting, with almost certainty, the subjects’ gender from their sculpted facial vector is a result of unprecedented accuracy in this debate. We have also mentioned these last aspects of the debate in the novel version. [Oh et al 2019] DongWon Oh, Ron Dotsch, Alexander Todorov, Contributions of shape and reflectance information to social judgments from faces, Vision Research 165, p. 131 (2019) [Hönekopp 2006] Hönekopp, J. (2006). Once more: is beauty in the eye of the beholder? relative contributions of private and shared taste to judgments of facial attractiveness. Journal of Experimental Psychology: Human Perception and Performance, 32(2):199. In the supplemental material the authors state that the model is not overfitted, so perhaps the higher order interaction is replicable, but is it understandable? We have observed that many higher-order tensor elements (say, $J_{ijk}$) of effective interactions, are different from zero within their statistical (bootstrap) errors and, hence, replicable in principle. While the pairwise matrix J_{ij} is associated with distances and angles of inter-landmark segments, c.f. fig-4, the question of the interpretability of triplets and/or quadruplets of landmarks is, in my opinion, much more complex. Pairwise correlations, C_ij among oblique coordinates are obviously related to proportions (see <<Average proportions and pairwise correlations>> in the SI), or quotients of two quantities d_i/d_j. But, what is a three-proportion? Tensor elements $J_{ijk}$, specially for i different from j different from k represent something like three Pag !19 proportions conditioned on each other. Perhaps they reflect global operations, involving pairs of angles. This interesting point should be, in any case, faced in future works. As a final remark, it is worth to mention that, given the presence of a constraint, not even the interpretation of C_{ij} is straightforward (c.f. fig. 4-C and Two ways of inferring with constraints in the database of facial modifications in the SI). When inferred through the zero-mode subtraction technique, however, at least matrix J becomes interpretable in terms of the torsion and longitudinal “resistance” (elastic constant) of inter-landmark segments to be deformed with respect to their average (preferred) value. The aim of section 3.2 is precisely to prove that such an interpretation is, indeed, possible. We have clarified this point in a further paragraph in section 3.2: >> We prove, in particular, that at least the matrix of effective interactions $J$ admits an interpretation in terms of “resistance” (elastic constant) of inter-landmark segment distances and angles to differ with respect to their average (preferred) value. and made it more explicit also in the caption of fig. 4. Pag !20 Answer to Referee #3 comments: The manuscript „Unsupervised inference approach to facial attractiveness“ deals with probalistic models that predict the gender of persons that created faces to their maximum attractiveness in virtual face spaces. The language of the whole manuscript is extremely vague. Therefore, it was quite often hard for me to follow the authors‘ thoughts. E.g., „it has been conjectured that this approach does not capture the complexity of the phenomenon.“ (Abstract). This might be true, but I cannot verify this claim since the authors did not give precise information on why the complexity oft he phenomenon is not captured. Following the suggestions of Dr. Gregor Hayn-Leichsenring, we have rewritten the introduction and conclusions, in order to make more clear the article’s aim and results. We have, in particular, clarified the passage that he mentions. We provide a clear explanation of the criticisms to the natural selection hypothesis in the introduction, accompanied by further references. We report the new version of the incriminated passage: >> The evolutionary approach explains several aspects of the phenomenon, as the impact in facial attractiveness of facial traits that are known to covary with a good phenotypic condition (averageness, symmetry, secondary sexual traits). Despite the success of the evolutionary approach, it is known that there are aspects of facial attractiveness eluding an evolutionary explanation. The natural selection hypothesis implies that the perception of attractiveness is mainly universal, species-typical. While a certain degree of universality has been assessed in many references, cultural and inter-person differences, beyond the species-typical criterion, definitely play a role (Little (2014)). Several factors are known to influence the single subject idiosyncrasies, as the subject’s self- and other-rated attractiveness, genetic propensity, sexual orientation, or the menstrual cycle (see references in Oh et al. (2019b)). >>Recently, many works have argued (the multiple motive hypothesis) that the evaluation of facial attractiveness is a complex process, influenced by the prior inference of semantic personality traits (as dominance, extroversion or trustworthiness) that we consensually attribute to specific shape and luminance patterns in others’ face (Oh et al. (2019a,b); Abir et al. (2017); Walker and Vetter (2016); Adolphs et al. (2016); Galantucci et al. (2014); Little (2014); Todorov and Oosterhof (2011); Oosterhof and Todorov (2008); Edler (2001); Cunningham et al. (1995)). According to this scenario, facial attractiveness is influenced by the single-subject relative inclination for some fundamental personality traits. In Oh et al. (2019a) words, individuals who highly value a personality trait, such as dominance, are likely to perceive faces that appear to possess the trait as attractive. This implies, in particular, that (A) the single subject preferred faces are expected to be, to some extent, distinguishable if characterised or inferred with sufficient accuracy, and (B) they are expected to reflect meaningful information regarding the Pag !21 subject. Another example: Line 43ff: If you criticize the natural selection hypothesis, please explain your criticism to the reader: „that it does not take into account the phenomenon in its various complex facets“ is no proper critique. Similar passages can be found throughout the manuscript and make it very hard to follow (or to criticize). We have tried make the article as linear and unambiguous as possible in its new version. As we hope it is clearer in the new version of the article, the criticism to the natural selection hypothesis in facial attractiveness is not our criticism, but a well documented limit. In the new version: >> The evolutionary approach explains several aspects of the phenomenon, as the impact in facial attractiveness of facial traits that are known to covary with a good phenotypic condition (averageness, symmetry, secondary sexual traits). Despite the success of the evolutionary approach, it is known that there are aspects of facial attractiveness eluding an evolutionary explanation. The natural selection hypothesis implies that the perception of attractiveness is mainly universal, species-typical. While a certain degree of universality has been assessed in many references, cultural and inter-person differences, beyond the species-typical criterion, definitely play a role (Little (2014)). Several factors are known to influence the single subject idiosyncrasies, as the subject’s self- and other-rated attractiveness, genetic propensity, sexual orientation, or the menstrual cycle (see references in Oh et al. (2019b)). To the same point: In my opinion, there is not a sufficient literature review. Quite a few important studies are cited, but the manuscript lacks clarity on the relevant (detailed) results of those studies. We have written a more prolific introduction, accompanied by further references. The manuscript needs a language check, preferably by a native speaker. There are numerous misspellings and grammatical errors. Furthermore, I found the citation style rather confusing (only the year oft he citation is in brackets) – this made the manuscript rather difficult to read. We have spellchecked the manuscript and corrected the bibliography. The introduction already includes the main results. Pag !22 We are used to physics journals, where this is a common practice. We have removed the results from the introduction. The research question is relevant, especially taking into account that the higher accuracy of the non-linear model includes implications on the nature of visual processing of facial attractiveness. While these implications remain to be tested, the results are in itself quite promising. We are glad that the referee acknowledges the relevance of the results From my point of view, the study is well designed. However, methods as well as results are not presented in a way that makes understanding easy for the reader. Descriptions are quite technical without any further explanation. (1) (2) The Restricted Boltzmann Machine model is not sufficiently explained. The manuscript lacks a technical comparison between all three methods. We thank the referee for raising these non-trivial issues. 1) In the SI of the article we have presented a section called Learning the database with the Gaussian Restricted Boltzmann Machine, in which we present a gentle introduction to the RBM model of artificial neural network, from its very definition to the details of the learning protocol. It is a clear, self-contained and succinct explanation. In this section, there are at least eight references to books, reviews and specialised articles. The RBM is a standard model of neural network, of which the reader may found pedagogical explanations in any book of machine learning, or in Wikipedia. We consequently disagree with the referee that the Restricted Boltzmann Machine is not sufficiently explained. We have, in any case, added a further synthesis of the section Learning the database with the Gaussian Restricted Boltzmann Machine in the main text, in sec. 2.4. 2) We agree with the referee that, in principle, an exhaustive comparison of the efficiency among the three methods could be done. Nevertheless, in our opinion, such comparison is not straightforward. One could perform a comparison of the methods in terms of the trainingset likelihood or of reconstruction errors. These, however, evaluate only the bias error, and would be biased towards models with high number of parameters. The test-likelihood is a quantity that takes into account both bias and variance errors. But, again, a straightforward comparison among test-likelihoods Pag !23 presents a further technical difficulty: there is no unambiguous way to compare the likelihoods of several MaxEnt models with different number of parameters. In my opinion a comparison among all models on firm information-theoretical grounds is possible but not at all straightforward. As a more general digression, I would say that there is no way to assess which probabilistic model “infers better” a database. The best inferring model depends on the application (and the need for interpretability, the need for reproducibility etc.). In this sense, the hierarchy of the various algorithms according to the accuracy score of the classification (see “Detailed comparison among several classification methods” in the SI) may, indeed, be take as our <<technical comparison between all three methods>>. I am not sure whether I missed it, but I did not find any information on the number of subjects that were included in the analysis. It was in footnote 3 (old manuscript): <<ns=95, N =28>>. We have now put this information in the main text (line 106). The authors state that it should be a next step to test the results with other datasets. I completely agree. However, I think the authors provide enough data for a coherent study. The high accuracy is surprising and extraordinary. The strength of the manuscript is that it compares several methods to predict the gender of a person based on their face attactiveness preferences. I like the use of the Maximal Entropy Model in this area of research, especially since it also provides some quantitive insight. We acknowledge Dr. Hayn-Leichsenring for such positive observations. The weakness is the structure of the manuscript itself as well as the language. Especially in the introduction, it is often not clear which point the authors‘ are making exactly. Within the materials, the authors provide lots of detailed information, but I lost track some times since I am not an expert in MaxEntropy. We are sure that the article in its present version drives the reader to the point more straightforwardly. Before (old) subsection 2.1 we have added a didactical introduction to unsupervised inference and MaxEnt inference. Furthermore, we have emphasised that in the SI the reader may find a more technical Introduction to the Maximum Entropy principle: Correlations vs effective interactions. Pag !24 I’d be highly interested in the effect of sexual orientation on the results, but I guess this information is not available in Ibanez-Berganza et al. (2019). Unfortunately, not. We could not ask the subjects at this regard for privacy issues. We would be happy if our software and expertise could be used to perform an experiment designed to address this question. We agree with the referee, this result would be very interesting. I’d like to encourage the authors to work on the structure and the language of the manuscript in ordert o make it more accessible. The approach itself is very promising and the results are more than interesting. Thank you very much. Please explain Figure 2 in more detail (longer caption). I did not fully understand what is demonstrated in this figure. We report the agreement among the theoretical (according to the inference model L) and empirical histograms of angle landmark displacements. For each angle phi in the interval (-pi:pi), in abscissa, we report the fraction of the i-th landmark displacements along an axis that forms an angle phi with the horizontal axis. This observable is a highly nonlinear observable of the landmark displacements (since it depends on the angle through the arc-tangent function). The agreement among theoretical and empirical histograms is an evidence of the fact that the 2-MaxEnt model is an “economic” description of the database: chosen to reproduce the empirical correlation matrix only, it reproduces also nonlinear observables. A posteriori, it turns out that, in fact, these may be explained in terms of empirical correlations only. This fact is by no means obvious. We have provided a more complete explanation in the caption of fig. 2: >> Comparison among empirical (h(i)(φ)) and theoretical (h(i)(φ)) histograms of angle landmark fluctuations, for several landmarks, i = 1, 5, 6, 7, see fig. 1 (from left to right, from top to bottom). The empirical histograms h(i)(φ) represent the probability density of empirical displacement ∆i(s) of the i-th landmark along an axes which subtends an angle φ ∈ (−π , π ) with the horizontal axis. These histograms are presented for all the landmarks also in fig. 1, under the form of polar histograms. h(i)(φ) is the theoretical prediction of the same quantity, obtained by sampling data from the inferred L (·|θ ). The terms beauty and attractiveness are not distinguished. Pag !25 Thank you for this observation. Coherently with the ambiguity that we have found in the specific literature, we treated these two terms as synonyms. In the new version we have replaced the term beauty by attractiveness throughout the manuscript. Abstract: What are „detailed and global facial features“? Good point. We intended both holistic (i.e., principal components) and detailed (i.e., the detailed shape of the eye). We have, however, reduced this sentence, >>[…] is a complex phenomenon depending on many facial features influencing each other. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>In the past 20 years, there has been growing research interest in the association between video games and cognition. Although many studies have found that video game players are better than non-players in multiple cognitive domains, other studies failed to replicate these results. Until now, the vast majority of studies defined video game players based on the number of hours an individual spent playing video games, with relatively few studies focusing on video game expertise using performance criteria. In the current study, we sought to examine whether individuals who play video games at a professional level in the esports industry differ from amateur video game players in their cognitive and learning abilities.</ns0:p><ns0:p>We assessed 14 video game players who play in a competitive league (Professional) and 16 casual video game players (Amateur) on set of standard neuropsychological tests evaluating processing speed, attention, memory, executive functions, and manual dexterity. We also examined participants' ability to improve performance on a dynamic visual attention task that required tracking multiple objects in threedimensions (3D-MOT) over five sessions.</ns0:p><ns0:p>Professional players showed the largest performance advantage relative to Amateur players in a test of visual spatial memory (Spatial Span), with more modest benefits in a test of selective and sustained attention (d2 Test of Attention), and test of auditory memory (Digit Span). Professional players also showed better speed thresholds in the 3D-MOT task overall, but the rate of improvement with training did not differ in the two groups. Future longitudinal studies of elite video game experts are required to determine whether the observed performance benefits of professional gamers may be due to their greater engagement in video game play, or due to pre-existing differences that promote achievement of high performance in action video games.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>In 2016, there were more than two billion video gamers worldwide and this number is projected to increase to 2.7 billion by 2021 <ns0:ref type='bibr'>(Statista, 2020)</ns0:ref>. In the United States only, the gamer population consists of more than 150 million individuals, representing a 17.7 billion dollar market <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b74'>SpillGames, 2013;</ns0:ref><ns0:ref type='bibr' target='#b75'>Statista, 2017)</ns0:ref>. There are many video game genres, such as action, real-time strategy, fighting, adventure, role playing or racing games. Among all types of games, action video games (AVGs), such as Call of Duty, Halo or Overwatch, are among the most popular in the United States <ns0:ref type='bibr' target='#b76'>(Statista, 2019)</ns0:ref>. More recently, we have witnessed the emergence of eSports, where expert video gamers compete individually or in teams in national and international competitions. For example, more than 117 schools in the United States have competitive esports programs, with many professional leagues experiencing a growth in audience and revenues <ns0:ref type='bibr' target='#b64'>(NACE, 2020;</ns0:ref><ns0:ref type='bibr'>Newzoo, 2020)</ns0:ref>.</ns0:p><ns0:p>The rise in popularity of video games in the last 20 years has led to a surge of research examining the impact of video games on the mind and brain, with a special focus on AVGs.</ns0:p><ns0:p>Although AVGs differ from one another, they all share four characteristics: a fast pace (moving objects, time constraints), a high perceptual load, a high degree of distraction, and a requirement for constant switching between focused and distributed state of attention <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018)</ns0:ref>.</ns0:p><ns0:p>AVGs are also highly engaging and intrinsically motivating activities, making them attractive and popular <ns0:ref type='bibr' target='#b67'>(Powers &amp; Brooks, 2014)</ns0:ref>. Among all types of AVGs, first-person shooter <ns0:ref type='bibr'>(FPS)</ns0:ref> games, in which the player has an egocentric view through its avatar's eyes, have been the focus of many studies, as they were suspected to be the most likely to influence cognition due to their high engagement on sensory, perceptual, and cognitive functions <ns0:ref type='bibr'>(Spence &amp; Feng, 2010)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed Although AVG are the must studied, other types of games, such as real-time strategy, has also been shown to impact cognition <ns0:ref type='bibr' target='#b39'>(Glass, Maddox, &amp; Love, 2013)</ns0:ref>. Cross-sectional studies that have compared performance of habitual players of AVGs with non-players have reported that, as a group, habitual players of AVGs are better than non-players in multiple cognitive domains, including selective attention <ns0:ref type='bibr' target='#b15'>(Castel, Pratt, &amp; Drummond, 2005;</ns0:ref><ns0:ref type='bibr'>Dye, Green, &amp; Bavelier, 2009;</ns0:ref><ns0:ref type='bibr' target='#b40'>Green &amp; Bavelier, 2003;</ns0:ref><ns0:ref type='bibr'>Green &amp; Bavelier, 2006)</ns0:ref>, speed of processing <ns0:ref type='bibr' target='#b15'>(Castel et al., 2005;</ns0:ref><ns0:ref type='bibr'>Dye et al., 2009)</ns0:ref>, executive functions <ns0:ref type='bibr' target='#b0'>(Andrews &amp; Murphy, 2006;</ns0:ref><ns0:ref type='bibr' target='#b21'>Colzato, Van Leeuwen, Van Den Wildenberg, &amp; Hommel, 2010)</ns0:ref> and working memory <ns0:ref type='bibr' target='#b20'>(Colzato, van den Wildenberg, Zmigrod, &amp; Hommel, 2013)</ns0:ref>. These cross-sectional, observational studies have been reinforced by several intervention studies that have demonstrated an improvement in the same cognitive domains in non-players following training with AVGs <ns0:ref type='bibr' target='#b35'>(Feng, Spence, &amp; Pratt, 2007;</ns0:ref><ns0:ref type='bibr' target='#b67'>Powers &amp; Brooks, 2014;</ns0:ref><ns0:ref type='bibr' target='#b73'>Spence, Yu, Feng, &amp; Marshman, 2009)</ns0:ref>. A recent meta-analysis of 82 studies focusing on AVGs concluded that AVGs are associated with improved cognitive function in general, with the most robust effects seen in the domains of spatial cognition, top-down attention, and perception, medium effects in multitasking and task-switching, and only weak effects in inhibition and verbal cognition <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018)</ns0:ref>. Nevertheless, several studies have failed to find benefits of video gaming using similar methodologies <ns0:ref type='bibr' target='#b14'>(Cain, Landau, &amp; Shimamura, 2012;</ns0:ref><ns0:ref type='bibr' target='#b48'>Irons, Remington, &amp; McLean, 2011;</ns0:ref><ns0:ref type='bibr' target='#b62'>Murphy &amp; Spencer, 2009)</ns0:ref>.</ns0:p><ns0:p>The vast majority of studies examining the effects of AVG on perceptual and cognitive function have defined video game players solely using a criterion average number of hours of video game play over the last 6 -12 months, with only a few studies examining video game expertise in relation to the individual's level of performance in a game. As argued by <ns0:ref type='bibr' target='#b55'>Latham, Patston and Tippett (2013)</ns0:ref>, the lack of consideration of individual differences in video game play experience and expertise likely contributes to the heterogeneity of the results observed in the literature and limits our understanding of video game expertise. The concept of elite experts is useful when considering differences in performance amongst experts. In the broadest sense, expertise can be described as knowledge/abilities in a specific area such as a profession, a hobby, a sport, or games as a result of a substantial amount of time devoted to the activity <ns0:ref type='bibr' target='#b16'>(Chi, Glaser, &amp; Farr, 2014;</ns0:ref><ns0:ref type='bibr' target='#b31'>Ericsson &amp; Towne, 2013;</ns0:ref><ns0:ref type='bibr' target='#b32'>Farrington-Darby &amp; Wilson, 2006)</ns0:ref>. To be considered as an elite, in addition to gaining experience in a certain domain, individuals must also achieve a high level of performance in comparison to others, as established through a competitive process, such as athletes who play in professional leagues or in international competitions <ns0:ref type='bibr' target='#b79'>(Swann, Moran, &amp; Piggott, 2015)</ns0:ref>. In the world of video games, players who consistently achieve high rankings, or those selected to participate in professional leagues, are considered elites. While practice is necessary to achieve high levels of performance, the amount of practice alone it is not sufficient, as individuals can practice a lot and acquire knowledge in a specific area without ever becoming an elite <ns0:ref type='bibr' target='#b31'>(Ericsson &amp; Towne, 2013)</ns0:ref>.</ns0:p><ns0:p>Understanding what characteristics enable individuals to achieve a high level of performance is the focus of much research in the domain of expertise <ns0:ref type='bibr' target='#b16'>(Chi et al., 2014)</ns0:ref>. Within the context of their discipline, elite athletes from various sports have shown better perceptual-cognitive capacities, as they are better able to extract pertinent information in the visual scene, and show a different pattern of eye movements and visual search strategies, relative to non-elite athletes <ns0:ref type='bibr' target='#b61'>(Mann, Williams, Ward, &amp; Janelle, 2007)</ns0:ref>. Perceptual-cognitive capacities refers to the ability to identify and amass information to combine with actual knowledge in order to select and execute the appropriate response <ns0:ref type='bibr' target='#b16'>(Chi et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b61'>Mann et al., 2007)</ns0:ref>. The ability to extract information is a crucial element of high-level competitive sports. Given that the visual scene is often wide and contains a high density of information, athletes must direct their attention appropriately to extract relevant information in order to make a fast decision <ns0:ref type='bibr' target='#b61'>(Mann et al., 2007)</ns0:ref>. Similarly, in videogaming, a player must also select and extract relevant information in order to keep track of his or her enemies while anticipating their actions and deciding the best strategy to reach his or her objective.</ns0:p><ns0:p>At the same time, growing research suggests that elite athletes may also differ from non-athletes on certain core perceptual or cognitive capacities in general, outside the specific context of their expertise. For example, several recent studies have found that elite athletes outperform nonathletes in cognitive tests evaluating attention, multitasking, working memory, and processing speed with a small to medium effect size <ns0:ref type='bibr' target='#b33'>(Faubert, 2013;</ns0:ref><ns0:ref type='bibr' target='#b70'>Scharfen &amp; Memmert, 2019;</ns0:ref><ns0:ref type='bibr' target='#b85'>Vaughan &amp; Laborde, 2020;</ns0:ref><ns0:ref type='bibr' target='#b87'>Voss, Kramer, Basak, Prakash, &amp; Roberts, 2010)</ns0:ref>. Professional athletes were also found to have a greater ability to improve their performance on a three-dimensional multiple-object-tracking task (3D-MOT) as a function of training compared to high level amateurs (NCAA &amp; Olympic) and to non-athletes <ns0:ref type='bibr' target='#b33'>(Faubert, 2013;</ns0:ref><ns0:ref type='bibr' target='#b34'>Faubert &amp; Sidebottom, 2012)</ns0:ref>.</ns0:p><ns0:p>The 3D-MOT task requires participants to track several moving targets among identical distractors in a three-dimensional space at various speeds. The speed at which a given number of targets can be tracked is limited and shows large individual variability, but improves with training <ns0:ref type='bibr' target='#b33'>(Faubert, 2013;</ns0:ref><ns0:ref type='bibr' target='#b56'>Legault, Allard, &amp; Faubert, 2013;</ns0:ref><ns0:ref type='bibr'>Parsons et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b83'>Tullo, Faubert, &amp; Bertone, 2018)</ns0:ref> and has been shown to lead to improved decision making in sports <ns0:ref type='bibr' target='#b69'>(Romeas, Guldner, &amp; Faubert, 2016)</ns0:ref> . The finding that the learning rate in 3D-MOT was greater with PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed increasing level of sports performance indicates that professionals may have enhanced learning abilities within the context of a general, dynamic visual scene. In sum, the above studies suggest that the outstanding performance reached by elite athletes may be associated with enhanced abilities in certain cognitive domains (attention, processing speed, working memory, learning abilities), indicating that professional athletes may also exhibit cognitive expertise.</ns0:p><ns0:p>To our knowledge, no studies have previously examined whether professional action video game players also exhibit distinct cognitive abilities relative to amateur players. While growing evidence supports an association between action video games and cognition <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018)</ns0:ref>, further research is needed to better understand the nature of this association. Studying the cognitive abilities of expert video gamers can shed more light on this relationship by addressing the question: does the outstanding performance of professional video game players stem from extraordinary cognitive abilities in certain domains, or is it largely due to an enhanced expertise within the context of the game? Furthermore, studying the cognitive expertise of professional videogame players can provide clues as to how expertise is developed, the mechanisms at play, and how best to support it and improve it <ns0:ref type='bibr' target='#b32'>(Farrington-Darby &amp; Wilson, 2006)</ns0:ref>.</ns0:p><ns0:p>To address this gap, the purpose of this study was to characterize the cognitive and learning abilities of high-performance action video game players, recruited amongst the Houston Outlaws, a professional team in the Overwatch league&#8482;. We used a selection of standardized neuropsychological tests to evaluate cognitive abilities, and trained participants on the 3D-MOT task to assess the players' abilities to learn a novel, dynamic perceptual-cognitive task. We hypothesized that professional players will perform better than amateur players on PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed neuropsychological tasks that evaluate attention, processing speed, executive functions, working memory and visuo-spatial manipulation, as those aspects of cognition were found to be better in habitual video game players when compared with non-players <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018)</ns0:ref>. We also hypothesized that professional players would show faster learning rates on 3D-MOT than amateur players, as was observed with expert athletes <ns0:ref type='bibr' target='#b56'>(Allard &amp; Faubert, 2013)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Participants</ns0:head><ns0:p>The experimental protocol was evaluated and approved by the Comit&#233; d'&#201;thique de la Recherche en Sant&#233; of Universit&#233; de Montr&#233;al (18-009-CERES-D). Fourteen participants (all men, righthanded) were recruited amongst competitive players in the Overwatch League&#8482; for the Houston Outlaws, and will be heretofore referred as the Professional group. These participants are considered elite video gamers, because they needed to achieve a high level of performance to be able to enter the professional league. They reported daily FPS video game usage in the last 6 months and were ranked as Grandmaster or Top 500/Pro in the game. As a comparison group, we recruited habitual video game players (Amateur group) through online advertisements targeted at undergraduate students at the Universit&#233; de Montr&#233;al. Knowing that the video game category and type may be important influencing factors <ns0:ref type='bibr' target='#b25'>(Dobrowolski, Hanusz, Sobczyk, Skorko, &amp; Wiatrow, 2015)</ns0:ref>, participants in the Amateur group needed to be current FPS video game players, engaging in an average of 6 to 20 hours per week of FPS in the last 6 months.</ns0:p><ns0:p>Participants who previously participated in organized video game competitions, or who played more than 20 hours per week, were excluded. A total of 20 participants (3 left-handed, 4 female) were enrolled in the Amateur group. Two participants were excluded for playing more than 20h</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed per week or having taken part in competitions, and two more were excluded due to inadequate testing environments, resulting in a sample of 16 participants in the Amateur group.</ns0:p><ns0:p>Demographic and video game experience characteristics of the two groups are summarized in Table <ns0:ref type='table'>1</ns0:ref>. All participants were screened for depressive symptoms using the Beck Depression Inventory II (BDI-II, exclusion &gt;20 <ns0:ref type='bibr' target='#b88'>(Wang &amp; Gorenstein, 2013)</ns0:ref>; no participants were excluded based on their BDI-II scores. Participants had normal or corrected-to-normal vision and were free of visual, neurological, musculoskeletal, cardiovascular and vestibular impairments, as assessed by self-report. Handedness was also self-reported. All participants gave their verbal and written informed consent to participate after receiving verbal and written information about the study. They were not paid for their participation.</ns0:p></ns0:div> <ns0:div><ns0:head>Neuropsychological measures</ns0:head><ns0:p>Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref> summarizes the eight neuropsychological tests that were used in this study.</ns0:p><ns0:p>The d2 Test of Attention <ns0:ref type='bibr' target='#b12'>(Brickenkam &amp; Zillmer, 1998)</ns0:ref> was selected to evaluate selective and sustained attention skills, as well as speed of processing. In this test, participants are presented with a sheet of paper containing 14 lines of 47 items each. The items are either a 'p' or a 'd' with one to four dashes placed alone or in pairs below and above the letter. Participants are given 20 seconds per line to cross out all the items containing a 'd' with two dashes. The outcome measures include the total number of items processed (TN), the percent of errors of omission and commission (%E), number of correct items (TN-E), concentration performance (CP), and the variability in performance across lines (fluctuation ratio, FR). The WAIS-IV Coding test was selected to evaluate visual processing speed <ns0:ref type='bibr' target='#b89'>(Wechsler, 2011)</ns0:ref>. In this task, participants are required to code a series of numbers using symbols shown on a key at the top of the page, similar to the Digit Symbol Substitution Test. The total number of items that are coded in two minutes is recorded. The WAIS-IV Visual Puzzles was selected to evaluate visual reasoning and the ability to manipulate visual information <ns0:ref type='bibr' target='#b89'>(Wechsler, 2011)</ns0:ref>. This task requires the participant to decide which three of six puzzle pieces combine together to reconstruct a larger puzzle within limited time. The number of successfully completed puzzles is scored. The WAIS-IV Digit Span test was selected to evaluate auditory working memory (aWM) and short-term memory (aSTM; <ns0:ref type='bibr' target='#b89'>(Wechsler, 2011)</ns0:ref>. The test requires participants to listen to series of digits that are read out loud and to recite them back in the same order (Forward subtest), backwards order (Backward), or in increasing numerical order (Sequencing). The total number of correctly reported sequences is scored <ns0:ref type='bibr' target='#b90'>(Weiss, Saklofske, Coalson, &amp; Raiford, 2010)</ns0:ref>. The Wechsler Memory Scale-III (WMS-III) Spatial Span test was selected to evaluate visual working memory (vWM) and visual shortterm memory (vSTM ; <ns0:ref type='bibr' target='#b51'>(Kessels, van den Berg, Ruis, &amp; Brands, 2008)</ns0:ref>. In this test, participants are shown nine cubes placed randomly on a board. The examiner taps a number of cubes in a sequence and participants have to reproduce this sequence either in the order presented (forward subtest) or in backwards order (backward subtest). One point is allowed per successful sequence.</ns0:p><ns0:p>Two tests from the Delis Kaplan Executive Function System (D-KEFS) were selected to evaluate executive function <ns0:ref type='bibr' target='#b24'>(Delis, Kaplan, Kramer, Delis, &amp; Kramer, 2001)</ns0:ref>. The D-KEFS Tower test evaluates problem solving and planning. The task requires to move five disks across three pegs to build a tower in the fewest number of moves possible. Performance is scored using the total achievement score, representing the sum of achievement points for all the administered items, and the move accuracy ratio score, which assesses the efficiency with which the participant constructed the towers. The D-KEFS Colour-Word Interference test is a version of the Stroop test that evaluates inhibition and cognitive flexibility. In the inhibition condition, participants are PeerJ reviewing <ns0:ref type='table' target='#tab_4'>PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:ref> Manuscript to be reviewed required to name the colour of the ink of a series of words that spell a name of a different colour.</ns0:p><ns0:p>In the flexibility condition, participants are required to read the spelled word for words outlined by a rectangle and to name the ink colour for the other words. The time required to complete a set of words is recorded <ns0:ref type='bibr' target='#b78'>(Strauss, Sherman, &amp; Spreen, 2006)</ns0:ref>. Finally, the Grooved Pegboard test (Lafayette Model 32025) was selected to evaluate eye-hand coordination and dexterity <ns0:ref type='bibr' target='#b78'>(Strauss et al., 2006)</ns0:ref>. In this task, participants are timed on their speed to place pegs with a key along the side in holes, requiring rotating the peg in order to match the hole before it can be inserted.</ns0:p></ns0:div> <ns0:div><ns0:head>Three-Dimensional Multiple Objects Tracking (3D-MOT)</ns0:head><ns0:p>The 3D-MOT was developed as an optimal training procedure to improve mental abilities critical for processing dynamic scenes, such as those encountered during sports or video gaming <ns0:ref type='bibr' target='#b34'>(Faubert &amp; Sidebottom, 2012)</ns0:ref>. The method relies on particular features such as distributing attention among a number of moving targets with distractors, known in the literature as Multiple Object Tracking <ns0:ref type='bibr' target='#b68'>(Pylyshyn &amp; Storm, 1988)</ns0:ref>, a large visual field, speed thresholds, and stereoscopic vision <ns0:ref type='bibr' target='#b34'>(Faubert &amp; Sidebottom, 2012)</ns0:ref>. The 3D-MOT sessions were conducted in a quiet room using a fully immersive environment with a Fove&#8482; virtual reality device. The headmounted display had a resolution of 2560 x 1440 pixels and covered a maximal visual field of 45 degrees. The 3D-MOT experiment was supported by a Dell Inspiration 15 700 Gaming Series computer.</ns0:p><ns0:p>During the 3D-MOT task (Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>), participants were required to track four of eight spheres that moved within a cube delineated by light grey walls. The spheres moved following linear trajectories in random directions within the cube and changed directions when colliding with PeerJ reviewing <ns0:ref type='table' target='#tab_4'>PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:ref> Manuscript to be reviewed each other or with the walls. A green fixation square was presented in the center of the cube and participants were asked to maintain fixation on the square throughout the tracking phase and to track the targets with their attention only, without eye movements. Each trial begins with the presentation of all eight spheres, colored homogeneously in yellow for two seconds. The four target spheres turn red with a surrounding white halo for two second before returning to their original color and restore homogeneity for one second. After that, all eight spheres move along a linear path. If a sphere comes in contact with another sphere or a wall of the cube, it bounces off and resumes its trajectory. This phase last eight seconds. All eight spheres cease movement and are labeled with number from 1 to 8 allowing the subject to verbally state their responses. The targets are revealed, and feedback is given. This phase last 2 seconds. On each trial, the speed of all the spheres varied according to a 1-up 1-down staircase procedure to estimate the speed required to track all four targets 50% of the time <ns0:ref type='bibr' target='#b57'>(Levitt, 1971)</ns0:ref>. The speed increased by 0.05 log units if the participant accurately identified all the targets and decreased by the same amount if least one target was missed. The staircase was interrupted after 20 trials and the speed threshold was estimated using the geometric mean of the speeds at the last four reversals. Each staircase lasted approximately 8 minutes. </ns0:p></ns0:div> <ns0:div><ns0:head>Analysis</ns0:head><ns0:p>Two participants in the Professional group did not have high proficiency in English or French, so they were not tested on the Digit Span and Colour Word Interference tests, as performance in these tests depends on language proficiency. One of these participants also did not complete the Tower test, due to difficulty with understanding instructions. Data for the 3D-MOT training sessions were available for 27 participants, as three participants in the Amateur group did not complete the five 3D-MOT sessions due to travel restrictions, so their data were excluded from these analyses. In addition, data from 17 out of 405 blocks across seven participants were missing due to a technical error and were treated as missing at random. Manuscript to be reviewed Statistical analyses were performed in SPSS and the statistical computing environment R (R Core <ns0:ref type='bibr'>Team, 2015)</ns0:ref>. Performance on all the neuropsychological measures was compared in the two groups using univariate analyses on each measure separately using independent Welch's ttests, as the variance across the two groups was unequal for some outcome measures (e.g., Spatial Span total score, Levene's test p &lt; 0.01). Hedges' g was calculated to provide a measure of effect size using the effsize package in R <ns0:ref type='bibr' target='#b82'>(Torchiano, 2016)</ns0:ref>. To evaluate global group differences in neuropsychological measures and to compare the contribution of different outcome measures to the group difference, we conducted a descriptive discriminant analysis <ns0:ref type='bibr' target='#b13'>(Brown &amp; Wicker, 2000;</ns0:ref><ns0:ref type='bibr' target='#b72'>Smith, Lamb, &amp; Henson, 2020)</ns0:ref>. Additionally, bivariate Spearman's correlations were calculated to examine associations among neuropsychological outcome measures.</ns0:p><ns0:p>To examine the effects of learning on speed thresholds in both groups, we conducted a linear mixed effects analysis using the lme4, pbkrtest, and lmerTest packages in R <ns0:ref type='bibr' target='#b2'>(Baayen, Davidson, &amp; Bates, 2008;</ns0:ref><ns0:ref type='bibr'>Bates et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b53'>Kuznetsova, Brockhoff, &amp; Christensen, 2014;</ns0:ref><ns0:ref type='bibr' target='#b59'>Luke, 2017;</ns0:ref><ns0:ref type='bibr' target='#b80'>Team, 2018)</ns0:ref>. The model's outcome variable was the speed threshold, with fixed effects of group, the logarithm of the block number, and their interaction. As random effects, we fit a maximal random effects structure that included by-subject intercepts and by-subject slopes for block (lmer(speed ~ Group * log2(block) + (1+log2(block) | subject)). This analysis is equivalent to fitting a logarithmic learning curve separately for each participant and comparing the effect of group on overall speed thresholds and on the learning rate. P-values for fixed effects were obtained using F-tests with the Kenward -Roger approximation for degrees of freedom <ns0:ref type='bibr' target='#b44'>(Halekoh &amp; H&#248;jsgaard, 2014)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Table <ns0:ref type='table'>1</ns0:ref> summarises the demographic information and video game experience of participants in the groups. The two groups were well matched in age (Professionals: M = 23.66, SD = 2.44, Amateurs: M = 25.31, SD = 3.77, t(25.9) = -1.44, p = 0.16) and in the average age at which participants started playing video games (Professionals: M = 6.93, SD = 2.81, Amateurs: M = 6.75, SD = 2.62, t(26.8) = 0.18, p = 0.86). Participants in the Professional group devoted significantly more time to FPS games than those in the Amateur group in the last six months (Professionals: M = 55.79 h, SD = 16.72, Amateurs: M = 9.47 h, SD = 3.48, t(14) = 10.18, p &lt;0.001). There was no evidence for any differences in the level of depression symptoms in the two groups (Professionals: M = 6.85, SD = 5.27, Amateurs: M = 4.93, SD = 4.62, t(24.1) = 1.01, p = 0.32).</ns0:p></ns0:div> <ns0:div><ns0:head>Neuropsychological assessments</ns0:head><ns0:p>Figure <ns0:ref type='figure' target='#fig_2'>2</ns0:ref> shows the outcome measures from the eight neuropsychological tests for the two groups and Table <ns0:ref type='table' target='#tab_1'>3</ns0:ref> presents their summary statistics and the results of univariate, between group comparisons for each measure. In the d2 Test of Attention, Professional players processed, on average, a greater number of stimuli than those in the Amateur group (TN: t(28) = 2.41, p = 0.02, g = 0.85), while maintaining a similar error rate (E%: t(27.3) = 0.70, p = 0.49, g = 0.25). When accounting for the error rate, Professional players processed a greater number of stimuli correctly (TN-E: t(28) = 2.3; p = 0.03; g = 0.81), but their Concentration Performance score did not differ significantly from the Amateur group (CP: t(26.4) 1.31; p = 0.20 ; g = 0.47). The Fluctuation Rate, which measures the consistency of performance throughout the task, was lower in the Professional group (FR: t(28)= -2,14 ; p = 0.04 ; g = -0.75), indicating better sustained attention.</ns0:p><ns0:p>In the WAIS-IV Spatial Span task, the Professional group showed better performance than the Amateurs on the Total score (t(25.5) = 3.52, p &lt; 0.001, g = 1.27), with a large effect size.</ns0:p><ns0:p>Analyzing each subscale separately revealed a large, reliable effect in the Forward subscale, (t(28) = 3.85 ; p = 0.001, g = 1.36), but no reliable difference in the Backward subscale (t(24.4) = 1.92, p = 0.07, g = 0.7). In the auditory working memory task, Digit Span, the Professional group also showed higher performance on the Total score (t(23) = 2.20; p = 0.04, g = 0.82), with a smaller effect size than in the Spatial Span test. Scores for the Digit Span Forward, Backward, and Sequencing subscales were not reliably different in the two groups (p= 0.06, 0.11, 0.13, respectively).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>In the Coding test, the average score in the Professional group was slightly higher than for the Amateurs, but this group difference was not reliable (t(26) = 1.54, p = 0.14, g= 0.55). There was no evidence for a difference in performance between the two groups on tests of executive function, D-KEFS Towers (ps &gt; 0.08), and D-KEFS Colour-Word Interference (ps &gt; 0.36), nor on the Visual Puzzles test (ps = 0.44), that evaluates perceptual reasoning. There was also no evidence for any group difference in the Grooved Pegboard test (ps &gt; 0.17), which evaluates eyehand coordination and manual dexterity.</ns0:p><ns0:p>To evaluate whether the two groups showed a global difference across all the tasks, we conducted a descriptive discriminant analysis (DDA; <ns0:ref type='bibr' target='#b72'>Smith et al., 2020)</ns0:ref> on a subset of outcome measures comprising of one measure per task, to ward against the issue of multicollinearity. The outcome measures included were d2 TN-E, Spatial Span Total, Digit Span Total, Grooved Peg for the dominant hand, Color-Word Inhibition score, and total scores for Coding, Visual Puzzles, Towers, and Coding. The largest bivariate correlation across these measures was -0.55, indicating that the variables were not multicollinear. The DDA analysis calculates a linear composite of the outcome variables that best separates the two groups. The canonical correlation, R c , between the composite and Group was 0.67, with a corresponding R c 2 = 0.45, which is the variance accounted for Group in the composite scores. This difference was not statistically significant, Wilk's = 0.54, F(8, 19) = 1.97, p = 0.11. Examining the standardized discriminant &#923; function coefficients revealed that Spatial Span Total score made the largest contribution to the composite score with a coefficient of -0.29 and an r 2 = 0.62. Table <ns0:ref type='table' target='#tab_4'>4</ns0:ref> provides the full results of this analysis.</ns0:p></ns0:div> <ns0:div><ns0:head>3D-MOT training</ns0:head><ns0:p>Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref> shows the average speed thresholds for tracking four targets in the 3D-MOT task as a function of block number for each group. As can be seen, the Professional group showed higher thresholds than the Amateur group overall, indicating better ability to track multiple targets among distractors. Thresholds in both groups increased as a function of block number, reflecting improvements in task performance as a function of training, with a similar rate of improvement in both groups. These observations were confirmed by a linear mixed effects analysis (see Table <ns0:ref type='table'>5</ns0:ref>), which revealed a main effect of Group, F(1, 24.78) = 5.54, p = 0.03, with the Professional group having higher thresholds, = 0.28, 95%CI [0.05, 0.52]. There was also a main effect of &#120573; block, F(1, 24.78) = 76.97, p &lt;0.001, with thresholds increasing by = 0.14, 95%CI [0.09, 0.20] &#120573; for every doubling of the block number. The interaction between group and log2(block) was not statistically significant, F(1, 24.78) = 1.23, p = 0.28, providing no evidence for any difference in learning rate across the two groups. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Association between Attention, Working Memory, and Short-term memory</ns0:head><ns0:p>Previous studies have indicated that visual working memory (WM) and selective attention are related both on a behavioral and neuroanatomical level <ns0:ref type='bibr' target='#b0'>(Awh &amp; Jonides, 2001;</ns0:ref><ns0:ref type='bibr' target='#b38'>Gazzaley &amp; Nobre, 2012)</ns0:ref>. Selective attention is known to be central to effectively filtering irrelevant information in the encoding phase <ns0:ref type='bibr' target='#b86'>(Vogel, McCollough, &amp; Machizawa, 2005)</ns0:ref>. Because working memory has a very limited capacity, attention is required to appropriately select the relevant information to encode in WM to avoid unnecessary clutter <ns0:ref type='bibr' target='#b60'>(Ma, Husain, &amp; Bays, 2014;</ns0:ref><ns0:ref type='bibr' target='#b63'>Myers, Stokes, &amp; Nobre, 2017)</ns0:ref>. Selective attention may also be involved in maintaining information activated in WM <ns0:ref type='bibr' target='#b0'>(Awh &amp; Jonides, 2001;</ns0:ref><ns0:ref type='bibr' target='#b1'>Awh, Vogel, &amp; Oh, 2006)</ns0:ref>. Many studies also report an association between WM and STM <ns0:ref type='bibr' target='#b22'>(Conway, Cowan, Bunting, Therriault, &amp; Minkoff, 2002;</ns0:ref><ns0:ref type='bibr' target='#b30'>Engle, Tuholski, Laughlin, &amp; Conway, 1999;</ns0:ref><ns0:ref type='bibr' target='#b50'>Kail &amp; Hall, 2001)</ns0:ref>, as STM is often theorized as a subcomponent of WM <ns0:ref type='bibr' target='#b23'>(Cowan, 1998;</ns0:ref><ns0:ref type='bibr' target='#b30'>Engle et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b50'>Kail &amp; Hall, 2001)</ns0:ref>.</ns0:p><ns0:p>Figure <ns0:ref type='figure'>4</ns0:ref> shows the results of bivariate Spearman's correlations among attention and processing speed outcome measures (d2 Test of Attention TN-E, WAIS-IV Coding, and average of the 3D</ns0:p><ns0:p>MOT speed thresholds from the first session) and auditory and visual WM and STM outcome measures (Spatial Span Forward and Backward subscales, Digit Span Forward, Backward, and Sequencing subscales). We only examined correlations for both groups together, as the sample sizes in each group were not sufficient to provide stable correlation estimates <ns0:ref type='bibr' target='#b71'>(Sch&#246;nbrodt &amp; Perugini, 2013)</ns0:ref>. As can be seen, d2 TN-E scores were correlated with Spatial Span Backward subscale (r s = 0.50, p = 0.01), as well as the WAIS-IV Coding (r s = 0.45, p = 0.01), but not with Spatial Span Forward (r s = 0.21, p = 0.26). Thus, our measure of selective attention correlated</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed with measures of vWM and processing speed, but not with vSTM. The d2 TN-E score also correlated with the Digit Span Sequencing subscale (r s = 0.51, p = 0.01), but not the Forward or Backward subscales. The Spatial Span Forward and Backward subscales were moderately correlated with each other (r s = 0.43, p = 0.02). Performance on the 3D-MOT task showed a strong correlation with the Spatial Stan Forward (r s = 0.68, p &lt; 0.001) and Backward (r s = 0.69, p &lt; 0.001) subscales, indicating that these two tasks require similar cognitive capacities. Finally, the Spatial Span Forward was the only variable that correlated with the average weekly hours of video game play (r s = 0.45, p = 0.12). This result may be another reflection of the group difference in performance on that task.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>To gain a better understanding of the cognitive determinants of expertise in action video games, the current study compared the performance of professional action video gamers with that of a group of individuals who play similar FPS video games non-competitively on a set of eight neuropsychological tests and on their ability to improve performance on a multiple object tracking task. The results revealed that the professional video game players showed better performance on the 3D-MOT task, Spatial Span Forward subscale, Digit Span Forward subscale and d2 Test of Attention compared to experienced video game players who are not highperformers. These results indicate that high performance in FPS video games is associated with enhanced abilities in visual spatial attention, visual and auditory short-term memory, and selective and sustained attention. There was no evidence for any group differences in performance on tasks evaluating executive functions, perceptual manipulation, or manual dexterity. Furthermore, both groups showed similar capacity to improve performance in the 3D-PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed MOT task with training. Given the cross-sectional, observational nature of this group comparison, this study cannot speak to the causality of the differences in cognitive performance and video game expertise. The presence of group differences may either indicate that certain cognitive abilities are conducive to achieving high performance in FPS games, or that the greater amount of experience with FPS games in the professional group lead to improved performance in the above-mentioned abilities.</ns0:p><ns0:p>The results from the d2 Test of Attention indicated that Professional players are better than Amateurs in selective and sustained attention. This result is consistent with previous studies that reported attentional benefits following practice with action video games <ns0:ref type='bibr' target='#b8'>(Belchior et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b40'>Green &amp; Bavelier, 2003;</ns0:ref><ns0:ref type='bibr'>Green &amp; Bavelier, 2006;</ns0:ref><ns0:ref type='bibr' target='#b73'>Spence et al., 2009)</ns0:ref> and results of the metaanalysis that found strong evidence for a robust effect of action video games on attention using similar tasks <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018)</ns0:ref>. Some authors have raised the possibility that AVG players show higher performance in attention tasks because they employ a more optimal search strategy <ns0:ref type='bibr' target='#b19'>(Clark, Fleck, &amp; Mitroff, 2011)</ns0:ref>. In the d2 test, participants were told to search line by line without the possibility to go back, limiting the possibility of employing different search strategies. Furthermore, even if Professional players were able to analyze more stimuli than Amateurs, they maintained the same accuracy rate, suggesting no apparent trade-offs. These results suggest that Professional players display an enhancement in visual selective attention when compared to Amateurs. Furthermore, the performance of Professional players was more stable than Amateur's in terms of items processed per line, suggesting better capacities in sustained attention. Sustained attention is an important ability in the context of professional videogaming, where players often need to train for many hours consecutively. While previous research has demonstrated an advantage of AVG players compared to non-players on attention <ns0:ref type='bibr' target='#b15'>(Castel et al., 2005;</ns0:ref><ns0:ref type='bibr'>Green &amp; Bavelier, 2006)</ns0:ref>, the current results indicate that selective and sustained attention are further enhanced in elite video game experts. Thus, taken together, those results suggest that attention capacities could be influenced by AVG.</ns0:p><ns0:p>Previous studies have reported that experience with AVG is related to better vSTM capacities which were assessed using change detection task with simple and complex stimuli <ns0:ref type='bibr' target='#b9'>(Blacker &amp; Curby, 2013;</ns0:ref><ns0:ref type='bibr' target='#b91'>Wilms, Petersen, &amp; Vangkilde, 2013)</ns0:ref>. In the present study, vSTM was indexed using the Spatial Span Forward subscale, and performance in this subtask showed the greatest difference between the two groups. Previous researchers have proposed that benefits on vSTM could be linked to the enhancement of visual selective attention <ns0:ref type='bibr' target='#b6'>(Bavelier, Green, Pouget, &amp; Schrater, 2012)</ns0:ref>. They inferred that advantages in vSTM may be related to a greater ability to select task-relevant information and ignore task-irrelevant information. In the context of our study, the bivariate correlation showed no significant relationship between attention and vSTM, suggesting that the benefits in vSTM are not due to better selective attention abilities.</ns0:p><ns0:p>Because of the visual nature of video games, past studies were mainly focused on the visual aspect of cognition, with only a few studies examining auditory or multisensory task performance. Those studies have observed a gain that extended beyond visual capacities and impacted multisensory processing in healthy adults <ns0:ref type='bibr' target='#b26'>(Donohue, Woldorff, &amp; Mitroff, 2010)</ns0:ref> and auditory capacities in dyslexic children as they showed enhancement in phonological short-term memory after AVG training <ns0:ref type='bibr' target='#b36'>(Franceschini &amp; Bertoni, 2019;</ns0:ref><ns0:ref type='bibr' target='#b37'>Franceschini et al., 2013)</ns0:ref>. In this</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed study, Professionals did not differ from Amateurs on Digit Span Forward subscale, suggesting that aSTM is not a characteristic of video game expertise.</ns0:p><ns0:p>The present study suggests a link between the level of video gaming expertise and the ability to perform an abstract dynamic task. The 3D-MOT task strongly engages several attention and mental skills; performing this task well requires selective, dynamic, distributed and sustained attention skills <ns0:ref type='bibr' target='#b56'>(Allard &amp; Faubert, 2013)</ns0:ref>. Professional video game players showed better performances than Amateurs on the 3D-MOT task across the 5 training sessions, suggesting that video game expertise is also related to perceptive-cognitive ability. This is consistent with the idea that Professionals players have to be efficient at extracting meaningful information from a visual scene in order to anticipate and make decisions to be high performing in the game. The results on 3D-MOT task are consistent with the enhancement of motion perception highlighted by other studies using the multiple objects tracking task or dots motion task <ns0:ref type='bibr' target='#b11'>(Boot, Kramer, Simons, Fabiani, &amp; Gratton, 2008;</ns0:ref><ns0:ref type='bibr'>Green &amp; Bavelier, 2006;</ns0:ref><ns0:ref type='bibr' target='#b47'>Hutchinson &amp; Stocks, 2013)</ns0:ref>. This result also contributes to growing evidence pointing to a specific influence of action video games on the dorsal pathway <ns0:ref type='bibr' target='#b17'>(Chopin, Bediou, &amp; Bavelier, 2019)</ns0:ref>. The dorsal pathway is a network that is involved in spatial working memory and specializes in capturing dynamic spatial and temporal relationship between multiple items <ns0:ref type='bibr' target='#b52'>(Kravitz, Saleem, Baker, Ungerleider, &amp; Mishkin, 2013)</ns0:ref>, and is engaged during multiple object tracking tasks <ns0:ref type='bibr' target='#b10'>(Blumberg, Peterson, &amp; Parasuraman, 2015;</ns0:ref><ns0:ref type='bibr' target='#b46'>Howe, Horowitz, Morocz, Wolfe, &amp; Livingstone, 2009)</ns0:ref>. It is often referred to as the 'where/how' pathway as it is involved in the localization and guides motor action <ns0:ref type='bibr' target='#b17'>(Chopin et al., 2019)</ns0:ref>. However, in contrast to professional sports athletes who showed enhanced abilities to improve their 3D-MOT performance with training, relative to amateur athletes athletes <ns0:ref type='bibr' target='#b33'>(Faubert, 2013)</ns0:ref>, the professional and casual video game players in the current study showed similar learning rates across the five sessions.</ns0:p><ns0:p>While the effect in the multiple object tracking task may indicate differences in the dorsal pathway, which is also involved in action planning, there were no group differences in manual dexterity or visuomotor coordination as evaluated by the Grooved Pegboard task. Previous studies have found that players have better hand-eye coordination compared to non-players, but this benefit was not associated with the amount of time spent engaging in the games <ns0:ref type='bibr' target='#b43'>(Griffith, Voloschin, Gibb, &amp; Bailey, 1983)</ns0:ref>. Action video games were also shown to improve visuomotor control in an intervention study <ns0:ref type='bibr' target='#b58'>(Li, Chen, &amp; Chen, 2016)</ns0:ref>. Together with the current findings, it suggests that the benefits of action video games on motor dexterity and visuomotor coordination are limited in that extended practice does not lead to larger benefits.</ns0:p><ns0:p>The current results also do not provide evidence for any differences in working memory associated with professional gaming, as the average performance on the Backward subscales of the Spatial Span and Digit Span tasks did not differ between groups. As mentioned earlier, previous studies have emphasized that WM, which involves maintaining elements active and quickly accessible, is intricately linked with the concept of selective attention, both on a behavioral and anatomical level <ns0:ref type='bibr' target='#b0'>(Awh &amp; Jonides, 2001;</ns0:ref><ns0:ref type='bibr' target='#b29'>Engle, 2002;</ns0:ref><ns0:ref type='bibr' target='#b45'>Hitch, Hu, Allen, &amp; Baddeley, 2018)</ns0:ref>. Supporting this overlap between the two constructs, we observed positive associations between outcome measures of vWM, selective attention, and vSTM. Nevertheless, while there was some evidence for enhanced selective attention in professional players,</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed performance in tasks relying on auditory or visual working memory was similar in the two groups.</ns0:p><ns0:p>The present results also did not provide evidence for any differences in executive functions between Professional players and Amateurs, as measured by the inhibition and flexibility subscales of the Stroop task. Mental flexibility has been cited as one of the strongest enhancements in real time strategy games <ns0:ref type='bibr' target='#b3'>(Basak, Boot, Voss, &amp; Kramer, 2008)</ns0:ref>. For AVG, the meta-analysis conducted by Bedou (2017) suggested a medium size effect for flexibility, and only a weak effect for inhibition. Given that the current study only had high power to detect large effects, our findings are consistent with previous results. There was also no evidence of any group differences in visual planning skills or visual reasoning. These results are consistent with the results of <ns0:ref type='bibr'>Boot and colleagues (2008)</ns0:ref>, who showed no association between video game practice and planification skills using the Tower of London task <ns0:ref type='bibr' target='#b84'>(Tunstall, 1999)</ns0:ref>.</ns0:p><ns0:p>Previous studies have found that video game players are faster than non-video game players in reaction time tasks <ns0:ref type='bibr' target='#b15'>(Castel et al., 2005;</ns0:ref><ns0:ref type='bibr'>Dye et al., 2009)</ns0:ref>. In this study, there was no reliable difference in performance in the main visual processing speed task (WAIS-IV Coding), nor in the Grooved Peg task, which relied on rapid manual dexterity and eye-hand coordination. That said, the TN measure of the d2 Test of Attention showed that Professional players processed a greater number of stimuli in a given time than Amateurs, suggesting that video game expertise is related to a better ability to discriminate simple visual information. The different results provided by those d2 and Coding tests addresses a question raised by <ns0:ref type='bibr'>Dye, Green and Bavelier (2009)</ns0:ref> regarding the generalization of the advantage of gamers in processing speed to tasks with more</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed than two behavioral alternatives. The Codes task requires quickly coding different units using the correct symbol one out of a total of nine possible codes. It has been argued that, in addition to speed of processing, good performance in this task requires attention, motor speed, visuoperceptual abilities, and dexterity to write the appropriate symbols <ns0:ref type='bibr' target='#b49'>(Jaeger, 2018)</ns0:ref>. In contrast, the d2 test requires participants to choose one of two options: to mark or not to mark the symbol.</ns0:p><ns0:p>The two-choice response in the d2 test is closer to that used in the literature demonstrating the benefits of video gaming on the speed of processing (Matthew WG <ns0:ref type='bibr'>Dye et al., 2009)</ns0:ref>. The current findings may suggest that video game expertise is related to a better ability to discriminate simple visual information rather than a global benefit on processing speed in a more complex task.</ns0:p><ns0:p>By better understanding Professional videogaming, we can provide clues about how this expertise and these performances best develops and learn how to support it <ns0:ref type='bibr' target='#b32'>(Farrington-Darby &amp; Wilson, 2006)</ns0:ref>. In order to study video game expertise, it is crucial to define it appropriately. By using time gaming criterion, studies may have failed to appreciate the difference between video game players who have played 5 hours per week for the last 6 months and those who have played more than 20 hours per week for the last 10 years. Moreover, the assumption that recent video gaming experience reflect expertise could be mistaken <ns0:ref type='bibr' target='#b55'>(Latham et al., 2013)</ns0:ref>. Failure to consider expertise in terms of performance may explain some of the mixed results in the literature. By applying the same criterion of performances to video gaming research, differences between professional and amateur players allowed us to determine the factors that potentially underlie high-level performance, such as attention, STM and perceptive-cognitive ability.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The current study has serval limitations. First, due to our limited sample size, the current study had low power to detect small or medium effects (with alpha = 0.05, power = 0.80). Thus, we should remain careful in our interpretation of null results, as differences might exist but failed to be detected. Furthermore, the gender of the study participants may have acted as a confounding variable, since our Professional players group was composed only of men and our Amateur had 4 women, although women's results did not differ from those obtained by men in the same group.</ns0:p><ns0:p>Finally, the experimenter who administered the measures was not blind to the participant group, which may have introduced some bias.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In summary, this study was the first to examine the cognitive basis of elite performance in action video game players. Our results revealed that elite players show the greatest performance advantage in tests of visual spatial short-term memory and visual attention. Furthermore, professional action video gamers showed a better ability to track multiple objects within a complex and dynamic scene than amateur players, but both groups showed similar rates of improvement in the task with training. Future research is needed to clarify whether the observed differences in cognitive abilities emerge as a result of intense practice in action video games, or whether certain cognitive profiles are beneficial for achieving high-level performance in video gaming. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 |</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1 | Five stages of a trial in the 3D-MOT task. a) Presentation phase, in which eight</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 |</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 | Results of neuropsychological tests. Large symbols show the mean group score and</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 |</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3 | 3D-MOT task training data: Average speed thresholds for the Professional (red</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 1 Five</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 3 3D-</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>Means and standard deviations (SD) of the raw scores of neuropsychological tests for Professional and Amateur video gamer participants. a, b.: n = 12, 13 in the Professional group. WAIS = Weschler Adult Intelligence Scale (IV), WMS = Weschler Memory Scale (III), TN = total number of items processed, TN-E = total number of items processed minus the errors, E% = percentage of errors, CP = concentration performance, FR = fluctuation rate (difference between the line with the minimum and maximum number of items processed). DH = Dominant hand, NDH = Non-dominant hand. Bolded p-values are &lt; an alpha level of 0.05 (uncorrected). PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>4</ns0:head><ns0:label /><ns0:figDesc>participants. a, b.: n = 12, 13 in the Professional group. WAIS = Weschler Adult Intelligence Scale (IV), WMS = Weschler Memory 5 Scale (III), TN = total number of items processed, TN-E = total number of items processed minus the errors, E% = percentage of errors, 6 CP = concentration performance, FR = fluctuation rate (difference between the line with the minimum and maximum number of items 7 processed). DH = Dominant hand, NDH = Non-dominant hand. Bolded p-values are &lt; an alpha level of 0.05 (uncorrected).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>Results of the linear mixed effects model fit to speed thresholds in the 3D-MOT task. The proportion of the variance explained by fixed and random factors, conditional R 2 , is 0.68; the proportion of the variance explained by the fixed factors alone, marginal R 2 , is 0.29. PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='39,42.52,178.87,525.00,458.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 2 -Demographic and video game experience information for the two groups</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell cols='2'>Professionals (n=14) Amateurs (n=16)</ns0:cell><ns0:cell>Group comparison</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>M (SD)</ns0:cell><ns0:cell>M (SD)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Age (years)</ns0:cell><ns0:cell>23.66 (2.44)</ns0:cell><ns0:cell>25.31(3.77)</ns0:cell><ns0:cell>t(25.9) = -1.44, p = 0.16</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Gender ratio (male : female) 14:0</ns0:cell><ns0:cell>12:4</ns0:cell><ns0:cell>N / A</ns0:cell></ns0:row><ns0:row><ns0:cell>BDI-II score</ns0:cell><ns0:cell>6.85 (5.27)</ns0:cell><ns0:cell>4.93 (4.62)</ns0:cell><ns0:cell>t(24.1) = 1.01, p = 0.32</ns0:cell></ns0:row><ns0:row><ns0:cell>Age started playing video</ns0:cell><ns0:cell>6.93 (2.81)</ns0:cell><ns0:cell>6.75 (2.62)</ns0:cell><ns0:cell>t(26.8) = 0.18, p = 0.86</ns0:cell></ns0:row><ns0:row><ns0:cell>games (years)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Average FPS gaming per</ns0:cell><ns0:cell>55.79 (16.72)</ns0:cell><ns0:cell>9.47 (3.48)</ns0:cell><ns0:cell>t(14) = 10.18, p = 0.00</ns0:cell></ns0:row><ns0:row><ns0:cell>week in past six months (h)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Most frequent game</ns0:cell><ns0:cell>Overwatch (14)</ns0:cell><ns0:cell>Counter Strike (7),</ns0:cell><ns0:cell>N / A</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Call of Duty (3),</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Overwatch (3),</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Rainbow 6 (1), Player</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Unknown's</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Battlegrounds (1),</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Battlefield 4 (1),</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>BDI-II: Beck depression inventory (II) score, FPS: first person shooter</ns0:cell><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Average raw scores for all neuropsychological tests, difference scores, and univariate inferential statistics.</ns0:figDesc><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 -Average raw scores for all neuropsychological tests, difference scores, and univariate inferential 2</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Means and standard deviations (SD) of the raw scores of neuropsychological tests for Professional and Amateur video gamer</ns0:figDesc><ns0:table><ns0:row><ns0:cell>statistics.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Measure</ns0:cell><ns0:cell>Professionals</ns0:cell><ns0:cell>Amateurs</ns0:cell><ns0:cell cols='2'>Difference</ns0:cell><ns0:cell>Welch t-test</ns0:cell><ns0:cell>p</ns0:cell><ns0:cell>Effect size</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>(n=14)</ns0:cell><ns0:cell>(n=16)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Hedges' g</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>M (SD)</ns0:cell><ns0:cell>M (SD)</ns0:cell><ns0:cell>&#8710;</ns0:cell><ns0:cell>[95% CI]</ns0:cell><ns0:cell>t(df)</ns0:cell><ns0:cell /><ns0:cell>g [95%CI]</ns0:cell></ns0:row><ns0:row><ns0:cell>D2 Test of</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Attention</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>-TN</ns0:cell><ns0:cell>546.29 (56.14)</ns0:cell><ns0:cell cols='4'>493.56 (63.49) 52.73 [7.98, 97.47] t(28) = 2.41</ns0:cell><ns0:cell>0.02</ns0:cell><ns0:cell>0.85 [0.09, 1.61]</ns0:cell></ns0:row><ns0:row><ns0:cell>-E%</ns0:cell><ns0:cell>4.41 (2.98)</ns0:cell><ns0:cell>3.66 (2.91)</ns0:cell><ns0:cell cols='2'>0.75 [-1.46, 2.96]</ns0:cell><ns0:cell>t(27.3) = 0.7</ns0:cell><ns0:cell>0.49</ns0:cell><ns0:cell>0.25 [-0.48, 0.98]</ns0:cell></ns0:row><ns0:row><ns0:cell>-TN-E</ns0:cell><ns0:cell>521.86 (52.48)</ns0:cell><ns0:cell cols='4'>474.94 (59.31) 46.92 [5.11, 88.73] t(28) = 2.3</ns0:cell><ns0:cell>0.03</ns0:cell><ns0:cell>0.81 [0.05, 1.57]</ns0:cell></ns0:row><ns0:row><ns0:cell>-CP</ns0:cell><ns0:cell>208.79 (31.62)</ns0:cell><ns0:cell cols='4'>194.38 (28.41) 14.41 [-8.26, 37.08] t(26.4) = 1.31</ns0:cell><ns0:cell>0.20</ns0:cell><ns0:cell>0.47 [-0.27, 1.21]</ns0:cell></ns0:row><ns0:row><ns0:cell>-FR</ns0:cell><ns0:cell>11 (3.21)</ns0:cell><ns0:cell>13.75 (3.84)</ns0:cell><ns0:cell cols='3'>-2.75 [-5.39, -0.11] t(28) = -2.14</ns0:cell><ns0:cell>0.04</ns0:cell><ns0:cell>-0.75 [-1.51 ,0]</ns0:cell></ns0:row><ns0:row><ns0:cell>WAIS-IV</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Coding</ns0:cell><ns0:cell>77.5 (12.25)</ns0:cell><ns0:cell>71.0 (10.61)</ns0:cell><ns0:cell cols='2'>6.5 [-2.16, 15.16]</ns0:cell><ns0:cell>t(26) = 1.54</ns0:cell><ns0:cell>0.14</ns0:cell><ns0:cell>0.55 [-0.19, 1.3]</ns0:cell></ns0:row><ns0:row><ns0:cell>WMS-III</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Spatial Span</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>-Total</ns0:cell><ns0:cell>23 (2.94)</ns0:cell><ns0:cell>19.5 (2.45)</ns0:cell><ns0:cell cols='2'>3.5 [1.45, 5.55]</ns0:cell><ns0:cell>t(25.5) = 3.52</ns0:cell><ns0:cell>0.002</ns0:cell><ns0:cell>1.27 [0.47, 2.07]</ns0:cell></ns0:row><ns0:row><ns0:cell>-Forward</ns0:cell><ns0:cell>12.43 (1.5)</ns0:cell><ns0:cell>10.19 (1.68)</ns0:cell><ns0:cell cols='2'>2.24 [1.05, 3.43]</ns0:cell><ns0:cell>t(28) = 3.85</ns0:cell><ns0:cell>0.001</ns0:cell><ns0:cell>1.36 [0.55, 2.17]</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>-Backward 10.57 (1.99)</ns0:cell><ns0:cell>9.31 (1.54)</ns0:cell><ns0:cell cols='2'>1.26 [-0.09, 2.61]</ns0:cell><ns0:cell>t(24.4) = 1.92</ns0:cell><ns0:cell>0.07</ns0:cell><ns0:cell>0.7 [-0.06, 1.45]</ns0:cell></ns0:row><ns0:row><ns0:cell>WAIS-IV Digit</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Span WAIS-IV</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Visual Puzzles</ns0:cell><ns0:cell>18.5 (3.88)</ns0:cell><ns0:cell>19.5 (3.01)</ns0:cell><ns0:cell cols='2'>-1.00 [-3.64, 1.64]</ns0:cell><ns0:cell cols='2'>t(24.4) = -0.78 0.44</ns0:cell><ns0:cell>-0.28 [-1.02, 0.45]</ns0:cell></ns0:row><ns0:row><ns0:cell>D-KEFS</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Towers b</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>-Total</ns0:cell><ns0:cell>20.15 (4.32)</ns0:cell><ns0:cell>18.44 (4.32)</ns0:cell><ns0:cell cols='2'>1.71 [-1.6, 5.03]</ns0:cell><ns0:cell>t(25.8) = 1.06</ns0:cell><ns0:cell>0.30</ns0:cell><ns0:cell>0.39 [-0.37, 1.14]</ns0:cell></ns0:row><ns0:row><ns0:cell>-Accuracy</ns0:cell><ns0:cell>1.49 (0.29)</ns0:cell><ns0:cell>2 (1.04)</ns0:cell><ns0:cell cols='2'>-0.51 [-1.08, 0.06]</ns0:cell><ns0:cell cols='2'>t(17.9) = -1.86 0.08</ns0:cell><ns0:cell>-0.62 [-1.38, 0.15]</ns0:cell></ns0:row><ns0:row><ns0:cell>Ratio</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>D-KEFS Color-</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Word</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='2'>-Inhibition 43.67 (5.58)</ns0:cell><ns0:cell>45.94 (7.35)</ns0:cell><ns0:cell cols='2'>-2.27 [-7.3, 2.75]</ns0:cell><ns0:cell>t(26) = -0.93</ns0:cell><ns0:cell>0.36</ns0:cell><ns0:cell>-0.33 [-1.1, 0.44]</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>-Flexibility 51.42 (6.97)</ns0:cell><ns0:cell>52.25 (5.7)</ns0:cell><ns0:cell cols='2'>-0.83 [-5.96, 4.3]</ns0:cell><ns0:cell cols='2'>t(20.9) = -0.34 0.74</ns0:cell><ns0:cell>-0.13 [-0.89, 0.63]</ns0:cell></ns0:row><ns0:row><ns0:cell>Grooved</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Pegboard</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>-DH</ns0:cell><ns0:cell>69.73 (11.26)</ns0:cell><ns0:cell>64.1 (10.68)</ns0:cell><ns0:cell cols='2'>5.63 [-2.62, 13.89]</ns0:cell><ns0:cell>t(27) = 1.4</ns0:cell><ns0:cell>0.17</ns0:cell><ns0:cell>0.5 [-0.24, 1.24]</ns0:cell></ns0:row><ns0:row><ns0:cell>-NDH</ns0:cell><ns0:cell>71.58 (13.95)</ns0:cell><ns0:cell>66.12 (9.65)</ns0:cell><ns0:cell cols='2'>5.46 [-3.73, 14.66]</ns0:cell><ns0:cell>t(22.7) = 1.23</ns0:cell><ns0:cell>0.23</ns0:cell><ns0:cell>0.45 [-0.29, 1.19]</ns0:cell></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>a -Total 32.75 (5.5) 28.25 (5.17) 4.5 [0.27, 8.73] t(23) = 2.2 0.04 0.82 [0.03, 1.62] -Forward 11.67 (2.46) 9.75 (2.52) 1.92 [-0.04, 3.88] t(24.1) = 2.02 0.06 0.75 [-0.04, 1.53] -Backward 10.25 (2.7) 8.69 (2.09) 1.56 [-0.39, 3.52] t(20.1) = 1.67 0.11 0.64 [-0.14, 1.42] -Sequencing 10.83 (1.8) 9.81 (1.56) 1.02 [-0.33, 2.37] t(21.8) = 1.57 0.13 0.6 [-0.18, 1.37]</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 4 : Results of the linear mixed effects model fit to speed thresholds in the 3D-MOT task.</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>The proportion of the variance explained by fixed and random factors, conditional R 2 , is 0.68; the proportion of the variance explained by the fixed factors alone, marginal R 2 , is 0.29.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Fixed Effect</ns0:cell><ns0:cell>&#120631;</ns0:cell><ns0:cell>95%CI</ns0:cell><ns0:cell>t(df)</ns0:cell><ns0:cell>p</ns0:cell><ns0:cell>Random effect</ns0:cell><ns0:cell>St. Dev.</ns0:cell><ns0:cell>Corr</ns0:cell></ns0:row><ns0:row><ns0:cell>Intercept</ns0:cell><ns0:cell>0.59</ns0:cell><ns0:cell>[0.42, 0.76]</ns0:cell><ns0:cell>t(25.8) = 6.72</ns0:cell><ns0:cell cols='2'>&lt;0.001 Subj Intercept</ns0:cell><ns0:cell>0.24</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Group</ns0:cell><ns0:cell>0.28</ns0:cell><ns0:cell>[0.05, 0.52]</ns0:cell><ns0:cell>t(24.8) = 2.35</ns0:cell><ns0:cell>0.03</ns0:cell><ns0:cell>Subj log2(block)</ns0:cell><ns0:cell>0.10</ns0:cell><ns0:cell>0.06</ns0:cell></ns0:row><ns0:row><ns0:cell>log2(block)</ns0:cell><ns0:cell>0.15</ns0:cell><ns0:cell>[0.13, 0.29]</ns0:cell><ns0:cell>t(26.1) = 5.21</ns0:cell><ns0:cell cols='2'>&lt;0.001 Residual</ns0:cell><ns0:cell>0.28</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Group : log2(block)</ns0:cell><ns0:cell>0.06</ns0:cell><ns0:cell>[-0.05, 0.17]</ns0:cell><ns0:cell>t(24.8) = 1.10</ns0:cell><ns0:cell>0.28</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:01:44849:1:1:CHECK 8 Jun 2020)</ns0:note> </ns0:body> "

" Julie Justine Benoit Faubert Lab Université de Montréal (École d'optométrie) 3744, rue Jean-Brillant Bureau 260-01 Montréal, Québec H3T 1P1 Canada May 21th, 2020 Dear Editorial board, I would like to resubmit our manuscript entitled ' The neuropsychological profile of professional action video game players' for consideration for publication in PeerJ. This is a revised version of the manuscript that we had submitted to your board in February 2020, entitled “Neuropsychological profiling of videogame expertise” (#44849). Following the helpful comments of the reviewers, we have substantially revised our manuscript to include a multivariate analysis, new figures to illustrate individual differences, as well as several changes in the introduction and discussion sections. The letter below lists a point by point reply to all the reviewers’ comments. Please note that during the reanalysis in this revision process, one of the conclusions has changed. The manuscript was also edited to improve the clarity of the writing. We would like to thank the editor and reviewers for their constructive comments, which have contributed to the improvement of the manuscript. We look forward to your decision regarding this revised manuscript. Sincerely, Julie Justine Benoit Main comments Reviewer 1 • « The article is generally written clearly and professional English is used throughout. In the annotated document I have highlighted some instances where the language was not clear or was ambiguous.» Thank you for your comments regarding the writing. As suggested, the article has been reviewed in order to improve the writing. • « The article is well referenced however, there are two pockets of literature which need to be included. First, its acknowledged at the start of the paper that researchers have found null results in the video game literature but none of these studies are cited. Second, the authors emphasise the relation between video game play and cognitive abilities. And given that I think the authors think that the direction of the relation runs from video game play to cognitive abilities it would have been good to cite some targeted training studies with healthy populations. » Thank you for this suggestion. The articles reporting null results are now cited on lines 80 and training studies with healthy populations are cited a line 73. • « Currently, the discussion really only acknowledges that the current results are consistent with elite video game players being self selected at the very end. Up to that point the authors describe video game play being 'related' to certain capacities but 'related' here is ambiguous. While there are training studies which show that no video game players who play video games show abilities in the direction of causal video game players, there is currently no training studies that show that causal video game players matching elite video game players. This is no problem but it does raise interesting questions about the use and testing of elite players (supposedly it would be to identify target capacities for enhancement) and what the possible limits of training might be. Given that this is a cross sectional study there are limitations on what can be concluded about the relationship between video gaming demographics and cognitive capacities. » We agree with the reviewer that, due to the cross-sectional design, it is not possible to determine the causality between the variables. We now mention this fact at the end of the abstract, as well as in several places in the discussion. Please see lines 51 and 585. • « There are some missing details in the methods section. For example, the reader is not told what the selection criteria the casual video game group had to respect was. Nor are we told how many were excluded for failing those criteria (or the BDI-II inventory for that matter). Was handedness self-reported or assessed using something like the EHI? And so on. There are a number of other minor queries of this nature in the annotated document.» The methods section has been expanded to add more details about the neuropsychological tests, to provide more information on the participants demographics and video game habits (Table 2), and to specify the participant selection criteria. Please see the manuscript, starting at line 171. • « It would have been better to report exact p-values when possible, and report standard deviations rather than standard errors (unless the authors have some reason for doing otherwise). There are a number of other minor queries in the annotated document. For the most part this section is fine. » We now report exact p-values in the Tables and in the text, as well as standard deviations. Reviewer 2 • «The relationship between selective attention and working memory could be better describe considering also the relevant reviews such as […] » As suggested, the relationship between selective attention and working memory is now described in the result section (see lines 405 to 416) and in the discussion (lines 525 to 530) • « In addition, in order to explore better the possible relationship between selective attention and working memory in visual domain (main comment 1), a simple bivariate correlation analysis could be used. The same for the possible relation between working memory in visual and auditory domains (see main point 4). » We thank the reviewer for this suggestion. We have added a section in the Results to examine the relationship between selective attention, working memory and short term memory, in which we conducted bivariate Spearman’s correlations. We also have included a new figure (Figure 4) illustrating these correlations. Results are reported starting on line 424 and discussed at line 525. • « Only group analysis are reported. I suggest to explore also individual data. How many EVGPs perform better than the control group? For example, the Authors could use a cut off of 1 DS. » We thank the reviewer for the suggestion to explore individual data. For this purpose, we have plotted all individual data points in Figure 2, to allow readers to appreciate the overlap between performance in the two groups. The errors bars in the figure show 1 SD, which allows to view the individual data points in relation to the other group. • « A multivariate analysis between the two groups could be use to investigate the global results of the complex neuropsychological evaluation.» We agree with the reviewer’s suggestion to investigate global results of the neuropsychological evaluation. To do so, we conducted a descriptive discriminant analysis (DDA). Details are given in table 5 and in text at line 369. • « The multi-sensory effects of FPS action video games (i.e., WAIS Digit Span result) could be better considered also reporting recent results from action video game training in children with neurodevelopmental disorders such as developmental dyslexia (see Franceschini et al., 2013 Curr Biol, 2017 Sci Rep; Franceschini & Bertoni, 2019 NeuroPsychologia). » We thank the reviewer for bringing these references to our attention. These studies are now mentioned in the discussion, starting on line 488. • « The interesting result of learning during 3D-MOT task could suggest the relevant role of FPS action video games mainly on dorsal-action pathway (but see the null results on visuo-motor skills also reported in the present article). » The implication of the dorsal pathway is now in the discussion. See line 508. In texts comments of Reviewer 1 The lines numbers at the beggining of the citations refers to the line number in the original manuscript. Title • « I would be tempted to modify the title slightly to bring out the fact that you used 'professional' video game players. After all many people in the past simply characterized expertise in terms of hours played.» We changed the title of the article from “Neuropsychological profiling of videogame expertise” to “The neuropsychological profile of professional action video game players” to address this comment. Abstract • « It might be worth characterizing what you mean by 'elite' video game players in the abstract. One of the things which really sets your study apart from others is the use of 'professional' video game players.» We thank the reviewer for this comment. The abstract now clearly states that we studied professional video game players: “We assessed 14 video game players who play in a competitive league (Professional) and 16 casual video game players (Amateur) […]” Introduction • Line 43: « Unfortunately I do not have access to this survey. I just want to check that AVG in this survey is being used in the same sense that AVG is being used in the video-game literature. AVG in the video-game literature typically picks out FPS games (and excludes many RTS, MOBA, MMORPG, Sports, and so on titles). But I take it that this is meant to pick out a much broader array of game genres. It might be worth just briefly saying what game genres are included in AVG's, or else giving a few examples of game titles.» We changed the reference to include one that was publicly available and added a few examples of game titles. • Line 51: «This doesn't sound right. For instance, what about RTS games which also result in various cognitive enhancements (e.g. Glass, Maddox, and Love, 2013). While FPS games obviously emphasize certain capacities more than others, I am not sure that 'high mental workload' is specific to just this genre.» We agree with the reviewer’s point. We modified the sentence accordingly, see line 64. • Line 64 : «Might also be worth citing some training studies involving healthy matched controls. See for example, Feng, Spence, and Pratt (2007) and Spence, Yu, Feng, and Marshman (2009).» The references are now cited at line 73. • Line 69: «I think that it's important to reference some of null findings as well. For instance, Murphy and Spencer (2009), Gobet, et al. (2014), van Ravenzwaaij et al. (2014), and so on. I think this will feed nicely into your discussion about what makes someone an expert and further motivate the use of professional video game players.» Thank you for the suggestion. We think it would fit nicely in the article. See line 80. • Line 81: «This is unclear. I take it that what you mean here is something like: EVGP and CVGP have the same capacities but EVGP are able to deploy them better?» We phrased it differently in order to make our point clearer. See lines 143 to 147. • Line 82: « Might be good to give a line or two description what this means. Reading above it looks like you are drawing a distinction between two things which might be enhanced by expertise: (1) the capacities themselves, or (2) the deployment of those capacities. It's an open question whether one, both, or neither is enhanced, and this is what you are seeking to address in this paper. Currently its just a little bit unclear.» The first step is to determine whether there are cognitive differences between the Professional players and amateurs. We believe that if there are no cognitive differences between the groups, it could suggest that Professional performances are driven by their knowledge of the game. We hope that the corrections make our point clearer (see lines 140 to 149). • Line 89: « Might be worth mentioning that another hallmark is that those skills tend to generalize beyond the training domain. After all one of the main reasons people are interested in these domains is that visual skills trained in video games show up outside of video games.» It has been argued that AVG expertise could generalize towards other tasks. As the recent paper published by Bavelier, Bedou and Green suggests, the generalization is broadest during early-to-intermediate phases of learning. We did not feel like this paper aligned with our frame of work. Ref: Bavelier, D., Bediou, B., & Green, C. S. (2018). Expertise and generalization: Lessons from action video games. Current opinion in behavioral sciences, 20, 169-173. • Line 105: «Minor point and perhaps not necessary. But it might be useful to give an example in the context of a sport of video game to make this absolutely clear.» Your suggestion has been added. See line 114. • Line 107: Not everyone is going to know what this task is. Further given that its being used in this paper it would be good to roughly describe it out here in the introduction. See line 128. • Line 116: «Which one is it? It's not immediately obvious that these are interchangeable. To this point it sounds like what you mean is 'underlying'» The sentence has been rephrased accordingly, see line 149. • Line 125: I think its important somewhere in the introduction that these elite video game players you assessing are in fact the Houston Outlaws! The information was added at line 151. Methods • Line 136: We added more information on the selection criteria, starting at line 168. • Line 137: «Were any participants excluded for failing to respect selection criteria or the BDI-II?» No participants were excluded based on their BDI-II score. This information was added at line 182. We now also report the average BDI scores in Table 2. • Line 146: «Was handedness self-reported or did you use something like the EHI?» Handedness was self-reported. See Line 186 • Line 153: « Just for clarification, do you mean in competition? Or something stronger, never playing in a competitive multi-player setting?» In order to participate in the Amateur group, participants could not have played in any competitions. This information is now explicitly stated on line 177. Analysis • Following the recommendation, exact p-values are now reported in the tables and the text. The only estimate is to reflect p-values inferior to 0.001 (p<0.001). • Line 222: « Is that right given that you are using t-tests? Eta squared is used only in ANOVA models. It would be more appropriate to use Cohen's d.». We agree that Eta squared was not the appropriate effect size measure. We now report Hedges g measure, which is very similar to Cohen’s d , but is recommended for groups with smaller sample sizes. Results • Across all tables and text, standard deviations are now reported instead of standard errors and exact p-values are given. • Line 227: « Report the test-statistic (for consistency) ». Test-statistics are reported at line 320. • Line 248: « EVGP? (I even think that PVGP and Professional video game player might be better.)» Thank you for this recommendation. We now refer to the two groups as Professionals and Amateurs, to avoid the use of acronyms. • Line 257: « Was there any association between hours played, age begun and various score measures (I assume that the numbers are too low).» We have included the number of hours played in the bivariate correlations figure (Fig 4). Note that because the number of hours played is very different in the two groups (~10h in Amateurs and ~55 h for Professionals), this relationship is confounded with the group membership. Regarding the age begun, given our limited sample size and small variability in the age begun, we did not examine this relationship. Discussion • Line 263: « Above and beyond those that might be shown by casual video game players who might have fulfilled requirements to be included as video game players in previous studies? After all, your casual video game players fulfil requirements included by some other studies as well. For example, Latham et al. (2019) added a requirement to have begun playing before a certain age to be included as 'experienced' video game players ». The first paragraph of the discussion has changed substantially and the sentence to which this comment applied has been removed. In general, we have emphasized that the comparisons we report are between casual gamers and professionals. • Line 266, regarding studies showing benefits of video games for attention « Might be good to specifically reference some of those here. Many studies are cross sectional and so do not actually establish a causal connection between training and enhanced capacity. » This section of the discussion now includes references of studies that demonstrated a causal effect between video game practice and attentional enhancement. See line 458. • Line 267: « This is unclear. Why does the visual search being organized the same way preclude AVGPs employing a more optimal search strategy?» Unlike typical visual search tasks, in the d2 test, participants are given a specific amount of time per line and are not allowed to go back to previous lines. Since everyone has to follow the same visual search pattern, we argue that this task organizes the search for every participant and strategy differences cannot play a substantial role in differences in performance. Furthermore, the statistical analysis does not suggest speed-accuracy trade-off. We clarified this reasoning on line 462. • Line 275: « I found this a bit unclear (had to reread it a few times). I take it that what you are saying here is that your results because they involve professional video game players are highlighting enhancements which might be characteristic of video game expertise (at least for FPS games). Is that right?» Exactly. Modifications were made in the discussion at line 472. • Line 278: « Keep in mind its also consistent with professional video game players possessing a certain suite of cognitive capacities which allows them to succeed in professional game play. It is perhaps worth noting this alternative explanation. This seems especially important given the distinction you are drawing between causal video game players and elite video game players. We know from some studies that going from no video game to causal video game has some benefits. But there is currently no research about whether training can take you from causal to elite and reach the kinds of benefits you are highlighting in this paper.» Thank you for your insight on this result. We agree with your point of view and withdrew the sentence. • Line 283 & 290: « Depends on the kind of relation you have in mind. Strictly speaking we cannot tell if the even further enhanced results shown by elite players is due to even greater training or some innate endowment.» The sentences have been rephrased and the matter addressed at the beginning of discussion. See line 450. • Line 300: « Would be good to take a sentence of two to just spell out what that would look like.» As suggested, the relationship between selective attention and working memory are now better described in the result section (see lines 405 to 416) and in the discussion (line 528) • Line 305: « While not perfect there are some multisensory tasks which provide some suggestive evidence in that direction already. For instance, see Donohue, Woldorff, and Mitroff (2010).» We agree. It is now discussed at line 488. • Line 321: « That might be right. However, given what you are looking for in this study, cognitive enhancements characteristic of video game expertise, this is fine. If there are such characteristic enhancements then these should be identifiable even with a small sample size. Other residual differences might exist but perhaps those are simply ones we might not think of as being characteristic to elite video gamers.» We reformulated it at line 585. • Line 326: « Might be worth pointing out that cognitive flexibility is often cited as the strongest enhancement when looking at RTS games. Perhaps its weak because while its shared across all AVG genres its only emphasized in elite RTS video game players? Also why its not found when looking at professional FPS players.» Thank you for this suggestion. We now refer to these findings on cognitive flexibility in the discussion, see line 543. • Line 344: « .. And hence which capacities are likely to be the strongest candidates to be enhanced by them (provided a causal connection between play and capacity to be established). Note that when I have commented on this connection I don't think it matters that we might not be able to train out ways to the level of professional gamers. All that matters is that training results in changes in the same direction as those people we have identified as being elite.» Thank you for sharing your thoughts on this. See lines 472. • Line 352: « This needs to be acknowledged a lot earlier (as per some of my above comments). As I mention above all that matters is that training pushes our ability in the same direction as elite players, it doesn't have to match them. And there is plenty of training studies you can bring to bare on this point.» We have moved the discussion regarding our inability to speak to the causal relationship between cognitive abilities and video game expertise to the end of the first paragraph in the discussion. Please see lines 450. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>In the past 20 years, there has been growing research interest in the association between video games and cognition. Although many studies have found that video game players are better than non-players in multiple cognitive domains, other studies failed to replicate these results. Until now, the vast majority of studies defined video game players based on the number of hours an individual spent playing video games, with relatively few studies focusing on video game expertise using performance criteria. In the current study, we sought to examine whether individuals who play video games at a professional level in the esports industry differ from amateur video game players in their cognitive and learning abilities.</ns0:p><ns0:p>We assessed 14 video game players who play in a competitive league (Professional) and 16 casual video game players (Amateur) on set of standard neuropsychological tests evaluating processing speed, attention, memory, executive functions, and manual dexterity. We also examined participants' ability to improve performance on a dynamic visual attention task that required tracking multiple objects in threedimensions (3D-MOT) over five sessions.</ns0:p><ns0:p>Professional players showed the largest performance advantage relative to Amateur players in a test of visual spatial memory (Spatial Span), with more modest benefits in a test of selective and sustained attention (d2 Test of Attention), and test of auditory memory (Digit Span). Professional players also showed better speed thresholds in the 3D-MOT task overall, but the rate of improvement with training did not differ in the two groups. Future longitudinal studies of elite video game experts are required to determine whether the observed performance benefits of professional gamers may be due to their greater engagement in video game play, or due to pre-existing differences that promote achievement of high performance in action video games.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>There were more than two billion video gamers worldwide in 2016 and this number is projected to increase to 2.7 billion by 2021 <ns0:ref type='bibr'>(Statista, 2020)</ns0:ref>. In the United States, the gamer population consists of more than 150 million individuals, representing a 17.7 billion dollar market <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018;</ns0:ref><ns0:ref type='bibr'>SpillGames, 2013;</ns0:ref><ns0:ref type='bibr' target='#b74'>Statista, 2017)</ns0:ref>. There is a wide variety of video game genres, including action, real-time strategy, fighting, adventure, role playing, and racing games. Action video games (AVGs) such as Call of <ns0:ref type='bibr'>Duty,</ns0:ref><ns0:ref type='bibr'>Grand Theft Auto,</ns0:ref><ns0:ref type='bibr'>Halo,</ns0:ref><ns0:ref type='bibr'>Fallout 4,</ns0:ref><ns0:ref type='bibr'>Fortnite,</ns0:ref><ns0:ref type='bibr'>and</ns0:ref> Overwatch, are among the most popular types of video games in the United States <ns0:ref type='bibr' target='#b75'>(Statista, 2019)</ns0:ref>. More recently, we have witnessed the emergence of the eSports industry, in which video gamers compete individually or in teams in national and international competitions. More than 117 schools in the United States offer competitive eSports programs and many professional leagues are experiencing growing audiences and revenues <ns0:ref type='bibr' target='#b64'>(NACE, 2020;</ns0:ref><ns0:ref type='bibr'>Newzoo, 2020)</ns0:ref>.</ns0:p><ns0:p>The rise in popularity of video games in the last 20 years has led to a surge of research examining their impact on the mind and brain, with a special focus on AVGs. Although AVGs differ from one another, they all share four characteristics: a fast pace (moving objects, time constraints), a high perceptual load, a high degree of distraction, and a requirement for constant switching between focused and distributed states of attention <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018)</ns0:ref>. AVGs are also highly engaging and intrinsically motivating activities, making them attractive and popular <ns0:ref type='bibr' target='#b66'>(Powers &amp; Brooks, 2014)</ns0:ref>. First-person shooter (FPS) games, in which the player has an egocentric view through his or her avatar's eyes, have been the focus of many studies, as they were suspected to be the most likely genre of AVGs to influence cognition due to their high engagement of sensory, perceptual, and cognitive functions <ns0:ref type='bibr'>(Spence &amp; Feng, 2010)</ns0:ref>. Although <ns0:ref type='bibr' target='#b55'>Tippett (2013)</ns0:ref> argued that the lack of consideration of individual differences in the level of performance in video games, in addition to experience, likely contributes to the heterogeneous results in the literature and limits our understanding of video game expertise. One category of experts that excels relative to others are elites. In the broadest sense, experts can be described as individuals who acquire knowledge or abilities in a specific domain such as a profession, hobby, sport, or game, by devoting a substantial amount of time to that activity <ns0:ref type='bibr' target='#b16'>(Chi, Glaser, &amp; Farr, 2014;</ns0:ref><ns0:ref type='bibr' target='#b31'>Ericsson &amp; Towne, 2013;</ns0:ref><ns0:ref type='bibr' target='#b32'>Farrington-Darby &amp; Wilson, 2006)</ns0:ref>. Elites are experts who achieve a high level of performance in their domain relative to others. In the context of sports for example, athletes who play in professional leagues or who rank highly in international competitions are considered elites <ns0:ref type='bibr' target='#b78'>(Swann, Moran, &amp; Piggott, 2015)</ns0:ref>. In video games, elites are those players who consistently achieve high rankings or who are selected to participate in professional leagues. While practice is necessary to achieve high levels of performance, the amount of practice alone is not sufficient, as an individual can practice a lot and acquire knowledge in a specific area without ever becoming an elite <ns0:ref type='bibr' target='#b31'>(Ericsson &amp; Towne, 2013)</ns0:ref>.</ns0:p><ns0:p>Research on expertise has sought to understand whether there are certain characteristics that enable individuals to achieve high levels of performance in various domains <ns0:ref type='bibr' target='#b16'>(Chi et al., 2014)</ns0:ref>. In sports, research has focused on evaluating perceptual-cognitive capacities, which refer to the ability to identify and amass information to combine with actual knowledge in order to select and execute the appropriate response <ns0:ref type='bibr' target='#b16'>(Chi et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b61'>Mann et al., 2007)</ns0:ref>. The ability to extract information rapidly is a crucial element of high-level competitive sports, as athletes must direct their attention to the relevant aspects of the wide and dense visual scene in order to make fast decisions <ns0:ref type='bibr' target='#b61'>(Mann et al., 2007)</ns0:ref>. A meta-analysis of athletes across various sports reported that elite PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed athletes are indeed better able to extract pertinent information in the visual scene in the context of their sport, while also showing a different pattern of eye movements and visual search strategies relative to non-elite athletes <ns0:ref type='bibr' target='#b61'>(Mann, Williams, Ward, &amp; Janelle, 2007)</ns0:ref>. Perceptualcognitive capacities may also be important in videogaming, where a player must also select and extract relevant information to keep track of his or her enemies while anticipating their actions and deciding the best strategy to reach his or her objective.</ns0:p><ns0:p>More broadly, it has been suggested that individuals who achieve high levels of expertise also show enhanced performance across a wide range of core cognitive or perceptual domains in general, outside the specific context of their expertise. To continue with the example of sports, several recent studies have found that elite athletes outperform non-athletes in cognitive tests evaluating attention, multitasking, working memory, and processing speed, with group effects ranging from small to medium effect sizes <ns0:ref type='bibr' target='#b33'>(Faubert, 2013;</ns0:ref><ns0:ref type='bibr' target='#b69'>Scharfen &amp; Memmert, 2019;</ns0:ref><ns0:ref type='bibr' target='#b84'>Vaughan &amp; Laborde, 2020;</ns0:ref><ns0:ref type='bibr' target='#b86'>Voss, Kramer, Basak, Prakash, &amp; Roberts, 2010)</ns0:ref>. Professional athletes also showed faster improvement in performance on a three-dimensional multiple-objecttracking task (3D-MOT) as a function of training, compared to high-level amateurs and to nonathletes <ns0:ref type='bibr' target='#b33'>(Faubert, 2013;</ns0:ref><ns0:ref type='bibr'>Faubert &amp; Sidebottom, 2012)</ns0:ref>. The 3D-MOT task determines the speed at which the participant can track a subset of identical moving objects in a three-dimensional space over several seconds. The maximum speed at which a given number of targets can be tracked shows large individual variability, improves with training <ns0:ref type='bibr' target='#b33'>(Faubert, 2013;</ns0:ref><ns0:ref type='bibr' target='#b56'>Legault, Allard, &amp; Faubert, 2013;</ns0:ref><ns0:ref type='bibr' target='#b65'>Parsons et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b82'>Tullo, Faubert, &amp; Bertone, 2018)</ns0:ref>, and is associated with better decision making in sports <ns0:ref type='bibr' target='#b68'>(Romeas, Guldner, &amp; Faubert, 2016)</ns0:ref>. The finding that the improvement in 3D-MOT performance with practice was greater in professionals may point to generally enhanced learning abilities within the context of any dynamic visual scene. In sum, the studies above suggest that the outstanding performance achieved by elite athletes may be associated with enhanced abilities in a range of cognitive domains, including attention, processing speed, working memory, and learning abilities.</ns0:p><ns0:p>To our knowledge, no existing studies have examined whether professional action video game players also exhibit enhanced cognitive abilities relative to amateur players. While growing evidence supports a link between playing action video games and cognitive ability <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018)</ns0:ref>, further research is needed to better understand the nature of this association. Studying cognitive abilities of professional video gamers can shed more light on this relationship, by providing clues as to how expertise is developed, the mechanisms at play, and how best to support and improve it <ns0:ref type='bibr' target='#b32'>(Farrington-Darby &amp; Wilson, 2006)</ns0:ref>. Specifically, we can address the following question: does the outstanding performance of professional video game players stem from enhanced cognitive abilities in certain domains, or is it largely due to a greater expertise within the context of the game?</ns0:p><ns0:p>To address this gap, this study aimed to characterize the cognitive and learning abilities of highperformance action video game players recruited amongst the Houston Outlaws, a professional team in the Overwatch league&#8482;. We used a selection of standardized neuropsychological tests to evaluate cognitive abilities, and trained participants on the 3D-MOT task to assess their abilities to learn a novel, dynamic perceptual-cognitive task. We hypothesized that professional players would perform better than amateur players on neuropsychological tasks that evaluate attention, processing speed, executive functions, working memory, and visuo-spatial manipulation, as these Manuscript to be reviewed aspects of cognition have been found to be more developed in habitual video game players when compared with non-players <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018)</ns0:ref>. We also hypothesized that professional players would show faster learning rates on 3D-MOT compared with amateur players, as was observed with expert athletes <ns0:ref type='bibr' target='#b33'>(Faubert, 2013)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Participants</ns0:head><ns0:p>The experimental protocol was evaluated and approved by the Comit&#233; d'&#201;thique de la Recherche en Sant&#233; of Universit&#233; de Montr&#233;al (18-009-CERES-D). Fourteen participants (all men, righthanded) were recruited amongst competitive players in the Overwatch League&#8482; for the Houston Outlaws (Professional group). These participants are considered elite video gamers, because they have achieved the necessary performance level to enter a professional league. They reported daily FPS video game usage in the last 6 months and were ranked as Grandmaster or Top 500/Pro in the game. As a comparison group, we recruited habitual video game players (Amateur group) through online advertisements targeted at undergraduate students at the Universit&#233; de Montr&#233;al. Knowing that the video game category and type may be important influencing factors <ns0:ref type='bibr' target='#b25'>(Dobrowolski, Hanusz, Sobczyk, Skorko, &amp; Wiatrow, 2015)</ns0:ref>, participants in the Amateur group needed have played more than 5 hours per week of FPS during the last 6 months. They also could not have previously participated in organized video game competitions or played more than 20 hours per week in the past 6 months. This exclusion criterion was used to ensure that the Amateur group was homogeneous and similar to previous studies in the range of hours of game play per week <ns0:ref type='bibr' target='#b39'>(Bavelier &amp; Green, 2003</ns0:ref><ns0:ref type='bibr'>, 2005</ns0:ref><ns0:ref type='bibr'>, 2006;</ns0:ref><ns0:ref type='bibr' target='#b50'>Karle, Watter &amp; Shedden, 2010;</ns0:ref><ns0:ref type='bibr' target='#b20'>Colzato, van den Wildenberg, Zmigrod &amp; Hommel, 2013)</ns0:ref>. A total of 20 participants (3 left-handed, 4</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed female) were enrolled in the Amateur group. Two participants were then excluded for playing more than 20h per week or for having taken part in competitions, and two more were excluded due to inadequate testing environments, resulting in a sample of 16 participants in the Amateur group. Demographic and video game experience characteristics of the two groups are summarized in Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>. All participants were screened for depressive symptoms using the Beck Depression Inventory II (BDI-II) <ns0:ref type='bibr' target='#b87'>(Wang &amp; Gorenstein, 2013)</ns0:ref>; no participants were excluded based on their BDI-II scores (exclusion &gt;20). Participants had normal or corrected-to-normal vision and were free of visual, neurological, musculoskeletal, cardiovascular and vestibular impairments, as assessed by self-report. Handedness was also self-reported. All participants gave their verbal and written informed consent to participate after receiving verbal and written information about the study. They were not paid for their participation.</ns0:p></ns0:div> <ns0:div><ns0:head>Neuropsychological measures</ns0:head><ns0:p>Table <ns0:ref type='table'>2</ns0:ref> summarizes the eight neuropsychological tests that were used in this study.</ns0:p><ns0:p>The d2 Test of Attention <ns0:ref type='bibr' target='#b12'>(Brickenkam &amp; Zillmer, 1998)</ns0:ref> was selected to evaluate selective and sustained attention skills, as well as speed of processing. In this test, participants are presented with a sheet of paper containing 14 lines of 47 items each. The items are either a 'p' or a 'd' with one to four dashes placed alone or in pairs below and above the letter. Participants are given 20 seconds per line to cross out all the items containing a 'd' with two dashes. The outcome measures include the total number of items processed (TN), percent of errors of omission and commission (%E), number of correct items (TN-E), concentration performance (CP), and variability in performance across lines (fluctuation ratio, FR).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The WAIS-IV Coding test was selected to evaluate visual processing speed <ns0:ref type='bibr' target='#b88'>(Wechsler, 2011)</ns0:ref>. In this task, participants are required to code a series of numbers using symbols shown on a key at the top of the page, similar to the Digit Symbol Substitution Test. The total number of items that are coded in two minutes is recorded.</ns0:p><ns0:p>The WAIS-IV Visual Puzzles was selected to evaluate visual reasoning and the ability to manipulate visual information <ns0:ref type='bibr' target='#b88'>(Wechsler, 2011)</ns0:ref>. This task requires the participant to decide which three of six puzzle pieces combine together to reconstruct a larger puzzle within a limited time. The number of successfully completed puzzles is scored.</ns0:p><ns0:p>The WAIS-IV Digit Span test <ns0:ref type='bibr' target='#b88'>(Wechsler, 2011)</ns0:ref> was selected to evaluate auditory working memory (aWM) and short-term memory (aSTM). The test requires participants to listen to a series of digits that are read out loud and to recite them back in the same order (Forward subtest), in backwards order (Backward subtest), or in increasing numerical order (Sequencing subtest).</ns0:p><ns0:p>The total number of correctly reported sequences is scored <ns0:ref type='bibr' target='#b89'>(Weiss, Saklofske, Coalson, &amp; Raiford, 2010)</ns0:ref>.</ns0:p><ns0:p>The Wechsler Memory Scale-III (WMS-III) Spatial Span test <ns0:ref type='bibr' target='#b51'>(Kessels, van den Berg, Ruis, &amp; Brands, 2008)</ns0:ref> was selected to evaluate visual working memory (vWM) and visual short-term memory (vSTM). In this test, participants are shown nine cubes placed randomly on a board. The examiner taps a number of cubes in a sequence and participants have to reproduce this sequence either in the order presented (Forward subtest) or in backwards order (Backward subtest). The total number of successful sequences on each subtest is scored.</ns0:p><ns0:p>Two tests from the Delis Kaplan Executive Function System (D-KEFS) were selected to evaluate executive function <ns0:ref type='bibr' target='#b24'>(Delis, Kaplan, Kramer, Delis, &amp; Kramer, 2001)</ns0:ref>. The D-KEFS Tower test evaluates problem solving and planning. The task requires moving five disks across three pegs to PeerJ reviewing <ns0:ref type='table' target='#tab_1'>PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:ref> Manuscript to be reviewed build a tower in the fewest number of moves possible. Performance is scored by combining the total achievement score, which is the sum of achievement points for all the administered items, and the move accuracy ratio score, which assesses the efficiency with which the participant constructed the towers.</ns0:p><ns0:p>The D-KEFS Colour-Word Interference test is a version of the Stroop test that evaluates inhibition and cognitive flexibility. In the Inhibition condition, participants are required to name the colour of the ink of a series of words that spell a name of a different colour. In the Flexibility condition, participants are required to read the words that are outlined by a rectangle, but to name the ink colour of the other words that are not outlined. The time required to complete a set of words is recorded <ns0:ref type='bibr' target='#b77'>(Strauss, Sherman, &amp; Spreen, 2006)</ns0:ref>.</ns0:p><ns0:p>Finally, the Grooved Pegboard test (Lafayette Model 32025) was selected to evaluate hand-eye coordination and dexterity <ns0:ref type='bibr' target='#b77'>(Strauss et al., 2006)</ns0:ref>. This test requires participants to pick up small metal pegs that have a key on one end and insert them into randomly oriented slots on the board by rotating the pegs into the correct position. The test is performed with each hand separately and the time required to insert twenty-five pegs into the slots is recorded.</ns0:p></ns0:div> <ns0:div><ns0:head>Three-Dimensional Multiple Objects Tracking (3D-MOT)</ns0:head><ns0:p>The 3D-MOT sessions were conducted in a quiet room using a fully immersive environment with a Fove&#8482; virtual reality device. The head-mounted display had a resolution of 2560 x 1440 pixels and covered a maximal visual field of 45 degrees. The 3D-MOT task was delivered using a Dell Inspiration 15 700 Gaming Series computer.</ns0:p><ns0:p>The 3D-MOT was developed as an optimal training procedure to improve mental abilities critical for processing dynamic scenes, such as those encountered during sports or video gaming <ns0:ref type='bibr'>(Faubert &amp; Sidebottom, 2012)</ns0:ref>. The procedure adapts the well-known multiple object tracking task <ns0:ref type='bibr' target='#b67'>(Pylyshyn &amp; Storm, 1988)</ns0:ref>, in which participants track several moving targets among distractors, by expanding it to cover a large span of the visual field in three dimensions using stereoscopic presentation, and by varying the speed of the moving objects on every trial to determine a speed threshold <ns0:ref type='bibr'>(Faubert &amp; Sidebottom, 2012)</ns0:ref>.</ns0:p><ns0:p>During the 3D-MOT task (Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>), participants were required to track four of eight spheres that moved within a cube delineated by light grey walls with their attention only, without eye movements. A green fixation square was presented in the center of the cube and participants were asked to maintain fixation on the square throughout the tracking phase. Each trial began with the presentation of all eight yellow spheres positioned at random locations within the cube for two seconds. The four target spheres were then highlighted by changing to a red colour with a white halo for two seconds. Once the targets returned to the yellow colour for once second, all eight spheres began to move along linear paths in random directions within the cube, changing directions when colliding with each other or with the walls. After eight seconds, the spheres stopped moving and were labeled with numbers 1 through 8. The participant was then prompted to verbally identify the target spheres. After their choice was entered, the correct targets were revealed for two seconds to provide the participant feedback. The next trial began shortly afterwards. The speed of all the spheres varied across trials according to a one-up, one-down staircase procedure to estimate the speed required to track all four targets correctly 50% of the time <ns0:ref type='bibr' target='#b57'>(Levitt, 1971)</ns0:ref>. The speed increased by 0.05 log units if the participant correctly identified all targets and decreased by the same amount if the participant missed at least one target. The staircase procedure was interrupted after 20 trials and the speed threshold was estimated using the geometric mean of the speeds for the last four reversals. A complete staircase procedure lasted approximately eight minutes. Manuscript to be reviewed Analysis Two participants in the Professional group did not have high proficiency in English or French, so they were not tested on the Digit Span and Colour Word Interference tests, since performance in these tests depends on language proficiency. One of these participants also did not complete the Tower test, due to difficulties with understanding instructions. Data for the 3D-MOT training sessions were available for 27 of 30 participants, because three participants in the Amateur group did not complete the five 3D-MOT sessions due to travel restrictions, so their data were excluded from these analyses. Additionally, data from 17 out of 405 blocks across seven participants were missing due to a technical error and were treated as missing at random. Statistical analyses were performed in SPSS and in the statistical computing environment R (R Core <ns0:ref type='bibr'>Team, 2015)</ns0:ref>. First, we compared performance on all the neuropsychological measures in the two groups using independent Welch's t-tests, as the variance in the two groups was unequal for some outcome measures (e.g., Spatial Span total score, Levene's test p &lt; 0.01). Hedges' g was calculated to provide a measure of effect size using the effsize package in R <ns0:ref type='bibr' target='#b81'>(Torchiano, 2016)</ns0:ref>. To evaluate global group differences in neuropsychological measures and to compare the contribution of different outcome measures to the group difference, we conducted a descriptive discriminant analysis <ns0:ref type='bibr' target='#b13'>(Brown &amp; Wicker, 2000;</ns0:ref><ns0:ref type='bibr' target='#b72'>Smith, Lamb, &amp; Henson, 2020)</ns0:ref>. Additionally, bivariate Spearman's correlations were calculated to examine associations among neuropsychological outcome measures.</ns0:p><ns0:p>To examine the effects of learning on speed thresholds in both groups, we conducted a linear mixed effects analysis using the lme4, pbkrtest, and lmerTest packages in R <ns0:ref type='bibr'>(Baayen, Davidson,</ns0:ref> PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed <ns0:ref type='bibr' target='#b2'>&amp; Bates, 2008;</ns0:ref><ns0:ref type='bibr'>Bates et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b54'>Kuznetsova, Brockhoff, &amp; Christensen, 2014;</ns0:ref><ns0:ref type='bibr' target='#b59'>Luke, 2017;</ns0:ref><ns0:ref type='bibr' target='#b79'>Team, 2018)</ns0:ref>. The model's outcome variable was the speed threshold, with fixed effects of group, the logarithm of the block number, and their interaction. As random effects, we fit a maximal random effects structure that included by-subject intercepts and by-subject slopes for block (lmer(speed ~ Group * log2(block) + (1+log2(block) | subject)). This analysis is equivalent to fitting a logarithmic learning curve separately for each participant and then evaluating the effect of group on overall speed thresholds and learning rate. P-values for fixed effects were obtained using F-tests with the Kenward-Roger approximation for degrees of freedom <ns0:ref type='bibr' target='#b43'>(Halekoh &amp; H&#248;jsgaard, 2014)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref> summarises the demographic information and video game experience of participants in the groups. The two groups were well matched in age (Professionals: M = 23.66, SD = 2.44, Amateurs: M = 25.31, SD = 3.77, t(25.9) = -1.44, p = 0.16) and in the average age at which participants started playing video games (Professionals: M = 6.93, SD = 2.81, Amateurs: M = 6.75, SD = 2.62, t(26.8) = 0.18, p = 0.86). Participants in the Professional group devoted approximately five times more time to FPS games than those in the Amateur group in the last six months (Professionals: M = 55.79 h, SD = 16.72, Amateurs: M = 9.47 h, SD = 3.48, t(14) = 10.18, p &lt;0.001). There was no evidence for any differences in depression symptoms between both groups (Professionals: M = 6.85, SD = 5.27, Amateurs: M = 4.93, SD = 4.62, t(24.1) = 1.01, p = 0.32).</ns0:p></ns0:div> <ns0:div><ns0:head>Neuropsychological assessments</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p><ns0:p>Figure <ns0:ref type='figure' target='#fig_2'>2</ns0:ref> shows the outcome measures from the eight neuropsychological tests for the two groups. Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref> presents their summary statistics and the results of univariate, between-group statistical analyses for each measure. In the d2 Test of Attention, Professional players processed, on average, a greater number of stimuli than those in the Amateur group (TN: t(28) = 2.41, p = 0.02, g = 0.85), while maintaining a similar error rate (E%: t(27.3) = 0.70, p = 0.49, g = 0.25). When accounting for the error rate, Professional players processed a greater number of stimuli correctly (TN-E: t(28) = 2.3; p = 0.03; g = 0.81), but their Concentration Performance score did not differ significantly from the Amateur group (CP: t(26.4)= 1.31; p = 0.20 ; g = 0.47). The Fluctuation Rate, which measures the consistency of performance throughout the task, was lower in the Professional group (FR: t(28)= -2,14 ; p = 0.04 ; g = -0.75), indicating better sustained attention.</ns0:p><ns0:p>In the WAIS-IV Spatial Span task, the Professional group showed better performance than the Amateurs on the Total score (t(25.5) = 3.52, p &lt; 0.001, g = 1.27), with a large effect size.</ns0:p><ns0:p>Analyzing each subscale separately revealed a large, reliable effect in the Forward subscale, (t(28) = 3.85 ; p = 0.001, g = 1.36), but no reliable difference in the Backward subscale (t(24.4) = PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed 1.92, p = 0.07, g = 0.7). In the WAIS-IV Digit Span task, the Professional group also showed better performance on the Total score (t(23) = 2.20; p = 0.04, g = 0.82), with a smaller effect size than in the Spatial Span test. Scores for the Digit Span Forward, Backward, and Sequencing subscales were not reliably different in the two groups (p= 0.06, 0.11, 0.13, respectively).</ns0:p><ns0:p>In the WAIS-IV Coding test, the average score in the Professional group was numerically higher than that of the Amateur group, but this group difference was not reliable (t(26) = 1.54, p = 0.14, g= 0.55). There was no evidence for a difference in performance between the two groups on tests of executive function, D-KEFS Towers (ps &gt; 0.08) and D-KEFS Colour-Word Interference (ps &gt; 0.36), nor on the Visual Puzzles test (ps = 0.44), which evaluates perceptual reasoning. There was also no evidence for any difference between groups in the Grooved Pegboard test (ps &gt; 0.17), which evaluates hand-eye coordination and manual dexterity.</ns0:p><ns0:p>Next, we used a multivariate analysis approach to probe for global differences between the two groups across all neuropsychological assessments. To ward against multicollinearity, we selected one measure per task and conducted a descriptive discriminant analysis (DDA; <ns0:ref type='bibr' target='#b72'>Smith et al., 2020)</ns0:ref> on this subset of outcome measures, The measures included were d2 TN-E, Spatial Span Total, Digit Span Total, Grooved Peg for the dominant hand, Color-Word Inhibition score, and total scores for Coding, Visual Puzzles, and Towers. The largest bivariate correlation across these measures was -0.55, indicating that the variables were not multicollinear. The DDA analysis calculates a linear composite of the outcome variables that best separates the two groups. The canonical correlation, R c , between the composite and Group was 0.67, with a corresponding R c 2 = 0.45, which is the variance accounted for Group in the composite scores. This difference was not statistically significant, Wilk's = 0.54, F(8, 19) = 1.97, p = 0.11. &#923;</ns0:p><ns0:p>Examining the standardized discriminant function coefficients revealed that the Spatial Span Total score made the largest contribution to the composite score, with a coefficient of -0.29 and r 2 = 0.62. Table <ns0:ref type='table'>4</ns0:ref> provides the full results of this analysis.</ns0:p></ns0:div> <ns0:div><ns0:head>3D-MOT training</ns0:head><ns0:p>Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref> shows the average speed thresholds for tracking four targets in the 3D-MOT task as a function of block number for each group. As can be seen, the Professional group showed higher thresholds overall than the Amateur group, indicating better ability to track multiple targets among distractors. Thresholds in both groups increased as a function of block number, reflecting improvements in task performance as a function of training, with a similar rate of improvement in both groups. These observations were confirmed by a linear mixed effects analysis (see Table <ns0:ref type='table' target='#tab_3'>5</ns0:ref>), which revealed a main effect of Group, F(1, 24.78) = 5.54, p = 0.03, with the Professional group having higher thresholds, = 0.28, 95%CI [0.05, 0.52]. There was also a main effect of &#120573; block, F(1, 24.78) = 76.97, p &lt;0.001, with thresholds increasing by = 0.14, 95%CI [0.09, 0.20] &#120573; for every doubling of the block number. The interaction between Group and log2(block) was not statistically significant, F(1, 24.78) = 1.23, p = 0.28, providing no evidence that the learning rates differed between the two groups. Manuscript to be reviewed deviations of the mean. Thin lines represent logarithmic regressions, which fit individual participants' data (dashed red for Professionals, solid black for Amateurs), and thick lines fit the groups' data. Speed is expressed in arbitrary speed units.</ns0:p></ns0:div> <ns0:div><ns0:head>Association between attention, working memory, and short-term memory</ns0:head><ns0:p>Previous studies have indicated that visual working memory (WM) and selective attention are related both on a behavioral and neuroanatomical level <ns0:ref type='bibr' target='#b0'>(Awh &amp; Jonides, 2001;</ns0:ref><ns0:ref type='bibr' target='#b37'>Gazzaley &amp; Nobre, 2012)</ns0:ref>. It has been argued that selective attention is crucial for effectively filtering irrelevant information at the encoding phase <ns0:ref type='bibr' target='#b85'>(Vogel, McCollough, &amp; Machizawa, 2005)</ns0:ref>.</ns0:p><ns0:p>Because WM has a limited capacity, attention is required to appropriately select the relevant information to encode in WM to avoid unnecessary clutter <ns0:ref type='bibr' target='#b60'>(Ma, Husain, &amp; Bays, 2014;</ns0:ref><ns0:ref type='bibr' target='#b63'>Myers, Stokes, &amp; Nobre, 2017)</ns0:ref>. Selective attention may also be involved in maintaining information activated in WM <ns0:ref type='bibr' target='#b0'>(Awh &amp; Jonides, 2001;</ns0:ref><ns0:ref type='bibr' target='#b1'>Awh, Vogel, &amp; Oh, 2006)</ns0:ref>. Many studies also report an association between WM and STM <ns0:ref type='bibr' target='#b22'>(Conway, Cowan, Bunting, Therriault, &amp; Minkoff, 2002;</ns0:ref><ns0:ref type='bibr' target='#b30'>Engle, Tuholski, Laughlin, &amp; Conway, 1999;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kail &amp; Hall, 2001)</ns0:ref>, as STM is often theorized as a subcomponent of WM <ns0:ref type='bibr' target='#b23'>(Cowan, 1998;</ns0:ref><ns0:ref type='bibr' target='#b30'>Engle et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b49'>Kail &amp; Hall, 2001)</ns0:ref>.</ns0:p><ns0:p>Figure <ns0:ref type='figure'>4</ns0:ref> shows the results of bivariate Spearman's correlations among attention and processing speed outcome measures (d2 Test of Attention TN-E, WAIS-IV Coding, and the average speed threshold for the 3D-MOT task at baseline), and among auditory and visual WM and STM outcome measures (Spatial Span Forward and Backward subscales, Digit Span Forward, Backward, and Sequencing subscales). We only examined correlations for both groups together, as the sample sizes in each group were not sufficient to provide stable correlation estimates <ns0:ref type='bibr' target='#b71'>(Sch&#246;nbrodt &amp; Perugini, 2013)</ns0:ref>. As can be seen, d2 TN-E scores were correlated with Spatial Span Backward subscale (r s = 0.50, p = 0.01), and with the WAIS-IV Coding (r s = 0.45, p = 0.01), but not with Spatial Span Forward (r s = 0.21, p = 0.26). Thus, our measure of selective attention correlated with measures of vWM and processing speed, but not with vSTM. The d2</ns0:p><ns0:p>TN-E score also correlated with the Digit Span Sequencing subscale (r s = 0.51, p = 0.01), but not with the Forward or Backward subscales. The Spatial Span Forward and Backward subscales were moderately correlated with each other (r s = 0.43, p = 0.02). Performance on the 3D-MOT task showed a strong correlation with the Spatial Stan Forward (r s = 0.68, p &lt; 0.001) and Backward (r s = 0.69, p &lt; 0.001) subscales, indicating that these two tasks index similar cognitive capacities. Finally, the Spatial Span Forward was the only variable that correlated with the average weekly hours of video game play (r s = 0.45, p = 0.12). Keeping in mind that the Professional and Amateur groups showed a large difference in their average weekly hours of video game play, this positive association is consistent with the previously-reported difference in Spatial Span performance in the two groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>To gain a better understanding of the cognitive determinants of expertise in action video games, the current study compared the performance of professional action video gamers with that of video gamers who play similar FPS games non-competitively on a set of eight neuropsychological tests, and on their ability to improve their performance on a multiple objects tracking task. The results revealed that Professionals performed better than Amateurs on some measures in the Spatial Span, Digit Span, d2 Test of Attention, and 3D-MOT tasks. These results</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed indicate that high performance in FPS video games is associated with enhanced abilities in visual and auditory short-term memory, selective and sustained attention, and visual spatial attention.</ns0:p><ns0:p>There was no evidence for any group differences in performance on tasks that evaluated executive functions, perceptual manipulation, or manual dexterity. Furthermore, both groups showed similar capacity to improve their performance in the 3D-MOT task with training. Given the cross-sectional, observational nature of this group comparison, this study cannot speak to the causality of the differences in cognitive performance and video game expertise. The presence of differences between groups may either indicate that certain cognitive abilities are conducive to achieving high performance in FPS games, or that the greater amount of experience with FPS games in the professional group lead to improved performance in the above-mentioned abilities.</ns0:p><ns0:p>The results from the d2 Test of Attention indicate that Professional players may have better selective and sustained attention than Amateur players. This finding is consistent with previous studies that reported attentional benefits in non video-game players following practice with action video games <ns0:ref type='bibr' target='#b8'>(Belchior et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b39'>Green &amp; Bavelier, 2003;</ns0:ref><ns0:ref type='bibr'>Green &amp; Bavelier, 2006;</ns0:ref><ns0:ref type='bibr' target='#b73'>Spence et al., 2009)</ns0:ref>. It is also consistent with results of a meta-analysis that found strong evidence for a robust effect of action video games on attention using similar tasks <ns0:ref type='bibr' target='#b7'>(Bediou et al., 2018)</ns0:ref>. Some authors have raised the possibility that AVG players show higher performance in attention tasks because they employ a more optimal visual search strategy <ns0:ref type='bibr' target='#b19'>(Clark, Fleck, &amp; Mitroff, 2011)</ns0:ref>. We believe that differences in search strategies were minimized in the d2 test, because participants were instructed to search line by line without the possibility of going back.</ns0:p><ns0:p>Furthermore, although Professional players processed, on average, more stimuli than Amateurs, they maintained the same accuracy rate, suggesting no apparent trade-offs between speed and</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed accuracy. These results suggest that Professional players displayed enhanced visual selective attention compared to Amateurs. Furthermore, the performance of Professional players was more stable than Amateurs' in terms of items processed per line, suggesting better capacities in sustained attention. Sustained attention is an important ability in the context of professional videogaming, where players often need to train for many hours consecutively. While previous research has demonstrated that AVG players hold an advantage over non-players on attention <ns0:ref type='bibr' target='#b15'>(Castel et al., 2005;</ns0:ref><ns0:ref type='bibr'>Green &amp; Bavelier, 2006)</ns0:ref>, the current results indicate that selective and sustained attention are further enhanced in elite video game experts. Thus, taken together, these results suggest that attention capacities could be influenced by AVGs.</ns0:p><ns0:p>Previous studies that used change detection tasks with simple and complex stimuli have reported better vSTM capacities in action video game players <ns0:ref type='bibr' target='#b9'>(Blacker &amp; Curby, 2013;</ns0:ref><ns0:ref type='bibr'>Wilms, Petersen, &amp; Vangkilde, 2013)</ns0:ref>. In the present study, vSTM was indexed using the Spatial Span Forward subscale, which showed the greatest benefit in performance in the Professional group. Previous researchers have proposed that improvements in vSTM could be linked to the enhancement of visual selective attention that enables to select task-relevant and ignore task-irrelevant information <ns0:ref type='bibr' target='#b6'>(Bavelier, Green, Pouget, &amp; Schrater, 2012)</ns0:ref>. In the context of our study, the bivariate correlation did not show a statistically significant association between our attention and vSTM measures, suggesting that the benefits in vSTM seen here are not strongly related to selective attention abilities.</ns0:p><ns0:p>While previous studies mainly examined the effects of video games on visual cognition, a few studies have also noted benefits of video games on performance in auditory or multisensory</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed tasks. For example, adult video game players showed better temporal processing of multisensory stimuli than non-players <ns0:ref type='bibr' target='#b26'>(Donohue, Woldorff, &amp; Mitroff, 2010)</ns0:ref> and training with action video games was associated with improvements in reading and phonological short-term memory in children with dyslexia <ns0:ref type='bibr' target='#b35'>(Franceschini &amp; Bertoni, 2019;</ns0:ref><ns0:ref type='bibr' target='#b36'>Franceschini et al., 2013)</ns0:ref>. In the present study, there was some evidence for a benefit in auditory memory in the Digit Span test for the Professional group, although there was no evidence of a difference in the Forward subscale that indexes auditory short-term memory. While experience with video games may impact auditory and multisensory performance, we do not find evidence that auditory short-term memory is a characteristic of video game expertise.</ns0:p><ns0:p>The present study suggests a link between the level of video gaming expertise and the ability to perform an abstract dynamic task. The 3D-MOT task strongly engages several attention and mental skills; performing this task well requires selective, dynamic, distributed, and sustained attention skills <ns0:ref type='bibr' target='#b33'>(Faubert, 2013)</ns0:ref>. Professional video game players performed better than Amateurs on the 3D-MOT task across the 5 training sessions, suggesting that video game expertise is also related to perceptive-cognitive ability. This is consistent with the idea that Professionals players must be efficient at extracting meaningful information from a visual scene in order to anticipate and make good decisions. The 3D-MOT task results are consistent with the enhancement of motion perception highlighted by other studies that employed the multiple objects tracking or dots motion tasks <ns0:ref type='bibr' target='#b11'>(Boot, Kramer, Simons, Fabiani, &amp; Gratton, 2008;</ns0:ref><ns0:ref type='bibr'>Green &amp; Bavelier, 2006;</ns0:ref><ns0:ref type='bibr' target='#b46'>Hutchinson &amp; Stocks, 2013)</ns0:ref>. These results are also consistent with the growing evidence that action video game experience has an impact on the dorsal pathway <ns0:ref type='bibr' target='#b17'>(Chopin, Bediou, &amp; Bavelier, 2019)</ns0:ref>. The dorsal pathway is a network involved in spatial working memory. It specializes in Manuscript to be reviewed capturing dynamic spatial and temporal relationships between multiple items <ns0:ref type='bibr' target='#b53'>(Kravitz, Saleem, Baker, Ungerleider, &amp; Mishkin, 2013)</ns0:ref>, and is engaged during multiple object tracking tasks <ns0:ref type='bibr' target='#b10'>(Blumberg, Peterson, &amp; Parasuraman, 2015;</ns0:ref><ns0:ref type='bibr' target='#b45'>Howe, Horowitz, Morocz, Wolfe, &amp; Livingstone, 2009)</ns0:ref>. The dorsal pathway is often referred to as the 'where/how' pathway, as it is involved in localizing and guiding motor action <ns0:ref type='bibr' target='#b17'>(Chopin et al., 2019)</ns0:ref>. Furthermore, the professional and casual video game players in the current study showed similar learning rates across the five sessions, in contrast to other studies, where professional sports athletes showed enhanced abilities to improve their 3D-MOT performance with training relative to amateur athletes <ns0:ref type='bibr' target='#b33'>(Faubert, 2013)</ns0:ref>.</ns0:p><ns0:p>While the effect in the multiple object tracking task is consistent with differences in the dorsal pathway, there were no group differences in the Grooved Pegboard task, which relies on action planning and visuomotor coordination that also depends on the dorsal pathway. Previous studies found that players have better hand-eye coordination than non-players, but this benefit was not associated with the amount of time spent engaging in the games <ns0:ref type='bibr' target='#b42'>(Griffith, Voloschin, Gibb, &amp; Bailey, 1983)</ns0:ref>. Action video games were also shown to improve visuomotor control in an intervention study <ns0:ref type='bibr' target='#b58'>(Li, Chen, &amp; Chen, 2016)</ns0:ref>. Together with the current findings, this suggests that the benefits of action video games on motor dexterity and visuomotor coordination are limited, in that extended practice does not lead to larger benefits.</ns0:p><ns0:p>The current results also do not provide evidence for any differences in working memory associated with professional gaming, as the average performance on the Backward subscales of the Spatial Span and Digit Span tasks did not differ between groups. As mentioned earlier, Manuscript to be reviewed previous studies have emphasized that WM, which involves maintaining elements active and quickly accessible, is intricately linked with the concept of selective attention, both on a behavioral and anatomical level <ns0:ref type='bibr' target='#b0'>(Awh &amp; Jonides, 2001;</ns0:ref><ns0:ref type='bibr' target='#b29'>Engle, 2002;</ns0:ref><ns0:ref type='bibr' target='#b44'>Hitch, Hu, Allen, &amp; Baddeley, 2018)</ns0:ref>. Supporting this overlap between the two constructs, we observed positive associations between outcome measures of vWM, selective attention, and vSTM. Nevertheless, while there was some evidence for enhanced selective attention in professional players, performance in tasks relying on auditory or visual working memory were similar in both groups.</ns0:p><ns0:p>The present results also do not provide evidence for any differences in executive functions between Professional players and Amateurs, as measured by the inhibition and flexibility subscales of the Stroop task. Mental flexibility has been cited as one of the strongest enhancements in real-time strategy games <ns0:ref type='bibr' target='#b3'>(Basak, Boot, Voss, &amp; Kramer, 2008)</ns0:ref>. The metaanalysis in AVGs conducted by <ns0:ref type='bibr'>Bediou (2017)</ns0:ref> suggested a medium size effect for flexibility, and only a weak effect for inhibition. Given that the current study is only well suited to detect large effects, our findings are consistent with previous results. There is also no evidence of any group differences in visual planning skills or visual reasoning. These results are consistent with the results of <ns0:ref type='bibr'>Boot and colleagues (2008)</ns0:ref>, who found no association between video game practice and planning skills, using the Tower of London task <ns0:ref type='bibr' target='#b83'>(Tunstall, 1999)</ns0:ref>.</ns0:p><ns0:p>Previous studies have found that video game players are faster than non-video game players in reaction time tasks <ns0:ref type='bibr' target='#b15'>(Castel et al., 2005;</ns0:ref><ns0:ref type='bibr'>Dye et al., 2009)</ns0:ref>. However, the current study found no reliable difference in performance in the main visual processing speed task (WAIS-IV Coding), nor in the Grooved Peg task, which relies on rapid manual dexterity and hand-eye coordination.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:p><ns0:p>That said, the TN measure of the d2 Test of Attention showed that Professional players process a greater number of stimuli in a given time than Amateurs, suggesting that video game expertise is related to a better ability to process simple visual information. The different results provided by the d2 and Coding tests address a question raised by <ns0:ref type='bibr'>Dye, Green and Bavelier (2009)</ns0:ref>, who wondered whether the advantages of video gaming are restricted to tasks involving only binary responses, or if they can generalize to more complex tasks with multiple response alternatives.</ns0:p><ns0:p>The Coding task requires participants to quickly code a series of items using the correct symbol among a total of nine codes. Thus, in addition to speed of processing, good performance in the Coding task requires attention, motor speed, visuo-perceptual abilities, and dexterity to write the appropriate symbols <ns0:ref type='bibr' target='#b48'>(Jaeger, 2018)</ns0:ref>. In contrast, the participant response in the d2 test involves a choice between one of two options: to mark or not to mark the symbol. The two-choice response in the d2 test is closer to that used in the literature demonstrating the benefits of video gaming on processing speed <ns0:ref type='bibr'>(Dye et al., 2009)</ns0:ref>. The current findings may suggest that video game expertise is related to a better ability to process simple visual information, rather than providing a global benefit in processing speed in more complex tasks.</ns0:p><ns0:p>By better understanding Professional videogaming, we can provide clues as to how this expertise and the corresponding performance best develops, and therefore learn how to support it <ns0:ref type='bibr' target='#b32'>(Farrington-Darby &amp; Wilson, 2006)</ns0:ref>. In order to effectively study video game expertise, it is crucial to define it appropriately. The definitions of video gamers in previous studies ignored potential differences between video game players who had played 5 hours per week over the previous 6 months, and those who had played more than 20 hours per week over the previous 10 years. Moreover, the assumption that recent video gaming experience reflects expertise could be Manuscript to be reviewed mistaken <ns0:ref type='bibr' target='#b55'>(Latham et al., 2013)</ns0:ref>. Failure to consider expertise in terms of performance may also contribute to some of the mixed results in the literature. By applying the same performance criteria to video gaming research, differences between professional and amateur players allowed us to determine the factors that potentially underlie high-level performance, such as attention, STM, and perceptive-cognitive ability.</ns0:p><ns0:p>The current study has serval limitations. First, due to our limited sample size, the current study had low power to detect small or medium effects (with alpha = 0.05, power = 0.80). Thus, we should remain careful in our interpretation of null results, as differences might exist but failed to be detected. Furthermore, the gender of the study participants may have acted as a confounding variable since our Professional players group was composed only of men, whereas our Amateur group had four women, although women's results did not differ from men's within the same group. Finally, the experimenter who administered the measures was not blind to the participant group, which may have introduced some bias.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In summary, this study was the first to examine the cognitive basis of elite performance in action video game players. Our results revealed that elite players show the greatest performance advantage in tests of visual spatial short-term memory and of visual attention. Furthermore, professional action video gamers showed a better ability to track multiple objects within a complex and dynamic scene than amateur players, but both groups showed similar rates of improvement in the task with training. Further research is needed to clarify whether the observed differences in cognitive abilities emerge as a result of intense practice in action video games, or Manuscript to be reviewed Manuscript to be reviewed 8 9 </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 |</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1 | Five stages of a trial in the 3D-MOT task. a) Presentation phase, in which eight</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 |</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 | Results of neuropsychological tests. Large symbols show the mean group scores and</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 |</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3 | 3D-MOT task training data: Average speed thresholds for the Professional (red</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 1 Five</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 3 3D-</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>4</ns0:head><ns0:label /><ns0:figDesc>participants. a, b.: n = 12, 13 in the Professional group. WAIS = Weschler Adult Intelligence Scale (IV), WMS = Weschler Memory 5 Scale (III), TN = total number of items processed, TN-E = total number of items processed minus the errors, E% = percentage of errors, 6 CP = concentration performance, FR = fluctuation rate (difference between the line with the minimum and maximum number of items 7 processed). DH = Dominant hand, NDH = Non-dominant hand. Bolded p-values are &lt; an alpha level of 0.05 (uncorrected).</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='41,42.52,70.87,525.00,437.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Demographic and video game experience information for the two groups BDI-II: Beck depression inventory (II) score, FPS: first person shooter</ns0:figDesc><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 -Demographic and video game experience information for the two groups</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell cols='2'>Professionals (n=14) Amateurs (n=16)</ns0:cell><ns0:cell>Group comparison</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>M (SD)</ns0:cell><ns0:cell>M (SD)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Age (years)</ns0:cell><ns0:cell>23.66 (2.44)</ns0:cell><ns0:cell>25.31(3.77)</ns0:cell><ns0:cell>t(25.9) = -1.44, p = 0.16</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Gender ratio (male : female) 14:0</ns0:cell><ns0:cell>12:4</ns0:cell><ns0:cell>N / A</ns0:cell></ns0:row><ns0:row><ns0:cell>BDI-II score</ns0:cell><ns0:cell>6.85 (5.27)</ns0:cell><ns0:cell>4.93 (4.62)</ns0:cell><ns0:cell>t(24.1) = 1.01, p = 0.32</ns0:cell></ns0:row><ns0:row><ns0:cell>Age started playing video</ns0:cell><ns0:cell>6.93 (2.81)</ns0:cell><ns0:cell>6.75 (2.62)</ns0:cell><ns0:cell>t(26.8) = 0.18, p = 0.86</ns0:cell></ns0:row><ns0:row><ns0:cell>games (years)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Average FPS gaming per</ns0:cell><ns0:cell>55.79 (16.72)</ns0:cell><ns0:cell>9.47 (3.48)</ns0:cell><ns0:cell>t(14) = 10.18, p = 0.00</ns0:cell></ns0:row><ns0:row><ns0:cell>week in past six months (h)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Most frequent game</ns0:cell><ns0:cell>Overwatch (14)</ns0:cell><ns0:cell>Counter Strike (7),</ns0:cell><ns0:cell>N / A</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Call of Duty (3),</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Overwatch (3),</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Rainbow 6 (1), Player</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Unknown's</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Battlegrounds (1),</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Battlefield 4 (1),</ns0:cell><ns0:cell /></ns0:row></ns0:table><ns0:note>BDI-II: Beck depression inventory (II) score, FPS: first person shooter PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 3 -Average raw scores for all neuropsychological tests, difference scores, and univariate inferential 2</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Means and standard deviations (SD) of the raw scores of neuropsychological tests for Professional and Amateur video gamer</ns0:figDesc><ns0:table><ns0:row><ns0:cell>statistics.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Measure</ns0:cell><ns0:cell>Professionals</ns0:cell><ns0:cell>Amateurs</ns0:cell><ns0:cell cols='2'>Difference</ns0:cell><ns0:cell>Welch t-test</ns0:cell><ns0:cell>p</ns0:cell><ns0:cell>Effect size</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>(n=14)</ns0:cell><ns0:cell>(n=16)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Hedges' g</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>M (SD)</ns0:cell><ns0:cell>M (SD)</ns0:cell><ns0:cell>&#8710;</ns0:cell><ns0:cell>[95% CI]</ns0:cell><ns0:cell>t(df)</ns0:cell><ns0:cell /><ns0:cell>g [95%CI]</ns0:cell></ns0:row><ns0:row><ns0:cell>D2 Test of</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Attention</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>-TN</ns0:cell><ns0:cell>546.29 (56.14)</ns0:cell><ns0:cell cols='4'>493.56 (63.49) 52.73 [7.98, 97.47] t(28) = 2.41</ns0:cell><ns0:cell>0.02</ns0:cell><ns0:cell>0.85 [0.09, 1.61]</ns0:cell></ns0:row><ns0:row><ns0:cell>-E%</ns0:cell><ns0:cell>4.41 (2.98)</ns0:cell><ns0:cell>3.66 (2.91)</ns0:cell><ns0:cell cols='2'>0.75 [-1.46, 2.96]</ns0:cell><ns0:cell>t(27.3) = 0.7</ns0:cell><ns0:cell>0.49</ns0:cell><ns0:cell>0.25 [-0.48, 0.98]</ns0:cell></ns0:row><ns0:row><ns0:cell>-TN-E</ns0:cell><ns0:cell>521.86 (52.48)</ns0:cell><ns0:cell cols='4'>474.94 (59.31) 46.92 [5.11, 88.73] t(28) = 2.3</ns0:cell><ns0:cell>0.03</ns0:cell><ns0:cell>0.81 [0.05, 1.57]</ns0:cell></ns0:row><ns0:row><ns0:cell>-CP</ns0:cell><ns0:cell>208.79 (31.62)</ns0:cell><ns0:cell cols='4'>194.38 (28.41) 14.41 [-8.26, 37.08] t(26.4) = 1.31</ns0:cell><ns0:cell>0.20</ns0:cell><ns0:cell>0.47 [-0.27, 1.21]</ns0:cell></ns0:row><ns0:row><ns0:cell>-FR</ns0:cell><ns0:cell>11 (3.21)</ns0:cell><ns0:cell>13.75 (3.84)</ns0:cell><ns0:cell cols='3'>-2.75 [-5.39, -0.11] t(28) = -2.14</ns0:cell><ns0:cell>0.04</ns0:cell><ns0:cell>-0.75 [-1.51 ,0]</ns0:cell></ns0:row><ns0:row><ns0:cell>WAIS-IV</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Coding</ns0:cell><ns0:cell>77.5 (12.25)</ns0:cell><ns0:cell>71.0 (10.61)</ns0:cell><ns0:cell cols='2'>6.5 [-2.16, 15.16]</ns0:cell><ns0:cell>t(26) = 1.54</ns0:cell><ns0:cell>0.14</ns0:cell><ns0:cell>0.55 [-0.19, 1.3]</ns0:cell></ns0:row><ns0:row><ns0:cell>WMS-III</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Spatial Span</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>-Total</ns0:cell><ns0:cell>23 (2.94)</ns0:cell><ns0:cell>19.5 (2.45)</ns0:cell><ns0:cell cols='2'>3.5 [1.45, 5.55]</ns0:cell><ns0:cell>t(25.5) = 3.52</ns0:cell><ns0:cell>0.002</ns0:cell><ns0:cell>1.27 [0.47, 2.07]</ns0:cell></ns0:row><ns0:row><ns0:cell>-Forward</ns0:cell><ns0:cell>12.43 (1.5)</ns0:cell><ns0:cell>10.19 (1.68)</ns0:cell><ns0:cell cols='2'>2.24 [1.05, 3.43]</ns0:cell><ns0:cell>t(28) = 3.85</ns0:cell><ns0:cell>0.001</ns0:cell><ns0:cell>1.36 [0.55, 2.17]</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>-Backward 10.57 (1.99)</ns0:cell><ns0:cell>9.31 (1.54)</ns0:cell><ns0:cell cols='2'>1.26 [-0.09, 2.61]</ns0:cell><ns0:cell>t(24.4) = 1.92</ns0:cell><ns0:cell>0.07</ns0:cell><ns0:cell>0.7 [-0.06, 1.45]</ns0:cell></ns0:row><ns0:row><ns0:cell>WAIS-IV Digit</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Span WAIS-IV</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Visual Puzzles</ns0:cell><ns0:cell>18.5 (3.88)</ns0:cell><ns0:cell>19.5 (3.01)</ns0:cell><ns0:cell cols='2'>-1.00 [-3.64, 1.64]</ns0:cell><ns0:cell cols='2'>t(24.4) = -0.78 0.44</ns0:cell><ns0:cell>-0.28 [-1.02, 0.45]</ns0:cell></ns0:row><ns0:row><ns0:cell>D-KEFS</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Towers b</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>-Total</ns0:cell><ns0:cell>20.15 (4.32)</ns0:cell><ns0:cell>18.44 (4.32)</ns0:cell><ns0:cell cols='2'>1.71 [-1.6, 5.03]</ns0:cell><ns0:cell>t(25.8) = 1.06</ns0:cell><ns0:cell>0.30</ns0:cell><ns0:cell>0.39 [-0.37, 1.14]</ns0:cell></ns0:row><ns0:row><ns0:cell>-Accuracy</ns0:cell><ns0:cell>1.49 (0.29)</ns0:cell><ns0:cell>2 (1.04)</ns0:cell><ns0:cell cols='2'>-0.51 [-1.08, 0.06]</ns0:cell><ns0:cell cols='2'>t(17.9) = -1.86 0.08</ns0:cell><ns0:cell>-0.62 [-1.38, 0.15]</ns0:cell></ns0:row><ns0:row><ns0:cell>Ratio</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>D-KEFS Color-</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Word</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='2'>-Inhibition 43.67 (5.58)</ns0:cell><ns0:cell>45.94 (7.35)</ns0:cell><ns0:cell cols='2'>-2.27 [-7.3, 2.75]</ns0:cell><ns0:cell>t(26) = -0.93</ns0:cell><ns0:cell>0.36</ns0:cell><ns0:cell>-0.33 [-1.1, 0.44]</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>-Flexibility 51.42 (6.97)</ns0:cell><ns0:cell>52.25 (5.7)</ns0:cell><ns0:cell cols='2'>-0.83 [-5.96, 4.3]</ns0:cell><ns0:cell cols='2'>t(20.9) = -0.34 0.74</ns0:cell><ns0:cell>-0.13 [-0.89, 0.63]</ns0:cell></ns0:row><ns0:row><ns0:cell>Grooved</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Pegboard</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>-DH</ns0:cell><ns0:cell>69.73 (11.26)</ns0:cell><ns0:cell>64.1 (10.68)</ns0:cell><ns0:cell cols='2'>5.63 [-2.62, 13.89]</ns0:cell><ns0:cell>t(27) = 1.4</ns0:cell><ns0:cell>0.17</ns0:cell><ns0:cell>0.5 [-0.24, 1.24]</ns0:cell></ns0:row><ns0:row><ns0:cell>-NDH</ns0:cell><ns0:cell>71.58 (13.95)</ns0:cell><ns0:cell>66.12 (9.65)</ns0:cell><ns0:cell cols='2'>5.46 [-3.73, 14.66]</ns0:cell><ns0:cell>t(22.7) = 1.23</ns0:cell><ns0:cell>0.23</ns0:cell><ns0:cell>0.45 [-0.29, 1.19]</ns0:cell></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>a -Total 32.75 (5.5) 28.25 (5.17) 4.5 [0.27, 8.73] t(23) = 2.2 0.04 0.82 [0.03, 1.62] -Forward 11.67 (2.46) 9.75 (2.52) 1.92 [-0.04, 3.88] t(24.1) = 2.02 0.06 0.75 [-0.04, 1.53] -Backward 10.25 (2.7) 8.69 (2.09) 1.56 [-0.39, 3.52] t(20.1) = 1.67 0.11 0.64 [-0.14, 1.42] -Sequencing 10.83 (1.8) 9.81 (1.56) 1.02 [-0.33, 2.37] t(21.8) = 1.57 0.13 0.6 [-0.18, 1.37]</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 5 : Results of the linear mixed effects model fit to speed thresholds in the 3D-MOT task.</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>The proportion of the variance explained by fixed and random factors, conditional R 2 , is 0.68; the proportion of the variance explained by the fixed factors alone, marginal R 2 , is 0.29.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Fixed Effect</ns0:cell><ns0:cell>&#120631;</ns0:cell><ns0:cell>95%CI</ns0:cell><ns0:cell>t(df)</ns0:cell><ns0:cell>p</ns0:cell><ns0:cell>Random effect</ns0:cell><ns0:cell>St. Dev.</ns0:cell><ns0:cell>Corr</ns0:cell></ns0:row><ns0:row><ns0:cell>Intercept</ns0:cell><ns0:cell>0.59</ns0:cell><ns0:cell>[0.42, 0.76]</ns0:cell><ns0:cell>t(25.8) = 6.72</ns0:cell><ns0:cell cols='2'>&lt;0.001 Subj Intercept</ns0:cell><ns0:cell>0.24</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Group</ns0:cell><ns0:cell>0.28</ns0:cell><ns0:cell>[0.05, 0.52]</ns0:cell><ns0:cell>t(24.8) = 2.35</ns0:cell><ns0:cell>0.03</ns0:cell><ns0:cell>Subj log2(block)</ns0:cell><ns0:cell>0.10</ns0:cell><ns0:cell>0.06</ns0:cell></ns0:row><ns0:row><ns0:cell>log2(block)</ns0:cell><ns0:cell>0.15</ns0:cell><ns0:cell>[0.13, 0.29]</ns0:cell><ns0:cell>t(26.1) = 5.21</ns0:cell><ns0:cell cols='2'>&lt;0.001 Residual</ns0:cell><ns0:cell>0.28</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Group : log2(block)</ns0:cell><ns0:cell>0.06</ns0:cell><ns0:cell>[-0.05, 0.17]</ns0:cell><ns0:cell>t(24.8) = 1.10</ns0:cell><ns0:cell>0.28</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)</ns0:note> <ns0:note place='foot'> Faubert, J., &amp; Sidebottom, L. (2012). Perceptual-cognitive training of athletes. Journal of Clinical Sport Psychology, 6(1), 85-102.</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:01:44849:2:1:NEW 18 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

" Julie Justine Benoit Faubert Lab Université de Montréal (École d’optométrie) 3744, rue Jean-Brillant Bureau 260-01 Montréal, Québec H3T 1P1 Canada September 1st, 2020 Dear Editorial board, I would like to resubmit our manuscript entitled “The neuropsychological profile of professional action video game players” (#44849) following your decision requesting minor revisions. We have revised our manuscript to address the comments raised in the last round of revisions and these changes are outline in the letter below. We also proofread the article and edited the writing for clarity. As per your suggestion, these minor changes are not listed in the rebuttal letter below. On behalf of all the co-authors, I would like to thank the editor and reviewers for their constructive comments. I look forward to your decision regarding this revised manuscript. Sincerely, Julie Justine Benoit Comments • “FPS games are introduced as a sub-category of AVGs. However, all the previous examples of AVGs on Line 49–50 are FPS games. If AVGs are meant to be a more general category, then it might be worth giving some examples earlier of AVGs which are not FPS games.” As suggested, we give examples of AVG that are not FPS games at line 48 of the revised manuscript. specifically, we changed “Among all types of games, action video games (AVGs), such as Call of Duty, Halo or Overwatch, are among the most popular in the United States” to the following: “Action video games (AVGs) such as Call of Duty, Grand Theft Auto, Halo, Fallout 4, Fortnite, and Overwatch, are among the most popular types of video games in the United States” • “The concept of elite experts is useful when considering difference in performance amongst experts.”? Unclear sentence.” The concept of elite experts and the definition of expertise is now better explained in lines 90 to 101: “One category of experts that excels relative to others are elites. In the broadest sense, experts can be described as individuals who acquire knowledge or abilities in a specific domain such as a profession, hobby, sport, or game, by devoting a substantial amount of time to that activity (Chi, Glaser, & Farr, 2014; Ericsson & Towne, 2013; Farrington-Darby & Wilson, 2006). Elites are experts who achieve a high level of performance in their domain relative to others.” • “While I get the comparison being drawn elite athletes I think that it would be worth making clear that this is just being used as a paradigm case of expertise and its associated wide-ranging benefits. After all, the same point being made here with elite athletes could also be made using elite musicians (for example) who also show similar wide-ranging benefits (including to the visuospatial domain).” We thank the reviewer for this suggestion. Changes were made in lines 94 and 120: “In the context of sports for example, athletes who play in professional leagues or who rank highly in international competitions are considered elites (Swann, Moran, & Piggott, 2015)” and “To continue with the example of sports, several recent studies have found that elite athletes outperform non-athletes in cognitive tests evaluating attention, multitasking, working memory, and processing speed, with group effects ranging from small to medium effect sizes” • “Not sure what cognitive expertise means in this context. Is is something over and above the previously listed enhanced cognitive abilities?” We have clarified this sentence on lines 134–137 as follows: “In sum, the studies above suggest that the outstanding performance achieved by elite athletes may be associated with enhanced abilities in a range of cognitive domains, including attention, processing speed, working memory, and learning abilities.” • “What was the reason for excluding participants who played more than 20 hours per week? Given the focus on expertise, then so long as these participants were not competitive (the other exclusion criteria) I am not seeing why they should be excluded. It would be good to say a little more about why this exclusion criteria was used.” The reason for excluding participants who played more than 20 hours was to ensure that the Amateur group was homogeneous and similar to previous studies in the range of hours of game play per week. We now mention it at lines 176 to 178. • “The Grooved pegboard test description could be clearer.” Thank you for your comment. The test description is now improved following your recommendation on lines 235–239: “This test requires participants to pick up small metal pegs that have a key on one end and insert them into randomly oriented slots on the board by rotating the pegs into the correct position. The test is performed with each hand separately and the time required to insert twenty-five pegs into the slots is recorded” • “It might be worth making absolutely clear that while it might not be a characteristic of expertise it is open that it might be a characteristic of video game experience (or exposure of some sorts).” Specification were added in order to address your recommendation at lines 508 to 510: “While experience with video games may impact auditory and multisensory performance, we do not find evidence that auditory short-term memory is a characteristic of video game expertise”. • “Could be stated more clearly. The behavioural results observed here are not evidence that action video games impact on the dorsal pathway. They are simply consistent with the hypothesis that they do impact on the dorsal pathway.” Thank you for your comment. Details were added to better reflect this nuance at lines 530 and 531: “These results are also consistent with the growing evidence that action video game experience has an impact on the dorsal pathway”. • “Any thoughts why there might be such a difference between athletes and video game players on the 3D-MOT?” It is difficult to say for certain, but we this difference may be due to low power to detect a difference, which was not a concern for Faubert, 2013, as their sample size was ~10x larger. [Also, we think it is possible that our professional gamer are more like the elite-amateurs in sports (Olympic and NCAA). The gaming esport community does not have the same level of competitiveness then professional sports that have evolved in some cases over many decades of organized sports. Although these are speculations, we felt that it is best not to include it in the article. • “What was the question raised by Dye et al. (2009)?” Dye and colleagues wondered whether the advantages of video gaming are restricted to tasks involving only binary responses, or if they can generalize to more complex tasks with multiple response alternatives. The information was added in text on lines 577 to 579: “The different results provided by the d2 and Coding tests address a question raised by Dye, Green and Bavelier (2009), who wondered whether the advantages of video gaming are restricted to tasks involving only binary responses, or if they can generalize to more complex tasks with multiple response alternatives.” "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. A few papers studying healthy, first-degree relatives of people with borderline personality disorder (BPD) have found that this group presents attention and memory problems. However, current research has not analyzed their social cognition.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods.</ns0:head><ns0:p>We designed an age-, gender-, and education-level matched casecontrol study involving 57 people with BPD, 32 of their first-degree relatives, and 57 healthy controls in Spain in 2018-2019. All were assessed for social cognition and functioning using the Movie for Assessment of Social Cognition and the Social Functioning Scale; other potential confounders were also collected (marital status, occupation, and household variables). Results. There were differences in the social cognition domain of overmentalizing errors, with the BPD group scoring significantly higher than controls; however, there was no significant difference with relatives; in the social functioning domain of family relationships, with the controls showing the highest scores. Social engagement/withdrawal, interpersonal behavior, independence-competence, prosocial activities, full scale and categorization domains showed the same pattern: the BPD group had lower scores than their relatives and the controls. Relatives were significantly different from BPD patients in family relationships, social engagement/withdrawal and interpersonal behavior, as well as on the full Social Functioning Scale (both as a linear and categorical variable). However, only controls showed differences with relatives in family relationships.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions.</ns0:head><ns0:p>All in all, relatives show similar levels of social cognition and functioning compared with controls, and people with BPD show some alterations in different domains of both social cognition and functioning.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>INTRODUCTION</ns0:head><ns0:p>Borderline personality disorder (BPD) is a severe psychiatric disease that predominantly manifests in young adults through a pattern of instability in interpersonal relationships, selfimage, and affect, along with intense impulsivity <ns0:ref type='bibr'>(American Psychiatric Association, 2014)</ns0:ref>.</ns0:p><ns0:p>Epidemiological studies in the United States estimate its prevalence at 0.5% to 5.9% of the population <ns0:ref type='bibr' target='#b18'>(Lenzenweger et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b9'>Grant et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b17'>Leichsenring et al., 2011)</ns0:ref> , generating a high burden for public health systems <ns0:ref type='bibr' target='#b33'>(Soeteman et al., 2008)</ns0:ref>.</ns0:p><ns0:p>Social cognition refers to the abilities to perceive, interpret, and process social stimuli that guide social interactions <ns0:ref type='bibr' target='#b10'>(Green et al., 2008)</ns0:ref>. Alterations in these processes could cause difficulties in identifying others' emotions, thoughts, and intentions; these problems could cause different symptoms, such as intense fear of abandonment or dichotomous thinking and idealization <ns0:ref type='bibr' target='#b24'>(Prei&#223;ler et al., 2010)</ns0:ref>. Some studies relate the diagnosis of BPD with a disturbance in social cognition <ns0:ref type='bibr' target='#b20'>(Minzenberg et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b24'>Prei&#223;ler et al., 2010)</ns0:ref>, although there is controversy on this point, probably because of the sensitivity of the instruments used <ns0:ref type='bibr' target='#b7'>(Dziobek et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b1'>Arntz et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b24'>Prei&#223;ler et al., 2010)</ns0:ref>. On the other hand, when more naturalistic methods are used, like the Movie for Assessment of Social Cognition (MASC) <ns0:ref type='bibr' target='#b7'>(Dziobek et al., 2006)</ns0:ref>, the results more precisely support alterations in the social cognition of people with BPD <ns0:ref type='bibr' target='#b24'>(Prei&#223;ler et al., 2010)</ns0:ref>. Social functioning is a complex and multidimensional construct, encompassing a person's ability to achieve goals and play defined social roles, as well as to take care of oneself and enjoy leisure time <ns0:ref type='bibr' target='#b22'>(Mueser &amp; Tarrier, 1998)</ns0:ref>. Some authors note that social functioning covers different areas, including an individual's social cognition, skills, interactions, and behaviors <ns0:ref type='bibr' target='#b2'>(Beauchamp &amp; Anderson, 2010)</ns0:ref>. In terms of the relationship between these aspects and BDP, people with BPD display lower social functioning compared to the general population <ns0:ref type='bibr' target='#b13'>(Hill et al., 2008;</ns0:ref><ns0:ref type='bibr'>Gunderson et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b19'>Liebke et al., 2017)</ns0:ref>, and this difference is even more pronounced in the presence of other psychiatric comorbidities <ns0:ref type='bibr' target='#b21'>(Mosio&#322;ek et al., 2018)</ns0:ref>.</ns0:p><ns0:p>Although few studies have investigated healthy first-degree relatives of people with BPD, these family members present more attention and memory problems than the general population <ns0:ref type='bibr' target='#b26'>(Ruocco, Lam &amp; McMain, 2014)</ns0:ref>. We have not found studies that analyze social cognition in first-degree relatives of people with BPD, though these studies do exist in other mental pathologies like schizophrenia or bipolar disorder <ns0:ref type='bibr' target='#b16'>(Lavoie et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b25'>Reynolds, Van Rheenen &amp; Rossell, 2014)</ns0:ref>. The constant deficit in social cognition has been shown to be a characteristic feature of both of these conditions, extending beyond the period of crisis and constituting an endophenotypic marker in populations with a heightened genetic loading for the disorder, including first-degree relatives <ns0:ref type='bibr'>(Santos et al., 2017)</ns0:ref>. Moreover, self-perceived function incapacity is increased in both people with BPD and in their first-degree relatives, although in the latter group to a lesser extent and in fewer functional areas <ns0:ref type='bibr' target='#b26'>(Ruocco, Lam &amp; McMain, 2014)</ns0:ref>. We are not aware of any research studying social cognition in healthy, first-degree relatives of people with BPD. Thus, our objective was to determine whether diminished social cognition is a characteristic feature in the first-degree relatives of people with BPD.</ns0:p></ns0:div> <ns0:div><ns0:head>MATERIAL &amp; METHODS</ns0:head></ns0:div> <ns0:div><ns0:head>Study population</ns0:head><ns0:p>The study included people with BPD, their first-degree relatives (parents or children), and members of the general population without any mental illness, from health department 20</ns0:p><ns0:p>(Valencian Region, in the southeast of Spain). The catchment area of this health department is the entire population of Elche and Santa Pola, which had a registered population of 465,119 inhabitants in 2018. Manuscript to be reviewed Interview; <ns0:ref type='bibr'>Sheehan et al., 1998)</ns0:ref>. If more than one relative was willing to participate, they were both allowed. On the other hand, if the person with BPD did not have close relatives, if the relative(s) did not want to or could not participate, or if they presented an exclusion criterion, then we collected data only for the person with BPD. The controls were recruited from the companions of patients in the services of surgery, internal medicine, traumatology, neurology, and obstetrics. Selected controls were matched with the BPD study population for age, gender, and educational level. With regard to age, three controls had an age difference of one year with respect to the matched patient. They were assessed using the International Neuropsychiatric Interview to rule out any psychiatric disorders <ns0:ref type='bibr'>(Sheehan et al., 1998)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Study design and participants</ns0:head></ns0:div> <ns0:div><ns0:head>Variables and measurement</ns0:head><ns0:p>Social cognition was measured by means of the Spanish version of MASC <ns0:ref type='bibr' target='#b15'>(Lahera et al., 2014)</ns0:ref>. This is a naturalistic measure combining auditory, verbal, and emotional channels. For its administration, participants were asked to watch a short film in which four people appeared in different daily situations. During the movie, they had to answer 45 multiple-choice questions about the characters' feelings, thoughts, and intentions. In addition to the correct answer, there were three error categories: undermentalizing errors, wherein the person has a general-but underdeveloped-idea of what the other could be feeling or thinking; theory of mind absence errors, which occur when there is no connection between one's observation and interpretation; and overmentalizing errors; which stem from an excessive interpretation of another's state of mind <ns0:ref type='bibr' target='#b7'>(Dziobek et al., 2006;</ns0:ref><ns0:ref type='bibr'>Sharp et al., 2011)</ns0:ref>.</ns0:p><ns0:p>The scores took into account both the total number of correct answers and the total errors, and the latter were analyzed by subtype <ns0:ref type='bibr' target='#b15'>(Lahera et al., 2014)</ns0:ref>. A lower number of correct answers indicates a worse condition. This measure presents high test-retest reliability and high internal consistency in both its original English version <ns0:ref type='bibr' target='#b7'>(Dziobek et al., 2006)</ns0:ref> and its translation into Spanish <ns0:ref type='bibr' target='#b15'>(Lahera et al., 2014)</ns0:ref> Social functioning was measured using the Spanish version of the self-administered Social Functioning Scale (SFS, <ns0:ref type='bibr' target='#b34'>V&#225;zquez &amp; Jim&#233;nez, 2000)</ns0:ref>. The SFS assesses seven areas of social functioning in the previous three months on a scale of 70 to 129: social isolation/integration (0 to 15), interpersonal communication (0 to 9), pro-social activities (0 to 48), recreation (0 to 32), independence-competence (13 to 39), independence-performance (0 to 39), and employment/occupation (0 to 129). The score cutoffs group respondents in three categories: low-functioning (&lt; 95), medium-functioning (95-106), and high-functioning (&gt;106).</ns0:p><ns0:p>Two versions of the scale exist, depending on the information source used to understand the patient's social functioning: in the self-report version, patients themselves complete the questionnaire and provide information on their behavior; and in the informant report, relatives take on this role. Because we aimed to analyze all of the participants' behavior (people with BPD, relatives, and controls), we opted to use the self-report version. The English version shows adequate reliability, validity, and sensitivity <ns0:ref type='bibr' target='#b3'>(Birchwood et al., 1990)</ns0:ref>. In the Spanish version, internal consistency and test-retest reliability demonstrate some variability, but the results are still satisfactory <ns0:ref type='bibr' target='#b34'>(V&#225;zquez &amp; Jim&#233;nez, 2000)</ns0:ref>.</ns0:p><ns0:p>In addition, the following variables were collected: gender, age (in years), highest educational level attained (primary school, secondary school, and university), marital status (single, married/with stable partner, and separated/widower), occupation (active, unemployed, sick leave/pensioner, and student) and household composition (own family, family of origin, and single).</ns0:p><ns0:p>Participants were convened in groups of four or fewer in the classroom space at the General University Hospital of Elche. The facilities had a projector, screen, tables, and chairs.</ns0:p><ns0:p>Participants received an information sheet on the study and signed informed consent. They then underwent assessments with the MASC and SFS -always in that order and administered by the same professional, a psychiatric occupational therapist with more than 10 years of experience in the service.</ns0:p></ns0:div> <ns0:div><ns0:head>Sample size</ns0:head><ns0:p>The sample size was calculated to compare mean scores on the SFS scale among the three groups (ANOVA). To estimate the means in each group, we randomly selected 15% of the total sample, obtaining the following values: 114.4 for the control group; 115.9 for the relatives; and 101.3 for the BPD group. The estimated standard deviation (SD) was 10.9. According to these parameters and using a type I and type II error of 5%, we calculated a minimum number of 15 participants per group <ns0:ref type='bibr' target='#b5'>(Chow, Wang &amp; Shao, 2008)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical methods</ns0:head><ns0:p>Qualitative variables were described as absolute and relative frequencies, while quantitative variables were expressed as means (SD) or medians (interquartile range). To compare group characteristics, Pearson's chi-squared and ANOVA tests were applied. To assess differences in the scales administered to the three groups, median or ANOVA tests were used, depending on whether the variable of interest was continuous or discrete. Post-hoc analysis was carried out using the Bonferroni correction. For the multivariable analysis, linear or ordinal quantile (median) regression models were fitted to adjust the results for marital status, occupation, and household composition. All analyses were performed at a significance level of 5%, and confidence intervals (CIs) were calculated for each relevant parameter. The statistical software used was IBM SPSS Statistics 25 and R 3.5.1.</ns0:p></ns0:div> <ns0:div><ns0:head>Ethical considerations</ns0:head><ns0:p>Both the Research Commission and the Research Ethics Committee at the General University</ns0:p><ns0:p>Hospital of Elche approved the study (25 June 2018 and 26 June 2018, respectively). All participants were adequately informed of the study aims and methods, and if they agreed to take part, they signed informed consent before their inclusion.</ns0:p></ns0:div> <ns0:div><ns0:head>RESULTS</ns0:head><ns0:p>A total of 146 participants were included: 57 had a diagnosis of BPD, 32 were first-degree relatives of these people, and 57 were healthy controls. Tables <ns0:ref type='table' target='#tab_4'>1-2</ns0:ref> show the demographic characteristics of the three groups. Most of the participants in the BPD and control groups were women (91.2%), while a smaller majority were women in the relatives group (62.5%; p &lt; 0.001 in the total comparison and p = 0.002 when we compared relatives versus controls or patients).</ns0:p><ns0:p>Mean age was 33.4 years in the BPD and control groups, and it was 52.9 in the group of firstdegree relatives (p&lt;0.001 in both the global analysis and the comparison of relatives with BPD versus controls). Cases and controls showed a similar educational level (p &gt; 0.0056), with most having completed secondary school, while the relatives showed a lower level (p = 0.003 versus Manuscript to be reviewed controls and p = 0.005 versus patients in secondary school). There were also differences in marital status (p=0.006), occupation (p&lt;0.001), and household composition (p=0.004).</ns0:p><ns0:p>Specifically, the relatives were less likely to be single than patients (p = 0.002), more likely to be on disability or pension rolls than controls (p &lt; 0.001), and less likely to be living with their family of origin compared with patients (p = 0.001). Bivariable analysis of the questionnaires among the three groups (Tables <ns0:ref type='table' target='#tab_7'>3-4</ns0:ref>) showed statistically significant differences (p &lt; 0.05) in the number of correct MASC items (p=0.012)</ns0:p><ns0:p>and the MASC Overmentalizing errors (p=0.006). Controls scored higher on the first and lower on the second; relatives did not present statistical differences with the other groups (p &gt; 0.017).</ns0:p><ns0:p>All SFS dimensions showed differences as well (p &lt; 0.05), with the relatives group presenting higher scores than the BPD group. However, the only dimensions reaching statistical differences between relatives and BPD patients (p &lt; 0.017) were social engagement/withdrawal (p &lt; 0.001), independence-performance (p = 0.008) and recreation (p = 0.008). In contrast, relatives showed significantly higher overall scores on the SFS than BPD patients (p &lt; 0.001) and similar scores to the control group (p = 0.198). When the variable was categorized, likewise there was a significantly larger proportion of relatives compared to BPD patients with higher scores (p = 0.001).</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_9'>5</ns0:ref> shows the results of the multivariable analysis, assessing differences between groups in the questionnaires used, but adjusting for marital status, occupation, and household composition. After controlling for these confounders, using the relatives group as a reference, there were no significant differences in the MASC subscales. On the family relationships subscale of the SFS, the controls scored the highest (2, p &lt; 0.001), followed by the relatives (0)</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed and finally the cases (&#8722;2, p = 0.014). The SFS subscales of social engagement/withdrawal, interpersonal behavior, independence-competence, and prosocial activities, plus the full scale and the categorization, showed the same pattern, with the BPD group achieving lower scores than the relatives and the controls. However, the statistical differences (p &lt; 0.05) were in: social engagement/withdrawal (relatives vs BPD, p = 0.002), interpersonal behavior (relatives vs BPD, p = 0.019), SFS full scale (relatives vs BPD, p &lt; 0.001) and categorized SFS scores (relatives vs BPD, p = 0.003).</ns0:p></ns0:div> <ns0:div><ns0:head>DISCUSSION</ns0:head></ns0:div> <ns0:div><ns0:head>Summary</ns0:head><ns0:p>The present study investigated social cognition and functioning in people with BPD, their healthy, first-degree relatives, and a group of healthy controls. Our results show that relatives of people with BPD show some alterations in social cognition; however, results were not statistically significant, so there is insufficient evidence to support that this is a characteristic feature of BPD. With regard to social functioning, first-degree relatives showed a significant deficit on the family relationships subscale compared to controls and BPD patients, and in social engagement/withdrawal and interpersonal behavior compared with patients. We observed similar results when assessing the SFS full scale, as both a linear and categorical variable.</ns0:p></ns0:div> <ns0:div><ns0:head>Strengths and limitations</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The main strength of our study is its novel nature; we did not find any other paper in the literature examining social cognition in first-degree relatives of people with BPD. In addition, the statistical power was over 95% for testing differences in means in the calculation of the sample size, which increases the precision of our results.</ns0:p><ns0:p>To minimize selection bias, the sampling frame was the list of patients in the hospital coding database, not those attending the consult, as in previous studies <ns0:ref type='bibr' target='#b20'>(Minzenberg, Poole &amp; Vinogradov, 2006)</ns0:ref>. This is an important issue, as it increases the representativeness of the sample of people with BPD. Furthermore, the controls were selected using a population-based approach from the same geographical area, and they did not have any other pathology, especially mental disorders. With regard to information bias, data collection was undertaken by a single professional with experience administering the questionnaires used in this study, which enhances the reliability of the results obtained. Other studies have not taken the same precautions to limit this form of bias <ns0:ref type='bibr' target='#b15'>(Lahera et al., 2014)</ns0:ref>. In addition, we used internationally validated scales;</ns0:p><ns0:p>MASC <ns0:ref type='bibr' target='#b7'>(Dziobek et al., 2006)</ns0:ref> is much more naturalistic and precise than other measurement instruments. Moreover, by estimating the magnitude of effects through multivariable models, we could minimize the risk of confounding bias, as evidenced by the loss of statistical significance between the bivariable and the multivariable analysis after adjusting for other factors. On the other hand, it was not feasible to match the relatives for gender, age, or educational level, therefore we cannot rule out the influence of confounding in this group. Furthermore, we could not guarantee that the patients with BPD were in the same disease stage during assessment, which could alter the results and should be taken into account in future studies. Finally, we were unable to determine whether the origin of the alterations of function and the perception of Manuscript to be reviewed emotions were due to genetic or environmental factors, for example living with a person that had BPD.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparison with existing literature</ns0:head><ns0:p>We did not find any paper that assessed social cognition in first-degree family members of people with BPD, although there are similar studies in other mental disorders, like bipolar disorder and schizophrenia, that have reported alterations. In the case of schizophrenics, their relatives did not show important deficits in social cognition, but they did show lower performance than the general population <ns0:ref type='bibr' target='#b16'>(Lavoie et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b25'>Reynolds et al., 2014)</ns0:ref>. These results, together with the literature reporting that alterations in social cognition can be observed in patients 'in remission' <ns0:ref type='bibr' target='#b4'>(Bora, Yucel &amp; Pantelis, 2009)</ns0:ref> support the hypothesis that social cognition capacities may be related to a disorder's genetic component <ns0:ref type='bibr' target='#b8'>(Gottesman &amp; Gould, 2003)</ns0:ref>, and deficits in these processes could stem from genetic vulnerability in BPD <ns0:ref type='bibr' target='#b16'>(Lavoie et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b25'>Reynolds et al., 2014)</ns0:ref>.</ns0:p><ns0:p>Our results differ from those of other studies that have not found any diminishment of social cognition in people with BPD, for example in <ns0:ref type='bibr' target='#b24'>Prei&#223;ler et al.'s (2010)</ns0:ref> study, which used the 'Reading the Mind in the Eyes' test (RME), or <ns0:ref type='bibr'>Arntz et al.'s (2009)</ns0:ref> paper, which used the advanced test of theory of mind. On the other hand, <ns0:ref type='bibr' target='#b20'>Minzenberg et al. (2006)</ns0:ref> used the Buss-Durkee hostility index, finding a normal capacity for recognizing isolated facial or prosodic emotions but difficulties in recognizing integrated ones. These differences could be due to the psychometric tools used, as naturalistic scales like MASC <ns0:ref type='bibr' target='#b7'>(Dziobek et al., 2006)</ns0:ref> Manuscript to be reviewed cognition. We obtained higher scores in social cognition in the form of overmentalization errors, which coincides with <ns0:ref type='bibr'>Sharp et al.'s (2011)</ns0:ref> study in a sample of adolescents with borderline features.</ns0:p><ns0:p>With regard to social functioning, our results differ from <ns0:ref type='bibr'>Ruocco et al.'s (2014)</ns0:ref>, where relatives reported greater functional limitations than controls in life activities and participation in society. However, in our study, despite the lower scores achieved by relatives compared to controls in some domains, significant differences were only apparent in family relationships.</ns0:p><ns0:p>Likewise, we found small but significant differences in our BPD group in the domains of social engagement/withdrawal, interpersonal behavior, independence-competence, prosocial activities, and on the full-scale SFS, similarly to <ns0:ref type='bibr' target='#b26'>Ruocco et al., (2014)</ns0:ref>, who reported that the probands showed higher levels of incapacity than their relatives and the controls in all functional domains: comprehension and communication, mobility, self-care, interpersonal relations, life activities (domestic, leisure, work, and academic activities), and participation in society. Finally, <ns0:ref type='bibr'>Liebke et al., (2016)</ns0:ref> used the same social functioning scale as we did, although their sample did not include first-degree relatives. Patients with BPD showed low social functioning, while in our sample they presented medium functioning. Likewise, in their study there were significant alterations in all domains in BPD participants compared to controls, while in our study the differences were not significant in the domains of recreation or employment/occupation. These differences could be due to the distinct cultural characteristics, as their study took place in Germany, while ours was in Spain. Finally, <ns0:ref type='bibr' target='#b32'>Skodol et al., (2005)</ns0:ref> used the Longitudinal Interval Follow-up Evaluation, and they found significant deficits in the domains of interpersonal behavior, prosocial activities, full scale, and occupation. However, it is difficult to draw a comparison with our results because of the different measures used.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Implications for clinical practice and research</ns0:head><ns0:p>We detected diminished social cognition skills in people with BPD, along with limitations in some domains of social functioning in both the people with BPD and in their first-degree relatives. These results could support development of interventions to reduce the deficits identified. In light of our findings, future studies are needed to determine whether a deficit in the domain of family relationships in healthy relatives influences the social functioning, social cognition, and/or the symptomology of people with BPD. Additional research is also needed to understand the pathophysiology of BPD, including the role of genetic and socioenvironmental factors.</ns0:p></ns0:div> <ns0:div><ns0:head>CONCLUSIONS</ns0:head><ns0:p>Our results show that healthy first-degree relatives of people with BPD present similar social cognition skills as healthy controls, with no genetic vulnerability related to BPD. The social cognition of people with this disorder demonstrates greater deficits in the form of overmentalization. Compared to patients, relatives showed significant differences in social functioning with regard to family relationships, social engagement/withdrawal and interpersonal behavior, and compared to controls, relatives showed differences in family relationships.</ns0:p><ns0:p>Otherwise, social functioning is quite similar between relatives and controls, while people with BPD show lower social functioning across many domains.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed Post-hoc analysis with the Bonferroni correction (p-values) of the sociodemographic factors in the three analyzed groups: people with borderline personality disorder, firstdegree relatives, and controls BPD, borderline personality disorder.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Multivariable analysis of the scales used in our patients, relatives and controls (coefficients with their 95% confidence intervals).</ns0:p><ns0:p>BPD, borderline personality disorder; MASC, Movie for the Assessment of Social Cognition; SFS, Social Functioning Scale. All the coefficients were adjusted by marital status, occupation, and household composition.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_9'>5</ns0:ref>: Multivariable analysis of the scales used in our patients, relatives and controls (coefficients with their 95% confidence intervals). </ns0:p></ns0:div> <ns0:div><ns0:head>Variable</ns0:head></ns0:div> <ns0:div><ns0:head>Linear regression</ns0:head><ns0:p>SFS (full scale) 0 -0.94 (-4.7 to 2.8) 0.627 -9.9 (-13.7 to -6.1) &lt;0.001</ns0:p><ns0:p>Ordinal regression (odds ratio) SFS (categorized) 1 1.24 (0.27 to 5.76) 0.780 0.14 (0.04 to 0.52) 0.003 BPD, borderline personality disorder; MASC, Movie for the Assessment of Social Cognition; SFS, Social Functioning Scale.</ns0:p><ns0:p>All the coefficients were adjusted by marital status, occupation, and household composition.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>&#8224;</ns0:head><ns0:label /><ns0:figDesc>Abbreviations: BPD, borderline personality disorder; MASC, Movie for the Assessment of Social Cognition; SFS, Social Functioning</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Sociodemographic factors in the three analyzed groups: people with borderline 2 personality disorder, first-degree relatives, and controls</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1 Variable</ns0:cell><ns0:cell>Controls N=57</ns0:cell><ns0:cell>Relatives N=32</ns0:cell><ns0:cell>BPD N=57</ns0:cell><ns0:cell>p-value</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>n (%) &#8224;</ns0:cell><ns0:cell>n (%) &#8224;</ns0:cell><ns0:cell>n (%) &#8224;</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Women</ns0:cell><ns0:cell>52 (91.2)</ns0:cell><ns0:cell>20 (62.5)</ns0:cell><ns0:cell>52 (91.2)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Educational level:</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Primary school</ns0:cell><ns0:cell>17 (29.8)</ns0:cell><ns0:cell>19 (59.4)</ns0:cell><ns0:cell>18 (31.6)</ns0:cell><ns0:cell>0.027</ns0:cell></ns0:row><ns0:row><ns0:cell>Secondary school</ns0:cell><ns0:cell>33 (57.9)</ns0:cell><ns0:cell>8 (25.0)</ns0:cell><ns0:cell>32 (56.1)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>University</ns0:cell><ns0:cell>7 (12.3)</ns0:cell><ns0:cell>5 (15.6)</ns0:cell><ns0:cell>7 (12.3)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Marital status:</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Single</ns0:cell><ns0:cell>18 (31.6)</ns0:cell><ns0:cell>4 (12.5)</ns0:cell><ns0:cell>26 (45.6)</ns0:cell><ns0:cell>0.006</ns0:cell></ns0:row><ns0:row><ns0:cell>Married/with stable partner</ns0:cell><ns0:cell>35 (61.4)</ns0:cell><ns0:cell>20 (62.5)</ns0:cell><ns0:cell>25 (43.9)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Separated/widower</ns0:cell><ns0:cell>4 (7.0)</ns0:cell><ns0:cell>8 (25.0)</ns0:cell><ns0:cell>6 (10.5)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Occupation:</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Active</ns0:cell><ns0:cell>37 (64.9)</ns0:cell><ns0:cell>12 (37.5)</ns0:cell><ns0:cell>16 (28.1)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Unemployed</ns0:cell><ns0:cell>5 (8.8)</ns0:cell><ns0:cell>4 (12.5)</ns0:cell><ns0:cell>20 (35.1)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Sick leave/pensioner</ns0:cell><ns0:cell>3 (5.3)</ns0:cell><ns0:cell>11 (34.4)</ns0:cell><ns0:cell>8 (14.0)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Student</ns0:cell><ns0:cell>12 (21.1)</ns0:cell><ns0:cell>5 (15.6)</ns0:cell><ns0:cell>13 (22.8)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Household composition:</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Own family</ns0:cell><ns0:cell>40 (70.2)</ns0:cell><ns0:cell>25 (78.1)</ns0:cell><ns0:cell>24 (42.1)</ns0:cell><ns0:cell>0.004</ns0:cell></ns0:row><ns0:row><ns0:cell>Family of origin</ns0:cell><ns0:cell>13 (22.8)</ns0:cell><ns0:cell>4 (12.5)</ns0:cell><ns0:cell>22 (38.6)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Single</ns0:cell><ns0:cell>4 (7.0)</ns0:cell><ns0:cell>3 (9.4)</ns0:cell><ns0:cell>11 (19.3)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Age (years), mean &#177; SD</ns0:cell><ns0:cell cols='4'>33.4 &#177; 10.7 52.9 &#177; 16.3 33.4 &#177; 10.7 &lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>3 &#8224; Unless otherwise noted.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>4 BPD, borderline personality disorder; SD, standard deviation.</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Post-hoc analysis with the Bonferroni correction (p-values) of the sociodemographic factors in the three analyzed groups: 2 people with borderline personality disorder, first-degree relatives, and controls</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1 Variable</ns0:cell><ns0:cell>Relatives vs</ns0:cell><ns0:cell>Relatives vs</ns0:cell><ns0:cell>BPD vs</ns0:cell><ns0:cell>Number of</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Controls</ns0:cell><ns0:cell>BPD</ns0:cell><ns0:cell>Controls</ns0:cell><ns0:cell>comparisons</ns0:cell><ns0:cell>Significance (&lt;p-value)</ns0:cell></ns0:row><ns0:row><ns0:cell>Women</ns0:cell><ns0:cell>0.002</ns0:cell><ns0:cell>0.002</ns0:cell><ns0:cell>&gt;0.999</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>Educational level:</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Primary school</ns0:cell><ns0:cell>0.006</ns0:cell><ns0:cell>0.011</ns0:cell><ns0:cell>0.839</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>Secondary school</ns0:cell><ns0:cell>0.003</ns0:cell><ns0:cell>0.005</ns0:cell><ns0:cell>0.850</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>University</ns0:cell><ns0:cell>0.750</ns0:cell><ns0:cell>0.750</ns0:cell><ns0:cell>&gt;0.999</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Marital status:</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Single</ns0:cell><ns0:cell>0.045</ns0:cell><ns0:cell>0.002</ns0:cell><ns0:cell>0.124</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>Married/with stable partner</ns0:cell><ns0:cell>0.919</ns0:cell><ns0:cell>0.091</ns0:cell><ns0:cell>0.061</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Separated/widower</ns0:cell><ns0:cell>0.024</ns0:cell><ns0:cell>0.072</ns0:cell><ns0:cell>0.508</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Occupation:</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Active</ns0:cell><ns0:cell>0.013</ns0:cell><ns0:cell>0.358</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>0.0042</ns0:cell></ns0:row><ns0:row><ns0:cell>Unemployed</ns0:cell><ns0:cell>0.717</ns0:cell><ns0:cell>0.021</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Sick leave/pensioner</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>0.025</ns0:cell><ns0:cell>0.113</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Student</ns0:cell><ns0:cell>0.532</ns0:cell><ns0:cell>0.418</ns0:cell><ns0:cell>0.821</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Household composition:</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Own family</ns0:cell><ns0:cell>0.417</ns0:cell><ns0:cell>0.001</ns0:cell><ns0:cell>0.003</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>Family of origin</ns0:cell><ns0:cell>0.235</ns0:cell><ns0:cell>0.009</ns0:cell><ns0:cell>0.068</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020) Manuscript to be reviewed PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Scores of the scales applied in the three study groups.It was not possible to carry out the median test due to the number of valid cases.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Abbreviations: BPD, borderline personality disorder; MASC, Movie for the Assessment of</ns0:cell></ns0:row><ns0:row><ns0:cell>Social Cognition; IQR, interquartile range; SFS, Social Functioning Scale.</ns0:cell></ns0:row></ns0:table><ns0:note>&#8224;PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Scores of the scales applied in the three study groups. It was not possible to carry out the median test due to the number of valid cases.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1 Item</ns0:cell><ns0:cell>Controls</ns0:cell><ns0:cell>Relatives</ns0:cell><ns0:cell>BPD</ns0:cell><ns0:cell>p-value</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>N=57</ns0:cell><ns0:cell>N=32</ns0:cell><ns0:cell>N=57</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>MASC, median (IQR)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Correct</ns0:cell><ns0:cell>31 (6)</ns0:cell><ns0:cell>27 (9)</ns0:cell><ns0:cell>28 (5)</ns0:cell><ns0:cell>0.012</ns0:cell></ns0:row><ns0:row><ns0:cell>Overmentalizing errors</ns0:cell><ns0:cell>6 (4)</ns0:cell><ns0:cell>8 (6)</ns0:cell><ns0:cell>8 (4)</ns0:cell><ns0:cell>0.006</ns0:cell></ns0:row><ns0:row><ns0:cell>Undermentalizing errors</ns0:cell><ns0:cell>6 (3)</ns0:cell><ns0:cell>6 (4)</ns0:cell><ns0:cell>6 (3)</ns0:cell><ns0:cell>0.23</ns0:cell></ns0:row><ns0:row><ns0:cell>Theory of mind absence errors</ns0:cell><ns0:cell>2 (3)</ns0:cell><ns0:cell>3 (2)</ns0:cell><ns0:cell>3 (3)</ns0:cell><ns0:cell>0.27</ns0:cell></ns0:row><ns0:row><ns0:cell>SFS domains, median (IQR)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Family relationships</ns0:cell><ns0:cell>10 (2)</ns0:cell><ns0:cell>9 (2)</ns0:cell><ns0:cell>7 (3)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Social engagement/withdrawal</ns0:cell><ns0:cell>13 (2)</ns0:cell><ns0:cell>12 (2)</ns0:cell><ns0:cell>9 (5)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Interpersonal behavior</ns0:cell><ns0:cell>8 (1)</ns0:cell><ns0:cell>8 (1)</ns0:cell><ns0:cell>7 (3)</ns0:cell><ns0:cell>&#8224;</ns0:cell></ns0:row><ns0:row><ns0:cell>Independence-performance</ns0:cell><ns0:cell>34 (8)</ns0:cell><ns0:cell>32 (10)</ns0:cell><ns0:cell>28 (10)</ns0:cell><ns0:cell>0.004</ns0:cell></ns0:row><ns0:row><ns0:cell>Independence-competence</ns0:cell><ns0:cell>39 (0)</ns0:cell><ns0:cell>38 (1)</ns0:cell><ns0:cell>36 (4)</ns0:cell><ns0:cell>&#8224;</ns0:cell></ns0:row><ns0:row><ns0:cell>Recreation</ns0:cell><ns0:cell>22 (8)</ns0:cell><ns0:cell>22 (8)</ns0:cell><ns0:cell>18 (7)</ns0:cell><ns0:cell>0.009</ns0:cell></ns0:row><ns0:row><ns0:cell>Prosocial activities</ns0:cell><ns0:cell>23 (11)</ns0:cell><ns0:cell>20 (12)</ns0:cell><ns0:cell>16 (16)</ns0:cell><ns0:cell>0.011</ns0:cell></ns0:row><ns0:row><ns0:cell>Employment/occupation</ns0:cell><ns0:cell>9 (1)</ns0:cell><ns0:cell>9 (1)</ns0:cell><ns0:cell>6 (8)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>SFS full scale, mean &#61617; SD</ns0:cell><ns0:cell cols='4'>114.5&#61617;5.5 112.6&#61617;8.4 102.4&#61617;11.6 &lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>SFS scores, n (%)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Low</ns0:cell><ns0:cell>0 (0)</ns0:cell><ns0:cell>2 (6.3)</ns0:cell><ns0:cell>12 (21.1)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Medium</ns0:cell><ns0:cell>5 (8.8)</ns0:cell><ns0:cell>4 (12.5)</ns0:cell><ns0:cell>20 (35.1)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>High</ns0:cell><ns0:cell>52 (91.2)</ns0:cell><ns0:cell>26 (81.3)</ns0:cell><ns0:cell>25 (43.9)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>2 &#8224;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Post-hoc analysis with the Bonferroni Correction (p-values) for the scores of the scales applied in the three study groups.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Item</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_8'><ns0:head>Relatives vs Controls Relatives vs BPD BPD vs Controls Number of comparisons Significance (&lt;p-value)</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>MASC</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Correct</ns0:cell><ns0:cell>0.080</ns0:cell><ns0:cell>0.887</ns0:cell><ns0:cell>0.005</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>Overmentalizing errors</ns0:cell><ns0:cell>0.347</ns0:cell><ns0:cell>0.842</ns0:cell><ns0:cell>0.002</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>SFS domains</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Family relationships</ns0:cell><ns0:cell>0.021</ns0:cell><ns0:cell>0.055</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>Social engagement/withdrawal</ns0:cell><ns0:cell>0.709</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>Independence-performance</ns0:cell><ns0:cell>0.832</ns0:cell><ns0:cell>0.008</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>Recreation</ns0:cell><ns0:cell>0.104</ns0:cell><ns0:cell>0.008</ns0:cell><ns0:cell>0.005</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>Pro-social activities</ns0:cell><ns0:cell>0.142</ns0:cell><ns0:cell>0.236</ns0:cell><ns0:cell>0.003</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>Employment/occupation</ns0:cell><ns0:cell>&#8224;</ns0:cell><ns0:cell>0.148</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>SFS full scale</ns0:cell><ns0:cell>0.198</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.017</ns0:cell></ns0:row><ns0:row><ns0:cell>SFS scores</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>9</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>Low</ns0:cell><ns0:cell>0.127</ns0:cell><ns0:cell>0.066</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Medium</ns0:cell><ns0:cell>0.717</ns0:cell><ns0:cell>0.021</ns0:cell><ns0:cell>0.001</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49128:1:1:NEW 17 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_9'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> </ns0:body> "

"Dear Dr Preda: Following the indications of the reviewers, we have adapted the paper to address the various comments and clarify the contents. We trust that the changes made are acceptable. Thank you for the opportunity to submit a revised version, which we believe has been improved by the reviewers’ suggestions. Yours sincerely, Prof. Antonio Palazón-Bru, PhD on behalf of all the co-authors. Reviewer 1 (Anonymous) Basic reporting 1. In table 3, BPD is spelt wrongly as BDP. We have corrected this typo. 2. It is unclear in Table 2 what the numbers in brackets are e.g. 31 (6). I understand that 31 is the number of people in a group. What does the (6) mean? For each variable, we indicated the meaning of these numbers. For example, in “SFS domains”: median (IQR). Experimental design 1. Throughout the tables 1 and 2, where there are omnibus p values that are significant when comparing the three groups, it would be important for the authors to analyse which of the paired comparisons between two groups are significant. This can be achieved by post-hoc tests e.g. Bonferroni correction after the chi-squared and ANOVA testing. For example, for any given comparison where the omnibus p value is <0.05: is the significant difference between controls and relatives? Is the significant difference between relatives and BPD patients? Is the significant difference between controls and BPD patients? This would more clearly answer the study question, about whether relatives are more 'similar' to controls or more 'similar' to BPD patients. We have performed the post-hoc analysis, providing data in new tables and reordering the others. Validity of the findings 1. Similarly, the results section of the text should be re-written to always focus on the results of the relatives when compared to controls, and also when compared to BPD patients. Comparisons focusing on the BPD patients, comparing them with controls, are not novel and not as relevant to the overall aim of the study. For example, 'relatives showed statistically similar scores in the MASC to BPD patients. Both relatives and BPD patients scored more poorly than controls'. For example: 'On the family relationships subscale of the SFS, the relatives scored better than BPD patients (p value xxx). However, the relatives scored worse than the controls (p value xxx).' For example ' On the SFS subscales of social engagement/withdrawal, interpersonal behavior, independence-competence, and prosocial activities, plus the full scale and the categorization, there were no statistically significant differences between relatives and controls. However, relatives scored better than BPD patients'. Thank you; we have revised the presentation of findings according to these suggestions. 2. Similarly, it would be important in Table 3 to change the structure: have the relatives scores 'set' at 0, and then present the coefficients of controls compared to relatives, then present the coefficients of BPD patients compared to relatives. Currently, looking at Table 3, it is not possible to compare relatives with BPD patients which would be of much more clinical interest than comparing controls with BPD patients. We have changed the reference group as you suggested. Reviewer 2 (Anonymous) Basic reporting Well written, appropriate referencing. Experimental design Novel study, with research question well defined and explained, and the rationale appropriately determined and cited. Thank you very much for your feedback! Ethical approval was provided, but no English translation was available, so this could not be evaluated. This point has been assessed by the PeerJ staff. Methods well described. Recruiting both parents and children of people with BPD caused issues with matching samples, and demographic group differences, However this is acceptable given the nature of the research and is addressed in the limitations. Measures and their selection, as well statistical analysis techniques were described in detail and easy to understand. Validity of the findings Limitations are well covered. No research is perfect, and does not need to be, and thorough addressing of limitations is key for transparency. The research group does this well. Conclusions are clear and appropriate, and further research paths are suggested. Thank you very much for your positive comments! Reviewer 3 (John Michael) Basic reporting The manuscript reports the results of solid study carried out a sound methodology and investigating a novel and important question: do the close relatives of individuals with BPD exhibit any signs of the difficulties in social cognition and interaction which are characteristic of individuals with BPD. This is relevant to attempts to better understand the aetiology, and hence also the treatment, of BPD. In addition, they report evidence of social-cognitive impairments in the BPD group which are consistent with previous research and thus contribute to firming up those previous findings. Thank you very much for your analysis! Experimental design One issue which may merit mentioning is that people with BPD do not always exhibit the same symptoms but, rather fluctuate between extremes and indeed also often exhibit no symptoms. This means that the results of the tests could depend on what phase they happen to be in during testing. One way to try to address this would be to attempt to trigger their symptoms, or to wait until they exhibit symptoms in order to test them. We have commented this point in Limitations. The authors state that the study has been carried out in accordance with the latest version of the Declaration of Helsinki, yet there is no information about the pre-registration. Please clarify. As we did not register our study, we have removed that phrase. Confidence Intervals for the ANOVAs do not appear in the table; perhaps add them? We have added the confidence intervals for the regression coefficients in Table 3 (Table 5 in the new version of the manuscript). Validity of the findings It is not straightforward that any potential impairments in interpersonal functioning of family members should be interpreted as evidence of a genetic component. A plausible alternative interpretation would be that living with a person with BPD can lead to such impairments — in particular among the children of individuals with BPD. This should be noted as a limitation. Following your comment, we have written this point as a limitation (Discussion). "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. Birds have an extremely well-developed acoustic communication and have become popular in bioacoustics research. A majority of studies on bird song have been conducted in the temperate zones where usually males of birds sing to attract females and defend territories. In over 360 bird species inhabiting mostly tropics both males and females sing together in duets. Avian duets are usually formed when a male and female coordinate their songs. We focused on a species with relatively weakly coordinated duets, with male solo as the prevailing vocalisation type. Methods. Instead of analysing a set of recordings spread over a long time, we analysed whole day microphone-array recordings of the Yellow-breasted Boubou (Laniarius atroflavus), a species endemic to West African montane rainforests. We described the structure of the solo and duet vocalisations and temporal characteristics of daily activity based on 5,934 vocal bouts of 18 focal pairs and their neighbours. Results. Birds had small, sex specific repertoires. All males shared three types of loud whistles functioning as song type repertoires in both solos and duets.</ns0:p><ns0:p>Females vocalised with five types of harsh, atonal notes with a more variable and usually lower amplitude. Three of them were produced both as solos and in duets, while two seem to function as alarm and excitement calls given almost exclusively as a solo. Solos were the most common vocalisation mode (75.4%), with males being more vocally active than females. Duets accounted for 24.6% of all vocalisations and in most cases were initiated by males (81%). The majority of duets were simple (85.1%) and consisted of a single male and female song type, but altogether 38 unique duet combinations were described. Males usually initiated calling at dawn and for this used one particular song type more often than expected by chance. Male solo and duet activities peaked around dawn, while female solos were produced evenly throughout the day. Discussion. Yellow-breasted Boubous is a duetting species in which males are much more vocal than females and duetting is not a dominating type of vocal activity. Duet structure, context and timing of daily production support the joint resource defence hypothesis and mate guarding/preventing hypotheses, however maintaining pair contact also seems to be important. This study provides for the</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Birds have an extremely well-developed form of acoustic communication and so have become one of the most popular models in bioacoustics studies <ns0:ref type='bibr' target='#b9'>(Catchpole &amp; Slater, 2008)</ns0:ref>. The overwhelming majority of studies on bird song have been conducted in the temperate zone, a region in which only a small proportion of bird species breed <ns0:ref type='bibr' target='#b51'>(Riebel et al. 2019)</ns0:ref>. Such research has been neglected in the tropics which is a region where extremely high bird biodiversity is observed <ns0:ref type='bibr' target='#b22'>(Greenwood, 2001)</ns0:ref>. This geographical bias contributed to the formulation of an incorrect definition of bird song -an elaborate vocalisation produced by males during the breeding season to attract mates and defend territories <ns0:ref type='bibr' target='#b9'>(Catchpole &amp; Slater, 2008)</ns0:ref>. However, recently <ns0:ref type='bibr' target='#b41'>Odom et al. (2015)</ns0:ref> showed that female song performance is much more common than once thought, especially in the tropics, and was likely ancestral in oscine species <ns0:ref type='bibr' target='#b40'>(Odom et al., 2014)</ns0:ref>. Although many songbirds are now classified as having female song, not many are truly monomorphic in singing <ns0:ref type='bibr' target='#b19'>(Garamszegi et al., 2005)</ns0:ref> with both male and female songs varying in acoustic rate, structure and complexity <ns0:ref type='bibr' target='#b49'>(Price, 2015)</ns0:ref>. What is more, in many songbirds males and females sing together. Duetting can be described as vocalisations initiated by an individual that has a consistent time lag between the vocalisation of another individual, with this pattern being reproduced in the same way over time <ns0:ref type='bibr' target='#b33'>(Langmore 2002)</ns0:ref>. In summary, duetting is essentially a collective behaviour consisted of initiation by an individual and response of vocalisations by a different individual <ns0:ref type='bibr' target='#b38'>(Logue &amp; Krupp, 2016)</ns0:ref>. Duetting has been described for over 360 species</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed across 50 different families of passerines and non-passerines <ns0:ref type='bibr' target='#b25'>(Hall, 2009)</ns0:ref>. Despite the growing interest in female song and duets, and the vast reviews on functions <ns0:ref type='bibr' target='#b25'>(Hall 2009)</ns0:ref>, there can be further for specific species, thereby adding to the general repertoire of knowledge being created <ns0:ref type='bibr' target='#b10'>(Dahlin &amp; Benedict, 2014)</ns0:ref>.</ns0:p><ns0:p>Research on duetting in birds has led to the formulation of many hypotheses trying to explain their functions. The historical development of these hypotheses was shown in a very detailed reviews by <ns0:ref type='bibr' target='#b23'>Hall (2004</ns0:ref><ns0:ref type='bibr' target='#b25'>Hall ( , 2009))</ns0:ref>. It was described that birds can gain different types of information through information conveyed to different receivers (partner, rivals or even predators) and this has evolved under cooperative or conflicting situations between partners <ns0:ref type='bibr' target='#b23'>(Hall, 2004)</ns0:ref>. As a result, these hypotheses have diversified the potential for a general explanation of duetting evolution and functionality. Moreover, many different functions are not mutually exclusive and there may be a diverse use of duets in different species <ns0:ref type='bibr' target='#b23'>(Hall, 2004)</ns0:ref>. For example, the sex recognition function <ns0:ref type='bibr' target='#b27'>(Hooker &amp; Hooker, 1969)</ns0:ref> may in fact act as a prerequisite for maintaining contact, synchronisation of reproduction, territory defence and so on.</ns0:p><ns0:p>We do not want to repeat and discuss all the possibilities, but rather indicate the most promising explanations which seem to be important for the study species. Maintenance of contact between paired individuals using duets was found in habitats with dense vegetation and was one of the earliest functions proposed (e.g. <ns0:ref type='bibr'>Thorpe &amp; North 1966;</ns0:ref><ns0:ref type='bibr' target='#b31'>Lamprecht et al., 1985;</ns0:ref><ns0:ref type='bibr' target='#b36'>Logue, 2005)</ns0:ref>.</ns0:p><ns0:p>Duetting for maintenance of contact should occur all year round <ns0:ref type='bibr' target='#b42'>(Odom et al., 2017)</ns0:ref>, whereas, if duets are used for reproductive synchrony, as suggested by <ns0:ref type='bibr' target='#b11'>Dilger (1953)</ns0:ref>, there should be a peak in activity around the nest building phase (e.g. <ns0:ref type='bibr' target='#b63'>Topp &amp; Mennill, 2008)</ns0:ref>. Mate guardingbehaviour which clearly involves a conflict situation -can also utilise duetting behaviour. If an individual responds to its partner in a duet it advertises its mated status. Individuals can also</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed answer a mate to guard paternity and deter rival males, as seen in male Rufous-and-white Wrens (Thryophilus rufalbus; <ns0:ref type='bibr' target='#b28'>Kahn et al., 2018)</ns0:ref>. Another explanation related to a conflicting situation is signal jamming avoidance, which was experimentally shown to determine structure of duets in one of the pair-living antbird species (Hypocnemis peruviana; <ns0:ref type='bibr' target='#b54'>Seddon &amp; Tobias, 2009)</ns0:ref>. The other group of proposed duet explanations belongs to the joint resource defence hypothesis, which assume that mated birds defend some resources, like a territory, together against outsiders <ns0:ref type='bibr' target='#b57'>(Seibt &amp; Wickler, 1977)</ns0:ref>. As with the aforementioned functions, one can expect a variety of male and female signalling strategies related to their locations, fighting abilities or mated status. For example, male and female birds may respond stronger to the same-sex intruder <ns0:ref type='bibr' target='#b36'>(Logue, 2005)</ns0:ref> or with equivalent intensity to both sexes like in Barred Antshrikes (Thamnophilus doliatus) <ns0:ref type='bibr' target='#b29'>(Koloff &amp; Mennill, 2013)</ns0:ref>. Several hypotheses are more or less directly related to the fact that duetting behaviour is more often found in tropical birds than temperate species. Therefore, explanations for duetting are largely based on the differences between temperate and tropical birds' biology <ns0:ref type='bibr' target='#b25'>(Hall, 2009)</ns0:ref>. Surprisingly, a recent broad-scale phylogenetic comparison revealed duetting evolved in association with the lack of migration, but not with sexual monomorphism or breeding in the tropics <ns0:ref type='bibr' target='#b37'>(Logue &amp; Hall, 2014)</ns0:ref>. Thus, despite increasing number of studies on duetting birds, there is still a great need for basic duetting data for unexplored species. One of the relatively well studied families of birds, with regards to duetting behaviour, are the bush-shrikes (Malaconotidae). These exclusively African birds are usually resident and are highly territorial, with a monogamous breeding system <ns0:ref type='bibr' target='#b26'>(Harris &amp; Franklin, 2010)</ns0:ref>, thus evolved under ecological conditions promoting the evolution of coordinated defence of resources <ns0:ref type='bibr' target='#b37'>(Logue &amp; Hall, 2014)</ns0:ref>. Among bush-shrikes, the most abundant is the genus Laniarius with 22 species. The majority of Laniarius species are monomorphic in colour, with the exceptions differing slightly in colour with paler females, <ns0:ref type='bibr' target='#b26'>(Harris &amp; Franklin, 2010)</ns0:ref> and utilise a skulking behaviour using their loud calls as the main sort of communication <ns0:ref type='bibr' target='#b59'>(Sonnenschein &amp; Reyer, 1984)</ns0:ref>. The Tropical Boubou (Laniarius aethiopicus), Crimson-breasted Gonolek (Laniarius atroccineus) and Slate-coloured Boubou (Laniarius funebris) have all been described as using duets for territorial defence and mutual mate guarding <ns0:ref type='bibr' target='#b20'>(Grafe &amp; Bitz, 2004a;</ns0:ref><ns0:ref type='bibr' target='#b65'>van den Heuvel, Cherry &amp; Klump, 2014;</ns0:ref><ns0:ref type='bibr' target='#b59'>Sonnenschein &amp; Reyer, 1984)</ns0:ref>. Although bush-shrikes have a relatively small acoustic repertoire they can alter the various parameters of their songs, such as the repetition of a note or the pitch, in order to produce more complicated or more simple duets <ns0:ref type='bibr' target='#b26'>(Harris &amp; Franklin, 2010)</ns0:ref>. <ns0:ref type='bibr' target='#b21'>Grafe, Bitz &amp; Wink (2004)</ns0:ref> explain that the Tropical Boubou may have a more precise way of communication due to the large number of duet types in its repertoire, compared to other boubou species.</ns0:p><ns0:p>The formulation of hypotheses that allow for unambiguous testing of duet functions requires prior knowledge of natural song variation. Hence, the use of vocalisations obtained through natural, unprovoked settings provides a baseline for the standard behaviours and can be used as a guide for further experiments <ns0:ref type='bibr' target='#b39'>(Mennill &amp; Vehrencamp, 2008)</ns0:ref>. Therefore, in the first step of our wider study we describe (1) the various vocalisation types produced by male and female Yellow-breasted Boubous (Laniarius atroflavus) and (2) we analyse how particular types of vocalizations are used as a solo or as part of a duet. Then, (3) we try to indicate the potential functions of the different vocalisation types based on natural vocalisation patterns. This is for vocalisations produced during within-and between-pair interactions. We used recordings from microphone arrays which allow for the analysis of whole day interactions between neighbouring pairs in the peak of the breeding season. The present study will increase the knowledge of duetting behaviours in a relatively well studied group of species. However, the adding of data on a new species adapted to live in a mountain rainy forest <ns0:ref type='bibr' target='#b13'>(Fry, 2020a)</ns0:ref>, should help to better understand factors affecting evolution of duetting in Laniarius species.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head><ns0:p>The Yellow-breasted Boubou is a sexually monochromatic (likely human perception only, see <ns0:ref type='bibr' target='#b48'>Osinubi et al., 2018)</ns0:ref> and socially monogamous bush-shrike, endemic to the montane forests of south-eastern Nigeria and western Cameroon <ns0:ref type='bibr' target='#b60'>(Stuart 1986;</ns0:ref><ns0:ref type='bibr' target='#b2'>Borrow &amp; Demey, 2001;</ns0:ref><ns0:ref type='bibr' target='#b13'>Fry, 2020a)</ns0:ref>.</ns0:p><ns0:p>Pairs inhabit dense undergrowth at the edge of clearings, secondary scrubs, small forest remnants and bamboo highlands above 1500 m above sea level <ns0:ref type='bibr' target='#b52'>(Riegert, P&#345;ibylov&#225; &amp; Sedl&#225;&#269;ek, 2004)</ns0:ref> in which they hold year-round territories. On Mount Cameroon Yellow-breasted Boubous can also be found at lower elevations, from 700 m above sea level <ns0:ref type='bibr' target='#b13'>(Fry, 2020a)</ns0:ref>. While there has been a description of Yellow-breasted Boubou vocalisations <ns0:ref type='bibr' target='#b52'>(Riegert, P&#345;ibylov&#225; &amp; Sedl&#225;&#269;ek, 2004;</ns0:ref><ns0:ref type='bibr' target='#b13'>Fry, 2020a)</ns0:ref>, little is known about their function or the context in which they are produced. Manuscript to be reviewed 2006). During the study, the habitats within the study area were a mosaic of montane forest patches, shrubby corridors and grasslands, with vegetable plantations below 1800 m above sea level. The study species was common in this area and was found inside larger forest patches, as well as in smaller remnants along streams. In these areas its population was continuous, and the Yellow-breasted Boubou vocalizations were one of the most common signals heard <ns0:ref type='bibr' target='#b50'>(Reif et al., 2006)</ns0:ref>. Detailed characteristics of the habitats in the study area is presented in Budka et al.</ns0:p><ns0:p>(2020).</ns0:p><ns0:p>The study was conducted at the beginning of the dry season (November-December), a time when most bird species in this region start to breed <ns0:ref type='bibr' target='#b58'>(Serle, 1981;</ns0:ref><ns0:ref type='bibr' target='#b64'>Tye, 1992;</ns0:ref><ns0:ref type='bibr' target='#b55'>Sedl&#225;&#269;ek et al., 2007)</ns0:ref>. During this period, we observed boubous building nests, laying and incubating eggs, and adult birds with young. Our own observations suggest that the breeding period may start at the beginning of November but that it can be elongated, as brood losses are quite common and so pairs may attempt to breed multiple times. Manuscript to be reviewed 06:14) and stopped recording at 19:00 (sunsets were between 17:58 and 18:01). This recording regime allowed us to obtain the entire vocal activity of the Yellow-breasted Boubou pairs. SM3 units recorded single channel soundscape with 48 kHz frequency sampling and 16 bits quality.</ns0:p><ns0:p>Altogether we collected array recordings for 18 focal pairs, covering eight separate areas, producing a whole day activity recording using an eight-channel microphone array setup (see Figure <ns0:ref type='figure' target='#fig_2'>S1</ns0:ref>). In each of the eight areas we recorded 1-3 focal pairs bordered with 1 or 2 recognised neighbours. We used an 8-channel microphone array to simultaneously record 3 pairs in 3 sessions, 2 pairs in 4 sessions and 1 focal pair in 1 session. These numbers reflected natural locations and sizes of particular territories and made it possible to place the microphones in a specific way so we could assign a particular channel(s) to a particular pair, based on the highest Manuscript to be reviewed -call -short and simple vocalisation, usually used in specific contexts such as alarm, begging;</ns0:p><ns0:p>etc.;</ns0:p><ns0:p>-song -vocalisations used for advertising mate or territory ownership;</ns0:p><ns0:p>-phrase -unit within a song, which may be an element (uninterrupted trace on sonogram) or set of elements occurring together;</ns0:p><ns0:p>-call bout and song bout -continuous call or song phrase output, where calls or phrases are separated by a silent interval (gap) lasting substantially longer than intervals between calls or phrases within the bout;</ns0:p><ns0:p>-call type and phrase type -version of call or song phrase, which could be defined on the basis of a specific (repeatable among individuals) structure;</ns0:p><ns0:p>-duet -coordinated singing by male and female so that their phrases alternate or overlap; in the study species duets usually consist of two or more phrases and form a duet bout, the equivalent of a 'duet train' like male-female-male-female etc. <ns0:ref type='bibr' target='#b3'>(Brown &amp; Lemon, 1979)</ns0:ref>;</ns0:p><ns0:p>-duet type -particular combination of the phrase types used by duetting birds;</ns0:p><ns0:p>-solo -song bout consisting of a single or a series of phrases produced in a sequence by one individual and separated from its other vocalisations by a substantially longer time than intervals within the bout; for the study species the same phrase types were used for solos and duets and so our definition of solo is equivalent to that proposed by <ns0:ref type='bibr' target='#b38'>Logue &amp; Krupp (2016)</ns0:ref> which is the initiation of a duet which remained without answer.</ns0:p><ns0:p>Each call and song bout can be characterised by its: duration (s), number of units (calls or phrases) produced by a male, female or both sexes and rate (units / min). For duets one may also calculate sex bias -defined here as a ratio of female to male phrases in a single duet bout. Sex bias reflects the contribution of a particular sex to a duet train <ns0:ref type='bibr' target='#b38'>(Logue &amp; Krupp, 2016)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Recognition of individuals. Assignment of vocalisations recorded of particular pairs was a multistep process. First, one person (AW) assigned each vocalisation bout to a particular song or call type category and to a particular pair (or non-focal neighbour) based on the highest amplitude on a particular channel (see Figure <ns0:ref type='figure' target='#fig_2'>S1</ns0:ref>). A simple map showing locations of each recorder (and respective channel on multi-channel file) in relation to territories position was used as an aid. For the majority of cases there was no problem as birds called from known positions within their territories and usually for a short time of a few seconds or for a few minutes (depending on the time during the day), with neighbours responding from their own positions. Birds from outside the recorded area appeared on a single (edge) channel and were easy to recognize as non-focal birds, due to the low amplitude presented on the array channels (see Figure <ns0:ref type='figure' target='#fig_2'>S1</ns0:ref>). In addition, a second person (TSO) was checking all identified bouts and in case of any doubts pointed by the first person was checking, in detail, characteristics of a particular bout. Doubts appeared usually because of the quality of songs, e.g. when target sound overlapped with signals of other species.</ns0:p><ns0:p>With male song phrases it was easy, despite a fully shared repertoire, to assign particular individuals as each male song from a particular category has its individual specificity reflected by small but consistent differences in frequency and duration. This time-frequency characteristic of male calls was already used in a methodological study on measuring individual identity in general <ns0:ref type='bibr' target='#b34'>(Linhart et al., 2019)</ns0:ref>. We compared the shape of phrases with the Peak Frequency Contour measurement of Raven Pro with measurements visible on screen and listening to the signal with slow speed. In case of doubts because of quality we also used measurements of frequency and time in order to compare phrases directly with earlier recordings of recognised males (Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>). Please notice, that for each session we only need to discriminate between a maximum of three focal males and 1-2 additional neighbours (assigned only to the category non-PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed focal pair). To our knowledge it is not possible to discriminate between females based on their simple time-frequency characteristics of songs (personal observations). Therefore, for female solos we assigned bouts solely based on the location in which they were produced. In such cases the preceding and followings bouts of neighbours or their own partner, make such assignments certain. Hence, the main potential error in our dataset may be a result of singing by focal females </ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Sound material analysed. In total, eight whole day recording sessions were analysed with 1-3 focal pairs recorded simultaneously (N = 18 pairs). This produced nearly 900 hrs of single channel recordings in which we found 5,934 call and song bouts which contained a total of 88,442 calls and song phrases. Among those bouts, 4,753 (80%) were assigned to the 18 focal pairs, while 1,181 (20%) were considered as being produced by neighbours from adjacent PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed territories outside the microphone array based on their appearance on particular channels of the recording.</ns0:p><ns0:p>Types of call and song bouts produced. As many as 75.4% of all bouts recorded (N = 4,472) were produced by a male (63.2%) or by a female (36.8%). However, among female solos 991 bouts (16.7% of all bouts) were call bouts or non-song vocalisations (more details below); duets accounted for 24.6% (N = 1,462) of all bouts. We found that the phrases of males and females produced in solos and duets were easy to categorise to a limited number of classes based on audio detection and visual inspection of spectrograms. Male solos. Males produced three whistle phrase types named High whee-oo, Low wheeoo and Hwee-hwee (Fig. <ns0:ref type='figure'>3</ns0:ref>). We found very consistent and statistically significant differences in proportions of these three phrase types used by all males as solos (GLMM, &#61538; &#61617; SE = -0.21 &#177; 0.014; z = -14.75, p &lt; 0.001). High whee-oo were produced the most often 57 &#177; 2.3 % (95%CI:</ns0:p><ns0:p>52.2-61.4%), then Low whee-oo 28 &#177; 1.8% (95%CI: 24.3-31.5%), and Hwee-hwee 15 &#177; 1. 2% used by all females 98.1 &#177; 0.01% (95%CI: 96.6-99.7%) while Rasps were found 1.9 &#177; 0.7% (95%CI: 0.33-3.39%) incidentally.</ns0:p><ns0:p>Duets. Yellow-breasted Boubous used the same phrase types for duetting as were used for solo vocalisations. Among 1,462 analysed duetting bouts, 85.1% were simple duets consisting of a single type of both male and female phrases. In 81% of cases duets were initiated by males and in 19% by females, however, even if a female initiated a duet, she usually reverted to following the male components of a duet. Even in duets where female phrases prevail over male phrases, female phrases were organised in time in relation to male elements which were always produced with a very constant rate (Fig. <ns0:ref type='figure'>5</ns0:ref>). The most typical male initiated duets used High whee-oo phrases (52%) then Low whee-oo (38%) and finally the Hwee-hwee phrase type</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed (10%). Female initiated duets most often used the Chock-series (42%), Kee-roo (35%) and Chock (20%) phrase types (Table <ns0:ref type='table'>S1</ns0:ref>).</ns0:p><ns0:p>When we focused on duets produced by the 18 focal pairs, we found that only one duet type was found in the repertoire of all pairs. It was initiated by females with Chock-series, then males produced High whee-oo and females overlapped these phrases with Kee-roo. Another few duet types which were common and found in repertoires of majority of pairs were also simple in structure and consisted of a single male and female phrase produced with time overlap. We found 16 duet types produced only once by a single pair and their uniqueness was that in a single duetting bout male and/or female switched between different phrase type. More details are in Table <ns0:ref type='table'>S1</ns0:ref>.</ns0:p><ns0:p>Duet initiation and answering analysis. If we assume that every spontaneous song phrase produced by a male or female has been answered by its mate, we may consider that our results reflect individual decisions <ns0:ref type='bibr' target='#b38'>(Logue &amp; Krupp, 2016)</ns0:ref>. In total, the study species tend to sing more in solos than duets. The three male phrase types remained unanswered by the female in 60.8-79.4% of cases (Table <ns0:ref type='table'>S1</ns0:ref>). The very common female phrase Chock-series remained unanswered by a mate in 81.9% of cases (Table <ns0:ref type='table'>S1</ns0:ref>). The female phrase types Kee-roo and Chock remained unanswered in 37.0% and 53.8% of cases, respectively. A completely different pattern was found for Keck calls as they were almost never answered (99.8%) by males. The Rasp calls were also rarely answered by males (76.0%), but they were also very rarely recorded.</ns0:p><ns0:p>We speculate that both Kecks and Rasps are not produced by females to form duets, but just when females are alarming (Kecks) or are highly excited (Rasps), males may also produce song phrases, but not in a coordinated way with the female (Table <ns0:ref type='table'>S1</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Temporal characteristics of male and female solos. Male solo bouts produced phrases with surprisingly similar average rates (Table <ns0:ref type='table'>1</ns0:ref>) which did not differ significantly between phrase types (GLMM, &#61538; &#61617; SE = 0.02 &#177; 0.795, z = 0.03, p = 0.976). On the other hand, the differences in the number of phrases within a bout (GLMM, &#61538; &#61617; SE = 0.07 &#177; 0.012, z = 5.92, p &lt; 0.001) and as a consequence the bout duration (GLMM, &#61538; &#61617; SE = 0.05 &#177; 0.015, z = 3.62, p &lt; 0.001) were significantly different between bouts produced with different phrase types (with the following pattern High whee-oo &gt; Low whee-oo &gt; Hwee-hwee). Thus, males produced solos with a very regular and fixed rate, but obviously changed bout duration by producing more or fewer phrases in a series. We did not record male solo bouts with more than a single phrase type.</ns0:p><ns0:p>A different situation was found for females (Table <ns0:ref type='table'>1</ns0:ref>). As was mentioned already, three types of vocalisations (Chock-series, Chocks and Kee-roos) were used by females as songs, while the remaining two were used as calls (Kecks and Rasp). In the majority of cases the Chock-series remained unanswered by males and they were never repeated one after another.</ns0:p><ns0:p>Chocks and Kee-roos produced as a solo had similar temporal organisation, typically with 4-8 notes in a bout (Table <ns0:ref type='table'>1</ns0:ref>) and they were used both to initiate duets and as a response to males during duets. Female solo song bouts of different types (Chock-series, Chocks and Kee-roos) significantly differed in number of phrases (GLMM, &#61538; &#61617; SE = 1.04 &#177; 0.204, z = 5.07, p &lt; 0.001), duration (GLMM, &#61538; &#61617; SE = 2.81 &#177; 0.192, z = 14.63, p &lt; 0.001) and call rate (GLMM, &#61538; &#61617; SE = -76.21 &#177; 3.901, z = -19.53, p &lt; 0.001). Keck calls were clearly different from other vocalisations, as they were produced with extremely high rates and sometimes in a very long series (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p><ns0:p>Rasps were recorded rarely, hence it is hard to temporally characterise them in more detail.</ns0:p><ns0:p>However, recorded examples indicate a sudden and irregular appearance (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed We found significant differences in the number of the male and the female phrases in duets initiated by male and female (GLMM, &#61538; &#61617; SE = -1.75 &#177; 0.114, z = -15.41, p &lt; 0.001). If duets were initiated by males, the number of male and female phrases within a duet was almost equal (Sex bias = 0.98 &#177; 0.014, 95%CI: 0.95-1.01). However, if females were initiating duets, they produced significantly more phrases than males (Sex bias = 2.67 &#177; 0.206, 95%CI: 2.27-3.08). Characteristically, males responded to females initiating duets with any type of their song phrase repertoire (Table <ns0:ref type='table'>S1</ns0:ref>). If a female initiated the duet with a Chock-series she always switched later in a bout to Chock or Kee-roo phrases (e.g. Fig. <ns0:ref type='figure' target='#fig_4'>4b</ns0:ref>, Table <ns0:ref type='table'>S1</ns0:ref>). Consequently, Chock-series were never used within a duet and never repeated one after another. Diurnal pattern of calling activity during breeding season. We found that Yellow-breasted Boubous started to vocalise on average 16 &#177; 6.1 mins before sunrise (95%CI 30.0-3.3 mins before sunrise; extremes from 61.1 mins before to 23.7 mins after sunrise) and that singing activity was the highest during the first two hours after sunrise (Figs. <ns0:ref type='figure'>6-7</ns0:ref>). Interestingly, birds were vocally active during the whole day, even between 11:00 and 15:00 when the temperature was usually quite high (24.8-31.0&#61616;C) in comparison to dawn (14.5-16.4&#61616;C; more details in Manuscript to be reviewed females were involved were small (Figs. <ns0:ref type='figure'>6-7</ns0:ref>), and we found no significant trends for number of female solos produced during the daytime (GLMM, &#61538; &#61617; SE = 0.07 &#177; 0.047, z = 1.54, p = 0.124) and duet bouts initiated by females (GLMM, &#61538; &#61617; SE = -0.02 &#177; 0.019, z = -0.85, p = 0.393). Thus, the main part of the overall variability of the singing activity during the day resulted from the activity of male solos and duets initiated by males (Figs. <ns0:ref type='figure'>6-7</ns0:ref>). The number of male song bouts significantly decreased during the day time (GLMM, &#61538; &#61617; SE = -0.32 &#177; 0.107, z = -2.95, p = 0.003), although male initiated duets did not differ significantly throughout the day (GLMM, &#61538; &#61617; SE = -0.10 &#177; 0.057, z = -1.78, p = 0.075).</ns0:p><ns0:p>We analysed who, and with what call type, first started vocalising in the morning. When we analysed 18 focal pairs, 78% of cases started with a male solo bout (and 9 of these 14 cases were males calling with the Hwee-hwee phrase type). Duets were observed as the first call bout in two pairs (11%; Kee-roo -Low whee-oo and High whee-oo -Kee-roo) as were female solos (two cases, 11% of Kecks). A long series of Kecks given by females were observed (personal observations) as an apparent response to a threat (human or squirrels close to nest) and so these two early cases of Kecks given by females might be interpreted as an unspontaneous dawn chorus but are more likely used as a response to a predator.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Here we provide the first paper to thoroughly explore the form and potential functions of the vocalisations, both in solo and duet form, of the Yellow-breasted Boubou. Through the use of a microphone array setup we have been able to analyse natural singing and calling behaviours of this species which provides basic information about the study species' vocalisations and can later be used to better interpret experimentally induced behaviours.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Repertoire of male and female vocalizations. We found that the Yellow-breasted Boubou has a small and sex specific repertoire of vocalisations that are usually used in both a solo and duet context. The males perform three distinct, tonal song phrases whilst the females vocalise with five atonal, harsh notes (Figs. <ns0:ref type='figure' target='#fig_3'>2-3</ns0:ref>). All three male song types were produced with a very repeatable pattern characterised by virtually fixed repetition rate both between phrase types and between males. Moreover, series of tonal songs produced by males were similar in solos and duets.</ns0:p><ns0:p>For females we recorded five types of sexually specific, atonal vocalisations, but only three of them seem to be functional song units (Chock-series, Chocks and Kee-roos). They were produced as solos or in duets, and when they were performed together with male vocalisations they were coordinated with the male output (Fig. <ns0:ref type='figure'>5</ns0:ref>). The common Keck call was given by females almost exclusively as a solo. Based on our visual observations this is an alarm call produced in the context of the potential presence of a predator, e.g. squirrel close to the nest or a human. The Rasp calls were recorded extremely rarely and if they appeared alongside a male call (14 bouts only) they were not synchronized precisely in time. Again, visual observations of such displays were found in most of the cases during playback experiments and suggest that Rasp is a high excitation call (A Wheldon et al., 2020, unpublished data testing response of focal pairs to different types of song). For example, they were recorded during a failed experiment where two adjacent pairs approached the speakers and met and chased each other aggressively (personal observation). To summarise, within the studied population males and females used sexually dimorphic vocalisations, both in the context of solo and duet singing.</ns0:p><ns0:p>Duets. The rules of duet organisation for the Yellow-breasted Boubou seem to be simple:</ns0:p><ns0:p>(1) both sexes may start a duet but males do so much more frequently than females; (2) males</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed always produce their phrases with a very regular time pattern while females add one or more phrases (Chock or Kee-roo) per single male call; (3) males and females initiated duets with any kind of their sex specific song phrases, but female Chock-series were never produced inside duets; (4) the majority of duets consist of one male and one female phrase type only; (5) females produce more phrases per male phrase if they started the duetting bout. So, the duets of the study species are sex specific, and male and female components are easy to identify even from a longer distance. As summarised in <ns0:ref type='bibr' target='#b23'>Hall's (2004)</ns0:ref> review, loud, locatable and sex-specific duet elements support the hypothesis for maintaining contact. Indeed, in the Yellow-breasted Boubou the environment is visually occluded and the duet could be initiated in order to locate a partner. On the other hand, they also produce duets when sitting right next to each other and so the maintaining contact hypothesis is not the only function <ns0:ref type='bibr' target='#b23'>(Hall, 2004)</ns0:ref>. The aforementioned duet properties are also described as being linked to guarding/preventing partner usurpation as well as for joint resource defence <ns0:ref type='bibr' target='#b23'>(Hall, 2004)</ns0:ref> and it seems Yellow-breasted Boubous also duet to convey information about their mated status and defence ability. Further research on this topic demands more detailed information about the duet characteristics in relation to duet context and the status of each bird. When assessing duet function, it is important to look at the different sexes. Yellowbreasted Boubous have a sex specific repertoire used for both solo and duet bouts Within the Laniarius genus, the situation of sex specific call types is complicated. For example, in some species like the Gabela Bush-shrike (Laniarius amboimensis) and Red-naped Bush-shrike (Laniarius ruficeps), males and females produce structurally similar phrases <ns0:ref type='bibr' target='#b15'>(Fry, 2020b;</ns0:ref><ns0:ref type='bibr'>c)</ns0:ref>.</ns0:p><ns0:p>However, the Tropical Boubou has strictly sex specific phrases when performing duets <ns0:ref type='bibr' target='#b20'>(Grafe &amp; Bitz, 2004a)</ns0:ref>, with males using tonal whistles and females producing both (sex specific) tonal</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>whistles and atonal notes. Another interesting bush-shrike is the Southern Boubou (Laniarius ferrugineus) in which males and females exchange phrase types when producing duets <ns0:ref type='bibr' target='#b67'>(Wickler &amp; Seibt, 1982)</ns0:ref>. With the absence of plumage or size dimorphism in certain duetting species, the ability to produce sex specific song types is one way that duet members can establish mate guarding or paternity guarding behaviours through sex recognition <ns0:ref type='bibr' target='#b23'>(Hall, 2004)</ns0:ref>. Both the Tropical Boubou and Crimson-breasted Shrike (Laniarius atrococcineus) are Malaconotidae species that utilise sex specific songs for mate guarding behaviours <ns0:ref type='bibr' target='#b20'>(Grafe &amp; Bitz 2004a;</ns0:ref><ns0:ref type='bibr' target='#b65'>van den Heuvel, Cherry &amp; Klump, 2014)</ns0:ref>, and so it is likely that the role of sex specific songs in the Yellow-breasted Boubou is a function of mate guarding behaviour in this monomorphic species.</ns0:p><ns0:p>If we compare all Laniarius species for which we have any data on vocal behaviour <ns0:ref type='bibr' target='#b69'>(Winkler, Billerman &amp; Lovette, 2020)</ns0:ref>, it seems that in the majority of cases males tend to produce whistle like phrases while females use (at least more often) atonal harsh notes. Such differences may suggest some functions which remain to be studied in detail. Tonal whistles are more efficiently propagated through dense forest habitat <ns0:ref type='bibr' target='#b1'>(Boncoraglio &amp; Saino, 2007)</ns0:ref> which, together with a higher amplitude, suggests that male phrases (A Wheeldon et al., 2020 unpublished data) are aimed at receivers at a further distance than the phrases produced by females. Although males share all phrase types they are clearly individually distinct <ns0:ref type='bibr' target='#b34'>(Linhart et al., 2019)</ns0:ref>. At the moment we do not know if this is also the case for females due to the complexity of the atonal harsh notes and limited amount of isolated female recordings in the field. However, experiments suggest that females can discriminate easily between their own mate and stranger males based on songs while there is no evidence that it works the other way around (own unpublished data). Such observations support the idea that differentiated structures of male and female song only reflect their functional distinctiveness.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Diurnal pattern of vocal activity. Knowledge of the temporal pattern of singing is another aspect of duetting behaviour necessary to understand its function. In this study we collected material representing a pairs' activity for an entire daily activity period during the peak of the breeding season. The analysed material was collected during eight different days between 12 Nov and 5 Dec, and for 18 pairs, hence it is rather unlikely that it is biased because of, for example, unusual weather or random events (e.g. losing brood). In general, the Yellow-breasted Boubou has a classic diurnal pattern of vocal activity, with a clear peak early in the morning and smaller peak in activity before dusk. Hence, this pattern was similar to that of other duetting species (e.g. White-eared Ground sparrow Melozone leucotis, <ns0:ref type='bibr' target='#b53'>Sandoval et al. 2016)</ns0:ref>. Several more detailed observations may help in linking their solos and duets with particular functions.</ns0:p><ns0:p>For example, Yellow-breasted Boubous do not exhibit any regular diel variation in any of the duet types used and peaks of diurnal activities were largely caused by male solos or any duets initiated by males. Similarly, the Tropical Boubou which produces up to 12 duet types did not exhibit any consistent variation of how these types are used during the day <ns0:ref type='bibr' target='#b20'>(Grafe &amp; Bitz, 2004a)</ns0:ref>..</ns0:p><ns0:p>For the Yellow-breasted Boubou, differences in durations of male and female unanswered solos suggest that males are regularly producing long bouts of solos, which are often responded to by neighbouring males (or pairs), whilst females are just trying to evoke a male response and stop calling shortly after if there is no response. Thus, we observed some kind of dichotomy of vocal activity for males and females. The only female vocalisation type to show any diel variation was the Keck call which is produced more often at the end of the day and with</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed a high calling rate. It seems that this call type is linked to an alarm context as it was often produced when human observers were close, and usually followed by the males' appearance (personal observations). Langmore (1998) explains that certain female call types may be used to coordinate the care of young, and so it may be that such vocalisations are produced by the females of the study species in order to synchronise certain behaviours with their mate.</ns0:p><ns0:p>Therefore, we do not rule out that this alarm call can also be used to summon the mate.</ns0:p><ns0:p>Females of the study species vocalise less than males in both solo and their initiated duets. The amount in which females sing in the tropics varies across species. Chirruping</ns0:p><ns0:p>Wedgebill (Psophodes cristatus) females vocalise at a lower rate than males <ns0:ref type='bibr' target='#b0'>(Austin et al., 2019)</ns0:ref>, this reduced rate of vocalising could be because females may only increase the amount of singing if a mate dies and so they need to be able to hold a territory independently <ns0:ref type='bibr' target='#b32'>(Langmore, 1998)</ns0:ref>. Conversely, in certain species the females have an increased singing activity compared to males. Slate-coloured Boubou (Laniarius funebris) females have a higher vocal activity due to aggressive encounters <ns0:ref type='bibr' target='#b66'>(Wickler &amp; Seibt, 1979)</ns0:ref>. In general, it seems that females singing more intensively than males are relatively rare. <ns0:ref type='bibr' target='#b12'>Dutour &amp; Ridley (2020)</ns0:ref> indicated only six such species in literature, and some of them concern duetting birds, for example the Cocos Flycatcher (Nesotriccus ridgwayi) <ns0:ref type='bibr' target='#b30'>(Kroodsma et al., 1987)</ns0:ref> and New Zealand Bellbird (Anthornis melanura) <ns0:ref type='bibr'>(Bruntin &amp; Li, 2006;</ns0:ref><ns0:ref type='bibr' target='#b5'>Brunton et al., 2008)</ns0:ref>. A reason for the variability in male and female vocalisation rates may be due to the hormonal balance in a species, with higher testosterone levels equating to increased vocal activity <ns0:ref type='bibr' target='#b40'>(Odom et al., 2014)</ns0:ref>. It appears the Yellow-breasted Boubou males are more vocally active than females as there is less need for aggressive solo displays by females and possibly a lack in intense female-female competition due to the monogamous life history strategy pursued. However, this interpretation must be treated with</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed caution, as it is known that in some closely related species, despite social monogamy the proportion of extra pair offspring could be substantial <ns0:ref type='bibr' target='#b65'>(van den Heuvel et al., 2014)</ns0:ref>. The dawn chorus acts as a communication network, whether signals are directed at an individual or are eavesdropped by other individuals <ns0:ref type='bibr' target='#b7'>(Burt &amp; Vehrencamp, 2005)</ns0:ref>. In the Yellowbreasted Boubou, the first calls at dawn are typically produced by males as solo calls, followed by female solos and duets. Surprisingly, the least frequently produced male phrase type, the Hwee-hwee, was usually used as the first vocalisation type in the morning. In Banded Wrens (Thryophilus pleurostictus), vocalisations that are produced in the dawn chorus are usually longer and have a higher bandwidth than other songs in their repertoire <ns0:ref type='bibr' target='#b62'>(Trillo &amp; Vehrencamp, 2005)</ns0:ref>. However, the Hwee-hwee phrase is not used exclusively as an early morning song and is not so structurally different from other male whistles. Yellow-breasted Boubou pairs hold stable, year-round territories and so it seems that the morning peak in male vocal activity followed by the females joining mates in duets might have a double function. It could be interpreted as something like checking the attendance list, which could be important for both within-pair as well as between-neighbour communication. Similarly in White-eared Ground-sparrows, solos are produced as the first vocalisation type as a way of demonstrating pair bond maintenance <ns0:ref type='bibr' target='#b53'>(Sandoval et al., 2016)</ns0:ref> however, it may also be a way of eliciting extra-pair copulations. Blackcapped Chickadee (Poecile atricapillus) females can compare the solo songs sung by males in the morning and use this to assess fitness <ns0:ref type='bibr' target='#b18'>(Gammon, 2004)</ns0:ref>. Yellow-breasted Boubou pairs are described as utilising a monogamous breeding system <ns0:ref type='bibr' target='#b26'>(Harris &amp; Franklin, 2010</ns0:ref>) and so it is likely that the first solos calls produced are a means of pair-bond maintenance or territorial defence, rather than to seek extra-pair paternity opportunities.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Yellow-breasted Boubous represent a duetting species in which males are more vocally active than females and duetting is not a dominating type of vocal activity. Males and females have distinctive, small and sex specific repertoires used both in solos and duets. There is a dawn chorus effect shown with male solos that can be interpreted as a form of within and between pair communication. We found some interesting differences in call types used for both males and females, suggesting that some calls may have specific functions. Our findings suggest that male solos and duets initiated by males are used for territorial defence. On the other hand, the female calling pattern with more effort being put into female-initiated duets suggests that their own calls are directed to own mates. For simplicity only three channels presented.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 5</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>amplitude. If focal pairs produced vocalisations, they were always recorded on three or more channels within the microphone array. Definitions used for describing vocalisations and sound analysis. Bird vocalisations are traditionally divided into songs and calls, and songs are usually louder and longer than calls and are involved in mate attraction and territory ownership (Catchpole &amp; Slater, 2008). However, Yellow-breasted Boubous produce a variety of vocal signals which are short, relatively simple and are not intuitively easy to classify into one of these two separate categories. Based on scarce literature data, our own preliminary observations and recordings, we tried to use song and call terms, together with the naming of vocalisations based on their structure in an onomatopoeic way (referring when possible to Fry, 2020a). In further terminology, describing vocalisations and duets in particular, we try to apply suggestions presented by Hall (2009) and Logue &amp; Krupp (2016) (see Fig. 1): PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>Temporal characteristics of duets. On average, birds used 22.3 &#177; 0.63 (95%CI: 21.1-23.5) phrases in a duet, and the average duet duration was 30.3 &#177; 0.89 s (95%CI: 28.5-32.0). The rate of duet phrases doubled those of solos, with an average of 68.0&#177;1.27 phrases per minute (95%CI: 65.5-70.5). Duets initiated by males were longer (on average 32.0 vs 24.7 s; GLMM, &#61538; &#61617; SE = 4.81 &#177; 2.042, z = 2.35, p = 0.019), but contained fewer phrases (21.4 vs 25.1; GLMM, &#61538; &#61617; SE = -3.57 &#177; 1.721, z = -2.07, p = 0.038) and had a lower rate (62.5 vs 94.6 phrases/min; GLMM, &#61538; &#61617; SE = -29.22 &#177; 3.229, z = -9.05, p &lt; 0.001) than female initiated duets.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='42,42.52,280.87,525.00,371.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='43,42.52,250.12,525.00,371.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='44,42.52,250.12,525.00,371.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head /><ns0:label /><ns0:figDesc>from outside of their own territories and assignment of such bouts to other pairs or non-focal birds. However, based on our observations of colour-ringed birds we assume that such cases, if To quantitatively characterise the production of male and female solos, as well as duets, basic descriptive statistics were used. We focused on the frequency ofdifferent vocalisation bouts produced by focal pairs, and quantified them by the number of phrases, duration and rate. In order to characterise the general daily pattern of vocalising we counted the number of different bout classes (e.g. call bouts, solos, duets etc.) produced by each pair during every hour of activity and with reference to the time of sunrise. In addition to descriptive statistics, we used generalized mixed models (GLMM) with a log-link function and Poisson error distribution, or identity link function and Gaussian error distribution, that included pair identity as a random factor, with time of day (hour in relation to sunrise), type of bout (solo, This study has exclusively observational character, and due to national law for this type of study formal consent is not required (The Act on Experiments on Animals (Disposition no. 289 from 2005). However, it was part of a wider project which as a whole was approved by the Local Ethical Committee for Scientific Experiments on Animals permit no. 16/2015, and Polish Laboratory Animal Science Association 1952/2015 certificate to TSO.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>and additional notes.</ns0:cell></ns0:row><ns0:row><ns0:cell>At this stage all calling bouts were selected from recordings and the following parameters</ns0:cell></ns0:row><ns0:row><ns0:cell>of Raven Pro were used: Window type: Hann, 1024 samples; 3 dB Filter Bandwidth: 67.4 Hz;</ns0:cell></ns0:row><ns0:row><ns0:cell>Time grid: overlap 50% giving Hop Size: 512 samples; Frequency Grid: DFT Size: 1024</ns0:cell></ns0:row><ns0:row><ns0:cell>samples giving 46.9 Hz &#215; 10.7 ms resolution of measurements.</ns0:cell></ns0:row></ns0:table><ns0:note>any, were extremely rare (personal observations). Sound analyses were done in Raven Pro v. 1.5 (Cornell Lab of Ornithology, Ithaca, NY; http://www.birds.cornell.edu/raven). All eight channels of the microphone array recordings were visually inspected (with auditory examination if necessary) and all call and song bouts were selected within the channel with the highest signal amplitude which came from the recorder placed in the song activity centre of a particular territory. Additional annotation columns were added to each recording in a standard way and, as a consequence, each selection containing a bout included the following information: time of the start and end (actual and in relation to sunrise and sunset time), category of bout (call, solo or duet), sex of initiator, type and number of units produced by each sex, pair identity (based on location and individual call characteristics) PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020) Manuscript to be reviewed Statistical analysis. duet), sex (male, female) and duet initiator (male or female) as explanatory effects. All statistical analyses were performed using the program STATA/MP 16.x (StataCorp, College Station, Texas, USA). Mean &#177; SE values and 95% CI are reported. &#119909; Ethical approval.</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head /><ns0:label /><ns0:figDesc>Kecks were rattle-like calls exclusively produced in a high rate series consisting of up to hundreds of single and very short notes. Visual observations clearly suggest that Kecks were produced in an alarm context, e.g. close to the nest. Chock-series were always produced as a Manuscript to be reviewed without consistent spacing in time, apparently different to the characteristics for the Chockseries. Rasps were very rarely produced (recorded only 33 times) and to our knowledge they are given in the context of high excitation (personal observations). Rasps were also relatively quieter in comparison to the other vocalisations, and because of that might, on occasion, have not been recorded. Therefore, we did not include them in most of the analyses. Based on both array recordings and observations of vocalising birds we cannot state that Kecks and Rasp calls are also produced by males.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>series of 2-14 calls with a high rate, almost without gaps between phrases (0.8-0.15 s) and with</ns0:cell></ns0:row><ns0:row><ns0:cell>up to 14 phrases in a row. Chocks had a similar but distinguishably different structure to chock-</ns0:cell></ns0:row></ns0:table><ns0:note>(95%CI: 12.8-17.8%). Female solos. Female vocalisations had a completely different acoustic structure, being atonal, harsh notes of differing durations. Most of them were classified as Keck (59.1%), Chockseries (32.5%), Chock (3.8%) and Kee-roo (3.5%) with very few examples of Rasp (1.1%) (Fig. 4). series, and were produced as a single, double or triple-unit as one phrase after another but PeerJ reviewing PDF | (2020:06:50332:1:2:NEW 14 Aug 2020) Unlike males, the proportions of phrase types (Chock-series, Chocks and Kee-roos) used for solo singing were very variable (GLMM, &#61538; &#61617; SE = -0.29 &#177; 0.054; z = -5.44, p &lt; 0.001) among females from the 18 focal pairs. Chock-series were the most commonly observed call type among female solos: 71 &#177; 8.7% (95%CI: 53.8-88.0%), then Kecks 16.8 &#177; 8.2% (95%CI: 0.3-33.4%), Kee-roos 12.2 &#177; 4.3% (95%CI: 3.1-20.7%) and finally Chocks 5.6&#177;2.7% (95%CI: 0.01-10.98%). If we consider female notes classified as functional calls, Kecks were commonly</ns0:note></ns0:figure> </ns0:body> "

"Rebuttal Letter Structure and functions of Yellow-breasted Boubou (Laniarius atroflavus) solos and duets Response: indicated in bold Editor's Decision MINOR REVISIONS For the most part this is a nice descriptive study; I agree with reviewer 2 that this type of study is important and appreciate this one. My main concern is that reviewer 1 feels that that methods need to be a lot clearer. Please follow all suggestions to do so. I agree with the comments of reviewer 2 regarding the length of the discussion (too long) and that some of the comparisons with others species in that section seem tangential. Response: We tried to shorten the manuscript. It was not so easy as we received, on one hand suggestions to shorten Discussion, while on the other hand, suggestions to include comparison to other species or explain in detail some methodological issues. First of all, we have reviewed all suggestions and made necessary changes in the manuscript along with giving details in this rebuttal letter. I hope we were able to address all mentioned issues. In the second step, we reviewed manuscript again and tried to removed or shorten some duplicated fragments or removed parts which seemed not to be crucial for perception of our results (and also suggested by reviewers). Finally, we completed some supplementary materials as was suggested by one of the reviewer, namely we included as supplementary material a piece of 8 channel recordings as a raven Pro screen capture and sound files used for preparing figures illustrating different song and call categories. Below we shortly answer to all editor and reviewers remarks: Please fix the following small errors. line 19 - “A majority” Response: Corrected line 42 - “study provides” Response: Corrected line 43 - “solos” Response: Corrected line 44 - I’m not following what the phrase “what allows for planning” is doing in this sentence. Response: Corrected, we removed the second part of the sentence line 99 - change “the recent” to “a recent” Response: Corrected line 133 - cut “The difference being” and replace “this” in the next line with “which” Response: Corrected line 234 - change “Fristly” to “First” Response: Corrected line 569 - missing an “in” after “Similarly' Response: Corrected Comments from the reviewers Reviewer 1 Basic reporting The paper is in general good writing; some sentences need more explanation (see comments). The paper is focused on a particular genus and the majority of the information is bias in that direction. I will recommend that authors use examples from other species in other tropical regions that study duets and diel patterns for example. The paper provides new important information for the group of investigators that study boubous, about duets as mentioned before, the discussion is biased to this group, so this makes this manuscript poorly attractive to other duet investigators. Response: We tried to do some compromise as it is hard to add new citations and simultaneously shorten the manuscript as was suggested by the another reviewer and the editor. Experimental design My main concern is with the method of multichannel recording. Authors need to explain more how they recognize each pair and individual. For example, they can provide actual Raven screen captures, where they signaling how they separated continuous pairs unambiguously. Response: We added such screen capture from Raven Pro as supplementary material. Additionally, they did not explain well how they solve the ambiguous ID and how that data was included in the manuscript. Response: We have clarified our explanations and we also added supplementary material (Raven screen captures) which should help understanding how bioacoustics analyses were conducted. Validity of the findings In general, the manuscript is well writing and results look interesting and well analyzed and presented. Comments for the author Line 48: add a reference Response: Corrected Line 50: add a reference Response: Corrected Line62-63: this sentence is unclear, what are you trying to summarize Response: We clarified this sentence. Line65-66: Although the information in this sentence is true, as is presented looks like that we do not know anything about duets. This appreciation is unfair, because a lot of work has been made to understand the functions, and we know very well some functions and codes. So, I recommend changing how this is presented to avoid intruding on a mistake in the duet knowledge. Response: The sentence was re-written as suggested by reviewer. Line 129-131: How using a microphone array you can describe male and female vocalizations and the context use? Response: microphone array enables to record simultaneously many individuals with known location of their song posts. This is the first step (and complementary to experiments) in which the collective character of duetting could be registered and analysed. As we present in the study, it is possible to calculate possibility of response to a particular song type by the partner, or analyse how neighbours responds to each other (this will be the topic of a next paper analysing the same dataset). Line 133-135: It is clear for you, but not for a reader. Please explain better this sentence. Response: We clarified this sentence. Line 135-137: Why this information about the other boubou species is important? Line 138-141: After read your introduction the information in this sentence is unclear. You need to explain more your idea that a small distribution range will affect duet behavior. Additionally, without a phylogenetic tree or information is hard to understand if your selected species is the base of the group or is more recent in origin. I say this because it is important to understand the phylogenetic relationship to disentangle the habitat effect from species distribution. Response (to both 135-137 and 138-141): We only meant here that adding basic information about practically not studied species from the genus which live in a restricted and specific habitat type may help in better understanding the song evolution in the group as a whole. We shorten this part of Introduction, Line 154: change sols for solos Response: Corrected Line 242-243: You need to explain more in detail how the information in this sentence. What are all recognitions? When occurred a doubt? What this means: was checking, in detail, characteristics of a particular bout? Response: We improved this sentence to make it more readable. By 'recognition' we mean any bout on recording with assigned information about song type, pair identity etc. If the first person who was checking recordings had any doubts because of quality etc., the second person was checking it carefully. This checking was comparing with vocalizations of potential neighbours, listening with slower speed what sometimes better help with recognizing presence of a short female chocks overlapping male song (H type especially). Line 243-246: You need to provide more information about this method, with detail enough for a reader that never read the Linhart et al., 2019 paper, could understand how you recognize male vocalizations in your recordings Response: We added information that males' song differed in frequency and duration even when shared structure of whistle. Line 248: What is a doubt? Response: Sometimes at the same time sang more individuals or even songs of different species overlapped with our target signal. Simply, if the first person was not sure about song type, assigning to particular territory etc., the second person put more effort to check if everything was verified correctly or not. There was not too many such 'doubts', I can estimate it in numbers as 1-2 per 2 hours (the whole-day recordings were divided into 2hrs pieces for analysis). The most of the cases concerned differentiation between female Chock and Kee-roo if they were produced from larger distance to all microphones or overlapped seriously with other signals. However, looking at the zoom in spectrogram and playing the portion signal with slower speed usually helped with decision. We clarified this in manusctipt. Line 252-255: Unclear Response: We simply do not know at the moment if there is any identity information in female vocalisations. At least the basic comparison of frequency and temporal characteristics shows that it is not possible to differentiated between females as easy as between males. It is however possible, that this is caused by the fact the females sing less and often their phrases are overlapped by males and it is hard to collect enough of high quality sound material for the analysis. We plan in the future to compare male and female vocalisations based on samples collected during playback experiments. We clarified this sentence. Line 257-258: How common this occurs, please add a number of observations, and how many times you observed this occurring? Response: We cannot present a number of such observations directly because of the reasons which are already mentioned with details in the manuscript. But we had birds with colour rings and quite large number of birds (altogether over 100 pairs) tested with playback, and we know that finding a female calling outside own territory in this period was very unlikely. Most female solos were observed from locations well within territory, which seem to be produced for evoking own-mate response (however, it could be also treated as blackmail of the partner). So even if a few such behaviours happened, they were assigned as to unknown-neighbour signal and should not affect significantly the analysed material from 18 focal pairs. Line 434: what is the meaning of: Calls or songs? Response: Traditionally in songbirds (temperate zone bias), songs are learned, given by males only and are more complex than calls, which are given by both sexes, simpler and inherited. Hence with a duetting species in which all vocal signals are relatively short and simple, and both sexes are active while singing together, the differentiation between songs and calls is not a trivial problem. We were presenting results of this study on many conferences and listeners often asked about what is song and what is call in this species. Therefore, we think that it is very important to present with details what kind of signals seem to be functional equivalent of (temperate birds) song and what seem to be rather a kind of call. However, we agree that maybe adding 'Calls and songs?' as a part of paragraph header was not the best idea and we removed it. Line 438: what is a stable repetition rate? Add more information about what is a repetition rate Response: Corrected Rate was defined in methods (line 230), it is just a number of units per minute. Line 440-441: Songs are very diverse in bird species. So, if you defined song as: “vocalisations used for advertising mate or territory ownership”, why to say that “male phrase types are the equivalent of song types”. This makes that a reader thinks that your song definition did not work. Delete this sentence. Response: Corrected. Line 449-452. You mention here visual observation but in methods is little or nothing about how much visual observation was conducted to associate vocalizations with behavior. Response: This statement concerns not observation of birds during microphone array recording but during any other observations done between 2008 and 2017. While array was recording, we intentionally did not disturb birds. Line 456-564: These sentences are results Response: The reviewer is right; this is some kind of summarizing results with words only (numbers are in Results sections). We think that this is a right place for them and starting point for discussion on the possible function. We think that moving this part to the end of results section will make it more difficult to perceive Line 490-492: This sentence is unnecessary for your discussion because did not provide support or discussion to your idea of the sex role in vocalizations. Response: We removed this sentence. Line 502-504: Add more information about why you suggest this. Response: We added a little bit more information about partner recognition and possible differentiation of male and female song. Line 509-515: Very speculative paragraph without support information. Delete it. Response: We removed this paragraph as was suggested, but I have to write that it is with great regret as this ideas were further tested experimentally and one of the manuscript on this topic is almost accepted. Line 525-527: Something that may help you to understand the diel patterns is to refer to other tropical species studies where was analyzed the diel pattern for solo and duet songs. Response: The problem is that there is really a few papers only on that topics and some of the species studied have so different behaviour (e.g. cooperative breeding and chorusing - Bradley & Mennill2009; or active by night - Odom & Mennill 2010), that it is really hard to compare them directly with the study species in a reasonable way. But we have added one citation and comment. Line 544: You need to provide examples of species where females vocalize more than males, it is important the contrast. Response: Actually, there was one example of species where females sing less than males (Psophodes cristatus) and one for the opposite situation (Laniarius funerbis). We added more examples from outside Laniarius sp. to extend Discussion to other duetting group as was also suggested earlier by reviewer. Line 551: Could be that the female vocalizes more in aggressive context because this reduces the probability that her male will be stolen for another female, as has been proposed in other species? Response: It is of course possible that in some species females may increase singing to defend her mates, and this is not an alternative explanation to the general relation between testosterone level and vocal activity (Odom et al. 2014). In this study particular case, i.e. analysis of natural singing activity among neighbours which know each other very well and are engaged in breeding activities we think that it would be hard to speculate about such link between female's activity and aggressive context. It would be easier with experimental approach, and we did such experiments which are under review now. We found that the main response of territorial pairs were always duets led by males, regardless of the intrusion was done with a males solo, female solo or duet (stranger songs used always for playback). However, we found that if a female was engaged in response more seriously, e.g. started response, came closer than male, produced more than 1 song phrase per 1 male phrase, the overall duetting response of a pair was longer and more intensive. So experimental approach shows that females may induced stronger response toward strangers in some situations. Line 556: They are truly monogamous or have extra-pair copulations? How EPC will affect the territorial behavior between females? Response: Unfortunately, there is no information available for the study species. In one of the close relatives but living in a different type of habitat, the Crimson-breasted Shrike (Laniarius atrococcineus), the number of extra-pair offspring could be substantial (14 cases per 74 tested offspring, van den Heuvel et al. 2014). We included this information in revised version of the manuscript. Reviewer: Scott MacDougall-Shackleton Basic reporting Some minor copy editing is needed to correct typos and improve the written English, but overall the basic reporting is clear and sufficient.   Raw data are provided. It would also be useful if example sound files were included as supplementary material so that readers could listen to the different vocalizations. Response: We have added as supplementary material the sound files used for preparing figures 3-5 illustrating song and call categories. Experimental design This is a descriptive study, rather than an experiment. The methods and analyses are appropriate. Data such as these are critical to facilitate future comparative studies. Response: Thank you. The only shortcoming is in Figure 2. Plots of PC analyses used to differentiate songs from different individuals are provided, but no details on these analyses are provided other than a very short descriptor on line 249.   If the PC analysis is described in another study I would remove the PC plots and just leave the spectrograms. Alternatively, the methods for the PC analysis could be added as supplementary information. Response: The Figure 2 has only an illustrative character but we have added provided more details for the PCA analysis used for preparing the plots. Validity of the findings Meets journal standards. Comments for the author Kroodsma and Byers (1991) wrote 'to experiment first is human, to describe first, divine.' Descriptive studies such as this one are the foundation on which experimental and hypothesis-testing work can be conducted. Thus I congratulate the authors on providing a thorough and detailed description of vocalizations for this duetting bird species.  Thank you again. The article is generally clear. I think the discussion could be shortened. There is quite a bit of comparison with other boubou species that can be removed to make this paper more focussed, and comparisons across species could be the topic of a comparative or review paper. Response: We have added in Discussion a few new comparisons with other species. However, as we are aware that the manuscript is already long we would rather not expand it any further. Minor comments:  line 121: it is not clear what 'species-adequate' means Response: Hypotheses often have a general character as were formulated to give a probable explanation of a phenomenon with (often silent) assumption that the phenomenon is uniform by meaning of its function and evolutionary origin. This is also the case for duetting in birds. There are some hypotheses proposed for explaining duetting, but there is no insurance that a hypothesis formulated based on observation on species A is also valid for species B. We removed “species-adequate” which seems to be confusing term. . line 144: monochromatic to human visual systems, not necessarily to birds Response: That’s true, we have added a relevant citation. l. 143: change sols to solo Response: Done. l 351 change sinfle to single Response: Done. l 364, the interpretation of these calls indicating alarm or excitement do not have any evidence provided. These interpretations should be removed, or clearly indicated as speculation. Response: Done. l. 424 how were these apparent threats observed based on songmeter recordings? Response: Such observations were done not while the array was recording. We clarified this in text. l. 426 remove extraneous text Response: Done. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Loss of tooth or enamel is widespread in multiple mammal lineages. Although several studies have been reported, the evolutionary mechanisms of tooth / enamel loss are still unclear. Most previous studies have found that some tooth-related genes have been inactivated in toothless and / or enamel-less mammals, such as ENAM, ODAM, C4orf26, AMBN, AMTN, DSPP, etc. Here, we conducted evolutionary analyses on ACPT playing a key role in amelogenesis, to interrogate the mechanisms. We obtained the ACPT sequences from 116 species, including edentulous and enamel-less mammals. The results shows that variant ORF-disrupting mutations were detected in ACPT coding region among nine edentulous baleen whales and three enamel-less taxa (pygmy sperm whale, aardvark, nine-banded armadillo). Furtherly, selective pressure uncovered that the selective constraints have been relaxed among all toothless and enamel-less lineages. Moreover, our results support the hypothesis that mineralized teeth were lost or degenerated in the common ancestor of crown Mysticeti through two shared single-base sites deletion in exon 4 and 5 of ACPT among all living baleen whales. D N / d S values on transitional branches were used to estimate ACPT inactivation records. In the case of aardvark, inactivation of ACPT was estimated at ~23.60-28.32 Ma, which is earlier than oldest aardvark fossil record (Orycteropus minutus, ~19Ma), suggesting that ACPT inactivation may result in degeneration or loss of enamel. Conversely, the inactivation time of ACPT estimated in armadillo (~10.18-11.30 Ma) is later than oldest fossil record, suggesting that inactivation of ACPT may result from degeneration or loss of enamel in these mammals. Our findings suggested that different mechanisms of degeneration of tooth / enamel might exist among toothless and enamel-less lineages during evolution. Our study further considered that ACPT is a novel gene for studying tooth evolution.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Dental innovations (such as differentiated dentitions and the evolution of tri-bosphenic molar) have been regarded as the great success of mammalian evolution and adaptation <ns0:ref type='bibr' target='#b37'>(Ungar, 2010)</ns0:ref>.</ns0:p><ns0:p>However, in spite of their importance for animal survival, teeth have been lost independently in multiple mammalian lineages, such as baleen whales and pangolins. In addition, some lineages have lost their outer enamel of teeth, such as pygmy sperm whale and dwarf sperm whale, aardvarks and species from Xenarthra <ns0:ref type='bibr'>(Davitbeal et al., 2009)</ns0:ref>. Tooth loss and / or enamel loss is one of the most important field for mammalian tooth evolution.</ns0:p><ns0:p>Amelogenesis imperfecta (AI) and tooth loss are the diseases that characterized by genetic defects in the formation of enamel and teeth. Multiple studies have suggested these genetic disorders are mainly caused by mutations of protein-coding genes functioned in formation of enamel and teeth <ns0:ref type='bibr' target='#b34'>(Stephanopoulos et al., 2005;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. Of these genes, three enamel matrix protein genes (EMPs, i.e., AMELX, AMBN and ENAM), two enamel proteases genes (MMP20 and KLK4), and some other related genes (e.g., C4orf26, AMTN, ODAM, <ns0:ref type='bibr'>ACPT, DSPP)</ns0:ref> have been confirmed to be candidate genes responsible for the diseases <ns0:ref type='bibr' target='#b6'>(Crawford et al., 2007;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. The variant inactivating mutations have been detected in these genes among toothless and enamel-less mammalian lineages. However, the mechanisms of tooth loss or enamel loss are still completely unclear.</ns0:p><ns0:p>It has been reported that ACPT was lower expressed in testicular cancer tissues compared to normal tissues and is regulated by steroid hormones <ns0:ref type='bibr' target='#b41'>(Yousef et al., 2001)</ns0:ref>. Besides, ACPT is also expressed in the brain and acts as a tyrosine phosphatase to modulate signals mediated by ErbB4 <ns0:ref type='bibr' target='#b12'>(Fleisig et al., 2004)</ns0:ref>. But, it is interesting to note that ACPT is expressed in secretory-stage ameloblasts <ns0:ref type='bibr' target='#b27'>(Seymen et al., 2016)</ns0:ref>, which can induce odontoblasts differentiation, mineralization of dentin, and amelogenesis <ns0:ref type='bibr' target='#b3'>(Choi et al., 2016)</ns0:ref>. Furthermore, there are some increasing evidences that homozygous missense variants of ACPT would lead to AI (e.g., c.226C&gt;T, p.Arg76Cys; c.746C4T, p.P249L) <ns0:ref type='bibr' target='#b27'>(Seymen et al., 2016;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. These evidences suggested that ACPT play an important role in amelogenesis.</ns0:p><ns0:p>All extant Mysticeti, descended from toothed ancestors, have no teeth and instead have baleen <ns0:ref type='bibr' target='#b36'>(Uhen, 2010)</ns0:ref>. Paleontological evidences have shown that mineralized teeth were lost in the common ancestor of crown Mysticeti. Moreover, a transitional stage from tooth to baleen in stem mysticetes have been revealed in some taxa bearing both teeth and baleen <ns0:ref type='bibr'>(Dem&#233;r&#233; et al.,</ns0:ref> PeerJ reviewing PDF | (2020:03:46572:1:1:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed 2008). Although many tooth-related genes have been revealed to be inactivated in various living mysticetes (e.g., AMBN, ENAM, AMEL, AMTN, MMP20, C4orf26 and DSPP) <ns0:ref type='bibr' target='#b9'>(Dem&#233;r&#233; et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b19'>Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b18'>Meredith et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b13'>Gasse et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b8'>Delsuc et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b33'>Springer et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b31'>Springer et al., 2019)</ns0:ref>, only the MMP20 are commonly inactivated across all the living baleen whales <ns0:ref type='bibr' target='#b18'>(Meredith et al., 2011)</ns0:ref>. This molecular evidence is consistent with earlier studies of paleontology and anatomy.</ns0:p><ns0:p>Despite its significance in mammalian enamel maturation, very little is known about ACPT evolutionary trajectory, relationship and function in mammals. To address this issue, we carried out a series of evolutionary analyses on ACPT, aim to uncover the evolutionary pattern of ACPT gene among mammalian lineages.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sequences mining and BLAST searches</ns0:head><ns0:p>The full-length coding sequences (CDS) of ACPT gene were extracted from the OrthoMaM v10b (http://orthomam2.mbb.univ-montp2.fr/OrthoMaM_v10b10/), ENSEMBL (http://www.ensembl.org/index.html?redirect=no) and NCBI (http://www.ensembl.org/index.html?redirect=no) databases (Table <ns0:ref type='table'>S1</ns0:ref>). ACPT of some whales were extracted from their Genome and SRA database of NCBI (Table <ns0:ref type='table'>S2 and S3</ns0:ref>). To further ensure the sites of inactivating mutation of toothless / enamel-less lineages, we used the CDSs of some representative placental species with well-annotated genomes (Homo sapiens [human],</ns0:p><ns0:p>Canis lupus familiaris [Dog], Bos taurus <ns0:ref type='bibr'>[Cow]</ns0:ref>, Echinops telfairi [Lesser hedgehog tenrec]) as queries including &#8764;50bp of flanking sequence on each exon. These sequences were used as queries to BLAST against toothless / enamel-less mammals to confirm the related inactivating mutation among baleen whales.</ns0:p></ns0:div> <ns0:div><ns0:head>Identification of inactivating mutations and functional sites and domains</ns0:head><ns0:p>The intact ACPT sequences (human, cow, tenrec) were used for identifying inactivating mutations (including mutation of initiation codons, frame-shift insertions and deletions, premature stop codons, splice sites mutation of intron / exon boundary [GT/AG], etc.). The inactivating mutation was identified based on BLAST searches against whole genomes of the relevant taxon from NCBI. The information on gene function, related key amino acid sites/domains was searched from UniProtKB/Swiss-Prot (http://www.uniprot.org/) and some references.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46572:1:1:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Alignment and phylogenetic analysis of mammalian ACPT</ns0:head><ns0:p>The 116 mammalian ACPT sequences were aligned based on their amino acid translations using online PRANK (https://www.ebi.ac.uk/goldman-srv/webprank/), and then deleted the gaps and non-homologous regions by using GBLOCK, then we corrected the multiple sequences alignment (MSA) in MEGA 7 <ns0:ref type='bibr' target='#b16'>(Kumar et al., 2016)</ns0:ref> by eye.</ns0:p><ns0:p>A gene tree was reconstructed by Mrbayes 3.2 <ns0:ref type='bibr' target='#b25'>(Ronquist et al., 2012)</ns0:ref> with a general time reversible (GTR) substitution model and rate heterogeneity modeled with a Gamma distribution, as conducted by MrModeltest version 2 using the Akaike information criterion (AIC) <ns0:ref type='bibr' target='#b21'>(Nylander, 2004)</ns0:ref>. In bayesian analysis, four simultaneous runs with four chains each were run for two million generations, sampling every 1000 trees. The first 25% of these trees were discarded as burn-in when computing the consensus tree. Tracer v1.5 software was used for checking convergence among chains in Bayesian analysis. When the ESS value is higher than 200, and the average standard deviation of spilt frequencies is lower than 0.01, we think it reach convergence level.</ns0:p></ns0:div> <ns0:div><ns0:head>Selection analyses</ns0:head><ns0:p>To evaluate the selective pressure of relevant branches leading to enamel-less and toothless lineages respectively, we implemented two ratio branch model to calculate the ratio of the nonsynonymous substitution rate (d N ) to the synonymous substitution rate (d S ) (&#969; = d N /d S ) by running CodeML in PAML 4.8a package <ns0:ref type='bibr' target='#b39'>(Yang, 2007)</ns0:ref>. We also recoded premature stop codons as missing data. Akaike information criterion (AIC) scores were used to select the most appropriate codon frequency model in CodeML. The ACPT gene tree exhibits different topological relationship compared to species tree, which may be unrelated to incomplete lineage sorting. In order to illuminate the detected signal reasonably and accurately, we used a species tree supported by some previous studies (Fig. <ns0:ref type='figure' target='#fig_3'>S1</ns0:ref>).</ns0:p><ns0:p>Refer to the methods of Springer and Gatesy <ns0:ref type='bibr' target='#b32'>(Springer and Gatesy, 2018)</ns0:ref>, several different branch categories were considered during selective analyses: (1) One category accounted for 'background' branches, which are lineages with intact teeth and an intact copy of ACPT. <ns0:ref type='table'>2020:03:46572:1:1:NEW 14 Aug 2020)</ns0:ref> Manuscript to be reviewed were degraded. ( <ns0:ref type='formula'>5</ns0:ref>) One branch categories were assigned for crown Mysticeti.</ns0:p><ns0:p>To better understand the selective pressure, a series of evolutionary models were compared in the likelihood. We first use the M0 model (Model A), which assumed that all branches in the phylogenetic tree has a common value, and compare it with the null hypothesis (Model B), which assumed that the common value in the phylogenetic tree is 1. To further understand whether the selective pressure on the lineages leading to pseudogenes was relaxed, we constructed Model C, which assumed that the branches with pseudogene had their own selection pressure &#969; 2 , while the background branches without pseudogenization was &#969; 1 , and then compared Model C with Model A. To further confirm whether the selective pressure on the lineages leading to pseudogenes was completely relaxed, we build the Model D, which assumed that the branches with pseudogene had their own selection pressure &#969; 2 = 1, while the selective pressure of background branches was &#969; 1 , and then compared Model C with Model D.</ns0:p></ns0:div> <ns0:div><ns0:head>Estimation of inactivation times</ns0:head><ns0:p>To estimate when ACPT was inactivated in different lineages of Placentalia, the method described in <ns0:ref type='bibr'>Chou et al. (2003)</ns0:ref> and <ns0:ref type='bibr' target='#b43'>Zhang et al. (2010)</ns0:ref> was used. Among the branches along which the gene became pseudogenes, this method presumes that gene evolves under a selective pressure similar to that in other species until it is inactivated. Next, this gene was presumed to accumulate both nonsynonymous and synonymous mutations at an equal rate. The K a / K s (K) value was assessed for this entire branch. The average K a / K s value was just for a part of the branch, where the gene was under selection (Ks). In addition, the K a / K s value for the rest of part of the branch where the gene evolved neutrally (K n = 1). Thus, the evolutionary time was weighted by the proportion, for which the gene was evolving under selection (T s / T) and neutrally (T n / T):</ns0:p><ns0:formula xml:id='formula_0'>K = K s &#215;T s / T + K n &#215;T n / T</ns0:formula><ns0:p>where T is the time since the split from the last common ancestor (LCA). By selecting the lower and upper bound of the confidence interval for the species divergence time T, which was obtained from TimeTree website (http://www.timetree.org/) to estimate a lower and upper bound for T n as:</ns0:p><ns0:formula xml:id='formula_1'>T n = T&#215;(K-K s ) / (1-K s )</ns0:formula><ns0:p>which provides an estimate of how long the ACPT gene has been evolving neutrally.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46572:1:1:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Characterization of ACPT sequence 120 sequences were obtained in this study. Due to the poor quality and low coverage of sequences among three pangolins (Manis javanica, M. javanica, Phataginus tricuspis) and one sloth (Choloepus hoffmanni), they were not used for subsequent analysis. However, some inactivating mutations (most of them are indels) were found in these sequences (Fig. <ns0:ref type='figure' target='#fig_4'>S2</ns0:ref>). The complete protein-coding sequence of ACPT in 116 taxa were used for alignment by PRANK.</ns0:p><ns0:p>Interestingly, one or more inactivating mutations (frame-shift mutation, initial codon mutation, premature stop codons, splice site mutations, etc.) were detected in another placental taxa without teeth or without enamel. (Fig. <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>, Table <ns0:ref type='table'>S4</ns0:ref>, Fig. <ns0:ref type='figure'>S3</ns0:ref>). For example, among toothless baleen whales, the initial codon mutation (n. ATG&#8594;GTG, p. M&#8594;V) was found in Balaenoptera borealis, B. physalus, B. musculus, Eschrichtius robustus, Eubalaena glacialis. Meanwhile, premature stop codons were found in B. acutorostrata and B. bonaerensis, frameshift indels were also found in baleen whales. Interestingly, two shared single-base site deletion was found on exon 4 and 5 of ACPT among all living baleen whales (Fig. <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>, Fig. <ns0:ref type='figure'>S3</ns0:ref>). The splice site mutations were detected in B. acutorostrata, Eubalaena japonica and Megaptera novaeangliae (Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p><ns0:p>Whilst, the premature stop codons were found in enamel-less D. novemcinctus and . afer.</ns0:p><ns0:p>Besides, frameshift indels were found in enamel-less Kogia breviceps.</ns0:p><ns0:p>Except for the species mentioned above, ACPT gene in other species whose teeth are intact were found to be activated. Nevertheless, some crucial amino acids mutation was found in toothed species, such as site 76 has been mutated (R76C) in Neophocaena asiaeorientalis.</ns0:p></ns0:div> <ns0:div><ns0:head>Reconstruction of ACPT gene tree</ns0:head><ns0:p>We recovered the ACPT gene tree with well-supported values by using Mrbayes method (Fig. <ns0:ref type='figure' target='#fig_4'>2</ns0:ref>).</ns0:p><ns0:p>In this gene tree, most of orders have been well reconstructed, and have high support rate, e.g., Cetartiodactyla, Perissodactyla, Eulipotyphla, Carnivora, Chiroptera etc. In addition, phylogenetic relationships of higher levels have also been well reconstructed, such as Laurasiatheria, Euarchontoglires, Boreoeutheria and Afrotheria. In this gene tree, bayesian posterior probability (PP) values of nearly 70% nodes are generally greater than 0.70. However, the relationship between some order level were relatively chaotic, such as Lagomorpha didn't cluster with Rodentia, but as the sister group of Primate; Chiroptera and Carnivora clustered together first, and then they became sister group of Perissodactyla.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46572:1:1:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Evolutionary analyses among toothless and enamel-less mammals</ns0:head><ns0:p>We carried out the PAML analysis to detect the selective pressure of toothless / enamel-less lineages, and found the selective pressure of these toothless / enamel-less lineages (including ancestral nodes, terminal branches and even the whole toothless / enamel-less group) was significantly higher than that of background branches. For example, the terminal branch of B. physalus: &#969; 1 =0.116, &#969; 2 =1.883; the terminal branch of M. novaeangliae: &#969; 1 =0.116, &#969; 2 =0.641; the terminal branch of E. robustus: &#969; 1 =0.116, &#969; 2 =2.688; the terminal branch of E. glacialis: &#969; 1 =0.116, &#969; 2 =0.503. A similar tendency was found in the terminal branches of other baleen whales, and further model comparison shows that the selective pressure of these branches had been completely relaxed. Whilst, much higher selective pressure was detected in the ancestral branch of stem mysticeti (&#969; 1 =0.120, &#969; 2 =0.436), even the clade of crown mysticeti (&#969; 1 =0.116, &#969; 2 =0.522). Meanwhile, higher selective pressure was detected among enamel-less lineages, such as the terminal branch of D. novemcinctus (&#969; 1 =0.116, &#969; 2 =0.206), the terminal branch of O. afer (&#969; 1 =0.116, &#969; 2 =0.414), and the terminal branch of K. breviceps (&#969; 1 =0.116, &#969; 2 =0.581). And the selective pressure of these branches had been completely relaxed, except for the terminal branch of K. breviceps (Table <ns0:ref type='table'>S5</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>ACPT inactivation dates</ns0:head><ns0:p>Estimates of inactivation times for ACPT based on d N / d S ratios and equations in Sharma et al. <ns0:ref type='bibr' target='#b28'>(Sharma et al., 2018)</ns0:ref>. The mean estimate for the inactivating time of ACPT on the branch of K. breviceps, D. novemcinctus and O. afer is 12. , respectively (Fig. <ns0:ref type='figure'>3</ns0:ref>). The mean estimate for the inactivation of ACPT on the Mysticeti clade is 14.05-16.30Ma.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head>ACPT is a novel candidate gene for studying mammalian tooth loss and enamel loss</ns0:head><ns0:p>The well-conserved gene structure in extant species indicates that this organization and arrangement might be present in the last common mammalian ancestor, which represented the vital function for organisms <ns0:ref type='bibr' target='#b17'>(Madsen, 2009)</ns0:ref>. In our study, the number of ACPT exons are 11 in placental mammals, which encode 427 amino acids (human ACPT sequence as the reference sequence). Our study collected that four residues (191N, 269N, 330N and 339N) of the extracellular region were for glycosylation, two residues (41H and 289D) directly involved in catalysis (from UniProt database). In addition, mutation in seven residues were reported that PeerJ reviewing PDF | (2020:03:46572:1:1:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed were responsible for AI <ns0:ref type='bibr' target='#b27'>(Seymen et al., 2016;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref> (Fig. <ns0:ref type='figure'>S4</ns0:ref>). Besides, there are three disulfide bond regions, namely, site 159 to 378, site 214 to 312, site 353 to 357. In fact, we detected not only teratogenic mutations but also inactivated mutations in these functional sites and domains. For example, enamel in finless porpoise were degenerated <ns0:ref type='bibr' target='#b14'>(Ishiyama, 1987)</ns0:ref>, mutation in site 76 (R&#8594;C) was found in N. asiaeorientalis. Previous research has confirmed that site 76 mutated into Cys (C) in human ACPT would lead to hypoplastic AI <ns0:ref type='bibr' target='#b27'>(Seymen et al., 2016)</ns0:ref>, from which this result further supported that teeth in finless porpoise were degenerated in molecular level. Of cause, most obvious characteristics of ACPT is that different types of inactivating mutations were found in toothless and enamel-less mammals, e.g., baleen whales, pangolins, sloths and so on (Fig. <ns0:ref type='figure' target='#fig_4'>S2, S</ns0:ref>). Therefore, ACPT could be a candidate gene for AI and studying mammalian tooth loss and enamel loss.</ns0:p></ns0:div> <ns0:div><ns0:head>Degeneration or loss of mineralized teeth in LCA of Mysticeti</ns0:head><ns0:p>Fossil evidence shows that the earliest ancestors of baleen whales possessed complete dentitions without baleen (such as Janjucetus and Mammalodon), and then evolved the baleen with teeth (such as Aetiocetus), until the lineages only baleen existed (e.g., Eomysticetus and Micromysticetus) <ns0:ref type='bibr' target='#b10'>(Fitzgerald, 2006;</ns0:ref><ns0:ref type='bibr' target='#b11'>Fitzgerald, 2010)</ns0:ref>. This supported the hypothesis that mineralized teeth were lost or degenerated in the common ancestor of crown Mysticeti. The fact is all living baleen whales lack teeth and instead baleen <ns0:ref type='bibr' target='#b36'>(Uhen, 2010)</ns0:ref>. However, the successive steps of vestigial tooth development was found in the fetal period of living baleen whales <ns0:ref type='bibr' target='#b7'>( Davit-B&#233;al et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b35'>Thewissen, 2018)</ns0:ref>. Molecular sequences of some specific genes, such as AMBN, ENAM, AMELX, AMTN, C4orf26 and ODAM, contain different types of inactivating mutations (e.g., stop codons, frameshift mutations, splice site mutations, etc.) in various mysticete species <ns0:ref type='bibr' target='#b9'>(Dem&#233;r&#233; et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b19'>Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b0'>Alhashimi et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b13'>Gasse et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b20'>Meredith et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b8'>Delsuc et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b31'>Springer et al., 2019)</ns0:ref>, which is consistent with loss-of-teeth in this group. But none of the inactivating mutations are shared by all living mysticetes species. Meredith et al. found a common insertion of CHR-2 SINE retroposon in MMP20 gene among all living baleen whales <ns0:ref type='bibr' target='#b18'>(Meredith et al., 2011)</ns0:ref>. It has been confirmed that mutations or deletions of MMP20 gene would result in thin and brittle enamel layer <ns0:ref type='bibr' target='#b2'>(Caterina et al., 2002)</ns0:ref>. Based on this result, they confirmed the hypothesis that mineralized teeth were lost or degenerated in the common ancestor of crown Mysticeti in the molecular level.</ns0:p><ns0:p>In this research, we also identified different inactivating mutations was detected among all PeerJ reviewing PDF | (2020:03:46572:1:1:NEW 14 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed mysticete species in ACPT gene, among which two shared single-base sites deletion were found on exon 4 and 5 of ACPT among all living baleen whales, which result in loss of function. Some studies have confirmed that ACPT gene is responsible for the development of enamel, and mutations can also lead to amelogenesis imperfecta <ns0:ref type='bibr' target='#b3'>(Choi et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b27'>Seymen et al., 2016;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. Similar to the result of Meredith et al. <ns0:ref type='bibr' target='#b18'>(Meredith et al., 2011)</ns0:ref>, our study furtherly supported the hypothesis that mineralized teeth were lost or degenerated in the common ancestor of crown Mysticeti.</ns0:p></ns0:div> <ns0:div><ns0:head>Is inactivation of ACPT neutral or adaptive?</ns0:head><ns0:p>The degeneration and / or loss of some morphological structures (such as limbs, teeth, and eyes, etc.) is a complex process that may result from the relaxation of the negative selection (neutral evolution), adaptive evolution (direct natural / positive selection to conserve energy and / or eliminate the disadvantageous effects of morphological structure), and / or gene pleiotropy (indirect selection on another traits) <ns0:ref type='bibr' target='#b38'>(Wang et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b42'>Zhang, 2008;</ns0:ref><ns0:ref type='bibr' target='#b15'>Krishnan and Rohner, 2017)</ns0:ref>. In some conditions, evolutionary change also results from differences in the reproductive success of individuals with different genotypes <ns0:ref type='bibr'>(Olson,1999)</ns0:ref>. <ns0:ref type='bibr' target='#b28'>Sharma et al. (2018)</ns0:ref> revealed that evolutionary gene losses are not only a consequence, but may also be causally involved in phenotypic adaptations. By estimating the inactivation time of pseudogenes, and comparing with oldest fossil records, we might be able to speculate whether gene inactivation is due to the adaptive or neutral selection after the loss of phenotype.</ns0:p><ns0:p>The record of enamel-degenerated armadillo fossil is significantly earlier than the estimated time of ACPT inactivation (10.18-11.30Ma) <ns0:ref type='bibr' target='#b5'>(Ciancio et al., 2014)</ns0:ref>, which suggested gene loss as a consequence of adaptation is likely the result of the relaxation of the negative selection. The results further supported the previous study <ns0:ref type='bibr' target='#b28'>(Sharma et al., 2018)</ns0:ref>. Besides, during the tooth evolution, some enamel-related genes (e.g., ODAM, ENAM, AMBN) also have gone through the similar evolutionary trajectory. By integrating different results from different methods, we may better understand the evolution of teeth and enamel. The inactivation time of ENAM (~45.5Ma) and <ns0:ref type='bibr'>ODAM (~40.43 Ma,</ns0:ref>) is much earlier than inactivation date for ACPT in armadillo <ns0:ref type='bibr' target='#b31'>(Springer et al., 2019)</ns0:ref>. ACPT inactivation is later than the fossil record, conversely, the inactivation time of ENAM is relatively earlier than the fossil record, which implied the various mechanisms of enamel loss in armadillo. Here, the inactivation of ENAM gene might be the causes of degeneration / loss of tooth enamel in armadillos, ACPT inactivation might be the Manuscript to be reviewed consequence of enamel loss.</ns0:p><ns0:p>For O. afer, even the inactivation date for ACPT (23.60-28.32Ma) is relatively younger than inactivation dates for ENAM ) and ODAM (~30.7Ma) in O. afer <ns0:ref type='bibr' target='#b19'>(Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b31'>Springer et al., 2019)</ns0:ref>. However, the estimated inactivation times by ACPT, ODAM and ENAM gene markers are all earlier than the oldest fossil record of aardvark (O. minutus, ~19Ma) <ns0:ref type='bibr' target='#b24'>(Patterson, 1975)</ns0:ref>. It should be suggested that gene loss may be the reason, not the consequence, for degeneration and / or loss of enamel. Moreover, due to the difference of species number, sequences quality and topological structure of species tree, the result of ACPT inactivation time is different from the result of Sharma et al. <ns0:ref type='bibr' target='#b28'>(Sharma et al., 2018)</ns0:ref>.</ns0:p><ns0:p>Cetacean includes both toothless Mysticeti and enamel-less Kogia. Relaxation of selective pressure was detected in both crown and stem Mysticeti (Table <ns0:ref type='table'>S5</ns0:ref>), which is consistent with the archaic toothless mysticete, namely, all stem Mysticeti were toothless. For example, Eomysticetus whitmorei, an edentulous species, was the geologically oldest mysticete <ns0:ref type='bibr' target='#b9'>(Dem&#233;r&#233; et al., 2008)</ns0:ref>. Molecular evidence shows ACPT has been lost its function in LCA of Mysticeti.</ns0:p><ns0:p>However, the inactivation time of ACPT in Mysticeti is 14.05-16.30Ma, which is much younger than the toothless mysticete (~30Ma) and the split of Mysticeti (~25.9Ma). Obviously, this is not consistent with the facts. It might be associated with relatively lower rates of frameshift accumulation during evolution of mysticete pseudogenes and long lifespan of mysticete <ns0:ref type='bibr' target='#b19'>(Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b18'>Meredith et al., 2011)</ns0:ref>. Whether adaptive or neutral, the shared single-base site deletion in ACPT fills an important gap in our understanding of the macroevolutionary transition leading from the LCA of crown Cetacean to the LCA of crown Mysticeti. Stem physeteroids (sperm whales) are known from the Miocene and had teeth with enamel <ns0:ref type='bibr' target='#b1'>(Bianucci and Landini, 2010)</ns0:ref>. Our results provide support for loss of the intact ACPT in K. breviceps.</ns0:p><ns0:p>ACPT was reported that play key roles in amelogenesis and differentiation of odontoblasts <ns0:ref type='bibr' target='#b3'>(Choi et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b27'>Seymen et al., 2016;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. Our result is in line with the enamel-less morphological structure in K. breviceps.</ns0:p></ns0:div> <ns0:div><ns0:head>CONCLUSIONS</ns0:head><ns0:p>We detected the different types of inactivated mutation in ACPT. Furthermore, selective pressure uncovered that the selective constraints have been relaxed among all toothless and enamel-less lineages. In addition, our results supported the hypothesis that mineralized teeth were lost or degenerated in the common ancestor of crown Mysticeti through two shared single-base sites (a) Dasypus novemcinctus (nine-banded armadillo), (b) Orycteropus afer (aardvark), (c) Kogia breviceps (pygmy spermwhale). The inactivation times of ENAM is from <ns0:ref type='bibr' target='#b19'>(Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b31'>Springer et al., 2019)</ns0:ref>.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>to terminal branches with unique inactivating mutations (baleen whales), which lacks teeth. (3) Three branch categories to terminal branches with unique inactivating mutations (pygmy sperm whale, nine-banded armadillo and aardvark), whose enamel has been vestigial. (4) One branch categories were assigned for stem Mysticeti where mineralized teeth PeerJ reviewing PDF | (</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46572:1:1:NEW 14 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46572:1:1:NEW 14 Aug 2020)Manuscript to be reviewed deletion in exon 4 and 5 of ACPT among all living baleen whales. Together with our evidence, ACPT might be a good marker to research the mechanism of tooth loss. By comparing the molecular time with the fossil time, we found there might be different mechanisms of degeneration of tooth / among toothless and enamel-less lineages during evolution, which is needed further researches.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 2 The</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> </ns0:body> "

"Dear Dr. Mu and colleagues: Thanks for submitting your manuscript to PeerJ. I have now received two independent reviews of your work, and as you will see, the reviewers raised some concerns about the research. Despite this, these reviewers are optimistic about your work and the potential impact it will have on research studying dentition in mammals. Thus, I encourage you to revise your manuscript, accordingly, taking into account all of the concerns raised by both reviewers. Please minimize over-speculation, particularly in light of an ambiguous fossil record. It appears that key organisms are missing in your comparative analyses (pangolin was brought up by both reviewers). Please add sequences from as many enamel-less and toothless mammals as possible (especially those for which sequenced genomes are available, like pangolin, sloth, and others). Your decisions for excluding (and overall taxon sampling) need to be justified, and analyses should be robust such that perturbations of your analyzed taxa do not drastically change your results and interpretations. Reviewer 2, in particular, has some expert advice on many aspects of your analyses. Please address these suggestions accordingly. Importantly, please ensure that an English expert has edited your revised manuscript for content and clarity. Please also ensure that your figures and tables contain all of the information that is necessary to support your findings and observations. Please make sure that all relevant literature is cited, and that your findings are compared to what is already established in the literature. Therefore, I am recommending that you revise your manuscript, accordingly, taking into account all of the issues raised by the reviewers. I look forward to seeing your revision, and thanks again for submitting your work to PeerJ. Good luck with your revision, -joe [# PeerJ Staff Note: Reviewer 2 declared a potential Conflict of Interest, and the Editor was aware of this when making their decision #] Reviewer 1 Basic reporting Mu et al. provide a potentially interesting study on the evolutionary loss of the ACPT gene in enamel-less and edentate mammals. Overall, I like the paper but there is much work that still needs to be done. The writing style needs work as does the English. Switching of tenses is also prevalent throughout paper - some examples are given below. —Thank you for your suggestion. There are some vital questions about gramma and sentences. We revised some parent mistake first, and then applied for English Copyediting Services to make the paper pleased and better to understand. Figures are fine but where did the images come from? —Many thanks to remind us the copyright of relative images used in this paper. Indeed, our group have published many papers about evolutionary research. Among these, we have already used some picture which were drawn by ourselves. Another related information, I indicated the source in figure legend. Experimental design The question is well defined but more investigation is required. What about Manis spp. (pangolins)? They are edentulous as well. There is no discussion on this group at all. Why are there no sequences from this species in this study given that two genomes have been sequenced? —Thank you. It’s a vital question. Indeed, pangolins, sloths, armadillos are special groups because of their loss/degeneration of tooth and enamel. In fact, we have blasted their sequences of these species before. However, due to the poor quality and low coverage of the sequences among these species, we did not display the results in the article, as well as no any description. Now, we added the related results of pangolins (three species) and sloths, the results are exhibited in supplementary files. At the same time, some discussion was shown in the main text. The related sentences were highlighted by yellow. Validity of the findings I question, whether or not there is anything known about different isoforms of ACPT. This obviously could directly impact results of this study if there is evidence of an isoform that excludes exon 4 and 5 or any other exons that have deleterious mutations. If there is nothing known than that should be stated as well. —Thank you. There are another two isoforms of ACPT that excludes exon 4 and 5 or any other exons, you can obtain from UniProt Website (https://www.uniprot.org/). But now, we know little about the function of these two isoforms. However, there are many key domains and sites, which play essential role in ACPT basic function, as well as, it will give rise to amelogenesis imperfecta, such as site 111, 128 and 133. Besides, site 159 to 378 is the disulfide bond which include 25 amino acids of exon 5 (site 151 to 183, 33 amino acids in total). I find the whole section 'Is inactivation of ACTP neutral or adaptive' to be very speculative. Dating methods between the different studies used both in this paper and others are not the same. This might also be influencing the discussion in this section - the assumptions of the equations will strongly affect the resulting date estimates. This section is also assuming that the oldest describe fossils are indeed the oldest representative of that lineage which we know is probably not the case given the incompleteness of the fossil record. —Thank you for your suggestion. For some enamel-related genes (e.g., ODAM, ENAM, AMBN), they have gone through the similar evolutionary trajectory. Even the data from different researches which used different methods to estimate the inactivation time, which also might be influencing the discussion. However, it might reflect the evolution of teeth to a certain extent. By integrating different methods, we may better understand the evolution of teeth and enamel. Besides, like you said, fossil evidence is indeed incomplete, but so far, we can only discuss it based on existing fossil evidence, and similar methods have been previously reported in the literature. Of course, we will continue to pay attention to the follow-up research, as far as possible to improve the research. Comments for the author Italicize Amelogenesis imperfecta throughout paper —Thank you. We’ve revised according to your suggestion and highlighted by yellow. line 48: etc. not needed —Thank you. We have deleted. line 49-50: Awkwardly written —Thank you. I read this sentence again, it is much better to delete. line 77: Not necessarily true. ACTP could play an important role in amelogenesis but simply being pseudogenized does not guarantee that —Thank you for your advice. I made an arbitrary inference. I revised the related sentence by using proper expression. line 78: delete 'To our knowledge' —Thank you. We have deleted. line 79: delete 'where instead of' replace with 'and instead have' —Thank you. We have revised. line 111: Alignment and phylogenetic analysis of mammalian ACPT No mention of checking for convergence among chains in Bayesian analysis. Why a 50% majority rule tree? —Thank you for your reminding. Indeed, we checked for convergence among chains in Bayesian analysis by using Tracer v1.5 software. We forgot to describe the analysis procedure, the relative sentences were added in main text, and highlighted by yellow. In addition, we re-collated the data and found that the “50% majority rule tree” is not our preset conditions. We are very sorry for this mistake. line 129: do you mean 'related' not 'unrelated' —Thank you. It is “related”. We have revised. line 151: Estimation of inactivation times This section is not properly cited. The method Sharma et al used was published by two other studies - see the paper for details. —Thank you for your reminding. I have read and added the related references. line 219: I'm not following this sentence —I am sorry for confusing you. I have revised this sentence. line 222: ' Our study highlighted that four 223 residues (191N, 269N, 330N and 339N) of the extracellular region were for glycosylation, two 224 residues (41H and 289D) directly involved in catalysis. ' Where were the methods for this result or what paper did this come from?? —Sorry for losing the important information. I obtained the information about these sites from UniProtKB/Swiss-Prot (http://www.uniprot.org/) and some relative references. I have added related statements in the methods section of the article, and highlighted the sentence. line 238: replaced 'showed' with 'shows' - this paper —Thank you. We have revised. line 304: replace 'Furtherly' with 'Furthermore' —Thank you. We have revised. Italicize species names throughout —Thank you. We have revised. Italicize gene names throughout —Thank you. We have revised. Reviewer 2 Basic reporting Generally this is fine. The authors should get help to fix English grammar, vocabulary usage, conjugation of verbs, nouns as adjectives, etc. throughout the manuscript. The text is not so far off but does need extensive work in this context and is pretty rough in parts in terms of grammar. I generally do not make these sorts of changes in manuscript ad hoc review. —Thank you for your suggestion. We applied for English Copyediting Services to promote this paper. Experimental design The experimental design is generally fine in terms of methods, but additional sequences should be included from various enamel-less and toothless mammals that have sequenced genomes (pangolin, sloth, and perhaps others). —Thank you for this valuable question. We have done some analyses about these enamel-less/toothless species, such as blast their sequence. However, because of the poor quality and low coverage of the sequences, we did not display the results in the article, as well as no any description. According to your suggestion, we added the related results of pangolins (three species) and sloths, the results are exhibited in supplementary files. At the same time, some discussion was shown in the main text. The related sentences were highlighted by yellow. Validity of the findings 1) The authors should seek to clearly note what Sharma et al. (2018) noted about inactivation of ACPT in mammals with no teeth or enamel and distinguish this clearly from what this new study shows relative to that earlier study that originally documented the gene knockouts in mammals without teeth or enamel. For example, extending analyses to more mysticete whale species and to pygmy sperm whale, etc. and inference of inactivation times. Did Sharma et al. (2018) estimate inactivation times as well? If so, how do dates and error bars on dates differ? —Thank you. It’s a very valuable suggestion, indeed. Our research is a little similar with Sharma’s which published in 2018. However, many differences exist between us. Firstly, the amount of species. We collected ~120 species in our research, which included complete tooth phenotype. Besides, our research included toothless and enamel-less species as many as possible, 9 baleen whales and enamel-less pygmy sperm whale, 2 pangolins, sloth and so on. For Sharma et al. (2018), just 62 species (just included 1 baleen whale, 1 pangolin, no sloth). Secondly, the method of sequences mining. In our research, we collected ACPT sequences from database. Especially, for toothless and enamel-less species, we do the local BLASTN, and compared with query to make sure the quality and identify the inactivated mutation sites, from which the quality of related sequences is guaranteed. For Sharma et al. (2018), the sequences were acquired by using self-developed method which screen the pseudogenes from whole genome. Our method provides a more comprehensive understanding of the quality and characteristics of ACPT gene sequence. Thirdly, we calculated the inactivation time of ACPT, whereas, Sharma et al. provides a rough approximation of the results. Moreover, due to the difference of species number, sequences quality and topological structure of species tree, there’s different conclusion of ACPT inactivation between us. 2) line 33. ' which is earlier than the oldest pangolin' should be ' which is earlier than the oldest aardvark'. —thanks, we have revised. 3) lines 33-36. It is not clear in the abstract what is meant by ' the oldest fossil time'. Perhaps this is a word choice issue and is ambiguous as written in the context of these sentences. i.e., 'oldest fossil time' of what? —thanks, we have revised. 4) Is it known exactly what the ACPT gene does in enamel formation? Or, is this still not well studied by experimental means in past literature? Are there hypotheses regarding what role this gene plays in tooth development? —Thank you. ACPT gene plays key roles in enamel formation. Some previous studies have confirmed. Firstly, GO analyses showed that ACPT gene take part in odontogenesis. Secondly, many previous studies also showed that ACPT gene involved in amelogenesis, for example, it is expressed in secretory-stage ameloblasts (Seymen et al., 2016), which can induce odontoblasts differentiation, mineralization of dentin, and amelogenesis (Choi et al., 2016). Third, there are many important amino acid residues in ACPT, which experience interactions with another enamel-related proteins, such as KLK4, AMTN, ENAM (STRING: https://string-db.org). 5) Why was only one species of Xenarthran analyzed in this paper? Why are there no pangolin sequences in the study? These are critical excluded species that are toothless (pangolins, anteaters) or lack enamel (sloths and other aramadillos). Are genomes for these additional species not available? Or, is the ACPT gene completely lacking from currently available genome sequences? If the latter, are flanking genes relative to ACPT found in these toothless or enamel-less mammals? My understanding is that Dasypus is an armadillo with very recent degradation of enamel based on previous morphological, paleontological, and molecular work and that multiple losses of enamel occurred within the armadillo clade. Are the authors up to date on this literature? —Thanks for your advice. Actually, we have obtained the ACPT sequence of sloth, pangolins, however, the quality and the coverage is a little poor, so we didn’t show the results and do the subsequent analyses. According to your suggestion, we have added the related results (additional files) and description. The discussion was shown in the main text, and the related sentences were highlighted by yellow. Based on the results, the ACPT gene completely exist in currently available genome sequences, only different types of gene inactivation were identified in these toothless and enamel-less mammals. For current researches of armadillos’ enamel degeneration, we cited the related references, at the same time, our results add molecular biological evidence to armadillo tooth enamel degradation. 6) line 263. The subtitle of this section is ' Is inactivation of ACPT neutral or adaptive?' but I think this challenging question was not really answered adequately in this section. I did not find the authors' arguments here to be compelling. There are multiple hypothesized losses of enamel in Xenarthra, not just one in the common ancestor of this clade. Because the authors included just one Xenarthran in their analysis and this is in an armadillo that seems to have lost enamel very recently, the text of the authors does not make sense to me. I think much more work has to be done here to make a compelling argument (i.e., more sequences from xenarthrans need to be included from sloths, anteaters, and more armadillo genera). I did not follow the logic of the statement, 'However, estimates for ACPT, ODAM and ENAM inactivation are both older than the oldest fossil aardvark, O. minutus, which is ~19Ma (Patterson, 1975). It strongly suggested that gene loss may be the reason, not the consequence, for degeneration and / or loss of enamel, which is different from the result of Sharma et al. (Sharma et al., 2018). ' What did Sharma et al. say and how does this differ logically from the interpretation of the authors here. I am also not understanding how the very young date for inactivation of ACPT was calculated. What was the time range used for the ancestral branch to Mysticeti, and what was this based on? Isn't the basal node of Mysticeti estimated from previous work to be older than 15 MY, which is the authors' estimate for inactivation on the stem lineage of Mysticeti? Or, maybe I am missing something here. At any rate, this should be clarified in revision. Also, there is recent evidence that the 'toothless' mysticete Eomysticetus is in a clade (Eomysticetidae) in which some close relatives have vestigial teeth at the tips of their jaws. This region of anatomy is not, I think, well preserved enough in Eomysticetus to tell whether this genus was truly toothless? —Thank you for giving us so many valuable suggestion. We have made some revise according to your suggestions, hoping to solve your questions, which is highlighted by yellow in text. For losses of enamel in Xenarthra, there are different hypotheses: (1) Ancestral reconstructions which is based solely on the phenotypes of extant taxa imply that enamel was lost on the stem xenarthran branch; however, (2) Meredith et al. (2009) speculated that all stem xenarthran fossils will have teeth with enamel based on selective pressure of ENAM gene. In general, the jury is still out so far. In fact, we have acquired ACPT sequences of sloth, due to the low coverage and quality, we didn’t do the further analysis. In this version, we show the character of sloth sequences, and added the related description. In Sharma et al. research, the accurate time of ACPT inactivation was not shown, and they speculated gene loss as a consequence of adaptation is likely the result of relaxed selection to maintain a gene whose function became obsolete. In our research, we calculated the inactivation time, and the result of aardvark is that ACPT inactivation is earlier than fossil record, which implied that gene loss might be the reason for loss of enamel in aardvark. For time rang selection, we mainly refer to the TimeTree. For Eomysticetidae, many fossil researches have implied that species in this group were edentulous (Boessenecker, 2015, PeerJ; Boesseneckera, 2017, New Zealand Journal of Geology and Geophysics; Boessenecker, 2015, Zoological Journal of the Linnean Society; Deméré et al., 2008, Systematic Biology). 7) line 266. The author's definition here seems off. ' adaptive evolution (direct natural / positive selection to conserve energy and / eliminate the disadvantageous effects of morphological structure)' What about reproductive fitness implied by different genotypes? Their definition is unconventional even if it is as in the references given. —Thank you for you suggestion. We have revised according to your suggestion, and then added the related reference. Comments for the author Yuan Mu et al. analyze sequence data for the ACPT gene in a phylogenetic context to characterize inferred gene inactivations over the history of Mammalia. The authors note that they seek to analyze the 'mechanisms' of gene inactivation as related to tooth loss in the abstract and in the introduction. This is a challenge as it is difficult to assess cause and effect when so many genes have been inactivated on the same evolutionary branches where inferred losses of enamel or teeth have occurred in mammalian phylogeny. The authors document knockouts of ACPT in baleen whales, pygmy right whale, aardvark, and armadillo which are all characterized by lack of enamel or degraded enamel. This work follows a previous paper that first noted some of these inactivations (Sharma et al., 2018) that was recently published using broad genomic screens. So, as the authors note, it was previously known that inactivations of ACPT in mammals without enamel were present, but the authors provide extensive further detail on these events within the context of phylogenetic trees from many more mammalian species (116 species) that were extracted from published genomes and estimate inactivation times using dN/dS ratios on branches where loss of enamel is inferred. The paper is pretty simple and straightforward and represents a contribution to the field, but the new insights presented are perhaps not great given previous work on this gene by Sharma et al. (2018). An important issue is point #6 below. Why were pangolin and anteater sequences not included in this study, as well as sloth sequences? These are critical species without teeth or enamel that have published genomes? In general the authors methods seem sound, and the results and discussion are simply stated and not overinterpreted. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Loss of tooth or enamel is widespread in multiple mammal lineages. Although several studies have been reported, the evolutionary mechanisms of tooth / enamel loss are still unclear. Most previous studies have found that some tooth-related genes have been inactivated in toothless and / or enamel-less mammals, such as ENAM, ODAM, C4orf26, AMBN, AMTN, DSPP, etc. Here, we conducted evolutionary analyses on ACPT playing a key role in amelogenesis, to interrogate the mechanisms. We obtained the ACPT sequences from 116 species, including edentulous and enamel-less mammals. The results shows that variant ORF-disrupting mutations were detected in ACPT coding region among nine edentulous baleen whales and three enamel-less taxa (pygmy sperm whale, aardvark, nine-banded armadillo). Furtherly, selective pressure uncovered that the selective constraints have been relaxed among all toothless and enamel-less lineages. Moreover, our results support the hypothesis that mineralized teeth were lost or degenerated in the common ancestor of crown Mysticeti through two shared single-base sites deletion in exon 4 and 5 of ACPT among all living baleen whales. D N / d S values on transitional branches were used to estimate ACPT inactivation records. In the case of aardvark, inactivation of ACPT was estimated at ~23.60-28.32 Ma, which is earlier than oldest aardvark fossil record (Orycteropus minutus, ~19Ma), suggesting that ACPT inactivation may result in degeneration or loss of enamel. Conversely, the inactivation time of ACPT estimated in armadillo (~10.18-11.30 Ma) is later than oldest fossil record, suggesting that inactivation of ACPT may result from degeneration or loss of enamel in these mammals. Our findings suggested that different mechanisms of degeneration of tooth / enamel might exist among toothless and enamel-less lineages during evolution. Our study further considered that ACPT is a novel gene for studying tooth evolution.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Dental innovations (such as differentiated dentitions and the evolution of tri-bosphenic molar) have been regarded as the great success of mammalian evolution and adaptation <ns0:ref type='bibr' target='#b38'>(Ungar, 2010)</ns0:ref>.</ns0:p><ns0:p>However, in spite of their importance for animal survival, teeth have been lost independently in multiple mammalian lineages, such as baleen whales and pangolins. In addition, some lineages have lost their outer enamel of teeth, such as pygmy sperm whale and dwarf sperm whale, aardvarks and species from Xenarthra <ns0:ref type='bibr'>(Davitbeal et al., 2009)</ns0:ref>. Tooth loss and / or enamel loss is one of the most important field for mammalian tooth evolution.</ns0:p><ns0:p>Amelogenesis imperfecta (AI) and tooth loss are the diseases that characterized by genetic defects in the formation of enamel and teeth. Multiple studies have suggested these genetic disorders are mainly caused by mutations of protein-coding genes functioned in formation of enamel and teeth <ns0:ref type='bibr' target='#b35'>(Stephanopoulos et al., 2005;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. Of these genes, three enamel matrix protein genes (EMPs, i.e., AMELX, AMBN and ENAM), two enamel proteases genes (MMP20 and KLK4), and some other related genes (e.g., C4orf26, AMTN, ODAM, <ns0:ref type='bibr'>ACPT, DSPP)</ns0:ref> have been confirmed to be candidate genes responsible for the diseases <ns0:ref type='bibr' target='#b7'>(Crawford et al., 2007;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. The variant inactivating mutations have been detected in these genes among toothless and enamel-less mammalian lineages. However, the mechanisms of tooth loss or enamel loss are still completely unclear.</ns0:p><ns0:p>It has been reported that ACPT was lower expressed in testicular cancer tissues compared to normal tissues and is regulated by steroid hormones <ns0:ref type='bibr' target='#b42'>(Yousef et al., 2001)</ns0:ref>. Besides, ACPT is also expressed in the brain and acts as a tyrosine phosphatase to modulate signals mediated by ErbB4 <ns0:ref type='bibr' target='#b13'>(Fleisig et al., 2004)</ns0:ref>. But, it is interesting to note that ACPT is expressed in secretory-stage ameloblasts <ns0:ref type='bibr' target='#b28'>(Seymen et al., 2016)</ns0:ref>, which can induce odontoblasts differentiation, mineralization of dentin, and amelogenesis <ns0:ref type='bibr' target='#b4'>(Choi et al., 2016)</ns0:ref>. Furthermore, there are some increasing evidences that homozygous missense variants of ACPT would lead to AI (e.g., c.226C&gt;T, p.Arg76Cys; c.746C4T, p.P249L) <ns0:ref type='bibr' target='#b28'>(Seymen et al., 2016;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. These evidences suggested that ACPT play an important role in amelogenesis.</ns0:p><ns0:p>All extant Mysticeti, descended from toothed ancestors, have no teeth and instead have baleen <ns0:ref type='bibr' target='#b37'>(Uhen, 2010)</ns0:ref>. Paleontological evidences have shown that mineralized teeth were lost in the common ancestor of crown Mysticeti. Moreover, a transitional stage from tooth to baleen in stem mysticetes have been revealed in some taxa bearing both teeth and baleen <ns0:ref type='bibr'>(Dem&#233;r&#233; et al.,</ns0:ref> PeerJ reviewing PDF | (2020:03:46572:2:1:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed 2008). Although many tooth-related genes have been revealed to be inactivated in various living mysticetes (e.g., AMBN, ENAM, AMEL, AMTN, MMP20, C4orf26 and DSPP) <ns0:ref type='bibr' target='#b10'>(Dem&#233;r&#233; et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b20'>Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b19'>Meredith et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b14'>Gasse et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b9'>Delsuc et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b34'>Springer et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b32'>Springer et al., 2019)</ns0:ref>, only the MMP20 are commonly inactivated across all the living baleen whales <ns0:ref type='bibr' target='#b19'>(Meredith et al., 2011)</ns0:ref>. This molecular evidence is consistent with earlier studies of paleontology and anatomy.</ns0:p><ns0:p>Despite its significance in mammalian enamel maturation, very little is known about ACPT evolutionary trajectory, relationship and function in mammals. To address this issue, we carried out a series of evolutionary analyses on ACPT, aim to uncover the evolutionary pattern of ACPT gene among mammalian lineages.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sequences mining and BLAST searches</ns0:head><ns0:p>The full-length coding sequences (CDS) of ACPT gene were extracted from the OrthoMaM v10b (http://orthomam2.mbb.univ-montp2.fr/OrthoMaM_v10b10/), ENSEMBL (http://www.ensembl.org/index.html?redirect=no) and NCBI (http://www.ensembl.org/index.html?redirect=no) databases (Table <ns0:ref type='table'>S1</ns0:ref>). ACPT of some whales were extracted from their Genome and SRA database of NCBI (Table <ns0:ref type='table'>S2 and S3</ns0:ref>). To further ensure the sites of inactivating mutation of toothless / enamel-less lineages, we used the CDSs of some representative placental species with well-annotated genomes (Homo sapiens [human],</ns0:p><ns0:p>Canis lupus familiaris [Dog], Bos taurus <ns0:ref type='bibr'>[Cow]</ns0:ref>, Echinops telfairi [Lesser hedgehog tenrec]) as queries including &#8764;50bp of flanking sequence on each exon. These sequences were used as queries to BLAST against toothless / enamel-less mammals to confirm the related inactivating mutation among baleen whales.</ns0:p></ns0:div> <ns0:div><ns0:head>Identification of inactivating mutations and functional sites and domains</ns0:head><ns0:p>The intact ACPT sequences (human, cow, tenrec) were used for identifying inactivating mutations (including mutation of initiation codons, frame-shift insertions and deletions, premature stop codons, splice sites mutation of intron / exon boundary [GT/AG], etc.). The inactivating mutation was identified based on BLAST searches against whole genomes of the relevant taxon from NCBI. The information on gene function, related key amino acid sites/domains was searched from UniProtKB/Swiss-Prot (http://www.uniprot.org/) and some references.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46572:2:1:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Alignment and phylogenetic analysis of mammalian ACPT</ns0:head><ns0:p>The 116 mammalian ACPT sequences were aligned based on their amino acid translations using online PRANK (https://www.ebi.ac.uk/goldman-srv/webprank/), and then deleted the gaps and non-homologous regions by using GBLOCK, then we corrected the multiple sequences alignment (MSA) in MEGA 7 <ns0:ref type='bibr' target='#b17'>(Kumar et al., 2016)</ns0:ref> by eye.</ns0:p><ns0:p>A gene tree was reconstructed by Mrbayes 3.2 <ns0:ref type='bibr' target='#b27'>(Ronquist et al., 2012)</ns0:ref> with a general time reversible (GTR) substitution model and rate heterogeneity modeled with a Gamma distribution, as conducted by MrModeltest version 2 using the Akaike information criterion (AIC) <ns0:ref type='bibr' target='#b22'>(Nylander, 2004)</ns0:ref>. In bayesian analysis, four simultaneous runs with four chains each were run for two million generations, sampling every 1000 trees. The first 25% of these trees were discarded as burn-in when computing the consensus tree. Tracer v1.5 software was used for checking convergence among chains in Bayesian analysis. When the ESS value is higher than 200, and the average standard deviation of spilt frequencies is lower than 0.01, we think it reach convergence level.</ns0:p></ns0:div> <ns0:div><ns0:head>Selection analyses</ns0:head><ns0:p>To evaluate the selective pressure of relevant branches leading to enamel-less and toothless lineages respectively, we implemented two ratio branch model to calculate the ratio of the nonsynonymous substitution rate (d N ) to the synonymous substitution rate (d S ) (&#969; = d N /d S ) by running CodeML in PAML 4.8a package <ns0:ref type='bibr' target='#b41'>(Yang, 2007)</ns0:ref>. We also recoded premature stop codons as missing data. Akaike information criterion (AIC) scores were used to select the most appropriate codon frequency model in CodeML. The ACPT gene tree exhibits different topological relationship compared to species tree, which may be unrelated to incomplete lineage sorting. In order to illuminate the detected signal reasonably and accurately, we used a species tree supported by some previous studies (Fig. <ns0:ref type='figure' target='#fig_5'>S1</ns0:ref>).</ns0:p><ns0:p>Refer to the methods of Springer and Gatesy <ns0:ref type='bibr' target='#b33'>(Springer and Gatesy, 2018)</ns0:ref>, several different branch categories were considered during selective analyses: (1) One category accounted for 'background' branches, which are lineages with intact teeth and an intact copy of ACPT. <ns0:ref type='table'>2020:03:46572:2:1:NEW 28 Sep 2020)</ns0:ref> Manuscript to be reviewed were degraded. ( <ns0:ref type='formula'>5</ns0:ref>) One branch categories were assigned for crown Mysticeti.</ns0:p><ns0:p>To better understand the selective pressure, a series of evolutionary models were compared in the likelihood. We first use the M0 model (Model A), which assumed that all branches in the phylogenetic tree has a common value, and compare it with the null hypothesis (Model B), which assumed that the common value in the phylogenetic tree is 1. To further understand whether the selective pressure on the lineages leading to pseudogenes was relaxed, we constructed Model C, which assumed that the branches with pseudogene had their own selection pressure &#969; 2 , while the background branches without pseudogenization was &#969; 1 , and then compared Model C with Model A. To further confirm whether the selective pressure on the lineages leading to pseudogenes was completely relaxed, we build the Model D, which assumed that the branches with pseudogene had their own selection pressure &#969; 2 = 1, while the selective pressure of background branches was &#969; 1 , and then compared Model C with Model D.</ns0:p></ns0:div> <ns0:div><ns0:head>Estimation of inactivation times</ns0:head><ns0:p>To estimate when ACPT was inactivated in different lineages of Placentalia, the method described in <ns0:ref type='bibr'>Chou et al. (2003)</ns0:ref> and <ns0:ref type='bibr' target='#b44'>Zhang et al. (2010)</ns0:ref> was used. Among the branches along which the gene became pseudogenes, this method presumes that gene evolves under a selective pressure similar to that in other species until it is inactivated. Next, this gene was presumed to accumulate both nonsynonymous and synonymous mutations at an equal rate. The K a / K s (K) value was assessed for this entire branch. The average K a / K s value was just for a part of the branch, where the gene was under selection (Ks). In addition, the K a / K s value for the rest of part of the branch where the gene evolved neutrally (K n = 1). Thus, the evolutionary time was weighted by the proportion, for which the gene was evolving under selection (T s / T) and neutrally (T n / T):</ns0:p><ns0:formula xml:id='formula_0'>K = K s &#215;T s / T + K n &#215;T n / T</ns0:formula><ns0:p>where T is the time since the split from the last common ancestor (LCA). By selecting the lower and upper bound of the confidence interval for the species divergence time T, which was obtained from TimeTree website (http://www.timetree.org/) to estimate a lower and upper bound for T n as:</ns0:p><ns0:formula xml:id='formula_1'>T n = T&#215;(K-K s ) / (1-K s )</ns0:formula><ns0:p>which provides an estimate of how long the ACPT gene has been evolving neutrally. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Characterization of ACPT sequence 120 sequences were obtained in this study. Due to the poor quality and low coverage of sequences among three pangolins (Manis javanica, M. javanica, Phataginus tricuspis) and one sloth (Choloepus hoffmanni), they were not used for subsequent analysis. However, some inactivating mutations (most of them are indels) were found in these sequences (Fig. <ns0:ref type='figure' target='#fig_6'>S2</ns0:ref>). The complete protein-coding sequence of ACPT in 116 taxa were used for alignment by PRANK.</ns0:p><ns0:p>Interestingly, one or more inactivating mutations (frame-shift mutation, initial codon mutation, premature stop codons, splice site mutations, etc.) were detected in another placental taxa without teeth or without enamel. (Fig. <ns0:ref type='figure' target='#fig_5'>1</ns0:ref>, Table <ns0:ref type='table'>S4</ns0:ref>, Fig. <ns0:ref type='figure'>S3</ns0:ref>). For example, among toothless baleen whales, the initial codon mutation (n. ATG&#8594;GTG, p. M&#8594;V) was found in Balaenoptera borealis, B. physalus, B. musculus, Eschrichtius robustus, Eubalaena glacialis. Meanwhile, premature stop codons were found in B. acutorostrata and B. bonaerensis, frameshift indels were also found in baleen whales. Interestingly, two shared single-base site deletion was found on exon 4 and 5 of ACPT among all living baleen whales (Fig. <ns0:ref type='figure' target='#fig_5'>1</ns0:ref>, Fig. <ns0:ref type='figure'>S3</ns0:ref>). The splice site mutations were detected in B. acutorostrata, Eubalaena japonica and Megaptera novaeangliae (Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p><ns0:p>Whilst, the premature stop codons were found in enamel-less D. novemcinctus and . afer.</ns0:p><ns0:p>Besides, frameshift indels were found in enamel-less Kogia breviceps.</ns0:p><ns0:p>Except for the species mentioned above, ACPT gene in other species whose teeth are intact were found to be activated. Nevertheless, some crucial amino acids mutation was found in toothed species, such as site 76 has been mutated (R76C) in Neophocaena asiaeorientalis.</ns0:p></ns0:div> <ns0:div><ns0:head>Reconstruction of ACPT gene tree</ns0:head><ns0:p>We recovered the ACPT gene tree with well-supported values by using Mrbayes method (Fig. <ns0:ref type='figure' target='#fig_6'>2</ns0:ref>).</ns0:p><ns0:p>In this gene tree, most of orders have been well reconstructed, and have high support rate, e.g., Cetartiodactyla, Perissodactyla, Eulipotyphla, Carnivora, Chiroptera etc. In addition, phylogenetic relationships of higher levels have also been well reconstructed, such as Laurasiatheria, Euarchontoglires, Boreoeutheria and Afrotheria. In this gene tree, bayesian posterior probability (PP) values of nearly 70% nodes are generally greater than 0.70. However, the relationship between some order level were relatively chaotic, such as Lagomorpha didn't cluster with Rodentia, but as the sister group of Primate; Chiroptera and Carnivora clustered together first, and then they became sister group of Perissodactyla. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Evolutionary analyses among toothless and enamel-less mammals</ns0:head><ns0:p>We carried out the PAML analysis to detect the selective pressure of toothless / enamel-less lineages, and found the selective pressure of these toothless / enamel-less lineages (including ancestral nodes, terminal branches and even the whole toothless / enamel-less group) was significantly higher than that of background branches. For example, the terminal branch of B. physalus: &#969; 1 =0.116, &#969; 2 =1.883; the terminal branch of M. novaeangliae: &#969; 1 =0.116, &#969; 2 =0.641; the terminal branch of E. robustus: &#969; 1 =0.116, &#969; 2 =2.688; the terminal branch of E. glacialis: &#969; 1 =0.116, &#969; 2 =0.503. A similar tendency was found in the terminal branches of other baleen whales, and further model comparison shows that the selective pressure of these branches had been completely relaxed. Whilst, much higher selective pressure was detected in the ancestral branch of stem mysticeti (&#969; 1 =0.120, &#969; 2 =0.436), even the clade of crown mysticeti (&#969; 1 =0.116, &#969; 2 =0.522). Meanwhile, higher selective pressure was detected among enamel-less lineages, such as the terminal branch of D. novemcinctus (&#969; 1 =0.116, &#969; 2 =0.206), the terminal branch of O. afer (&#969; 1 =0.116, &#969; 2 =0.414), and the terminal branch of K. breviceps (&#969; 1 =0.116, &#969; 2 =0.581). And the selective pressure of these branches had been completely relaxed, except for the terminal branch of K. breviceps (Table <ns0:ref type='table'>S5</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>ACPT inactivation dates</ns0:head><ns0:p>Estimates of inactivation times for ACPT based on d N / d S ratios and equations in Sharma et al. <ns0:ref type='bibr' target='#b29'>(Sharma et al., 2018)</ns0:ref>. The mean estimate for the inactivating time of ACPT on the branch of K. breviceps, D. novemcinctus and O. afer is 12. , respectively (Fig. <ns0:ref type='figure'>3</ns0:ref>). The mean estimate for the inactivation of ACPT on the Mysticeti clade is 14.05-16.30Ma.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head>ACPT is a novel candidate gene for studying mammalian tooth loss and enamel loss</ns0:head><ns0:p>The well-conserved gene structure in extant species indicates that this organization and arrangement might be present in the last common mammalian ancestor, which represented the vital function for organisms <ns0:ref type='bibr' target='#b18'>(Madsen, 2009)</ns0:ref>. In our study, the number of ACPT exons are 11 in placental mammals, which encode 427 amino acids (human ACPT sequence as the reference sequence). Our study collected that four residues (191N, 269N, 330N and 339N) of the extracellular region were for glycosylation, two residues (41H and 289D) directly involved in catalysis (from UniProt database). In addition, mutation in seven residues were reported that PeerJ reviewing PDF | (2020:03:46572:2:1:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed were responsible for AI <ns0:ref type='bibr' target='#b28'>(Seymen et al., 2016;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref> (Fig. <ns0:ref type='figure'>S4</ns0:ref>). Besides, there are three disulfide bond regions, namely, site 159 to 378, site 214 to 312, site 353 to 357. In fact, we detected not only teratogenic mutations but also inactivated mutations in these functional sites and domains. For example, enamel in finless porpoise were degenerated <ns0:ref type='bibr' target='#b15'>(Ishiyama, 1987)</ns0:ref>, mutation in site 76 (R&#8594;C) was found in N. asiaeorientalis. Previous research has confirmed that site 76 mutated into Cys (C) in human ACPT would lead to hypoplastic AI <ns0:ref type='bibr' target='#b28'>(Seymen et al., 2016)</ns0:ref>, from which this result further supported that teeth in finless porpoise were degenerated in molecular level. Of cause, most obvious characteristics of ACPT is that different types of inactivating mutations were found in toothless and enamel-less mammals, e.g., baleen whales, pangolins, sloths and so on (Fig. <ns0:ref type='figure' target='#fig_6'>S2</ns0:ref>, Fig. <ns0:ref type='figure'>S3</ns0:ref>). Therefore, ACPT could be a candidate gene for AI and studying mammalian tooth loss and enamel loss.</ns0:p></ns0:div> <ns0:div><ns0:head>Degeneration or loss of mineralized teeth in LCA of Mysticeti</ns0:head><ns0:p>Fossil evidence shows that the earliest ancestors of baleen whales possessed complete dentitions without baleen (such as Janjucetus and Mammalodon), and then evolved the baleen with teeth (such as Aetiocetus), until the lineages only baleen existed (e.g., Eomysticetus and Micromysticetus) <ns0:ref type='bibr' target='#b11'>(Fitzgerald, 2006;</ns0:ref><ns0:ref type='bibr' target='#b12'>Fitzgerald, 2010;</ns0:ref><ns0:ref type='bibr' target='#b19'>Meredith et al., 2011)</ns0:ref>. However, the fact is all living baleen whales lack teeth and instead baleen <ns0:ref type='bibr' target='#b37'>(Uhen, 2010)</ns0:ref>. This implied that that mineralized teeth were lost or degenerated gradually in the common ancestors of all modern baleen whales <ns0:ref type='bibr' target='#b2'>(Boessenecker and Fordyce, 2015)</ns0:ref>. In addition, the successive steps of vestigial tooth development was found in the fetal period of living baleen whales <ns0:ref type='bibr' target='#b8'>(Davit-B&#233;al et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b36'>Thewissen, 2018)</ns0:ref>, which was also confirmed by genetic evidence. Molecular sequences of some specific genes, such as AMBN, ENAM, AMELX, AMTN, C4orf26 and ODAM, contain different types of inactivating mutations (e.g., stop codons, frameshift mutations, splice site mutations, etc.) in various mysticete species <ns0:ref type='bibr' target='#b10'>(Dem&#233;r&#233; et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b20'>Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b0'>Alhashimi et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b14'>Gasse et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b21'>Meredith et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b9'>Delsuc et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b32'>Springer et al., 2019)</ns0:ref>, which is consistent with loss-of-teeth in this group. But none of the inactivating mutations are shared by all living mysticetes species. Meredith et al. found a common insertion of CHR-2 SINE retroposon in MMP20 gene among all living baleen whales <ns0:ref type='bibr' target='#b19'>(Meredith et al., 2011)</ns0:ref>. Previous study has been confirmed that mutations or deletions of MMP20 gene would result in thin and brittle enamel layer <ns0:ref type='bibr' target='#b3'>(Caterina et al., 2002)</ns0:ref>. Based on this result, they confirmed the hypothesis that mineralized teeth were lost or degenerated in the common ancestor of crown Mysticeti in the Manuscript to be reviewed molecular level.</ns0:p><ns0:p>In this research, we also identified different inactivating mutations was detected among all mysticete species in ACPT gene, among which two shared single-base sites deletion were found on exon 4 and 5 of ACPT among all living baleen whales, which result in loss of function. Some studies have confirmed that ACPT gene is responsible for the development of enamel, and mutations can also lead to amelogenesis imperfecta <ns0:ref type='bibr' target='#b4'>(Choi et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b28'>Seymen et al., 2016;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. Similar to the result of <ns0:ref type='bibr' target='#b19'>Meredith et al. (2011)</ns0:ref>, our study supported the hypothesis that mineralized teeth were lost or degenerated in the common ancestor of all extant baleen whales.</ns0:p></ns0:div> <ns0:div><ns0:head>Is inactivation of ACPT neutral or adaptive?</ns0:head><ns0:p>The degeneration and / or loss of some morphological structures (such as limbs, teeth, and eyes, etc.) is a complex process that may result from the relaxation of the negative selection (neutral evolution), adaptive evolution (direct natural / positive selection to conserve energy and / or eliminate the disadvantageous effects of morphological structure), and / or gene pleiotropy (indirect selection on another traits) <ns0:ref type='bibr' target='#b40'>(Wang et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b43'>Zhang, 2008;</ns0:ref><ns0:ref type='bibr' target='#b16'>Krishnan and Rohner, 2017)</ns0:ref>. In some conditions, evolutionary change also results from differences in the reproductive success of individuals with different genotypes <ns0:ref type='bibr'>(Olson,1999)</ns0:ref>. <ns0:ref type='bibr' target='#b29'>Sharma et al. (2018)</ns0:ref> revealed that evolutionary gene losses are not only a consequence, but may also be causally involved in phenotypic adaptations. By estimating the inactivation time of pseudogenes, and comparing with oldest fossil records, we might be able to speculate whether gene inactivation is due to the adaptive or neutral selection after the loss of phenotype.</ns0:p><ns0:p>The record of enamel-degenerated armadillo fossil is significantly earlier than the estimated time of ACPT inactivation (10.18-11.30Ma) <ns0:ref type='bibr' target='#b6'>(Ciancio et al., 2014)</ns0:ref>, which suggested gene loss as a consequence of adaptation is likely the result of the relaxation of the negative selection. The results further supported the previous study <ns0:ref type='bibr' target='#b29'>(Sharma et al., 2018)</ns0:ref>. Besides, during the tooth evolution, some enamel-related genes (e.g., ODAM, ENAM, AMBN) also have gone through the similar evolutionary trajectory. By integrating different results from different methods, we may better understand the evolution of teeth and enamel. The inactivation time of ENAM (~45.5Ma) and <ns0:ref type='bibr'>ODAM (~40.43 Ma,</ns0:ref>) is much earlier than inactivation date for ACPT in armadillo <ns0:ref type='bibr' target='#b32'>(Springer et al., 2019)</ns0:ref>. ACPT inactivation is later than the fossil record, conversely, the inactivation time of ENAM is relatively earlier than the fossil record, which implied the various mechanisms of enamel loss in armadillo. Here, the inactivation of ENAM gene might be the causes of degeneration / loss of tooth enamel in armadillos, ACPT inactivation might be the consequence of enamel loss.</ns0:p><ns0:p>For O. afer, even the inactivation date for ACPT ) is relatively younger than inactivation dates for ENAM ) and ODAM (~30.7Ma) in O. afer <ns0:ref type='bibr' target='#b20'>(Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b32'>Springer et al., 2019)</ns0:ref>. However, the estimated inactivation times by ACPT, ODAM and ENAM gene markers are all earlier than the oldest fossil record of aardvark (O. minutus, ~19Ma) <ns0:ref type='bibr' target='#b25'>(Patterson, 1975)</ns0:ref>. It should be suggested that gene loss may be the reason, not the consequence, for degeneration and / or loss of enamel. Moreover, due to the difference of species number, sequences quality and topological structure of species tree, the result of ACPT inactivation time is different from the result of Sharma et al. <ns0:ref type='bibr' target='#b29'>(Sharma et al., 2018)</ns0:ref>.</ns0:p><ns0:p>Cetacean includes both toothless Mysticeti and enamel-less Kogia. Relaxation of selective pressure was detected in both crown and stem Mysticeti (Table <ns0:ref type='table'>S5</ns0:ref>), which is consistent with the archaic toothless mysticete, namely, all stem Mysticeti were toothless. For example, Eomysticetus whitmorei, an edentulous species, was the geologically oldest mysticete <ns0:ref type='bibr' target='#b10'>(Dem&#233;r&#233; et al., 2008)</ns0:ref>. Molecular evidence shows ACPT has been lost its function in LCA of Mysticeti.</ns0:p><ns0:p>However, the inactivation time of ACPT in Mysticeti is 14.05-16.30Ma, which is much younger than the toothless mysticete (~30Ma) and the split of Mysticeti (~25.9Ma). Obviously, this is not consistent with the facts. It might be associated with relatively lower rates of frameshift accumulation during evolution of mysticete pseudogenes and long lifespan of mysticete <ns0:ref type='bibr' target='#b20'>(Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b19'>Meredith et al., 2011)</ns0:ref>. Whether adaptive or neutral, the shared single-base site deletion in ACPT fills an important gap in our understanding of the macroevolutionary transition leading from the LCA of crown Cetacean to the LCA of crown Mysticeti. Stem physeteroids (sperm whales) are known from the Miocene and had teeth with enamel <ns0:ref type='bibr' target='#b1'>(Bianucci and Landini, 2010)</ns0:ref>. Our results provide support for loss of the intact ACPT in K. breviceps.</ns0:p><ns0:p>ACPT was reported that play key roles in amelogenesis and differentiation of odontoblasts <ns0:ref type='bibr' target='#b4'>(Choi et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b28'>Seymen et al., 2016;</ns0:ref><ns0:ref type='bibr'>Smith et al., 2017)</ns0:ref>. Our result is in line with the enamel-less morphological structure in K. breviceps.</ns0:p></ns0:div> <ns0:div><ns0:head>CONCLUSIONS</ns0:head><ns0:p>We detected the different types of inactivated mutation in ACPT. Furthermore, selective pressure uncovered that the selective constraints have been relaxed among all toothless and enamel-less (a) Dasypus novemcinctus (nine-banded armadillo), (b) Orycteropus afer (aardvark), (c) Kogia breviceps (pygmy spermwhale). The inactivation times of ENAM is from <ns0:ref type='bibr' target='#b20'>(Meredith et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b32'>Springer et al., 2019)</ns0:ref>. The images are from the PHYLOPIC database: http://phylopic.org/.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>to terminal branches with unique inactivating mutations (baleen whales), which lacks teeth. (3) Three branch categories to terminal branches with unique inactivating mutations (pygmy sperm whale, nine-banded armadillo and aardvark), whose enamel has been vestigial. (4) One branch categories were assigned for stem Mysticeti where mineralized teeth PeerJ reviewing PDF | (</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46572:2:1:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46572:2:1:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46572:2:1:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46572:2:1:NEW 28 Sep 2020)Manuscript to be reviewed lineages. In addition, our results supported the hypothesis that mineralized teeth were lost or degenerated in the common ancestor of crown Mysticeti through two shared single-base sites deletion in exon 4 and 5 of ACPT among all living baleen whales. Together with our evidence, ACPT might be a good marker to research the mechanism of tooth loss. By comparing the molecular time with the fossil time, we found there might be different mechanisms of degeneration of tooth / among toothless and enamel-less lineages during evolution, which is needed further researches.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 2 The</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> </ns0:body> "

"Reviewer 2 Basic reporting This is fine. English grammar and word usage could still use some help. -Thank you very much. We have applied for the English Copyediting Services to improve our paper. And we have replied to the Jackie Thai’s email from English Copyediting Services. Experimental design no comment -Many thanks again for your patience. Validity of the findings This is generally fine. I think there is still some confusion on stem baleen whales (Mysticeti). Some have teeth, and even eomysticetids that have been described in the past as toothless show some evidence of having teeth at the tips of their jaws in at least one species (see Boessenecker papers from 2015). This affects some of the discussion section on whales, and it would be best to get this right. -Thank you for your valuable suggestion. Indeed, many toothed species in stem Mysticeti, so we will not know the truth of all species. Thus, we made an inaccurate conjecture. According to your suggestion, we revised the related description in context, and added the related references. The revised parts have been highlighted by yellow. Comments for the author I think the authors have generally dealt with the comments from my initial review in an adequate way. -It is a great honor for us to have your help. Best wishes! "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Wild animals are the source of many pathogens of livestock and humans. Concerns about the potential transmission of economically important and zoonotic diseases from wildlife have led to increased surveillance at the livestock-wildlife interface. Knowledge of the types, frequency and duration of contacts between livestock and wildlife is necessary to identify risk factors for disease transmission and to design possible mitigation strategies.</ns0:p><ns0:p>Observing the behaviour of many wildlife species is challenging due to their cryptic nature and avoidance of humans, meaning there are relatively few studies in this area. Further, a consensus on the definition of what constitutes a 'contact' between wildlife and livestock is lacking. A systematic review was conducted to investigate which livestock-wildlife contacts have been studied and why, as well as the methods used to observe each species. Over 30,000 publications were screened, of which 122 fulfilled specific criteria for inclusion in the analysis. The majority of studies examined cattle contacts with badgers or with deer; studies involving wild pig contacts with cattle or with domestic pigs were the next most frequent. There was a range of observational methods including motion-activated cameras and global positioning system collars. As a result of the wide variation and lack of consensus in the definitions of direct and indirect contacts, we developed a unified framework to define livestock-wildlife contacts that is sufficiently flexible to be applied to most wildlife and livestock species for non-vector-borne diseases. We hope this framework will help standardise the collection and reporting of contact data; a valuable step towards being able to compare the efficacy of wildlife-livestock observation methods. In doing so, it may aid the development of better disease transmission models and improve the design and effectiveness of interventions to reduce or prevent disease transmission.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The interface where livestock and wildlife may come into contact with each other is an area of growing scientific interest, particularly as wildlife can act as a 'reservoir' for diseases of livestock <ns0:ref type='bibr' target='#b0'>[1]</ns0:ref>. Disease transmission between livestock and wildlife can have marked economic impact, such as African swine fever outbreaks in domestic pigs and wild boar (Sus scrofa) in Europe and Asia <ns0:ref type='bibr' target='#b1'>[2]</ns0:ref>, where the loss of 12-20% of the global pig herd in 2019 led to a 10% increase in the food price index of pork <ns0:ref type='bibr' target='#b2'>[3]</ns0:ref>. The impact of disease transmission on wildlife can be seen in the loss of around half the global saiga (Saiga tatarica) antelope population in 2015 to Pasteurella multocida, a pathogen harboured by livestock <ns0:ref type='bibr' target='#b3'>[4]</ns0:ref>. Contact between wildlife and livestock may also lead to conflict between humans and wildlife, with compensation for large carnivore predation and other damage costing 28.5 million euros annually in Europe <ns0:ref type='bibr' target='#b4'>[5]</ns0:ref>. The proximity of agricultural land to wildlife habitats is a key factor in human-wildlife conflicts and in the spill-over of pathogens from wildlife to livestock and humans <ns0:ref type='bibr' target='#b6'>[6]</ns0:ref>. The emergence of diseases from wildlife that infect humans via livestock intermediaries, such as bat-borne Hendra virus (affecting humans via horses) and Nipah virus (affecting humans via pigs) <ns0:ref type='bibr' target='#b7'>[7]</ns0:ref>, further highlight the importance of contacts between wildlife, livestock and people. These contacts are seldom recorded, however, because many wildlife species are cryptic and therefore difficult to observe, capture and sample.</ns0:p><ns0:p>Observing wildlife-livestock contacts is becoming easier with advances in remote technologies such as motion-activated cameras, global positioning system (GPS) collars and proximity loggers <ns0:ref type='bibr' target='#b8'>[8]</ns0:ref><ns0:ref type='bibr' target='#b9'>[9]</ns0:ref><ns0:ref type='bibr' target='#b10'>[10]</ns0:ref>. These methods are usually (but not always) used to monitor one species at a time. They are not standardised, however, meaning there are many variations in monitoring protocols, often Manuscript to be reviewed depending on basic practicalities such as battery life, people-hours, cost and the aims of the study. The methods used to monitor livestock-wildlife contacts may influence (or be influenced by) the kind of contact to be monitored, the context of the study and what the data will be used for.</ns0:p><ns0:p>Livestock-wildlife contact data is needed to inform the simulation and modelling of diseases that have multiple host species, but information on the types of contact needed for transmission and the rates at which these occur is lacking <ns0:ref type='bibr' target='#b11'>[11]</ns0:ref>. Knowledge of livestock-wildlife contact data can be used to identify risk factors and predict where these contacts are more or less likely to occur, for example predicting the likelihood of badger (Meles meles) visits to cattle farms in the context of bovine tuberculosis transmission <ns0:ref type='bibr'>[12]</ns0:ref>. It could also be used to implement and improve mitigation strategies to prevent unwanted livestock-wildlife contacts. To mitigate wolf (Canis lupus) predation on sheep, for example, the effectiveness of prevention programs needs to be evaluated in ways that do not depend on livestock attacks alone, using methods such as GPS monitoring of wolf movements around sheep farm bio-fences <ns0:ref type='bibr' target='#b4'>[5,</ns0:ref><ns0:ref type='bibr' target='#b146'>13]</ns0:ref>. Similarly, the effectiveness of measures taken to prevent disease transmission can also be evaluated such as by comparing deer-cattle contact rates between farms with and without deer fences installed <ns0:ref type='bibr'>[14]</ns0:ref><ns0:ref type='bibr'>[15]</ns0:ref><ns0:ref type='bibr'>[16]</ns0:ref>.</ns0:p><ns0:p>Knowledge of livestock-wildlife contacts can be used in these contexts to limit the economic loss associated with disease and predation. Given these multiple ways of gathering and using livestock-wildlife contact data, the definition of what constitutes a relevant contact will vary depending on the aim of the study.</ns0:p><ns0:p>In the context of disease transmission, defining contact is challenging and while types of contact are often broadly grouped into being 'direct' or 'indirect', there are no standardised definitions <ns0:ref type='bibr'>[17]</ns0:ref>. Direct contacts are usually thought of as representing physical contact or being in close proximity over a short period of time, and so may include fighting, mating between feral and domestic animals of the same species, or being face-to-face or nose-to-nose. Indirect contacts are more difficult to define due to issues of long-distance aerosol transmission, environmental persistence of pathogens in spores and fomites, and intermediate insect vectors <ns0:ref type='bibr' target='#b11'>[11]</ns0:ref>. Other ecological definitions of livestock-wildlife contacts could also include avoidance behaviour or competition for resources between species. This variation in definitions means it is difficult to make meaningful comparisons between studies and to apply findings from one study to different contexts. Therefore, a standardised generic template for defining livestock-wildlife contacts would be useful.</ns0:p><ns0:p>The aim of this study was to systematically review the reasons for, and observational methods used in, studies investigating livestock-wildlife contacts, and to propose a generalised framework for defining contacts between livestock and wildlife. that collected, used or analysed data to investigate direct or indirect contacts between farmed livestock and terrestrial wild mammals whose adult bodyweight is typically &gt;5kg. Specifically, publications were included if they attempted to quantify, characterise, or identify risk factors for livestock-wildlife contacts. Only articles in English and those accessible to researchers were included. All reasonable efforts were made to access papers that passed abstract screening. We excluded studies in which predation events were the sole indicator of livestock-wildlife contacts, and studies of wild animals that were not free-living, were tamed or were relocated for the purpose of the study. Publications until 11 November 2019 were included, and no time restrictions were applied to the start of the search. Working definitions of direct and indirect contact were developed before performing the literature search and used to avoid ambiguity when evaluating publications for inclusion.</ns0:p><ns0:p>Direct contact was provisionally defined prior to reviewing the papers as physical contact between at least one wild animal and one farm animal. Indirect contact was provisionally defined as contact between at least one wild animal and a resource used by at least one farm animal including, but not limited to, food, water and space. Therefore, studies that investigated wildlife and livestock shared resource use, but did not explicitly investigate contacts, were included. These definitions were used throughout the process of identifying and analysing the papers in this review. Study data was extracted and livestock and wildlife species, observation methods and definitions were categorised. Where available, the power of each study, defined as the likelihood of detecting contacts, was recorded. Themes that emerged during data extraction were grouped into seven broad study themes, namely behavioural, competition, conservation, disease, human-wildlife conflict, methods papers and wildlife management (Fig. <ns0:ref type='figure' target='#fig_10'>S1</ns0:ref>). Where studies had PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed more than one theme, themes were subjectively allocated as dominant (primary) or secondary based on the aims of the study. Results were visualised and plotted using R (version 3.6. <ns0:ref type='bibr'>3 [21]</ns0:ref>) and R packages listed in Table <ns0:ref type='table'>S2</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Development of a Generic Unified Framework</ns0:head><ns0:p>Following categorisation of definitions, a generic unified framework was developed by grouping and identifying commonalities in definitions of 'direct' and 'indirect' contact, namely relating to space and time. The spatial and temporal limits separating relevant contacts from inconsequential contacts and non-contact events were identified for each study, and a framework was developed based on defining contacts in relation to both space and time. Using this framework, relevant contacts were defined using the parameters of critical space (S C ) and critical time (T C ). We defined S C as the critical space (distance or area) between animals below which a contact relevant to the study is considered to have occurred, and T C as the critical time window within which a relevant contact is considered to have occurred.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>During data categorisation and analyses, many publications were categorised into more than one group due to studying multiple species, using multiple detection methods and having multiple themes, and therefore the number of studies exceed 122 (100%) in several instances reported below.</ns0:p></ns0:div> <ns0:div><ns0:head>Search results, quality appraisal and themes</ns0:head><ns0:p>A total of 43,032 papers were identified by the search terms across all three databases, of which 30,080 were unique results. After screening using the exclusion and inclusion criteria in Table <ns0:ref type='table'>1</ns0:ref>, 122 publications remained in the final analysis (Fig. <ns0:ref type='figure' target='#fig_10'>1</ns0:ref>). Publication date ranged from 1980 to 2019, with 117 (96%) published in the last 20 years (Fig. <ns0:ref type='figure' target='#fig_11'>2</ns0:ref>). Studies conducted in Europe, North America and Africa made up 89% of the results (Table <ns0:ref type='table' target='#tab_4'>S3</ns0:ref>) with the USA and UK producing the most publications (21% and 18%, respectively).</ns0:p><ns0:p>Low study power was mentioned briefly in only 11 (9%) publications and statistical power calculations were not performed. The level of uncertainty was acknowledged in 64 (53%) publications.</ns0:p><ns0:p>Disease was the dominant theme and featured in 80 of 122 studies (66%), followed by humanwildlife conflict <ns0:ref type='bibr'>(22/122; 18%)</ns0:ref>, competition between wildlife and livestock (17/122; 14%), conservation (16/122; 13%), wildlife management (11/122; 9%), behavioural studies (3/122; 2%) and methods validation (2/122; 2%) (Fig. <ns0:ref type='figure' target='#fig_10'>S1</ns0:ref>). Within the disease-themed papers, Mycobacterium bovis was the most studied pathogen (49/80; 61%) followed by foot-and-mouth disease virus Manuscript to be reviewed (8/80; 10%) (Tables <ns0:ref type='table' target='#tab_6'>S4 and S5</ns0:ref>). Wildlife-cattle contacts were the focus of 98 of the 122 studies (80%) and a further 22 studies (18%) focussed on sheep, pigs, farmed deer and camelids. The most studied wildlife species were deer (30/122; 25%), wild pigs [including wild boar] (26/122; 21%) and badgers (25/122; 20%: Fig. <ns0:ref type='figure' target='#fig_12'>S2 and S3</ns0:ref>). The wildlife species were not specified in 11 papers, some of which studied wild ungulates competing for livestock grazing <ns0:ref type='bibr' target='#b127'>[22]</ns0:ref><ns0:ref type='bibr' target='#b128'>[23]</ns0:ref><ns0:ref type='bibr'>[24]</ns0:ref>, others that concerned wildlife as hosts of cattle diseases such as bovine tuberculosis [25-27] and footand-mouth disease <ns0:ref type='bibr'>[28,</ns0:ref><ns0:ref type='bibr'>29]</ns0:ref>, and the remainder that were completely unspecified.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods used to observe livestock-wildlife contacts</ns0:head><ns0:p>Methods that monitored both livestock and wildlife species were used in 88 publications (72%) whereas 34 studies (28%) monitored wildlife only. Camera trapping was the most frequent method of monitoring wildlife (37 studies, 31%), and was most prominently used in badgers, deer and wild pigs (Fig. <ns0:ref type='figure' target='#fig_12'>3</ns0:ref>). GPS collars were the second most used method to monitor wildlife (29 studies, 24%), and while they were also used predominantly on badgers, deer and wild pigs, they were used proportionally more than cameras to monitor predators such as big cats and wolves and large herbivores such as buffalo, wild horses and elephants. Other methods used to monitor wildlife were direct visualisation (21; 17%), farmer questioning (20; 16%), radiotransmitters (17; 14%), activity signs (15; 12%) and proximity loggers (7; 6%). Some studies utilised more than one observation method, and therefore the numbers of studies exceed 122 (100%) Studies that monitored livestock tended to use the same methods as for wildlife, although 10 studies dedicated fewer resources to monitor livestock; for example <ns0:ref type='bibr'>[30]</ns0:ref> used GPS collars to monitor wild deer and farmer questioning to monitor cattle behaviour. Studies that did not monitor livestock tended to infer wildlife-livestock contact from monitoring only the activities of Manuscript to be reviewed wildlife on or around livestock holdings, such as on pasture, in buildings and the shared use of resources such as livestock feed.</ns0:p><ns0:p>A variety of methods were used to observe different types of contact data (Fig. <ns0:ref type='figure' target='#fig_13'>S4</ns0:ref>). Methods such as GPS collars and radio-tracking (telemetry) were used to collect the locations of wildlife (e.g. <ns0:ref type='bibr' target='#b10'>[10,</ns0:ref><ns0:ref type='bibr'>31,</ns0:ref><ns0:ref type='bibr'>32]</ns0:ref>), whereas proximity loggers were used to detect close proximity contacts between livestock and wildlife or with postulated high-risk disease transmission areas such as badger latrines (e.g. <ns0:ref type='bibr' target='#b9'>[9]</ns0:ref>). Camera traps and direct visualisation were used to observe behavioural activity, such as nose-to-nose contacts between cattle and badgers <ns0:ref type='bibr' target='#b113'>[33]</ns0:ref>, foxes taking piglets from farrowing huts <ns0:ref type='bibr' target='#b137'>[34]</ns0:ref> and wild boar eating from cattle troughs <ns0:ref type='bibr'>[35]</ns0:ref>. Some methods were used to detect the presence of wild animals on farms or on pasture only, such as surveys of activity signs to detect wild boar rooting on sheep pasture <ns0:ref type='bibr'>[36]</ns0:ref> and GPS collars to demonstrate the avoidance of livestock pasture by lions <ns0:ref type='bibr'>[37]</ns0:ref>. Thirty studies combined more than one method to monitor wildlife, such as <ns0:ref type='bibr'>[38]</ns0:ref> which combined activity signs, GPS collar data and camera traps to monitor feral swine activity at and around domestic pig pens. The majority of studies, however, used only one method and were able to collect information about the type of contact defined by the study.</ns0:p></ns0:div> <ns0:div><ns0:head>Definitions of direct and indirect contacts</ns0:head><ns0:p>Definitions for both direct contact and indirect contact were provided by 27 studies, with a further four defining direct contact only and 54 defining indirect contact only (Table <ns0:ref type='table'>2</ns0:ref>; Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref>).</ns0:p><ns0:p>Definitions of direct contact tended to focus on the spatial distance between wildlife and livestock at one point in time (Table <ns0:ref type='table'>2</ns0:ref>). Definitions of indirect contact tended to focus on the use Manuscript to be reviewed of space or resources by wildlife in a location previously or subsequently occupied by livestock, within a certain time frame (Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref>). There were some variations to these trends: two studies specified a time frame longer than one time point to define direct contact <ns0:ref type='bibr'>[15,</ns0:ref><ns0:ref type='bibr'>39]</ns0:ref>. The amount of time was usually determined by the context of the study, such as the survival time of a specified pathogen in the environment, known as the critical time window of a contact <ns0:ref type='bibr' target='#b123'>[40]</ns0:ref>. Contacts were also defined in 15 studies as the shared use of resources between livestock and wildlife, such as feed and water. There were large variations between studies in the defined distances and time windows, with direct contact distances ranging from physical contact (seven studies) to within 120 metres of each other (one study), and indirect definitions ranging from within the same camera image (two studies) to within 50 kilometres of a location (one study). There was less variation in definitions between studies with similar contexts and aims. For example, among M. bovis transmission studies in cattle and badgers, the definition of direct contact ranged from physical contact to within two metres (six studies), and indirect contacts were defined as presence on farmland, sharing of resources and visits to badger latrines by cattle (20 studies).</ns0:p><ns0:p>Importantly, no definition of contact was provided in 25 studies (44%) that reported direct contacts, and 34 studies (29%) that reported indirect contacts.</ns0:p><ns0:p>Regardless of the contact definitions or methods used to observe contacts, direct contacts were detected much less frequently than indirect contacts. For example, one study <ns0:ref type='bibr'>[15]</ns0:ref> found no instances of cattle within two metres of deer, compared to over 40,000 indirect contacts of deer with cattle via shared feed. Overall, the median number of direct contacts between wildlife and livestock was in single figures, whereas the median number of indirect contacts occurred in the order of hundreds or even thousands (Table <ns0:ref type='table' target='#tab_6'>4</ns0:ref>). Low study power was acknowledged, but not Manuscript to be reviewed calculated, by 11 studies (9%), and is likely to be a feature of many more which did not report it.</ns0:p><ns0:p>No studies reported adequate power. The low power of studies to observe rare contacts, coupled with the variation in, or lack of, contact definitions, makes it very difficult to compare the effectiveness of the methods used to observe wildlife-livestock contacts.</ns0:p></ns0:div> <ns0:div><ns0:head>Proposed unified framework to define direct and indirect contacts</ns0:head><ns0:p>Space (area or distance between animals) and time were crucial components of the varied definitions of direct and indirect contact in this review. In an effort to unify these parameters, a novel generic framework to categorise wildlife-livestock contacts is proposed in Fig. <ns0:ref type='figure' target='#fig_13'>4</ns0:ref>, based on the locations of individuals in space and time. Using this framework, we propose that the contact type (direct or indirect) is defined using the two parameters S C and T C . Multiple critical thresholds can be used within the framework to differentiate between definitions of direct contact (S C1 and T C1 ) and indirect contact (S C2 and T C2 ). For a direct contact to occur, two individuals are within the same pre-specified critical space (distance or area: S C1 ) within a pre-specified critical time window (T C1 ). Similarly, for an indirect contact to occur, animals are within another prespecified critical space (S C2 ) within another pre-specified critical time window (T C2 ). The reader is directed to Fig. <ns0:ref type='figure' target='#fig_13'>4</ns0:ref> for examples from the literature of possible combinations of S C and T C . T C2 may be the same as T C1 (if S C2 is larger than S C1 : compare example A with example B in Figure <ns0:ref type='figure' target='#fig_13'>4</ns0:ref>) or T C2 may be different from T C1 (in which case T C2 will usually, but not always, be larger than T C1 : compare example A with examples C, D, E and F in Figure <ns0:ref type='figure' target='#fig_13'>4</ns0:ref>). Similarly, S C2 may be the same as S C1 (if T C2 is larger than T C1 : compare example A with examples C and E in Figure <ns0:ref type='figure' target='#fig_13'>4</ns0:ref>) or S C2 may be different from S C1 (in which case S C2 will usually, but not always, be larger than S C1 : compare example A with examples B, D and F in Figure <ns0:ref type='figure' target='#fig_13'>4</ns0:ref>). Same, near and different are Manuscript to be reviewed used here to illustrate spatial and temporal differences between examples. These terms are relative and will vary along with S C and T C depending on the system being studied, the objectives of the study and other factors such as host behaviour and the biology of the pathogen, in the case of disease studies; therefore, values for T C1 , T C2 , S C1 and S C2 should be decided in advance of a study being conducted, and they should be clearly reported when data are presented.</ns0:p><ns0:p>Although the exact values of the critical distance between animals and the critical time window over which this happens will depend on the system being studied as well as the specific objectives of each study, the adoption of this generic framework to define direct and indirect contacts will help identify studies with similar definitions where results are more easily comparable.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The need for a generic unified framework This review has found that definitions of contact are wide-ranging and highly dependent on the context of the study. Definitions can vary depending on the species and demographics of the wildlife and livestock involved, the methods used to detect contacts and the system being studied such as the environmental conditions and pathogen characteristics in studies where contacts are representative of disease transmission. Definitions of direct contact were extremely diverse, ranging from direct physical contact to animals being merely within a hundred metres of each other. Indirect contact ranged from animals sharing resources, being within five kilometres of each other or overlapping in home ranges, and the time window that these events occurred in varied from hours to weeks.</ns0:p><ns0:p>The aim of this generic unified framework is to promote consistent reporting of definitions of contacts enabling comparisons to be made between the approaches of wildlife-livestock contact studies, regardless of the species or pathogen studied or the context of the study. This is needed because our systematic review found that while wildlife-livestock contact data was collected in terms of space and time, some studies omitted space or time in their definitions, or there was a complete lack of a definition. Conflicting and overlapping definitions of direct and indirect contact were also identified. Making any sort of meaningful comparison between such studies is challenging. For example it is difficult to assess what, if any, implications there are for deercattle disease transmission from a behavioural study showing deer avoid cattle despite similar habitat preferences [41], without knowing what types of contact (e.g., direct or indirect; what specific types) were likely to be meaningful. It is even difficult to compare studies within the same system, for example establishing the relevance of cattle-badger contacts for bovine tuberculosis transmission when some studies define a contact as 'presence on farm <ns0:ref type='bibr'>' [42, 43]</ns0:ref> and others define it as 'presence in buildings', and neither study defines the time window. Use of the generic unified framework would enable consistent reporting of definitions between studies and is an important step if the results of wildlife-livestock contact studies are to be comparable.</ns0:p></ns0:div> <ns0:div><ns0:head>Applications of a generic unified framework</ns0:head><ns0:p>Models that incorporate empirical rather than theoretical information on the frequency and duration of contacts important for disease transmission are more likely to be useful for disease mitigation <ns0:ref type='bibr' target='#b11'>[11]</ns0:ref>. The use of a standardised definition framework in future studies of livestockwildlife contacts would enable consistency in datasets and enable the retrospective selection of contact data relevant to a particular model, which could then be incorporated in a similar way to the data used in recent bovine tuberculosis transmission models <ns0:ref type='bibr'>[16,</ns0:ref><ns0:ref type='bibr'>44]</ns0:ref>. The generic unified framework proposed in this current paper could also be useful in designing livestock-wildlife contact studies, since defining the type of contact to be detected -in addition to practical considerations, such as an area's signal strength affecting the viability of GPS device use -helps with the choice of detection method. The framework is also flexible and applicable to different contexts, species and diseases since it allows for the variation in definitions seen in this review, and it is hoped it will broaden the range of future livestock-wildlife contact studies.</ns0:p><ns0:p>To resolve human-wildlife conflicts usually requires robust livestock-wildlife contact studies. At least 120 studies that only used predation events to infer livestock-wildlife contacts were excluded from the review, yet predators -particularly wolves -were the second most commonly studied group of wild mammals. Given that predation studies appear to form a large proportion of wildlife-livestock contact studies, this is an area where adoption of the generic framework could help design meaningful contact studies to evaluate preventive measures without relying solely on predation events.</ns0:p></ns0:div> <ns0:div><ns0:head>Further development of the generic unified framework</ns0:head><ns0:p>The generic unified framework does not provide an overall consensus on definitions of direct and indirect contact, but does provides a structure with which to start this process. While using the generic unified framework provides a standardised definition of contact in time and space, identifying the types of contact that are relevant to the study, and thus the values of S C and T C , will vary depending on the objectives and context of each study. While a universally accepted set of definitions for contacts is difficult to devise, we hope that by defining Sc and Tc here we will encourage the start of the debate around (and between) studies of similar contexts, and perhaps then acceptable ranges for these values will emerge. Developing a framework for deriving S C an T C , based upon the species studied, environment, pathogen and methodology is beyond the scope of this review, and would be a necessary next step so that wildlife-livestock contact rates could be comparable between studies of similar contexts. For example, for disease studies, it would be advisable that S C and T C were based on values below which transmission is likely to occur, such as aerosol dispersion distance and environmental survivability. For any system, there may be a range of appropriate values for S C and T C .</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The generic unified framework presented in this paper is a step towards being able to compare observation methods and contact data in order to standardise and evaluate different monitoring methods. This is important as our systematic review revealed that the methods used to observe livestock-wildlife contacts to date have often had low detection rates and therefore been of low power due to the difficulty of monitoring cryptic wildlife species, and the rarity of some types of wildlife-livestock contacts, particularly direct contacts. Further considerations for the comparison of observation methods are the representativeness of individuals monitored, especially with methodologies that require the marking of individuals such as GPS and proximity loggers, and a standardised system for relativizing the number of contacts with regards to the total observation effort. For example, two studies will not be comparable if study A only uses 3 camera traps and study B uses 100 camera traps, or if study C collects GPS locations every hour when study D collects only one GPS fix per day. Reporting representativeness of individuals and relativizing contact rates in terms of total population will go some way to establishing the power of wildlife-contact studies. Furthermore, it may be useful for studies to indicate the detection limits of the methodology used, in terms of space and time.</ns0:p></ns0:div> <ns0:div><ns0:head>Scope of existing wildlife-livestock contact studies</ns0:head><ns0:p>This review has identified the narrow scope and limited geographic range of livestock-wildlife contact studies, which means the data summarised in this review should not be considered representative of all wildlife-livestock contacts worldwide. The majority of studies focussed on cattle-wildlife contacts and diseases of cattle. Bovine tuberculosis (infection with M. bovis) featured prominently, indicative of the economic and potentially zoonotic importance of this disease to the USA and UK, where the most livestock-wildlife contact studies were conducted <ns0:ref type='bibr'>[45,</ns0:ref><ns0:ref type='bibr'>46]</ns0:ref>. Foot-and-mouth-disease was the most studied viral pathogen and this is most likely in saiga antelope <ns0:ref type='bibr' target='#b130'>[49]</ns0:ref><ns0:ref type='bibr'>[50]</ns0:ref><ns0:ref type='bibr'>[51]</ns0:ref>. If we are to collect more (and better) wildlife-livestock contact data that include a broader range of species and contexts, careful consideration must be used when selecting the most effective and practical observational method for monitoring cryptic wildlife species.</ns0:p><ns0:p>This review highlights that observing contacts between multiple species is possible and can yield high quality information. Increasing the efficiency of monitoring methods would justify their use for more applications. Health surveillance systems at livestock-wildlife interfaces have been suggested as a method to detect and control emerging diseases along with preventing contact between wildlife and livestock <ns0:ref type='bibr'>[52]</ns0:ref>. Preventing high-risk contacts may be more cost-effective than surveillance, but the effectiveness of prevention strategies will need to be evaluated by monitoring contacts, or lack thereof. More efficient monitoring will also allow for quantitative risk assessments of wildlife-livestock contacts which are presently difficult to conduct due to a limited understanding of potential contacts leading to pathogen transmission <ns0:ref type='bibr'>[53]</ns0:ref>. Some observation methods such as camera traps are likely to have the ability to identify new potential transmission routes between livestock and wildlife (e.g., the use of cattle salt licks by racoons Manuscript to be reviewed may be the origin of rapidly emerging human diseases is a priority to prevent future pandemics <ns0:ref type='bibr'>[55]</ns0:ref>. In situations where human infections are mediated by livestock, rapid implementation of observational methods to detect contacts between wildlife and livestock could more quickly identify wildlife hosts and risky behaviours. In order to determine the efficiency and efficacy of different observational methods, the methods used and data collected by them must be comparable, hence the need for a unified framework.</ns0:p></ns0:div> <ns0:div><ns0:head>Limitations of this review</ns0:head><ns0:p>Our study has some limitations which we summarise here. At present, our generic unified framework does not explicitly account for disease transmission via vectors or fomites, although the latter will to some extent be captured within our definition of indirect contact. In order that observation methods were likely to be comparable between species, we focussed on terrestrial mammals so did not address diseases primarily hosted by birds or bats such as avian influenza, Nipah virus and Hendra virus. Small terrestrial mammals (&lt;5kg) were also not included for this reason, and because a disproportionate number of rodent studies focus on their roles as laboratory animals or farm pests, and not on contacts with livestock. While the generic unified framework may be applicable to these types of wildlife, it is unclear which observational methods seen in this review would be most effective or efficient, and the conclusions drawn from this review may not be reflective of systems that involve other taxa .</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>As human populations continue to expand and agriculture encroaches further on wildlife habitats, disease spill-over (in both directions) between wildlife, livestock and humans is becoming more frequent <ns0:ref type='bibr' target='#b0'>[1]</ns0:ref>. As a result, the study of contacts between livestock and wildlife is receiving ever increasing attention. This systematic review of the observational methods used to 12.</ns0:p><ns0:p>Robertson, A., J. Judge, G. Wilson, I.J. Vernon, R.J. Delahay, and R.A.</ns0:p><ns0:p>McDonald, Predicting badger visits to farm yards and making predictions available to farmers. PloS one, 2019. 14(5). <ns0:ref type='bibr' target='#b146'>13</ns0:ref> Manuscript to be reviewed Manuscript to be reviewed Examples from studies of contacts between badgers and cattle are provided to demonstrate the use of the framework. S C1 represents 'critical space 1', the maximum amount of space (distance or area) within which direct contact may occur; and T C1 represents 'critical time 1', the maximum duration of time within which direct contact may occur. Similarly, S C2 represents 'critical space 2', the maximum amount of space (distance or area) within which indirect contact may occur; and T C2 represents 'critical time 2', the maximum duration of time within which indirect contact may occur. Same, near and different are used here to illustrate spatial and temporal differences between examples (see Tables <ns0:ref type='table' target='#tab_6'>3 and 4</ns0:ref> for values and ranges for these parameters from published studies). Note that the lighter blue shading does not extend all the way to the right of the diagram because there is an upper limit to the value of time which T C2 can take: beyond this value, animals in the same (or nearby) space will not be in contact. </ns0:p></ns0:div> <ns0:div><ns0:head>Exclusion Criteria</ns0:head></ns0:div> <ns0:div><ns0:head>Inclusion Criteria</ns0:head><ns0:p>The study aims to collect, use, or analyse data to establish at least one of the following: 1. A quantifiable measure of direct contact between wildlife and livestock, where direct contact is defined as physical contact between at least one wild animal and one farm animal .</ns0:p></ns0:div> <ns0:div><ns0:head n='2.'>A quantifiable measure of indirect contact between wildlife and livestock,</ns0:head><ns0:p>where indirect contact is defined as contact between at least one wild animal and a resource used by at least one farm animal including, but not limited to, food, water and space 3. Characterise and establish the type of, or risk factors for, direct or indirect contact between wildlife and livestock, as defined above.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 2(on next page)</ns0:head><ns0:p>Definitions of direct contact from a systematic review of studies of livestock and wildlife.</ns0:p><ns0:p>Parameters are listed in ascending order of distance and time between animals and time windows. Definitions that have been used for both direct and indirect contacts are shaded grey. Percentages are rounded to the nearest integer.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed A summary of the types of contact(s) reported between livestock and wildlife, and the method(s) used to observe contacts, from a systematic review of 122 studies.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)Manuscript to be reviewed explained by its broad geographical spread and high economic impact[47]. This demonstrates the human-centric view of the wildlife-livestock interface, with most focus on the impacts on humans and domestic animals, and very little (if any) focus on the value of wildlife[48]. There were, however, some livestock-wildlife contact studies of high impact conservation importance such as infection with Mannheimia spp. in bighorn sheep (Ovis canadensis) and Pasteurella spp.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>[</ns0:head><ns0:label /><ns0:figDesc>26]), and may identify livestock-wildlife contacts previously not considered (e.g., observing farm visits by foxes during a study focussing on badgers [54]). Identifying wildlife species that PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>9( 5 )</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>: p. 18-26. 21. 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Southeastern Naturalist, 2015. 14(2): p. 267-280.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 1 Flow</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 2 Distribution</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 3 Observation</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 4 A</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='41,42.52,70.87,525.00,525.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='43,42.52,70.87,525.00,294.75' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head /><ns0:label /><ns0:figDesc>Applied Animal Behaviour Science, 2015. 171: p. 170-176. 43. 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White, Interactions between four species in a complex wildlife: livestock disease the risks of infectious diseases to wildlife species. Royal Society open science, Cornelis, F. Casabianca, and E.M.C. Etter, Questionnaire-based assessment of</ns0:cell></ns0:row><ns0:row><ns0:cell>30.</ns0:cell><ns0:cell>Pruvot, M., D. Seidel, M.S. Boyce, M. Musiani, A. Massolo, S. Kutz, and K. community: implications for Mycobacterium bovis maintenance and transmission. 2019. 6(1): p. 181043. wild boar/domestic pig interactions and implications for disease risk management</ns0:cell></ns0:row><ns0:row><ns0:cell>52.</ns0:cell><ns0:cell>Orsel, What attracts elk onto cattle pasture? Implications for inter-species disease European Journal of Wildlife Research, 2016. 62(1): p. 51-64. Gortazar, C., I. Diez-Delgado, J.A. Barasona, J. Vicente, J. De La Fuente, and M. in Corsica. Frontiers in Veterinary Science, 2017. 4(December): p. 198.</ns0:cell></ns0:row><ns0:row><ns0:cell>41. 63.</ns0:cell><ns0:cell>transmission. Preventive Veterinary Medicine, 2014. 117(2): p. 326-339. Mattiello, S., W. Redaelli, C. Carenzi, and C. Crimella, Effect of dairy cattle Boadella, The wild side of disease control at the wildlife-livestock-human Trabucco, B., F. Chabrier, F. Jori, O. Maestrini, D. Corn&#233;lis, E. Etter, S. Molia, A.</ns0:cell></ns0:row><ns0:row><ns0:cell>31.</ns0:cell><ns0:cell>Raizman, E.A., H.B. Rasmussen, L.E. King, F.W. Ihwagi, and I. Douglas-husbandry on behavioural patterns of red deer (Cervus elaphus) in the Italian interface: a review. Frontiers in veterinary science, 2015. 1: p. 27. Relun, and F. Casabianca, Stakeholder's practices and representations of contacts</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>between domestic and wild pigs: a new approach for disease risk assessment?</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Acta argiculturae Slovenica, 2013: p. 117-122.</ns0:cell></ns0:row></ns0:table><ns0:note>Mizutani, F., M. Kadohira, and B. Phiri, Livestock-wildlife joint land use in dry lands of Kenya: a case study of the Lolldaiga Hills ranch. Animal Science Journal, 2012. 83(6): p. 510-516. 23. Sitters, J., I.M.A. Heitk&#246;nig, M. Holmgren, and G.S.O. Ojwang, Herded cattle and Tryland, Cattle owners' awareness of bovine tuberculosis in high and low prevalence settings of the wildlife-livestock interface areas in Zambia. BMC Veterinary Research, 2010. 6(21): p. (20 April 2010). 26. Witmer, G., A.E. Fine, J. Gionfriddo, M. Pipas, K. Shively, K. Piccolo, and P. Burke, Epizootiologic survey of Mycobacterium bovis in wildlife and farm environments in northern Michigan. Journal of Wildlife Diseases, 2010. 46(2): p. 368-378. 27. Katale, B.Z., E.V. Mbugi, E.D. Karimuribo, J.D. Keyyu, S. Kendall, G.S. Kibiki, P. Godfrey-Faussett, A.L. Michel, R.R. Kazwala, P.v. Helden, and M.I. Matee, Prevalence and risk factors for infection of bovine tuberculosis in indigenous cattle in the Serengeti ecosystem, Tanzania. BMC Veterinary Research, 2013. 9(267): p. (30 December 2013). 28. Brahmbhatt, D.P., G.T. Fosgate, E. Dyason, C.M. Budke, B. Gummow, F. Jori, M.P. Ward, and R. Srinivasan, Contacts between domestic livestock and wildlife at the Kruger National Park Interface of the Republic of South Africa. Preventive Hamilton, Feasibility study on the spatial and temporal movement of Samburu's PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020) Manuscript to be reviewed cattle and wildlife in Kenya using GPS radio-tracking, remote sensing and GIS. 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VerCauteren, Movement and habitat use of feral swine near domestic swine facilities. Wildlife Society Bulletin, 2012. 36(1): p. 130-138. 39. Cooper, S.M., H.M. Scott, G.R.d.l. Garza, A.L. Deck, and J.C. Cathey, Alps. Applied Animal Behaviour Science, 2002. 79(4): p. 299-310. PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020) Manuscript to be reviewed 42. Mullen, E.M., T. MacWhite, P.K. Maher, D.J. Kelly, N.M. Marples, and M. Good, The avoidance of farmyards by European badgers Meles meles in a medium density population. O'Brien, D.J., S.M. Schmitt, S.D. Fitzgerald, and D.E. Berry, Management of bovine tuberculosis in Michigan wildlife: current status and near term prospects. Veterinary microbiology, 2011. 151(1-2): p. 179-187. 47. Knight-Jones, T. and J. Rushton, The economic impacts of foot and mouth disease-What are they, how big are they and where do they occur? Preventive veterinary medicine, 2013. 112(3-4): p. 161-173. 48. Chardonnet, P., B.d. Clers, J. Fischer, R. Gerhold, F. Jori, and F. Lamarque, The value of wildlife. Revue scientifique et technique-Office international des &#233;pizooties, 2002. 21(1): p. 15-52. 49. Clifford, D.L., B.A. Schumaker, T.R. Stephenson, V.C. Bleich, M.L. Cahn, B.J. Gonzales, W.M. Boyce, and J.A.K. Mazet, Assessing disease risk at the wildlifelivestock interface: a study of Sierra Nevada bighorn sheep. Biological Miller, R.S., M.L. Farnsworth, and J.L. Malmberg, Diseases at the livestockwildlife interface: status, challenges, and opportunities in the United States. Preventive veterinary medicine, 2013. 110(2): p. 119-132. 54. O'Mahony, D.T., Multi-species visit rates to farmyards: implications for Campbell, E.L., A.W. Byrne, F.D. Menzies, K.R. McBride, C.M. McCormick, M. Scantlebury, and N. Reid, Interspecific visitation of cattle and badgers to fomites: A transmission risk for bovine tuberculosis? Ecology and Evolution, 2019. 9(15):</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head /><ns0:label /><ns0:figDesc>1. Study does not involve a wild mammal species where adults are typically heavier than 5kg. 2. Study does not involve a farmed mammal species where adults are typically heavier than 5kg, or farmland associated with such livestock. 3. Study does not attempt to collect, use or analyse data to investigate contacts between wild animals and livestock or livestock farms. 4. Study does not attempt to collect, use or analyse data to establish at least one of the following: characterisation of, the nature of, frequency of, or risk factors for, contacts between wildlife and livestock. 5. Full text not available in English. 6. Full text not accessible to reviewers. 7. The method of recording livestock-wildlife contacts relies solely on predation events where the only observations are livestock kills or scat analysis 8. Wild animals were non-free-living, pre-tamed or relocated for the purpose of the study.</ns0:figDesc><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Direct contact' definition Number (%) of publications using this definition % Cumulative References</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>At least two individuals</ns0:cell><ns0:cell>9 (16)</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell>[33, 56-63]</ns0:cell></ns0:row><ns0:row><ns0:cell>making physical contact</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals close enough to</ns0:cell><ns0:cell>1 (2)</ns0:cell><ns0:cell>18</ns0:cell><ns0:cell>[64]</ns0:cell></ns0:row><ns0:row><ns0:cell>inhale expired breath</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within one</ns0:cell><ns0:cell>1 (2)</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>[15]</ns0:cell></ns0:row><ns0:row><ns0:cell>metre of the same location</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>within one second</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within two</ns0:cell><ns0:cell>5 (9)</ns0:cell><ns0:cell>29</ns0:cell><ns0:cell>[9, 40, 65-</ns0:cell></ns0:row><ns0:row><ns0:cell>metres of each other</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>67]</ns0:cell></ns0:row><ns0:row><ns0:cell>Individuals within five</ns0:cell><ns0:cell>3 (5)</ns0:cell><ns0:cell>34</ns0:cell><ns0:cell>[8, 68, 69]</ns0:cell></ns0:row><ns0:row><ns0:cell>metres of each other</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within the same</ns0:cell><ns0:cell>5 (9)</ns0:cell><ns0:cell>43</ns0:cell><ns0:cell>[35, 70-73]</ns0:cell></ns0:row><ns0:row><ns0:cell>camera image</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 20 metres</ns0:cell><ns0:cell>1 (2)</ns0:cell><ns0:cell>45</ns0:cell><ns0:cell>[74]</ns0:cell></ns0:row><ns0:row><ns0:cell>of each other</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 20 metres</ns0:cell><ns0:cell>1 (2)</ns0:cell><ns0:cell>46</ns0:cell><ns0:cell>[39]</ns0:cell></ns0:row><ns0:row><ns0:cell>of the same location within</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>15 minutes</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within same</ns0:cell><ns0:cell>1 (2)</ns0:cell><ns0:cell>48</ns0:cell><ns0:cell>[34]</ns0:cell></ns0:row><ns0:row><ns0:cell>farm building</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within holding</ns0:cell><ns0:cell>1 (2)</ns0:cell><ns0:cell>50</ns0:cell><ns0:cell>[75]</ns0:cell></ns0:row><ns0:row><ns0:cell>(farm) boundary</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 100</ns0:cell><ns0:cell>2 (4)</ns0:cell><ns0:cell>54</ns0:cell><ns0:cell>[76, 77]</ns0:cell></ns0:row><ns0:row><ns0:cell>metres of each other</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 120</ns0:cell><ns0:cell>1 (2)</ns0:cell><ns0:cell>55</ns0:cell><ns0:cell>[78]</ns0:cell></ns0:row><ns0:row><ns0:cell>metres of each other</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Studies that reported the</ns0:cell><ns0:cell>25 (45)</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>[13, 22, 25,</ns0:cell></ns0:row><ns0:row><ns0:cell>frequency of, types of, or</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>26, 29, 30,</ns0:cell></ns0:row><ns0:row><ns0:cell>risk factors for, direct</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>41, 79-96]</ns0:cell></ns0:row><ns0:row><ns0:cell>contacts without first</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>defining them</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>56 (100)</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>1 '</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Definitions of indirect contact from a systematic review of studies of livestock and wildlife.Parameters are listed in ascending order of distance and time. Definitions that have been used for both direct and indirect contacts are shaded grey. Percentages are rounded to the nearest integer.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>'Indirect contact' definition</ns0:cell><ns0:cell>Number (%) of</ns0:cell><ns0:cell cols='2'>% Cumulative References</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>publications</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>using this</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>definition</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within the same camera</ns0:cell><ns0:cell>2 (2)</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>[73, 97]</ns0:cell></ns0:row><ns0:row><ns0:cell>image</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Two individuals photographed by the</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>[35]</ns0:cell></ns0:row><ns0:row><ns0:cell>same camera trap within a specific time</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>interval</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Latrine (faecal pits) visits</ns0:cell><ns0:cell>5 (4)</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>[9, 65, 98-</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>100]</ns0:cell></ns0:row><ns0:row><ns0:cell>Individuals visiting the same food or</ns0:cell><ns0:cell>2 (2)</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>[25, 62]</ns0:cell></ns0:row><ns0:row><ns0:cell>water source at the same time</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals visiting the same food and</ns0:cell><ns0:cell>13 (11)</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>[15, 27, 56,</ns0:cell></ns0:row><ns0:row><ns0:cell>water sources at unspecified time</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>63, 66, 68,</ns0:cell></ns0:row><ns0:row><ns0:cell>intervals</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>70, 89, 90,</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>101-104]</ns0:cell></ns0:row><ns0:row><ns0:cell>Individuals in the same space at the same</ns0:cell><ns0:cell>2 (2)</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>[106, 107]</ns0:cell></ns0:row><ns0:row><ns0:cell>time</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals in the same space at different</ns0:cell><ns0:cell>3 (3)</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>[31, 58, 105]</ns0:cell></ns0:row><ns0:row><ns0:cell>times</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals in the same space at</ns0:cell><ns0:cell>3 (3)</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>[10, 12, 69]</ns0:cell></ns0:row><ns0:row><ns0:cell>unspecified time interval</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals using the same food or water</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>28</ns0:cell><ns0:cell>[40]</ns0:cell></ns0:row><ns0:row><ns0:cell>source within six hours</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 20 metres of the same</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>28</ns0:cell><ns0:cell>[39]</ns0:cell></ns0:row><ns0:row><ns0:cell>location within six hours</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 30 metres of livestock</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>29</ns0:cell><ns0:cell>[108]</ns0:cell></ns0:row><ns0:row><ns0:cell>or feed</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Presence in farm buildings at unspecified</ns0:cell><ns0:cell>5 (4)</ns0:cell><ns0:cell>34</ns0:cell><ns0:cell>[26, 33, 59,</ns0:cell></ns0:row><ns0:row><ns0:cell>time interval</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>109, 110]</ns0:cell></ns0:row><ns0:row><ns0:cell>Individuals within 50 metres of each</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>34</ns0:cell><ns0:cell>[85]</ns0:cell></ns0:row><ns0:row><ns0:cell>other</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 52 metres of the same</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>35</ns0:cell><ns0:cell>[111]</ns0:cell></ns0:row><ns0:row><ns0:cell>location within one hour</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 120 metres</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>36</ns0:cell><ns0:cell>[28]</ns0:cell></ns0:row><ns0:row><ns0:cell>Individuals using the same space with</ns0:cell><ns0:cell>2 (2)</ns0:cell><ns0:cell>38</ns0:cell><ns0:cell>[24, 72]</ns0:cell></ns0:row><ns0:row><ns0:cell>seven days</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals using the same space within</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>39</ns0:cell><ns0:cell>[74]</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)Manuscript to be reviewed 'Indirect</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>contact' definition Number (%) of publications using this definition % Cumulative References</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>15 days</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Presence on pasture at the same time</ns0:cell><ns0:cell>5 (4)</ns0:cell><ns0:cell>43</ns0:cell><ns0:cell>[49, 64, 91,</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>95, 96]</ns0:cell></ns0:row><ns0:row><ns0:cell>Presence on pasture at unspecified time</ns0:cell><ns0:cell>8 (7)</ns0:cell><ns0:cell>50</ns0:cell><ns0:cell>[30, 34, 36,</ns0:cell></ns0:row><ns0:row><ns0:cell>interval</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>67, 112-115]</ns0:cell></ns0:row><ns0:row><ns0:cell>Presence on pasture at different times</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>51</ns0:cell><ns0:cell>[116]</ns0:cell></ns0:row><ns0:row><ns0:cell>At holding boundary and on pasture at</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>52</ns0:cell><ns0:cell>[117]</ns0:cell></ns0:row><ns0:row><ns0:cell>unspecified time interval</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Presence on farm at unspecified time</ns0:cell><ns0:cell>12 (10)</ns0:cell><ns0:cell>62</ns0:cell><ns0:cell>[42, 43, 50,</ns0:cell></ns0:row><ns0:row><ns0:cell>interval</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>54, 88, 94,</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>118-123]</ns0:cell></ns0:row><ns0:row><ns0:cell>At holding (farm) boundary</ns0:cell><ns0:cell>3 (3)</ns0:cell><ns0:cell>65</ns0:cell><ns0:cell>[60, 61, 124]</ns0:cell></ns0:row><ns0:row><ns0:cell>Individuals within 120 metres of the</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>66</ns0:cell><ns0:cell>[78]</ns0:cell></ns0:row><ns0:row><ns0:cell>same location at different times</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 300 metres of the</ns0:cell><ns0:cell>2 (2)</ns0:cell><ns0:cell>67</ns0:cell><ns0:cell>[125, 126]</ns0:cell></ns0:row><ns0:row><ns0:cell>same location within 15 days</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 500 metres of the</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>68</ns0:cell><ns0:cell>[93]</ns0:cell></ns0:row><ns0:row><ns0:cell>same location within six weeks</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 500 metres from</ns0:cell><ns0:cell>2 (2)</ns0:cell><ns0:cell>70</ns0:cell><ns0:cell>[75, 76]</ns0:cell></ns0:row><ns0:row><ns0:cell>holding (farm) boundary</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Individuals within 50 kilometres of the</ns0:cell><ns0:cell>1 (1)</ns0:cell><ns0:cell>71</ns0:cell><ns0:cell>[51]</ns0:cell></ns0:row><ns0:row><ns0:cell>same location within three months</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Studies that reported the frequency of,</ns0:cell><ns0:cell>34 (29)</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>[22, 23, 29,</ns0:cell></ns0:row><ns0:row><ns0:cell>types of, or risk factors for, indirect</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>32, 37, 41,</ns0:cell></ns0:row><ns0:row><ns0:cell>contacts without first defining them</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>79-84, 89,</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>92, 127-146]</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>116 (100)</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 4 (on next page)</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Type of contact recorded Examples of the types of contact(s) reported between each livestock and wildlife species Referenc Livestock Wildlife Method(s) *</ns0:head><ns0:label /><ns0:figDesc>being within two metres of each other. Cattle investigating badger setts and latrines. Badgers visiting farms, feed stores and cattle houses and foraging on cattle pasture. Shared use of water and feed troughs</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Direct</ns0:cell><ns0:cell>Indirect</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Camelid</ns0:cell><ns0:cell>Antelope</ns0:cell><ns0:cell>Multiple (d,k,q)</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Shared space use</ns0:cell><ns0:cell>[51]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Camelid</ns0:cell><ns0:cell cols='2'>Direct visualisation Yes</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Wild camelids grazing with domestic llamas</ns0:cell><ns0:cell>[79]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Multiple (a,d)</ns0:cell><ns0:cell>No</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Shared forage</ns0:cell><ns0:cell>[130]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Antelope</ns0:cell><ns0:cell>Activity signs</ns0:cell><ns0:cell>No</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Shared space use</ns0:cell><ns0:cell>[129]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell cols='2'>Direct visualisation No</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Unspecified contact</ns0:cell><ns0:cell>[145]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Model #</ns0:cell><ns0:cell>No</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>No contacts observed</ns0:cell><ns0:cell>[92]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Multiple (a,k,q)</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Shared space use</ns0:cell><ns0:cell>[51]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Questioning</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Shared space use. Shared grazing and water source</ns0:cell><ns0:cell>[93]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Activity signs</ns0:cell><ns0:cell>No</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Cattle investigating or grazing at badger latrines and setts on pasture</ns0:cell><ns0:cell>[98]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Camera</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Yes</ns0:cell><ns0:cell>Badgers and cattle</ns0:cell><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48700:1:1:NEW 10 Sep 2020)</ns0:note> </ns0:body> "

"Response to Reviewers Dear Editor, We greatly appreciate the time the three reviewers have taken to provide this constructive feedback. Please see below for our responses in red italics to each of their comments. In particular, the discussion has been significantly restructured to address the reviewers’ concerns. We believe the manuscript is much improved as a result of these revisions. We hope that you will now consider the manuscript fit for publication and look forward to hearing from you in due course. Yours faithfully Sonny Bacigalupo, on behalf of all co-authors Reviewer 1 (Anonymous) Basic reporting The MS meet standards  Experimental design The approach, literature search, filtering and analysis meet the standards  Validity of the findings A relevant stop forward on standardizing contact data art the wildlife-livestock interface  Comments for the Author The aim of this study was to systematically review the reasons for, and observational methods used in, studies investigating livestock-wildlife contacts, and to propose a generalized framework for defining contacts between livestock and wildlife. Definitively, as the authors claim, a standardized generic template for defining livestock-wildlife contacts is needed. And this MS is an important step forward.  The MS is excellent as a comprehensive review on the topic. Thank you The authors show in the results section the novel generic framework to categorise wildlife-livestock contacts (Fig. 4), based on the locations of individuals in space and over time. It shroud previously be introduced also in Material and Methods (the general approach) We had considered the generic unified framework to be an output of this research, and so previously only mentioned it in the Methods section. However, you are right that developing the model is an important part of the methods. We have therefore expanded the ‘Development of a Generic Unified Framework’ section of the Methods (lines 163-172) to introduce general information on the space and time elements of the generic framework. We then provide specific detail on these in the Results section (lines 336-376). L123: legend for Figure S1 (two categories by column??) explain).  We have modified the legend and added a clarification on line 130 to make this clearer. Legend now reads: “Figure S1: Themes of the review. Livestock-wildlife studies (n = 122) grouped by themes that emerged during data extraction. Where studies had more than one theme, each theme was identified as either primary (main) or secondary (supportive) based on the aims of the study; hence the total number of primary themes in this figure exceeds the number of studies.” L129. Remark that research addressing resource use by wildlife and livestock, but not directly the contacts, is included. This is implied in our pre-defined definitions of contact but a clarifying sentence has been added on line 144: “Therefore, studies that investigated wildlife and livestock shared resource use, but did not explicitly investigate contacts, were included.” L147. Define “study power”: ability to detect rare contacts?? We did mean the ability to detect rare contacts, but more generally the likelihood that any contacts that occur will be detected. This is now clarified in line 148: “Where available, the likelihood of detecting contacts, or power, for each study was recorded.” We have added text to indicate that some studies mentioned low power, but none performed statistical calculations to determine power (line 210). L148. Authors mention: “Conclusions were robust and directly derived from the results in 109 (89%) publications. Is that subjective”. Provide indication how you assessed this (they all are peer-reviewed papers), did you question conclusions in 11% remaining? This is a subjective measure, and the 11% remaining would usually have formed conclusions that were more abstract or theoretical without referring to the results of the study, although these conclusions were not necessarily unbelievable. On reflection, due to the subjective nature of the quality scores and the difficulty in drawing objective conclusions, and as the scores were not influential in the inclusion or exclusion of studies, we have now deleted the section on quality scores from the review. L160: do you include wild boar as wild pig? Specify since it is used over the MS (e.g. fig. 3). Yes, wild boar are included as wild pig, as the distinction between ‘feral swine’ and wild boar in the context of wildlife-livestock contacts seems arbitrary. We have added a clarification on line 237. Further analyses (i..e according to system, or geography) of paper scores can provide interesting results. This may be true, but we feel that the subjective nature of the scores may cause the conclusions drawn from such analyses to be questionable, and so have not pursued this suggestion. L202. What about locations first visited by livestock? This is a good point. Some studies investigated the influence of domestic grazing on wildlife space and resource use. An amendment has been made to line 293: “Definitions of indirect contact tended to focus on the use of space or resources by wildlife in a location previously or subsequently occupied by livestock, within a certain time frame.” L229. The proposed unified framework to define direct and indirect contacts must be introduced (the approach) in Mat & Met), and briefly commented in the summary. We now explain the development of the generic unified framework in the Materials and Methods section (lines 163-172) and provide specific details in the Results section (lines 336-376). L236: define SC (critical distance between animals, depending on the system being studied as well as the specific objectives of each study, I only found the definition in legend of figure 34) and Tc (critical time over which critical distance happens between 2 individuals, depending on the system being studied as well as the specific objectives of each study) (maybe in Mat & Met). We now define Sc and Tc on lines 168-172. Discussion. Proposed unified framework: I agree the approach of this generic framework to define direct and indirect contacts will help ensure results between studies are more easily comparable. However, the main problem: the definition of Sc1, Sc2, Tc2, and Tc2 according to the system and specific conditions. This, itself, needs a common framework (guidance or rules) which is not addressed here and vaguely commented. Then, studies can be comparable. For discussion and future research: I encourage authors to discuss if it can be developed a generic framework to define Sc1,2, Tc1,2 as a function of objective characteristics of the pathogen- host-environmental systems and objectives. This would be also very useful for researchers to approach their study systems to generate comparable values and use the appropriate methodology (and not to make the definition on contact dependent on methods or other practical issues). This would be useful. This suggestion, as well as an example of how Sc and Tc could be defined in disease transmission studies, is now included in lines 490-499. Provide any clue for what is near or different in Figure 4 for a specific system (this distinction, as it is presented, is vague). Most discussion could be part of the introduction. I encourage authors to expand discussion on the abovementioned, on the limitations of this framework, which need more detail (e.g. definition on near and different) and a parallel framework for definition of Sc1,2, Tc1,2 (in a separate research) The reviewer is right in saying that the difference between near and different is relative. We use these terms broadly in Figure 4 to illustrate the types of difference in spatiotemporal values and definitions between studies. We have added some clarification and acknowledgment of this on lines 371-374. L251: Meaningful comparison only to a certain extend. See my previous comment. We agree with the reviewer. It is still difficult to meaningfully compare results, but the framework will help compare definitions. We believe we have clarified this on lines 409-411: “The aim of this generic unified framework is to promote consistent reporting of definitions of contacts enabling comparisons to be made between the approaches of wildlife-livestock contact studies, regardless of the species or pathogen studied or the context of the study.” L329: Agree! This is a necessary step forward.  Thank you! Reviewer 2 (Anonymous) Comments for the Author The present manuscript performs a systematic review of papers studying wildlife-livestock contacts, and subsequently propose a generalised framework for defining direct and indirect contacts between domestic and wild mammals (Figure 4). The manuscript addresses a highly relevant topic, especially in the current situation of sanitary uncertainty, in which we must increase efforts in sanitary surveillance and in the implementation of control measures of zoonotic diseases. Besides, the review includes the most important published studies of the topic.  However, I have some concerns about the methodology, discussion and the applicability of the proposed framework: Methodology:  1. Line 88-89: As stated at the end of the paragraph, a contact could be an association between animals and farms, so, this must be included in the formal definition of the contact.  We have extended the definition on line 105 to clarify contact means an ‘activity implying an interaction or association between species including the shared use of resources such as farmland’. 2. Line 96-97 and (Table S1). Just curiosity: regarding the terms included in the searching process, why did you specify so much wild species (lion, antelopes, buffalo, wolf……….) when the most important concepts were also included (i.e. carnivore, herbivore, wildlife….). By being so specific, many species will be forgotten (as for example: giraffe). Not all studies included generic terms such as ‘carnivore’ and ‘herbivore’ in titles and abstracts. Also, while the majority of publications had the wildcard ‘wild*’ in the title or abstract, a minority didn’t and so it was necessary to specify wildlife species in the search terms. One example is vicuna and guanaco, which initially were not specified in the search terms but were the subject of some publications. Including the terms vicuna and guanaco in the search yielded one or two more relevant publications for inclusion in the review. Titles and abstracts that did not contain generic terms or the species specified in the search terms would indeed have been missed. 3. Line 126: what is the point of defining the quality of the papers? I suggest being more precise on what you mean with quality, since this is a very broad term, and (probably) all of the papers considered in the revision have been published after a peer review, so the quality of all of them is implied.  On reflection, due to the subjective nature of the quality scores, we agree that it is difficult to draw objective conclusions. Given this and the fact that the scores were not influential in the inclusion or exclusion of studies, we have now decided they should not be included in the review and so have removed them. They were initially intended as another way of comparing the results of studies and a structured way of recording aims and definitions of the studies, however the variation between the publications and subjective nature of some of the measures made these comparisons very difficult. 4. The development of the “generic unified framework” is my major concern. I agree that this is a major weakness in the study of contacts, since many studies are not comparable between them, so the proposal of a unified framework appears like a great solution. However, your proposed framework does not really contribute to the consensus of a generic definition of direct/indirect contacts. This definition has to go beyond a spatio-temporal agreement of what it will be considered as a contact, since this definition will depend on the pathogen (in the case of disease studies), the species, the aim of the study, the methodology employed… For example, an indirect contact (see Figure 4) could be “near in time”; according to this, the temporal window could be 1 hour or 1 day, and this not make comparable the studies using such different windows.  You should also include the problem of the representativeness of the individuals, especially when the contacts have been recorded with a methodology that requires the marking of individuals (GPS, proximity loggers, VHF…). This representativeness will also modify how comparable are two studies.  It is also very important to relativize the number of contacts (both direct and indirect) with regards to the total population. Two studies won’t be comparable if study A only uses 3 camera traps and study B uses 100 camera traps. I suggest to improve the “proposed unified framework” by including all these considerations, for example, proposing a definition of contact regarding the topic of the study (disease, behaviour…), or regarding the pathogen studied, or the species included….  We absolutely agree with the reviewer here, and thank them for their excellent suggestions. What are considered direct and indirect contacts will vary depending on all the factors you mentioned. While a universally accepted set of definitions for contacts is difficult to devise, we hope that by defining Sc and Tc here we will encourage the start of the debate around (and between) studies of similar contexts, and perhaps then acceptable ranges for these values will emerge. We have added words to this effect on lines 490-493. In addition, an example of how Sc and Tc could be defined in disease transmission studies is now discussed in lines 496-499. A section of the discussion now addresses the further work and standardisations that are needed, in addition to use of the framework, to enable meaningful comparisons to be made between studies. We have added discussion of the reporting of representativeness and relativizing the number of contacts, as suggested by the reviewer, on lines 507-515. Results:  1. Line 224: what do you mean with “power”? Explain (maybe in the methodology section?) We have clarified the text in the Materials and Methods, Line 148: ‘Where available, the power of each study, defined as the likelihood of detecting contacts, was recorded.’ Discussion:  2. Line 253: however, you don’t give a real range either You are correct, and there will always be a wide range. It is hoped the framework will enable grouping of studies with similar definitions, encourage definition consensus within those studies and so help enable comparisons. These and other reasons for the need for a unified framework are now discussed in lines 398-440. 3. Line 271 – 273: this is not precise, since sometimes, the species involved or the study area will condition the methodology employed. For example, we can’t use GPS devices if our study area doesn’t have a proper signal; or we cannot observe directly the contacts if the visibility of our study area is not good. So, the choice of the methodology will depend on many factors, and not only on the spatio-temporal window employed to define contact. This is a good point. We have added more specificity to this statement to include practical considerations. Line 448: ‘ The generic unified framework proposed in this current paper could also be useful in designing livestock-wildlife contact studies, since defining the type of contact to be detected - in addition to practical considerations, such as an area’s signal strength affecting the viability of GPS device use - helps with the choice of detection method.’ 4. Line 273: be careful with the term “observation method” because it could be confused with the direct observation of the contacts (as for example in the case of Richomme et al. 2006) To reduce the likelihood of such confusion we have changed the phrase ‘direct observation’ to ‘direct visualisation’ throughout the paper. We prefer to retain the use of the phrase ‘observation method’ when referring to the range of methods because this is widely used and understood to mean just that. 5. Line 332-333: the direct observation of the contact (which is a methodology included in the review) could be applied in this case The reviewer is correct in that it would be applicable, but not necessarily the most effective or efficient. We have clarified the text on line 585 to now say ‘While the generic unified framework may be applicable to these types of wildlife, it is unclear which observational methods seen in this review would be most effective or efficient, and the conclusions drawn from this review may not be reflective of systems that involve other taxa.’ Figures: 1. Figure S1: what does represent the numbers in the bars? The sum of these numbers is higher than 122 (which is the total number of papers included in the review). Besides, what does represent the two themes or categories in this figure (primary and secondary theme)?  We have modified the legend and added a clarification on line 151 to make this clearer. Legend now reads: “Figure S1: Themes of the review. Livestock-wildlife studies (n = 122) grouped by themes that emerged during data extraction. Where studies had more than one theme, each theme was identified as either primary (main) or secondary (supportive) based on the aims of the study; hence the total number of primary themes in this figure exceeds the number of studies.” 2. Figure 4: the title of Figure 4 is too long, especially if we consider that almost all this information appears in the Results section We have simplified the title and legend by reducing the amount of text. Minor comments:  1. Line 10: maybe not so surprising, since (as you estate below throughout the text) the definition of contact will depend on many factor: the pathogen under study [transmission route, survival capability…], the species involved, the methodology applied for the recording of contacts….  We accept the reviewer’s comment and have removed the phrase ‘and perhaps surprisingly’ from line 8. Reviewer 3 (Megan Moriarty) Basic reporting 1. The introduction and background were clear, provided a good foundation for the review, and generally well-referenced. There were several points where clarification was needed (see comments in PDF) in the abstract and results:  a. Lines 13 – 14: 30,080 unique publications were eligible for screening, based on Figure 1. It's more accurate to report the 30,080 rather than 43,000 since many of these were duplicates. Amended to ‘over 30,000’ (line 11). b. Lines 14 – 16 (abstract) vs. 160 – 161 (results): it’s unclear what the most studied wildlife species were (and in what order): deer, wild pigs, or badgers? The Abstract details which livestock-wildlife contacts were most frequent, whereas lines 236-238 indicate which wildlife species were most studied. We have amended the text on lines 12-14 to clarify this: ‘The majority of studies examined cattle contacts with badgers or with deer; studies involving wild pig contacts with cattle or with domestic pigs were the next most frequent.’ 2. There are several errors, omissions, typos that need to be fixed in the tables. Please see notes in the PDF. Particular attention should be paid to Table 4, which currently has several errors ranging from issues of formatting to statistical reporting.  a. Your reporting of descriptive statistics needs attention. I'm unsure how you arrived at your summary statistics (mean, median, range). For example, are you reporting the mean number of direct contacts within a single study or are you calculating the mean number of observations within multiple studies? For example, the mean, median, and range are often reported to be the exact same numbers. This is odd and suggests that there is only a single value, in which case there is no need for summary statistics. Also, the range, by definition, has two numbers: a lower limit and an upper limit. Just reporting one number is confusing and incorrect (e.g. PRISMA Checklist #13 is “State the principal summary measures (e.g., risk ratio, difference in means)” and all you say is “Descriptive”). With multiple varying frequencies reported in different studies, an effort was made to summarise these data. This resulted in summary statistics being reported in instances of only one study, which, as you have suggested, was perhaps unwise. We have revised Table 4 to improve clarity. These summary statistic values have been removed as they are only mentioned briefly in the text (line 314-330). Instead, Table 4 now shows whether or not direct and/or indirect contact were observed for each wildlife-livestock contact and method, and provides descriptions of those contacts. We believe that this is a better way of summarising the types of study and data published, and allows the reader to follow up with any particular referenced study should they wish to discover the numerical details. b. Can you clarify what you mean by “Number of studies” and “References” as column headings (and what the difference is?). For example, on row 3 – 4, I'm confused why the livestock camelid + wildlife camelid rows say that there is only one study, but two different references? Same question applies to numerous rows in the table. Number of studies no longer appears in the new version of Table 4. (It showed only the number of studies that reported frequency of contacts.) Additionally, studies reporting extrapolated data were excluded from the calculations in this table: this is no longer relevant since we no longer report summary statistics. References include all studies that involved particular species, whether reporting frequency, type, risk factors or any combination of these. c. A table should be used to summarize and this table is too large and doesn’t condense information effectively. One possible solution is to just reserve this table for actual summarizing of studies involving > 2 studies? Can you further edit or summarize the last column (type of contact). Or perhaps just include publications that actually provide information on the frequency of contacts (i.e. no rows with “-' in them?) We agree that Table 4 had become a bit big! For simplicity, frequency values have been removed from Table 4 as they are only mentioned briefly in the text (line 314-330). Instead, Table 4 now shows whether direct or indirect contact were observed between species and method, and descriptions of those contacts. d. I am unsure why “models” are included as methods used to observe contact. Models are either based on empirical data (from observation methods like the ones you mentioned) or theoretical information. Can you explain why you consider “models” an observational method? Models were included where they used empirical data to model contacts between livestock and wildlife. Where modelling alone is reported, it is because the empirical data used was not specifically wildlife-livestock contact data e.g. using data on cattle grazing habits to model the frequency of contact with badger faeces on pasture (ref 99 and 100). We have added a footnote to Table 4 to clarify this. 3. I think it’s important to mention what “themes” emerged in the actual text of the paper (lines 122 – 123) and then refer the reader to the Supplemental figure to see the breakdown. For example, I didn’t know what themes you were referring to until the results section, but it should be mentioned earlier. We have added this information to lines 149-151. 4. Please use caution when reporting percentages and mention in the text when they sum to > 100% due to overlap or non-mutually-exclusive outcomes (e.g. lines 153 – 156). The caption for figure 3 was useful and a similar note should be made in the text where appropriate (e.g. “Many publications used more than one method to monitor contacts, and therefore the numbers of studies exceed 100% for some groups.”) This is true, and occurs many times throughout the analyses. This has been stated at the start of the results section. Line 197: “During data categorisation and analyses, many publications were categorised into more than one group due to studying multiple species, using multiple detection methods and having multiple themes, and therefore the number of studies exceeds 100% in several instances reported below.” 5. Table 2 also had numerous minor calculation errors, please see individual notes in the PDF and change accordingly. Recommend using more concise language in Tables 2 and 3 (see PDFs for specific suggestions). We have amended the numbers in Table 2, which were due to rounding errors, and added some words to each Table legend so that it is clear that the figures have been rounded. Some of the language used in Tables 2 and 3 is now more concise as suggested. 6. Figure 3 (and supplemental figure S4): I recommend increasing the contrast between the shades of blue for the dots. It does not stand out very well currently. Unfortunately, this is difficult to achieve, which is why the size of the dots are also used in conjunction with the colour shade as an additional point of difference. 7. Figure and table captions/legends should provide more information, in general. The figures and tables should provide enough information to stand on their own (see notes in PDF). The exception is Figure 4, which contains far too much information and is taken verbatim from the text. This should be simplified and redundancy removed. The legend for Figure 4 has been condensed and we have reviewed all the other legends, adding detail where necessary. 8. It is already implied that findings in this paper are 'agreed upon by the authors' and it’s not necessary to mention this 'agreement' several times (e.g. lines 106, 116, 123). Noted and amended throughout manuscript. 9. There was no problem accessing the raw data provided (Supplementary_File_3) a. It’s unclear why the first reference says “no author name available.” That particular reference is a secondary report in The Veterinary Record and an author is not specified. We have amended the author name in Supplementary_File_3 to “Anon”. 10. Supplemental tables and figures do not have titles or captions. Tables S4 and S5 do not match the text of lines 156 – 158 (the text has a denominator of 80 for both diseases, while the total bacterial diseases in Table S4 is 58 and the total viral diseases in Table S5 is 13) and Table S5 has a typo (should read 62% cumulative for foot-and-mouth disease).  We apologise: Supplemental tables and figures did have titles and captions but these may not have been visible to the reviewers as they were attached to each individual file and so may not have transferred to the main merged file. Our understanding is that the legend for each supplementary file will be visible for readers next to the file download button. We present the amended legends here: Fig S1: Themes of the review. Livestock-wildlife studies (n = 122) grouped by themes that emerged during data extraction. Where studies had more than one theme, each theme was identified as either primary (main) or secondary (supportive) based on the aims of the study; hence the total number of primary themes in this figure exceeds the number of studies. Fig S2: Wildlife and livestock species represented in the review. Many publications monitored multiple species of wildlife and livestock and therefore numbers of studies may exceed 100% for some groups. Fig S3: Livestock-wildlife contacts observed. Data from 122 papers included in the systematic review. The size and shade of circles indicate the number of studies in each category. Many publications used more than one method to monitor contacts, and therefore the numbers of studies exceed 100% for some groups. Fig S4: Methods used to monitor different types of contact. Methods used to observe wildlife grouped by methods used alone and in combination with other methods, and grouped by whether direct or indirect contact, or both, was monitored. Table S1: Search strings used to identify publications that investigated contact between any wild and domestic mammal in Pubmed, Scopus and CAB Abstracts databases. Table S2: R packages used in the systematic review. Table S3: Location of the 122 wildlife-livestock contact studies included in the systematic review, stratified by continent. Table S4: Bacterial diseases studied in the context of wildlife-livestock contact studies. Table S5: Viral diseases studied in the context of wildlife-livestock contact studies. 11. Manuscript structure and organization were clear and easy to follow; however, it would be helpful to add some additional subheadings to organize the flow of the paper (see PeerJ Literature Review standard sections: https://peerj.com/about/author-instructions/#literature-review-sections)  We agree this is a good suggestion. Subheadings have been added to the Discussion section to improve readability. Experimental design 1. The research question and aims were generally well-defined and clearly stated; however, there are some points of clarification or further discussion needed either in the introduction or discussion.  a. The systemic review question (lines 90-92) includes “risk factors for contacts between wild animals and livestock”, but risk factors were not addressed clearly in this review. Can this be included/addressed or else removed from this sentence? Many publications stated that they investigated the risk factors for contacts between wildlife and livestock, and therefore monitored wildlife-livestock contacts. But we agree with the reviewer that risk factors were not the focus of this review, and so we have removed reference to ‘risk factors’ in the review question (lines 108-110). b. The systemic review question also said, “… contacts between wild animals and livestock or livestock farms worldwide?”. A brief discussion on reporting/ publishing bias is important for any review article. It was useful that you included a geographic breakdown of where articles were published (e.g. Table S3), but it is important to point out that the predominant countries where livestock-wildlife articles were published was the U.S. and U.K., which is hardly representative of the world at large. In order to promote critical thinking and transparency, it recommended that they include the potential bias this introduces into their review in the discussion section. We have added a sentence to highlight this bias on lines 518-520: “This review has identified the narrow scope and limited geographic range of livestock-wildlife contact studies, which means the data summarised in this review should not be considered representative of all wildlife-livestock contacts worldwide.” It could be interesting to combine Table S1 (regional distribution) with Figure 2 (yearly distribution) in the same figure with 2 panels, particularly since both space and time are prominent themes of the review. This is a nice suggestion, but the size difference between Figure 2 and Table S1 mean that they don’t look appealing when displayed together. We therefore prefer to retain them as they are. c. The aims of the review (lines 11-13) included investigating “which livestock-wildlife contacts have been studied and why,” but this did not receive as much attention as the second aim, which was to investigate the observational methods used. More time and thought should go into the discussion of “why” certain livestock-wildlife contacts have been studied. In addition, it’s unclear whether they are referring to the types of contact (e.g. direct vs. indirect) or the species of livestock and wildlife that have been studied.  The intention was to investigate which species have been studied and why. The themes that emerged lend some answer to this, although the emergent themes for every specific wildlife-livestock contact are not displayed (too many to present meaningfully). Broad explanations for why studies are conducted are addressed in the discussion lines 456-483 and 520-537, in particular in relation to disease transmission studies, predation studies and, to a lesser extent, conservation studies. 2. The methods were well described, with sufficient detail and information to replicate. The adherence to PRISMA reporting guidelines was very helpful. Some clarification is needed: a. Lines 116 – 121: can you clarify whether or not your working/provisional definitions of direct and indirect contact fail to mention space and time considerations? Working definitions were deliberately broad to capture as many potentially relevant publications as possible. Space is included as a resource that can be shared between wildlife and livestock. Time was not specifically mentioned. It can be assumed that if an animal is in physical contact with another, then it is at the same time. For the shared use of resources, no time limit was set. We have amended the text in the PRISMA checklist (section #6) to clarify this. And I’m assuming that these were developed a priori before performing the literature review, but can you confirm?  Yes, working definitions of direct and indirect contact were developed before performing the literature search and used to avoid ambiguity when evaluating publications for inclusion. Direct contact was provisionally defined as physical contact between at least one wild animal and one farm animal. Indirect contact was provisionally defined as contact between at least one wild animal and a resource used by at least one farm animal including, but not limited to, food, water and space. We have amended the text in the PRISMA checklist (section #6) to clarify this. 3. The description of the development of a generic unified framework (lines 131 – 134) in the Methods section is currently quite vague and more detail is warranted. For example, was this framework used to refine your provisional definitions of direct and indirect contact and if so, what is the improved/revised definition? It became clear during the review process that while the working definition was suitable and applicable to all publications included in the review, and was useful for identifying publications, it is a loose catch-all definition that is not specific enough to group studies of similar types. The generic framework was a way of compartmentalising definitions of contact, based on space and time, and it is this, therefore, which is our improved/revised definition. How did you define “meaningful” contacts in each study? Meaningful contacts were those contacts that publications included in their analysis, as these were the contacts relevant to their research question. In contrast, the results section is overly complicated in its explanation of the framework, both in the text (lines 235 – 244) and Figure 4 (as noted above, the wording is redundant). The way it is currently written is not intuitive and makes the topic more complicated than it needs to be. Also, lines 233 – 235 and 244 – 247 are very similar and these ideas only need to be conveyed once in a single sentence. We accept the reviewer’s point that there was some repetition and redundant wording. We have amended and reduced the wording to Figure 4 legend and the wording in the text has been amended in lines 337-376. Some of the scenarios in Figure 4 are somewhat helpful, but I don't understand why scenarios B and D are both considered 'near in space' when both involve badgers, but scenario B space is 10-15 m, while scenario D space is >50 m. This seems like a substantial difference in 'space.'  We are glad that the reviewer finds the examples in Fig 4 helpful. Our aim in this Figure was to illustrate the framework concept in broad terms. The terms ‘near’ and ‘different’ are relative and they differ between studies. As indicated on the Figure, Scenario B considered contacts to be within 15m and scenario D considered contacts happening up to and beyond 50m, which were considered relevant distances for each study. As the reviewer points out, these examples illustrate the current variation in interpretation of the meaning of ‘indirect contact’. We have amended the legend to Fig 4 to make this clearer and it now refers the reader to Tables 3 and 4 for values and ranges for these parameters from published studies. 4. This review article fits within the scope of PeerJ since it is focused on the biological sciences. I commend you for utilizing the most current PRIMSA checklist for literature reviews (and thank you for including it in the supplemental materials). Inclusion and exclusion criteria were clearly defined in the text and Table 1.  Thank you! Validity of the findings 1. In the abstract (lines 2 –4) and discussion (lines 312 – 314), COVID-19 is mentioned very briefly, although your paper focuses on diseases arising from contact between wildlife and livestock, not humans. It would be more beneficial to highlight emerging infectious zoonotic diseases that impact people directly through livestock that were infected from wildlife (e.g. as you mentioned, Hendra and Nipah are good examples of this). Although COVID-19 is an important emerging infectious zoonotic disease, the most recent evidence of spillover is from bats and potentially other wildlife species in wet markets. I’m not aware of any evidence that livestock played a role in disease transmission. It is misleading to begin your abstract with COVID-19 simply because it's a current public health emergency with international attention, when your paper has a different focus. If you are going to mention it in the discussion, please elaborate more. References to COVID-19 have been removed as you’re right, it does not have a livestock intermediary. 2. I was initially concerned that your paper excluded small mammals (rodents, bats) and birds, particularly given their global importance in disease spill-over dynamics. For example, Wiethoelter et al (PNAS, 2015) states, “The bird–poultry interface was the most frequently cited wildlife–livestock interface worldwide.” I was grateful to see this omission partially addressed later in the discussion (lines 329 – 333), but additional explanation would make the paper much stronger. Simply stating that your research does not address avian influenza is insufficient. It is likely that other readers will have similar concerns and will expect more in-depth discussion of this point. I don't think you need to re-do your entire study, but more time must be devoted to justifying why these important animals were omitted, and how your findings may not be reflective of these other important wildlife taxa (e.g. how to interpret your results, recognizing the bias this contributes, etc.). Also, reconsider whether you should use the term “most” wildlife and livestock interfaces throughout the paper because I question whether this is accurate, given your omission of several key taxa. Additional reasoning has been added to the limitations section of the discussion. Lines 580-589: “In order that observation methods were likely to be comparable between species, we focussed on terrestrial mammals so did not address diseases primarily hosted by birds or bats such as avian influenza, Nipah virus and Hendra virus. Small terrestrial mammals (<5kg) were also not included for this reason, and because a disproportionate number of rodent studies focus on their roles as laboratory animals or farm pests, and not on contacts with livestock. While the generic unified framework may be applicable to these types of wildlife, it is unclear which observational methods seen in this review would be most effective or efficient, and the conclusions drawn from this review may not be reflective of systems that involve other taxa.” 3. Your discussion section and study conclusions need revisions that include a more in-depth examination of this broad topic and future directions.  a. I think that more persuasive arguments need to be made as to why a unified generic framework is necessary. Lines 252 – 253 give a reason of “wide-ranging definitions describing contacts,” but this is not surprising given the fact that the details or livestock-wildlife contacts are highly context-dependent and variable based on the species of wildlife and livestock (as well as demographics like age and sex), the pathogen (infectious dose, mode of transmission, half-life, etc.), and environmental conditions (temperature, humidity, weather, region, etc.). You do a nice job mentioning some of this in lines 204 – 206, but more is needed. One of the more important points that you make (lines 215 – 216 and 225) is the complete lack of definition of contact, omission of a space or time component, and conflicting or overlapping definitions of direct and indirect contact. These are fundamental problems that make comparisons between studies impossible and necessitates the use of a generic framework like the one you suggest. This needs to be emphasized in the discussion/conclusion of your paper. We agree with the reviewer that currently these fundamental problems make comparisons between studies impossible and necessitates the use of a generic framework like the one we suggest. These points have been given more attention and a specific section added to the discussion with the subheading ‘The need for a generic unified framework’ (lines 398-440). b. Lines 22 – 24 mention that this framework “may aid the development of better disease transmission models and improve the design and effectiveness of interventions to reduce or prevent disease transmission.” This sounds great, but is not addressed anywhere else besides your abstract. Further elaboration on this point in your discussion section would be worthwhile. Applications of the generic unified framework now have a specific section in the discussion with the subheading ‘Applications of a generic unified framework’ (lines 442-483). c. Try to identify unresolved questions, remaining knowledge gaps, and future directions for research pertaining to the livestock-wildlife interface. This will help fit your review into the greater context. Further work needed in addition to the generic unified framework now has a specific section in the discussion ‘Further development of the generic unified framework’ (lines 485-516). 4. I applaud the fact that you mentioned study power and uncertainty in the publications, since this is important for interpretation of findings. You report the number and percentage of studies with low power (lines 147 – 148), but you do not indicate the number or percentage that reported adequate power, or the total number that assessed statistical power (unfortunately, this is commonly omitted from studies, so it would be helpful to know how many even addressed the topic). Can you provide more information here, especially since you mention that power assessment was a criterion for your publication quality score? We thank the reviewer for this positive comment. The few studies that mentioned the power of the study, or the likelihood of detecting wildlife-livestock contacts, only mentioned the low power and rarity of these events. No statistical power calculations were performed by any study. We have made this more explicit on lines 210-212: “Low study power was mentioned briefly in only 11 (9%) publications and statistical power calculations were not performed. The level of uncertainty was acknowledged in 64 (53%) publications.” Also, in lines 322 – 324, you mention low power, but I’m unsure what you meant by “considering the relatively rare nature of certain types of direct contact.” Are you referring to cryptic wildlife species and our inability to capture or document instances of direct contact using current observational methods? Can you clarify and be more specific? We were referring to the low frequency of certain types of wildlife-livestock contact, particularly direct contact, but the difficulty in monitoring cryptic wildlife species also impacts the power of the study. Making a comment about the effectiveness of detection methods and their influence on the power of the study is difficult as there are a wide range of definitions of relevant contacts. We have clarified this on lines 330-334: “Low study power was acknowledged, but not calculated, by 11 studies (9%), and is likely to be a feature of many more which did not report it. No studies reported adequate power. The low power of studies to observe rare contacts, coupled with the variation in, or lack of, contact definitions, makes it very difficult to compare the effectiveness of the methods used to observe wildlife-livestock contacts.” 5. Thank you for acknowledging that diseases can also go the other way, from livestock to wildlife. Lines 285 – 287 provide some examples that are much needed. I think more recognition of this bidirectionality aspect is crucial. You mention that there is “little (if any) focus on the value of wildlife,” so I recommend you take this opportunity in the introduction and discussion of your own review paper to highlight the conservation implications of disease spillover into wildlife.  We agree that this is an important concept and not often considered. The example of the Saiga antelope in line 44 demonstrates this. We have also added a mention of this bi-directionality to the conclusion (line 592). Comments for the Author I commend you for your thorough review and adherence to the PRISM reporting guidelines. You have summarized a lot of information in a fairly efficient manner that was clear and easy to follow. You stated how the research fills an identified knowledge gap. Potential weakness of the manuscript include the statistical summaries provided in Table 4 (as I have noted above), the description of the unified generic framework and its utility, and the discussion section, which should be improved upon before Acceptance.  We thank the reviewer for these positive comments, and believe we have now addressed all the points raised in our revised manuscript. Annotated manuscript The reviewer has also provided an annotated manuscript as part of their review: Line 34: hmm ... this is an important point, but this conflict stems from predation, rather than disease transmission We agree, but ideally a unified framework would be applicable to any study of wildlife-livestock contacts including predation studies, hence we include this example. Line 109: Include explanation as to why small rodents were excluded, especially since they are often resevoirs of diseases ... there are also many other small wild mammals that are being excluded (e.g. lagomorphs, weasles, etc.). Also, importantly, this also excludes bats, and you mentioned the importance of bats quite a bit in your introduction. We have now addressed this. Please see our response to point 2 above (under ‘Validity of the findings’). Line 116 & 118: Start new paragraph here, to address direct vs. indirect contact definitions. Were the working definitions defined prior to reviewing the papers? why 'provisionally'? Was the definition changed during the course of the study? We confirm that these definitions were used throughout the process of identifying and analysing the papers in this review. We have added a sentence to help clarify this on lines 146-147. Line 121: what about contact between at least one farm animal and a resource used by at least one wild animal (e.g. cattle investigating a raccoon latrine?) This is a good point, but was not included in the definition as in many cases livestock are restricted and any contact with wildlife would usually involve the wild animal utilising a space used by livestock. In the case of cattle investigating latrines, the latrine would usually be on pasture grazed by livestock and hence the racoon has shared use of the grazing area. It would exclude instances where cattle escape from farms and investigate latrines off-pasture, although this would probably be a rare event. Line 122: say something more about these 'themes' e.g. disease, conflict, conservation, etc (I gathered this from the results section, but should be mentioned earlier)... what were they based on? How were they defined? What do they imply/signify? This seems important and should be explained briefly in the actual text and not just relegated to supplemental information. We have added text to clarify this on lines 149-161: ‘Themes that emerged during data extraction were grouped into seven broad study themes, namely behavioural, competition, conservation, disease, human-wildlife conflict, methods papers and wildlife management (Fig. S1). Where studies had more than one theme, themes were subjectively allocated as dominant (primary) or secondary based on the aims of the study.’ Can you further define this 'quality score,' e.g. was the score out of 7 total points? It's not until the results section that we find out more. Also, how was this information used? On reflection, due to the subjective nature of the quality scores it is difficult to draw objective conclusions, and as that the scores were not influential in the inclusion or exclusion of studies, it has been decided they should not be included in the review. And so we have removed all mention of them from the manuscript. Line 150: It seems that if a publication had a quality score of 0, perhaps it should have been excluded? Since quality scores were subjective, and aspects of the score were related to the relevance of the paper to the review question, studies were not excluded or given more or less weight based on the score. Line 156: These percentages do not add up to 100% (they add to 124%), so it should be mentioned that themes were not mutually exclusive. It may be misleading to present percentages here We have now clarified this at the start of the Results section. Some studies were grouped into more than one theme, and therefore the numbers of studies exceed 122 (100%). Just making sure that this is correctly represented in your abstract becasue in the results section you say: 'The most studied wildlife species were deer (30/122; 25%), wild pigs (26/122; 21%) and badgers (25/122; 20%). Can you clarify? The abstract refers to livestock/wildlife contacts (we indicate which types were most common but don’t give numbers here) and the sentence has been amended to be clearer. The section in the results refers only to the numbers of wildlife species. The abstract refers to livestock-wildlife contacts in Figure S4, and the results refer to the species totals in Figure S3. Line 177: can you provide the number of studies that only monitored wildlife and inferred livestock interactions (but did not directly document it)? We mention on line 245 that 34 studies monitored wildlife only, and usually the definition of a contact in terms of space was broad e.g. on farm or on pasture. Line 200: I'm unclear as to how this compares to your working/provisional definitions for direct and indirect contacts (was that done a-priori and as a way to compare with what you found in the various publications?). The provisional definitions were broad and defined before the search. They were used to capture publications for inclusion in the review, and once publications were selected, the definitions used in the publications were compared to each other and not to our provisional definition, since they would have all aligned with the provisional definitions, or else been excluded from the review. Can you refine this to 'indirect' contact? You’re right, it does appear to be indirect contact but there are a minority of studies that would define this type of contact as direct, for example if wildlife and livestock were eating or drinking from the same source at the same time. Line 253: recommend adding more to this sentence ... I don't think 'wide-ranging' is necessarily a problem given the diverse species, systems, pathogens, etc. involved in all these articles. If key information was missing, or only space or only time components were included, or a complete lack of definition, these are fundamental problems that make comparisons between studies impossible and necessitates the use of a generic framework like the one you suggest. These points have now been given more attention and a specific section added to the discussion ‘The need for a generic unified framework (lines 398-440). Line 312: I think it would be more beneficial to discuss an emerging infectious zoonotic disease that impacts people directly through livestock were likely infected directly from wildlife (e.g. as you mentioned, Hendra and Nipah are good examples of this). Of course COVID-19 is an important emerging infectious disease of people that is zoonotic, but the most recent evidence of spillover is from bats and potentially other wildlife species in wetmarkets. There is no well-documented evidence that livestock (as you've defined them) played a significant role and your paper focuses on contact between livetsock and wildlife, not between humans and wildlife. I think it's not entirely accurate or in line with your paper to explicitly identify COVID-19 simply because it's a current public health emergency and there is a lot of attention on this viral disease at the moment. References to COVID-19 have been removed as you’re right, it does not have a livestock intermediary. Line 323: Power was really not addressed in depth in your review. It was mentioned briefly, but if you could add more information and insight here, it would strengthen your review quite a bit. Further discussion has been added from line 330. Please also see our previous responses above on this subject. Line 324: I'm not sure what exactly you mean here. Are you talking about cryptic wildlife species and the fact that capturing instances of direct contact is challenging? Or are you referring to the fact that it's uncommon for articles to utilize certain types of observation methods? Amendment made: ‘methods used to observe livestock-wildlife contacts to date have often had low detection rates and therefore been of low power due to the difficulty of monitoring cryptic wildlife species, and the rarity of some types of wildlife-livestock contacts, particularly direct contacts.’ Line 324: Overall, this paragraph needs improvement. It should be more clear and compelling. You didn't mention the fact that many defintions of direct and indirect contact were often unclear or were overlapping or were missing key information related to space and/or time. This makes comparisons between studies very difficult. You mention this elsewhere, but it really belong here, where you're trying to convince the reader why your framework is a necessary contribution to the field. These points have been given more attention and a specific section added to the discussion ‘The need for a generic unified framework (lines 398-440). Line 330: See my comments earlier in the manuscript. It's good that you bring this up, since it was a concern of mine (and will likely be a concern of other readers), but you need a more convinvcing arguement as to why you excluded birds and rodents and bats, given the global importance of these species in disease dynamics. I don't think you need to repeat your entire study, but I do think you need to devote more time to explaining/justifying why these important animals were omitted. Additional reasoning has been added to the limitations section of the discussion. Lines 580-586. Please also see our previous response to this same point above. Figure 3: add a qualifier here that says 'not specificied (wild ungulates)' or 'unspecified wild ungulates' ... in the results section it says non-specified wildlife were wild ungulates (which gives more info than just 'not specified' by itself). Not all unspecified wildlife were ungulates and some studies were completely unspecified, recording any and all wildlife. We have clarified this on lines 238-241: ‘The wildlife species were not specified in 11 papers, some of which studied wild ungulates competing for livestock grazing [22-24] others that concerned wildlife as hosts of cattle diseases such as bovine tuberculosis [25-27] and foot-and-mouth disease [28, 29], and the remainder that were completely unspecified.’ I don't know if it's my imagination, but this size and shade dot seems different from all the others (e.g. not quite a '13' or a '9', but rather something in between?) You are right, the size and colour are a continuous scale, and sizes/colour in between legend values represent in-between values. In the case you pointed out, the value is 10. It is difficult to increase contrast or change colour, which is why size was also used as a complementary legend. We have done our best to address in our revised manuscript all the other points that the reviewer made in the annotated pdf . "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>checklist of portanines from Peru is given, including several new species records for the country, elevating the known diversity from nine to 22 species. In addition, four species have their department ranges expanded in Peru. Two new portanine species are also described: Metacephalus mamaquilla sp. nov. and Portanus tambopata sp. nov. both from Tambopata National Reserve, Madre de Dios, Peru and we make available habitus photos of other Portanini species from this reserve.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The hemipteran infraorder Cicadomorpha comprises approximately 35,000 described species of plant sap-sucking insects distributed worldwide <ns0:ref type='bibr' target='#b30'>(Dietrich, 2005)</ns0:ref>. It includes the superfamily Membracoidea that comprises the treehoppers (Membracidae, Aetalionidae, and Melizoderidae) and leafhoppers (Cicadellidae and Myerslopiidae) <ns0:ref type='bibr' target='#b24'>(Deitz &amp; Dietrich, 1993)</ns0:ref>. With approximately 21,000 species, 2,550 genera and 25 subfamilies, Cicadellidae is the largest hemipteran family, being cosmopolitan in distribution, occurring everywhere plants (their hosts) can survive <ns0:ref type='bibr' target='#b31'>(Dietrich, 2013;</ns0:ref><ns0:ref type='bibr' target='#b17'>Bartlett et al., 2018)</ns0:ref>.</ns0:p><ns0:p>Included in the subfamily Aphrodinae by <ns0:ref type='bibr' target='#b30'>Dietrich (2005)</ns0:ref>, Portanini was erected by <ns0:ref type='bibr' target='#b41'>Linnavuori (1959)</ns0:ref> as one of the leafhopper tribes restricted to the Neotropical region. Portanines can be recognized by their long and slender bodies; their crown triangularly produced; their ocelli on anterior margin of head, distant from the eyes; and the antennae unusually long <ns0:ref type='bibr' target='#b41'>(Linnavuori, 1959;</ns0:ref><ns0:ref type='bibr' target='#b32'>Felix &amp; Mejdalani, 2016)</ns0:ref>. Currently, the tribe include 63 valid species divided into two genera: Portanus Ball, 1932 and Metacephalus <ns0:ref type='bibr' target='#b29'>Delong &amp; Martinson, 1973</ns0:ref> with 49 and 14 valid species, respectively <ns0:ref type='bibr' target='#b32'>(Felix &amp; Mejdalani, 2016;</ns0:ref><ns0:ref type='bibr' target='#b51'>Souza, Takiya &amp; Felix, 2017;</ns0:ref><ns0:ref type='bibr' target='#b21'>Carvalho &amp; Cavichioli, 2017;</ns0:ref><ns0:ref type='bibr' target='#b35'>Freytag, 2017;</ns0:ref><ns0:ref type='bibr' target='#b33'>Felix et al., 2020)</ns0:ref>. Members of Metacephalus can be distinguished from Portanus by the following set of male features <ns0:ref type='bibr' target='#b20'>(Carvalho &amp; Cavichioli, 2009)</ns0:ref>: (1) pygofer strongly produced posteriorly, usually with a pair of spiniform processes on posteroventral margin (pygofer slightly produced and with variable posterior margin in Portanus); (2) subgenital plates triangular, without transverse unpigmented line at basal third (subgenital plates with transverse unpigmented line at basal third in Portanus); and (3) connective V-shaped (T-shaped in Portanus).</ns0:p><ns0:p>The leafhopper fauna of the Neotropical region is still poorly known. Approximately 5,000 species are described, but there can easily be 5,000 to 10,000 undescribed species in the region, and perhaps many more <ns0:ref type='bibr'>(Freytag &amp; Sharkey, 2002)</ns0:ref>. Peru has one of the most megadiverse leafhopper faunas in the Neotropical region with currently 634 species of which only nine species of Portanini are recorded <ns0:ref type='bibr' target='#b41'>(Linnavuori ,1959;</ns0:ref><ns0:ref type='bibr' target='#b29'>DeLong &amp; Martinson, 1973;</ns0:ref><ns0:ref type='bibr' target='#b28'>DeLong &amp; Linnavuori, 1978;</ns0:ref><ns0:ref type='bibr'>DeLong, 1980;</ns0:ref><ns0:ref type='bibr'>DeLong, 1982;</ns0:ref><ns0:ref type='bibr' target='#b46'>Lozada, 1992;</ns0:ref><ns0:ref type='bibr' target='#b20'>Carvalho &amp; Cavichioli, 2009;</ns0:ref><ns0:ref type='bibr' target='#b22'>Costa &amp; Lozada, 2010;</ns0:ref><ns0:ref type='bibr' target='#b32'>Felix &amp; Mejdalani, 2016;</ns0:ref><ns0:ref type='bibr' target='#b51'>Souza, Takiya &amp; Felix, 2017)</ns0:ref>.</ns0:p><ns0:p>In this paper, a checklist of Portanini from Peru is provided, including eleven new country records, elevating the diversity of known Peruvian portanines from nine to 22 species and four species have their distribution expanded in the country. Additionally, two new species of Portanini from Tambopata National Reserve (Madre de Dios, Peru) are described and illustrated and habitus photos of the 10 Portanini species identified from this reserve are also provided.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head><ns0:p>Specimens studied are deposited in the following collections: Museo de Historia Natural, Universidad Nacional Mayor de San Marcos, Lima (MUSM); Cole&#231;&#227;o Entomol&#243;gica Prof. Jos&#233; Alfredo Pinheiro Dutra, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro (DZRJ); and Insect Collection, Illinois Natural History Survey, Champaign (INHS). Labels of type material are quoted separately, line breaks are indicated by a backslash (\) and additional information given between brackets ([ ]).</ns0:p><ns0:p>For species identification, male genitalia were prepared following <ns0:ref type='bibr' target='#b48'>Oman (1949)</ns0:ref>, where the abdomen is cleared in 10% KOH hot solution for some minutes and washed for a short time in water. For the female genitalia, the protocol from <ns0:ref type='bibr' target='#b53'>Zanol (1988)</ns0:ref> was used, in which the abdomen is cleared in 10% KOH at room temperature for nearly 15 hours and washed with distilled water for 15 minutes. Observation and dissection of genital parts were conducted in glycerin. Structures were observed and photographed with a Leica M205C stereomicroscope equipped with a Leica DFC450 digital camera attached. Photographs at different focal planes to eyes. Ocellus red. Face (Figs. <ns0:ref type='figure' target='#fig_3'>1A and 2A</ns0:ref>) ivory to pale yellow; lateral margin of frontoclypeus and anteclypeus dark brown; lorum (Figs. <ns0:ref type='figure' target='#fig_3'>1A and 2A</ns0:ref>) ivory; gena (Figs. <ns0:ref type='figure' target='#fig_3'>1A and 2A</ns0:ref>) mostly light-brown with outer margin pale yellow. Pronotum dark brown, with several ivory spots. Mesonotum orange; anterior margin and pair of lateral triangular maculae dark brown; short pale-yellow stripe on anterior half. Scutellum orange. Forewing (Figs. <ns0:ref type='figure' target='#fig_3'>1B and 2B</ns0:ref>) translucent brown; clavus with slender line along anal margin, large spot connected to line at apex of first anal vein and another at base, orange, additionally, three large dark-brown elongate maculae adjacent to orange longitudinal line; corium with slender brown line adjacent to claval suture, with three dark-brown maculae near costal margin: first small, near base, second forming broad oblique band extending close to Cu vein, and third forming oblique narrower band extending to base of inner anteapical cell. Thoracic venter ivory. Profemur with two large brown maculae, one larger at middle third and one smaller at apex; protibia pale yellow on dorsal surface and dark brown on ventral surface, setae dark brown; mesofemur with large brown subapical macula, mesotibia similar to protibia; metafemur pale yellow with slender brown stripe on dorsal surface, apex orange; metatibia pale yellow with brown areas, base orange; all tarsomeres pale yellow. Female: color pattern similar to male except for forewing with narrower darkbrown maculae (Fig. <ns0:ref type='figure'>2B</ns0:ref>). Description. <ns0:ref type='bibr'>Head (Figs. 1A and 2A)</ns0:ref>, in dorsal view, with anterior margin rounded; crown median length approximately half to eight-tenths of interocular width and three to four-tenths of transocular width; lateral frontal suture reaching ocellus; epicranial suture not extended to imaginary transverse line between ocelli; texture shagreen. Pronotum slightly wider than head; lateral margin angulate; dorsolateral carina conspicuous and complete; posterior margin straight; texture smooth. Mesonotum shagreen. Forewing (Figs. <ns0:ref type='figure' target='#fig_3'>1B and 2B</ns0:ref>) with distinct venation; three closed anteapical cells. Metatibia with rows AD and PD both with 10-11 long cucullate setae intercalated by 0-3 shorter cucullate setae; tibia apex with three platellae between pair of outer slightly longer cucullate setae; first tarsomere slightly longer than combined length of second and third; tarsomeres posterior margin with three, two, and zero platellae, respectively, between pair of outer slightly longer setae. Male genitalia. Pygofer (Fig. <ns0:ref type='figure' target='#fig_3'>1C</ns0:ref>), in lateral view, longer than high; subrectangular; posterior margin acute; with few macrosetae distributed near dorsal margin and at apex; posteroventral margin with slender and acute ventral process turned dorsally. Valve (Fig. <ns0:ref type='figure' target='#fig_3'>1D</ns0:ref>), in ventral view, about three times wider than long; posterior margin sinuous. Subgenital plate (Fig. <ns0:ref type='figure' target='#fig_3'>1D</ns0:ref>) extending slightly beyond apex of pygofer; slightly upturned; in ventral view, surface with 11-14 robust macrosetae mostly uniseriate (some specimens have one or two additional macrosetae not aligned) and fine long microsetae. Connective (Fig. <ns0:ref type='figure' target='#fig_3'>1E</ns0:ref>), in dorsal view, Y-shaped; apex fused with aedeagus preatrium. Style (Figs. <ns0:ref type='figure' target='#fig_3'>1E and 1F</ns0:ref>) with apodeme (basal portion anterad of connective articulation) one-fifth of total length; apical fifth enlarged and appearing bifid due to elongate and robust preapical lobe; preapical lobe with few fine microsetae; preapical region sculptured; apex acute and curved outwards, bearing robust spine. Aedeagus (Figs. <ns0:ref type='figure' target='#fig_3'>1G-1I</ns0:ref>) with long preatrium; dorsal apodeme well developed, long and narrow; shaft tubular; apex with pair of long and slender divergent processes curved posteroventrally with apices acute. Anal tube segment X (Fig. <ns0:ref type='figure' target='#fig_3'>1C</ns0:ref>) with base conical and remainder tubular; with dentiform microsculpturing throughout. Female genitalia. Sternite VII (Fig. <ns0:ref type='figure'>2C</ns0:ref>), in ventral view, as wide as long; subtriangular; lateral margins slightly sinuous and strongly converging apically; posterior margin convex. Pygofer (Fig. <ns0:ref type='figure'>2D</ns0:ref>), in lateral view, higher than long; subtriangular; ventral margin twice longer than dorsal margin; dorsal margin with concavity at apical third; macrosetae distributed on posterior two-thirds; some interspersed microsetae; apex angulate. First valvifer (Fig. <ns0:ref type='figure'>2E</ns0:ref>) subquadrangular. First valvula (Fig. <ns0:ref type='figure'>2E</ns0:ref>), in lateral view, expanded apically; ventral interlocking device located on basal fourth of blade; dorsal sculptured area on apical third, with sculpturing elongate derived from a strigate pattern (Fig. <ns0:ref type='figure'>2F</ns0:ref>); apex falciform. Second valvifer (Fig. <ns0:ref type='figure'>2I</ns0:ref>) about three times higher than long. Second valvula (Figs. <ns0:ref type='figure'>2G and 2H</ns0:ref>) with apical half expanded, narrowing to apex; dorsal margin with 28 separate teeth without denticles (single specimen dissected); duct area with maculose sculpturing; ventral margin without preapical prominence or denticles; apex acute. Third valvula (Fig. <ns0:ref type='figure'>2I</ns0:ref>), in lateral view, with basal half distinctly narrower than apical half; microsetae distributed along ventral margin and near apex on dorsal margin; two apical macroseta; apex narrowly rounded. Anal tube segment X (Fig. <ns0:ref type='figure'>2D</ns0:ref>), in lateral view, short, length one-third of dorsal margin of pygofer; basal half conical; apical half cylindrical. Remarks. Metacephalus mamaquilla sp. nov. is similar to Metacephalus facetus <ns0:ref type='bibr' target='#b39'>(Kramer, 1961)</ns0:ref> and Metacephalus sakakibarai <ns0:ref type='bibr' target='#b51'>(Souza, Takiya &amp; Felix, 2017)</ns0:ref> in the aspect of the paired apical aedeagus processes, which are long and divergent in caudal view. However, the new species can be distinguished from all other Metacephalus species by the following characteristics: (1) male pygofer (Fig. <ns0:ref type='figure' target='#fig_3'>1C</ns0:ref>) with posterior margin acute and preapical acute ventral process turned dorsally; and (2) aedeagus (Fig. <ns0:ref type='figure' target='#fig_3'>1G-1I</ns0:ref>) with shaft apex curved dorsally with pair of long, narrow and divergent processes curved posteroventrally. Etymology. The species epithet is a homage to the Inca goddess Mama Quilla, considered a defender of women. The species epithet is treated as a noun in apposition. Material studied. Holotype. 1 male, 'PERU, MD [Madre de Dios], Albergue \ Refugio Amazonas \ 12&#176;52'30'[S]/69&#176;24'35'[W] \ 231 m 20.ii.2016 \ J. Grados', 'WIRED AMAZON \ PROJECT \ PAN TRAP' (MUSM). Paratypes. 1 male, same data as holotype (DZRJ); 1 male, same data as holotype, except '19.ii.2016' (MUSM); 1 male, same data as holotype, except '29.ii.2016' (MUSM); 1 male, same data as holotype, except '241 m 05.iii.2016 \ D. Couceiro' (MUSM); 1 male, same data as holotype, except '05.x.2016 \ D. Couceiro' (MUSM); 1 male, 2 females, same data as holotype, except '17.x.2016 \ D. Couceiro' (DZRJ); 3 males, same data as holotype, except '06.xi.2016 \ D. Couceiro' (DZRJ); 1 female, same data as holotype, except '241 m 02.iii.2017' (MUSM); 1 male, same data as holotype, except '241 m 04.iii.2017' (MUSM); 1 male, same data as holotype, except '241 m 10.iv.2017 \ D. Couceiro' (MUSM); 1 female, same data as holotype, except '241 m 20.iv.2017 \ D. Couceiro' (MUSM); 1 male, 1 female, same data as holotype, except '241 m 26.iv.2017 \ D. Couceiro' (MUSM).</ns0:p></ns0:div> <ns0:div><ns0:head>Portanus Ball, 1932</ns0:head><ns0:p>Portanus Ball, 1932: 18. Type species: Scaphoideus stigmosus Uhler, 1895.</ns0:p><ns0:p>Portanus tambopata sp. nov. urn:lsid:zoobank.org:act: 9C799CBA-FD0C-4DB3-931D-7FB7ECA440E6 (Figures <ns0:ref type='figure'>3-4</ns0:ref>) Type locality. Refugio Amazonas, Madre de Dios, Peru. Diagnosis. Male pygofer (Fig. <ns0:ref type='figure'>3C</ns0:ref>), in lateral view, subtriangular; posterior margin truncate, with small dorsal teeth and subquadrate ventral lobe bearing slender and acute process directed posteriorly. Aedeagus (Figs. <ns0:ref type='figure'>3H-3J</ns0:ref>) preatrium slightly sinuous; shaft enlarged at base, narrowing towards apex; apex with single bifurcated process turned ventrally, sinuous and with apices turned outwards, resembling an anchor (Fig. <ns0:ref type='figure'>3I</ns0:ref>). Male anal tube (Figs. <ns0:ref type='figure'>3C and 3K</ns0:ref>) segment X with pair of small, lateral, strongly sclerotized toothed lobes at middle third. Female sternite VII (Fig. <ns0:ref type='figure'>4C</ns0:ref>) approximately rectangular; posterior margin with prominent rounded median lobe. Measurements (mm). Males (n=5)/females (n=2): body length, 4.3-4.8/4.6-4.7; crown length, 0.4/0.4; transocular width, 1.1/1.2; interocular width, 0.5-0.6/0.6; maximum pronotum width, 1.0-1.1/1.1; forewing length, 3.3-3.6/3.5-3.7. Coloration. Crown brown; anterior margin with dark brown line; apical third with subtriangular marking between ocelli, which extends to posterior margin as a median line, pale yellow; basal two-thirds with longitudinal pale-yellow line surrounded by a reddish-brown area. Ocellus red. Face and gena pale brown and lorum ivory (Figs. <ns0:ref type='figure'>3A and 4A</ns0:ref>). Pronotum brown, with several ivory spots. Mesonotum brown; pair of lateral triangular dark-brown maculae on anterior margin; posterolateral margin ivory. Scutellum pale brown to ivory. Forewing (Figs. <ns0:ref type='figure'>3B and 4B</ns0:ref>) translucent yellowish brown; veins dark brown with alternating ivory spots; five dark brown triangular maculae along costal margin; apex dark brown. Thoracic venter ivory. Legs ivory; posterior apexes of tibia, first and second tarsomeres brown. Description. Head (Figs. <ns0:ref type='figure'>3A and 4A</ns0:ref>), in dorsal view, with anterior margin angulate; crown median length approximately seven to eight-tenths of interocular width and three to four-tenths of transocular width; lateral frontal suture reaching ocellus; epicranial suture not extended to imaginary transverse line between ocelli; texture shagreen. Pronotum width subequal to head width; lateral margin angulate; posterior margin straight; texture smooth with transverse striae. Mesonotum shagreen. Forewing (Figs. <ns0:ref type='figure'>3B and 4B</ns0:ref>) with distinct venation; with three closed anteapical cells, median anteapical cell slightly longer than others. Metatibia with row AD with 9-11 long cucullate setae intercalated by 3-4 shorter setae; PD row with 10 very long cucullate setae intercalated by one smaller long cucullate seta. First tarsomere slightly longer than combined length of second and third; tarsomeres posterior margin with three, two, and zero platellae, respectively, between pair of outer slightly longer setae. Male genitalia. Pygofer (Fig. <ns0:ref type='figure'>3C</ns0:ref>), in lateral view, slightly longer than high; subtriangular; posterior margin truncate, with small dorsal teeth and subquadrate ventral lobe bearing slender and acute process directed posteriorly; macrosetae distributed at median portion dorsally; microsetae at apex. Valve (Fig. <ns0:ref type='figure'>3E</ns0:ref>), in ventral view, oblong; wider than long; anterior and posterior margin convex. Subgenital plate (Figs. <ns0:ref type='figure'>3D and 3E</ns0:ref>) extending posteriorly farther than pygofer apex; apical third upturned; in ventral view, basal third with transverse unpigmented line; surface with 5-6 robust macrosetae uniseriate and many long and fine microsetae at apical half. Connective (Fig. <ns0:ref type='figure'>3F</ns0:ref>), in dorsal view, Y-shaped; anterior margin with short median basiventral triangular projection; apex truncate. Style (Figs. <ns0:ref type='figure'>3F and 3G</ns0:ref>) with apodeme (basal portion anterad of connective articulation) long, one-third of total length; apical third widened with preapical lobe elongate and robust; apex truncated with digitiform process; in lateral view, subcylindrical and sinuous. Aedeagus (Figs. <ns0:ref type='figure'>3H-3J</ns0:ref>) with long and slightly sinuous preatrium; dorsal apodeme not so sclerotized; shaft wider at base, narrowing towards apex; apex with single bifurcated process directed ventrally, with rami sinuous, half-length of shaft, with apices turned outwardly, resembling an anchor. Anal tube segment X (Figs. <ns0:ref type='figure'>3C and 3K</ns0:ref>) subcylindrical; as long as pygofer; with few denticles on ventral margin at base; with pair of small lateral, strongly sclerotized, toothed lobes at median third. Female genitalia. Sternite VII (Fig. <ns0:ref type='figure'>4C</ns0:ref>), in ventral view, approximately rectangular; posterior margin with prominent rounded median lobe. Pygofer (Fig. <ns0:ref type='figure'>4D</ns0:ref>), in lateral view, higher than long; subtriangular; ventral margin twice longer than dorsal margin; dorsal margin with convex median portion; with long macrosetae concentrated at apical half; without microsetae; apex acute. First valvifer (Fig. <ns0:ref type='figure'>4E</ns0:ref>) subtrapezoidal. First valvula (Fig. <ns0:ref type='figure'>4E</ns0:ref>), in lateral view, expanded apically; ventral interlocking device located on basal third of blade; dorsal sculptured area on apical fourth, with sculpturing strigate (Fig. <ns0:ref type='figure'>4F</ns0:ref>); apex acute. Second valvifer (Fig. <ns0:ref type='figure'>4I</ns0:ref>) three times higher than long. Second valvula (Figs. <ns0:ref type='figure'>4G and 4H</ns0:ref>), in lateral view, with apical half expanded, narrowing to apex; dorsal margin with 24 separate subtriangular teeth without denticles (single specimen dissected); duct area with maculose sculpturing; ventral margin without preapical prominence or denticles; apex acute. Third valvula (Fig. <ns0:ref type='figure'>4I</ns0:ref>) with basal half distinctly narrower than apical half; microsetae distributed on ventral margin and dorsal margin near apex; one apical macroseta; apex acute. Remarks. Portanus tambopata sp. nov. is very similar to Portanus bifurcus Carvalho &amp; Cavichioli, 2017, both species sharing: (1) a similar color pattern; and (2) posterior margin of male pygofer truncate with ventral lobe. However, the new species can be distinguished from the latter and other Portanus species by its posterior margin of male pygofer lobe with subquadrate ventral lobe bearing a long and slender process directed posterodorsally (Fig. <ns0:ref type='figure'>3C</ns0:ref>) (in P. bifurcus, posterior margin of male pygofer lobe with ventral lobe acute without slender process) and aedeagus apex with single bifurcated process directed ventrally, with rami apices turned outwardly like an anchor (Figs. <ns0:ref type='figure'>3H-3J</ns0:ref>) (in P. bifurcus aedeagus apex has pair of bifurcated processes, which have apices directed ventrally). Etymology. The species epithet is a reference to Tambopata National Reserve, area from where the type series was collected. The species epithet is treated as a noun in apposition. Material studied. Holotype. 1 male, 'PERU, MD [Madre de Dios], Albergue \ Refugio Amazonas \ 12&#176;52'30'[S]/69&#176;24'35'[W] \ 231 m 28.iii.2016 \ D. Couceiro', 'Malaise Trap' (MUSM). Paratypes. 1 female, same data as holotype, except: 241 m 01.xii.2016', 'WIRED AMAZON \ PROJECT \ MALAISE TRAP' (MUSM); 1 female, same data as preceding, except '231 m 15.v.2016' (DZRJ); 1 male, same data as holotype, except '02.x.2016' (MUSM); 2 males, same data as holotype, except '12.iv.2016; WIRED AMAZON \ PROJECT \ MALAISE TRAP' (DZRJ); 1 male, same data as preceding, except '26.ii.2016 \ J. Grados' (MUSM).</ns0:p></ns0:div> <ns0:div><ns0:head>Checklist of Portanini from Peru 1) Metacephalus albocrux DeLong &amp; Martinson, 1973</ns0:head><ns0:p>Distribution. <ns0:ref type='bibr'>Brazil (Souza, Takiya &amp; Felix, 2017)</ns0:ref> Material studied. PERU: 1 male, Madre de Dios, Refugio Amazonas, Albergue, 12&#176;52'30'S 69&#176;24'35'W 231 m, 03.ix.2016, D. Couceiro, Malaise Trap.; Wired Amazon Project (MUSM). 1 male, same data as preceding, except <ns0:ref type='bibr'>12.iv.2016 (DZRJ)</ns0:ref>. 1 male, same data as preceding, except <ns0:ref type='bibr'>14.x.2014, PAN Trap (MUSM)</ns0:ref>. <ns0:ref type='bibr' target='#b40'>(Kramer, 1964)</ns0:ref> Distribution. <ns0:ref type='bibr'>Brazil (Carvalho &amp; Cavichioli, 2009)</ns0:ref>; Colombia <ns0:ref type='bibr'>(Freytag &amp; Sharkey, 2002)</ns0:ref>; Guyana <ns0:ref type='bibr' target='#b32'>(Felix &amp; Mejdalani, 2016)</ns0:ref>; Panama (type locality: Fort. Gulick, Canal Zone); Peru [New Record]: Loreto Department; Venezuela <ns0:ref type='bibr' target='#b40'>(Kramer, 1964)</ns0:ref>. Material studied. PERU: 2 males and 1 female, Dept. Loreto, San Juan de Pamplona, 35 km S Yurimaguas, Malaise in Oil Palm/Cacao Plantation, 6&#186;7 <ns0:ref type='bibr'>'38'S 76&#186;11'26'W, 170m, 11-18.iv.2009, malaise, G. Ant&#243;n, A. Maya, M.E. Irwin (INHS)</ns0:ref>. 1 male, same data as preceding (DZRJ). <ns0:ref type='bibr' target='#b39'>(Kramer, 1961)</ns0:ref> (Figures <ns0:ref type='figure'>5K and 5L</ns0:ref>) Distribution. <ns0:ref type='bibr'>Brazil (Carvalho &amp; Cavichioli, 2009)</ns0:ref>; Colombia <ns0:ref type='bibr'>(Freytag &amp; Sharkey, 2002)</ns0:ref>; Peru [New Record]: Amazonas and Madre de Dios Departments; Venezuela (type locality: Culebra Community, Duida-Marahuaca National Park, Amazonas State). Material studied. PERU: 1 male and 1 female, Madre de Dios, Refugio Amazonas, Albergue, 12&#176;52'30'S 69&#176;24 <ns0:ref type='bibr'>'35'W 231 m, 03.v.2016, D. Couceiro, Malaise Trap.;</ns0:ref><ns0:ref type='bibr'>Wired Amazon Project (MUSM)</ns0:ref>. 1 male, Dept. Amazonas, Distr. Aguas Verdes, Bagua/Tarapoto Rd (5N) AT km 403, 5&#186;41'23'S 77&#186;38 <ns0:ref type='bibr'>'13'W, 1125m, Malaise, 19-26.ix.2008, M.E. Irwin, G. Ant&#243;n, A. Maya (INHS)</ns0:ref>. <ns0:ref type='bibr' target='#b39'>(Kramer, 1961)</ns0:ref> (Figures <ns0:ref type='figure' target='#fig_4'>6A and 6B</ns0:ref>) Distribution. <ns0:ref type='bibr'>Brazil (Carvalho &amp; Cavichioli, 2009)</ns0:ref>; Colombia <ns0:ref type='bibr'>(Freytag &amp; Sharkey, 2002)</ns0:ref>; Peru [New Record]: Amazonas, Cusco and Madre de Dios Departments; Venezuela (type locality: Upper Cunucunuma River, Tapara, Amazonas State). Material studied. PERU: 1 male, Dept. Amazonas, Distr. Aguas Verdes, Bagua/Tarapoto Rd (5N) AT km 403, 5&#186;41'23'S 77&#186;38 <ns0:ref type='bibr'>'13'W, 1125m, Malaise, 24-31.x.2008, M.E. Irwin, G. Ant&#243;n, A. Maya (INHS)</ns0:ref>. 1 male, same data as preceding, except 8- <ns0:ref type='bibr'>15.vii.2008</ns0:ref><ns0:ref type='bibr'>15.vii. .1 male, same data as preceding, except 20-27.ii.2009 (INHS) (INHS)</ns0:ref>. 1 male, same data as preceding, except 6- <ns0:ref type='bibr'>13.iii.2009 (DZRJ)</ns0:ref>. 1 male, <ns0:ref type='bibr'>Cusco, 19rd km W Quincemil, Rio Araza Tributary, 13&#186;20'10'S 70&#186;50'57'W, 874m, 23-31.viii.2012</ns0:ref>, malaise, RR Cavichioli, JA Rafael, APM Santos &amp; DM Takiya (DZRJ). 1 male, Madre de Dios, Refugio Amazonas, Albergue, 12&#176;52'30'S 69&#176;24 <ns0:ref type='bibr'>'35'W 231 m, 01.vi.2016, D. Couceiro, PAN Trap.;</ns0:ref><ns0:ref type='bibr'>Wired Amazon Project (MUSM)</ns0:ref>. 1 male, same data as preceding, except <ns0:ref type='bibr'>01.xii.2006 (MUSM)</ns0:ref>. 2 males, same data as preceding, except 02.x.2016 (MUSM). 3 males, same data as preceding, except <ns0:ref type='bibr'>03.v.2016, malaise (DZRJ)</ns0:ref>. 1 female, same data as preceding, except <ns0:ref type='bibr'>03.xi.2016, malaise (DZRJ)</ns0:ref>. 1 male, same data as preceding, except <ns0:ref type='bibr'>09.iii.2016, 241m, malaise (MUSM)</ns0:ref>. 1 male, same data as preceding, except 12.ii.2016, J. Grados (MUSM). 3 males, same data as preceding, except <ns0:ref type='bibr'>12.iv.2016, malaise (DZRJ)</ns0:ref>. 1 male, same data as preceding, except <ns0:ref type='bibr'>15.xi.2016 (MUSM)</ns0:ref>. 1 male, same data as preceding, except <ns0:ref type='bibr'>17.x.2016 (MUSM)</ns0:ref>. 1 male, same data as preceding, except 19.iii.2016, malaise, J. Grados (MUSM). 1 male, same data as preceding, except 21.xi.2016 (MUSM). 1 male, same data as preceding, except 08.iv.2018, 241m, malaise, J. Shoobridge (MUSM). 1 male, same data as preceding, except 21.vi.2017, 241m, malaise (MUSM). 1 female, same data as preceding, except 29.iii.2017, 241m, J. Shoobridge (MUSM). 1 female, same data as preceding, except 24.ii.2017, malaise, 241m, J. Grados (DZRJ). 1 female, same data as preceding, except 25.v.2018, 241m, J. Shoobridge (DZRJ). <ns0:ref type='bibr' target='#b49'>(Osborn, 1923)</ns0:ref> (Figures <ns0:ref type='figure' target='#fig_4'>6C and 6D</ns0:ref>) Distribution. Argentina <ns0:ref type='bibr' target='#b41'>(Linnavuori, 1959)</ns0:ref>; Bolivia (type locality: Sara Province, Santa Cruz de La Sierra Department); Brazil <ns0:ref type='bibr' target='#b20'>(Carvalho &amp; Cavichioli, 2009;</ns0:ref><ns0:ref type='bibr' target='#b33'>Felix et al., 2020)</ns0:ref>; Peru [New Record]: Loreto, Madre de Dios and San Mart&#237;n Departments; Venezuela <ns0:ref type='bibr' target='#b40'>(Kramer, 1964)</ns0:ref>. Material studied. PERU: 1 male, Madre de Dios, Refugio Amazonas, Albergue, 12&#176;52'30'S 69&#176;24'35'W 241 m, 8.iv.2018, D. Couceiro, malaise; Wired Amazon Project (MUSM). 1 male, same label, except 18.iii.2017, J. Grados (DZRJ). <ns0:ref type='bibr'>Cusco, 19rd km W quincemil, Rio Araza Tributary, 13&#186;20'10'S 70&#186;50'57'W, 847 m, 23-31.viii.2012</ns0:ref>, malaise, RR Cavichioli, JA Rafael, APM Santos &amp; DM Takiya (MUSM). 2 males, same data as preceding (DZRJ). <ns0:ref type='bibr' target='#b18'>(Carvalho &amp; Cavichioli, 2003)</ns0:ref> (Figures <ns0:ref type='figure' target='#fig_4'>6G and 6H</ns0:ref>) Distribution. Brazil (type locality: Ouro Preto d'Oeste, Rond&#244;nia State); Peru: Madre de Dios <ns0:ref type='bibr' target='#b20'>(Carvalho &amp; Cavichioli, 2009)</ns0:ref> and San Mart&#237;n [New Record] departments. Material studied. PERU: 44 males, San Mart&#237;n Prov., Concervaci&#243;n Mun. Zona Barreal, 23km S Picota, in dry forest, 7&#186;4.88 <ns0:ref type='bibr'>'S 76&#186;18.89'W, 335m, Malaise, 6-15.iii.2005, M.E. Irwin and J.D. Vasquez (INHS)</ns0:ref>. 10 males, same data as preceding (DZRJ). 1 male, Madre de Dios, Refugio Amazonas, Albergue, 12&#176;52'30'S 69&#176;24'35'W 241 m, 18.iii.2017, J. Grados, malaise; Wired Amazon Project (MUSM). 1 male, same label, except 19.iii.2016 (DZRJ). (A-B) Metacephalus facetus <ns0:ref type='bibr' target='#b39'>(Kramer, 1961)</ns0:ref>, male. (C-D) Metacephalus longicornis <ns0:ref type='bibr' target='#b49'>(Osborn, 1923)</ns0:ref>, male. (E-F) Metacephalus sakakibarai <ns0:ref type='bibr'>Souza, Takiya &amp; Felix 2017, male. (G-H)</ns0:ref> Metacephalus variatus <ns0:ref type='bibr' target='#b18'>(Carvalho &amp; Cavichioli, 2003)</ns0:ref>, male. (I-J) Portanus ocellatus <ns0:ref type='bibr'>Carvalho &amp; Cavichioli, 2003, male.</ns0:ref> (K-L) Portanus sagittatus <ns0:ref type='bibr' target='#b19'>Carvalho &amp; Cavichioli, 2004</ns0:ref>, male. Scale bars: 1 mm. Photo credit: Clayton C. Gon&#231;alves.</ns0:p></ns0:div> <ns0:div><ns0:head>3) Metacephalus eburatus</ns0:head></ns0:div> <ns0:div><ns0:head>4) Metacephalus elegans</ns0:head></ns0:div> <ns0:div><ns0:head>5) Metacephalus facetus</ns0:head></ns0:div> <ns0:div><ns0:head>6) Metacephalus longicornis</ns0:head></ns0:div> <ns0:div><ns0:head>9) Metacephalus variatus</ns0:head></ns0:div> <ns0:div><ns0:head>10) Portanus acerus</ns0:head></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>2)</ns0:head><ns0:label /><ns0:figDesc>Metacephalus bicornis (Carvalho &amp; Cavichioli, 2003) (Figures 5I and 5J) Distribution. Brazil (type locality: Vilhena, Rond&#244;nia State); Peru [New Record]: Madre de Dios Department.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>8 males and 2 females, Dept Loreto, San Juan de Pamplona, 35 km S Yurimaguas, Malaise in Oil Palm/Cacao Plantation, 6&#186;7'38'S 76&#186;11'26'W, 170m, 11-18.iv.2009, G. Ant&#243;n, A. Maya, M.E. Irwin (INHS). 3 males and 1 female, same data as preceding (DZRJ). 10 males and 1 female, San Mart&#237;n Prov., Concervaci&#243;n Mun. Zona Barreal, 23km S Picota, in dry forest, 7&#186;4.88'S 76&#186;18.89'W, 335m, Malaise, 6-15.iii.2005, M.E. Irwin and J.D. Vasquez (USNM). 2 males, same data as preceding (DZRJ). 7) Metacephalus mamaquilla sp. nov. (Figures 1, 2, 5A-5D) Distribution. Peru: Madre de Dios Department. Material studied. See above. 8) Metacephalus sakakibarai Souza, Takiya &amp; Felix 2017 (Figures 6E and 6F) Distribution. Brazil (type locality: Ipixuna, Amazonas State); Peru [New Record]: Cusco and Madre de Dios Departments. Material studied. PERU: 1 male, Madre de Dios, Refugio Amazonas, Albergue, 12&#176;52'30'S 69&#176;24'35'W 231 m, 02.x.2016, D. Couceiro, malaise; Wired Amazon Project (MUSM). 2 males,</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>DeLong, 1976 Distribution. Bolivia (type locality: San Esteban, Santa Cruz de La Sierra, Santa Cruz Department); Peru [New Record]: Loreto and San Mart&#237;n departments.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>;</ns0:head><ns0:label /><ns0:figDesc>Peru: Cusco [New Record], Ucayali (type locality: Pucallpa), and San Mart&#237;n [New Record] Departments). Material studied. PERU: 2 males, San Mart&#237;n Prov., Concervaci&#243;n Mun. Zona Barreal, 23km S Picota, in dry forest, 7&#186;4.88'S 76&#186;18.89'W, 335m, Malaise, 6-15.iii.2005, M.E. Irwin and J.D. Vasquez (INHS). 2 males, Cusco, 3rd Km E Quincemil, 13&#186;13'3'S 70&#186;43'40'W, 633m, 20.viii-01.ix.2012, malaise, RR Cavichioli, JA Rafael, APM Santos &amp; DM Takiya (DZRJ). 1 male, Cusco, Puente Inambari, 13&#186;10'53'S 70&#186;23'06'W, 365m 19.VIII.2012 light, APM Santos &amp; DM Takiya (MUSM).</ns0:figDesc><ns0:table /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:07:51460:1:2:NEW 27 Sep 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:07:51460:1:2:NEW 27 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

" September 20th, 2020 Dear Dr. Gillespie, We would like to thank you and reviewers for their comments and contribution to this manuscript. We have accepted most reviewer’s suggestions and list below all reviewer’s comments and our answers (in red). We are also sending the revised version in .docx with tracked changes and without tracked changes. We believe that the manuscript is now suitable for publication in PeerJ. Ms. Jádila Prando on behalf of all authors Reviewer 1 (James Zahniser) Comments made in revised .pdf: 1) Pg5 ln36: Included in the subfamily Aphrodinae.... I have rephrased this sentence. 2) Pg5 ln36-37: I'm not sure why this paper is referenced here. If you wish to keep it, please provide more context for the citation. E.g. the tribe as recognized by Dietrich (2005) ? What is the significance of that reference? I have rephrased this sentence. 3) Pg6 ln50: ...is poorly known. Approximately .... Accepted suggestion. 4) Pg6 ln60: have. Staying consistent with present tense earlier in the sentence Accepted suggestion. 5) Pg7 ln116: 0.5–0.8x ? I suggest this as a possible alternative for reporting these and similar ratios throughout the manuscript. Because this is a matter of style, I have maintained the original wording. 6) Pg8 ln124: remove 'ones'. Accepted suggestion. 7) Pg8 ln131: lateral? Reviewer is correct, it was wrong. I have rephrased using outer margin. 8) Pg8 ln151: A more precise description would be better: ...with a uniseriate row of ~10–12 (or whatever number you observe in your specimens) macrosetae. Also, figure 1D shows that on at least one of the plates there are two other macrosetae mesad of the uniseriate row, so something about that should be included in the description too. I have rephrased and added information about macrosetae. 9) Pg8 ln152: Do you mean apophysis here? Dietrich (2005) which was cited for terminology in Mat & Methods does not use the term apodeme in reference to any part of the style. Apophysis is used for the apical lobe of the style in Deltocephalinae (Linnavuori, 1959). I have used the term apodeme in accordance to an unpublished book chapter (Dietrich et al. in prep.). Thus, I have defined the term in the description for better understanding. 10) Pg8 ln157: There is no need to include 'Anal tube' here. You are describing segment X. I have maintained Anal tube. 11) Pg9 ln161: The height and length here seem to be dependent on the angle at which the pygofer is viewed laterally. If you rotated the pygofer in Fig. 2D by 45 deg. clockwise, which is how I would assess height and length of pygofer, the length is much more than the height. I understand, however, I describe these measurements taking in consideration that the dorsal margin of the pygofer lobe is straight and not up- or downturned, in accordance to how it was oriented on the figure plate. I have maintained the original. 12) Pg9 ln165: Describe sculpturing pattern. Appears to be maculose in parts, and elongated/reticulate to strigate in others. I have rephrased this sentence to highlight the description of the sculpturing pattern and included terminology followed in the material & methods section. 13) Pg9 ln170: Appears to have two distinct macrosetae on ventral margin near apex. Should be noted. I have added this information. 14) Pg9 ln182: nice one :) Thanks. 15) Pg10 ln223: remove 'ones' Accepted suggestion. 16) Pg11 ln243: apophysis? Replied above in (9). 17) Pg11 ln248: Remove 'Anal tube' Replied above in (10). 18) Pg11 ln252: See above, consider re-wording. Replied above in (11). 19) Pg17 ln496: Instead of 'completely', maybe 'highly' or 'vastly' Accepted suggestion. 20) Pg17 ln50: doubles Accepted suggestion. 21) Pg17 ln502: remove 'definitely' Accepted suggestion. 22) Pg17 ln502: remove comma after 'region' Accepted suggestion. _____ Reviewer 3 (Márcio Felix) Comments made in revised .pdf: 1) Pg3 ln116: eight-tenths of interocular width – added Accepted suggestion. 2) Pg4 ln145: dark-brown – Excluded: - Accepted suggestion. 3) Pg6 ln215: with anterior margin angulate Accepted suggestion. 4) Pg6 ln215: with crown – Excluded: with Accepted suggestion. 5) Pg6 ln216: eight-tenths of interocular width – added Accepted suggestion. 6) Pg6 ln218: Pronotum (Figs. 5E and 5G) width subequal – added Accepted suggestion. 7) Pg13 ln481/482: Tambopata National Reserve, as well as Peruvian – added; Excluded: and Accepted suggestion. 8) Pg13 ln483: new records from Peru – Excluded: for known species Accepted suggestion. 9) Pg13 ln487: provided to help – Excluded: , Accepted suggestion.. 10) Pg13 ln497: from Brazil is also known – Excluded: , Accepted suggestion. _____ Reviewer 4 (Michael Webb) Comments made in revised .pdf: 1) Pg1 ln1: Is it necessary to give the date of the tribe in the title? Some authors (like me!) even omit the author of taxa in the title! Maybe better to have these in the Abstract? Just a thought. Accepted suggestion and modified in revised manuscript. 2) Pg1 ln20: Portanini Linnavuori, 1959 – Italic Accepted suggestion. 3) Pg1 ln37-39: Included in Aphrodinae subfamily, Portanini Linnavuori (1959) is one of the leafhopper tribes of Aphrodinae (Dietrich, 2005) erected by Linnavuori (1959) and restricted to the Neotropical region. - I have rephrased this sentence I have rephrased this sentence to better describe the information and according different reviewers suggestions. 4) Pg2 ln39-41: Portanines can be recognized by their long and slender bodies; their crown triangularly produced; their ocelli on anterior margin of head, distant from the eyes; and the antennae unusually long (Linnavuori, 1959; Felix & Mejdalani, 2016). - Other than the long antennae the other characters mentioned don’t seem very special and what is the character that places them in Aphrodinae? Dietrich (2005) synonymized Xestocephalinae (Xestocephalini and Portanini) in Aphrodinae, following Hamilton (1975). However, this last author simply lumps several tribes based on generalized characters, not mentioning specific synapomorphic characters. All recent phylogenetic information (Dietrich et al. 2001, 2017) does not support Portanini as related to neither Xestocephalini nor Aphrodini, but we are still following the most recent classification, as of Dietrich 2005, because of the lack of other proposals. So, we have maintained the original phrase. 5) Pg2 ln42: Portanus Ball, 1932 with 49 – Excluded Accepted suggestion. 6) Pg2 ln43: Delong & Martinson, 1973, with 49 and 14 valid species respectively Accepted suggestion. 7) Pg2 ln51-56: The leafhopper fauna of the Neotropical region is still poorly known with and, approximately 5,000 described species are described, but there can be easily be 5,000 to 10,000 undescribed species in the region, and perhaps many more (Freytag & Sharkey, 2002). Peru has is one of the most megadiverse leafhopper faunas countries in the Neotropical region with and currently only 634 species of which of some groups of leafhoppers are recorded from there, with only nine species of Portanini are recorded - I have rephrased this sentence, is it correct? I have rephrased and accepted most of these suggestions. 8) Pg2 ln60-61: In this paper, a checklist of Portanini from Peru is provided, including where eleven new country records species are herein firstly recorded Accepted suggestion. 9) Pg3-4 ln119-120: ocelli transverse line; - Do you mean “extended to transverse line between ocelli”? Accepted suggestion. 10) Pg4 ln128: Coloration. - It is more usual to put color first before structure. Here it is between to different structure, external and genitália Reviewer is correct. Changed position of sections, but did not leave mark on the revised version. 11) Pg4 ln132-133: brown;. lLorum (Figs. 1A and 2A) ivory;. gGena - As the lorum and gena are part of the face they should be separated by a semicolon. Accepted suggestion. 12) Pg4 ln152: slightly turned dorsally - upturned? Accepted suggestion 13) Pg5 ln172-173: Third valvula (Fig. 2I), in lateral view, with basal half distinctly narrower than apical half; - Isn’t this more or less the case in all leafhoppers? Reviewer is correct. The structure morphology is very conserved across leafhopper subfamilies. However, we prefer to maintain the phrase, following all other female terminalia descriptions. 14) Pg6 ln218-219: ocelli transverse line - See comment above Replied above in (9). 15) Pg6 ln227: Coloration - See above comment Replied above in (10). 16) Pg7 ln263-264: with basal half distinctly narrower than apical half; - See above comment Replied above in (13). 17) Pg13 ln485-486: For Because of this reason – Rephrased Accepted suggestion. 18) Pg13 ln494: outdated - “a highly underestimate”? Accepted suggestion. 19) Pg13 ln498: considered known – changed Accepted suggestion. 20) Pg13 ln503: This study adds to the knowledge of leafhoppers from the Neotropical region. It - Does this read better? Sentence rephrased based on other reviewer’s suggestions too. 21) Pg13 ln504: doubles Accepted suggestion. 22) Pg13 ln 504-505: Peru. It definitely adds to the knowledge about leafhoppers from the Neotropical region, - Accepted suggestion. 23) Pg13 ln507: from this megadiverse leafhopper Accepted suggestion. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Fibronectin (FN) is a multi-functional glycoprotein that primarily acts as a cell adhesion molecule and tethers cells to the extra cellular matrix. In order to clarify the effect of FN deficiency on hematopoiesis, biochemical and immune parameters in mice. We constructed a tamoxifen-induced conditional (cre-loxp system) fibronectin knock-out (FnKO) mouse model on a C57BL/6 background, and monitored their behavior, fertility, histological, hematopoietic, biochemical and immunological indices. We found that the Fn KO mice had reduced fertility, high platelet counts, smaller bone marrow megakaryocytes and looser attachment between the hepatocyte and vascular endothelial junctions compared to the wild type (WT) mice. In contrast, the behavior, hematological counts, serum biochemical indices and vital organ histology were similar in both Fn KO and WT mice. This model will greatly help in elucidating the role of FN in immune-related diseases in future.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Fibronectin (FN) is a cell adhesion glycoprotein that was first discovered in plasma by <ns0:ref type='bibr' target='#b13'>Morrison (Morrison et al. 1948)</ns0:ref>, and it was characterized by Mosesson in 1970 in plasma <ns0:ref type='bibr' target='#b14'>(Mosesson &amp; Umfleet 1970)</ns0:ref>. It was called CIG (cold-insoluble globulin) before being named as Fibronectin. Subsequent studies have found that FN is widespread in the intercellular medium and even on the surface of cancer cells <ns0:ref type='bibr' target='#b1'>(Hynes 1985)</ns0:ref>. FNs are generated by alternative splicing from a single gene, and it exists in two different forms, one form is cellular FN (cFN), which contains, depending on the tissue, variable proportions of the alternatively spliced exons coding for the extra domains A and B (EDA, EDB). The other form is plasma FN (pFN), which lacks EDA and EDB. pFN is synthesized by hepatocytes and released into the circulation where it remains soluble <ns0:ref type='bibr' target='#b20'>(White et al. 2008)</ns0:ref>. FN has multiple functional domains that can bind to integrin, collagen, fibrin and heparin, and participate in cell adhesion, migration, proliferation and differentiation <ns0:ref type='bibr' target='#b2'>(Hynes 2012;</ns0:ref><ns0:ref type='bibr' target='#b11'>Mao &amp; Schwarzbauer 2005;</ns0:ref><ns0:ref type='bibr' target='#b16'>Pankov 2002</ns0:ref>). More and more studies have demonstrated that FN plays an important role in assessement the severity of severe infection and sepsis <ns0:ref type='bibr' target='#b5'>(Lema&#324;ska-Perek &amp; Adamik 2019;</ns0:ref><ns0:ref type='bibr' target='#b18'>Ruiz Martin et al. 2004)</ns0:ref>.</ns0:p><ns0:p>At present, FN knockout animal models are urgently needed to study the role of FN in infection and sepsis. In order to study the physiological function of FN, scientists began to try to construct PeerJ reviewing PDF | (2020:06:49574:1:0:NEW 16 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Fn gene knockout mice in the 1990s. At first, the researchers found that Fn gene knockout at embryonic level was fatal because the development of cardiovascular system in mesoderm was blocked <ns0:ref type='bibr' target='#b0'>(George et al. 1993)</ns0:ref>. In 2001, F&#228;ssler et al. established a conditional Fn gene knockout (KO) mouse model based on the cyclo-recombinase (cre-loxp) system <ns0:ref type='bibr' target='#b19'>(Sakai et al. 2001)</ns0:ref>, which was induced by the intraperitoneal injection of polyI-polyC. However, the latter can promote interferon (IFN) production in body and thus potentially affect the immune system, making this model unsuitable for studying the hematopoietic and immune-related functions of FN. The F&#228;ssler group also used albumin-cre mice in later work, they analyzed the role of FN in many different pathophysiological states such as atherosclerosis and skeletal muscle regeneration and many others <ns0:ref type='bibr' target='#b3'>(Konstandin et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b17'>Rohwedder et al. 2012</ns0:ref>). However, no reports are available so far on the effects of Fn gene knockout on the vital organs, hematopoiesis, biochemical indices and immune status of mice.</ns0:p><ns0:p>To clarify the effects of FN on the above, we constructed a tamoxifen-induced conditional Fn KO model against the C57BL/6 background using the cre-loxp system, where in the first exon of the Fn gene was modified by loxp. We achieved a knockout efficiency was 95%, as determined by the decrease in the levels of circulating plasma FN after tamoxifen induction. In addition, the Fn KO mice also showed significantly lower in situ expression of FN in the vital organs compared to the wild type (WT) mice. Although the hematopoietic, biochemical and histological indices of the Fn KO and WT mice were largely similar, the former differed in some aspects, our findings can help elucidate the functions of FN. </ns0:p></ns0:div> <ns0:div><ns0:head>The propagation of mice</ns0:head><ns0:p>Fn Loxp+ F1 mice were backcrossed with wild C57BL/6J mice, and the offspring were either self-mating or mating with UBC-cre/ERT2 mice to obtain progeny Fn Loxp+/+ and Fn Loxp+Cre+ mice. Fn Loxp+/+ mice were mated with Fn Loxp+Cre+ mice to obtain progeny Fn Loxp+/+Cre+ mice finally. WT, Fn Loxp+ and Fn Loxp+/+Cre+ (Fn KO) mice of the same age and born in the same litter were selected for the study. The mice began intraperitoneal injection of tamoxifen 0.2 mg/g body weight (corn oil with tamoxifen 10 mg/ml) at 4 weeks age for 2 times, interval 2 days. The dietary and defecation habits, changes in body weight and fur, and the fertility status of the three groups mice were observed for 12 months. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Routine blood, biochemical and histological examination</ns0:head><ns0:p>WT, Fn Loxp and Fn KO mice (4 male and 4 females per group) weighing 20-22 g were randomly selected 4 weeks after the tamoxifen injection, and anaesthetized by the intraperitoneal injection of 100-120&#956;l 0.1% pentobarbital. Blood was collected from the canthal vein, and subjected to routine cytological and biochemical tests. The chest and abdominal wall were dissected along the midline, and the liver, spleen, kidney, heart, lungs, femur and brain were extracted. All tissues were fixed overnight in 10% formalin, embedded in paraffin, sectioned and stained with hematoxylin and eosin as per standard protocols. In addition, the liver and peritoneal blood vessels were also processed for transmission electron microscopy (TEM).</ns0:p></ns0:div> <ns0:div><ns0:head>Flow cytometry</ns0:head><ns0:p>The bone marrows were flushed out, and the spleen was homogenized in PBS. The different homogenates were filtered through a 75&#181;m mesh after erythrocyte lysis. The Fc receptors on the mononuclear cells were blocked with anti-mouse CD16/32 (BD Pharmingen) antibodies for 10 minutes, and the cells were then stained with the fluorochrome-conjugated antibodies for 30 minutes at 4&#176;C in the dark. After washing twice with PBS, the cells were acquired on a BD FACS Verse flow cytometer (BD Bioscience) and the data was analyzed with FlowJo 10 software.</ns0:p></ns0:div> <ns0:div><ns0:head>Reagents</ns0:head><ns0:p>Tamoxifen (T5648) was purchased from Sigma-Aldrich. The antibodies (Abs) against mouse CD11b-PE, CD4-PE, CD3-APC-Cy&#8482;7, CD8a-FITC, CD220-FITC and CD25-FITC, and the isotype control were from BD Pharmingen. The cell staining buffer was purchased from Manuscript to be reviewed eBiolegend, and PBS and erythrocyte lysis buffer were from Hyclone. The ELISA kit (ab210967) and the antibody (ab23750) against FN were from Abcam.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical Analysis</ns0:head><ns0:p>All data were analyzed using GraphPad Prism6 software. Two groups were compared by Student t test, and P&lt;0.05 was considered statistically significant. Proportions for categorical variables were compared using the &#967;2 test. Values are presented as the mean or mean&#177;SD.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Successful generation of Fn gene conditional knockout mice</ns0:head><ns0:p>Identification and linearization of the Fn1 gene targeting vector, and the results of Hind III digestion, the theoretical band size is 9.8 kb, 5.8 kb (810 bp band is too small to shown) (Figure <ns0:ref type='figure'>2A</ns0:ref>). A total of 144 ES cells resistant clones were obtained, after sequencing the above cloning PCR products, a total of 10 correct homologous recombination positive ES cell clones were obtained. And finally, we got three mice with homologous recombination-positive F1 mice, which were number 7, 14, and 16 respectively, which were confirmed to be Loxp-positive by sequencing. The long-segment PCR identification electrophoresis 5' homology arm (5'arm) and Manuscript to be reviewed PCR analysis suggested that the knockout efficiency was up to 99% in gene level from liver (Figure <ns0:ref type='figure'>2C</ns0:ref>). The efficiency of FN knockout was determined by analyzing the levels of the protein in plasma and liver by ELISA and Western blotting, and a 95% reduction was observed (Figure <ns0:ref type='figure'>2D</ns0:ref>). In addition, the in situ levels of FN in the vital organs of the Fn KO mice were significantly reduced compared to that in the WT mice, FN immunohistochemical and immunofluorescence staining of liver and kidney indicated that FN expression was decreased significantly in Fn KO mice (Figure <ns0:ref type='figure'>2E</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Reproductive ability of Fn KO mice was significantly reduced</ns0:head><ns0:p>No significant changes were seen in the body weight, fur and other physiological indices of three groups of mice even after 12 months of tamoxifen induction. However, the fertility of female Fn KO mice was significantly reduced, the average number of pregnancies per year was significantly reduced, with a litter size of only 1-2, and the neonates showed high rates of malformation and mortality in Fn KO mice, p&lt;0.0001 (Table <ns0:ref type='table'>1</ns0:ref>). The malformed mouse offspring we observed were mainly spinal dysplasia and slender limbs.</ns0:p></ns0:div> <ns0:div><ns0:head>Changes of Hematopoietic, Biochemical and Immune Parameters in Fn KO Mice</ns0:head><ns0:p>We found except that platelet counts increased in Fn KO mice (P&lt;0.05), the whole blood and serum analysis did not reveal any significant differences between the Fn KO and other two groups of mice in terms of cytological and biochemical indices (Tables <ns0:ref type='table'>2 and 3</ns0:ref>).</ns0:p><ns0:p>Flow cytometry analysis of peripheral blood, bone marrow and spleen cells also did not show any aberration in the proportions of the lymphocyte, NK cell and monocyte subsets in the Fn KO mice, which were overall similar to that of the other two groups of mice (Figure <ns0:ref type='figure' target='#fig_8'>3A</ns0:ref>). Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Histological and electron microscopic observation of important organs in Fn KO mice</ns0:head><ns0:p>No major histological changes were observed in the heart, liver, spleen, lung, kidney and brain of the Fn KO mice relative to the WT mice, and the lymph node distribution was also normal.</ns0:p><ns0:p>However, compared to the WT mice, the megakaryocytes in the bone marrow of Fn KO mice were smaller with decreased nuclear lobulation, but their proportion was higher (Figure <ns0:ref type='figure' target='#fig_8'>3B</ns0:ref>). TEM of the liver sections of WT mice showed tight and clear-edged intercellular links between the liver parenchyma and peritoneal vascular endothelial cells (VECs), while the liver parenchyma in the Fn KO mice was loose with blurred cell edges and increased space between the VECs (Figure <ns0:ref type='figure' target='#fig_8'>3C</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Gene knockout animal models are a powerful tool to study the physiological functions of the respective genes. The Fn knockout model was first devised in the 1990s, but was embryonically lethal due to abnormal development of cardiovascular system in the mesoderm <ns0:ref type='bibr' target='#b0'>(George et al. 1993</ns0:ref>). In 2001, F&#228;ssler et al. established a conditional Fn knockout using the Cre-Loxp system, which reduced the plasma FN levels to less than 5% of the physiological value. This model helped elucidate the role of FN in coagulation, tissue repair, atherosclerosis and stroke <ns0:ref type='bibr' target='#b15'>(Ni et al. 2003;</ns0:ref><ns0:ref type='bibr' target='#b17'>Rohwedder et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b19'>Sakai et al. 2001)</ns0:ref>. However, the Cre-induced knockout was dependent on interferon, which was stimulated in vivo by intraperitoneal injection of polyI-polyC. We developed a conditional knockout model based on tamoxifen induction, and validated absence of FN in the plasma as well as the solid tissues after 4 weeks of induction. Fn knockout had no significant effect on the food intake, defecation frequency, fur color and body weight, although the fecundity of the female Fn KO mice and the viability of the neonates were significantly reduced compared to the WT mice. Previous studies have documented that FN is crucial in the development of blood vessels during embryogenesis <ns0:ref type='bibr' target='#b0'>(George et al. 1993;</ns0:ref><ns0:ref type='bibr' target='#b4'>Kumra et al. 2018</ns0:ref>). It has also been reported that Fank1 (Fibronectin Type3 domain)-knockout did not cause changes in sperm quality or quantity in male mice <ns0:ref type='bibr' target='#b21'>(Zhang et al. 2019)</ns0:ref>, however, the effect of FN deficiency on the fertility of male mice still need to be further studied.</ns0:p><ns0:p>We found there were no substantial differences between the Fn KO and WT mice in terms of peripheral blood counts, serum biochemical indices, tissue architecture, and the hematological cell subtypes in bone marrow, spleen and peripheral blood. However, we found the platelet counts increased in Fn KO mice, but the megakaryocytes in the bone marrow of Fn KO mice were noticeably smaller and showed decreased nuclear lobulation. It has been reported that FN can regulate and impact megakaryocyte behavior differently during their differentiation <ns0:ref type='bibr' target='#b6'>(Malara et al. 2014;</ns0:ref><ns0:ref type='bibr' target='#b9'>Malara et al. 2011)</ns0:ref>. It was recently reported that fibronectin EDA isoform can sustain megakaryocyte expansion and participate in the inflammatory process of myelofibrosis <ns0:ref type='bibr'>(Malara et al. 2019;</ns0:ref><ns0:ref type='bibr' target='#b12'>Matsuura et al. 2020)</ns0:ref>. However, the mechanism by which FN Manuscript to be reviewed affects megakaryocytes and platelets has not been fully elucidated.</ns0:p><ns0:p>In addition, ultrastructural observation of the liver parenchyma showed tightly inter-connected liver cells and peritoneal VECs in the WT mice, which was loose in the Fn KO mice. These results indicate that FN affects the integrity and permeability of VECs, this may be due to the loss of cellular type FN, which should be verified in future studies.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>To summarize, we established a tamoxifen-induced conditional Fn gene knockout mouse model, and observed that FN deletion did not have any systemic effects on the adult mice, except for fertility. However, changes in platelet counts in blood, megakaryocyte morphology and VEC integrity point to certain non-canonical functions. Our mouse model will greatly help in elucidating the role of FN in infection and immune-related diseases in future. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Target gene name (MGI number): Fn1 (95566), Fn transcript for the knockout protocol (Ensembl number): Fn1-001(ENSMUST00000055226), Flox-targeted Fn exons: exon 1. Using the principle of homologous recombination, the Fn1 gene was subjected to flox modification by means of embryonic stem (ES) cell targeting. The brief process is as follows: Bacterial artificial chromosome (BAC) clones containing Fn gene are purchased from Sanger Institute (UK). The ES cell targeting vector was constructed by the method of ET-clone. The vector comprises a 4 kb 5' homology arm, a 0.5 kb flox region, a PGK-Neo-polyA, a 4 kb 3' homology arm, and a MC1-TK-polyA negative selection marker. After the vector is linearized, it is electrotransfected into C57*129 cells. After screening with G418 and Ganc drugs, hundreds of resistant clones wereobtained, and positive clones with correct homologous recombination were identified by long fragment PCR. The positive ES cell clone was amplified and injected into the blastocyst of C57BL/6J mice to obtain a chimeric mouse. High proportion of chimeric mice were mated with Flp mice to obtain positive F1 mice (This part of the experiment was completed with the assistance of Southern Model Biotechnology). The Fn vector plasmid construction model is shown in Figure 1. Animals Specific pathogen free (SPF) male and female C57BL/6J mice (8 to 12 weeks old, weighing 20~22g) were purchased from Shanghai SLAC LABORATORY ANIMAL COMPANY. The Fn loxp+/+(Fn Flox) mice were generated in our lab with technical support from the Shanghai PeerJ reviewing PDF | (2020:06:49574:1:0:NEW 16 Sep 2020) Manuscript to be reviewed Biomodel Organism Science &amp; Technology Development. UBC-cre/ERT2 mice were purchased from Shanghai Biomodel Organism Science &amp; Technology Development. The mice were housed five to six per cage under specific pathogen-free conditions, and the animal housing included a controlled light and dark cycle (12h: 12h), ad libitum food and ultra filtered water, 50-55% humidity, ventilated caging systems and standardized environmental enrichment. Except that the mice used to observe the lifespan were waiting for natural death, all the other surviving mice were euthanized by inhalation of an overdose of sevoflurane after the end of the experiment. All animals were handled in strict accordance with good animal practice as defined by the National Regulations for the Administration of Experimental Animals of China and the National Guidelines for Experimental Animal Welfare of China. Animal protocols and experimental procedures were also approved by the Institutional Animal Care and Use Committee of the University of Fujian Medical University (Ethical Approval Number: 2017-0135).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49574:1:0:NEW 16 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49574:1:0:NEW 16 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>3' homology arm (3'arm) are shown in Figure 2B. The 5 'arm homologous recombination positive clones amplified 4.2 kb and 5.6 kb fragments, while the negative clones amplified only 5.6 kb fragments. 3 'arm homologous recombination positive cloning should amplify the fragment of 4.6kb and 5.9kb, while the negative cloning could only amplify the fragment of 5.9kb. Fn loxP+/+ Cre+ mice were induced by tamoxifen peritoneal injection for 1 week. The PeerJ reviewing PDF | (2020:06:49574:1:0:NEW 16 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49574:1:0:NEW 16 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>High levels of interferon can potentially affect the immune function, making this model unsuitable for studying the role of FN in hematopoietic and immune-related functions. Although later used albumin-cre mice, F&#228;ssler et al extensively analyzed the role of fibronectin in many PeerJ reviewing PDF | (2020:06:49574:1:0:NEW 16 Sep 2020) Manuscript to be reviewed different pathophysiological states such as atherosclerosis and skeletal muscle regeneration. No reports are available so far on the effects of Fn gene knockout on the vital organs, hematopoiesis, biochemical indices and immune status of mice.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49574:1:0:NEW 16 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:06:49574:1:0:NEW 16 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

" Dear editor: We thank the reviewers for their generous comments on the manuscript and have have edited the manuscript to address their concerns. Due to the impact of COVID-19 and the time-consuming follow-up research, we were not able to revise manuscript as soon as possible. I hope the editor will understand our difficulties. We replied one by one to the comments of reviewers and made necessary modifications according to the suggestions. We believe that the manuscript is now suitable for publication in PeerJ. Thank you and best regards. Yours sincerely, Professor Yuanzhong Chen On behalf of all authors. September 15, 2020 Reviewer 1 Comments for the author The authors generate conditional fibronectin knock-out mice, which could be induced by tamoxifen. The authors monitored fertility and some histological, hematopoietic, biochemical and immunological parameters. The authors speculate that their animal model will help to elucidate the role of fibronectin in immune-related diseases in the future. This is an interesting study. There are, however, numerous points the authors should address. Major points: 1. In the introduction of the manuscript the authors should explain in much more details the biology of fibronectin. The splice forms of fibronectin need to be mentioned and explained. Do the conditional fibronectin knock-out mice lead to the deletion of both splice forms? We added descriptions of FN structure and gene splicing in the introduction. In our study, we designed to knock out the first exon of FN, so both forms of FN were knocked out, which was confirmed by the tissue WB test. 2. Along the same line: in Fig. 2, the authors use the abbreviations of the two spliced forms of fibronectin pFN and cFN. These spliced forms have not been mentioned and explained in the text. Thanks for the reviewer's careful reading, the description of cFN and pFN has been added to the introduction of manuscript. 3. It needs to be explained in much more details how the conditional fibronectin knock-out mice work. What happens upon tamoxifen induction; in which cells is the functional fibronectin gene deleted? In Fig. 2C, many bands are shown but it is not clear whether they are derived from different tissues. Please explain. Tamoxifen-induced gene knockout based on Cre-Loxp system has been widely accepted by academic circles. In the absence of tamoxifen, Cre-ER binds with Hsp90, and is located in the cytoplasm. When tamoxifen is present, it binds with the ER, displacing Hsp90. The Cre-ER-tamoxifen complex translocates to the nucleus, in which Cre executes its function. The gene sequence of Loxp sites was cut off. In Fig. 2C, all PCR band templates were derived from mouse liver, we have made further supplement to the description of figure. 4. The authors claim that they studied behavior of the conditional fibronectin knock-out mice. These data are not in the manuscript. This claim should therefore be deleted. We have made some deletions according to the comments of reviewer. 5. The authors mention the previous work on conditional fibronectin knock-out mice by the group of Fässler (ref. Sakai et al). They claim that the work of this group was not conclusive because they used mx-cre mice, which need to induced by poly I/C, which affects the immune system. The Fässler group also used albumin-cre mice and in later work the group extensively analyzed the role of fibronectin in many different pathophysiological states such as atherosclerosis and skeletal muscle regeneration and many others. It is very unfair to ignore this important work and to pretend that close to nothing is known about the biology of fibronectin. The authors should be fair about the extensive published work of other groups. The results obtained by the authors should be compared to the published work. Thanks for the reviewer's professional advice, we did notice that the follow-up work of Fässler (ref. Sakai et al) team mentioned by the reviewer, and we did not deliberately ignore the above contents. Here, we added relevant content in the manuscript, meanwhile, references to relevant literature are also added. However, no reports are available so far on the effects of Fn gene knockout on the vital organs, hematopoiesis, biochemical indices and immune status of mice. So we're answering some very basic questions. Minor points: 1. The language of the manuscript should be corrected by a native speaker. Thanks for the comments of the reviewer. We are working hard. If necessary, we will invite professional language editors. 2. It is not clear to this reviewer why a 810 bp DNA band should not be visible on a DNA gel (line 127). This is gel electrophoresis of plasmid after HindIII enzymatic digestion. Theoretically there would be three bands (9.8kb, 5.8kb and 810bp), but 810bp were not found in many tests. This may be related to incomplete enzyme digestion and too little yield. However, the results did not affect the identification of the target gene. 3. The right panes shown in Fig. 2E does not show anything in this reviewers copy. Perhaps because the image pixel contrast is not strong, we have optimized the immunofluorescence contrast graph of FN expression. 4. How many resistant clones have been identified and analyzed (line 65/66)? A total of 144 ES cells resistant clones were obtained, after sequencing the above cloning PCR products, a total of 10 correct homologous recombination positive ES cell clones were obtained. We added this to the first part of the result of the manuscript. 5. What is fibronectin type 3 (line 181)? Please explain. The fibronectin type III domain (Fn3) is a repeated domain in FN, its main functions are to mediate protein-protein interactions. Fn3 domains have been found in intracellular, extracellular, and membrane-spanning proteins. We made a brief supplement in the manuscript 6. What is fibronectin EDA (line 190)? Please explain. Fibronectin EDA is a domain of cellular FN, we added descriptions of FN structure and gene splicing in the introduction of manuscript . Reviewer 2(Stefanie Krick) Basic reporting Overall, this is a very interesting manuscript focusing on conditional FN knockout and the hematopoetic system. The authors reliably established their model. There are some concerns though: 1. Please specify in the results section at what age mice were injected with tamoxifen and for how long they were observed afterwards. We described this in detail in the Materials & Methods (The propagation of mice) 2. Please specify the malformations seen in the offspring of FN KO mice. The malformed mouse offspring we observed were mainly spinal dysplasia and slender limbs, which were not the main research in this paper, we will organize further research in the future. 3. Please try to quantify the results of the KO mice. The efficiency of FN KO was determined by analyzing the levels of the protein in plasma and liver by ELISA and Western blotting, and a 95% reduction was observed. The PCR analysis suggested that the knockout efficiency was up to 99% in gene level, show in figure2c-d. 4. The differences between both models should be discussed more in detail – why did the authors not decide to get the already established model but rather establish a new model. First, it has been 20 years since the previous FnKO model was established, and the genetic phenotype of the mice was uncertain as there were many passages. Secondly, we have tried to seek help from relevant researchers in the early stage, but failed. Our research group has been studying the value of FN in the diagnosis and treatment of sepsis, and it is indeed necessary to establish FnKO mouse model. 5. Please comment further on the described survival rate of the mice? What is meant here? In our study, we established the FnKO mouse model to study the effects of FN deficiency on hematopoietic and immune function, so we first evaluated the physiological parameters of adult FnKO mice and found that the gestation ability of female FnKO mice was significantly reduced, but this was not the focus of our study, so we've only given a brief description of this results. 6. Table 3: what was the reasoning of chosen these parameters? Why not including a basic metabolic panel which includes Na, Cl, K, HCO3? Due to the limitation of blood collection volume in mice, the serum volume was only sufficient for partial blood biochemical indexes, so we selected the liver and kidney function and blood lipid of mice for priority monitoring. The electrolyte indexes of some mice were tested in the preliminary experiment, and no difference was found among the three groups. Experimental design 1. The authors should include more detailed description about their control groups, which should include a FnLoxp+Cre+ group, which they did not inject with Tamoxifen to show the truly conditional nature of their knockout mouse. In the pre-experiment we had this FnLoxp+Cre+ without tamoxifen control group, the phenotypic results were similar to those of the WT and FnLoxp groups with or without tamoxifen addition, they were not statistically significant. 2. Please include information about what Fn antibiodies and ELISA kits were used. We used parentheses in the Materials & Methods Reagents to provide supplementary information. 3. Fig. 2E should include a negative control as well and show higher magnifications. Immunohistochemistry was completed with the assistance of pathologists, and the laboratory had good quality control of positive and negative controls, so the negative control group was not designed in this experiment. Both optical and fluorescence microscopes were 400 x magnification. Validity of the findings Although this is a very thorough and elaborate approach and definitely important for studying the role of FN in the hematopoietic system, all results are here of descriptive nature and show that conditional FN deficiency does not seem to exert an effect at baseline, though the authors did not look at any functional outcomes, such as platelet function assays, coagulation cascade or immune cell function, which should be included. In addition, I would recommend to further work up why the fertility is reduced in these mice by looking at the reproductive organs as well. General comments 1. Fig. 2D – please change order of Western blots to unify direction for both plasma and liver lysates. We revise as suggested. 2. I recommend to label Fig. 3B and C including arrows to show the authors findings in a clearer way. We revise as suggested. Comments for the author Minor spell check is required, otherwise, please see all comments above. Thanks for the comments of the reviewer. We are working hard. If necessary, we will invite professional language editors. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Recent studies have determined that long non-coding RNAs (lncRNAs) are potential prognostic biomarkers for non-small cell lung cancers (NSCLCs). The purpose of this study was to analyze the function and associated pathways of zinc finger protein multitype 2 antisense RNA 1 (ZFPM2-AS1) in NSCLC cells. Methods: We used qRT-PCR to analyze ZFPM2-AS1's transcription level. Its proliferation, migration, and invasion capacities were determined using MTT, colony forming, wound healing, and transwell assays. We additionally analyzed the correlation between ZFPM2 and immune infiltration using the Tumor Immune Estimation Resource (TIMER) database, and the protein expression levels using Western blots. Results: We found that ZFPM2-AS1 expression in NSCLC specimens and cell lines was elevated compared to the control group. ZFPM2-AS1 is an oncogene and independent prognostic predictor of poor survival in NSCLCs, and its expression had a positive correlation with tumor size and lymph node metastasis in our clinical data. MTT, colony forming, wound healing, and transwell assays showed a positive correlation between ZFPM2-AS1 expression and the proliferation, migration, and invasion of NSCLC cells in the presence and absence of interferon-&#947; (IFN-&#947;). Using the TIMER database, we hypothesized that ZFPM2 was negatively correlated with ZFPM2-AS1 expression, as well as the immune infiltration levels in lung adenocarcinoma (LUAD).</ns0:p><ns0:p>Finally, we found that ZFPM2-AS1 negatively regulated ZFPM2 expression, and had a positive correlation with PD-L1 expression through the JAK-STAT and AKT pathways.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion:</ns0:head><ns0:p>Our study confirmed that ZFPM2-AS1 promotes the proliferation, migration, and invasion of NSCLC cells via the JAK-STAT and AKT pathways. Further research on the ZFPM2-AS1 pathway regulation mechanism is needed.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Lung cancer is the most deadly malignant tumor, accounting for more than 80% of non-small cell lung cancers (NSCLCs) worldwide, most of which are lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Multiple therapies have improved the prognosis of NSCLCs,</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed but the 5-year survival rate has remained lower than 20% <ns0:ref type='bibr' target='#b0'>(1)</ns0:ref>. Therefore, it is crucial to explore novel diagnostic biomarkers and therapeutic approaches <ns0:ref type='bibr' target='#b1'>(2,</ns0:ref><ns0:ref type='bibr' target='#b2'>3)</ns0:ref>. Long non-coding RNAs (lncRNAs), defined as non-coding transcripts longer than 200 nucleotides, are associated with the initiation, progression, and prognosis of various tumors <ns0:ref type='bibr' target='#b3'>(4,</ns0:ref><ns0:ref type='bibr' target='#b4'>5)</ns0:ref>.</ns0:p><ns0:p>Mounting dysregulated lncRNAs may also play a role as tumor suppressors or oncogenes in multiple tumors, including NSCLCs. We previously screened differential expression lncRNAs in NSCLCs using The Cancer Genome Atlas (TCGA) database <ns0:ref type='bibr' target='#b5'>(6)</ns0:ref>. We speculated that one of the most distinct lncRNAs, zinc finger protein multitype 2 antisense RNA 1 (ZFPM2-AS1), may play an important role in the biological behavior of NSCLC cells. In this study, we concentrated on the functions of ZFPM2-AS1. ZFPM2-AS1 reportedly induces p53 destabilization by stabilizing macrophage migration inhibitory factor (MIF), leading to the progression of gastric cancer <ns0:ref type='bibr' target='#b6'>(7)</ns0:ref>. ZFPM2-AS1 has also been shown to promote metastasis and proliferation, as well as inhibit renal cell cancer apoptosis by targeting miR-137 <ns0:ref type='bibr' target='#b8'>(8)</ns0:ref>. Additionally, ZFPM2-AS1 can promote NSCLC progression via the miR-511-3p/AFF4 and miR-18b-5p/VMA21 pathways <ns0:ref type='bibr' target='#b9'>(9,</ns0:ref><ns0:ref type='bibr' target='#b10'>10)</ns0:ref>, and enhance the malignancy of cervical cancer by sponging microRNA-511-3p <ns0:ref type='bibr' target='#b11'>(11)</ns0:ref>. By upregulating TRAF4, ZFPM2-AS1 facilitates cell proliferation in both esophageal squamous cell carcinoma and small cell lung cancer <ns0:ref type='bibr' target='#b12'>(12,</ns0:ref><ns0:ref type='bibr' target='#b13'>13)</ns0:ref>.</ns0:p><ns0:p>However, ZFPM2-AS1's molecular regulatory network in NSCLC cells remains unclear. The PI3K/AKT and JAK/STAT signaling pathways promote cell proliferation and motility by activating key metastasis-promoting genes <ns0:ref type='bibr' target='#b15'>(14)</ns0:ref>. STAT activation is restricted in normal cells.</ns0:p><ns0:p>However, once STAT is activated, numerous genes that control tumor cell proliferation, angiogenesis, and evasion of immune surveillance are uncontrollably expressed <ns0:ref type='bibr' target='#b16'>(15)</ns0:ref>. Interferon-&#947; (IFN-&#947;) is crucial for immunity against intracellular pathogens and tumor cells <ns0:ref type='bibr' target='#b17'>(16)</ns0:ref>. Since IFN-&#947; has the ability to induce PD-L1, IFN-&#947; expression in cancer cells may weaken the immunity of specific tumor cells <ns0:ref type='bibr' target='#b18'>(17)</ns0:ref>. Additionally, it has been found that PD-L1 expression is positively correlated with JAK2 in NSCLCs via the JAK-STAT axis <ns0:ref type='bibr' target='#b20'>(18)</ns0:ref>. However, it has not been proved whether ZFPM2-AS1 can regulate PD-L1 via the JAK-STAT and AKT pathways.</ns0:p><ns0:p>In this study, we investigated ZFPM2-AS1's proliferation, migration, and invasion abilities in NSCLC cells. We also determined the regulatory roles of ZFPM2-AS1 in the JAK-STAT and AKT pathways.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and methods</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>| TCGA and Tumor Immune Estimation Resource (TIMER) databases</ns0:head><ns0:p>We used ZFPM2-AS1 transcript expression levels extracted from TCGA's database for our tumor types from TCGA <ns0:ref type='bibr' target='#b21'>(19)</ns0:ref>, along with specific genes' tumor immune inltration levels. We analyzed ZFPM2 expression across multiple tumor types using the dierent expression module, and identified the association between ZFPM2 expression and immune inltration level using the gene module. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>| Patients and samples</ns0:head></ns0:div> <ns0:div><ns0:head n='2.3'>| Cell culture, reagent, and transfection</ns0:head><ns0:p>The human NSCLC cell lines (A549 and H460) were purchased from the Shanghai Institutes of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China. The A549 and H460 cell lines had been cultured in RPMI-1640 with 10% fetal bovine serum (Clark Biosciences, Richmond, VA, USA), 100 U/ml penicillin, and 100 ug/ml streptomycin (Sigma-Aldrich, St.</ns0:p><ns0:p>Louis, MO, USA) in a 5% CO 2 incubator at 37&#176;C. During IFN-&#947; stimulation, cells were incubated with 100 ng/ml of recombinant human IFN-&#947; (Peprotech, Cranbury, NJ, USA) for 48 hrs. We applied Lipo3000 (Invitrogen, Carlsbad, CA, USA) according to our transfection protocol. We used 20 uM of lncRNA Smart Silencer (RiboBio, Guangzhou, China) and a mixture of three siRNAs and three antisense oligonucleotides. The sequences are provided in Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>. ZFPM2-AS1 overexpression plasmid was provided by GenePharma (Shanghai, China).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>| RNA isolation, cDNA synthesis, and quantitative real-time RT-PCR</ns0:head><ns0:p>We extracted total RNA using TRIzol reagent, and performed reverse-transcription using HisScript&#8482; QRT SuperMix (Vazyme Biotech Co., Ltd., Nanjing, China). We used qRT-PCR and ChamQ&#8482; Universal SYBR qPCR Master Mix (Vazyme Biotech Co., Ltd.) to analyze the relative expression of the control group. The specific primers are shown in Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>. GAPDH and RPS18</ns0:p><ns0:p>were used as housekeeping genes. The relative gene expression was calculated using the 2 -&#916;&#916;Cq method.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>| MTT assay</ns0:head><ns0:p>Cell viability was determined using MTT reagent (Sigma-Aldrich) with a concentration of 0.5 mg/mL for 4 h. Following that, we seeded 4&#215;10 3 cells per well in 96-well plates for 0, 1, 2, 3, 4, and 5 days. The supernatant was abandoned, and we precipitated formazan with DMSO. Finally, we analyzed the absorbance at 450 nm using a microplate reader (Thermo Fisher Scientific, Waltham, MA, USA).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>| Colony formation assay</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>We cultured about 3,000 terminated trypsinized cells in 6-cm dishes three times at 37 &#176;C in 5% CO 2 . Two weeks later, the cell colonies were fixed with 10% methanol for 30 s, and then stained with 0.1% crystal violet (Sigma-Aldrich) for 15 min. Finally, the visible colonies were counted using a microscope.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>| Wound healing assay</ns0:head><ns0:p>A549 and H460 cells were seeded into 5&#215;10 5 cells/well in six-well plates three times. A 200 &#956;L pipette tip was used to make a scratch where the conuence reached 90%. The cells were then incubated at 37&#176;C in 5% CO 2 for 24 h. We studied the migration distances using an FSX100</ns0:p><ns0:p>Biological Image system (Olympus, Tokyo, Japan).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.8'>| Transwell migration and invasion assay</ns0:head><ns0:p>Migration and invasion assays were placed in 24-well Transwell chambers that had 8 &#956;m size pores (Costar, Washington, D.C., USA). In the invasion assay, the pores were covered with 100 &#956;L of Matrigel (BD Biosciences, San Jose, CA, USA). After trypsinization, we placed 100 &#956;L of medium (5&#215;10 4 cells) supplemented with 2% fetal bovine serum in the upper Transwell chamber, and 600 &#956;L of medium supplemented with 10% fetal bovine serum in the lower chamber. After 24 h of incubation, the upper cells were removed, and the lower ones were fixed with paraformaldehyde and stained with hematoxylin. The number of migrated/invaded cells was analyzed using 10 randomly selected fields at &#215;200 magnification under phase contrast microscopy (Olympus). All assays were performed independently at least three times.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.9'>| Nuclear-cytoplasmic localization</ns0:head><ns0:p>We harvested and washed the A549 cells before adding 500 &#181;l of cell disruption buffer (PARIS kit; cat. no. AM1921; Invitrogen/Thermo Fisher Scientific) to the cells on ice for 10 min.</ns0:p><ns0:p>Following centrifugation at 500 x g, the supernatants were preserved as cytoplasmic RNA. They were washed, an equal volume of nuclear lysate buffer was added, and they were centrifuged at 500 x g. Finally, the supernatants were collected as nuclear RNA and we performed qRT-PCR using the primers listed in Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='2.10'>| Flow cytometry</ns0:head><ns0:p>For cell cycle analysis, we harvested the transfected cells, washed them with PBS, resuspended them in 0.9 ml of PBS, and gradually added ice-cold ethanol up to a volume of 3 ml.</ns0:p><ns0:p>After 24 hours of fixation, the cells were incubated with 0.1% Triton X-100, 0.2 mg/ml RNase A, and 25 &#956;g/ml propidium iodide (PI) for 30 minutes at room temperature. We used flow cytometry to assay the DNA content (Becton Dickinson, Bedford, MA, USA), and ModFit software (Verify Software) to quantify the percentage of cells within the S-, G0/G1-, and G2/M-phases of the cell cycle.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.11'>| Western blot analysis</ns0:head><ns0:p>After harvesting the proteins using a lysis buffer (50 mM of Tris (pH 7.4), 1% Triton X-100, 0.5% Nonidet P-40, 150 mM NaCl, and protease inhibitor), we separated them using 10% sodium dodecyl sulfate (SDS) polyacrylamide gel electrophoresis. The proteins were then transferred to polyvinylidene difluoride (PVDF) membranes (Millipore, Burlington, MA, USA) for 2 h at 220 mA. The membranes were blocked in 5% BSA with TBST for 1 h at room temperature, and were incubated overnight using primary antibodies at 4&#176;C. We incubated the secondary antibody with horseradish peroxidase (HRP) conjugates for 1 h at room temperature. We identified the bands using a chemiluminescence detection kit (Tanon, Shanghai, China). We found that the primary antibodies included PDL1 (E1L3N), JAK2 (D2E12), phospho-STAT3 (Tyr705; D3A7), STAT3 (79D7), phospho-AKT (Ser473; D9E), AKT (40D4; all purchased from Cell Signaling Technology, Boston, MA, USA), and ZFPM2 (OriGene).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.12'>| Statistical analysis</ns0:head><ns0:p>The log-rank test was performed using the Kaplan-Meier survival analysis procedure <ns0:ref type='bibr' target='#b17'>(16)</ns0:ref>.</ns0:p><ns0:p>We conducted statistical analyses with GraphPad Prism7 (GraphPad Software, Inc., San Diego, CA, USA). Test data were manifested as means &#177; standard deviation (SD). We used the student's t-test (two-tailed) to find the differences between two groups, and one-way ANOVA to find the differences across more than two groups, followed by Dunnett's post-test. P&lt;0.05 was considered statistically signicant.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>|</ns0:head><ns0:p>Increased ZFPM2-AS1 related to poor survival in in NSCLC patients During our investigation, we used ZFPM2-AS1 RNA-seq data from TCGA to analyze the differential expressions across 59 normal lung tissues and 535 LUADs or LUSCs. We found a significant increase of ZFPM2-AS1 in NSCLCs compared to normal lung tissues (Fig. <ns0:ref type='figure' target='#fig_10'>1A</ns0:ref>).</ns0:p><ns0:p>Furthermore, when analyzing the ROC curve based on the screened TCGA data, we found that ZFPM2-AS1's AUC value was 0.891 (Fig. <ns0:ref type='figure' target='#fig_10'>1B</ns0:ref>), indicating that ZFPM2-AS1 may be a novel diagnostic biomarker. Generated using screened data from TCGA, the Kaplan-Meier survival curve showed that higher ZFPM2-AS1 expression levels were significantly associated with poor prognoses for NSCLC patients (Fig. <ns0:ref type='figure' target='#fig_10'>1C</ns0:ref>). Ultimately, our results suggested that ZFPM2-AS1 is a possible oncogene in NSCLCs.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>| Validating ZFPM2-AS1 expression patterns in NSCLC samples and cell lines</ns0:head><ns0:p>To further verify the ZFPM2-AS1 expression patterns that we found in TCGA's RNA-Seq databases, we used qRT-PCR to validate 50 pairs of collected NSCLC and adjacent normal samples. We found that the relative transcription expression levels were significantly higher in NSCLC tissue compared to the adjacent normal tissues (Fig. <ns0:ref type='figure' target='#fig_3'>2A</ns0:ref>; P&lt;0.0001). We also validated BEAS-2B, A549, NCI-H460, H1299, H292, and HEK293 cells by performing qRT-PCR, and found that ZFPM2-AS1 was expressed in all of these cell lines. Compared to the BEAS-2B cell expression levels, ZFPM2-AS1 was significantly upregulated in the A549 and H460 cells. The expression levels were significantly downregulated in the NSCLC cell lines H1299 and H292 (Fig. <ns0:ref type='figure' target='#fig_3'>2B</ns0:ref>). These results implied that ZFPM2-AS1's function in A549 and H460 cells may be similar to its functions in NSCLC samples.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>| The association between ZFPM2-AS1 and NSCLC clinical characteristics</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>When examining the possible association between ZFPM2-AS1 expression levels and the clinical parameters of 50 NSCLC patients, we found that tumor size was significantly positively correlated with ZFPM2-AS1 expression (p=0.007). The tumor-node-metastasis (TNM) stage was also positively correlated with ZFPM2-AS1 expression (p=0.047). However, ZFPM2-AS1 expression did not have a significant correlation with other clinical characteristics, including age, gender, tumor differentiation, smoking history, and lymph node metastasis (Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>). Our results</ns0:p><ns0:p>showed that ZFPM2-AS1 expression was positively correlated to tumor size and TNM stage.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.4'>| ZFPM2-AS1 knockdown decreases proliferation and colony formation in NSCLC cell lines</ns0:head><ns0:p>Since ZFPM2-AS1 was highly expressed in A549 cells, we used siRNA-mediated ZFPM2-AS1 knockdown in A549 cells to analyze ZFPM2-AS1's biological functions. To minimize the off-target effects on lncRNA, we used specific Smart Silencers, including three individual siRNAs and three individual antisense oligonucleotides. The decreased efficiency was confirmed by qRT-PCR (Fig. <ns0:ref type='figure' target='#fig_4'>3A</ns0:ref>). Subsequently, we used an MTT assay to show any cell proliferation caused by ZFPM2-AS1 silencing or overexpression. We also stimulated ZFPM2-AS1 using IFN-&#947; because of its ability to induce PD-L1 and promote the immune escape of tumor cells. The results showed that the proliferation rate of ZFPM2-AS1 silencing in the H460 cells was aberrantly lower than in the control group after 72-120 hours (Fig. <ns0:ref type='figure' target='#fig_4'>3B</ns0:ref>). In the A549 cells, the proliferation rate was significantly lower when silencing ZFPM2-AS1 after 72 hours without IFN-&#947;, and after 96-120 hours with IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_4'>3C</ns0:ref>). Meanwhile, ZFPM2-AS1 overexpression significantly promoted A549 cell proliferation after 96-120 hours without IFN-&#947;, and after 72-120 hours with IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_4'>3D</ns0:ref>). We obtained similar results when performing colony forming assays, confirming that ZFPM2-AS1 knockdown distinctly inhibited colony forming in both A549 and H460 cells (Fig. <ns0:ref type='figure' target='#fig_4'>3E-H</ns0:ref>). These results suggest that ZFPM2-AS1's role as an oncogene involves promoting NSCLC cell line proliferation.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.5'>| ZFPM2-AS1 promotes the migration and invasion of NSCLC cell lines</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The results of the wound healing assay indicated that ZFPM2-AS1 knockdown significantly inhibited A549 and H460 cell motility when compared to the control group (Fig. <ns0:ref type='figure' target='#fig_5'>4A-D</ns0:ref>). We used the Transwell assay to investigate whether migration and invasion were also affected by ZFPM2-AS1 in NSCLC cells. We found that the siRNA-mediated ZFPM2-AS1 knockdown significantly inhibited the invasion capacities of both A549 and H460 cells (Fig. <ns0:ref type='figure' target='#fig_5'>4E, F</ns0:ref>). The silencing of ZFPM2-AS1 distinctly impeded the invasion and migration capabilities of A549 cells, in both the presence and absence of IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_5'>4G-J</ns0:ref>). Meanwhile, ZFPM2-AS1 overexpression significantly promoted invasion and migration in the presence or absence of IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_5'>4K-N</ns0:ref>). Ultimately, we determined that ZFPM2-AS1 promoted migration and invasion in both A549 and H460 cells.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.6'>| ZFPM2-AS1's primary expression in the nucleus did not affect the A549 cell cycle</ns0:head><ns0:p>To clarify its cellular localization, we used qRT-PCR to determine ZFPM2-AS1 expression in both the nuclear and cytoplasmic fractions of A549 cells. We used GAPDH expression for the cytoplasmic indicator, and U1 snRNA enrichment for the nuclear indicator. The results showed that ZFPM2-AS1 was primarily expressed in the nucleus (Fig. <ns0:ref type='figure' target='#fig_6'>5A</ns0:ref>), indicating that ZFPM2-AS1 may also regulate the functions of NSCLC cells in the nucleus. We used a flow cytometric analysis to determine whether ZFPM2-AS1 silencing or overexpression had an impact on the cell cycle, with and without IFN-&#947;. The results showed that IFN-&#947; arrested A549 cells at the G0/G1 phase.</ns0:p><ns0:p>However, ZFPM2-AS1 silencing and overexpression did not significantly affect the A549 cell cycle (Fig. <ns0:ref type='figure' target='#fig_6'>5B-I</ns0:ref>). Our results confirmed that ZFPM2-AS1 was primarily expressed in the nucleus, but its effect on the proliferation, migration, and invasion of A549 cells was not dependent on the cell cycle.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.7'>| The association between ZFPM2, a potential target for ZFPM2-AS1, and LUAD tumor immune infiltration level</ns0:head><ns0:p>To determine whether ZFPM2-AS1 was associated with tumor immune infiltration level, we mined data from the TIMER database. Since ZFPM2 is a potential target for ZFPM2-AS1, we found that ZFPM2 expression was significantly lower in most human tumors compared to the adjacent normal tissues, including LUAD and LUSC (Figure <ns0:ref type='figure' target='#fig_7'>6A</ns0:ref>). ZFPM2-AS1 expression was significantly higher in NSCLC tissues compared to normal lung tissues (Fig. <ns0:ref type='figure' target='#fig_10'>1A</ns0:ref>), suggesting a possible negative correlation between ZFPM2-AS1 and ZFPM2. We also found a negative correlation between ZFPM2 expression and the immune infiltrate levels of tumor purity (R=-0.352, P=8.14e -16 ) in LUAD (Figure <ns0:ref type='figure' target='#fig_7'>6B</ns0:ref>). These results implied that ZFPM2 expression was significantly lower in LUAD and LUSC, as well as negatively correlated with tumor immune infiltration levels. We wanted to further verify the positive correlation between ZFPM2-AS1 and the immune infiltrating marker PD-L1 using Western blot.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.8'>| ZFPM2-AS1's negative regulation of ZFPM2 expression and positive regulation of PD-L1</ns0:head><ns0:p>expression via the JAK-STAT and AKT pathways First, we silenced ZFPM2-AS1 expression using three individual siRNAs in the A549 cells.</ns0:p><ns0:p>The results showed a significant increase in ZFPM2 expression, indicating that ZFPM2-AS1 may negatively regulate ZFPM2 expression. Meanwhile, JAK2, p-STAT3, and p-AKT expression decreased in comparison to the control group. However, there was no significant differential STAT3 and AKT expression (Fig. <ns0:ref type='figure' target='#fig_8'>7A, B</ns0:ref>). We used siRNA to induce more significant ZFPM2 differences in the following experiment. We performed ZFPM2-AS1 silencing, both with and without IFN-&#947; exposure, to identify the differences between the JAK-STAT and AKT pathways.</ns0:p><ns0:p>We found that in both the presence and absence of IFN-&#947;, ZFPM2-AS1 knockdown significantly upregulated ZFPM2 expression and downregulated JAK2, p-STAT3, and p-AKT expression. PD-L1 expression was distinctly inhibited when ZFPM2-AS1 was silenced by IFN-&#947; stimulation (Fig. <ns0:ref type='figure' target='#fig_8'>7C, D</ns0:ref>). Furthermore, ZFPM2-AS1 overexpression downregulated ZFPM2 expression and upregulated JAK2, p-STAT3, p-AKT, and PD-L1 expression in the presence or absence of IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_8'>7E, F</ns0:ref>). Ultimately, we determined that ZFPM2-AS1 negatively regulated ZFPM2 expression and positively regulated PD-L1 expression through the JAK-STAT and AKT pathways.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>Recent studies have shown that lncRNAs can operate as biomarkers in the diagnosis, therapy, and prognosis of various malignant tumors <ns0:ref type='bibr' target='#b22'>(20,</ns0:ref><ns0:ref type='bibr' target='#b23'>21)</ns0:ref>. Our results indicated that ZFPM2-AS1 was upregulated in NSCLC specimens and cell lines when compared to the control groups.</ns0:p><ns0:p>Additionally, we found a correlation between ZFPM2-AS1 and poor survival in TCGA. When looking at clinical statistics, we found that higher ZFPM2-AS1 expression levels were positively correlated with larger tumor sizes and later TNM stages. These findings suggest that ZFPM2-AS1 may be a potential novel biomarker for NSCLC. Our study also verified that the downregulation of ZFPM2-AS1 expression significantly inhibited the proliferation, migration, and invasion of A549 and H460 cells, suggesting that ZFPM2-AS1 frequently played an oncogenic role. Similarly, Han et al. ( <ns0:ref type='formula'>2020</ns0:ref>) reported that ZFPM2-AS1 facilitated the proliferation, invasion, and epithelialto-mesenchymal transition in LUAD, and that UPF1 de-stabilized the ZFPM2 mRNA level negatively regulated by ZFPM2-AS1. Their observation of a negative correlation between ZFPM2-AS1 and ZFPM2 was also consistent with our findings. ZFPM2-AS1 has been reported to induce p53 destabilization stabilizing MIF, leading to the progression of gastric cancer <ns0:ref type='bibr' target='#b6'>(7)</ns0:ref>. However, the connection between ZFPM2-AS1 and the JAK/STAT signal pathway has not been explored. In our study, we found that ZFPM2-AS1 positively regulated the expression of JAK2, p-STAT3, and PD-L1 in A549 cells. JAK kinase phosphorylated STAT C-terminus Tyr705 in STAT3, initiated by the binding of IL-6 to its specific receptor and the activation of phosphorylated JAK. A different study reported that the activation of p-STAT3 enhanced cell proliferation, metastasis, and angiogenesis in multiple cancers including NSCLC <ns0:ref type='bibr' target='#b25'>(23)</ns0:ref>. PI3K/AKT, RAS/MAPK, and JAK/STAT3 are three major downstream activated EGFR phosphorylation pathways <ns0:ref type='bibr' target='#b26'>(24)</ns0:ref>. Our results revealed that ZFPM2-AS1 also positively regulated p-AKT expression, confirming the existence of crosstalk between the JAK2-STAT3 and PI3K-AKT pathways.</ns0:p><ns0:p>Previous research has shown that PD-L1 expression is involved in two main mechanisms: the innate immune escape, which is associated with multiple oncogenes, and the adaptive immune expression in the presence of IFN-&#947;, suggesting that ZFPM2-AS1 may be a potential target during PD-L1 immunotherapy. However, our study's exploration of how ZFPM2-AS1 regulates PD-L1</ns0:p><ns0:p>in NSCLC cells was limited, and this mechanism should be thoroughly studied in future investigations. ZFPM2's role as a cytokine has been shown to play a crucial role in the regulation of the immune system <ns0:ref type='bibr' target='#b34'>(30)</ns0:ref>. Our study demonstrated that ZFPM2 expression was negatively regulated by ZFPM2-AS1, indicating that ZFPM2 may also be correlated with tumor immune infiltration. The TIMER database showed that ZFPM2 expression had a negative correlation with the immune infiltrating levels of tumor purity in LUAD, which was consistent with our initial hypothesis. However, we found that ZFPM2-AS1 was downregulated in H1299 and H292 cell lines, revealing that low ZFPM2-AS1 expression may progress cancer using other signal pathways.</ns0:p><ns0:p>Further investigations are needed to determine how ZFPM2-AS1 regulates NSCLC function in these cell lines.</ns0:p></ns0:div> <ns0:div><ns0:head n='5'>| Conclusion</ns0:head><ns0:p>In this study, we found that the lncRNA ZFPM2-AS1 functioned as an oncogene by promoting the proliferation, migration, and invasion of NSCLC cells. Furthermore, we determined that ZFPM2-AS1 positively regulated PD-L1 expression via the JAK-STAT and AKT pathways in A549 cell lines. Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>. The association between ZFPM2-AS1 expression and clinical measures in LUAD patients.</ns0:p><ns0:note type='other'>Figure legends</ns0:note></ns0:div> <ns0:div><ns0:head>Additional files</ns0:head><ns0:p>Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>: Specific primers for qRT-PCR and siRNA Smart Silencer sequences.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head>Table1</ns0:head><ns0:p>The association between ZFPM2-AS1 expression and clinical measures in LUAD patients</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed The positive correlation between ZFPM2-AS1 and NSCLC cell proliferation.</ns0:p><ns0:note type='other'>Figure 2</ns0:note><ns0:note type='other'>Figure 3</ns0:note><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 4</ns0:note><ns0:note type='other'>Figure 5</ns0:note><ns0:p>Figure5</ns0:p><ns0:p>The location and effect on the ZFPM2-AS1 cell cycle.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure 6</ns0:note><ns0:note type='other'>Figure 7</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Surgical specimens were collected from 50 individual patients undergoing NSCLC surgery at the Affiliated Shengjing Hospital of China Medical University (Shenyang, China) between May 2017 and August 2018. All specimens had been pathologically diagnosed as LUAD or LUSC. The specimens were frozen at -80&#730;C directly following surgery. Our experimental protocol was authorized by the Shengjing Hospital Ethics Committee (2018PS170K), and we acquired written informed consent from each patient. PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020) Manuscript to be reviewed escape, which consists of various tumor microenvironment inflammatory factors (25-28). Wang et al. (2019) reported that the lncRNA MALAT1 regulated PD-L1 by sponging miR-195 in diffuse large B cell lymphoma, affecting PD-L1's proliferation, apoptosis, migration, and immune escape capacities. Notably, our study confirmed that ZFPM2-AS1 knockdown decreased PD-L1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Correlation between higher ZFPM2-AS1 expression and poor prognosis. (A) Scatter plot of ZFPM2-AS1 expression values in NSCLC and normal tissue samples from the RNA-Seq dataset of TCGA (y-axis represents the FPKM value, **** means p&lt;0.0001). (B) AUC value of the ROC curve based on ZFPM2-AS1 expression values. (C) The Kaplan-Meier survival curve with its corresponding log-rank test of ZFPM2-AS1.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. ZFPM2-AS1 upregulation in NSCLC samples and cell lines. The expression levels of samples and cell lines were determined using quantitative RT-PCR. All data analyses were performed using the mean values of individual tissues or the mean value &#177; SD of each cell line</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. The positive correlation between ZFPM2-AS1 and NSCLC cell proliferation. (A) qRT-PCR was used to evaluate the knockdown efficiency (24h) of ZFPM2-AS1 with the specific siRNAs and scrambled target sequences. The y-axis value represented the ratio of ZFPM2-AS1 expression in siRNA groups to that of the control group. GAPDH was used as the reference gene. (B) The MTT assay was performed so that the ZFPM2-AS1 knockdown inhibited H460 cell proliferation. The statistical data were analyzed using an unpaired Student's t-test. (C) ZFPM2-AS1 knockdown inhibited A549 cell proliferation with and without IFN-&#947;. (D) The effect of ZFPM2-AS1 overexpression on A549 cell proliferation with and without IFN-&#947;. (E-H) Colony formation assays were performed to illuminate A549 and H460 cell proliferation upon ZFPM2-AS1 knockdown. *P &lt; 0.05. **P &lt; 0.01. ***P &lt; 0.001. ****P &lt; 0.0001.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. The positive correlation between ZFPM2-AS1 and the migration and invasion of NSCLC cells. (A-D) ZFPM2-AS1 knockdown inhibited the motility of A549 and H460 cells by the wound healing assay. (E) (F) The transwell assay was performed to determine whether ZFPM2-AS1 knockdown inhibited A549 and H460 cell invasion. (G-J) In A549 cells, ZFPM2-AS1 silencing decreased the invasion and migration potential with and without IFN-&#947; (48h). (K-N) The impact of ZFPM2-AS1 overexpression on the invasion and migration ability of A549 cells with and without IFN-&#947; (48h). *P &lt; 0.05. **P &lt; 0.01. ***P &lt; 0.001.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5. The location and effect on the ZFPM2-AS1 cell cycle. (A) The ZFPM2-AS1expression levels in the A549 cell nucleus and cytoplasm fractions were found using qRT-PCR.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6. Correlations between ZFPM2 expression and immune infiltration level. (A) ZFPM2 expression levels of various human tumor types were validated using TIMER (*p&lt;0.05, **p&lt;0.01, ***p&lt;0.001). The color red signified tumor tissues, blue signified normal tissues, and purple signified metastasis tissue. (B) The correlations between ZFPM2 expression and tumor purity, B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, or dendritic cells were analyzed.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 7 .</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7. ZFPM2-AS1 positively regulated PD-L1 expression via the JAK-STAT and AKT pathways. (A, B) ZFPM2-AS1 was downregulated by three individual siRNAs. The relevant proteins were identified by Western blot during ZFPM2-AS1 knockdown (C, D) or overexpression, (E, F) with or without IFN-&#947; treatment.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>by Chi-square. Median value: 5.04. *P&lt;0.05, **P&lt;0.01. Data were analyzed by Chi-square test. The high and low groups were divided by the median expression value of ZFPM2-AS1 (5.04).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 1 Figure1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure2ZFPM2-</ns0:head><ns0:label /><ns0:figDesc>Figure2</ns0:figDesc><ns0:graphic coords='25,42.52,204.37,525.00,221.25' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure3</ns0:head><ns0:label /><ns0:figDesc>Figure3</ns0:figDesc><ns0:graphic coords='26,42.52,204.37,525.00,352.50' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure4</ns0:head><ns0:label /><ns0:figDesc>Figure4</ns0:figDesc><ns0:graphic coords='27,42.52,204.37,525.00,516.75' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Figure6</ns0:head><ns0:label /><ns0:figDesc>Figure6</ns0:figDesc><ns0:graphic coords='29,42.52,204.37,525.00,321.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure7ZFPM2-</ns0:head><ns0:label /><ns0:figDesc>Figure7</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='28,42.52,204.37,525.00,352.50' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>1 2 Table 1 .</ns0:head><ns0:label>21</ns0:label><ns0:figDesc>The association between ZFPM2-AS1 expression and clinical measures in LUAD 3 patients.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell cols='3'>Relative ZFPM2-AS1 expression</ns0:cell></ns0:row><ns0:row><ns0:cell>Characteristics</ns0:cell><ns0:cell>N</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Low</ns0:cell><ns0:cell>High</ns0:cell><ns0:cell>P value</ns0:cell></ns0:row><ns0:row><ns0:cell>Age(years)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>&gt;65</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>&#8804;65</ns0:cell><ns0:cell>39</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>0.733</ns0:cell></ns0:row><ns0:row><ns0:cell>Gender</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Male</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.258</ns0:cell></ns0:row><ns0:row><ns0:cell>Female</ns0:cell><ns0:cell>26</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>15</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Differentiation</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Well,moderate</ns0:cell><ns0:cell>38</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.999</ns0:cell></ns0:row><ns0:row><ns0:cell>Poor</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Tumor size(maximum diameter)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>&#65310;3cm</ns0:cell><ns0:cell>33</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>21</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.007 **</ns0:cell></ns0:row><ns0:row><ns0:cell>&#8804;3cm</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Histological tumor type</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Squamous cell carcinoma</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.248</ns0:cell></ns0:row><ns0:row><ns0:cell>Adenocarcinoma</ns0:cell><ns0:cell>30</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Smoking history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Smokers</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.564</ns0:cell></ns0:row><ns0:row><ns0:cell>Never smokers</ns0:cell><ns0:cell>30</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Lymph node metastasis</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Positive</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>0.777</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:48469:1:1:NEW 13 Aug 2020)</ns0:note></ns0:figure> </ns0:body> "

"Editor comments (Zekiye Altun) MAJOR REVISIONS Dear Dr. Li, Thank you for your submission to PeerJ. It is my opinion as the Academic Editor for your article - ZFPM2-AS1 promotes the proliferation, migration and invasion in human non-small cell lung cancer cells by targeting JAK/AKT/STAT pathway - that it requires a number of Major Revisions. My suggested changes and reviewer comments are shown below and on your article 'Overview' screen. Please address these changes and resubmit. Although not a hard deadline please try to submit your revision within the next 55 days. With kind regards, Zekiye Altun Academic Editor, PeerJ Reviewer 1 (Anonymous) Basic reporting The manuscript needs careful editing by English native speaker OR professional language editing service. Experimental design Most experiments perform with rigorous design. only one experiment may need more evidence. Validity of the findings The conclusion needs to be re-written. Comments for the Author Wang et. al. submitted the manuscript ” ZFPM2-AS1 promotes the proliferation, migration and invasion in human non-small cell lung cancer cells by targeting JAK/AKT/STAT pathway” The authors provide clinical evidence to show the correlation between ZFPM2-AS1 and NSCLC and use multiple methods (MTT, colony forming, wound healing, and Transwell assay and Flow cytometry,) to confirm that ZFPM2-AS1 regulates the proliferation/colony formation, migration, and invasion of lung cancer cell lines. In addition, they employed ZFPM2-AS1-siRNA and western blot to show ZFPM2-AS1 might regulate via JAK-STAT and AKT pathway and PD-L1. The data is enough to support the ZFPM2-AS1 is involved in NSCLC. The ZFPM2-AS1 might serve as a potential target of lung cancer treatment/immunotherapy in the future. However, the whole manuscript was poorly written, and results/figures are not well-organized, and it still needs more evidence to prove ZFPM2-AS1 involved in the JAK-STAT and AKT pathway. The manuscript requires substantial revision before acceptance. Here I have some suggestions and comments that may be helpful to improve the manuscript. Major point: A. Your most important issue is scientific paper writing. your manuscript needs careful editing by English native speaker OR professional language editing service. Please pay attention to sentence structure, verb tense, and clause construction. Additionally, the authors should write the paper in logistic order, especially the result section (Figure 7). Reply: Thank you very much for the suggestion. The manuscript has been edited by professional language editing service. We are sorry for the inconvenience. As you suggested, the manuscript has been re-written in logistic order, especially the Result 3.7 and 3.8 section. B. The next most important item is Figure 6. It still needs more convincing evidence to support ZFPM2-AS1 involved in JAK-STAT and AKT pathway. JAK-STAT and AKT pathway is the new and most important finding of ZFPM2-AS function in your study. Reply: Thanks very much for your enlightening suggestion. We have finished the relevant experiment (Figure7C). C. All the figures need to be carefully edited. Reply: Thank you for your reminding. We have made the relevant revisions. All details are listed below: 1. The author should use “targeting” carefully in the title. According to the results you presented, you did not figure out the real target (gene/miRNAs) of LncRNA ZFPM2-AS1. In addition, it is generally believed that JAK-STAT and AKT are two distinct signaling pathways, and the AKT pathway is not the direct upstream of STAT, although these signaling pathways can be integrated in some cases. Reply: Thanks very much for your enlightening suggestion. We have changed the title to “ZFPM2-AS1 promotes the proliferation, migration and invasion of human non-small cell lung cancer cells via the JAK-STAT and AKT pathway.” 2. Line 29. Please make sure if you use “RT-PCR” rather than “qRT-PCR” to examine the transcription level of ZFPM2-AS1. Reply: Thank you for your careful review. We used “qRT-PCR” in this section, we have made the revision. 3. Line 41, the author mentioned the “PD-1” in abstract, but there is no description concerning PD-1 in the result section. Reply: Thanks for your careful review. We have deleted “PD-1” and made the relevant revisions in this section. 4. Line 64” warranted” in here is very confused. Reply: We are sorry for the confusion. We have replaced it with “needed” 5. There are many sentences with sentence structure problems, i.e. Line 51-53, line 62-64… please addressed these issues in the whole manuscript. Reply: Yes, as you suggested, we made the revisions. 6. The introduction was not well-written, your need to make a comprehensive review on the LncRNA of your interest (ZFPM2-AS1)[there are more than 10 papers in PubMed (https://pubmed.ncbi.nlm.nih.gov/?term=ZFPM2-AS1)], and don’t pay too much attention to other unrelated lncRNAs in JAK-STAT and AKT pathway(line 71-85). And it needs some background information about IFN-γ to make your audience clear about your study. Reply: Thanks very much for your professional advice. As you suggested, we indeed should focus on ZFPM2-AS1 rather than other unrelated lncRNAs. Also, we should introduce some background information about IFN-γ. We have made the relevant revisions. 7. Line 97 “different ” Reply: Thanks very much. Yes, we have made the relevant revision. 8. Line 110 &131, ”CO2” (“2” here should be subscript) Reply: Thanks for your careful review. We have made the relevant revisions. 9. Line 125, 4x103; (“3” here should be superscript), please carefully check the same issues in otherwhere, line 135, line 143…etc. Reply: Thank you. We have made the relevant revisions. 10. Line 165, please indicated the manufacture information of “IP lysis”, check if “IP lysis” is the correct name of this reagent. Reply: Thank you for your kind reminding. We have indicated the manufacture information of “lysis buffer”. 11. line 198, “one lung normal epithelial cell line, four NSCLC cell lines, and one tool cell line ”, avoid this kind of usage in a scientific paper, please state the specific name of cell lines. Reply: Thank you very much for your professional advice. We have made the relevant revisions. 12. Line 202, “including H1299 and H292”, should be “including H1299 cells and H292 cells”, please carefully proofread the similar issues in otherwhere, line 218, line 219, line 229, line 232, line233…... Reply: Thanks for your careful review. We have made the relevant revisions. 13. Line 206, please indicate the abbreviation” TNM” information. Reply: Thank you for your kind reminding. We have indicated the abbreviation” TNM” information. 14. Line 216, please add a short description of why you use IFN-γ for your study, and there is no description in introduction and otherwhere (result and discussion), which will make the readers very confused. Reply: Thank you very much for your professional advice. As you suggested, we have added the description of IFN-γ here. Furthermore, we added the relevant description in introduction. 15. Another confusing point: The whole paper focused on the ZFPM2-AS1 rather than ZFPM2 (although ZFPM2 is a potential target of ZFPM2-AS1 lncRNA). The authors present lots of data to prove the role of ZFPM2-AS1 in NSCLC, but at the end of the results (Result-3.8), the authors tried to explain the role of ZFPM2 in tumor immune infiltration. Please explain it OR re-organize the results to make readers clear about the object of your research. Reply: Thank you for your helpful advice. Yes, as you suggested, we re-organized the Result 3.7 and 3.8 to make it clear. 16. Line 253 “Meanwhile, the expression of JAK2, p-STAT3 and p-AKT was decreased, compared with the control group. However, there was no significant differential expression in STAT3 and AKT”. Typically, phosphorylated JAK2 (pJAK2), rather than JAK2, represents “active status” in the signaling study, in my opinion, you should check the pJAK2 (the ratio of pJAK2/total JAK2). Reply: Thank you very much for your professional advice. Yes, pJAK2 level should be checked. However, the effect of p-JAK2 primary antibody in Westernblot was not satisfied (shown in Supplemental Figure2). 17. Result 3.7, The most important finding in this article is ZFPM2-AS1 involved with JAK-STAT and AKT pathway. I guess the authors try to use the IFN-γ to activate the JAK-STAT pathway (not stated in the manuscript), however, it still cannot exclude that ZFPM2-AS1 regulate NSCLC by other pathways(like p53 pathways), in my opinion, you should use JAK inhibitors to block the JAK-STAT pathway, and then check if the inhibitors can abolish (at least attenuate) the effect of ZFPM2-AS1 on proliferation/migration/invasion of lung cancer cells. You may present at least one piece of data in this section. Reply: Thanks very much for your enlightening suggestion. Yes, as you suggested, we checked if the JAK inhibitor can abolish the proliferation of ZFPM2-AS1 in Fig3C. The result showed that the difference became smaller when the inhibitor was added. However, the difference still existed (Supplemental Figure1). We will analyze this issue carefully in our future experiments. 18. Line 287-299. Please don’t overstate the JAK-STAT pathway that is well-known signaling in cancer, this paper focused on ZFPM2-AS1, you may discuss how ZFPM2-AS1 regulates JAK-STAT pathway and whether other pathways (for example, p53 pathway that you mentioned in the introduction) involved in ZFPM2-AS1 regulatory network. Reply: Yes. As you suggested, we have carefully reviewed this section and made the relevant revisions. 19. Conclusion. Usually, the conclusion just briefly summarizes your finding, which differs from the abstract and result. Reply: Thank you for your reminding. We have revised the conclusion. 20. Please provide a brief title for each figure and avoid unnecessary descriptions in the text. According to the Journal requirement, use ”Figure x” rather than all capital ” FIGURE x”. Reply: Yes, as you suggested, we revised the titles and ”Figure x”. 21. Figure 3, panel E is already in Figure 3, please remove figure 3E on Page 31. Reply: Yes, as you suggested, we removed figure 3E on Page 31. 22. Figure 4, there are 5 panels (A.B.C.D.E) in Figure 4, which located on different pages. The authors should re-organize the layout and combine all panels in one page OR divide them into two figures. Reply: Thank you for your reminding. We combined all panels in one page. 23. Figure 5. Combine all panels in one page. Figure 5B, please use “IFN-γ” instead of “γ”. Reply: Yes, as you suggested, we have revised the Figure 5. 24. Figure 6. Combine all panels in one page. Figure 6B, I cannot see a significant difference(as the author wrote, line 259-260) of pSTAT3 level in groups, please confirm. In addition, the author should add a bar graph to each protein in Figure 6. For the phosphorylated protein, a phospho/total ratio (i.e., p-STAT3/STAT3…) need to be presented. Reply: Thanks very much for your professional advice. We have added a bar graph and the ratio in Figure 6(now figure7). 25. Figure 7. Combine all panels in one page. Reply: Thank you for your reminding. We combined all panels in one page(now figure6). Reviewer 2 (Anonymous) Basic reporting a. The overall language used is acceptable however minor grammatical and typological errors need to be fixed. For example, in lines #59, #67, #81– words like mounting, frustrate and sponging are out of context and provide ambiguous meaning. I would recommend that the authors restructure these sentences to make it clear. Reply: Yes, as you suggested, we restructured these sentences to make it clear. b. It is not clearly stated that the authors consider both lung adenocarcinomas and lung squamous cell carcinomas for their work presented here. It is to be assumed based on their results. However, I would recommend adding a clear statement to their methods section to remove any ambiguity. Reply: Thank you very much for your professional advice. As you suggested, we have added a clear statement to the methods section. Experimental design a. The authors choose to focus specifically on signaling driven by phosphorylation of Akt on Ser47 vs Thr308. However studies have shown activation at these sites have different phenotypic effects and consequences in cancer cells such as https://doi.org/10.1038/bjc.2011.132 . The authors should address this by looking at Akt phosphorylation at this site via western blotting. (If possible). Reply: Thanks very much for your enlightening suggestion. The reference( https://doi.org/10.1038/bjc.2011.132) was more concerned about the function of Akt in NSCLC specimens based on the activation of p-Akt308, not 473. Our research was more concerned about the alteration of ZFPM2-AS1 affected the p-Akt / Akt signaling pathway, finding that p-Akt473 was more significant. Thanks again for your professional reminding, we will further explore the relationship between p-Akt308 and 473 in the future experiments. b. The data shown in figures 3C and 3D do not seem very convincing. There is significant inconsistency in the data presented with some experiments performed in only H460 and some only in A549. Specifically, in figure 3C and 3D, the difference in proliferation between the control and sample (either siZFPM-AS1 or overexpression of AFPKM-AS1) seems too small to be significant. The raw data provided show much variation in their values. I would recommend that the authors verify their statistical tests keeping the variation between replicated in mind. The authors should also address why only one cell line was chosen for certain experiments vs others or provide data for both to make their study more robust. Reply: 1) Thank you very much for your professional advice. According to your reminding, we re-performed MTT assay for figure 3C, and checked the data mistakes for figure 3D. We have made the relevant revisions. 2) Yes, we should address two cell lines. However, the condition of H460 cells became significantly poor after 72 hours with IFN-γ, due to some unknown reasons. c. There is a lack of explanation on the relevance of the JAK-STAT pathway and the use of IFN-gamma induction of this pathway in NSCLC specifically. The authors do try to expand on this in the discussion but some further expansion on this may be helpful. The authors can refer to reviews like 10.1080/21623996.2014.999503 and https://doi.org/10.3390/cancers6020708 to further supplement the introduction and discussion. Reply: Yes, as you suggested, we have expanded the introduction and discussion. d. In their TCGA data analysis, the authors do not mention what studies were included in their 535 lung cancer cohort. What criteria was used to be included in their study compared to normal. If this analysis was based off their previous publication that should be mentioned here. Reply: Thank you for your careful review. The Reference 6 {6. Wang X, Su R, Guo Q, Liu J, Ruan B, Wang G. Competing endogenous RNA (ceRNA) hypothetic model based on comprehensive analysis of long non-coding RNA expression in lung adenocarcinoma. PeerJ 2019, 7: e8024.} in this article was the basis for our early screening of ZFPM2-AS1. e. The analysis/ data used for the calculation of the ROC in Figure 1B is not explained. If this is part of the TCGA provided analysis it needs to be clearly stated. Furthermore, the ROC curve is depicted in an unusual manner with the AUC shaded and the random guess line is not shown. Can the authors please comment as to why they chose to depict the results in such a manner over the conventional representation? Reply: Thank you for your pertinent advice. 1) Yes, as you suggested, we clearly stated that the data used for the ROC was part of the TCGA provided analysis. 2) Yes, as your suggestion, we should use a more conventional representation. However, the ROC curve analysis was based on our previous article, using the OmicShare tools (http://www.omicshare.com/ tools). We have added the relevant statement in 2.1 Method section. f. In their RNA,qRT-PCR methods section, the authors fail to mention how the relative gene expression was calculated and which housekeeping gene was used. (Lines 120-122) Reply: Thanks very much for your professional advice. Yes, as you suggested , In 2.4 Method section, we added the relevant statement. The relative gene expression was calculated by the 2‑ΔΔCq method. GAPDH and RPS18 were used as the housekeeping genes, as shown in Supplementary Table 1. g. The authors need to mention if the colonies were counted manually or under a microscope for their colony formation assay. (Line 133) Reply: Thanks very much for your kind advice. Yes, as you suggested, we made the relevant revision in 2.6 Method section. h. Lines 147-148. This is ambiguous. Please provide information on the magnification and the specifications of the microscope. Reply: Yes. We have added the relevant information according to your kind advice. i. In figures 4D and 4E the bottom panel of the quantification of results should be H460, not A549 again. Please correct this typographical error in your figures. Reply: Thank you, both of the bottom panels referred to the numbers of migrated cells in A549 cells. j. In Figure 7A the color legend is missing to indicate what the red, blue and purple mean. Reply: Thank you for your reminding. We have made the relevant revisions. Validity of the findings None. Comments for the Author The article ZFPM2-AS1 promotes the proliferation, migration and invasion in human non-small cell lung cancer cells by targeting JAK/AKT/STAT pathway by Wang et al is a generally well-put together article aimed at elucidating the molecular mechanism of lncRNA ZFPKM-AS1 on the tumorigenic characteristics of NSCLC. I commend the authors on testing the effects of both loss and overexpression of ZFPKM-AS1 on multiple characteristics of tumor cells. I was specifically impressed by their assessment of 50 clinical samples in this context. I further appreciate the efforts of the authors in sharing the raw data for almost figure represented in the paper to aid transparency and provide confidence in their results. However, there are some concerns with the paper in its current version as detailed above. Reviewer 3 (Anonymous) Basic reporting 1. The most important issue is the English language used throughout the manuscript. I suggest the authors carefully proof-read and further improve the quality. Many sentences were grammatically incorrect. Some examples include line 60(…lncRNAs might role…), line 61 (…differential expression lncRNAs…), line 237(…in the nuclear...), etc. Some other phrases, albeit grammatically correct, were scientifically confusing. Examples include line 63 (...biological behavior of NSCLC cells...), line 86(...proliferation, migration, and invasion capacity of ZFPM2-AS1 in NSCLC cells), line 215(...the decreased efficiency...), line 261 (...distinctly inhibited...), etc. Reply: Thank you very much for the suggestion. The manuscript has been edited by professional language editing service. 2. Please define and spell out acronyms where they appeared for the first time. Some examples include ZFPM2-AS1, MIF, NC, etc. Reply: Thank you for your reminding. We have made the relevant revisions. 3. I think it would be helpful to briefly summarize/conclude at the end of each Results subsection. The last sentence of section 3.4 was a good example. Reply: Yes, as you suggested, we made the revisions. 4. Some figure labels are barely visible. Reply: Thank you for your reminding. We made them clear as possible as we could. 5. Line 283 needs reference Reply: Thank you, the reference was in Line 285. We marked it in revised manuscript. Experimental design 1. It would be helpful to explain the rationales of different analyses done in Figures 1B and 1C, either in the legends or text. Reply: Yes, thank you very much for your professional advice. As you suggested, we have added the explanation in Result 3.1. 2. Could the authors explain why they used IFN-γ in the proliferation experiments. Because this was used extensively throughout the manuscript, it might be worth mentioning in the introduction. Along the same line, could the authors comment on why some differences were only significant in the presence of IFN-γ, e.g. Figure 3C? Reply: Thanks very much for your enlightening suggestion. 1) We have added the relevant introduction about IFN-γ. 2) As IFN-γ could activate the JAK-STAT pathway, it amplified the difference in tumor cell proliferation. The relevant results were more obvious in our experiments. Validity of the findings I appreciate that this manuscript had extensive amount of results, most of which are well controlled. My biggest concern, however, is that the differential expression of the lncRNA ZFPM2-AS1 in various NSCLC samples and cell lines. In fact, as the authors reported, ZFPM2-AS1 was significantly downregulated in two out of four cell lines experimented. This should not be overlooked and should be commented on, given that the authors proposed this to be a promising prognostic marker and even a therapeutic target. Reply: Yes, thank you very much for your professional advice. In this manuscript, we mainly focused on A549 and H460 cell lines, in which lncRNA ZFPM2-AS1 was upregulated and affected JAK-STAT and AKT pathways. Besides, ZFPM2-AS1 might be downregulated in other NSCLC cell lines and affected other signal pathways, I supposed it acted as oncogene as well. Yes, as you suggested, these should not be overlooked and should be commented on. We are aware that this was a potential limitation of this study, which has been discussed in the revised manuscript. Please include quantification of the western blotting results in Figures 6A and 6B, normalized to internal controls. Reply: Thanks very much. Yes, we have made the relevant revision. Comments for the Author N/A "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Recent studies have determined that long non-coding RNAs (lncRNAs) are potential prognostic biomarkers for non-small cell lung cancers (NSCLCs). The purpose of this study was to analyze the function and associated pathways of zinc finger protein multitype 2 antisense RNA 1 (ZFPM2-AS1) in NSCLC cells. Methods: We used qRT-PCR to analyze ZFPM2-AS1's transcription level. Its proliferation, migration, and invasion capacities were determined using MTT, colony forming, wound healing, and transwell assays. We additionally analyzed the correlation between ZFPM2 and immune infiltration using the Tumor Immune Estimation Resource (TIMER) database, and the protein expression levels using Western blots. Results: We found that ZFPM2-AS1 expression in NSCLC specimens and cell lines was elevated compared to the control group. ZFPM2-AS1 is an oncogene and independent prognostic predictor of poor survival in NSCLCs, and its expression had a positive correlation with tumor size and lymph node metastasis in our clinical data. MTT, colony forming, wound healing, and transwell assays showed a positive correlation between ZFPM2-AS1 expression and the proliferation, migration, and invasion of NSCLC cells in the presence and absence of interferon-&#947; (IFN-&#947;). Using the TIMER database, we hypothesized that ZFPM2 was negatively correlated with ZFPM2-AS1 expression, as well as the immune infiltration levels in lung adenocarcinoma (LUAD).</ns0:p><ns0:p>Finally, we found that ZFPM2-AS1 negatively regulated ZFPM2 expression, and had a positive correlation with PD-L1 expression through the JAK-STAT and AKT pathways.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion:</ns0:head><ns0:p>Our study confirmed that ZFPM2-AS1 promotes the proliferation, migration, and invasion of NSCLC cells via the JAK-STAT and AKT pathways. Further research on the ZFPM2-AS1 pathway regulation mechanism is needed.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Lung cancer is the most deadly malignant tumor, accounting for more than 80% of non-small cell lung cancers (NSCLCs) worldwide, most of which are lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Multiple therapies have improved the prognosis of NSCLCs,</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed but the 5-year survival rate has remained lower than 20% <ns0:ref type='bibr' target='#b0'>(1)</ns0:ref>. Therefore, it is crucial to explore novel diagnostic biomarkers and therapeutic approaches <ns0:ref type='bibr' target='#b1'>(2,</ns0:ref><ns0:ref type='bibr' target='#b2'>3)</ns0:ref>. Long non-coding RNAs (lncRNAs), defined as non-coding transcripts longer than 200 nucleotides, are associated with the initiation, progression, and prognosis of various tumors <ns0:ref type='bibr' target='#b3'>(4,</ns0:ref><ns0:ref type='bibr' target='#b4'>5)</ns0:ref>.</ns0:p><ns0:p>Mounting dysregulated lncRNAs may also play a role as tumor suppressors or oncogenes in multiple tumors, including NSCLCs. We previously screened differential expression lncRNAs in NSCLCs using The Cancer Genome Atlas (TCGA) database <ns0:ref type='bibr' target='#b5'>(6)</ns0:ref>. We speculated that one of the most distinct lncRNAs, zinc finger protein multitype 2 antisense RNA 1 (ZFPM2-AS1), may play an important role in the biological behavior of NSCLC cells. In this study, we concentrated on the functions of ZFPM2-AS1. ZFPM2-AS1 reportedly induces p53 destabilization by stabilizing macrophage migration inhibitory factor (MIF), leading to the progression of gastric cancer <ns0:ref type='bibr' target='#b6'>(7)</ns0:ref>. ZFPM2-AS1 has also been shown to promote metastasis and proliferation, as well as inhibit renal cell cancer apoptosis by targeting miR-137 <ns0:ref type='bibr' target='#b8'>(8)</ns0:ref>. Additionally, ZFPM2-AS1 can promote NSCLC progression via the miR-511-3p/AFF4 and miR-18b-5p/VMA21 pathways <ns0:ref type='bibr' target='#b9'>(9,</ns0:ref><ns0:ref type='bibr' target='#b11'>10)</ns0:ref>, and enhance the malignancy of cervical cancer by sponging microRNA-511-3p <ns0:ref type='bibr' target='#b12'>(11)</ns0:ref>. By upregulating TRAF4, ZFPM2-AS1 facilitates cell proliferation in both esophageal squamous cell carcinoma and small cell lung cancer <ns0:ref type='bibr' target='#b13'>(12,</ns0:ref><ns0:ref type='bibr' target='#b14'>13)</ns0:ref>.</ns0:p><ns0:p>However, ZFPM2-AS1's molecular regulatory network in NSCLC cells remains unclear. The PI3K/AKT and JAK/STAT signaling pathways promote cell proliferation and motility by activating key metastasis-promoting genes <ns0:ref type='bibr' target='#b16'>(14)</ns0:ref>. STAT activation is restricted in normal cells.</ns0:p><ns0:p>However, once STAT is activated, numerous genes that control tumor cell proliferation, angiogenesis, and evasion of immune surveillance are uncontrollably expressed <ns0:ref type='bibr' target='#b17'>(15)</ns0:ref>. Interferon-&#947; (IFN-&#947;) is crucial for immunity against intracellular pathogens and tumor cells <ns0:ref type='bibr' target='#b18'>(16)</ns0:ref>. Since IFN-&#947; has the ability to induce PD-L1, IFN-&#947; expression in cancer cells may weaken the immunity of specific tumor cells <ns0:ref type='bibr' target='#b19'>(17)</ns0:ref>. Additionally, it has been found that PD-L1 expression is positively correlated with JAK2 in NSCLCs via the JAK-STAT axis <ns0:ref type='bibr' target='#b21'>(18)</ns0:ref>. However, it has not been proved whether ZFPM2-AS1 can regulate PD-L1 via the JAK-STAT and AKT pathways.</ns0:p><ns0:p>In this study, we investigated ZFPM2-AS1's proliferation, migration, and invasion abilities in NSCLC cells. We also determined the regulatory roles of ZFPM2-AS1 in the JAK-STAT and AKT pathways.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and methods</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>| TCGA and Tumor Immune Estimation Resource (TIMER) databases</ns0:head><ns0:p>We used ZFPM2-AS1 transcript expression levels extracted from TCGA's database for our tumor types from TCGA <ns0:ref type='bibr' target='#b23'>(19)</ns0:ref>, along with specific genes' tumor immune infiltration levels. We analyzed ZFPM2 expression across multiple tumor types using the different expression module, and identified the association between ZFPM2 expression and immune infiltration level using the gene module.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>| Patients and samples</ns0:head><ns0:p>Surgical specimens were collected from 50 individual patients undergoing NSCLC surgery at the Affiliated Shengjing Hospital of China Medical University (Shenyang, China) between May 2017 and August 2018. All specimens had been pathologically diagnosed as LUAD or LUSC. The specimens were frozen at -80&#730;C directly following surgery. Our experimental protocol was authorized by the Shengjing Hospital Ethics Committee (2018PS170K), and we acquired written informed consent from each patient.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>| Cell culture, reagent, and transfection</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The human NSCLC cell lines (A549 and H460) were purchased from the Shanghai Institutes of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, China. The A549 and H460 cell lines had been cultured in RPMI-1640 with 10% fetal bovine serum (Clark Biosciences, Richmond, VA, USA), 100 U/ml penicillin, and 100 ug/ml streptomycin (Sigma-Aldrich, St.</ns0:p><ns0:p>Louis, MO, USA) in a 5% CO 2 incubator at 37&#176;C. During IFN-&#947; stimulation, cells were incubated with 100 ng/ml of recombinant human IFN-&#947; (Peprotech, Cranbury, NJ, USA) for 48 hrs. We used Lipo3000 (Invitrogen, Carlsbad, CA, USA) according to our transfection protocol. We used 20 uM of lncRNA Smart Silencer (RiboBio, Guangzhou, China) and a mixture of three siRNAs and three antisense oligonucleotides. The sequences are provided in Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>. ZFPM2-AS1 overexpression plasmid was provided by GenePharma (Shanghai, China).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>| RNA isolation, cDNA synthesis, and quantitative real-time RT-PCR</ns0:head><ns0:p>We extracted total RNA using TRIzol reagent, and performed reverse-transcription using HisScript&#8482; QRT SuperMix (Vazyme Biotech Co., Ltd., Nanjing, China). We used qRT-PCR and ChamQ&#8482; Universal SYBR qPCR Master Mix (Vazyme Biotech Co., Ltd.) to analyze the relative expression of the control group. The specific primers are shown in Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>. GAPDH and RPS18</ns0:p><ns0:p>were used as housekeeping genes. The relative gene expression was calculated using the 2 -&#916;&#916;Cq method.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>| MTT assay</ns0:head><ns0:p>Cell viability was determined using MTT reagent (Sigma-Aldrich) with a concentration of 0.5 mg/mL for 4 h. We seeded 4&#215;10 3 cells per well in 96-well plates for 0, 1, 2, 3, 4, and 5 days.</ns0:p><ns0:p>The supernatant was abandoned, and we precipitated formazan with DMSO. Finally, we analyzed the absorbance at 450 nm using a microplate reader (Thermo Fisher Scientific, Waltham, MA, USA).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>| Colony formation assay</ns0:head><ns0:p>We cultured about 3,000 terminated trypsinized cells in 6-cm dishes three times at 37 &#176;C in 5% CO 2 . Two weeks later, the cell colonies were fixed with 10% methanol for 30 s, and then Manuscript to be reviewed stained with 0.1% crystal violet (Sigma-Aldrich) for 15 min. Finally, the visible colonies were counted using a microscope.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>| Wound healing assay</ns0:head><ns0:p>A549 and H460 cells were seeded into 5&#215;10 5 cells/well in six-well plates three times. A 200 &#956;L pipette tip was used to make a scratch where the confluence reached 90%. The cells were then incubated at 37&#176;C in 5% CO 2 for 24 h. We studied the migration distances using an FSX100</ns0:p><ns0:p>Biological Image system (Olympus, Tokyo, Japan).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.8'>| Transwell migration and invasion assay</ns0:head><ns0:p>Migration and invasion assays were placed in 24-well Transwell chambers that had 8 &#956;m size pores (Costar, Washington, D.C., USA). In the invasion assay, the pores were covered with 100 &#956;L of Matrigel (BD Biosciences, San Jose, CA, USA). After trypsinization, we placed 100 &#956;L of medium (5&#215;10 4 cells) supplemented with 2% fetal bovine serum in the upper Transwell chamber, and 600 &#956;L of medium supplemented with 10% fetal bovine serum in the lower chamber. After 24 h of incubation, the upper cells were removed, and the lower ones were fixed with paraformaldehyde and stained with hematoxylin. The number of migrated/invaded cells was analyzed using 10 randomly selected fields at &#215;200 magnification under phase contrast microscopy (Olympus). All assays were performed independently at least three times.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.9'>| Nuclear-cytoplasmic localization</ns0:head><ns0:p>We harvested and washed the A549 cells before adding 500 &#181;l of cell disruption buffer (PARIS kit; cat. no. AM1921; Invitrogen/Thermo Fisher Scientific) to the cells on ice for 10 min.</ns0:p><ns0:p>Following centrifugation at 500 x g, the supernatants were preserved as cytoplasmic RNA. They were washed, an equal volume of nuclear lysate buffer was added, and they were centrifuged at 500 x g. Finally, the supernatants were collected as nuclear RNA and we performed qRT-PCR using the primers listed in Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.10'>| Flow cytometry</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>For cell cycle analysis, we harvested the transfected cells, washed them with PBS, resuspended them in 0.9 ml of PBS, and gradually added ice-cold ethanol up to a volume of 3 ml.</ns0:p><ns0:p>After 24 hours of fixation, the cells were incubated with 0.1% Triton X-100, 0.2 mg/ml RNase A, and 25 &#956;g/ml propidium iodide (PI) for 30 minutes at room temperature. We used flow cytometry to assay the DNA content (Becton Dickinson, Bedford, MA, USA), and ModFit software (Verify Software) to quantify the percentage of cells within the S-, G0/G1-, and G2/M-phases of the cell cycle.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.11'>| Western blot analysis</ns0:head><ns0:p>After harvesting the proteins using a lysis buffer (50 mM of Tris (pH 7.4), 1% Triton X-100, 0.5% Nonidet P-40, 150 mM NaCl, and protease inhibitor), we separated them using 10% sodium dodecyl sulfate (SDS) polyacrylamide gel electrophoresis. The proteins were then transferred to polyvinylidene difluoride (PVDF) membranes (Millipore, Burlington, MA, USA) for 2 h at 220 mA. The membranes were blocked in 5% BSA with TBST for 1 h at room temperature, and were incubated overnight using primary antibodies at 4&#176;C. We incubated the secondary antibody with horseradish peroxidase (HRP) conjugates for 1 h at room temperature. We identified the bands using a chemiluminescence detection kit (Tanon, Shanghai, China). We found that the primary antibodies included PDL1 (E1L3N), JAK2 (D2E12), phospho-STAT3 (Tyr705; D3A7), STAT3 (79D7), phospho-AKT (Ser473; D9E), AKT (40D4; all purchased from Cell Signaling Technology, Boston, MA, USA), and ZFPM2 (OriGene).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.12'>| Statistical analysis</ns0:head><ns0:p>The log-rank test was performed using the Kaplan-Meier survival analysis procedure <ns0:ref type='bibr' target='#b18'>(16)</ns0:ref>.</ns0:p><ns0:p>We conducted statistical analyses with GraphPad Prism7 (GraphPad Software, Inc., San Diego, CA, USA). Test data were manifested as means &#177; standard deviation (SD). We used the student's t-test (two-tailed) to find the differences between two groups, and one-way ANOVA to find the differences across more than two groups, followed by Dunnett's post-test. P&lt;0.05 was considered statistically significant.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>| Increased ZFPM2-AS1 related to poor survival in in NSCLC patients</ns0:head><ns0:p>During our investigation, we used ZFPM2-AS1 RNA-seq data from TCGA to analyze the differential expressions across 59 normal lung tissues and 535 LUADs or LUSCs. We found a significant increase of ZFPM2-AS1 in NSCLCs compared to normal lung tissues (Fig. <ns0:ref type='figure' target='#fig_14'>1A</ns0:ref>).</ns0:p><ns0:p>Furthermore, when analyzing the ROC curve based on the screened TCGA data, we found that ZFPM2-AS1's AUC value was 0.891 (Fig. <ns0:ref type='figure' target='#fig_14'>1B</ns0:ref>), indicating that ZFPM2-AS1 may be a novel diagnostic biomarker. Generated using screened data from TCGA, the Kaplan-Meier survival curve showed that higher ZFPM2-AS1 expression levels were significantly associated with poor prognoses for NSCLC patients (Fig. <ns0:ref type='figure' target='#fig_14'>1C</ns0:ref>). Ultimately, our results suggested that ZFPM2-AS1 is a possible oncogene in NSCLCs.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>| Validating ZFPM2-AS1 expression patterns in NSCLC samples and cell lines</ns0:head><ns0:p>To further verify the ZFPM2-AS1 expression patterns that we found in TCGA's RNA-Seq databases, we used qRT-PCR to validate 50 pairs of collected NSCLC and adjacent normal samples. We found that the relative transcription expression levels were significantly higher in NSCLC tissue compared to the adjacent normal tissues (Fig. <ns0:ref type='figure' target='#fig_6'>2A</ns0:ref>; P&lt;0.0001). We also validated BEAS-2B, A549, NCI-H460, H1299, H292, and HEK293 cells by performing qRT-PCR, and found that ZFPM2-AS1 was expressed in all of these cell lines. Compared to the BEAS-2B cell expression levels, ZFPM2-AS1 was significantly upregulated in the A549 and H460 cells. The expression levels were significantly downregulated in the NSCLC cell lines H1299 and H292 (Fig. <ns0:ref type='figure' target='#fig_6'>2B</ns0:ref>). These results implied that ZFPM2-AS1's function in A549 and H460 cells may be similar to its functions in NSCLC samples.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>| The association between ZFPM2-AS1 and NSCLC clinical characteristics</ns0:head><ns0:p>When examining the possible association between ZFPM2-AS1 expression levels and the clinical parameters of 50 NSCLC patients, we found that tumor size was significantly positively Manuscript to be reviewed correlated with ZFPM2-AS1 expression (p=0.007). The tumor-node-metastasis (TNM) stage was also positively correlated with ZFPM2-AS1 expression (p=0.047). However, ZFPM2-AS1 expression did not have a significant correlation with other clinical characteristics, including age, gender, tumor differentiation, smoking history, and lymph node metastasis (Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>). Our results</ns0:p><ns0:p>showed that ZFPM2-AS1 expression was positively correlated to tumor size and TNM stage.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.4'>| ZFPM2-AS1 knockdown decreases proliferation and colony formation in NSCLC cell lines</ns0:head><ns0:p>Since ZFPM2-AS1 was highly expressed in A549 cells, we used siRNA-mediated ZFPM2-AS1 knockdown in A549 cells to analyze ZFPM2-AS1's biological functions. To minimize the off-target effects on lncRNA, we used specific Smart Silencers, including three individual siRNAs and three individual antisense oligonucleotides. The decreased efficiency was confirmed by qRT-PCR (Fig. <ns0:ref type='figure' target='#fig_7'>3A</ns0:ref>). Subsequently, we used an MTT assay to show any cell proliferation caused by ZFPM2-AS1 silencing or overexpression. We also stimulated ZFPM2-AS1 using IFN-&#947; because of its ability to induce PD-L1 and promote the immune escape of tumor cells. The results showed that the proliferation rate of ZFPM2-AS1 silencing in the H460 cells was aberrantly lower than in the control group after 72-120 hours (Fig. <ns0:ref type='figure' target='#fig_7'>3B</ns0:ref>). In the A549 cells, the proliferation rate was significantly lower when silencing ZFPM2-AS1 after 72 hours without IFN-&#947;, and after 96-120 hours with IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_7'>3C</ns0:ref>). We obtained similar results when performing colony forming assays, confirming that ZFPM2-AS1 knockdown distinctly inhibited colony forming in both A549 and H460 cells (Fig. <ns0:ref type='figure' target='#fig_7'>3D-G</ns0:ref>). Meanwhile, ZFPM2-AS1 overexpression significantly promoted A549 cell proliferation after 96-120 hours without IFN-&#947;, and after 72-120 hours with IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_7'>3H</ns0:ref>).</ns0:p><ns0:p>These results suggest that ZFPM2-AS1's role as an oncogene involves promoting NSCLC cell line proliferation.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.5'>| ZFPM2-AS1 promotes the migration and invasion of NSCLC cell lines</ns0:head><ns0:p>The results of the wound healing assay indicated that ZFPM2-AS1 knockdown significantly inhibited A549 and H460 cell motility when compared to the control group (Fig. <ns0:ref type='figure' target='#fig_8'>4A-D</ns0:ref>). We used the Transwell assay to investigate whether migration and invasion were also affected by ZFPM2- Manuscript to be reviewed AS1 in NSCLC cells. We found that the siRNA-mediated ZFPM2-AS1 knockdown significantly inhibited the invasion capacities of both A549 and H460 cells (Fig. <ns0:ref type='figure' target='#fig_8'>4E, F</ns0:ref>). The silencing of ZFPM2-AS1 distinctly impeded the invasion and migration capabilities of A549 cells, in both the presence and absence of IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_8'>4G-J</ns0:ref>). Meanwhile, ZFPM2-AS1 overexpression significantly promoted invasion and migration in the presence or absence of IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_8'>4K-N</ns0:ref>). Ultimately, we determined that ZFPM2-AS1 promoted migration and invasion in both A549 and H460 cells.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.6'>| ZFPM2-AS1's primary expression in the nucleus did not affect the A549 cell cycle</ns0:head><ns0:p>To clarify its cellular localization, we used qRT-PCR to determine ZFPM2-AS1 expression in both the nuclear and cytoplasmic fractions of A549 cells. We used GAPDH expression for the cytoplasmic indicator, and U1 snRNA enrichment for the nuclear indicator. The results showed that ZFPM2-AS1 was primarily expressed in the nucleus (Fig. <ns0:ref type='figure' target='#fig_9'>5A</ns0:ref>), indicating that ZFPM2-AS1 may also regulate the functions of NSCLC cells in the nucleus. We used a flow cytometric analysis to determine whether ZFPM2-AS1 silencing or overexpression had an impact on the cell cycle, with and without IFN-&#947;. The results showed that IFN-&#947; arrested A549 cells at the G0/G1 phase.</ns0:p><ns0:p>However, ZFPM2-AS1 silencing and overexpression did not significantly affect the A549 cell cycle (Fig. <ns0:ref type='figure' target='#fig_9'>5B-I</ns0:ref>). Our results confirmed that ZFPM2-AS1 was primarily expressed in the nucleus, but its effect on the proliferation, migration, and invasion of A549 cells was not dependent on the cell cycle.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.7'>| The association between ZFPM2, a potential target for ZFPM2-AS1, and LUAD tumor immune infiltration level</ns0:head><ns0:p>To determine whether ZFPM2-AS1 was associated with tumor immune infiltration level, we mined data from the TIMER database. Since ZFPM2 is a potential target for ZFPM2-AS1, we found that ZFPM2 expression was significantly lower in most human tumors compared to the adjacent normal tissues, including LUAD and LUSC (Figure <ns0:ref type='figure' target='#fig_10'>6A</ns0:ref>). ZFPM2-AS1 expression was significantly higher in NSCLC tissues compared to normal lung tissues (Fig. <ns0:ref type='figure' target='#fig_14'>1A</ns0:ref>), suggesting a possible negative correlation between ZFPM2-AS1 and ZFPM2. We also found a negative Manuscript to be reviewed correlation between ZFPM2 expression and the immune infiltrate levels of tumor purity (R=-0.352, P=8.14e -16 ) in LUAD (Figure <ns0:ref type='figure' target='#fig_10'>6B</ns0:ref>). These results implied that ZFPM2 expression was significantly lower in LUAD and LUSC, as well as negatively correlated with tumor immune infiltration levels. We wanted to further verify the positive correlation between ZFPM2-AS1 and the immune infiltrating marker PD-L1 using Western blot.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.8'>| ZFPM2-AS1's negative regulation of ZFPM2 expression and positive regulation of PD-L1</ns0:head><ns0:p>expression via the JAK-STAT and AKT pathways First, we silenced ZFPM2-AS1 expression using three individual siRNAs in the A549 cells.</ns0:p><ns0:p>The results showed a significant increase in ZFPM2 expression, indicating that ZFPM2-AS1 may negatively regulate ZFPM2 expression. Meanwhile, JAK2, p-STAT3, and p-AKT expression decreased in comparison to the control group. However, there was no significant differential STAT3 and AKT expression (Fig. <ns0:ref type='figure' target='#fig_11'>7A, B</ns0:ref>). We used siRNA to induce more significant ZFPM2 differences in the following experiment. We performed ZFPM2-AS1 silencing, both with and without IFN-&#947; exposure, to identify the differences between the JAK-STAT and AKT pathways.</ns0:p><ns0:p>We found that in both the presence and absence of IFN-&#947;, ZFPM2-AS1 knockdown significantly upregulated ZFPM2 expression and downregulated JAK2, p-STAT3, and p-AKT expression. PD-L1 expression was distinctly inhibited when ZFPM2-AS1 was silenced by IFN-&#947; stimulation (Fig. <ns0:ref type='figure' target='#fig_11'>7C, D</ns0:ref>). Furthermore, ZFPM2-AS1 overexpression downregulated ZFPM2 expression and upregulated JAK2, p-STAT3, p-AKT, and PD-L1 expression in the presence or absence of IFN-&#947; (Fig. <ns0:ref type='figure' target='#fig_11'>7E, F</ns0:ref>). Ultimately, we determined that ZFPM2-AS1 negatively regulated ZFPM2 expression and positively regulated PD-L1 expression through the JAK-STAT and AKT pathways.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Recent studies have shown that lncRNAs can operate as biomarkers in the diagnosis, therapy, and prognosis of various malignant tumors <ns0:ref type='bibr' target='#b24'>(20,</ns0:ref><ns0:ref type='bibr' target='#b25'>21)</ns0:ref>. Our results indicated that ZFPM2-AS1 was upregulated in NSCLC specimens and cell lines when compared to the control groups.</ns0:p><ns0:p>Additionally, we found a correlation between ZFPM2-AS1 and poor survival in TCGA. When looking at clinical statistics, we found that higher ZFPM2-AS1 expression levels were positively correlated with larger tumor sizes and later TNM stages. These findings suggest that ZFPM2-AS1 may be a potential novel biomarker for NSCLC. Our study also verified that the downregulation of ZFPM2-AS1 expression significantly inhibited the proliferation, migration, and invasion of A549 and H460 cells, suggesting that ZFPM2-AS1 frequently played an oncogenic role. Similarly, Han et al. ( <ns0:ref type='formula'>2020</ns0:ref>) reported that ZFPM2-AS1 facilitated the proliferation, invasion, and epithelialto-mesenchymal transition in LUAD, and that UPF1 de-stabilized the ZFPM2 mRNA level negatively regulated by ZFPM2-AS1. Their observation of a negative correlation between ZFPM2-AS1 and ZFPM2 was also consistent with our findings. ZFPM2-AS1 has been reported to induce p53 destabilization stabilizing MIF, leading to the progression of gastric cancer <ns0:ref type='bibr' target='#b6'>(7)</ns0:ref>. However, the connection between ZFPM2-AS1 and the JAK/STAT signal pathway has not been explored. In our study, we found that ZFPM2-AS1 positively regulated the expression of JAK2, p-STAT3, and PD-L1 in A549 cells. JAK kinase phosphorylated STAT C-terminus Tyr705 in STAT3, initiated by the binding of IL-6 to its specific receptor and the activation of phosphorylated JAK. A different study reported that the activation of p-STAT3 enhanced cell proliferation, metastasis, and angiogenesis in multiple cancers including NSCLC <ns0:ref type='bibr' target='#b27'>(23)</ns0:ref>. PI3K/AKT, RAS/MAPK, and JAK/STAT3 are three major downstream activated EGFR phosphorylation pathways <ns0:ref type='bibr' target='#b28'>(24)</ns0:ref>. Our results revealed that ZFPM2-AS1 also positively regulated p-AKT expression, confirming the existence of crosstalk between the JAK2- Manuscript to be reviewed capacities. Notably, our study confirmed that ZFPM2-AS1 knockdown decreased PD-L1 expression in the presence of IFN-&#947;, suggesting that ZFPM2-AS1 may be a potential target during PD-L1 immunotherapy. However, our study's exploration of how ZFPM2-AS1 regulates PD-L1</ns0:p><ns0:p>in NSCLC cells was limited, and this mechanism should be thoroughly studied in future investigations. ZFPM2's role as a cytokine has been shown to play a crucial role in the regulation of the immune system <ns0:ref type='bibr' target='#b36'>(30)</ns0:ref>. Our study demonstrated that ZFPM2 expression was negatively regulated by ZFPM2-AS1, indicating that ZFPM2 may also be correlated with tumor immune infiltration. The TIMER database showed that ZFPM2 expression had a negative correlation with the immune infiltrating levels of tumor purity in LUAD, which was consistent with our initial hypothesis. However, we found that ZFPM2-AS1 was downregulated in H1299 and H292 cell lines, revealing that low ZFPM2-AS1 expression may progress cancer using other signal pathways.</ns0:p><ns0:p>Further investigations are needed to determine how ZFPM2-AS1 regulates NSCLC function in these cell lines.</ns0:p></ns0:div> <ns0:div><ns0:head n='5'>| Conclusion</ns0:head><ns0:p>In this study, we found that the lncRNA ZFPM2-AS1 functioned as an oncogene by promoting the proliferation, migration, and invasion of NSCLC cells. Furthermore, we determined that ZFPM2-AS1 positively regulated PD-L1 expression via the JAK-STAT and AKT pathways in A549 cell lines. Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>. The association between ZFPM2-AS1 expression and clinical measures in LUAD patients.</ns0:p><ns0:note type='other'>Figure legends</ns0:note></ns0:div> <ns0:div><ns0:head>Additional files</ns0:head><ns0:p>Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>: Specific primers for qRT-PCR and siRNA Smart Silencer sequences.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head>Table1</ns0:head><ns0:p>The association between ZFPM2-AS1 expression and clinical measures in LUAD patients Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure 2</ns0:note><ns0:note type='other'>Figure 3</ns0:note><ns0:note type='other'>Figure 4</ns0:note><ns0:note type='other'>Figure 5</ns0:note><ns0:note type='other'>Figure 6</ns0:note><ns0:note type='other'>Figure 7</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>STAT3 and PI3K-AKT pathways. Previous research has shown that PD-L1 expression is involved in two main mechanisms: the innate immune escape, which is associated with multiple oncogenes, and the adaptive immune escape, which consists of various tumor microenvironment inflammatory factors (25-28). Wang et al. (2019) reported that the lncRNA MALAT1 regulated PD-L1 by sponging miR-195 in diffuse large B cell lymphoma, affecting PD-L1's proliferation, apoptosis, migration, and immune escape PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Correlation between higher ZFPM2-AS1 expression and poor prognosis. (A) Scatter plot of ZFPM2-AS1 expression values in NSCLC and normal tissue samples from the RNA-Seq dataset of TCGA (y-axis represents the FPKM value, **** means p&lt;0.0001). (B) AUC value of the ROC curve based on ZFPM2-AS1 expression values. (C) The Kaplan-Meier survival curve with its corresponding log-rank test of ZFPM2-AS1.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. ZFPM2-AS1 upregulation in NSCLC samples and cell lines. The expression levels of samples and cell lines were determined using quantitative RT-PCR. All data analyses were performed using the mean values of individual tissues or the mean value &#177; SD of each cell line from three independent experiments. (A) Differential ZFPM2-AS1 expression across 50 NSCLC pairs and adjacent normal tissues. An unpaired Student's t-test was used to find this statistical result. (B) Differential ZFPM2-AS1 expression in individual cell lines. The statistical result was found using ANOVA (parametric) test. * P&lt;0.05, ** P&lt;0.01, *** P&lt;0.001, **** P&lt;0.0001.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. The positive correlation between ZFPM2-AS1 and NSCLC cell proliferation. (A) qRT-PCR was used to evaluate the knockdown efficiency (24h) of ZFPM2-AS1 with the specific siRNAs and scrambled target sequences. The y-axis value represented the ratio of ZFPM2-AS1 expression in siRNA groups to that of the control group. GAPDH was used as the reference gene. (B) The MTT assay was performed so that the ZFPM2-AS1 knockdown inhibited H460 cell proliferation. The statistical data were analyzed using an unpaired Student's t-test. (C) ZFPM2-AS1 knockdown inhibited A549 cell proliferation with and without IFN-&#947;. (D-G) Colony formation assays were performed to illuminate A549 and H460 cell proliferation upon ZFPM2-AS1 knockdown. (H) The effect of ZFPM2-AS1 overexpression on A549 cell proliferation with and without IFN-&#947;. *P &lt; 0.05. **P &lt; 0.01. ***P &lt; 0.001. ****P &lt; 0.0001.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. The positive correlation between ZFPM2-AS1 and the migration and invasion of NSCLC cells. (A-D) ZFPM2-AS1 knockdown inhibited the motility of A549 and H460 cells by the wound healing assay. (E) (F) The transwell assay was performed to determine whether ZFPM2-AS1 knockdown inhibited A549 and H460 cell invasion. (G-J) In A549 cells, ZFPM2-AS1 silencing decreased the invasion and migration potential with and without IFN-&#947; (48h). (K-N) The impact of ZFPM2-AS1 overexpression on the invasion and migration ability of A549 cells with and without IFN-&#947; (48h). *P &lt; 0.05. **P &lt; 0.01. ***P &lt; 0.001.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5. The location and effect on the ZFPM2-AS1 cell cycle. (A) The ZFPM2-AS1 expression levels in the A549 cell nucleus and cytoplasm fractions were found using qRT-PCR. The statistical Chi-square test was performed with three independent experiments. (B-I) We analyzed the flow cytometric of the cell cycle 24 hrs after ZFPM2-AS1 knockdown or overexpression in the presence or absence of IFN-&#947;.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6. Correlations between ZFPM2 expression and immune infiltration level. (A) ZFPM2 expression levels of various human tumor types were validated using TIMER (*p&lt;0.05, **p&lt;0.01, ***p&lt;0.001). The color red signified tumor tissues, blue signified normal tissues, and purple signified metastasis tissue. (B) The correlations between ZFPM2 expression and tumor purity, B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, or dendritic cells were analyzed.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 7 .</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7. ZFPM2-AS1 positively regulated PD-L1 expression via the JAK-STAT and AKT pathways. (A, B) ZFPM2-AS1 was downregulated by three individual siRNAs. The relevant proteins were identified by Western blot during ZFPM2-AS1 knockdown (C, D) or overexpression, (E, F) with or without IFN-&#947; treatment.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head /><ns0:label /><ns0:figDesc>by Chi-square. Median value: 5.04. *P&lt;0.05, **P&lt;0.01. Data were analyzed by Chi-square test. The high and low groups were divided by the median expression value of ZFPM2-AS1 (5.04).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Figure 1 Figure1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure2ZFPM2-</ns0:head><ns0:label /><ns0:figDesc>Figure2</ns0:figDesc><ns0:graphic coords='25,42.52,204.37,525.00,221.25' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head>Figure3</ns0:head><ns0:label /><ns0:figDesc>Figure3</ns0:figDesc><ns0:graphic coords='26,42.52,204.37,525.00,352.50' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_17'><ns0:head>Figure4</ns0:head><ns0:label /><ns0:figDesc>Figure4</ns0:figDesc><ns0:graphic coords='27,42.52,204.37,525.00,516.75' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_18'><ns0:head>Figure5</ns0:head><ns0:label /><ns0:figDesc>Figure5</ns0:figDesc><ns0:graphic coords='28,42.52,204.37,525.00,352.50' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_19'><ns0:head>Figure6</ns0:head><ns0:label /><ns0:figDesc>Figure6</ns0:figDesc><ns0:graphic coords='29,42.52,204.37,525.00,321.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_20'><ns0:head>Figure7ZFPM2-</ns0:head><ns0:label /><ns0:figDesc>Figure7</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>1 2 Table 1 .</ns0:head><ns0:label>21</ns0:label><ns0:figDesc>The association between ZFPM2-AS1 expression and clinical measures in LUAD 3 patients.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell cols='3'>Relative ZFPM2-AS1 expression</ns0:cell></ns0:row><ns0:row><ns0:cell>Characteristics</ns0:cell><ns0:cell>N</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Low</ns0:cell><ns0:cell>High</ns0:cell><ns0:cell>P value</ns0:cell></ns0:row><ns0:row><ns0:cell>Age(years)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>&gt;65</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>&#8804;65</ns0:cell><ns0:cell>39</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>0.733</ns0:cell></ns0:row><ns0:row><ns0:cell>Gender</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Male</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.258</ns0:cell></ns0:row><ns0:row><ns0:cell>Female</ns0:cell><ns0:cell>26</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>15</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Differentiation</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Well,moderate</ns0:cell><ns0:cell>38</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.999</ns0:cell></ns0:row><ns0:row><ns0:cell>Poor</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Tumor size(maximum diameter)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>&#65310;3cm</ns0:cell><ns0:cell>33</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>21</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.007 **</ns0:cell></ns0:row><ns0:row><ns0:cell>&#8804;3cm</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Histological tumor type</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Squamous cell carcinoma</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.248</ns0:cell></ns0:row><ns0:row><ns0:cell>Adenocarcinoma</ns0:cell><ns0:cell>30</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Smoking history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Smokers</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.564</ns0:cell></ns0:row><ns0:row><ns0:cell>Never smokers</ns0:cell><ns0:cell>30</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Lymph node metastasis</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Positive</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>0.777</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:48469:2:0:NEW 12 Sep 2020)</ns0:note></ns0:figure> </ns0:body> "

"Editor comments (Zekiye Altun) MINOR REVISIONS Thank you for your revision in your manuscript. However, some corrections still need to be made in your revised article. Reviewer 1 (Anonymous) Basic reporting no comment Experimental design no comment Validity of the findings no comment Comments for the Author The authors submitted the revised manuscript ” ZFPM2-AS1 promotes the proliferation, migration, and invasion of human non-small cell lung cancer cells via the JAK-STAT and AKT pathways”. Thank you for a point-to-point response to my comments, the current manuscript had a great improvement in language and data presentation, which makes readers clearer about the object of the research. Here, I have several concerns that need to be addressed. 1. the authors presented excellent data to prove the ZFPM2-AS1 regulates proliferation, migration, and invasion of NSCLC cell lines and correlate with NSCLC clinical characteristics. Additionally, the readers can also make a clear conclusion from your data: (1) ZFPM2-AS1 enhance the IFN-gamma effect on proliferation/ migration/ invasion of NSCLC cells (2) ZFPM2-AS1 negatively regulate ZFPM2 (3) ZFPM2-AS1 positively regulate PD-L1 (4) ZFPM2-AS1 activates JAK-STAT3 and AKT pathway. However, the current data is not enough to prove ZFPM2-AS1 regulates its downstream effector (ZFPM2, PD-L1) through JAK-STAT3 and AKT pathway. It is a good thing to prove JAK-STAT3 and AKT pathways are the factors that contribute to proliferation/ migration/ invasion as well as the change of PD-L1 and ZFPM2, but you do not have to prove them, you just need a more comprehensive and accurate title. If you want to prove them, the most helpful experiment is the JAK inhibitors(and/or AKT inhibitors) assay (I mentioned in the last comments), I also reviewed the supplemental figure 1, you didn’t perform the assay in incorrect way. The following cohorts may be used for validating ZFPM2-AS regulate cell proliferation/ migration/ via the JAK-STAT pathway. a. Vector b. ZFPM2-AS c. Vector + JAK inhibitors d. ZFPM2-AS+JAK inhibitors And if you want to further prove its association with PD-L1, these 4 cohorts need to be performed in the presence OR absence of IFN-gamma (Totally 8 groups). Reply: Thanks very much for your professional advice. As you suggested, we have revised the title. The revised title was “ZFPM2-AS1 promotes the proliferation, migration, and invasion of human non-small cell lung cancer cells involving the JAK-STAT and AKT pathways”. 2. There are still have some typos/grammar/tense need to be corrected, although the revised manuscript was greatly improved in language. Reply: Thank you for your careful review. We have made the revision. 3. The revised Figure 3C is different from the previous version, please confirm and explain. Reply: Thanks very much. In the last peer-review, Reviewer 2 suggested that “In figure 3C, the difference in proliferation between the control and sample seems too small to be significant.” So we reperformed the relevant experiment and Figure 3C. Reviewer 2 (Anonymous) Basic reporting The revised manuscript is much better written and easier to follow. I would like to thank the authors for taking my concerns into account and sufficiently addressing them specifically in the aspect of language and grammar. These revisions make the science and the rationale provided by these authors easier to follow for a wider, more international audience. The pdf version of their manuscripts requires some minor edits as pointed out below (1) Lines 92-94 , lines 134 and 180 : missing letters 'fl' in words like influence, confluence etc. Please double check Reply: Thank you for your careful review. We have made the revision. (2) Line 135 : please change 'applied' to 'used' Reply: Sorry, we did not find 'applied' in Line 135. As you suggested, we have changed 'applied' to 'used' in Line 110. Thank you for your hard work. (3) Line 150 : Remove the phrase 'following that'. Unnecessary and causes ambiguity. Reply: Sorry, we did not find 'following that' in Line 150. As you suggested, we have removed the phrase 'following that' in Line 123. Thank you for your hard work. Apart from these changes in the text, the following minor edits need to be addressed in the figures (1) Figures 3E, 3G : please add the cell line labels to the images of the Colony formation assay Reply: Thank you for your careful review. We have add the relevant missing labels. (2) Please move figure 3D to panel H and group all the siRNA data consecutively. Figure 3D is the only one that has overexpression data Reply: Thanks very much for your professional advice. As you suggested, we have made the relevant revisions. (3) Figures 4E, G, I, K : please add cell line labels to the crystal violet images and magnification bars Reply: Thanks very much. As you suggested, we have added the cell line labels. (4) Figure 5G, H - Please add the percentages associated with each cell cycle stage consistent with the other panels in the figure. Reply: Thank you for your careful review. We have added the relevant percentages. Experimental design All comments have been addressed. Validity of the findings All comments have been addressed. Comments for the Author I would like to thank the authors for their effort in addressing all the concerns raised. The experiments designed and conducted add credence to their data. The written language better supports the data presented . "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Anthropogenic disturbance and peculiar geochemistry have resulted in rocky desertification in many karst regions of the world. Seed banks are crucial to vegetation regeneration in degraded karst ecosystems characterized by a discontinuous distribution of soil and seasonal drought stress. However, the dynamics of seed banks across one complete series of secondary succession and the underlying mechanisms remain unclear.</ns0:p><ns0:p>We selected eight typical stages during secondary succession in the Guiyang karst landscape of China, and 960 soil samples were collected. Seed density, species richness and plant life forms in seed banks were determined via the germination method. The results indicated that the seed density in seed banks before and after field seed germination was significantly different among most succession stages. Community succession had impacts on the seed density of seed banks before and after field seed germination. Seed density ranged from 1042 seedlings.m-2 in evergreen broadleaf forests to 3755 seedlings.m-2 in the herb community, which was a relatively high density. The seed density and similar species composition between the seed banks and vegetation declined with succession from early to later stages. Species richness in seed banks was highest in middle succession stages and increased with increasing species richness of aboveground vegetation. The species richness of the five life forms in the seed banks showed different variations across these succession stages. The conservation of diverse aboveground vegetation can maintain the diversity of seed banks for restoration.</ns0:p><ns0:p>Gathering effects of seeds occurring on naked stones in karst habitats explain the observed high seed density to some degree. There may be negative feedback among areas of rocky desertification, high seed density and vegetation restoration.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The study of seed banks in global karst regions can predict the future of degraded ecosystem restoration, considering that aboveground vegetation is often established from the germination and growth of seeds in soil seed banks <ns0:ref type='bibr' target='#b41'>(Shen et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b40'>Plue et al., 2017)</ns0:ref>. Moreover, the data from the study on seed banks can be applied to quantify the relationships between species diversity in seed banks and aboveground vegetation. Although the compositional vegetation-seed bank dissimilarity identified in many studies indicates that a sizeable share of seed bank diversity is not represented aboveground, the seed banks responsible for the assembly of aboveground vegetation remain an important topic in ecology <ns0:ref type='bibr' target='#b45'>(Thompson and Grime, 1979;</ns0:ref><ns0:ref type='bibr' target='#b47'>Walck et al., 2005)</ns0:ref>. Seed banks are often classified into two (transient and persistent) or three (transient, short-term and long-term persistent) categories based on their annual dynamics and dormancy, according to the comparison of autumn and spring seed occurrence <ns0:ref type='bibr' target='#b2'>(Bekker et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b13'>Funes et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b47'>Walck et al., 2005)</ns0:ref>. According to the categories of seed banks, ecologists have conducted many studies on the similarity between seed banks and aboveground vegetation and the effects of different types of disturbance and management practices on seed banks <ns0:ref type='bibr' target='#b1'>(Bakker et al., 2005</ns0:ref> The elucidation of the dynamics of seed banks with plant community succession can provide knowledge for the restoration of degraded ecosystems, which is an important research hotpot <ns0:ref type='bibr' target='#b38'>(O'Donnell et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b43'>Tamura et al., 2016)</ns0:ref>. <ns0:ref type='bibr' target='#b44'>Thompson (2000)</ns0:ref> formulated the dominant paradigm of 'declining seed numbers and diversity and decreasing similarity between seed bank and vegetation as succession proceeds.' A review based on 108 articles published between 1945 and 2006 indicates that the standing vegetation and its associated seed bank are least similar great role in the maintenance of habitat sustainability, stability, and resistance to disturbance <ns0:ref type='bibr' target='#b46'>(Tilman et al., 1996;</ns0:ref><ns0:ref type='bibr' target='#b18'>Hooper et al., 2005)</ns0:ref>. Through the study of seed banks and the corresponding aboveground vegetation, the relationships between plant diversity in aboveground vegetation and in its associated seed banks can be revealed.</ns0:p><ns0:p>Based on these relationships, ecologists can indirectly evaluate potential ecosystem functions, sustainability and stability at the studied sites <ns0:ref type='bibr' target='#b49'>(Wu, 1995;</ns0:ref><ns0:ref type='bibr'>Jo&#235;t et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Many ecologists have indicated that when the seeds of a plant species miss the germination season with suitable conditions, the seeds lose viability, and only transient seed banks of that plant species then remain <ns0:ref type='bibr' target='#b45'>(Thompson and Grime, 1979;</ns0:ref><ns0:ref type='bibr' target='#b2'>Bekker et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b13'>Funes et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b47'>Walck et al., 2005)</ns0:ref>. Conversely, if the seeds of the plant species retain viability, the plant species will exhibit persistent seed banks. In practice, plant species that appear only before field seed germination and not after field seed germination are considered to exhibit transient seed banks, while plant species that are present both before and after field seed germination exhibit persistent seed banks <ns0:ref type='bibr' target='#b47'>(Walck et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b11'>Esmailzadeh et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b37'>Martinez-Duro et al., 2012)</ns0:ref>. However, it is still difficult to precisely differentiate plant species with transient and persistent seed banks <ns0:ref type='bibr' target='#b47'>(Walck et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b34'>Ma et al., 2010)</ns0:ref>. In this study, our focus is not to clearly differentiate plant species with transient and persistent seed banks but to elucidate the dynamics of seed banks along a series of succession stages both before and after field seed germination.</ns0:p><ns0:p>We put forth the following hypotheses: (I) the dynamics of seed banks along one chronosequence of secondary succession in a karst landscape conform to the dominant paradigm of 'declining seed numbers and diversity and decreasing similarity between seed bank and vegetation as succession proceeds.', although the chronosequence is distributed in a karst landscape with unique hydrological and geological conditions; and (II) when high plant diversity is observed in aboveground vegetation along the chronosequence of secondary succession, there will also be high plant diversity in the seed banks corresponding to the aboveground vegetation due to the effects of the aboveground vegetation seed sources. To test these two assumptions, we selected a complete chronosequence of secondary succession in central Guizhou Province and investigated the aboveground vegetation. Then, soil samples were collected before and after field seed germination to test seed density and species richness in seed banks via germination methods. The objective of the study was to reveal the dynamics of seed banks along a plant community succession series in a karst region and then to clarify the relationships between plant diversity in seed banks and aboveground vegetation. We primarily answer the following questions: (1) How do seed density and species richness in seed banks and the similarity between seed banks and aboveground vegetation change from early to later succession stages? (2) Is seed density relatively higher in seed banks in karst landscapes than in other regions? <ns0:ref type='bibr' target='#b2'>(3)</ns0:ref> What are the correlations between species richness in aboveground vegetation and its associated seed banks with community succession?</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and methods</ns0:head></ns0:div> <ns0:div><ns0:head>Study area</ns0:head><ns0:p>We sampled vegetation and seed banks in secondary succession stages of evergreen broadleaf forests within Guiyang (26&#176;11&#8242;-26&#176;55&#8242;N, 106&#176;07&#8242;~106&#176;17&#8242;E) in central Guizhou Province in China (All field work was approved by Administration Bureau of Two Lakes and One Reservoir in Guiyang City). Guiyang is characterized by a midsubtropical humid monsoon climate. The average annual rainfall is between 1148.3 and 1336.1 mm. The average annual temperatures range from 13 to 15&#176;C. The different stages of secondary succession include primitive evergreen broadleaf forest (PEBF), secondary evergreen broadleaf forest (SEBF), thorn-vine shrub forest (TVSF), shrub forest (SF), shrub-grass community II (SGC-II), shrub-grass community I (SGC-I), grass community-II (GC-I), and grass community-I (GC-I) <ns0:ref type='bibr' target='#b20'>(Huang et al., 1988;</ns0:ref><ns0:ref type='bibr' target='#b53'>Zhou, 1992</ns0:ref>) (Fig. <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>). These eight stages of secondary succession are among the most typical types in the karst landscape of China. PEBF is a primitive type of forest that is not significantly influenced by anthropogenic disturbance. SEBF is a secondary type recovered after the intermediate cutting of PEBF. In TVSF, vines and plants with thorns are relatively more abundant than in SF, and most of the plants in the two forest types are short. SGC-I and GC-I are more influenced by grazing than SGC-II and GC-II. Therefore, in SGC-I and GC-I, plant height is relatively short. In all these stages, the soil type consists of calcareous soil, and the bare bedrock ratio is 30-70%.</ns0:p></ns0:div> <ns0:div><ns0:head>Vegetation sampling</ns0:head><ns0:p>We selected four representative plots of 10 m&#215;10 m in size in PEBF and SEBF. Each individual plant in the plots was carefully identified and recorded <ns0:ref type='bibr' target='#b20'>(Huang et al., 1988;</ns0:ref><ns0:ref type='bibr' target='#b53'>Zhou, 1992)</ns0:ref>. The height and canopy coverage of these individual plants and their diameter at breast height were measured. In each plot, three subplots with a 1 m&#215;1 m size were set up along a diagonal plot line. All individuals of each herb species in the subplots were also recorded, and their height and base diameter were measured. In TVSF, SF, SGC-I, SGC-II, GC-I and GC-II, the size of the plots that were set up was 5 m&#215;5 m, and the number of plots was four. Similarly, we recorded the taxa of all individuals of woody plants in these plots and measured their height, canopy coverage and base diameter. Then, three 1 m&#215;1 m subplots were set up along a diagonal line of the 5 m&#215;5 m plot to survey the vegetation parameters of Manuscript to be reviewed herb plants with the same method in the PEBF and SEBF.</ns0:p></ns0:div> <ns0:div><ns0:head>Soil sampling and experimentation</ns0:head><ns0:p>Twenty soil sampling sites were stochastically selected in each stage, including PEBF, SEBF, TVSF, SF, SGC-II, SGC-I, GC-II and GC-II sites. These sites were all distributed in the area where vegetation was surveyed. Spring comes relatively earlier in Guiyang, which is characterized by a mid-subtropical humid monsoon climate, than it does in a temperate climate. Thus, soil samples were collected at the end of February and May to separately describe the seed banks before field seed germination and the seed banks after field seed germination but before the dispersal of the current-season seeds. Soil samples were collected with a small shovel in an area of 10 cm&#215;10 cm at each soil sampling site and were divided into three depths: 0-5 cm, 5-10 cm and 10-15 cm. The volume of each soil sample was 500 cm 3 . After soil sampling, small stones in the soil samples were picked out, and the large bulk soil sample was broken up by hand. All soil samples were initially dried in laboratory and then kept at 4.5&#176;C for a month to break seed dormancy. The number of soil samples in each stage of secondary succession was 120 (two collections).</ns0:p><ns0:p>The total number of soil samples in all eight stages of secondary succession was 960.</ns0:p><ns0:p>Germination trays (20 cm&#215;20 cm size) were filled with fine sands that had been sterilized at high temperature to a depth of approximately 2-3 cm. Then, the soil samples were placed in the germination trays. The germination trays were cultivated in a large greenhouse at the farm of Guizhou University. To ensure that the seeds in the soil samples not contaminated, we constructed a small greenhouse from vinyl inside of the large greenhouse, and the germination experiment was conducted in the small greenhouse. The temperature in the small greenhouse was maintained at 20 to 30&#176;C. We identified each of the germinated seedlings and counted their number at 10-day intervals. The identified seedlings were directly removed. Unidentified taxa were transplanted into individual pots and allowed to grow until identification was possible. As no seedlings were observed in the germination experiments, the soil samples in the germination trays were thoroughly mixed and dried in a small greenhouse. Then, we continued to conduct a germination experiment until all seeds in the soil samples had germinated. The whole germination experiment lasted from April to February of the following year.</ns0:p></ns0:div> <ns0:div><ns0:head>Data analysis</ns0:head><ns0:p>The aboveground vegetation data were used to quantify important parameters of plant species in each successional stage (Supplemental Information I).</ns0:p><ns0:p>The data from the germination experiment were considered at the scale of 20 cm &#215; 20 cm plots. We obtained data on seed viability and species richness among the viable seeds at each stage and calculated their average, maximum and minimum values. Furthermore, the germination experiment data were processed to obtain the density of seeds per square meter. The normality of the data was tested with P-P figures. The data were analyzed using oneway ANOVA and LSD tests in IBM SPSS Statistics 19 to distinguish the differences in seed density between different stages. The number of seeds present for different plant life forms in the seed banks before and after seed germination was also identified. Based on these data, we used Equation (1) to calculate the similarity of the plant species between the seed banks and the aboveground vegetation.</ns0:p><ns0:p>(1)</ns0:p><ns0:formula xml:id='formula_0'>100% &#215; j b a j C j &#61485; &#61483;</ns0:formula><ns0:p>where Cj is the Jaccard index; a and b represent the number of species in the seed banks and aboveground vegetation, respectively; and j is the number of common species occurring in the seed banks and aboveground vegetation.</ns0:p><ns0:p>Then, the life forms were classified into ephemeral herbs, perennial herbs, vines, shrubs and trees. The variation in the species richness of all plant species and the respective plant life forms in the seed banks before and after seed germination along the series of secondary succession is presented in figures. Regression models were established with SPSS to fit the relationships between the species richness of all plant species and the respective plant life forms in the seed banks and plant species richness in the aboveground vegetation in these eight succession stages. The homogeneity of variance was determined by Levene`s tests for large samples. The correlation coefficients between regression residuals and predicted variables or independent variables were used to determine the homoscedasticity of the data for small samples because the coefficients can indirectly represent the homogeneity of variance for dependent variables <ns0:ref type='bibr' target='#b52'>(Zhu, 2017)</ns0:ref>. All analyses and tests are included in the raw data files that have been uploaded to the system.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Dynamics of seed banks along the succession series</ns0:head></ns0:div> <ns0:div><ns0:head>Seed density of recorded species</ns0:head><ns0:p>We identified 89 species in the seed banks both before and after field seed germination in all succession stages (Table <ns0:ref type='table'>1</ns0:ref>; Supplemental Information II). These plant species included 71 herb species, 3 vine species, 10 shrub species and 5 tree species. The number of species occurring in seed banks before and after field seed germination ranged from 20 to 38 and from 23-31, respectively (Table <ns0:ref type='table'>1</ns0:ref>). The number of common species ranged from 11 to 19. There were many viable seeds in each succession stage. For the species with the most seeds, 33-106 seedlings were recorded in these stages, but only 1-3 seedlings of the species with the fewest seeds were observed. The species with the most seeds were all herb plants, such as Digitaria sanguinalis, Arthraxon hispidus, Arthraxon lanceolatus, Setaria viridis, Centella asiatica, and Oxalis corniculata. The greatest seed number in the seed banks was observed for herb plants, which accounted for 62.9% of the total seed number. Herb plants occurred in nearly every succession stage. However, woody plants mainly occurred in the seed banks of TVSF, SF, SEBF and PEBF. The highest total species richness occurred in the seed banks from intermediate stages within the series of community succession.</ns0:p></ns0:div> <ns0:div><ns0:head>Total seed density in different stages</ns0:head><ns0:p>There were abundant seeds in the seed banks before and after field seed germination in the different stages of secondary succession (Table <ns0:ref type='table'>2</ns0:ref>). Among these stages, CG-II, which was relatively less influenced by grazing than GC-I, exhibited the most seedlings: 3755 and 1650.m -2 (total in three soil depths). SEBF and PEBF presented the fewest seedlings. The seed density in the early succession stages in which herbs dominated aboveground was greater than that in later stages. The seed density in seed banks before field seed germination was higher than after field seed germination in all stages of secondary succession. However, the differences in seed density in the seed banks before and after field seed germination were small in the later stages. With increasing soil depth, the number of recorded seedlings decreased. In addition, there was great variation in seed density among different sites in the same successional stage.</ns0:p><ns0:p>The seed density in the seed banks before and after field seed germination differed significantly among most of the successional stages (Supplemental Information III). No difference was generally observed between neighboring succession stages. There were relatively less significant differences in the seed density of seed banks after field seed germination between succession stages than before field seed germination. However, the seed density of the seed banks both before and after field seed germination showed more significant differences between successional stages.</ns0:p></ns0:div> <ns0:div><ns0:head>Seed density of different life forms</ns0:head><ns0:p>The seed density of ephemeral and perennial herbs in the seed banks in different succession stages was also greater before field seed germination than after field seed germination (Table <ns0:ref type='table'>3</ns0:ref>). The seed density of these two life forms showed a decreasing trend with community succession from early to later stages. However, trees showed an increasing trend in seed density. Vines presented relatively high seed density in middle succession stages. The seed Manuscript to be reviewed density of ephemeral and perennial herbs was far greater than that of vines, shrubs and trees. There was a grazing disturbance in GC-I compared to GC-II, and the seed density of ephemeral and perennial herbs was accordingly greater in GC-I than in GC-II.</ns0:p></ns0:div> <ns0:div><ns0:head>Similarity of plant species between seed banks and aboveground vegetation</ns0:head><ns0:p>Before and after field seed germination, the similarity of plant species among the seed banks from the three soil depths and the aboveground vegetation declined with community succession from early to later stages (Table <ns0:ref type='table' target='#tab_0'>4</ns0:ref>).</ns0:p><ns0:p>Early succession stages GC-I and GC-II exhibited much higher similarity than the later stages. Comparatively, the species composition in the seed banks before field seed germination showed higher similarity than that after field seed germination except in SGC-II and PEBF. The similarity of the plant species between the seed banks from the different soil depths and aboveground vegetation also decreased with community succession from early to later stages. The similarity coefficients (C j ) among the different soil depths were mostly lower than those over the depth of 0-15 cm. The C j values for the surface soil layer were mostly greater than those for the deep soil layer.</ns0:p></ns0:div> <ns0:div><ns0:head>Relationships between species richness in seed banks and aboveground vegetation</ns0:head></ns0:div> <ns0:div><ns0:head>Species richness in seed banks across different succession stages</ns0:head><ns0:p>Before field seed germination, species richness in the seed banks at soil depths of 5-10 cm and 10-15 cm showed a weak, nonsignificant increase (P&#65310;0.05) from early to later succession stages under decreasing similarity of the species composition between the seed banks and the aboveground vegetation, but at the depth of 0-5 cm, there was a slight decrease (P&#65310;0.05) (Fig. <ns0:ref type='figure' target='#fig_12'>2A-C</ns0:ref> ). However, after field seed germination, species richness in the seed banks at the three depths showed a statistically significant increase (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_12'>2D-F</ns0:ref>). Species richness in the seed banks both before and after field seed germination decreased with increasing soil depth based on the trend line.</ns0:p><ns0:p>Comparatively, species richness in the seed banks at the three depths before field seed germination was higher than that after field seed germination. There was great variation in species richness in the seed banks of each succession stage among sampling plots according to the highly variable standard deviation (error line) of species richness in the seed banks.</ns0:p></ns0:div> <ns0:div><ns0:head>Species richness of different life forms in seed banks across different succession stages</ns0:head><ns0:p>Before field seed germination, the species richness of ephemeral and perennial herbs in seed banks at the three soil depths first increased and then decreased with community succession from early to later stages (Fig. <ns0:ref type='figure' target='#fig_13'>3A</ns0:ref>).</ns0:p><ns0:p>However, the species richness of shrubs, vines and trees differed from that of ephemeral and perennial herbs, which changed in a linearly increasing form across these stages. After field seed germination, there was no great change in the species richness of ephemeral herbs in the seed banks with community succession (Fig. <ns0:ref type='figure' target='#fig_13'>3B</ns0:ref>). For perennial herbs, two peaks of species richness occurred in GC-I and SGC-II; species richness was similar among the other stages.</ns0:p><ns0:p>The species richness of shrubs and trees increased across these stages, analogous to what was observed in the seed banks before field seed germination. For vines, there was a humped distribution of species richness across these stages. The fitted models of the species richness of different life forms at different stages were statistically significant except for the species richness of vines (Table <ns0:ref type='table'>5</ns0:ref>). These fitted models showed humped, positive or negative linear shapes.</ns0:p></ns0:div> <ns0:div><ns0:head>Relationship between species richness in seed banks and aboveground vegetation</ns0:head><ns0:p>Both before and after field seed germination, an increase in species richness in the seed banks with increasing species richness of aboveground vegetation was a dominant pattern (irrespective of the succession stage) (Fig. <ns0:ref type='figure' target='#fig_9'>4</ns0:ref>).</ns0:p><ns0:p>Species richness in aboveground vegetation could not explain the variation in species richness in the seed banks before field seed germination (Fig. <ns0:ref type='figure' target='#fig_14'>4A-C</ns0:ref>). However, species richness in aboveground vegetation could explain 16.9-54.4% of the variation in species richness in the seed banks after field seed germination (Fig. <ns0:ref type='figure' target='#fig_14'>4D-F</ns0:ref>); the explanatory power of the species richness of aboveground vegetation decreased with soil depth. Overall, the variation in species richness in the seed banks before field seed germination was not dependent on the species richness of aboveground vegetation. Species richness in the seed banks after field seed germination was partially dependent on the species richness of aboveground vegetation.</ns0:p></ns0:div> <ns0:div><ns0:head>Relationships between the species richness of different life forms in seed banks and aboveground vegetation</ns0:head><ns0:p>The species richness of ephemeral and perennial herbs in the seed banks before field seed germination slowly decreased and increased, respectively, with increasing species richness of aboveground vegetation (Fig. <ns0:ref type='figure' target='#fig_15'>5A and B</ns0:ref>).</ns0:p><ns0:p>The species richness of ephemeral and perennial herbs in the seed banks after field seed germination showed irregular variation with increasing species richness (Fig. <ns0:ref type='figure' target='#fig_15'>5F and G</ns0:ref>). In the seed banks before and after field seed germination, vine, shrub and tree species showed an identical pattern of species richness; i.e., species richness continually increased with increasing species richness of aboveground vegetation (Fig. <ns0:ref type='figure' target='#fig_15'>5C-E</ns0:ref> and Fig. <ns0:ref type='figure' target='#fig_15'>5H-J</ns0:ref>).</ns0:p><ns0:p>However, there was often high species richness of vines, shrubs or trees in some soil samples from a given stage but low richness or no representation of that life form in other soil samples from that stage. Consequently, the standard deviation was even greater than the mean (Fig. <ns0:ref type='figure' target='#fig_15'>5C-E</ns0:ref> and Fig. <ns0:ref type='figure' target='#fig_15'>5H-J</ns0:ref>). Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>We found that total seed density and the seed density of ephemeral and perennial herbs in the seed banks both before and after field seed germination and the similarity between the seed banks and aboveground vegetation declined from early to later stages of secondary succession in the Guiyang karst landscape. These results conform to the dominant paradigm of 'declining seed numbers and diversity and decreasing similarity between seed bank and aboveground vegetation as succession proceeds' <ns0:ref type='bibr' target='#b44'>(Thompson, 2000)</ns0:ref>. Many results obtained from recent studies also support the pattern of declining seed density and similarity with plant community succession <ns0:ref type='bibr' target='#b41'>(Shen et al., 2007;</ns0:ref><ns0:ref type='bibr' /> Kwiatkowska-Fali&#324;ska et al., 2011; Egawa and Tsuyuzaki, 2013; Kiss et al., 2017). In the complete chronosequence of secondary succession in the karst landscape, aboveground ephemeral and perennial herbs were dominant in terms of both individual density and species diversity at early stages. A large number of seeds from these herbs fell to the ground when the seeds were mature. This resulted in a high seed density in seed banks and high species composition similarity between the seed banks and aboveground vegetation. However, shrubs and trees began to become dominant at the later stages of succession, and the seeds of herbs decreased. Conversely, the seeds of woody plants increased, but the number of seeds from woody plants was far lower than that from herbs. Therefore, the total density of the seed banks continually decreased with plant community succession. There were also numerous seeds of herbaceous plant species in soil but relatively few aboveground herbaceous species in later stages under dominant shrubs or trees. The herbaceous plant species in the seed banks were primarily the same species that occurred in early herbaceous-dominant stages, such as GC-I and GC-II. As a consequence, the similarity of the species composition between the seed banks and aboveground vegetation also declined with plant community succession. However, our results regarding the similarity of the species composition with community succession were also Manuscript to be reviewed via hard work. Therefore, our finding of low species similarity between seed banks and aboveground vegetation in later stages of succession implies that seed dispersal outside of the stages of secondary succession is a natural regeneration strategy for restoring degraded karst landscapes to forests.</ns0:p><ns0:p>It was found that the total seed density in the seed banks both before and after field seed germination in different stages in the Guiyang karst landscape was significantly greater than that in plant communities in which there in no bare rock in other regions. For example, a density of 84-562 seedlings m -2 was observed in soil seed banks at a depth of 0-10 cm in different stages of secondary succession in south subtropical forests <ns0:ref type='bibr' target='#b21'>(Huang et al., 1996)</ns0:ref>, 400-1400 seedlings m -2 in forest floor litter and soils at a depth of 0-5 cm in temperate forests in northeast China <ns0:ref type='bibr'>(Yan et al., 2010)</ns0:ref>, 642-985 seedlings in soil seed banks of a cool-temperate, damp old-growth forest in Japan <ns0:ref type='bibr' target='#b43'>(Tamura, 2016)</ns0:ref>, and fewer than 400 seedlings m -2 in soil seed banks at a depth of 0-12 cm in three alpine meadows on the Tibetan Plateau <ns0:ref type='bibr' target='#b34'>(Ma, 2010)</ns0:ref>. The densities observed along a well-preserved chronosequence in the Alps of Austria ranged from 273 seedlings m -2 in soil seed banks at a depth of 0-10 cm in the pioneer stage to 820 seedlings m -2 in the early stage and 3527 and 3674 seedlings m -2 in later stages; the seed density of the seed banks in these stages was lower than that in the stages of secondary succession in that study <ns0:ref type='bibr' target='#b36'>(Marcante et al., 2009)</ns0:ref>. However, the total seed density in the seed banks of both a secondary forest and Distylium chinensis communities in areas consisting of 50-70% bare rocks in a similar-latitude karst region of Guizhou Province was similar to the total seed density found in this study <ns0:ref type='bibr' target='#b29'>(Liu et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b28'>Liu, 2001;</ns0:ref><ns0:ref type='bibr' target='#b31'>Lu et al., 2007)</ns0:ref>. In another tropical karst region of China, a seed density of 3,900-14,900 seedlings.m -2 was observed in soil seed banks in tropical grass, shrub and forest communities, which was significantly higher than those found in the Guiyang karst landscape in our study and in other nonkarst regions <ns0:ref type='bibr' target='#b41'>(Shen et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b19'>Hopfensperger, 2007)</ns0:ref>; these tropical karst communities were characterized by similar bare rock percentages of 50 to 70% <ns0:ref type='bibr' target='#b41'>(Shen et al., 2007)</ns0:ref>. In karst landscapes, plants grow in a stressed environment, and the seed density in seed rains is often low <ns0:ref type='bibr' target='#b28'>(Liu et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b41'>Shen et al., 2007)</ns0:ref>. However, the data obtained from the Guiyang karst landscape indicate a higher density of the seeds in seed banks than is found in other regions. Based on our field observations, when seeds fall on the surface of smooth bare rocks during seed rains in karst landscapes, these seeds are easily carried by wind or rainwater to the areas between the bare rocks <ns0:ref type='bibr'>(Wang et al., 2014)</ns0:ref>. Through these comparisons, we therefore infer that there may be a concentration effect of bare rocks on seed rains that results in a high seed density in seed banks during a succession series in a karst landscape. However, this effect needs to be verified by the results obtained under a different experimental design.</ns0:p><ns0:p>The species richness in the seed banks before and after field seed germination from early to later succession stages was high in intermediate stages but showed relatively small differences among these stages. This pattern is different from the decreasing diversity indicated by the dominant paradigm <ns0:ref type='bibr' target='#b44'>(Thompson 2000)</ns0:ref>, which is analogous to findings in central European grasslands <ns0:ref type='bibr' target='#b26'>(Kiss et al., 2017)</ns0:ref>. In intermediate succession stages, the species richness was higher than that in early stages but lower than that in later stages in this study. The aboveground vegetation added many seeds to the seed banks. There were few shrubs and trees, but herbaceous plants were still abundant, which caused some shade, but the habitats still received abundant sunlight. These conditions were beneficial to the maintenance of seed viability for different plant species <ns0:ref type='bibr' target='#b22'>(Jaganathan and Dalrymple, 2015)</ns0:ref>. Conversely, early and later stages might be slightly drier and wetter, respectively, making them unfavorable to seed viability for some plant species. Therefore, the intermediate stages exhibited the highest species richness in seed banks. The species richness of the different plant life forms in seed banks both before and after field seed germination showed a humped, positive or negative linear shape across these stages. The species richness of ephemeral and perennial herbs across all stages was approximately 2-10 times greater than that of shrubs, vines and trees. These are similar to the levels of species richness reported in second-growth stands, old-growth stands and logged stands in tropical wet forests <ns0:ref type='bibr' target='#b7'>(Dupuy and Chazdon, 1998)</ns0:ref> and in grazed and ungrazed eucalypt woodlands <ns0:ref type='bibr' target='#b14'>(Grant and Macgregor, 2001)</ns0:ref>.</ns0:p><ns0:p>In steppe deserts, ephemeral herbs have been found to account for a much higher percentage (&gt;90%) of the species richness in seed banks than perennial herbs and shrubs (&lt;5%), and the ratio of herbs was considerably higher than that indicated by our results <ns0:ref type='bibr' target='#b6'>(De et al., 2008)</ns0:ref>. The life-form pattern found here also disagrees with that reported in the Santa Genebra Municipal Reserve of Brasil, where trees account for 47.8% of the total species richness, which is much greater than the contributions of herbs and shrubs (6.5% and 16.5%, respectively) (Grombone-Guaratini and Rodrigues, 2002). The variations in species richness associated with different plant life forms across succession stages under habitat change explain the different species diversity observed in seed bands before and after seed germination at different succession stages to some degree.</ns0:p><ns0:p>Although there are many reports of species richness in seed banks, the relationship of the species richness in seed banks with the associated aboveground vegetation under decreasing similarity of the species composition across an individual chronosequence is seldom analyzed <ns0:ref type='bibr' target='#b19'>(Hopfensperger, 2007)</ns0:ref>. We conducted an analysis using the data for the species in the karst landscape. The species richness in seed banks after field seed germination significantly increased with increasing species richness of aboveground vegetation under decreasing similarity of the species composition, but the species richness in seed banks before field seed germination was maintained at an almost invariable level. The species richness of shrubs, trees and vines in seed banks also increased with increasing species richness of aboveground vegetation, but the species richness of ephemeral and perennial herbs showed almost no change. These results partially validate hypothesis II. Although we did not intend to clearly differentiate plant species with transient and persistent seed banks, the data on the seed banks before and after field seed germination to some degree represent plant species with transient and persistent seed banks, respectively <ns0:ref type='bibr' target='#b13'>(Funes et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b47'>Walck et al., 2005)</ns0:ref>. The above results also indicate that the change in species richness in transient and persistent seed banks differs with increasing species diversity of aboveground vegetation, but the changes in the species richness of shrubs, trees and vines in both transient and persistent seed banks are identical. Therefore, diverse aboveground vegetation is propitious for the maintenance of persistent seed banks. Plant diversity in vegetation can play a great role in ecosystem functions, sustainability, stability and resistance to disturbance <ns0:ref type='bibr' target='#b46'>(Tilman et al., 1996</ns0:ref><ns0:ref type='bibr' target='#b18'>Hooper et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b5'>Davis et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b22'>Jaganathan et al., 2015;</ns0:ref><ns0:ref type='bibr'>Jo&#235;t et al., 2016)</ns0:ref>. These monotonically increasing relationships between the species richness of aboveground vegetation and seed banks also indicate that high plant diversity in seed banks will to a great extent support the development of high plant diversity in the associated aboveground vegetation in the future. Therefore, high plant diversity in seed banks means that there is great potential to provide ecosystem services to humans in the long run <ns0:ref type='bibr' target='#b30'>(Loreau and Hector, 2001)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Decreasing seed density and species composition similarity with both community succession and decreasing soil depths is a dominant pattern in karst landscapes. Field seed germination in karst landscapes results in a decrease in the number of seeds in seed banks by approximately half. Community succession has a significant impact on the seed density in seed banks before and after field seed germination. The seed density in the seed banks of karst plant communities is relatively high, and there is consequently good potential for the restoration of degraded ecosystems from seed banks. The total species richness in seed banks and the species richness of shrubs, vines and trees increase with increasing species richness of aboveground vegetation. The decreasing species composition similarity between aboveground vegetation and seed banks with the succession of plant communities implies that the natural recovery of degraded ecosystems to relatively stable stages such as SEBF and PEBF is dependent on species dispersal from outside area. High plant diversity in aboveground vegetation is beneficial to the maintenance of plant diversity in Manuscript to be reviewed seed banks. .25 C j , Jaccard index; B and A represent seed banks before and after field seed germination, respectively. The calculation of C j -B or C j -A at a 0-15 cm soil depth for each stage is based on the plant species identified from 60 soil samples. The calculation of C j -B or C j -A at each of the other three soil depths is based on the plant species identified from 20 soil samples.</ns0:p><ns0:note type='other'>Figure legends</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>; Pakeman and Small, 2005; Li et al., 2005; Ma et al., 2011; Ma et al., 2013). In recent years, qualitative and quantitative studies of seed banks have included more detailed classifications, germination patterns, spatiotemporal patterns of seed banks and mechanisms underlying the persistence of seed banks (Walck et al., 2005; Yan et al., 2010; Joe et al., 2016).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:1:2:NEW 12 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:1:2:NEW 12 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:1:2:NEW 12 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>different from those of a few studies in European and Chinese grasslands<ns0:ref type='bibr' target='#b36'>(Marcante et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b32'>Ma et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b37'>Martinez-Duro et al., 2012)</ns0:ref>. In these studies, the species composition similarity between seed banks and aboveground vegetation was found to increase with community succession because some distinct species occurred in the aboveground vegetation that decreased the species composition similarity from early to later stages. Moreover, the similarity (&#65308;20%) between the seed banks and karst forests (SEBF and PEBF) in this study was far lower than that found in temperate secondary forests in northeastern China(Yan et al., 2010), wet dun slacks in the Netherlands (Bakker et al., 2005), and a subalpine pasture in the Alps of Europe (Marcante et al., 2009). Ecosystem restoration data indicate that the later stage of succession often represents the type of forest to which society wants land restored PeerJ reviewing PDF | (2020:05:48689:1:2:NEW 12 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:1:2:NEW 12 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Fig. 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Fig. 1 Different stages of secondary succession in the Guiyang karst landscape. A: GC-I; B: GC-II; C: SGC-I; D: SGC-II; E: TVSF; F: SF; G: SEBF; H: PEBF.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Fig. 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Fig. 2 Changes in species richness in seed banks across different stages of secondary succession. A, B and C are the seed banks before field seed germination at the soil depths of 0-5, 5-10 and 10-15 cm, respectively; D, E and F are the seed banks after field seed germination at the three different soil depths. Each stage of secondary succession corresponds to twenty species richness values obtained from twenty soil samples in one layer of soil (N=160 in each small figure). Species richness shows a normal distribution based on P-P figures. The variance in species richness at different successional stages is homogeneous. *, *, and ** represent significance at confidence levels of 95%, 99%and 99.9%, respectively. The notation is the same in the table and the figures below.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Fig. 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Fig.3Species richness of five plant life forms in seed banks before field seed germination (A) and after field seed</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Fig. 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Fig. 4 Relationship of the species richness in seed banks with the species richness of aboveground vegetation. A, B and C represent species richness in soil seed banks before field seed germination at depths of 0-5, 5-10 and 10-15 cm, respectively; D, E and F represent the soil seed banks after field seed germination at the three depths. The value of each dot in the figures is the mean species richness determined from twenty soil samples collected in each succession stage. The species richness on the x-axis corresponding to each dot in the figures is the mean species richness surveyed from four plots (for woody plants) and 12 subplots (for herb plants) in each succession stage. Note: the species richness of the aboveground vegetation and seed banks is highest in middle succession stages. Species richness shows a normal distribution based on P-P figures. The variance of species richness associated with different levels of the species richness of aboveground vegetation is homogeneous based on statistical tests.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Fig. 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Fig.5Relationship of the species richness of different life forms in seed banks with the species richness of aboveground vegetation. A, B, C, D and E represent the ephemeral herbs, perennial herbs, vines, shrubs and trees, respectively, included in seed banks before field seed germination; F, G, H, I, and J represent the ephemeral herbs, perennial herbs, vines, shrubs and trees, respectively, included in seed banks after field seed germination. The values of each dot in the figures are the mean species richness tested from sixty soil samples (total at three soil depths) in each stage of secondary succession. Species richness on the X-axis is the same as in Fig.4. The species richness of all plant life forms shows a normal distribution based on P-P figures. The variance of the species richness at different levels of the species richness of aboveground vegetation is homogeneous based on statistical tests.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 1 Different</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 2 Changes</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 3 Species</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Figure 4 Relationship</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure 5 Relationship</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Similarity of plant species between the seed bank and aboveground vegetation</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Jaccard index</ns0:cell><ns0:cell>Soil depths</ns0:cell><ns0:cell>GC-I</ns0:cell><ns0:cell>GC-&#8545;</ns0:cell><ns0:cell>SGC-&#8544;</ns0:cell><ns0:cell>SGC-&#8545;</ns0:cell><ns0:cell>TVSF</ns0:cell><ns0:cell>SF</ns0:cell><ns0:cell>SEBF</ns0:cell><ns0:cell>PEBF</ns0:cell></ns0:row><ns0:row><ns0:cell>C j -B</ns0:cell><ns0:cell>0-15 cm</ns0:cell><ns0:cell>56.00</ns0:cell><ns0:cell>37.50</ns0:cell><ns0:cell>23.10</ns0:cell><ns0:cell>17.86</ns0:cell><ns0:cell>18.99</ns0:cell><ns0:cell>15.48</ns0:cell><ns0:cell>17.86</ns0:cell><ns0:cell>11.10</ns0:cell></ns0:row><ns0:row><ns0:cell>C j -A</ns0:cell><ns0:cell>0-15 cm</ns0:cell><ns0:cell>35.48</ns0:cell><ns0:cell>38.46</ns0:cell><ns0:cell>13.11</ns0:cell><ns0:cell>18.57</ns0:cell><ns0:cell>16.00</ns0:cell><ns0:cell>13.89</ns0:cell><ns0:cell>15.66</ns0:cell><ns0:cell>12.82</ns0:cell></ns0:row><ns0:row><ns0:cell>C j -B</ns0:cell><ns0:cell>0-5 cm</ns0:cell><ns0:cell>28.13</ns0:cell><ns0:cell>25.71</ns0:cell><ns0:cell>14.04</ns0:cell><ns0:cell>20.00</ns0:cell><ns0:cell>17.11</ns0:cell><ns0:cell>20.83</ns0:cell><ns0:cell>13.58</ns0:cell><ns0:cell>11.69</ns0:cell></ns0:row><ns0:row><ns0:cell>C j -B</ns0:cell><ns0:cell>5-10 cm</ns0:cell><ns0:cell>28.57</ns0:cell><ns0:cell>30.00</ns0:cell><ns0:cell>10.91</ns0:cell><ns0:cell>14.71</ns0:cell><ns0:cell>19.44</ns0:cell><ns0:cell>15.49</ns0:cell><ns0:cell>10.67</ns0:cell><ns0:cell>9.59</ns0:cell></ns0:row><ns0:row><ns0:cell>C j -B</ns0:cell><ns0:cell>10-15 cm</ns0:cell><ns0:cell>31.82</ns0:cell><ns0:cell>15.15</ns0:cell><ns0:cell>11.54</ns0:cell><ns0:cell>20.34</ns0:cell><ns0:cell>10.61</ns0:cell><ns0:cell>8.70</ns0:cell><ns0:cell>5.26</ns0:cell><ns0:cell>9.23</ns0:cell></ns0:row><ns0:row><ns0:cell>C j -A</ns0:cell><ns0:cell>0-5 cm</ns0:cell><ns0:cell>27.59</ns0:cell><ns0:cell>24.32</ns0:cell><ns0:cell>17.65</ns0:cell><ns0:cell>14.93</ns0:cell><ns0:cell>18.31</ns0:cell><ns0:cell>12.50</ns0:cell><ns0:cell>10.26</ns0:cell><ns0:cell>10.96</ns0:cell></ns0:row><ns0:row><ns0:cell>C j -A</ns0:cell><ns0:cell>5-10 cm</ns0:cell><ns0:cell>29.63</ns0:cell><ns0:cell>25.00</ns0:cell><ns0:cell>9.62</ns0:cell><ns0:cell>14.92</ns0:cell><ns0:cell>11.11</ns0:cell><ns0:cell>11.43</ns0:cell><ns0:cell>6.49</ns0:cell><ns0:cell>7.04</ns0:cell></ns0:row><ns0:row><ns0:cell>C j -A</ns0:cell><ns0:cell>10-15 cm</ns0:cell><ns0:cell>37.50</ns0:cell><ns0:cell>18.75</ns0:cell><ns0:cell>8.00</ns0:cell><ns0:cell>11.67</ns0:cell><ns0:cell>13.43</ns0:cell><ns0:cell>7.69</ns0:cell><ns0:cell>8.22</ns0:cell><ns0:cell>7</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48689:1:2:NEW 12 Aug 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Responses to Reviews In the Responses to Reviews, the comments of Editors and reviewers are present in previous black sentence, but corresponding responses are showed by blue sentences for differences. Dear Dr. Wang, Thank you for your submission to PeerJ. It is my opinion as the Academic Editor for your article - A study of soil seed banks across one complete chronosequence of secondary succession in karst landscape - that it requires a number of Major Revisions. My suggested changes and reviewer comments are shown below and on your article 'Overview' screen. If you address these changes and resubmit, there's a good chance your article will be accepted (although this isn't guaranteed). Although not a hard deadline, we expect you to submit your revision within the next 55 days. With kind regards, Victoria Sosa Academic Editor, PeerJ Responses: Dear Dr. Sosa, Thank you very much for your work on my manuscript. We also thank you to give us the chance of major revision. We have revised the manuscript according to your comments below. How we concretely revise is given as follows. Editor comments (Victoria Sosa) MAJOR REVISIONS Both reviewers raised many issues among the most important are: 1) the lack of hypotheses; 2) explain design of collections; 3) lack of clarity in the Introduction; 4) present results in a clear way and 5) English does not reach a professional level. In addition reviewers indicated several issues indicated below. Responses: Thank you and reviewers raised many constructive comments. These comments help great for revision. We carefully considered the five issues and further revised the manuscript. After our revision based on all reviews, we invited English Language Service to edit the revision. The revised manuscript is English-ready for publication that English Edited Certificate promises. [# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #] Responses: We have done in the rebuttal letter and the revised manuscript per your request. We think that we can ensure that the manuscript can stand alone without the rebuttal letter to understand all contents. [# PeerJ Staff Note: The review process has identified that the English language must be improved. PeerJ can provide language editing services - please contact us at [email protected] for pricing (be sure to provide your manuscript number and title) #] Responses: The revised manuscript has been edited by English Language Service (Springer Nature Author Service). Reviewer 1 (You-Xin Shen) Basic reporting From hypothesis to the discussion, authors want to say the 'gathering effect' by rocks. However, this is not the point that your article should address since you did not have any design and results, the only evidence is 'reference' sited from everewhere (temperate forest). Responses: Your criticism is right. We had not conducted the comparison of seed number between plots covered by bare rocks and no bare rocks, and then got data to validate the hypothesis. Therefore, we deleted these in Introduction and Discussion. The gathering effect was discussed as a possibly season causing the high seed density in karst landscape. See line 99-114, Line 328-335 in revised manuscript. Experimental design no comment Validity of the findings relathionship between soil seed band and vegetation. Comments for the Author Karst ecosystems are all over the world. Most of them had suffered great disturbances. Caring on a study to determine the relationship between soil seed bank (SB) and above ground vegetation have scientific meaning and practical implications. This article was written on SB and vegetation data from eight typical stages in secondary succession in Guiyang karst landscape of China to addressing the correlation of SB and vegetation. However, there are still some problems in. Responses: Thank you for your positive reviews. We have carefully processed these problems according to your reviews below. Line 20: Guiyang. Responses: We have corrected the word. Thanks. Thank you very much. See line 20 in revised manuscript. Line 21 “tested” change to “determined” Responses: We have changed the word. See line 21. Line 21-23: Resulted indicated that seed density of seed banks before field seed germination showed significantly different between each pair of succession stages” is not the same with your result. Responses: We have revised the sentences which are not the same with the results. See 22-23. Line 25: How do you define “neighboring regions”? Guiyang is in subtropical region, you even cited data from “temperate forests” and made conclusion to say SB in karst is higher than non-karst. Responses: we had searched many literatures finished in neighboring regions, i.e., karst regions in China, but few study case had been found. Therefore, we also cited other studies in the earth. Totally, seed density is relatively high. However, because we have cited the data of non-neighboring regions in both previous and revised manuscripts, the neighboring regions do not seem to be proper as your comments, we deleted it in revised manuscript. See line 25. Line86-92: hypothesis 1 is not logical (richness in SB-aboveground diversity-habitat sustainability and stability-then richness in SB again?) and fully relevant to the study (do you want to approve this hypothesis thought your study). Do you have any design and result to approve hypothesis 2? Responses: We have revised the two assumptions based on the actual study and data in the study. Previous two assumptions were not really logical as your comments after we have carefully considered. Because in the 'richness in SB-aboveground diversity-habitat sustainability and stability-then richness in SB', we had not tested the indices of habitat sustainability and stability affecting seed viability. There were not also a design such as the area and slope of bare rock and the seed amount collected by the bare rock. Instead, we hypothesize: (I) the dynamics of seed banks along one chronosequence of secondary succession in karst landscape still conform to the dominant paradigm, i.e. “declining seed numbers and diversity and decreasing similarity between seed bank and vegetation as succession proceeds.”, although the chronosequence is distributed in an karst landscape with especial hydrological and geological conditions; (II) When high plant diversity is tested out in aboveground vegetation along the chronosequence of secondary succession, then there will also be high plant diversity in the seed banks corresponding to the aboveground vegetation due to the effects of seed source from aboveground vegetation. The two assumptions are based on the designs of the study. See line 99-105. Line 99-100: Again, do you have any design and result to approve “gathering effect”? Responses: we have revised the assumption. See Line 99-114. About “gathering effect”, we suggested it as a possible effect that needs to be studied. Line 328-335 in revised manuscript. Line 340-341:“Seed density in seed banks of karst plant communities is significantly greater than of plant communities in which there are not bare rocks”. No data can support this conclusion. Responses: We have deleted the sentence without support of data. See Line 384-385. Line 101-111. It should not be the last paragraph of the “Introduction”. Responses: we have moved them frontally. See Line 89-98. Line 345-347: “The low species composition similarity…needs to be dependent on species dispersal from outsides”. This low similarity is normal (larger seeds, distribution pattern, diverse seed rain pattern etc.). what do the author mean “natural recovery “? Does the SEBF and PEBF still need further recovery? Responses: You are right. This low similarity is normal (larger seeds, distribution pattern and diverse seed rain pattern etc. The recovery means the restoration from degraded ecosystems to SEBF and PEBF, and therefore, the processes need dispersal from outsides. The sentences in previous manuscript were not very proper here. Your comments are insightful. We have revised these sentences. See Line 388-391. Line 347-348: Species richness in seed banks increases with increasing…indicating that conservation of diverse aboveground vegetation may maintain diversity of seed banks for restoration in practice”. What does the author want to say? What is the logic of “conserve vegetation” to “maintain SB” and then “restoration in practice” Responses: Because the plant diversity of seed bank can help for the natural recovery of ecosystems, I want to express a conclusion: we found that species richness in seed banks increases with increasing species richness in aboveground vegetation; so the conservation of plant diversity in aboveground vegetation may maintain plant diversity in seed banks. This is useful for ecosystem restoration. We have revised the unclear sentence based on results in the study in the revised manuscript: High plant diversity in aboveground vegetation is beneficial to the maintenance of plant diversity in seed banks. See Line 391-392. Fig2. How can you made mathematic equations with your “succession stage” X axis? Bar chart may be more suitable. Responses: The regression models were obtained by assignment of eight succession stage as 1-8 in SPSS system and then conducted the regression of diversity data on 1-8. There is the function of gradually qualitative indices to be quantified in the SPSS system. These succession stages are just the gradually qualitative indices. As your comments, the figures are really suitable for bar charts. We have revised. See Fig. 2. Reviewer 2 (Melisa Rago) Basic reporting The manuscript studies the soil seed bank and above-ground vegetation in eight stages of secondary succession in a karstic landscape. Soil seed bank dynamic and its potential to restore degraded landscapes is an interesting topic. You recorded a great amount of very useful data. However, I found the manuscript difficult to follow and confusing regarding different aspects. For example, I would specify the main objective, hypotheses, and questions, and align them better to the analyses, results, and interpretation. Analyses description needs more details. Results should be limited to the questions. Discussion could be improved with a better interpretation of the possible reasons of the obtained results. I consider that correcting all these suggestions will increase the interest of your work. I also recommend checking the English and writing in all the sections to ensure the clarity of your work. Responses: thank you very much for your positive reviews and advise how we revise the manuscript. These reviews are constructive to improve the manuscript. We have carefully considered your reviews in revised manuscript. The revised manuscript was also edited by English Editing Service. Introduction Introduction gives a general background about soil seed bank dynamic. However, it repeats concepts in different paragraphs, making it difficult to follow. I consider that correcting the following suggestions could improve it. - I recommend stating the problem briefly in the first sentences of the introduction. Responses: I added the station of the problem with two sentences in the first sentences of the introduction. See Line 36-38. - I suggest expressing the main objective more clearly. It could be rewording lines 93 to 95. Responses: We have added the main objective in the place you suggested. See Line 108-114. - Hypotheses are confusing, consider rewording them. They should be affirmations stated in present tense. Responses: Thank you for your pointing out wrong writing as the first reviewer suggested. We reworded the hypotheses and corrected the wrong tense. See Line 99-105. - In lines 51 it says “… in forest ecosystems (later succession stages)…” and “… grasslands (early succession stages)…” what do you mean by that? Take into account that Hopfensperger (2007) makes a review in three ecosystems: grasslands, wetlands, and forests. The author evaluates the similarity between soil seed bank and vegetation, and in relation to succession at each ecosystem independently. Responses: We have revised the unsuitable expressions. See Line 54-57. - I recommend avoiding the use of words such as “obviously” (line 52), “evidently” (line 187). Responses: Thank you for your reviews on usage of words. We have revised these words through the manuscript. - In lines 54-56, what do you mean by “However, the relationships between plant diversity in above-ground vegetation and in its associated seed banks under the dominant paradigm are still unknown”. I found a contradiction with the well-known knowledge about the similarity between soil seed bank and vegetation reported previously. Responses: Thank you for your pointing out this. We have revised the sentence. See 57-69. - In line 74 I would mention briefly which the main anthropogenic disturbs are in the karstic landscape. Responses: We revised the sentence per your guidance. See Line 70-72. - I suggest finishing the introduction with the study questions. Thus, the paragraph in lines 101-111 should be previously. Responses: Thank you for your reminder. Reviewer one also suggested the same points. Great minds think alike. The paragraph should not be really at the end of Introduction. We have changed the position of the paragraph and revised unsuitable sentences. See Line 89-98. - From my point of view, in lines 61-71 you mention the main contribution of the study. I suggest focusing more in this aspect throughout the manuscript. Responses: We have revised many of the manuscript and focused on the aspect throughout the manuscript. It dealt with the revision of the structure of manuscript according to your guidance. See Line 61-98. Materials and Methods Sampling section is detailed, but I recommend improving writing and English in this section. Analyses need more details. I suggest aligning them with questions and results. Responses: The whole manuscript has been edited by English Language Service after we have revised. We added the details of analysis. We re-align them into two sections: seed density and species richness with questions and results. See Line 165-188. - Line 124, I miss the meaning of SF. Responses: It is shrub forest (SF). I have added the abbreviation occurred for the first time above text. See Line 122. - Lines 128-129, I suggest changing “The name of each individual plant….” To “Each individual plant was identified…” or similar. Responses: We have revised the expression according to your guidance. See Line 132-133. - Lines 129-130, I recommend avoiding the use of “carefully” and “precisely”. Instead, describe how you measured canopy cover, diameter at breast height, etc. I also recommend including the references used for plant species identification. Responses: Thank you very much for your guidance of word usage. We have revised these words and added references. See Line 133-134. - I wonder how you measured important value of species, and why. Responses: The important value of species in a plant community is basic information as study site in an article, which reflects the function and role of each plant species in plant community. Because we researched seed banks, and corresponding aboveground vegetation, the important value lets us know the function and role of a plant species tested in aboveground vegetation and seed bank. See Line 165-166 and Supplemental information I. - Lines 161-162, I recommend mentioning the anova analysis first, and then the LSD test, since LSD test should be only used if significant differences are detected by anova. Responses: Previous mentioning is 'using LSD-test after one-way ANOVA to distinguish the differences of seed density between different stages'. This time, we separated the sentence into two and in the first sentence we tested differences with ANOVA as your guidance. See Line 167-174. - Analyses should be more detailed. You should include the software used and libraries if it corresponds. Detail the variables you used, especially for anova and regression analyses, and how you evaluated the assumptions, such as normality and homocedasticity, etc. Responses: We added some contents to detail analysis, including software (IBM SPSS Statistics 19), what data collected, variables, and so on. We used P-P figures to identify the normality of data, used Levene`s test to identify the homocedasticity of data for great samples (seed density). However, we used the coefficients of correlations between regression residual and independent variables to identify the homocedasticity of data for small samples (plant diversity in aboveground vegetation and the plant diversity of different plant life-form in seed banks). If the coefficients of correlations are significant in statistics, the variance is heterocedasticity, and independent variables cannot well explain for the dependent variables by linear models. All analysis and tests are in the files of raw data uploaded to the system. Thank you for your guidance in data analysis. See Line 164-188. - I suggest changing “arbor” to “tree” in line 169 and throughout the manuscript. Responses: We have revised all words 'arbor' through the manuscript. Results Although results answer to some extend the questions, in some parts I found them confusing. I suggest you to check this section focusing in aligning the results with the questions and methods, and to improve the English and writing. Responses: We have revised the section of results to correspond to questions in Introduction and methods in Material and methods. The manuscript has been edited by English Editing Service. They promised that the manuscript is English-ready. See Line 109-114; 190-236. -All differences have to be statistically significant to be mentioned as a difference. For example, in lines 176-177 you say “Seed density showed greatly different among recorded species”, are they significant different? I suggest to take this into account in all the result section. Responses: Thank you for reminder of the professional issue. We have revised the expression. Because we can directly see the great differences of seed number among recorded species by Max and Min in Table 1, we will not further conduct statistical analysis on the differences. Instead, we only change sentences here. See Line 193-195 and Table 1. - I recommend avoiding the use of words such as “evidently” in line 187, “obviously” in line 210. As I have noted above, differences have to be statistically supported to be considered as differences. You could use the word “significant” in those cases. Responses: We have deleted all the usage of words in the manuscript. Somewhere afterwards, we added statistical analysis. See Line 214-218. - Why did you compare the soil seed bank among different soil depths? I consider that the importance of soil depths should be mentioned in the introduction. Responses: Your review is constructive to balance between results and introduction. By your reviews, we have studied many. The comparison of the soil seed bank at different soil depths shows the vertical variation of seed banks along the series. It can reflect the potential of restoration in such a stressed environment. We have added some contents in Introduction. See Line 64-66. Line 68-69. - Lines 217-220, I miss p-values significance, is it 0.05? State it clearly. Responses: It is 0.05, I have added. See Line 238-241. - I recommend to specify the area when you analyze species richness, since richness is dependent on area. For example, I understand that the area you are referring in table 1 is different from the area you are referring in figure 4. I consider that specifying it will improve the clarity of the manuscript, and could contribute to enhance the interpretation you do in lines 274-280. Responses: We have specified the area when we demonstrate results of seed density, species richness and similarity for each table or figure. For Table 1, Data of A or B at each succession stage was obtained from 60 soil samples (total at three depths; each soil sample collected from a 10cm×10cm plot). For Figure 3, species richness represented by each pillar is the number of all species for one life-form tested from 60 soil samples (total at three depths; each soil sample collected from a 10cm×10cm plot) at one succession stage. Therefore, the results in Table 1 and Figure 3 were obtained from the same scale. We have added explanation in the revised manuscript for the comments. Tables and Figures: - Table 1. I suggest changing “viable seeds” to “seedlings”. This table has a lot of information; check if all of it is relevant to answer the questions. Are you mentioning total number of species recorded at each successional stage? I recommend adding the complete name of each successional stage in the legend or somewhere in the table for understanding it independently from the text (the same for all figures and tables). Responses: You are insightful. Seedling is really better than viable seeds here. Total number of species is the number of all recorded species at each successional stage in both after and before germination from 60 soil samples (total at three depths; each soil sample collected from a 10cm×10cm plot). If we deleted species information in table 1, we feel no complete. We changed the previous title of table 1 to include species: Number of the recorded seedlings and species geminated from soil samples. We added the names of these succession stages in Table 1 occurred for the first time and represent all them in other tables and figures. See Table 1. - Table 4. I suggest using B and A to represent before and after field seed germination, instead of I and II for Jaccard index. Thereby, you will be consistent throughout the manuscript. Responses: we have changed these. See table 4. - Table 5. What does * mean? Responses: * and ** represent the significances at the confidence of 95% and 99% , respectively. We have added the explanation for these marks firstly occurring in the legend of Fig. 2. - Figure 2, 4, and 5. Add p-value, or specify what * means. Responses: We have added p-value. *, ** and ** represent the significances at the confidence of 95%, 99% and 99,9% , respectively. We have added them in the legend of Fig.2 and showed that the notation is the same in table and figures below. - Figure 3. I miss what dotted lines mean. Responses: The dotted lines represent the trend line across these succession stages. The corresponding model of the trend line is present in Table 5. Discussion Although discussion section compares the results with other studies, I suggest improving the interpretation of the obtained results by explaining which could be the reasons of what you found. Responses: we have added these reasons. - I suggest not mentioning again the figures and tables in discussion section. Response: we have deleted all theses repeated. I hope all of these suggestions help you to improve your manuscript. Responses: you are very professional. Each point of your review is helpful to improve the manuscript. ……………………………………………………………………………………………………………………… About the responses to 12 changes needed which was sent by you this time. The first-seventh changes and the ninth- twelfth changes have been changed according to your guidance. However, we have not revised the eighth you required. The reason is as follows: 8. Figures It's unclear whether the categories in your bar graphs (GC-I: grass community-I; GC-I: grass community-II; SGC-I: shrub-grass community; etc.) form a regular sequence. If the categories on the X-axis do not form a regular sequence then the trend lines on the graphs do not add value to your figures and should be removed. Please provide replacement figures measuring minimum 900 pixels and maximum 3000 pixels on all sides, saved as PNG, EPS or PDF (vector images) file format without excess white space around the images. Responses: According to literatures, GC-I, GC-II, SGC-I, SGC-II, TVSF, SF, SEBF and PEBF is one complete chronosequence of secondary succession in karst landscape (Huang et al., 1988; Zhou, 1992). The stages are linked each other as a regular sequence. These figures demonstrate a trend with community succession from early stage to relatively stable stage. Figures have revised per your guidance. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Anthropogenic disturbance and peculiar geochemistry have resulted in rocky desertification in many karst regions of the world. Seed banks are crucial to vegetation regeneration in degraded karst ecosystems characterized by a discontinuous distribution of soil and seasonal drought stress. However, the dynamics of seed banks across one complete series of secondary succession and the underlying mechanisms remain unclear.</ns0:p><ns0:p>We selected eight typical stages during secondary succession, conducted aboveground vegetation survey and collected 960 soil samples in the Guiyang karst landscape of China.</ns0:p><ns0:p>Seed density, species richness and plant life forms in seed banks were determined via the germination method. The results indicated that the seed density in seed banks before and after field seed germination was significantly different among most succession stages.</ns0:p><ns0:p>Community succession had impacts on the seed density of seed banks before and after field seed germination. Seed density ranged from 1042 seedlings.m -2 in evergreen broadleaf forests to 3755 seedlings.m -2 in the herb community, which was a relatively high density. The seed density and similar species composition between the seed banks and vegetation declined with succession from early to later stages. Species richness in seed banks was highest in middle succession stages and increased with increasing species richness of aboveground vegetation. The species richness of the five life forms in the seed banks showed different variations across these succession stages. The conservation of diverse aboveground vegetation can maintain the diversity of seed banks for restoration.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The study of seed banks in global karst regions can predict the future of degraded ecosystem restoration, considering that aboveground vegetation is often established from the germination and growth of seeds in soil seed banks <ns0:ref type='bibr' target='#b41'>(Shen et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b40'>Plue et al., 2017)</ns0:ref>. Moreover, the data from the study on seed banks can be applied to quantify the relationships between species diversity in seed banks and aboveground vegetation. Although the compositional vegetation-seed bank dissimilarity identified in many studies indicates that a sizeable share of seed bank diversity is not represented aboveground, the seed banks responsible for the assembly of aboveground vegetation remain an important topic in ecology <ns0:ref type='bibr' target='#b45'>(Thompson and Grime, 1979;</ns0:ref><ns0:ref type='bibr' target='#b47'>Walck et al., 2005)</ns0:ref>. Seed banks are often classified into two (transient and persistent) or three (transient, short-term and long-term persistent) categories based on their annual dynamics and dormancy, according to the comparison of autumn and spring seed occurrence <ns0:ref type='bibr' target='#b2'>(Bekker et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b12'>Funes et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b47'>Walck et al., 2005)</ns0:ref>. According to the categories of seed banks, ecologists have conducted many studies on the similarity between seed banks and aboveground vegetation and the effects of different types of disturbance and management practices on seed banks <ns0:ref type='bibr' target='#b1'>(Bakker et al., 2005</ns0:ref> The elucidation of the dynamics of seed banks with plant community succession can provide knowledge for the restoration of degraded ecosystems, which is an important research hotpot (O'Donnell et al., 2016; <ns0:ref type='bibr' target='#b43'>Tamura et al., 2016)</ns0:ref>. <ns0:ref type='bibr' target='#b44'>Thompson (2000)</ns0:ref> formulated the dominant paradigm of 'declining seed numbers and diversity and decreasing similarity between seed bank and vegetation as succession proceeds.' A review based on 108 articles published between 1945 and 2006 indicates that the standing vegetation and its associated seed bank are least similar in forests, intermediately similar in wetlands and most similar in grasslands among the three studied ecosystems <ns0:ref type='bibr' target='#b18'>(Hopfensperger, 2007)</ns0:ref>. This review supports the dominant paradigm because grasslands are generally considered relationships between plant diversity in aboveground vegetation and in its associated seed banks can be revealed.</ns0:p><ns0:p>Based on these relationships, ecologists can indirectly evaluate potential ecosystem functions, sustainability and stability at the studied sites <ns0:ref type='bibr' target='#b49'>(Wu, 1995;</ns0:ref><ns0:ref type='bibr'>Jo&#235;t et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Many ecologists have indicated that when the seeds of a plant species miss the germination season with suitable conditions, the seeds lose viability, and only transient seed banks of that plant species then remain <ns0:ref type='bibr' target='#b45'>(Thompson and Grime, 1979;</ns0:ref><ns0:ref type='bibr' target='#b2'>Bekker et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b12'>Funes et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b47'>Walck et al., 2005)</ns0:ref>. Conversely, if the seeds of the plant species retain viability, the plant species will exhibit persistent seed banks. In practice, plant species that appear only before field seed germination and not after field seed germination are considered to exhibit transient seed banks, while plant species that are present both before and after field seed germination exhibit persistent seed banks <ns0:ref type='bibr' target='#b47'>(Walck et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b10'>Esmailzadeh et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b37'>Martinez-Duro et al., 2012)</ns0:ref>. However, it is still difficult to precisely differentiate plant species with transient and persistent seed banks <ns0:ref type='bibr' target='#b47'>(Walck et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b34'>Ma et al., 2010)</ns0:ref>. In this study, our focus is not to clearly differentiate plant species with transient and persistent seed banks but to elucidate the dynamics of seed banks along a series of succession stages both before and after field seed germination.</ns0:p><ns0:p>We put forth the following hypotheses: (I) the dynamics of seed banks along one chronosequence of secondary succession in a karst landscape conform to the dominant paradigm of 'declining seed numbers and diversity and decreasing similarity between seed bank and vegetation as succession proceeds.', although the chronosequence is distributed in a karst landscape with unique hydrological and geological conditions; and (II) when high plant diversity is observed in aboveground vegetation along the chronosequence of secondary succession, there will also be high plant diversity in the seed banks corresponding to the aboveground vegetation due to the effects of the aboveground vegetation seed sources. To test these two assumptions, we selected a complete chronosequence of secondary succession in central Guizhou Province and investigated the aboveground vegetation. Then, soil samples were collected before and after field seed germination to test seed density and species richness in seed banks via germination methods. The objective of the study was to reveal the dynamics of seed banks along a plant community succession series in a karst region and then to clarify the relationships between plant diversity in seed banks and aboveground vegetation. We primarily answer the following questions: (1) How do seed density and species richness in seed banks and the similarity between seed banks and aboveground vegetation change from early to later succession stages? <ns0:ref type='bibr' target='#b1'>(2)</ns0:ref> What are the correlations between species richness in aboveground vegetation and its associated seed banks with community succession? Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and methods</ns0:head></ns0:div> <ns0:div><ns0:head>Study area</ns0:head><ns0:p>We sampled vegetation and seed banks in secondary succession stages of evergreen broadleaf forests within Guiyang (26&#176;11&#8242;-26&#176;55&#8242;N, 106&#176;07&#8242;~106&#176;17&#8242;E) in central Guizhou Province in China (All field work was approved by Administration Bureau of Two Lakes and One Reservoir in Guiyang City). Guiyang is characterized by a midsubtropical humid monsoon climate. The average annual rainfall is between 1148.3 and 1336.1 mm. The average annual temperatures range from 13 to 15&#176;C. The different stages of secondary succession include primitive evergreen broadleaf forest (PEBF), secondary evergreen broadleaf forest (SEBF), thorn-vine shrub forest (TVSF), shrub forest (SF), shrub-grass community II (SGC-II), shrub-grass community I (SGC-I), grass community-II (GC-I), and grass community-I (GC-I) <ns0:ref type='bibr' target='#b19'>(Huang et al., 1988;</ns0:ref><ns0:ref type='bibr' target='#b53'>Zhou, 1992</ns0:ref>) (Fig. <ns0:ref type='figure' target='#fig_12'>1</ns0:ref>). These eight stages of secondary succession are among the most typical types in the karst landscape of China. PEBF is a primitive type of forest that is not significantly influenced by anthropogenic disturbance. SEBF is a secondary type recovered after the intermediate cutting of PEBF. In TVSF, vines and plants with thorns are relatively more abundant than in SF, and most of the plants in the two forest types are short. SGC-I and GC-I are more influenced by grazing than SGC-II and GC-II. Therefore, in SGC-I and GC-I, plant height is relatively short. In all these stages, the soil type consists of calcareous soil, and the bare bedrock ratio is 30-70%.</ns0:p></ns0:div> <ns0:div><ns0:head>Vegetation sampling</ns0:head><ns0:p>We selected four representative plots of 10 m&#215;10 m in size in PEBF and SEBF. Each individual plant in the plots was carefully identified and recorded <ns0:ref type='bibr' target='#b19'>(Huang et al., 1988;</ns0:ref><ns0:ref type='bibr' target='#b53'>Zhou, 1992)</ns0:ref>. The height and canopy coverage of these individual plants and their diameter at breast height were measured. In each plot, three subplots with a 1 m&#215;1 m size were set up along a diagonal plot line. All individuals of each herb species in the subplots were also recorded, and their height and base diameter were measured. In TVSF, SF, SGC-I, SGC-II, GC-I and GC-II, the size of the plots that were set up was 5 m&#215;5 m, and the number of plots was four. Similarly, we recorded the taxa of all individuals of woody plants in these plots and measured their height, canopy coverage and base diameter. Then, three 1 m&#215;1 m subplots were set up along a diagonal line of the 5 m&#215;5 m plot to survey the vegetation parameters of herb plants with the same method in the PEBF and SEBF. Manuscript to be reviewed Twenty soil sampling sites were stochastically selected in each stage, including PEBF, SEBF, TVSF, SF, SGC-II, SGC-I, GC-II and GC-II sites. These sites were all distributed in the area where vegetation was surveyed. Spring comes relatively earlier in Guiyang, which is characterized by a mid-subtropical humid monsoon climate, than it does in a temperate climate. Thus, soil samples were collected at the end of February and May to separately describe the seed banks before field seed germination and the seed banks after field seed germination but before the dispersal of the current-season seeds. Soil samples were collected with a small shovel in an area of 10 cm&#215;10 cm at each soil sampling site and were divided into three depths: 0-5 cm, 5-10 cm and 10-15 cm. The volume of each soil sample was 500 cm 3 . After soil sampling, small stones in the soil samples were picked out, and the large bulk soil sample was broken up by hand. All soil samples were initially dried in laboratory and then kept at 4.5&#176;C for a month to break seed dormancy. The number of soil samples in each stage of secondary succession was 120 (two collections).</ns0:p></ns0:div> <ns0:div><ns0:head>Soil sampling and experimentation</ns0:head><ns0:p>The total number of soil samples in all eight stages of secondary succession was 960.</ns0:p><ns0:p>Germination trays (20 cm&#215;20 cm size) were filled with fine sands that had been sterilized at high temperature to a depth of approximately 2-3 cm. Then, the soil samples were placed in the germination trays. The germination trays were cultivated in a large greenhouse at the farm of Guizhou University. To ensure that the seeds in the soil samples not contaminated, we constructed a small greenhouse from vinyl inside of the large greenhouse, and the germination experiment was conducted in the small greenhouse. The temperature in the small greenhouse was maintained at 20 to 30&#176;C. We identified each of the germinated seedlings and counted their number at 10-day intervals. The identified seedlings were directly removed. Unidentified taxa were transplanted into individual pots and allowed to grow until identification was possible. As no seedlings were observed in the germination experiments, the soil samples in the germination trays were thoroughly mixed and dried in a small greenhouse. Then, we continued to conduct a germination experiment until all seeds in the soil samples had germinated. The whole germination experiment lasted from April to February of the following year.</ns0:p></ns0:div> <ns0:div><ns0:head>Data analysis</ns0:head><ns0:p>The aboveground vegetation data were used to quantify the important values (IV) of plant species in each successional stage (Supplemental Information I). IV represented the dominance of species in aboveground plant community.</ns0:p><ns0:p>The data from the germination experiment were considered at the scale of 10 cm &#215; 10 cm plots. We obtained data on seedlings and species richness among the seedlings at each stage and calculated their average, maximum and Manuscript to be reviewed minimum values. Furthermore, the germination experiment data were processed to obtain the density of seeds per square meter. The normality of the data was tested with P-P figures. The data were analyzed using one-way ANOVA and LSD tests in IBM SPSS Statistics 19 to distinguish the differences in seed density between different stages. The number of seeds present for different plant life forms in the seed banks before and after seed germination was also identified.</ns0:p><ns0:p>We further gave the list of all plant species in both the 10 m&#215;10 m or 5 m&#215;5 m plots of woody plants and 1 m&#215;1 m plots of herbs in each stage (Supplementary Information I) and the lists of all plant species germinating from 20 soil samples for each layer of soil in the range of the stage (Supplementary Information II). Then, the common species of the two lists of plant species in the aboveground vegetation and seed bank were identified in each stage.</ns0:p><ns0:p>Equation ( <ns0:ref type='formula'>1</ns0:ref>) was used to calculate the similarity of the plant species between the seed banks and the aboveground vegetation for each stage.</ns0:p><ns0:p>(1)</ns0:p><ns0:formula xml:id='formula_0'>100% &#215; j b a j C j &#61485; &#61483;</ns0:formula><ns0:p>where C j is the Jaccard index; a and b represent the number of species in the seed banks and aboveground vegetation, respectively; and j is the number of common species occurring in the seed banks and aboveground vegetation.</ns0:p><ns0:p>Then, plant species were classified by their life forms into ephemeral herbs, perennial herbs, vines, shrubs and trees. Regression models were established with SPSS to fit the relationships between the richness of plant species in the seed banks and succession stages (qualitative regression), and between the richness of plant species and respective plant life forms in the seed banks and richness of plant species in aboveground vegetation in these eight succession stages (quantitative regression). The homogeneity of variance was determined by Levene`s tests for large samples. The correlation coefficients between regression residuals and predicted variables or independent variables were used to determine the homoscedasticity of the data for small samples because the coefficients can indirectly represent the homogeneity of variance for dependent variables <ns0:ref type='bibr' target='#b52'>(Zhu, 2017)</ns0:ref>. All analyses and tests are included in the raw data files that have been uploaded to the system.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Dynamics of seed banks along the succession series</ns0:head></ns0:div> <ns0:div><ns0:head>Seed density of recorded species</ns0:head><ns0:p>We identified 89 species in the seed banks both before and after field seed germination in all succession stages (Table <ns0:ref type='table'>1</ns0:ref>; Supplemental Information II). These plant species included 71 herb species, 3 vine species, 10 shrub Manuscript to be reviewed species and 5 tree species. The number of species occurring in seed banks before and after field seed germination ranged from 20 to 38 and from 23-31, respectively (Table <ns0:ref type='table'>1</ns0:ref>). The number of common species ranged from 11 to 19.</ns0:p><ns0:p>There were many viable seeds in each succession stage. For the species with the most seeds, 33-106 seedlings were recorded in these stages, but only 1-3 seedlings of the species with the fewest seeds were observed. The species with the most seeds were all herb plants, such as Digitaria sanguinalis, Arthraxon hispidus, Arthraxon lanceolatus, Setaria viridis, Centella asiatica, and Oxalis corniculata. The greatest seed number in the seed banks was observed for herb plants, which accounted for 62.9% of the total seed number. Herb plants occurred in nearly every succession stage. However, woody plants mainly occurred in the seed banks of TVSF, SF, SEBF and PEBF. The highest total species richness occurred in the seed banks from intermediate stages within the series of community succession.</ns0:p></ns0:div> <ns0:div><ns0:head>Total seed density in different stages</ns0:head><ns0:p>There were abundant seeds in the seed banks before and after field seed germination in the different stages of secondary succession (Table <ns0:ref type='table'>2</ns0:ref>). Among these stages, CG-II, which was relatively less influenced by grazing than GC-I, exhibited the most seedlings: 3755 and 1650.m -2 (total in three soil depths). SEBF and PEBF presented the fewest seedlings. The seed density in the early succession stages in which herbs dominated aboveground was greater than that in later stages. The seed density in seed banks before field seed germination was higher than after field seed germination in all stages of secondary succession. However, the differences in seed density in the seed banks before and after field seed germination were small in the later stages. With increasing soil depth, the number of recorded seedlings decreased. In addition, there was great variation in seed density among different sites in the same successional stage.</ns0:p><ns0:p>The seed density in the seed banks before and after field seed germination differed significantly among most of the successional stages (Supplemental Information III). No difference was generally observed between neighboring succession stages. There were relatively less significant differences in the seed density of seed banks after field seed germination between succession stages than before field seed germination. However, the seed density of the seed banks both before and after field seed germination showed more significant differences between successional stages.</ns0:p></ns0:div> <ns0:div><ns0:head>Seed density of different life forms</ns0:head><ns0:p>The seed density of ephemeral and perennial herbs in the seed banks in different succession stages was also greater before field seed germination than after field seed germination (Table <ns0:ref type='table'>3</ns0:ref>). The seed density of these two life Manuscript to be reviewed forms showed a decreasing trend with community succession from early to later stages. However, trees showed an increasing trend in seed density. Vines presented relatively high seed density in middle succession stages. The seed density of ephemeral and perennial herbs was far greater than that of vines, shrubs and trees. There was a grazing disturbance in GC-I compared to GC-II, and the seed density of ephemeral and perennial herbs was accordingly greater in GC-I than in GC-II.</ns0:p></ns0:div> <ns0:div><ns0:head>Similarity of plant species between seed banks and aboveground vegetation</ns0:head><ns0:p>Before and after field seed germination, the similarity of plant species among the seed banks from the three soil depths and the aboveground vegetation declined with community succession from early to later stages (Table <ns0:ref type='table'>4</ns0:ref>).</ns0:p><ns0:p>Early succession stages GC-I and GC-II exhibited much higher similarity than the later stages. Comparatively, the species composition in the seed banks before field seed germination showed higher similarity than that after field seed germination except in SGC-II and PEBF. However, only few plant species, e.g., Digitaria sanguinalis, Arthraxon hispidus, Arthraxon lanceolatus, and Zanthoxylum planispinum Sieb.et Zucc., showed similar dominances in both seed banks and aboveground vegetation based on the data of vegetation and seed banks for concrete plant species (Supplementary Information I and II). The similarity of the plant species between the seed banks from the different soil depths and aboveground vegetation also decreased with community succession from early to later stages. The similarity coefficients (C j ) among the different soil depths were mostly lower than those over the depth of 0-15 cm. The C j values for the surface soil layer were mostly greater than those for the deep soil layer.</ns0:p></ns0:div> <ns0:div><ns0:head>Relationships between species richness in seed banks and aboveground vegetation</ns0:head></ns0:div> <ns0:div><ns0:head>Species richness in seed banks across different succession stages</ns0:head><ns0:p>Before field seed germination, species richness in the seed banks at soil depths of 5-10 cm and 10-15 cm showed a weak, nonsignificant increase (P&#65310;0.05) from early to later succession stages under decreasing similarity of the species composition between the seed banks and the aboveground vegetation, but at the depth of 0-5 cm, there was a slight decrease (P&#65310;0.05) (Fig. <ns0:ref type='figure' target='#fig_18'>2A-C</ns0:ref> ). However, after field seed germination, species richness in the seed banks at the three depths showed a statistically significant increase (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_18'>2D-F</ns0:ref>). Species richness in the seed banks both before and after field seed germination decreased with increasing soil depth based on the trend line.</ns0:p><ns0:p>Comparatively, species richness in the seed banks at the three depths before field seed germination was higher than that after field seed germination. There was great variation in species richness in the seed banks of each succession Manuscript to be reviewed stage among sampling plots according to the highly variable standard deviation (error line) of species richness in the seed banks.</ns0:p></ns0:div> <ns0:div><ns0:head>Species richness of different life forms in seed banks across different succession stages</ns0:head><ns0:p>Before field seed germination, the species richness of ephemeral and perennial herbs in seed banks at the three soil depths first increased and then decreased with community succession from early to later stages (Fig. <ns0:ref type='figure' target='#fig_19'>3A</ns0:ref>).</ns0:p><ns0:p>However, the species richness of shrubs, vines and trees differed from that of ephemeral and perennial herbs, which changed in a linearly increasing form across these stages. After field seed germination, there was no great change in the species richness of ephemeral herbs in the seed banks with community succession (Fig. <ns0:ref type='figure' target='#fig_19'>3B</ns0:ref>). For perennial herbs, two peaks of species richness occurred in GC-I and SGC-II; species richness was similar among the other stages.</ns0:p><ns0:p>The species richness of shrubs and trees increased across these stages, analogous to what was observed in the seed banks before field seed germination. For vines, there was a humped distribution of species richness across these stages. The fitted models of the species richness of different life forms at different stages were statistically significant except for the species richness of vines (Table <ns0:ref type='table'>5</ns0:ref>). These fitted models showed humped, positive or negative linear shapes.</ns0:p></ns0:div> <ns0:div><ns0:head>Relationship between species richness in seed banks and aboveground vegetation</ns0:head><ns0:p>Both before and after field seed germination, an increase in species richness in the seed banks with increasing species richness of aboveground vegetation was a dominant pattern (irrespective of the succession stage) (Fig. <ns0:ref type='figure' target='#fig_15'>4</ns0:ref>).</ns0:p><ns0:p>Species richness in aboveground vegetation could not explain the variation in species richness in the seed banks before field seed germination (Fig. <ns0:ref type='figure' target='#fig_20'>4A-C</ns0:ref>). However, species richness in aboveground vegetation could explain 16.9-54.4% of the variation in species richness in the seed banks after field seed germination (Fig. <ns0:ref type='figure' target='#fig_20'>4D-F</ns0:ref>); the explanatory power of the species richness of aboveground vegetation decreased with soil depth. Overall, the variation in species richness in the seed banks before field seed germination was not dependent on the species richness of aboveground vegetation. Species richness in the seed banks after field seed germination was partially dependent on the species richness of aboveground vegetation.</ns0:p></ns0:div> <ns0:div><ns0:head>Relationships between the species richness of different life forms in seed banks and aboveground vegetation</ns0:head><ns0:p>The species richness of ephemeral and perennial herbs in the seed banks before field seed germination slowly decreased and increased, respectively, with increasing species richness of aboveground vegetation (Fig. <ns0:ref type='figure' target='#fig_21'>5A and B</ns0:ref>).</ns0:p><ns0:p>The species richness of ephemeral and perennial herbs in the seed banks after field seed germination showed Manuscript to be reviewed irregular variation with increasing species richness (Fig. <ns0:ref type='figure' target='#fig_21'>5F and G</ns0:ref>). In the seed banks before and after field seed germination, vine, shrub and tree species showed an identical pattern of species richness; i.e., species richness continually increased with increasing species richness of aboveground vegetation (Fig. <ns0:ref type='figure' target='#fig_21'>5C-E</ns0:ref> and Fig. <ns0:ref type='figure' target='#fig_21'>5H-J</ns0:ref>).</ns0:p><ns0:p>However, there was often high species richness of vines, shrubs or trees in some soil samples from a given stage but low richness or no representation of that life form in other soil samples from that stage. Consequently, the standard deviation was even greater than the mean (Fig. <ns0:ref type='figure' target='#fig_21'>5C-E</ns0:ref> and Fig. <ns0:ref type='figure' target='#fig_21'>5H-J</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>We found that total seed density and the seed density of ephemeral and perennial herbs in the seed banks both before and after field seed germination and the similarity between the seed banks and aboveground vegetation declined from early to later stages of secondary succession in the Guiyang karst landscape. These results conform to the dominant paradigm of 'declining seed numbers and diversity and decreasing similarity between seed bank and aboveground vegetation as succession proceeds' <ns0:ref type='bibr' target='#b44'>(Thompson, 2000)</ns0:ref>. Many results obtained from recent studies also support the pattern of declining seed density and similarity with plant community succession <ns0:ref type='bibr' target='#b41'>(Shen et al., 2007;</ns0:ref><ns0:ref type='bibr' /> Kwiatkowska-Fali&#324;ska et al., 2011; Egawa and Tsuyuzaki, 2013; Kiss et al., 2017). In the complete chronosequence of secondary succession in the karst landscape, aboveground ephemeral and perennial herbs were dominant in terms of both individual density and species richness at early stages. A large number of seeds from these herbs were identified in the germination experiment. This resulted in a high seed density in seed banks and high species composition similarity between the seed banks and aboveground vegetation. However, shrubs and trees began to become dominant at the later stages of succession, and the seeds of herbs decreased. Conversely, the seeds of woody plants increased, but the number of seeds from woody plants was far lower than that from herbs. Therefore, the total density of the seed banks continually decreased with plant community succession. There were also numerous seeds of herbaceous plant species in soil but relatively few aboveground herbaceous species in later stages under dominant shrubs or trees. The herbaceous plant species in the seed banks were primarily the same species that occurred in early herbaceous-dominant stages, such as GC-I and GC-II. As a consequence, the similarity of the species composition between the seed banks and aboveground vegetation also declined with plant community succession. Manuscript to be reviewed aboveground vegetation was found to decrease with community succession because some distinct species occurred in the aboveground vegetation that decreased the species composition similarity from early to later stages. Moreover, the similarity (&#65308;20%) between the seed banks and karst forests (SEBF and PEBF) in this study was far lower than that found in temperate secondary forests in northeastern China <ns0:ref type='bibr'>(Yan et al., 2010)</ns0:ref>, wet dun slacks in the Netherlands <ns0:ref type='bibr' target='#b1'>(Bakker et al., 2005)</ns0:ref>, and a subalpine pasture in the Alps of Europe <ns0:ref type='bibr' target='#b36'>(Marcante et al., 2009)</ns0:ref>. Ecosystem restoration data indicate that the later stage of succession often represents the type of forest to which society wants land restored via hard work. Therefore, our finding of low species similarity between seed banks and aboveground vegetation in later stages of succession implies that seed introduction by dispersal to these eight typical stages of secondary succession is a natural regeneration strategy that is worthy of an attention for restoring degraded karst landscapes to forests.</ns0:p><ns0:p>It was found that the total seed density in the seed banks both before and after field seed germination in different stages in the Guiyang karst landscape was significantly greater than that in plant communities in which there in no bare rock in other regions. For example, a density of 84-562 seedlings m -2 was observed in soil seed banks at a depth of 0-10 cm in different stages of secondary succession in south subtropical forests <ns0:ref type='bibr' target='#b20'>(Huang et al., 1996)</ns0:ref>, 400-1400 seedlings m -2 in forest floor litter and soils at a depth of 0-5 cm in temperate forests in northeast China <ns0:ref type='bibr'>(Yan et al., 2010)</ns0:ref>, 642-985 seedlings in soil seed banks of a cool-temperate, damp old-growth forest in Japan <ns0:ref type='bibr' target='#b43'>(Tamura, 2016)</ns0:ref>, and fewer than 400 seedlings m -2 in soil seed banks at a depth of 0-12 cm in three alpine meadows on the Tibetan Plateau <ns0:ref type='bibr' target='#b34'>(Ma, 2010)</ns0:ref>. The densities observed along a well-preserved chronosequence in the Alps of Austria ranged from 273 seedlings m -2 in soil seed banks at a depth of 0-10 cm in the pioneer stage to 820 seedlings m -2 in the early stage and 3527 and 3674 seedlings m -2 in later stages; the seed density of the seed banks in these stages was lower than that in the stages of secondary succession in that study <ns0:ref type='bibr' target='#b36'>(Marcante et al., 2009)</ns0:ref>. However, the total seed density in the seed banks of both a secondary forest and Distylium chinensis communities in areas consisting of 50-70% bare rocks in a similar-latitude karst region of Guizhou Province was similar to the total seed density found in this study <ns0:ref type='bibr' target='#b29'>(Liu et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b28'>Liu, 2001;</ns0:ref><ns0:ref type='bibr' target='#b31'>Lu et al., 2007)</ns0:ref>. In another tropical karst region of China, a seed density of 3,900-14,900 seedlings.m -2 was observed in soil seed banks in tropical grass, shrub and forest communities, which was significantly higher than those found in the Guiyang karst landscape in our study and in other nonkarst regions <ns0:ref type='bibr' target='#b41'>(Shen et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b18'>Hopfensperger, 2007)</ns0:ref>; these tropical karst communities were characterized by similar bare rock percentages of 50 to 70% <ns0:ref type='bibr' target='#b41'>(Shen et al., 2007)</ns0:ref>. In karst landscapes, plants grow in a stressed Manuscript to be reviewed environment, and the seed density in seed rains is often low <ns0:ref type='bibr' target='#b28'>(Liu et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b41'>Shen et al., 2007)</ns0:ref>. However, the data obtained from the karst landscape indicate a higher density of the seeds in seed banks than is found in other regions.</ns0:p><ns0:p>Based on our field observations, when seeds fall on the surface of smooth bare rocks during seed rains in karst landscapes, these seeds are easily carried by wind or rainwater to the areas between the bare rocks <ns0:ref type='bibr'>(Wang et al., 2014)</ns0:ref>. Through above comparisons, we therefore infer that there may be a concentration effect of bare rocks on seed rains that results in a high seed density in seed banks during a succession series in a karst landscape. However, this effect needs to be verified by the results obtained under a different experimental design.</ns0:p><ns0:p>The total species richness in the seed banks before and after field seed germination from early to later succession stages was high in intermediate stages but showed relatively small differences among these stages.</ns0:p><ns0:p>However, the species richness in the seed banks before and after field seed germination for respective soil layers increased from early to later succession stages. This pattern is different from the decreasing diversity indicated by the dominant paradigm <ns0:ref type='bibr' target='#b44'>(Thompson 2000)</ns0:ref>, which is analogous to findings in central European grasslands <ns0:ref type='bibr' target='#b26'>(Kiss et al., 2017)</ns0:ref>. In intermediate succession stage, there were few shrubs and trees, but herbaceous plants were still abundant, which caused some shade, but the habitats still received abundant sunlight. These conditions were beneficial to the maintenance of seed viability for different plant species <ns0:ref type='bibr' target='#b21'>(Jaganathan and Dalrymple, 2015)</ns0:ref>. Conversely, early and later stages might be slightly drier and wetter, respectively, making them unfavorable to seed viability for some plant species. Therefore, the intermediate stages exhibited the highest species richness in seed banks. The species richness of the different plant life forms in seed banks both before and after field seed germination showed a humped, positive or negative linear shape across these stages. The species richness of ephemeral and perennial herbs across all stages was approximately 2-10 times greater than that of shrubs, vines and trees. These are similar to the levels of species richness reported in second-growth stands, old-growth stands and logged stands in tropical wet forests <ns0:ref type='bibr' target='#b7'>(Dupuy and Chazdon, 1998)</ns0:ref> and in grazed and ungrazed eucalypt woodlands <ns0:ref type='bibr' target='#b13'>(Grant and Macgregor, 2001)</ns0:ref>.</ns0:p><ns0:p>In steppe deserts, ephemeral herbs have been found to account for a much higher percentage (&gt;90%) of the species richness in seed banks than perennial herbs and shrubs (&lt;5%), and the ratio of herbs was considerably higher than that indicated by our results <ns0:ref type='bibr' target='#b6'>(De et al., 2008)</ns0:ref>. The life-form pattern found here also disagrees with that reported in the Santa Genebra Municipal Reserve of Brasil, where trees account for 47.8% of the total species richness, which is much greater than the contributions of herbs and shrubs (6.5% and 16.5%, respectively) (Grombone-Guaratini and Rodrigues, 2002). Manuscript to be reviewed Although there are many reports of species richness in seed banks, the relationship of the species richness in seed banks with the associated aboveground vegetation under decreasing similarity of the species composition across an individual chronosequence is seldom analyzed <ns0:ref type='bibr' target='#b18'>(Hopfensperger, 2007)</ns0:ref>. We conducted an analysis using the data for the species in the karst landscape. The species richness in seed banks after field seed germination significantly increased with increasing species richness of aboveground vegetation under decreasing similarity of the species composition, but the species richness in seed banks before field seed germination was maintained at an almost invariable level. The species richness of shrubs, trees and vines in seed banks also increased with increasing species richness of aboveground vegetation, but the species richness of ephemeral and perennial herbs showed almost no change. These results partially validate hypothesis II. Although we did not intend to clearly differentiate plant species with transient and persistent seed banks, the data on the seed banks before and after field seed germination to some degree represent plant species with transient and persistent seed banks, respectively <ns0:ref type='bibr' target='#b12'>(Funes et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b47'>Walck et al., 2005)</ns0:ref>. Therefore, the above results can indicate that the change in species richness in transient and persistent seed banks differs with increasing species diversity of aboveground vegetation, but the changes in the species richness of shrubs, trees and vines in both transient and persistent seed banks are identical.</ns0:p><ns0:p>Plant diversity in aboveground vegetation can play a great role in ecosystem services (Tilman et al., 1996 Hooper et al., 2005; Davis et al., 2005; Jaganathan et al., 2015; Jo&#235;t et al., 2016). These monotonically increasing relationships between the species richness of aboveground vegetation and seed banks mean that high plant richness in seed banks has a great potential to provide ecosystem services to humans in the long run <ns0:ref type='bibr' target='#b30'>(Loreau and Hector, 2001)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Decreasing seed density and species composition similarity with both community succession and decreasing soil depths is a dominant pattern in karst landscapes. Community succession has a significant impact on the seed density in seed banks before and after field seed germination. The seed density in the seed banks of karst plant communities is relatively high, and there is consequently good potential for the restoration of degraded ecosystems from seed banks. The total species richness in seed banks and the species richness of shrubs, vines and trees increase with increasing species richness of aboveground vegetation. The decreasing species composition similarity between aboveground vegetation and seed banks with the succession of plant communities implies that the natural recovery of degraded ecosystems to relatively stable stages such as SEBF and PEBF is dependent on species dispersal from Manuscript to be reviewed outside area. High plant diversity in aboveground vegetation is beneficial to the maintenance of plant diversity in seed banks. Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure legends</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>; Pakeman and Small, 2005; Li et al., 2005; Ma et al., 2011; Ma et al., 2013). In recent years, qualitative and quantitative studies of seed banks have included more detailed classifications, germination patterns, spatiotemporal patterns of seed banks and mechanisms underlying the persistence of seed banks (Walck et al., 2005; Yan et al., 2010; Joe et al., 2016).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head /><ns0:label /><ns0:figDesc>However, our results regarding the similarity of the species composition with community succession were also different from those of a few studies in European and Chinese grasslands (Marcante et al., 2009; Ma et al., 2011; Martinez-Duro et al., 2012). In these studies, the species composition similarity between seed banks and PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Fig. 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Fig. 1 Different stages of secondary succession in the Guiyang karst landscape. A: GC-I; B: GC-II; C: SGC-I; D: SGC-II; E: TVSF; F: SF; G: SEBF; H: PEBF.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Fig. 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Fig. 2 Changes in species richness in seed banks across different stages of secondary succession. A, B and C are the seed banks before field seed germination at the soil depths of 0-5, 5-10 and 10-15 cm, respectively; D, E and F are the seed banks after field seed germination at the three different soil depths. Each stage of secondary succession corresponds to twenty species richness values obtained from twenty soil samples in one layer of soil (N=160 in each small figure). Species richness shows a normal distribution based on P-P figures. The variance in species richness at different successional stages is homogeneous. *, *, and ** represent significance at confidence levels of 95%, 99%and 99.9%, respectively. X in equations represents succession stages. The notation is the same in the table and the figures below.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Fig. 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Fig.3Species richness of five plant life forms in seed banks before field seed germination (A) and after field seed germination (B). The species richness represented by each pillar is the number of all species of one life form recorded from 60 soil samples (total at three depths; each soil sample is collected from a 10 cm&#215;10 cm plot) in one succession stage. The species richness of all plant life forms shows a normal distribution based on P-P figures. The variance of the species richness for ephemeral and perennial plants (excluding shrubs, vines and trees) in different successional stages is homogeneous.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Fig. 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Fig. 4 Relationship of the species richness in seed banks with the species richness of aboveground vegetation. A, B and C represent species richness in soil seed banks before field seed germination at depths of 0-5, 5-10 and 10-15 cm, respectively; D, E and F represent the soil seed banks after field seed germination at the three depths. The value of each dot in the figures is the mean species richness determined from twenty soil samples collected in each succession stage. The species richness on the x-axis corresponding to each dot in the figures is the mean species richness surveyed from four plots (for woody plants) and 12 subplots (for herb plants) in each succession stage. Note: the species richness of the aboveground vegetation and seed banks is highest in middle succession stages. Species richness shows a normal distribution based on P-P figures. The variance of species richness associated with different levels of the species richness of aboveground vegetation is homogeneous based on statistical tests.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head>Fig. 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Fig.5Relationship of the species richness of different life forms in seed banks with the species richness of aboveground vegetation. A, B, C, D and E represent the ephemeral herbs, perennial herbs, vines, shrubs and trees, respectively, included in seed banks before field seed germination; F, G, H, I, and J represent the ephemeral herbs, perennial herbs, vines, shrubs and trees, respectively, included in seed banks after field seed germination. The values of each dot in the figures are the mean species richness tested from sixty soil samples (total at three soil depths) in each stage of secondary succession. Species richness on the X-axis is the same as in Fig.4. The species richness of all plant life forms shows a normal distribution based on P-P figures. The variance of the species richness at different levels of the species richness of aboveground vegetation is homogeneous based on statistical tests.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_17'><ns0:head>Figure 1 Different</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_18'><ns0:head>Figure 2 Changes</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_19'><ns0:head>Figure 3 Species</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_20'><ns0:head>Figure 4 Relationship</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_21'><ns0:head>Figure 5 Relationship</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48689:2:0:NEW 25 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Responses to reviews v1 Dear Dr. Wang, Thank you for your submission to PeerJ. It is my opinion as the Academic Editor for your article -A study of soil seed banks across one complete chronosequence of secondary succession in a karst landscape - that it requires a number of Minor Revisions. My suggested changes and reviewer comments are shown below and on your article 'Overview' screen. Please address these changes and resubmit. Although not a hard deadline please try to submit your revision within the next 40 days. With kind regards, Victoria Sosa Academic Editor, PeerJ Dear Dr. Sosa Thank you very much for your reviews and opinions about the manuscript. We have revised the manuscript according to your reviews and reviewers` comments. The responses are listed below. Best regards Zhenhong Editor comments (Victoria Sosa) MINOR REVISIONS Thank you very much for considering previous suggestions by reviewers. There are some that still need attention, one of them is to review and change the legend of Figure 2, as well as improve the Discussion and explain the analyses better. Responses: your reviews are nice for improvement of the manuscript. We have considered them. Reviewer 1 (You-Xin Shen) Basic reporting no comment Experimental design no comment Validity of the findings Fig. 2: We can make species richness comparison among different stages of secondary succession by ANOVA and then conduct post hoc test, we can also draw a trend line. However, I cannot understand your mathematic equations. What does the X means in your equations? Can succession stages be numbered? Responses: Thank you very much for your positive review on ANOVA and post hoc test of data. About the mathematic equations, x represents succession stages. The mathematic equations were obtained by the qualitative regression of species richness on succession stages. These succession stages show a gradual change from early to later stage defined by ecologists and represent some qualitative and quantitative ecosystem characteristics. Because these succession stages are monotonically increasing from early stage to later stage in representing some characteristics such as biomass and stability, they can be defined with the increasing number 1, 2, 3, 4, 5, 6, 7, and 8 on X-axis. Consequently, regression analysis can be conducted between species richness and succession stage. The method is defined as qualitative (variable) regression. In morphological anatomy of animals and plant, social science and market investigation, the method is widely used. For example, sociologists study the effects of nationality, sex, education, health and regions on the income of people. These indices are firstly defined as number such as sex: 0 (male) and 1(female); education: 0 (illiteracy), 1(elementary), 2(high school), 3(undergraduate), 4 (master), and (doctor), etc. Then, they can conduct regression analysis. In Excel and SPSS, the qualitative indices (such as succession stages) are listed in the column of independent variable and the quantitative indices are listed in the column of dependent column, we can directly conduct regression analysis. The figure 2 is finished by the method. About 'Can succession stages be numbered?', X in the equations means succession stages. Eight succession stages are numbered by software automatically because they show gradual changes (for the indices of no gradual change in other studies, the value of qualitative indices are assigned by researchers). We added a sentence to explain how the succession stage is numbered in the Data analysis and legend in Fig.2. Comments for the Author It had improved, but fig 2. still need to be reconsidered. Responses: Thank you for your concerns. We have added the sentences in Data analysis to explain how the succession stages were used in regression analysis to establish the equations in Fig. 2 Reviewer 2 (Melisa Rago) Basic reporting no comment Experimental design I found question 1 and 3 are well defined. I consider question 2 would be correct if the manuscript aim was to compare regions, and if such comparison was stated in methods and presented in results. In this case, I suggest to present the comparison among regions only in the discussion, as you did, but not as a question. Responses: Thank you very much for your positive and logical reviews. We have deleted the question 2 to correspond to two primarily sections in Results (bold) and comparison only occurs in Discussion as you reviewed. Data analyses are more detailed now, but I still find them a little confusing: In line 166 you mention “important parameters”, I suggest to mention which parameters you are referring to. For the supplemental Information I, I found that you are referring to the Important Value of Species. As you said in the responses, it is basic information in plant community. So, if you mention it in the methods you should mention the contribution of this index to the aim of the manuscript too, and discuss the most relevant results you found from it. Responses: Here, the important parameters are the IV of plant species and the name of corresponding species listed in table (Supplementary Information I). We have revised the sentence in line 166 in previous manuscript. Actually, the IV mainly contributed to the calculation of similarity index in species composition in aboveground vegetation and seed banks because in the table of Supplementary Information I, we listed all species in each stage in aboveground vegetation. We needed comparison to obtain the number of the common and different species occurred in aboveground vegetation and seed banks and then used Equation (1) to calculate similarity index Cj. We have added sentences to show the contribution of the IV in the sections of Data analysis, Results and Notes under Table 4. See line 163, 234-237 in current revised manuscript. In line 168 you say “the scale of 20 cm x 20 cm plots”. Are you referring to the germination trays? I suggest to refer to the field plot size, is it 10 cm x 10 cm for the three depths? Responses: Yes, we conducted germination experiments in the trays of 20 cm x 20 cm. However, we collected soil in the range of 10 cm x 10 cm plots in field for germination experiments. Seed density was calculated based on the area of 10 cm x 10 cm plots. All calculation was by extrapolation based on 10 cm x 10 cm plots. If it was based on 20 cm x 20 cm plots, seed density would be enlarged four times and the digits of all tables and figure need to be multiplied by 1/4. Sentence in line 168 was confused in previous manuscript. We have corrected here. You are attentive in review. If the sentence is not corrected, it is a big defect in the paper. See line 166 in current revised manuscript. In line 169 you mention “seed viability” and “viable seeds”. I think it would be better to use some terminology as seedlings or germinable fraction of the seed bank, because the seedling emergence method only determines the germinable fraction of the seed bank and fails to detect dormant seeds and those seeds with specific germination environmental requirements, but which are still viable. Responses: your suggestion is very correct. The seeds that can germinate only occupy one section of all viable seeds. Thus, we have revised the sentence per your guidance. See line 166-168. In lines 173-174 “Base on these data, ….” I suggest rewording the expression, because it is confusing. Also, I suggest to mention the scale at which you calculated the similarity, is it total species composition for each succession stage? Responses: we have revised sentence. We have mentioned the scale at which we calculated the similarity. It was total species composition in aboveground vegetation and corresponding seed bank for each succession stage. See line 173-179. In line 180, I suggest change “ life forms” to “species”, maybe you could say “species were classified by their life forms into……” Responses: we have revised per your good suggestion. See line 182. In lines 180-182, I wouldn’t say that “…… is presented in figures”, but it should be clearer that you analyze the relationship between species richness and succession stages through regression. Responses: The sentence seems to be redundant so it was deleted. But other sentences were revised per your review. See 182-190. Validity of the findings The results are in line with the aim and questions and contribute to the hypotheses. I suggest you to check the supplemental information III. I found there are some significant values as .000, do they mean < 0.001? Responses: Yes, it means <0.001. I have changed it into <0.001. I also found that levene test significant is .000, does it also mean < 0.001? If it so, I would interpret that the null hypothesis is rejected, so there is no homogeneity of the variance. In that case you could try some transformation for example, until you check the homogeneity of the variance. Finally, the first column of each table, and the first and second in some of them, have numbers, are they the stages? I suggest clearly state to which stage each number corresponds, or change the numbers to the stages name. Regarding the discussion I think it still needs a little bit of work. Reponses: thank you very much for your guidance of the statistical check and the method of processes. I have done the transformation of data for the check by standardization. After this, the levene test significant is＞0.05. Therefore, null hypothesis is not rejected. I also changed number into the succession stages in Supplementary Information III. In the last table, they could not be changed because the name of succession before and after gemination, I wrote the meanings of the number representing in titles. Discussion has been further improved. In line 290 you say “species diversity”, are you referring to species richness? In lines 290-292, you didn’t measure the seeds that fell to the ground, so it is a speculation and it should identified such as. I found the same kind of expressions in other parts, for example in lines 341-342 “The above-ground vegetation added many seeds to the seed banks”. Please, check them throughout the discussion section. Also, try focusing more in the interpretation of the results than in mentioning them again. In lines 310-311, what did you mean by “….implies that seed dispersal outside of the stages of secondary succession is a natural regeneration strategy for restoring degraded karst landscapes to forests”? Response: Yes, I referred species richness in line 290. I have corrected it into species richness. Two are different to a large extent. I have also revised the similar expression to lines 290-292 and lines 341-342 and focused on the interpretation of actual results throughout Discussion. In lines 310-311, the sentence means “…..implies that seed introduction by dispersal to these eight typical stages of secondary succession is a natural regeneration strategy that is worthy of an attention for restoring degraded karst landscapes to forests.” I have revised. See line 295-296, 314-317. Comments for the Author From my point of view the manuscript “A study of soil seed banks across one complete chronosequence of secondary succession in a karst landscape” improved from the previous version. I consider it is more clear now, especially the background provided, which is in line with the aim, hypotheses, and results. Hypotheses are now well stated and results contribute to them. Responses: Thank you very much for your positive reviews. I suggest to check it again, paying especial attention to the data analysis and the discussion. I also suggest to check some points in the abstract: - I suggest including something about the aboveground sampling. - I suggest not mentioning “Gathering effects of seeds occurring on naked stones in karst habitats explain the observed high seed density to some degree” because it is a speculation but it is not supported by the results. - I couldn’t understand the last sentence “There may be negative feedback among areas of rocky desertification, high seed density and vegetation restoration.” What do you mean? Responses: I have added and revised these sections in Abstract. “There may be negative feedback among areas of rocky desertification, high seed density and vegetation restoration.” means that rocky desertification can result in high ratio of rock naked, this induces seed collection effects of rock, and lastly high seed density in seed banks. It is only a speculation. Therefore, I deleted it. See Abstract in the current revised manuscript. I hope all of these suggestions help you to improve your manuscript. Responses: thank you very much for your reviews, which is very nice. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>In recent years, ozone (O 3 ) concentrations in the southeastern coastal areas of China have shown a gradual upward trend. As precursors and intermediates in the formation of O 3 , carbonyl compounds play key roles in the atmospheric photochemical oxidation cycle. To explore the main pollution characteristics of carbonyl compounds in a typical coastal city in southeast China, ambient samples were collected in Fuzhou (The provincial capital of Fujian province, located on the southeast coast of China) and analyzed using highperformance liquid chromatography with ultraviolet detection. The study was continuously carried out at an urban site (Jinjishan) and a suburban site (Gushan) in Fuzhou from May 8 to 20, 2018. The total concentration of 16 carbonyl compounds at the urban site was 15.45 &#177; 11.18 ppbv, and the total concentration at the suburban site was 17.57 &#177; 12.77 ppbv. Formaldehyde (HCHO), acetaldehyde, and acetone were the main species detected in the samples, and acetone had the highest concentration among the species detected. The suburban site had a higher formaldehyde/acetaldehyde ratio and lower acetaldehyde/propionaldehyde ratio than the urban site, implying that biogenic sources potentially contributed to the carbonyl compound concentrations at the suburban site. The results of an observation-based model showed that anthropogenic hydrocarbons promoted HCHO production on May 17 at the urban site. Compared to biogenic emissions, anthropogenic activity is a more important source of carbonyl compounds.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Carbonyl compounds are precursors of O 3 and secondary organic aerosols, and play key roles in the atmospheric photochemical oxidation cycle. The impact of carbonyl compounds on O 3 pollution has become a hot topic in the field of atmospheric chemistry research <ns0:ref type='bibr' target='#b11'>(Finlayson-Pitts &amp; Pitts, 1997;</ns0:ref><ns0:ref type='bibr' target='#b49'>Zhu et al., 2019)</ns0:ref>. These species can control the generation rates and efficiency of hydroxyl (HO 2 ) and peroxyalkyl (RO 2 ) groups in the atmosphere through their photolysis and reactions with OH radicals. Carbonyls are also important intermediates in the photo-oxidation of volatile organic compounds (VOCs) and important precursors of peroxyacetyl nitrate (PAN) and organic acids, which means they have an important influence on the potential effect of atmospheric oxidation on O 3 pollution.</ns0:p><ns0:p>Carbonyl compounds undergo oxidation reactions with atmospheric oxidants to affect the equilibrium relationship in the photochemical oxidant cycle. At the same time, they are oxidized to form less volatile organic compounds, which gradually enter the particulate phase through condensation and adsorption processes and then form secondary organic aerosols <ns0:ref type='bibr'>(Crutzen and</ns0:ref><ns0:ref type='bibr'>Andreae, 1990, Brey and</ns0:ref><ns0:ref type='bibr'>Fischer, 2016)</ns0:ref>. Carbonyls also have a direct negative impact on human health. Most aldehydes and ketones are strongly irritating, and can cause respiratory infections, sensitization, carcinogenesis, and mutation. Most of the unhealthy symptoms induced by carbonyl compounds are irritation to the eyes and lungs <ns0:ref type='bibr'>(WHO, 2000)</ns0:ref>. Among them, the International Agency for Research on Cancer classifies formaldehyde as the first category of human carcinogens <ns0:ref type='bibr'>(IARC, 2006)</ns0:ref>, which can cause nasopharyngeal cancer <ns0:ref type='bibr'>(IARC, 2004)</ns0:ref>, and may also be related to leukemia <ns0:ref type='bibr' target='#b46'>(Zhang et al., 2009)</ns0:ref>.</ns0:p><ns0:p>Carbonyl compounds are abundant components in ambient air. They are mainly formed by the oxidation of biogenic and anthropogenic hydrocarbons <ns0:ref type='bibr' target='#b49'>(Zhu et al., 2019)</ns0:ref>, and are also directly emitted from natural and anthropogenic sources <ns0:ref type='bibr' target='#b29'>(Singh et al., 1995;</ns0:ref><ns0:ref type='bibr' target='#b38'>Wu &amp; Wang, 2015;</ns0:ref><ns0:ref type='bibr' target='#b39'>Xiang et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b44'>Zarzana et al., 2017)</ns0:ref>. Generally, anthropogenic sources are significant in urban areas. Biological sources of carbonyl compounds are also considered important.</ns0:p><ns0:p>In China, the concentrations of carbonyl compounds in the atmosphere are usually high. For example, the atmospheric concentrations of carbonyl compounds measured in Beijing showed that the environmental level of carbonyl compounds is 3-5 times of that in Hong Kong <ns0:ref type='bibr' target='#b22'>(Pang &amp; Mu, 2006)</ns0:ref>. The concentration of HCHO in Guangzhou is 3 times that in Japan and 2 times that in Hong Kong <ns0:ref type='bibr' target='#b10'>(Feng et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b28'>Sin et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b30'>Tago et al., 2005)</ns0:ref>. The high concentrations of carbonyl compounds may be important contributors to serious atmospheric photochemical pollution in Chinese cities.</ns0:p><ns0:p>Fuzhou is a city with relatively good air quality in China, ranking 6th out of 168 key cities in China for ambient air quality in 2019. However, ozone concentrations show an increasing trend year by year. Fuzhou's current O 3 pollution situation is likely to be a brand-new challenge for China to face after PM 2.5 pollution is controlled. Therefore, the situation in Fuzhou deserves attention. The carbonyl compounds are important precursors of O 3 , and the study of its characteristics is of great significance to the control of O 3 pollution. As important precursors of O 3 , VOCs and NOx have attracted wide attention <ns0:ref type='bibr' target='#b13'>(Hong et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b36'>Wang et al., 2017)</ns0:ref>. However, most research to date has focused on non-methane hydrocarbons and carbonyl compounds have received limited attention. This research focuses on Fuzhou carbonyl compounds to explore their pollution characteristics and their relationship with ozone concentration. In this study, carbonyl compounds in ambient air were investigated using offline 2,4-dinitrophenylhydrazine (DNPH) cartridge sampling with high-performance liquid chromatography (HPLC) analysis. Fuzhou is in the western part of the Taiwan Strait and is subject to weaker winds during the monsoon exchange period in May and is less affected by regional transmission. Sixteen carbonyl compounds were analyzed in samples collected from May 8 to 20, 2018 in Fuzhou.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sampling sites</ns0:head><ns0:p>Two observation sites were chosen on the rooftop of the Jinjishan Environmental Protection Building (Jijishan site: JJS) and in the Gushan Scenic Area (Gushan site: GSS) in the suburbs of Fuzhou, China (Fig. <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>).</ns0:p><ns0:p>Fuzhou is located on the southeast coast of China. The JJS site was located 30 m above the ground at the foot of the southwest Jinjishan mountain in the Jin'an district, Fuzhou. The Jin'an River was located to the west of this site and Jinjishan Park to the northeast. The site was surrounded by residential areas and was considered a typical urban site with no pollution sources. The GSS site was located on the top of the Songtao Building of the Gushan Scenic Area Management Committee. This site was located to the south of the east side of Fuzhou city and north of the Minjiang River. The GSS was selected by China National Environmental Monitoring Center (CNEMC) as a suburban background site as it was surrounded by green trees and had no pollution sources. This site was located about 8 km away from the JJS site.</ns0:p></ns0:div> <ns0:div><ns0:head>Carbonyls sampling and analysis</ns0:head><ns0:p>The sampling and analysis procedures used were based on the Environmental Protection Agency method <ns0:ref type='bibr'>TO-11A (US EPA, 1999)</ns0:ref>. Ambient carbonyls were collected on silica cartridges coated with acidified DNPH (IC-DN3501, Agela Technologies, China). The sampling flow rate was 0.8 L/min. The sampling pumps in this study are all vacuum pumps with a rated voltage of 24v, and soap film flowmeters are used for flow calibration before sampling <ns0:ref type='bibr' target='#b32'>(Zhang et al. 2018)</ns0:ref>. Samples were collected at a 2 h intervals beginning at 00:00 (UTC+8) from May 8 to 20, 2018. The sampling duration was 2 h with 12 atmospheric samples collected each day: 00:00-02:00; 02:00-04:00; 04:00-06:00; 06:00-08:00; 08:00-10:00; 10:00-12:00; 12:00-14:00; 14:00-16:00; 16:00-18:00; 18:00-20:00; 20:00-22:00; 22:00-00:00. A total of 156 carbonyl compound samples were collected at each site. An O 3 scrubber loaded with potassium iodide (KI 140, Agela Technologies, PeerJ reviewing PDF | (2020:06:50164:1:0:NEW 9 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed China) was installed in front of the cartridge to eliminate O 3 . Two cartridges in series were sampled to evaluate the collection efficiency before application to the first sample collection in the field. Over 98% of carbonyls were detected in the first cartridge. After sampling, the cartridges were sealed with Teflon caps immediately, placed in an aluminum foil bag to protect them from light, and stored in a refrigerator (&lt; 4&#176;C). Throughout the sampling process, blank samples were collected at each location. Blank samples were collected by passive sampling, which involved opening a sealed cartridge and placing it in the ambient air at the same time as a cartridge was used for active air sampling. Six cartridges were collected every 12 hours, and the concentration of blank samples with no sampling for 12 hours had been deducted from the concentration of each sample. Two filed blank samples were collected both before and after the sampling process. At the end of the sample collection period, all the samples were transported to the Laboratory of Atmospheric Photochemical Simulation at the Chinese Research Academy of Environmental Sciences (Beijing, China) in a heat-resistant incubator maintained at 0&#176;C and then analyzed within 1 month.</ns0:p><ns0:p>In the sampling cartridges, the ambient carbonyls reacted with DNPH to form stable hydrazone derivatives. These derivatives were eluted slowly from the cartridges into a volumetric flask using 5 mL of acetonitrile (HPLC grade, J.T. Baker, USA). No DNPH or derivatives remained in the cartridges after this elution. Because we several eluted cartridges were chosen to be eluted with 5 ml of acetonitrile again, and no residual carbonyl compounds in the second eluted solutions were detected. This shows that 5 ml of acetonitrile is enough to elute all the carbonyl compounds in the cartridges. The extracts were then analyzed by HPLC (LC20A, Shimadzu, Japan) with UV-Vis detection at 360 nm. The separation column was a Inertsil ODS-P reversed-phase column (250 &#215; 4.6 mm i.d., 5 &#956;m particle size; Shimadzu, Japan) at 40&#176;C. The mobile phase consisted of acetonitrile and water and the following gradient elution was used: 0-20 min, 60% acetonitrile; 20-30 min, 60% to 100% acetonitrile; 30-32 min, 100% to 60% acetonitrile; and 32-40 min, 60% acetonitrile. The total flow rate was 1.0 mL/min and the injection volume was 20 &#956;L. A mixed calibration standard of 15 DNPH-carbonyl derivatives (Supelco, Bellefonte, PA), which contained HCHO, acetaldehyde, acrolein, acetone, propionaldehyde, crotonaldehyde, butyraldehyde, benzaldehyde, isovaleraldehyde, valeraldehyde, o-tolualdehyde, m-tolualdehyde, p-tolualdehyde, hexaldehyde, and 2,5-dimethylbenzaldehyde, and a calibration standard of methacrylaldehyde (MACR) were diluted to 0.03, 0.06, 0.09, 0.15, 0.24, 0.30, and 0.45 &#956;g/mL. Details for the detection of the 16 carbonyl compounds are given in Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Other measurements</ns0:head><ns0:p>The O 3 concentrations were measured by a UV photometric O 3 analyzer (Model 49i, Thermo Fisher Scientific, USA). The NO and NO 2 concentrations were measured by a chemiluminescence instrument (Model 42i, Thermo Fisher Scientific) coupled with a molybdenum oxide catalytic converter. The SO 2 and CO concentrations were measured by a pulsed fluorescence analyzer (Model 43i, Thermo Fisher Scientific) and an infrared absorption analyzer (Model 48i, Thermo Fisher Scientific), respectively. The PM 2.5 concentrations were measured by a multiangle absorption photometer (Model 5012, Thermo Fisher Scientific). The pollutants data (including O 3 , CO, NO 2 , SO 2 , PM 2.5 ) came from the National Environmental Monitoring Station in Fuzhou. All instruments in these sites are maintained by a professional service company every day and are turned on during the carbonyl compound sampling period.</ns0:p><ns0:p>The VOCs concentrations were determined on an O 3 pollution day (May 17) at the JJS site. Four samples were collected in 3.2-L stainless steel canisters at 8:00, 14:00, 18:00, and 21:00 local time. Fifty-seven VOCs species of Photochemical Assessment Monitoring Stations (PAMS) were identified using a gas chromatograph equipped with a flame ionization detector and a mass spectrometry detector (EPA/600-R-98/161, Technical Assistance Document for Sampling and Analysis of Ozone Precursors) at the same laboratory in Chinese Research Academy of Environmental Sciences. Meteorological data for the temperature, relative humidity, wind speed, wind direction, and pressure were obtained from the National Climate Data Center of the National Oceanic and Atmospheric Administration (National Climatic Data Center).</ns0:p></ns0:div> <ns0:div><ns0:head>Observation-based model</ns0:head><ns0:p>For quantification of the in situ photochemical production and sensitivity analysis of carbonyl compounds, an observation-based model (OBM) was utilized in this study. This model has been successfully applied in previous studies <ns0:ref type='bibr' target='#b12'>(He et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b21'>Mellouki et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b40'>Xue et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b41'>Yang et al., 2018;</ns0:ref><ns0:ref type='bibr'>Zhang et al., 2019)</ns0:ref>. Briefly, it is built on the Master Chemical Mechanism, which is a near-explicit mechanism describing the oxidation of 143 primary VOCs together with the latest IUPAC inorganic nomenclature <ns0:ref type='bibr' target='#b18'>(Jenkin et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b26'>Saunders et al., 2003)</ns0:ref>. In this study, the model was updated to the newest version of the Master Chemical Mechanism (MCM website). In the calculations, the observed concentrations of O 3 , NO, NO 2 , SO 2 , CO, and VOCs, and the temperature, relative humidity, and pressure were interpolated to a time resolution of 1 h and processed as the model input data sets. We only analyzed the case at JJS station on May 18, 2018 because of the VOCs data limited.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Concentration level</ns0:head><ns0:p>Fig. <ns0:ref type='figure'>2</ns0:ref> shows the measured time series of major carbonyl compounds, O 3 , NO 2 , SO 2 , CO, PM 2.5 , and meteorological parameters at the JJS and GSS sites in Fuzhou from May 8 to 20, 2018. The average concentrations of O 3 , NO 2 , SO 2 , CO, and PM 2.5 during the observation period at the GSS site were 48.29 ppbv, 6.99 ppbv, 2.67 ppbv, 0.47 ppmv, and 29.40 &#956;g/m 3 , respectively. At the JJS site, the corresponding average concentrations were 40.44 ppbv, 14.18 ppbv, 1.63 ppbv, 0.62 ppmv, and 31.06 &#956;g/m 3 (Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p><ns0:p>During the observation period, the concentrations of carbonyl compounds at the JJS and GSS sites were relatively low from May 8 to 11, and the. This may have been caused by low temperatures (average temperature was 21.3 &#8451;) that were not conducive to the formation of carbonyl compounds or strong southwesterly winds that facilitated dispersion of the pollutants. From May 12 to 18, the carbonyl compound concentrations at the two sites greatly increased, which may have been caused by high temperatures (average temperature was 27.1 &#8451;) and strong easterly winds facilitating the formation and accumulation of pollutants. On May 19 and 20, the temperature dropped and the wind direction changed, which resulted in decreases in the concentrations of carbonyl compounds at the two sites. The O 3 concentration changes were consistent with those for the carbonyl compounds during the observation period. The O 3 concentration remained at a low level from May 8 to 11, greatly increased from May 12 to 18, and slightly decreased on May 19 and 20. In addition, from May 12 to 20, the GSS site showed large diurnal variations in the concentrations of O 3 and the carbonyl compounds, and these concentrations peaked at almost the same time (around noon), which indicated that photochemical reactions were the main contributor to O 3 and carbonyl compound formation during the day at the GSS site. A similar situation was also observed at the JJS site. However, from May 13 to 19 at the JJS site, no obvious daily trends were observed in the carbonyl compound concentrations. These results suggested that anthropogenic sources around the site had considerable contributions in addition to the contribution of photochemical reactions during the day. These observations indicate that the photochemical pollution phenomena occur in Fuzhou. The overall trends for the carbonyl compounds at the two sites were similar, with a peak in the middle of the day, but the carbonyl compound composition varied greatly with time.</ns0:p><ns0:p>Among the carbonyl compounds detected at the GSS site from May 8 to 11, the dominant carbonyl compound was acetaldehyde, followed by HCHO. From May 12 to 13, the concentration of acetaldehyde increased sharply, and the main reason for this was the overall increase in the concentration of carbonyl compounds. In addition, the concentrations of other carbonyl compounds also increased. From May 14 to 17, the concentration of acetaldehyde decreased and that of acetone increased rapidly. The increasing trend of acetone is due to the conversion of acetaldehyde and the gradual accumulation of acetone. In addition, changes in wind direction and the influence of other man-made pollution sources may be the cause of this phenomenon. The concentration of acetone was much higher than that of any other species. During the observation period, the concentrations of the species varied greatly. The daily concentration changes were basically the same, indicating a stable source of the carbonyl compounds. From May 18 to 20, the total concentration of carbonyl compounds declined as the acetone concentration decreased.</ns0:p><ns0:p>From May 8 to 14, the JJS site was similar to the GSS site and the carbonyl compound concentration was relatively low. Starting on May 14, the concentration of acetaldehyde increased greatly and the concentration of acetone increased slightly, which was the main reason for the large increase in the carbonyl compound concentration. From May 15 to 18, the concentration of acetone increased rapidly and it became the main species, followed by acetaldehyde and HCHO, and the concentrations of the compounds continued to increase. From May 18 to 20, the concentration of acetone began to decrease relative to the previous period (May 15 to 18) but the concentration remained high and it was still the dominant species, followed by acetaldehyde and HCHO.</ns0:p><ns0:p>Table <ns0:ref type='table'>3</ns0:ref> shows the average concentrations and ranges of the 16 carbonyl compounds detected at the GSS and JJS sites in Fuzhou. The total average concentration (&#177; standard deviation) of carbonyl compounds at the GSS site was 17.57 &#177; 12.77 ppbv and the range was 1.11-53.22 ppbv. The total average concentration of carbonyl compounds at the JJS site was slightly lower than that at the GSS site, which was 15.45 &#177; 11.18 ppbv with a range of 0.04-46.83 ppbv.</ns0:p></ns0:div> <ns0:div><ns0:head>Diurnal variations in the ambient Carbonyl compounds</ns0:head><ns0:p>Fig. <ns0:ref type='figure'>3</ns0:ref> shows diurnal variation of the total carbonyl compound and O 3 concentrations at the GSS and JJS sites from May 18 to 20, 2018. Both sites showed diurnal variation. It is well-known that atmospheric photochemical reactions are one of the important production routes of carbonyl compounds in ambient air and an important method of O 3 generation. The intensity of solar radiation directly affects reaction rates in atmospheric photochemistry. Therefore, the intensity of solar radiation has an important influence on the concentrations of carbonyl compounds and O 3 . At the same time, anthropogenic emissions are also important and can affect the concentrations of carbonyl compounds, which directly affect the diurnal variation of carbonyl compounds.</ns0:p><ns0:p>Diurnal variation of the total carbonyl compounds at the GSS site showed a distinct single peak during the observation period. Overall, the total concentration of carbonyl compounds was much higher during the day than at night, with concentrations beginning to increase around 05:00 and peaking at around 12:00-14:00 when solar radiation was the strongest. As solar radiation decreased, the concentration decreased rapidly from 14:00 to 19:00 and stabilized after 19:00. From 19:00 to 05:00 the next day, the concentrations of the carbonyl compounds did not vary much and were maintained at low levels relative to those observed during the day. During the observation period, the daily change in the O 3 concentration at the GSS site also showed a single peak, and the trend was similar to that observed for the carbonyl compounds. Diurnal variation at the JJS site was different to that at the GSS site. Generally, variation in the concentrations of carbonyl compounds at the JJS site showed multiple peaks. Similar to the GSS site, the JJS site had higher concentrations of carbonyl compounds during the day than at night; however, the JJS site had much higher concentrations at night (19:00-07:00) than the GSS site, indicating a persistent source of pollution. During the day, the carbonyl compounds showed a peak at 07:00, concentrations then rose from 05:00 to 07:00 before decreasing slightly from 07:00 to 09:00. As solar radiation increased, the concentrations of the carbonyl compounds increased again after 09:00. Between 13:00 and 15:00, the atmospheric photochemical reaction rate reached its daytime peak, and the highest carbonyl compound concentrations were reached at 15:00. From 15:00 to 19:00, as solar radiation decreased, the concentrations of the carbonyl compounds gradually decreased, and between 19:00 to 23:00, a late peak for the carbonyl compounds was Manuscript to be reviewed reached and then the concentrations began to decrease. The diurnal variation of O 3 at the JJS site basically showed a single peak that was consistent with the variation observed for the carbonyl compounds from 9:00 to 19:00. This indicated that the concentrations of the carbonyl compounds were mainly affected by atmospheric photochemical reactions during this period. Fig. <ns0:ref type='figure'>4</ns0:ref> shows diurnal variation of the main carbonyl compounds at the two sites from May 8 to 20, 2018. The overall diurnal variation trend for these compounds was similar to that of the total carbonyl compounds. The concentrations of acetaldehyde and acetone at the GSS site were much higher than those of other species, indicating that this was the main species that affected diurnal variation. The diurnal variation of acetaldehyde at the JJS site was consistent with the change in the total carbonyl compounds, indicating that it was one of the main species that affected the total diurnal variation of carbonyl compounds at the JJS site. In addition, the high concentration of acetone also affected the diurnal variation trend of the total carbonyl compounds at the JJS site to a certain extent.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head>Comparison of urban and suburban stations</ns0:head><ns0:p>The carbonyl compounds at the GSS site, which had less human activity than the JJS site, mainly arise from secondary generation via photochemical reactions. By contrast, at the JJS site, in addition to secondary generation, human activity in the surrounding area has a high contribution to the carbonyl compound concentrations.</ns0:p><ns0:p>The JJS site was located in an urban area, the pollution sources were more complex than at the GSS site, and the carbonyl compound sources may also be more complex. Although the GSS site was located in a forested area with a single main source of carbonyl compounds, it was close to the JJS site and could be affected pollutants transported from other areas. This may be the main reason why the concentration of carbonyl compounds at the GSS site was slightly higher than that at the JJS site. Fig. <ns0:ref type='figure'>5</ns0:ref> shows the average contributions of different carbonyl compounds at the two sites. Acetone was the most abundant carbonyl compound at the GSS and JJS sites, which could be attributed to its chemical stability and long atmospheric lifetime. Acetone released from various sources accumulates in the atmosphere <ns0:ref type='bibr' target='#b0'>(Atkinson, 2000;</ns0:ref><ns0:ref type='bibr' target='#b7'>Dai et al., 2012)</ns0:ref> , and the most important sources are natural sources <ns0:ref type='bibr' target='#b17'>(Janson et al., 2001)</ns0:ref>, with pine trees accounting for a higher share of emissions. Among the anthropogenic sources, motor vehicle exhaust emissions are more significant <ns0:ref type='bibr' target='#b14'>(Ho KF et al., 2015)</ns0:ref>. The average concentration of acetone at the GSS site was 7.45 &#177; 8.13 ppbv (Table <ns0:ref type='table'>3</ns0:ref>), accounting for 42.26% of the total concentration of the 16 carbonyl compounds. The average acetone concentration at the JJS site (6.82 &#177; 8.11 ppbv) (Table <ns0:ref type='table'>3</ns0:ref>) was slightly lower than that at the GSS site, accounting for 44.14% of the total concentration of the 16 carbonyl compounds. These results were comparable to the acetone concentrations measured by <ns0:ref type='bibr'>Yang et al. in Beijing (Yang et al., 2018)</ns0:ref>. They were also similar to the concentrations measured by <ns0:ref type='bibr'>L&#252; et al. in Guangzhou,</ns0:ref> where acetone was one of the species with the highest concentrations <ns0:ref type='bibr' target='#b20'>(L&#252; et al., 2010)</ns0:ref>. The compound with the second highest concentration at the GSS site was acetaldehyde (4.41 &#177; 4.36 ppbv, 25.01% of the total) (Table <ns0:ref type='table'>3</ns0:ref>), and the third was HCHO (2.54 &#177; 2.09 ppbv, 14.41% of the total) (Table <ns0:ref type='table'>3</ns0:ref>). Similar to the GSS site, the species with second highest concentration at the JJS site was acetaldehyde (4.84 &#177; 3.63 ppbv, 31.35% of the total), and the third was HCHO oxidation (1.64 &#177; 0.75 ppbv, 10.64% of the total) (Table <ns0:ref type='table'>3</ns0:ref>). Higher concentration of MACR could be caused by the abundant vegetation at the GSS site, which would produce more MACR than at the JJS site <ns0:ref type='bibr' target='#b9'>(Duane et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b25'>Riemer et al., 1998)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Diurnal variation analysis</ns0:head><ns0:p>The concentration of carbonyl compounds at GSS sites has an obvious single-peak diurnal variation trend, which is basically consistent with the change of solar radiation intensity during a day, indicating that the concentration of carbonyl compounds is mainly caused by atmospheric photochemical reactions. However, there is no significant diurnal variation in the concentration of carbonyl compounds from the whole-time variation at the JSS site, indicating that the concentration of carbonyl compounds is not only influenced by atmospheric photochemical reactions, but also by certain anthropogenic factors.</ns0:p><ns0:p>The highest concentrations of acetone could be observed at the two sites at any time. Atmospheric oxidation affects the atmospheric lifetime of carbonyl compounds. The photolysis reactions of HCHO and acetaldehyde take about 4 h and 6 days, respectively, and their lifetimes initiated by OH radicals are about 1.2 days (HCHO) and 8.8 h (acetaldehyde) <ns0:ref type='bibr' target='#b7'>(Dai et al., 2012)</ns0:ref>. Acetone is more stable and has a longer lifetime (60 days uptake by photolysis and 53 days uptake by reaction with OH radicals) than those of HCHO and acetaldehyde. Therefore, acetone accumulates in the atmosphere easily and its concentration is higher than those of other carbonyl compounds such as HCHO and acetaldehyde <ns0:ref type='bibr' target='#b0'>(Atkinson, 2000;</ns0:ref><ns0:ref type='bibr' target='#b24'>Possanzini et al., 2007)</ns0:ref>. This further explains why the acetone concentration is much higher than other carbonyl compounds.</ns0:p></ns0:div> <ns0:div><ns0:head>Source apportionment of carbonyl compounds using ratio methods</ns0:head><ns0:p>The sources of carbonyl compounds can be roughly determined from the ratio of the concentrations of atmospheric formaldehyde/acetaldehyde (F/A) to that of acetaldehyde/propionaldehyde (A/P) <ns0:ref type='bibr' target='#b27'>(Shepson et al., 1991)</ns0:ref>. Fig. <ns0:ref type='figure'>6</ns0:ref> and Fig. <ns0:ref type='figure'>7</ns0:ref> show statistical analysis of the F/A and A/P ratios during the day and night at the GSS and the JJS sites from May 8 to 21.</ns0:p><ns0:p>The F/A value in the atmosphere is generally between 1-10. Generally, the amount of formaldehyde produced by biogenic-derived hydrocarbons through atmospheric photochemical reactions is higher than the amount of acetaldehyde. Therefore, the F/A ratio is higher in areas with high forest or vegetation coverage than in urban areas <ns0:ref type='bibr' target='#b23'>(Possanzini et al., 1996;</ns0:ref><ns0:ref type='bibr' target='#b27'>Shepson et al., 1991)</ns0:ref>. Overall, the F/A value at the GSS site (daytime: 0.19-1.38, nighttime: 0.10-1.42) first decreased and then increased during the observation period. The GSS site was located in a forested area and there was one main source of carbonyl compounds. However, the F/A values at the GSS site were much lower than those in typical forested areas, which may be related to the regional transportation of pollutants. During the observation period, the F/A value at the JJS site (daytime: 0.18-0.69, nighttime: 0.10-1.43) also first decreased and then increased.</ns0:p><ns0:p>Overall, the F/A value at the GSS site was slightly higher than that at the JJS site during the observation period. This may be because the vegetation coverage at the GSS site was higher than that at the JJS site as the GSS site was in a forested area. Therefore, the F/A value at the GSS site was higher than that at the urban JJS site. However, because the GSS site was located close to an urban area, the F/A value was lower than that in typical forested area because of the impact of pollutant transportation. The F/A values were slightly higher at night than during the day at both sites, which could be attributed to the fact that formaldehyde and acetaldehyde were removed at night mainly by reactions with NO 3 radicals. Acetaldehyde reacted at a higher rate than formaldehyde at night. From May 12 to 13, a sudden increase in the GSS acetaldehyde concentration led to a decrease in its F/A value to slightly lower than that at the JJS site.</ns0:p><ns0:p>Generally, the A/P ratio can be used to indicate the presence of man-made pollutants because propionaldehyde is considered only to be associated with anthropogenic sources <ns0:ref type='bibr' target='#b27'>(Shepson et al., 1991)</ns0:ref>. Therefore, the lower the A/P value, the greater the influence of anthropogenic sources. The A/P at the GSS website was between 2.22-23.64 during the day and 2.20-28.77 at night, while at the JJS site, the A/P was between 2.52-31.62 during the day and 2.99-39.09 at night. Propionaldehyde is mainly related to anthropogenic emissions, and acetaldehyde may come from secondary generation or primary emission. The A/P value at the JJS site was higher than the A/P value at the GSS site. From the A/P ratio, the GSS site seems to be more severely affected by manmade sources, which may be due to the GSS site producing more acetaldehyde. And the GSS site was affected by pollutant transportation from the source area (Table <ns0:ref type='table'>3</ns0:ref>), and the concentration of propionaldehyde was slightly higher than that at the JJS site.</ns0:p><ns0:p>The ratio of the concentrations of atmospheric formaldehyde/acetaldehyde (F/A) and acetaldehyde/propionaldehyde (A/P) can be analyzed the relative contribution of anthropogenic and biogenic sources. However, there were some arguments that the ratios of F/A and A/P often have large variations due to different sources of pollution and meteorological conditions <ns0:ref type='bibr'>(Grosjean, 1992;</ns0:ref><ns0:ref type='bibr' target='#b14'>Ho et al., 2015)</ns0:ref>, thus we should use it with caution. Furthermore, the ratio method also fails to identify different photochemical production. Thus we will discuss the sources of gaseous carbonyls more detail in the next section.</ns0:p></ns0:div> <ns0:div><ns0:head>Source apportionment of carbonyl compounds using observation-based model</ns0:head><ns0:p>Carbonyls production at the JJS site was observed on May 17, 2018 and simulated by an OBM model (Fig. <ns0:ref type='figure'>8</ns0:ref>). The simulated distribution of HCHO from photochemical production was compared with the observed HCHO concentration. Peaks appeared during the day and valleys appeared during the night. This was similar to the trend observed for O 3 , and indicated that the HCHO photochemical reaction had a large contribution during the day. The highest in situ HCHO was 0.64 ppbv/h at 12:00, and this value was lower than those measured in a previous study in Beijing on July 23 and 24, 2008 <ns0:ref type='bibr' target='#b41'>(Yang et al., 2018)</ns0:ref>. One aspect of the figure is of interest, two large increases were observed in HCHO in the early morning and after dusk. Rush hour traffic occurs during these two periods and vehicle emissions are a major source of HCHO at such times <ns0:ref type='bibr' target='#b3'>(Cao et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b34'>Tsai et al., 2014)</ns0:ref>. In addition, the nocturnal boundary layer build ups rapidly after sunset, and unfavorable dilution conditions may contribute to increases in the HCHO concentration <ns0:ref type='bibr' target='#b2'>(Brown &amp; Stutz, 2012)</ns0:ref>.</ns0:p><ns0:p>The highest observed rate of acetaldehyde appeared at dusk, because the major source of acetaldehyde is anthropogenic emission and it accumulated during daytime. But the highest in situ photochemical rate was 0.92 ppbv/h at 11:00 due to higher photolysis rate of acetaldehyde in the afternoon. Acetone has a lower in situ photochemical rate indicated photochemical generation is the minor source of acetone. And it has a higher background value (the lowest value of acetone, about 16 ppbv) , means it may be affected by local pollution sources on this day. Others represent the sum of other carbonyl compounds. Similar to formaldehyde, it affected by photochemical production during the daytime and anthropogenic emission during the nighttime. At 3:00 p.m., the net HCHO generation rate showed a decreasing trend, indicating that the on-site HCHO generation rate was lower than the HCHO destruction rate. In fact, many simulations showed that the concentration of OH radicals was highest in the afternoon during the day <ns0:ref type='bibr' target='#b31'>(Tan et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b50'>Zong et al., 2018)</ns0:ref>. The photolysis of formaldehyde is an important source of OH radicals. Negative values occur when the rate of formaldehyde photolysis is greater than the sum of the production rate and the primary release. It has been reported in many articles that the concentration of formaldehyde decreases between 14:00 and 18:00, and according to the published literature, this phenomenon is most pronounced in summer (de <ns0:ref type='bibr'>Blas et al., 2019;</ns0:ref><ns0:ref type='bibr'>Jiang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b19'>Jiang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b42'>Yang et al., 2019)</ns0:ref>.</ns0:p><ns0:p>Fig. <ns0:ref type='figure'>9</ns0:ref> shows that the model-calculated relative incremental reactivities (RIR) of the major precursors for secondary formation of carbonyl compounds on May 17, 2018. We further identified key precursors by calculating the RIR <ns0:ref type='bibr' target='#b4'>(Cardelino &amp; Chameides, 1995)</ns0:ref>, which has been applied in many previous studies <ns0:ref type='bibr' target='#b32'>(Tan et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b41'>Yang et al., 2018)</ns0:ref>. All VOCs species were categorized as biogenic or anthropogenic hydrocarbons (AHCs). The AHCs were divided into the following four subgroups: alkanes, alkenes, alkynes, and aromatics. All kinds of carbonyl compounds production were VOC-limited, and the dominant position was AHC. The RIRs for the NOx were negative. But the dominant species of different carbonyl compounds were different. Alkenes were dominant and aromatics followed for formaldehyde. For acetaldehyde and other carbonyl compounds, alkanes and alkenes both were important for its chemical generation, followed by aromatics. And alkanes dominate the formation of acetone. Therefore, anthropogenic VOCs emissions should be reduced for carbonyl compounds controlling.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>The characteristics and sources of 16 carbonyls compounds were measured in May 2018 in the southeastern coastal city of Fuzhou, China. The concentration at the urban site was 15.45 &#177; 11.18 ppbv and the concentration at the suburban site was 17.57 &#177; 12.77 ppbv. HCHO, acetaldehyde, and acetone were the main species in Fuzhou city, and acetone had the highest concentration. The F/A and A/P ratios were used to determine the sources of the carbonyl compounds. Suburban areas with high vegetation coverage had high F/A values, whereas urban areas were greatly affected by human activities and the A/P values were higher. HCHO production was VOC-limited, and AHCs were dominant and particularly sensitive to reactive alkenes. The RIR for NOx were negative and NOx would generally have a negative influence on attempts to control HCHO production. In summary, both anthropogenic emission and biogenic emissions sources were important source of OVOCs in Fuzhou, and the impact of anthropogenic emission was greater, deserve more attention in the future control of ozone precursors, both in Fuzhou and other cities of China. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50164:1:0:NEW 9 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='20,42.52,201.82,525.00,353.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='21,42.52,201.82,525.00,191.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='22,42.52,199.12,525.00,210.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='23,42.52,178.87,525.00,196.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='24,42.52,199.12,525.00,308.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,199.12,525.00,308.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='26,42.52,178.87,525.00,333.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='27,42.52,199.12,525.00,403.50' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Detection information of 16 carbonyl compounds by HPLC/UV.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Species</ns0:cell><ns0:cell>Retention time</ns0:cell><ns0:cell>Correlation coefficient</ns0:cell><ns0:cell>Detection limit</ns0:cell><ns0:cell>Quantitation limit</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>(min)</ns0:cell><ns0:cell>(R 2 )</ns0:cell><ns0:cell>(ppbv)</ns0:cell><ns0:cell>(ppbv)</ns0:cell></ns0:row><ns0:row><ns0:cell>Formaldehyde</ns0:cell><ns0:cell>4.97</ns0:cell><ns0:cell>1.0000</ns0:cell><ns0:cell>0.022</ns0:cell><ns0:cell>0.073</ns0:cell></ns0:row><ns0:row><ns0:cell>Acetaldehyde</ns0:cell><ns0:cell>6.24</ns0:cell><ns0:cell>1.0000</ns0:cell><ns0:cell>0.022</ns0:cell><ns0:cell>0.073</ns0:cell></ns0:row><ns0:row><ns0:cell>Acrolein</ns0:cell><ns0:cell>7.83</ns0:cell><ns0:cell>1.0000</ns0:cell><ns0:cell>0.023</ns0:cell><ns0:cell>0.076</ns0:cell></ns0:row><ns0:row><ns0:cell>Acetone</ns0:cell><ns0:cell>8.13</ns0:cell><ns0:cell>1.0000</ns0:cell><ns0:cell>0.026</ns0:cell><ns0:cell>0.085</ns0:cell></ns0:row><ns0:row><ns0:cell>Propionaldehyde</ns0:cell><ns0:cell>8.70</ns0:cell><ns0:cell>1.0000</ns0:cell><ns0:cell>0.028</ns0:cell><ns0:cell>0.092</ns0:cell></ns0:row><ns0:row><ns0:cell>Crotoraldehyde</ns0:cell><ns0:cell>10.55</ns0:cell><ns0:cell>1.0000</ns0:cell><ns0:cell>0.031</ns0:cell><ns0:cell>0.102</ns0:cell></ns0:row><ns0:row><ns0:cell>n-Butyraldehyde</ns0:cell><ns0:cell>12.00</ns0:cell><ns0:cell>0.9998</ns0:cell><ns0:cell>0.035</ns0:cell><ns0:cell>0.104</ns0:cell></ns0:row><ns0:row><ns0:cell>Benzaldehyde</ns0:cell><ns0:cell>13.31</ns0:cell><ns0:cell>0.9994</ns0:cell><ns0:cell>0.036</ns0:cell><ns0:cell>0.109</ns0:cell></ns0:row><ns0:row><ns0:cell>Isovaleraldehyde</ns0:cell><ns0:cell>16.20</ns0:cell><ns0:cell>0.9996</ns0:cell><ns0:cell>0.049</ns0:cell><ns0:cell>0.164</ns0:cell></ns0:row><ns0:row><ns0:cell>Valeraldehyde</ns0:cell><ns0:cell>17.13</ns0:cell><ns0:cell>0.9980</ns0:cell><ns0:cell>0.048</ns0:cell><ns0:cell>0.159</ns0:cell></ns0:row><ns0:row><ns0:cell>o-Tolualdehyde</ns0:cell><ns0:cell>18.32</ns0:cell><ns0:cell>0.9992</ns0:cell><ns0:cell>0.050</ns0:cell><ns0:cell>0.166</ns0:cell></ns0:row><ns0:row><ns0:cell>m-Tolualdehyde</ns0:cell><ns0:cell>18.95</ns0:cell><ns0:cell>0.9982</ns0:cell><ns0:cell>0.050</ns0:cell><ns0:cell>0.166</ns0:cell></ns0:row><ns0:row><ns0:cell>p-Tolualdehyde</ns0:cell><ns0:cell>19.76</ns0:cell><ns0:cell>0.9978</ns0:cell><ns0:cell>0.054</ns0:cell><ns0:cell>0.180</ns0:cell></ns0:row><ns0:row><ns0:cell>Hexaldehyde</ns0:cell><ns0:cell>24.21</ns0:cell><ns0:cell>0.9998</ns0:cell><ns0:cell>0.034</ns0:cell><ns0:cell>0.114</ns0:cell></ns0:row><ns0:row><ns0:cell>2,5-Dimethylbenzaldehyde</ns0:cell><ns0:cell>24.75</ns0:cell><ns0:cell>0.9998</ns0:cell><ns0:cell>0.031</ns0:cell><ns0:cell>0.102</ns0:cell></ns0:row><ns0:row><ns0:cell>MACR</ns0:cell><ns0:cell>11.67</ns0:cell><ns0:cell>0.9994</ns0:cell><ns0:cell>0.033</ns0:cell><ns0:cell>0.110</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot' n='1'>1 SD means standard deviations in pptv 2 BDL: below detection limit PeerJ reviewing PDF | (2020:06:50164:1:0:NEW 9 Sep 2020)</ns0:note> </ns0:body> "

" September 2rd, 2020 Dear Editors We thank the reviewers for their generous comments on the manuscript and have edited the manuscript to address their concerns. Now we submitting this revised manuscript after incorporating reviewer`s comments and making improvements. We believe that the manuscript is now suitable for publication in PeerJ. Yours sincerely, Rui Gao Associate professor of Chinese Research Academy of Environmental Sciences On behalf of all authors. Response to Reviewer 1: Basic reporting The manuscript measured the 16 carbonyls concentration two sites in Beijing in early summer. The authors tried to indicate the contributions of potential sources with ratios and model. Eventually, the manuscript is well written and provides full technical information. However, there were two critical concerns. The first one is the quantification of acetone with DNPH is highly questionable, even this includes in TO-11A method. The artifacts have been widely reported in the recent literatures. So, the uses of acetone ratios and their associated source apportionment are doubtful. The authors should take account this factor. [Reply]: There is a common method for carbonyl compound detections, and many articles have been published by using this method, reference is as follows (Ho et al., 2015; Jiang et al., 2019; Rao et al., 2016; Tang et al., 2019; Yang et al., 2019). To verify the feasibility of this method, we have done a series of experiments before the experiment in this article (Zhang et al., 2019). The results show that the uncertainty of acetone is within 15%. So, we think the result is feasible. Additionally, A/P means acetaldehyde/propionaldehyde, the C3 compounds is propionaldehyde not acetone. The following references were added in the revised manuscript. • Ho, K.F., Ho, S.S.H., Huang, R.J., Dai, W.T., Cao, J.J., Tian, L., Deng, W.J., 2015. Spatiotemporal distribution of carbonyl compounds in China. Environ Pollut 197, 316-324. • Jiang, Z., Zheng, X., Zhai, H., Wang, Y., Wang, Q., Yang, Z., 2019. Seasonal and diurnal characteristics of carbonyls in the urban atmosphere of Changsha, a mountainous city in south-central China. Environ Pollut 253, 259-267. • Rao, Z., Chen, Z., Liang, H., Huang, L., Huang, D., 2016. Carbonyl compounds over urban Beijing: Concentrations on haze and non-haze days and effects on radical chemistry. Atmospheric Environment 124, 207-216. • Tang, G., Chen, X., Li, X., Wang, Y., Yang, Y., Wang, Y., Gao, W., Wang, Y., Tao, M., Wang, Y., 2019. Decreased gaseous carbonyls in the North China plain from 2004 to 2017 and future control measures. Atmospheric Environment 218. • Yang, Z., Cheng, H.R., Wang, Z.W., Peng, J., Zhu, J.X., Lyu, X.P., Guo, H., 2019. Chemical characteristics of atmospheric carbonyl compounds and source identification of formaldehyde in Wuhan, Central China. Atmospheric Research 228, 95-106. • Zhang, X., Li, H., Zhang, C., Zhang, Y., He, Z., Gao, R., Wang, W., 2019. Optimization and Preliminary Application of the Detection Method of Carbonyl Compounds in the Ambient Air. Research of Environmental Sciences (in Chinese) 32, 821-829. Second, very honestly, the data expression and use of C1/C2 and C2/C3 ratios are outdated approaches (>20 years). One advantage of this manuscript is shown the use of OBM. However, this section is very unclear and short. This manuscript must be greatly improved before consideration for publication. [Reply]: 1. The ratio of the concentrations of atmospheric formaldehyde/acetaldehyde (F/A) and acetaldehyde/propionaldehyde (A/P) can be analyzed the relative contribution of anthropogenic and biogenic sources. However, there were some arguments that the ratios of F/A and A/P often have large variations due to different sources of pollution and meteorological conditions (Grosjean, 1992; Ho et al., 2015), thus we should use it with caution. Furthermore, the ratio method also fails to identify different photochemical production. The sources of gaseous carbonyls have been discussed using OBM model in the following section. 2. As suggested by the reviewer, we have supplemented and optimized the manuscript. The modified content was at Line175-185, 387-393 and 396-439 in the revised manuscript. And the following references were added in the revised manuscript. • Grosjean, D., 1992. Discussion: atmospheric concentrations and temporal variations of C1-C3 carbonyl compounds at two rural sites in central Ontario. Atmospheric Environment. Part A. General Topics 26, 349-351. • Ho, K.F., Ho, S.S.H., Huang, R.J., Dai, W.T., Cao, J.J., Tian, L., Deng, W.J., 2015. Spatiotemporal distribution of carbonyl compounds in China. Environ Pollut 197, 316-324. Experimental design Line 215: Acetone could be potentially coeluted with the derivatives formed between air oxidants and DNPH. Please check the following references. Even ozone could be removed by the ozone scrubber, other oxidants such as NO and NO2 reacted with the DNPH during the sampling. Ho, S. S. H.; Ho, K. F.; Liu, W. D.; Lee, S. C.; Dai, W. T., Cao, J. J.; Ip, H.S.S. Atmo. Environ. 2011, 45, 261-265. Schulte-Ladbeck, R.; Lindahl, R.; Levin, J. O.; Karst, U. J. Environ. Monit. 2001, 3, 306-310. Williams, J.; Li, H.; Ross, A.B.; Hargreaves, S.P. Atmo. Environ. 2019, 218, 117019. [Reply]: We did the removal efficiency of the ozone scrubber for ozone, NO and NO2: ozone scrubber was added to the inlet front of the ozone and NO/NO2 monitor. The results show that ozone was removed effectively, but the NO and NO2 monitoring data did not change before and after no addition. At present, many studies have mentioned the TO-11A method and used DNPH to sample acetone, which proved the scientificity and rationality of the method. We have carefully read the literature recommended by the reviewers, and all the references were added in the revised manuscript. The following references were added in the revised manuscript. • Dai WT, Ho SSH, Ho KF, Liu WD, Cao J, and Lee S. 2012. Seasonal and diurnal variations of mono- and di-carbonyls in Xi'an, China. Atmospheric Research 113:102–112 • Yang X, Xue L, Wang T, Wang X, Gao J, Lee S, Blake DR, Chai F, and Wang W. 2018. Observations and Explicit Modeling of Summertime Carbonyl Formation in Beijing: Identification of Key Precursor Species and Their Impact on Atmospheric Oxidation Chemistry. Journal of Geophysical Research: Atmospheres 123:1426-1440 Validity of the findings Line 213: When did these two peaks appear? Noon and when? The authors should also explain their different origins instead of elaborating the differences only. [Reply]: The bimodal phenomenon of the concentration of carbonyl compounds at the JJS site described here is not significant, but rather reflects a persistent high value of its concentration, so we delete the expression of bimodal phenomenon. The phenomenon shows that the carbonyl compounds at this site have no obvious diurnal changes during this period. These results indicate that, in addition to the photochemical reaction during the day, the anthropogenic sources around the site also make a considerable contribution. Based on the above analysis, we delete the expression of bimodal phenomenon in the revised manuscript. The modified content was at Line 211-215 in the revised manuscript. Line 288-289: The discussion on the total quantified carbonyls are not critical. Each carbonyl has unique formation pathways and photochemical reactions. [Reply]: In line 288-289 of manuscript, the total concentration of the 16 carbonyl compounds were discussed, and we focused on the formaldehyde, acetaldehyde and acetone. Figure 4 in revised manuscript shows that species were the highest concentration in a day at the two sites, indicating that they are the main species that affect the daily variation of carbonyl compounds. Line 348-386: The uses of C1/C2 and C2/C3 ratios could be used as references but not accurate indices to illustrate the sources, particularly considering the concentrations of acetone could be overestimated. [Reply]: The ratio method can only roughly estimate whether the source of carbonyl compounds is biased towards anthropogenic sources or natural sources. Therefore, we used the OBM model to further discuss the source of carbonyl compounds. However, our existing technical methods are still unable to provide specific sources of carbonyl compounds. In addition, C3 represents propionaldehyde which is considered only to be associated with anthropogenic emissions (Shepson et al., 1991). The following references were added in the revised manuscript. • Shepson, P.B., Hastie, D.R., Schiff, H.I., Polizzi, M., Bottenheim, J.W., Anlauf, K., et al., 1991. Atmospheric concentrations and temporal variations of C-1 C-3 carbonyl compounds at 2 rural sites in central Ontario. Atmos. Environ. A-Gen. 25 (9), 2001–2015. The molecular number on a chemical formula should be subscripted. Please standardize to use O3/ozone, HCHO/formaldehyde in the entire manuscript. Please aware the scientific figures expressed for all numbers. They are inconsistent. [Reply]: As suggested by the reviewer, we standardized all chemical formulas in the revised manuscript. Ozone and formaldehyde have been changed to O3 and HCHO in the entire manuscript, respectively. And we unified the scientific figures expressed for all numbers in the revised manuscript. Response to Reviewer 2: Basic reporting The paper was very clear, well written and easy to follow. There are a few sentences where there is some confusion in language for the reader and I tried to point this out for improvement. In addition, there were a few places to improve the background context and add context for those familiar with basic atmospheric chemistry but not with the specifics of why it is important to study carbonyls. The raw data and figures were shared and there were a few legends that needed correction or more information, which was pointed out in the detailed comments. But overall, the paper is to the point and direct, the data well presented, easy to follow, which is appreciated, and does not speculate. [Reply]: Many thanks to the reviewer for the comments in annotated manuscript, all the comments were answered in comment section. Experimental design The methods are described in sufficient detail except in a few places where more detail is suggested. I do think some more context is needed on the why it was important to study this city, and how the overall results here compared to other cities in the region or the country. What was the knowledge gap and what do we know now after this study? It seemed there was more that could be concluded from the data and I suggested where in the detailed comments. The sampling methods and chemistry were well done with sufficient information provided to be able to replicate. This was a strong point. [Reply]: Many thanks to the reviewer for the comments in annotated manuscript, all the comments were answered in comment section. Validity of the findings The data are robust and statistically sound. My main suggestions were to describe the differences between sites more in the Methods (it was hard to keep track of which was suburban and which wasn't, plus only 8 km apart, I wondered if they could be considered 'different'), and to provide more context on what the results mean - should there be more research/sampling sites in the area, were these sites adequate to measure air quality in the future, is the city more or less impacted by carbonyls compared to others in the region or country? I was very curious as to the impact of traffic as a source, too. [Reply]: As suggested by the reviewer, we added Google Earth map (Fig. 1, Line 20), and made more comparison between two sites. On the map, we can clearly see the difference between the two sites, although they are only 8km away. Figure 1 Google earth showing the location of JJS and GSS sample sites in Fuzhou I was also curious to know more about the comparison between the model and measurements. The authors were very careful not to speculate, but it is OK to put results in context and think of possible sources, and possible recommendations for the future. [Reply]: There are several models used to study the sources of VOCs (including OVOCS), and we used the OBM model. As suggested by the reviewer in the comment file, we discussed more details about model. The modified content was at Line 396-439 in the revised manuscript. Comments for the author The reader appreciated the study's focus on measurement over modeling. It is critical to still go out into the field and measure to observe. The authors chose a very reproducible method and real world measurements of carbonyls are often lacking. I appreciated this work and look forward to see the revised manuscript. [Reply]: Sampling and monitoring methods for aldehydes and ketones have been studied prior to this study, and this study is a further development of the previous study. • Zhang X, Li H, Zhang CL, et al. Optimization and Preliminary Application of the Detection Method of Carbonyl Compounds in the Ambient Air. Research of Environmental Sciences, 2019, 32(5):821-829. Commented [A1]: Line 52 City? Or Region? Or Province? [Reply]: Fuzhou is the provincial capital of Fujian province, located on the southeast coast of China. The added content was at Line 26-27, and 87-89 in the revised manuscript. Commented [A2]: Line 54 Are the identified named sites within the city of Fuzhou? It is not clear to the reader [Reply]: The observation points of this study are the Jinjishan environmental protection building site (JSS) in the urban area of Fuzhou and the Gushan Scenic Area site (GSS) in the suburbs of Fuzhou. Both sites are in Fuzhou city. The added content was at Line 94-96 in the revised manuscript. Commented [A3]: Line 61 Probably best to spell out as“formaldehyde (HCHO)” instead of listing the formula since the other compound were named. Then afterwards HCHO is OK. [Reply]: As suggested by the reviewer, we have changed HCHO to formaldehyde (HCHO) and other compounds in the revised manuscript. Commented [A4]: Line 79 Very reasonable and straightforward explanation of physical processes in atmosphere. Probably referencing previous research which should be cited. [Reply]: As suggested by the reviewer, the following references were cited in the revised manuscript. The following references were added in the revised manuscript. • Crutzen, P. J.; Andreae, M. O. Biomass burning in the tropics: Impact on atmospheric chemistry and biogeochemical cycles. Science 1990, 250, 1669−1678. • Brey SJ, Fischer EV. Smoke in the City: How Often and Where Does Smoke Impact Summertime Ozone in the United States? Environ Sci Technol. 2016;50(3):1288-94. Commented [A5]: Line 81 Please be specific on irritating to what? Eyes, throat? Sensitizing to what? And please cite references here for the health effects. Are there specific health references from government or epidemiological literature? [Reply]: As suggested by the reviewer, Most of the unhealthy symptoms induced by carbonyl compounds are irritation to the eyes and lungs (WHO, 2000). Among them, the International Agency for Research on Cancer classifies formaldehyde as the first category of human carcinogens (IARC, 2006), which can cause nasopharyngeal cancer (IARC, 2004), and may also be related to leukemia (Zhang et al., 2009). The modified content was at Line 56-60 in the revised manuscript. And the following references were added in the revised manuscript. • WHO, 2000. Air Quality Guidelines for Europe. Regional Office for Europe, Copenhagen, Denmark, pp. 87-91. • IARC, 2006. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans -Formaldehyde, 2-Butoxyethanol and 1-tert-Butoxypropan-2-ol. World Health Organization, International Agency for Research on Cancer, Lyon, France. • IARC, 2004. The IARC Monographs Series e IARC Classifies Formaldehyde as Carcinogenic to Humans e Press Release No. 153. World Health Organization, International Agency for Research on Cancer, Lyon, France. • Zhang, L.P., Steinmaus, C., Eastmond, D.A., Xin, X.J.K., Smith, M.T., 2009. Formaldehyde exposure and leukemia: a new meta-analysis and potential mechanisms. Mutat. Res. Rev. Mutat. Res. 681, 150e168. Commented [A6]: Line 89 Compared to other regions? [Reply]: Here is an example to illustrate that the concentration of carbonyl compounds in some cities in China is higher than that of Japan and Hong Kong. The content was at Line 69-74 in the revised manuscript. Commented [A7]: Line 97 Have other studies been done and why is the study of this particular city important? Perhaps this is the first time or one of the few studies for this city? Or there is another reason to collect the data? It’s always good practice to answer that question for the reader– why this study, in this place? [Reply]: Fuzhou is a city with relatively good air quality in China, ranking 6th out of 168 key cities in China for ambient air quality in 2019. However, ozone concentrations show an increasing trend year by year. Fuzhou's current ozone pollution situation is likely to be a brand-new challenge for China to face after PM2.5 pollution is controlled. Therefore, the situation in Fuzhou deserves attention. The carbonyl compounds are important precursors of ozone, and the study of its characteristics is of great significance to the control of ozone pollution. Research on carbonyl compounds is currently concentrated in heavily polluted areas, such as North China Plain, Yangtze River Delta, and Pearl River Delta areas, but there is almost no research on southeast coast of China. The modified content was at Line 76-81 in the revised manuscript. Commented [A8]: Line 101 And why is it important to receive more attention? Are there air pollution problems in this region that carbonyls may be playing a part in? [Reply]: Many studies have now shown that non-methane total hydrocarbons and carbonyl compounds are important precursors for ozone pollution. This research focuses on Fuzhou carbonyl compounds to explore their pollution characteristics and their relationship with ozone concentration. As the [Reply] of A7, Fuzhou's current ozone pollution situation is likely to be a brand-new challenge for China to face after PM2.5 pollution is controlled. Therefore, the situation in Fuzhou deserves attention. The added content was at Line 76-90 in the revised manuscript. Commented [A9]: Line 105 More justification is needed here on the why: why these dates? What is the knowledge gap this study is filling? See above comment. [Reply]: Fuzhou is in the west of Taiwan Strait. Based on the NCEP global reanalysis field data, we analyzed the monthly mean surface flow fields between the west coast of the Taiwan Strait and the area around Taiwan. We found that in May, during the monsoon exchange period, the wind speed is weak and the wind field is disorganized, and the west coast of the Taiwan Strait and Taiwan have the opportunity to transfer air currents to each other through backwind eddies and mesoscale disturbances. In other months, due to the narrow tube effect in the Taiwan Strait, air pollutants may be transported southward from the northern part of the Taiwan Strait during the northeast monsoon or northward from the southern part of the Taiwan Strait during the southwest monsoon, while air pollutants between the eastern and western shores of the Strait are less likely to be transported laterally. Therefore, we chose to observe in May to minimize the effects of out-of-area transport in order to obtain a local pollution profile. The added content was at Line 87-90 in the revised manuscript. Commented [A10]: Line 113 But aren’t urban sites in general considered “polluted”? At least by traffic if not by industrial sources? Otherwise if neither site has pollution sources why is the JJS site different? [Reply]: JJS site has no typical man-made industrial pollution source. But it is in an urban area, where human activities are frequent, and pollution sources such as traffic sources may be the main cause of air pollution at moment (such as traffic). Commented [A11]: Line 117 How many samples were collected at each site? This is making me wonder if the goal of the study was a comparison between sites? [Reply]: The sampling duration was 2 h with 12 atmospheric samples collected each day: 00:00-02:00; 02:00-04:00; 04:00-06:00; 06:00-08:00; 08:00-10:00; 10:00-12:00; 12:00-14:00; 14:00-16:00; 16:00-18:00; 18:00-20:00; 20:00-22:00; 22:00-00:00. We have added the statement of sampling duration in the revised manuscript. A total of 156 carbonyl compound samples were collected at each site. The added content was at Line 114-118 in the revised manuscript. Commented [A12]: Line 122 Spell out the DNPH for the first time it appears in the paper and then that doesn’t have to be stated beyond DPNH. [Reply]: DNPH had been changed to 2,4-dinitrophenylhydrazine (DNPH) when it appeared for the first time. In addition, our description of DNPH refers to the company that produced it. The modified content was at Line 86 in the revised manuscript. Commented [A13]: Line 125 Please include details on the personal sampling pumps make model and that the flowrates were checked prior to field deployment [Reply]: The sampling pumps in this study are all vacuum pumps with a rated voltage of 24v, and soap film flowmeters are used for flow calibration before sampling. The modified content was at Line 112-113 in the revised manuscript. Commented [A14]: Line 126 For a total of XXX samples per field site. [Reply]: A total of 156 samples were collected for per field site. The added content was at Line 117-118 in the revised manuscript. Commented [A15]: Line 129 After each 2 hour interval? Someone went and got the cartridges? [Reply]: Six cartridges were collected every 12 hours, and the concentration of blank samples with no sampling for 12 hours had been deducted from the concentration of each sample. After collected, the samples would be stored at low temperatures below -4°C. The modified content was at Line 126-127 in the revised manuscript. Commented [A16]: Line 143 How was this checked? Expand [Reply]: Several eluted cartridges were chosen to be eluted with 5 ml of acetonitrile again, and no residual carbonyl compounds in the second eluted solutions were detected. This shows that 5 ml of acetonitrile is enough to elute all the carbonyl compounds in the cartridges. The modified content was at Line 136-139 in the revised manuscript. Commented [A17]: Line 162 For final publication all the numbers need to be subscript PM2.5 should read PM 2.5. Also please discuss limitations of PM measurement using photometer or if research team did any kind of field validation against a reference instrument or filter collection. If not then give specifications of the instrument calibrated from the factory. Were all the real time instruments run during the carbonyl collection? These measurements should be added to Intro that they were measured in this study. Finally, please note if other instruments were calibrated prior to study. [Reply]: As suggested by the reviewer, we have standardized the format of all molecular formulas throughout the manuscript. The pollutants data (including O3, CO, NO2, SO2, PM2.5) came from the National Environmental Monitoring Station in Fuzhou. All instruments in these sites are maintained by a professional service company every day and are turned on during the carbonyl compound sampling period. The modified content was at Line 153-162 in the revised manuscript. Commented [A18]: Line 168 Did another laboratory do this analysis? If so that should be noted in manuscript. If the authors did the analysis then the GC model and detector model and more detail here would need to be provided. It’s unclear to the reader if the VOC was analyzed elsewhere – I think so, at the Chinese Research Academy but please clarify. [Reply]: All the VOCs and VOCs samples were analyzed in our laboratory (Chinese Research Academy of Environmental Sciences). The Fifty-seven VOCs species of Photochemical Assessment Monitoring Stations (PAMS) were identified using a gas chromatograph equipped with a flame ionization detector and a mass spectrometry detector (EPA/600-R-98/161, Technical Assistance Document for Sampling and Analysis of Ozone Precursors). The modified content was at Line 166-170 in the revised manuscript. Commented [A20]: Line 175 Was this expected so that is why the OBM was used? Otherwise this is a result. Also please expand more on the model – more background is needed for the reader. [Reply]： For quantification of the in situ photochemical production and sensitivity analysis of carbonyl compounds, an observation-based model (OBM) was utilized in this study. This model has been successfully applied in previous studies (He et al., 2019; Xue et al., 2014; Yang et al., 2018). Briefly, it is built on the Master Chemical Mechanism, which is a near-explicit mechanism describing the oxidation of 143 primary VOCs together with the latest IUPAC inorganic nomenclature (Jenkin et al., 2003; Saunders et al., 2003). In this study, the model was updated to the newest version of the Master Chemical Mechanism (MCM website). In the calculations, the observed concentrations of O3, NO, NO2, SO2, CO, and VOCs, and the temperature, relative humidity, and pressure were interpolated to a time resolution of 1 h and processed as the model input data sets. Due to the lack of VOCS data, we only analyzed the case in JJS, May 17, 2018. The modified content was at Line 175-185 in the revised manuscript. Commented [A21]: Line 195 Consider reporting the averages in a small table comparing the sites and showing the +/- standard error for the n= ???. OK the authors did this, so OK. Thank you. [Reply]: As suggested by the reviewer, we added Table 2, reporting this information in the revised manuscript. Compound Mean ±SD1 Number of samples GSS JJS GSS JJS PM2.5 (μg/m3) 29,40±18.83 31.06±19.36 n=311 n=311 SO2 (ppb) 2.67±0.34 1.65±0.66 n=311 n=311 O3 (ppb) 48.29±18.03 40.70±25.37 n=311 n=311 CO (ppm) 0.47±0.09 0.63±0.14 n=311 n=311 NO2 (ppb) 6.99±4.15 14.22±8.45 n=311 n=311 n:including samples below the detection limit of the instrument, but this part of the samples are not included in the calculation Also some ideas for organization - break out the results into– Time Series Concentration as one section. [Reply]: As suggested by the reviewer, add subheadings in the necessary places, with reference to the intent of the journal. Commented [A22]: Line 206 The diurnal variation in O3 supports smog formation? [Reply]: The O3 concentration reflects the intensity of atmospheric photochemical reaction to a certain extent. Ozone is a secondary product, which is often used as a photochemical indicator in research, and the diurnal variation of ozone is a characterization of the formation of photochemical smog. The following references were in the manuscript. • Xue L, Wang T, Louie PK, Luk CW, Blake DR, and Xu Z. 2014. Increasing external effects negate local efforts to control ozone air pollution: a case study of Hong Kong and implications for other Chinese cities. Environmental Science & Technology 48:10769-10775. Commented [A23]: Line 217 Re-state the trends briefly so the reader doesn’t have to go back and figure it out. [Reply]: As suggested by the reviewer, we rewrite the trends. The specific introduction has been presented from line 216 to 217. Commented [A24]: Line 225 This is super interesting and I am eager to read your thoughts on this. [Reply]: As shown is Fig.2 in revised manuscript, from May 14 to May 17 in the JJS site, the concentration of acetaldehyde was progressively decreasing, but the tendency for acetone to increase over the same period was, we suspect, due to a decrease in acetaldehyde with conversion and a progressive accumulation of acetone. Moreover, the change of wind direction and the influence of other anthropogenic pollution sources may be the cause of this phenomenon. The modified content was at Line 224-226 in the revised manuscript. Commented [A25]: Line 227 This is a little unclear – varied yet consistent. ? Please reword. [Reply]: The consistency of the changes in the concentration of each species is not strong, so the statement 'and showed strong regularity' is deleted. The modified content was at Line 226 to 228 in the revised manuscript. Commented [A26]: Line 241 This might have addressed my comment above on including a Table, so that is great! [Reply]: As suggested by the reviewer, we added Table 2. Commented [A27]: Line 248 Correct spelling error in graph and y axis carbonyl. [Reply]: As suggested by the reviewer, we have modified the graph. Commented [A28]: Line 254 This is reading like a combined Results and Discussion section. Which is fine to me but I amnot clear if this is the intent of the paper or journal? Should results be just results? Or results placed in context? [Reply]: We wrote this passage with reference to the intent of the journal. Commented [A29]: Line 295 Referring back to making this point in Intro that a comparison will be done between two different sites [Reply]: As suggested by the reviewer, we added Google Earth map (Fig. 1), and made more comparison between two sites. The modified content was at Line 94-96 and 104-105 in the revised manuscript. Figure 1 Google earth map showing the location of the Fuzhou sample sites of JJS and GSS. Commented [A30]: Line 296 So is the GSS site more remote and less impacted by people? It seems that would be clearer to state. [Reply]: The GSS site was selected by China National Environmental Monitoring Center (CNEMC) as a suburban background site. It was surrounded by green trees and had no pollution sources. Yes, the GSS site more remote and less impacted by people. Commented [A31]: Line 298 This cannot be truly proven as fact though, though it seems a reasonable hypothesis if the JJS site is located nearer to traffic. Expand and clarify. [Reply]: The ratio method and the OBM model method were used to discuss this phenomenon. As suggested by the reviewer, we expand and clarify this in line 380-393 and 396-439. Commented [A32]: Line 304 I think the paper would benefit from more discussion/description of the specifics of the JJS and GSS in the Methods section. Even a Google Earth view would be helpful. [Reply]: As suggested by the reviewer, we added Google Earth map (Fig. 1), and made more comparison between two sites. The modified content was at Line 94 to 96, and 104-105 in the revised manuscript. Commented [A33]: Line 310 Expand for reader – what types of sources? Car emissions, consumer products, paints, biogenic? [Reply]: The most important sources are natural sources, with pine trees accounting for a higher share of emissions (Janson et al., 2001). Among the anthropogenic sources, motor vehicle exhaust emissions are more significant (Ho KF et al., 2015). The modified content was at Line 310-313 in the revised manuscript. And the following references were in the manuscript. • Janson R, de Serves C. Acetone and monoterpene emissions from the boreal forest in northern Europe. Atmos Environ. 2001;35(27):4629-37. • Ho KF, Ho SSH, Huang RJ, Dai WT, Cao JJ, Tian L, et al. Spatiotemporal distribution of carbonyl compounds in China. Environ Pollut. 2015;197:316-24. Commented [A34]: Line 314 Very interesting why both sites had similar results here with mainly acetone as dominant species. Seems like an important finding to expand on. Is acetone more stable in the atmosphere and thus the sites not far enough apart for changes to be observed over 8 km? [Reply]: Acetone was the most abundant carbonyl compound at the GSS and JJS sites, which could be attributed to its chemical stability and long atmospheric lifetime. The phenomenon of acetone as the dominant species is present in many studies, We found the same thing and offered our conjecture on the situation in Fuzhou. • Chi Y, Feng Y, Wen S, Lü H, Yu Z, Zhang W, et al. Determination of carbonyl compounds in the atmosphere by DNPH derivatization and LC–ESI-MS/MS detection. Talanta. 2007;72(2):539-45. • Yang Z, Cheng HR, Wang ZW, Peng J, Zhu JX, Lyu XP, et al. Chemical characteristics of atmospheric carbonyl compounds and source identification of formaldehyde in Wuhan, Central China. Atmospheric Research. 2019;228:95-106. Commented [A35]: Line 316 For the reader who may not know all the details of photochemical reactions for smog – is acetone a key player so that is the importance of this result and why the authors are comparing it to other researchers in the literature? Expand for reader. [Reply]: Because the concentration of acetone at both sites is much higher than that of other carbonyl compounds, we compare the results of other people's studies on acetone here. Commented [A36]: Line 323 This seems really important and needing more explanation on the significance to atmospheric oxidation. [Reply]: As suggested by the reviewer, the modified content was at Line 337-345 in the revised manuscript. Commented [A37]: Line 327 Does isoprene come from vegetation emissions? [Reply]: Isoprene is a landmark product of plant origin. The following references were in the manuscript. • Duane M, Poma B, Rembges D, Astorga C, and Larsen B. 2002. Isoprene and its degradation products as strong ozone precursors in Insubria, Northern Italy. Atmospheric Environment 36:3867-3879. • Riemer D, Pos W, Milne P, Farmer C, Zika R, Apel E, Olszyna K, Kliendienst T, Lonneman W, Bertman S, Shepson P, and Starn T. 1998. Observations of nonmethane hydrocarbons and oxygenated volatile organic compounds at a rural site in the southeastern United States. Journal of Geophysical Research 1032:28111-28128. Commented [A38]: Line 337 I didn’t see that same trend in the figures. It seems JJS site carbonyl trends were more flat than GSS site…not sure if these conclusions are supported. Grammar/organization needs attention in this paragraph which might help with clearer description of conclusions. [Reply]: The concentration of carbonyl compounds at GSS sites has an obvious single-peak diurnal variation trend, which is basically consistent with the change of solar radiation intensity during a day, indicating that the concentration of carbonyl compounds is mainly caused by atmospheric photochemical reactions. However, there is no significant diurnal variation in the concentration of carbonyl compounds from the whole-time variation at the JSS site, indicating that the concentration of carbonyl compounds is not only influenced by atmospheric photochemical reactions, but also by certain anthropogenic factors. As suggested by the reviewer, this part was rewrite to be clearer (Line 329-335 in the revised manuscript). Commented [A39]: Line 340 Is this how long it takes for the reactions to begin in the atmosphere? [Reply]: Here it is shown that photolysis occurs and in the presence of OH radicals, i.e., the level of atmospheric oxidation affects the atmospheric lifetime of carbonyl compounds. In some studies, this is referred to as the atmospheric lifetime. As suggested by the reviewer, the modified content was at Line 337-338 in the revised manuscript. The following references were in the manuscript. • Dai WT, Ho SSH, Ho KF, Liu WD, Cao J, and Lee S. 2012. Seasonal and diurnal variations of mono- and di-carbonyls in Xi'an, China. Atmospheric Research 113:102–112. Commented [A40]: Line 344 Yes, I think this sentence is much clearer for the reader than the sentence above. [Reply]: As suggested by the reviewer, we rewrite the above sentences to be much clearer. The modified content was at Line 329-335 in the revised manuscript. Commented [A41]: Line 346 Explain again why the accumulation of acetone is important, what is the implication of this (needs to be somewhere in this section, per feedback above) [Reply]: This part further explains why the acetone concentration is much higher than other carbonyl compounds. Commented [A42]: Line 368 What is the implication of this finding? [Reply]: The value of F/A in forest areas is slightly larger than that in urban areas. This study fits this feature. As suggested by the reviewer, we explained the reason for this phenomenon in lines 353-357 in the revised manuscript. Commented [A43]: Line 375 The graphs in F/A and A/P need to have the colors explained in the legend, which color for formaldehyde, etc. [Reply]: Figure 6 in revised manuscript is a graph of the F/A values of the GSS site and the JJS site. The colors in the legend are used to distinguish different sites and day and night differences. Figure 7 is a graph of A/P values of GSS site and JJS site, and the legend is consistent with Figure 6. Commented [A44]: Line 386 Discuss the implications of the results. What are the human activities that are contributing? What are implications for air pollution formation, smog formation? [Reply]: The ratio method can only roughly judge the source of carbonyl compounds, and cannot accurately trace its source effects. Therefore, in the following, we tried to use the OBM model to continue to explore the source of carbonyl compounds. The modified content was at Line387-393 in the revised manuscript. Commented [A45]: Line 399 This was a really strong paragraph, explained the implications well. [Reply]: Thanks for the reviewer`s comments. Commented [A46]: Line 400 Why is there a dip in HCHO at 3 pm (as measured) compared to the predicted increase in the HCHO model prediction at the same time? [Reply]: At 3:00 p.m., the net HCHO generation rate showed a decreasing trend, indicating that the on-site HCHO generation rate was lower than the HCHO destruction rate. In fact, many simulations showed that the concentration of OH radicals was highest in the afternoon during the day (Tan et al., 2019; Zong et al., 2018). The photolysis of formaldehyde is an important source of OH radicals. Negative values occur when the rate of formaldehyde photolysis is greater than the sum of the production rate and the primary release. The modified content was at Line 418-423 in the revised manuscript. Commented [A47]: Line 411 What was the concentration predicted by the model and how did it compare to measured HCHO? [Reply]: It has been reported in many articles that the concentration of formaldehyde decreases between 14:00 and 18:00, and according to the published literature, this phenomenon is most pronounced in summer (de Blas et al., 2019; Jiang et al., 2016; Jiang et al., 2019; Yang et al., 2019). The modified content was at Line 423-426 in the revised manuscript. The following references were added in the revised manuscript. • N., Iza, J., Gangoiti, G., de Cámara, E.S., 2019. Summertime high resolution variability of atmospheric formaldehyde and non-methane volatile organic compounds in a rural background area. Science of the Total Environment 647, 862-877. • Jiang, Z., Grosselin, B., Daele, V., Mellouki, A., Mu, Y., 2016. Seasonal, diurnal and nocturnal variations of carbonyl compounds in the semi-urban environment of Orleans, France. Journal of Environmental Sciences 40, 84-91. • Jiang, Z., Zheng, X., Zhai, H., Wang, Y., Wang, Q., Yang, Z., 2019. Seasonal and diurnal characteristics of carbonyls in the urban atmosphere of Changsha, a mountainous city in south-central China. Environ Pollut 253, 259-267. • Tan, Z., Lu, K., Hofzumahaus, A., Fuchs, H., Bohn, B., Holland, F., Liu, Y., Rohrer, F., Shao, M., Sun, K., Wu, Y., Zeng, L., Zhang, Y., Zou, Q., Kiendler-Scharr, A., Wahner, A., Zhang, Y., 2019. Experimental budgets of OH, HO&lt;sub&gt;2&lt;/sub&gt;, and RO&lt;sub&gt;2&lt;/sub&gt; radicals and implications for ozone formation in the Pearl River Delta in China 2014. Atmospheric Chemistry and Physics 19, 7129-7150. • Yang, Z., Cheng, H.R., Wang, Z.W., Peng, J., Zhu, J.X., Lyu, X.P., Guo, H., 2019. Chemical characteristics of atmospheric carbonyl compounds and source identification of formaldehyde in Wuhan, Central China. Atmospheric Research 228, 95-106. • Zong, R., Xue, L., Wang, T., Wang, W., 2018. Inter-comparison of the Regional Atmospheric Chemistry Mechanism (RACM2) and Master Chemical Mechanism (MCM) on the simulation of acetaldehyde. Atmospheric Environment 186, 144-149. Commented [A49R48]: Line 425 It also seems that there wasn’t a big difference between the sites, so that regional contributions of carbonyls and VOCs are important. How does Fuzhou compare to other cities in China with respect to air pollution? More or less polluted? This seems very important to put into context to conclude the paper. [Reply]: As the [Reply] of A7, China can draw inspiration for future ozone pollution prevention and control from Fuzhou's experience with ozone pollution prevention and control. The modified content was at Line 452-453 in the revised manuscript. Response to Reviewer 3: Basic reporting This work investigated carbonyl compounds in ambient air in a coastal city (Fuzhou) in southeast China. Air samples were collected at an urban site (Jinjishan) and a suburban site (Gushan). The average total concentration of 16 carbonyl compounds at the urban site was 15.45 ± 11.18 ppbv, and the average total concentration at the suburban site was 17.57 ± 12.77 ppbv. Formaldehyde, acetaldehyde, and acetone were the main species detected in the samples, and acetone had the highest concentration among the species detected. The suburban site had a higher formaldehyde/acetaldehyde ratio and lower acetaldehyde/propionaldehyde ratio than the urban site, implying that biogenic sources potentially contributed to the carbonyl compound concentrations at the suburban site. The results are interesting in general. However, there are many errors and language issues that require a major revision. [Reply]: Many thanks to the reviewer for the comments. Errors pointed out by the reviewers were corrected one by one, and textual errors throughout the text were carefully checked and corrected. Experimental design 1. Line 125, what was the sampling time? 2 hours? Please specify sampling time. [Reply]: The sampling duration was 2 h with 12 atmospheric samples collected each day: 00:00-02:00; 02:00-04:00; 04:00-06:00; 06:00-08:00; 08:00-10:00; 10:00-12:00; 12:00-14:00; 14:00-16:00; 16:00-18:00; 18:00-20:00; 20:00-22:00; 22:00-00:00. We have added the statement of sampling duration in the revised manuscript. As suggested by the reviewer, the added content was at Line 114-118 in the revised manuscript. 2.Was there any stability measurement for the samples stored for up to month? [Reply]: This study strictly follows the TO-11A related quality control standards. Immediately after sampling, each cartridge was removed from the sampling system and stored in a refrigerator at (<-4°C). All samples are returned to the laboratory in a cold container and stored in a refrigerator at (<-4°C) until analysis. Refrigeration period prior to analysis did not exceed 2 weeks. Then each cartridge was extracted with 5 mL of acetonitrile, and the sample eluates were stable at -4°C for up to one month. Validity of the findings 3. Table 2, acrolein should not be 0. It might be due to within one month storage and transport. Please use below detection limit instead of 0. [Reply]: As suggested by the reviewer, we have changed the statement of acrolein concentration to below detection limit in the revised manuscript. As suggested by the reviewer, table 2 was modified. 4. Line 377 to 386, it states that “the lower the A/P value, the greater the influence of anthropogenic sources. The conclusion that “The A/P value at the JJS site was higher than the A/P value at the GSS site, indicating that the JJS site is was affected more by human activity than the GSS site.” is contradictory to the statement. [Reply]: The expression is wrong here and has been modified. The ratio method can only be used as a reference, and cannot accurately reflect the source of carbonyl compounds. Therefore, we introduce the OBM model analysis below. As suggested by the reviewer, the modified content was at Line 380-383, and the OBM model analysis were at line 396-439 in the revised manuscript. 5.Also in the abstract about A/P value and GSS lower acetaldehyde/propionaldehyde ratio than the urban site, implying that biogenic sources potentially contributed to the carbonyl compound concentrations at the suburban site. [Reply]: Biological sources may cause higher formaldehyde/acetaldehyde ratio and acetaldehyde/propionaldehyde ratio. 6. Line 198, Please specify low and high temperature such as in Fig. 1. [Reply]: In this research, low temperature and high temperature are a relative concept. As shown in Figure 1, the average temperature of the two sites during the observation period from the May 8 to the 11 is lower than that of May 12 to 18. Lower temperatures are usually accompanied by lower solar radiation intensity, which is not conducive to the formation of carbonyl compounds. As suggested by the reviewer, the modified content was at Line 196-199 in the revised manuscript. Comments for the author 7. There are many errors and language issues in the manuscript. Line 91: 3-5 times that of Hong Kong changes to 3-5 times of that in Hong Kong. Line 94, delete high activities in “The high concentrations high activities of carbonyl… Table 1 and 2: Spelling errors for crotonaldehyde. [Reply]: As suggested by the reviewer, we have changed all these errors. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>In some countries, anabolic-androgenic steroid abuse is rampant among adolescent boys and young men, including some of those seeking physical fitness and/or pleasing appearance through various exercise types. This tactic carries the risk of severe harmful health effects, including liver injury. Most anabolic-androgenic steroid stacking protocols employed are based on the use of the 'prototypic' anabolic-androgenic steroid testosterone and/or its esters. There is a vast body of data on the effects of anabolicandrogenic steroids' abuse combined with physical exercise training on the liver antioxidant barrier in adult subjects, whereas those concerning adolescents are scant. This study aimed at assessing, in adolescent male Wistar rats undergoing a 6-week moderateintensity endurance training (treadmill running), the influence of concurrent weekly supplementation with intramuscular testosterone enanthate (TE, 8 or 80 mg/kg body weight/week) on selected indices of liver status and oxidative stress. The rats were sacrificed, and their livers and blood samples were harvested two days after the last training session. High-dose TE treatment significantly reduced body and liver weight gains.</ns0:p><ns0:p>Neither low-dose nor high-dose TE treatment affected liver &#945;-tocopherol or &#947;-tocopherol content, whereas low-dose TE treatment significantly lowered hepatic reduced glutathione content. TE treatment significantly elevated liver thiobarbituric acid-reactive substances content and blood activities of alkaline phosphatase and &#947;-glutamyltransferase, but not of aspartate aminotransferase or alanine aminotransferase. Liver catalase activity was lowered by &gt;50% in both TE-treated groups, while superoxide dismutase activity was significantly but slightly affected (-15%) only by the high-dose TE treatment. Glutathione</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Endurance training (EndTr) plays a key role in various endurance sports, e.g., cross-country skiing, long-distance running, and cycling. However, it can also be a vital addition to both bodybuilding (M. Barroso. 8 tips for balancing bodybuilding and endurance training; for the URL, see &lt;WWW-references.docx&gt; in Supplemental Files) and strength training, particularly in team sports <ns0:ref type='bibr' target='#b12'>(Coffey &amp; Hawley, 2017)</ns0:ref>. It also gets growing attention from the general public as a health-promoting factor when used in moderation <ns0:ref type='bibr' target='#b19'>(Fikenzer et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b51'>Ruegsegger &amp; Booth, 2018)</ns0:ref>; the positive effects of the training also concern liver health <ns0:ref type='bibr' target='#b57'>(Shephard &amp; Johnson, 2015)</ns0:ref>. Some adolescents and young adults, mostly males <ns0:ref type='bibr' target='#b32'>(Kanayama &amp; Pope, 2018;</ns0:ref><ns0:ref type='bibr' target='#b29'>Johnston et al., 2019)</ns0:ref>, combine endurance-oriented physical training with the use of testosterone and/or its synthetic derivatives termed anabolic-androgenic steroids (AAS). The main goal of this tactic is a faster reduction of body fat and boosting muscularity with the idea of improving physical performance and appearance <ns0:ref type='bibr' target='#b26'>(Hartgens &amp; Kuipers, 2004;</ns0:ref><ns0:ref type='bibr' target='#b32'>Kanayama &amp; Pope, 2018)</ns0:ref>, and hence self-esteem. A positive correlation of the bodily effects with dosage inspires AAS abuse at high doses. Some endurance athletes reported the effectiveness of AAS for accelerating the recovery after intense physical exercises <ns0:ref type='bibr' target='#b26'>(Hartgens &amp; Kuipers, 2004)</ns0:ref>. AAS were also reported to improve running endurance in male rats <ns0:ref type='bibr' target='#b67'>(Van Zyl, Noakes &amp; Lambert, 1995;</ns0:ref><ns0:ref type='bibr' target='#b22'>Georgieva &amp; Boyadjiev, 2004</ns0:ref>), but no positive AAS effect on endurance or blood serum markers recovery was seen in other rat studies <ns0:ref type='bibr' target='#b15'>(Delgado, Saborido &amp; Megias, 2010)</ns0:ref> or healthy men <ns0:ref type='bibr' target='#b3'>(Baume et al., 2006)</ns0:ref>.</ns0:p><ns0:p>Xenobiotics and excess endobiotics are mostly processed and removed by the liver; this situation renders this organ the critical site of steroid toxicity <ns0:ref type='bibr' target='#b52'>(Russmann, Kullak-Ublick &amp; Grattagliano, 2009;</ns0:ref><ns0:ref type='bibr' target='#b69'>Vinken et al., 2013)</ns0:ref>. The abuse of AAS and their 'prototypic' testosterone is associated with a variety of severe adverse health effects <ns0:ref type='bibr' target='#b26'>(Hartgens &amp; Kuipers, 2004;</ns0:ref><ns0:ref type='bibr' target='#b66'>van Amsterdam, Opperhuizen &amp; Hartgens, 2010;</ns0:ref><ns0:ref type='bibr' target='#b68'>Vanberg &amp; Atar, 2010)</ns0:ref>, including a number of those directly linked to liver injury <ns0:ref type='bibr' target='#b52'>(Russmann, Kullak-Ublick &amp; Grattagliano, 2009;</ns0:ref><ns0:ref type='bibr' target='#b6'>Bond, Llewellyn &amp; Van Mol, 2016;</ns0:ref><ns0:ref type='bibr' target='#b62'>Solimini et al., 2017)</ns0:ref>. A growing body of data links this damage to a variety of genomic and nongenomic actions of these drugs, including enhanced generation of reactive oxygen species and lipid peroxidation, and the related activation of cellular stresssignaling pathways <ns0:ref type='bibr' target='#b52'>(Russmann, Kullak-Ublick &amp; Grattagliano, 2009;</ns0:ref><ns0:ref type='bibr' target='#b9'>Cerretani et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b6'>Bond, Llewellyn &amp; Van Mol, 2016)</ns0:ref>. Disruption of redox homeostasis is a well-established event in both drug hepatotoxicity and various liver diseases <ns0:ref type='bibr' target='#b11'>(Cicho&#380;-Lach &amp; Michalak, 2014;</ns0:ref><ns0:ref type='bibr' target='#b38'>Li et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b1'>Arauz, Ramos-Tovar &amp; Muriel, 2016)</ns0:ref>. The primary sources of reactive oxygen species, the noxious mediators of oxidative stress, are cytochrome P450 enzymes of the endoplasmic reticulum and mitochondria <ns0:ref type='bibr' target='#b23'>(Guengerich, 2008;</ns0:ref><ns0:ref type='bibr' target='#b31'>Jones, 2008)</ns0:ref> and several enzymes present in peroxisomes that abound in the liver <ns0:ref type='bibr' target='#b9'>(Cerretani et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b11'>Cicho&#380;-Lach &amp; Michalak, 2014)</ns0:ref>.</ns0:p><ns0:p>Hepatocytes carry several systems capable of preventing or limiting the adverse effects of enhanced oxidative stress <ns0:ref type='bibr' target='#b31'>(Jones, 2008;</ns0:ref><ns0:ref type='bibr' target='#b21'>Frankenfeld et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b58'>Sies, 2015)</ns0:ref>. These systems include various antioxidant enzymes, e.g., glutathione peroxidase (GPx), glutathione reductase (GR), superoxide dismutase (SOD) and catalase (CAT), and low molecular weight antioxidants, e.g., tocopherols and reduced glutathione (GSH) that act mostly in lipophilic and hydrophilic milieus, respectively. Data on the effects of AAS abuse combined with physical exercise training on the liver antioxidant barrier in adolescent subjects are scarce <ns0:ref type='bibr' target='#b41'>(Molano et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b48'>Pey et al., 2003)</ns0:ref>. Adolescence is a period when some people, mainly boys, become familiar with AAS as drugs of abuse. It is also a period of essential changes in androgen catabolism in men <ns0:ref type='bibr' target='#b27'>(Horst, Bartsch &amp; Dirksen-Thiedens, 1977;</ns0:ref><ns0:ref type='bibr' target='#b4'>Belgorosky &amp; Rivarola, 1987a;</ns0:ref><ns0:ref type='bibr' target='#b5'>Belgorosky &amp; Rivarola, 1987b;</ns0:ref><ns0:ref type='bibr' target='#b64'>St&#225;rka, Posp&#237;silov&#225; &amp; Hill, 2009)</ns0:ref>, which condition may significantly modify the outcome of androgen action <ns0:ref type='bibr' target='#b40'>(Mantovani &amp; Fucic, 2014)</ns0:ref>.</ns0:p><ns0:p>Our earlier study on the effects of long-term testosterone treatment on the liver antioxidant barrier and some blood markers of liver injury in sedentary adolescent male rats showed some signs of enhanced liver oxidative stress and toxicity but no potential lasting harm <ns0:ref type='bibr' target='#b54'>(Sadowska-Kr&#281;pa et al., 2017)</ns0:ref>. Here, we tested the possible harmful effects of this treatment in a situation aimed to model androgen abuse to aid physical exercise training. The studied constituents of hepatic antioxidant defense systems included selected antioxidant enzymes (SOD, CAT, GPx, and GR) and nonenzymatic low molecular weight antioxidants (&#61537;-and &#61543;-tocopherols and GSH); liver thiobarbituric acid-reactive substances (TBARS) content was assayed as an index of oxidative stress. Our choice of testosterone enanthate (TE) was mainly based on the fact that testosterone was for many years among the most frequently abused doping drugs <ns0:ref type='bibr' target='#b24'>(Handelsman, 2006)</ns0:ref>, and testosterone formulations (chiefly esters) are a cornerstone of most oral and injectable AAS stacking regimens (for the respective URLs see &lt;WWW-references.docx&gt; in Supplemental Files). However, we also intended to avoid hepatotoxicity related to chemical alteration (mostly 17&#945;-alkylation) of the sterane core in most AAS <ns0:ref type='bibr' target='#b26'>(Hartgens &amp; Kuipers, 2004;</ns0:ref><ns0:ref type='bibr' target='#b52'>Russmann, Kullak-Ublick &amp; Grattagliano, 2009;</ns0:ref><ns0:ref type='bibr' target='#b8'>B&#252;ttner &amp; Thieme, 2010)</ns0:ref>. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Animals</ns0:head><ns0:p>Five-week-old healthy specific pathogen-free male outbred Wistar rats of 91-120 g initial body weight (BW) from the Cmd:(WI)WU stock maintained at the Mossakowski Medical Research Centre, Warsaw, Poland, were used for the study. They were housed 4-5 per opaque plastic cage (60 &#215; 38 cm floor size) with dust-free deciduous wood chip bedding, in a controlled environment room (22-24 &#61616;C, 45-65% relative humidity, 15-20 air changes per hour), under 12 hours/12 hours light-dark cycle (lights on at 7 a.m.). Throughout the study (excepting an 8-hour fast just before the sacrifice, see below), the rats were allowed autoclaved laboratory rat maintenance chow (ssniff Spezialdi&#228;ten GmbH, Soest, Germany) and autoclaved purified tap water ad libitum. The cage environment was enriched with deciduous wood shavings as a material for gnawing and nesting; after each bedding change, a few fresh chow pellets were also left on the cage floor for playing and gnawing. The water bottles were replaced twice a week, and the bedding and enrichment material were changed weekly or more frequently if needed.</ns0:p></ns0:div> <ns0:div><ns0:head>Drugs</ns0:head><ns0:p>Stock TE solution (Testosteronum prolongatum, Jelfa, Jelenia G&#243;ra, Poland; active substance: testosterone enanthate, 100 mg/ml) was diluted with sesame oil (Sigma-Aldrich, St. Louis, MO, USA) as necessary to provide the same injection volume of 1 ml/kg BW irrespective of weekly TE dose employed. The diluted solution was injected intramuscularly each Monday for six weeks, alternatively into the left and right hind leg. TE-untreated rats received 1 ml/kg BW of the oil by an identical schedule.</ns0:p></ns0:div> <ns0:div><ns0:head>Experimental design</ns0:head><ns0:p>All rats meant for EndTr were first run-tested (at 18-20 m/min, 0&#61616; slope, 3 &#215; 5 min daily, with 15-min breaks) for three consecutive days on a BTP-10 motorized rodent treadmill (Porfex, Bia&#322;ystok, Poland) to acquaint them with this setting and identify and exclude rats reluctant to exercise. A low-intensity electrical shock (0.5 mA, 170V AC) was used during the habituation to motivate the rats to run. Two rats that were found unwilling to run during the habituation period did not enter the experiment. The remaining rats were randomly divided between three groups: 1) TE-untreated EndTr rats (EndTr, N = 11), 2) EndTr rats given 8 mg/kg BW /week of TE (EndTr+TE8, N = 11) and 3) EndTr rats given 80 mg/kg BW /week of TE (EndTr+TE80, N = 12). Manuscript to be reviewed An additional group of na&#239;ve sedentary (untrained, UTr, N = 11) male Wistar rats from the same stock and kept under the same conditions, 11-12-week old at the moment of sacrifice, was used to estimate reference ranges of blood serum lipids. All the rats belonging in the EndTr, EndTr+TE8, and EndTr+80 group were trained to run (at 0&#61616; slope) on the treadmill five days a week (Monday through Friday) for six weeks starting two days after the last habituation session.</ns0:p><ns0:p>Treadmill speed was gradually elevated from 16 m/min for the first week to 28 m/min for the fourth week and then was kept steady. The EndTr session duration for weeks 1-4 began at 40 min/day each week and was extended by 5 min daily; for the last two weeks, the rats ran for 60 min daily. This moderate-intensity EndTr (at about 60% VO 2 max) was shown by various measures to improve endurance in rats <ns0:ref type='bibr' target='#b34'>(Langfort, Budohoski &amp; Newsholme, 1988;</ns0:ref><ns0:ref type='bibr' target='#b35'>Langfort et al., 1996;</ns0:ref><ns0:ref type='bibr' target='#b16'>Dobrzyn et al., 2013)</ns0:ref>. One rat of the EndTr group and two rats of the EndTr+TE8 group developed an aversion to run and showed noticeable weight loss (by &#61619;10% over a single week) at some time point of the training course. These rats were euthanized by decapitation while deeply anesthetized with an intraperitoneal injection of a solution of pentobarbital sodium and pentobarbital (50 mg/ml and 10 mg/ml, respectively; Vetbutal, Biowet Pu&#322;awy, Poland) at a dose of 80 mg/kg BW . Two days after the last EndTr session, all the surviving endurance-trained rats and the UTr rats were fasted for 8 hours, anesthetized with an intraperitoneal injection of the pentobarbital sodium and pentobarbital mixture as above, and decapitated. Trunk blood samples were collected, let to clot at room temperature, and centrifuged to yield serum for biochemical assays. Livers were perfused in situ with 10 mM glucose-supplemented cold Krebs-Henseleit buffer pH 7.4, then quickly removed, weighed, and cut into several pieces that were instantly frozen in liquid nitrogen and stored at -80&#61616;C until analyzed. The study protocol complied with the Directive 2010/63/EU of the European Parliament and of the Council of 22 September 2010 on the protection of animals used for scientific purposes, was in line with the respective Polish law then in force, and was accepted by the IV Local Ethics Committee for Animal Experimentation in <ns0:ref type='bibr'>Warsaw, Poland (Permit No. 38/2011)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Assay methods</ns0:head><ns0:p>All biochemical determinations in blood serum and liver samples, except for serum lipids that were not determined before, were performed as described earlier <ns0:ref type='bibr' target='#b54'>(Sadowska-Kr&#281;pa et al., 2017)</ns0:ref>. Specifically: The total serum testosterone (TT) level was assessed with a DSL-4100 Testosterone RIA Kit (Diagnostic Systems Laboratories, Webster, TX, USA). Serum activities of aspartate aminotransferase (AST; EC:2.6.1.1), alanine aminotransferase (ALT; EC:2.6.1.2), alkaline phosphatase (ALP; EC:3.1.3.1), and &#947;-glutamyltransferase (GGT; EC:2.3.4.2) were determined on a model Cobas Integra 400/800 analyzer (Roche, Switzerland). For antioxidant status testing, liver samples were homogenized in ice-cold buffers prepared according to the respective diagnostic kit instructions, using a model Ultra-Turrax T8 homogenizer (IKA Labortechnik, Staufen, Germany). Protein content in homogenate supernatants was determined with the BCA-1 Protein Assay Kit (Sigma-Aldrich, UK). CAT (EC:1.11.1.6) activity was measured as described by <ns0:ref type='bibr' target='#b0'>Aebi (1984)</ns0:ref>, while GSH content and GPx (EC:1.11.1.9) and GR (EC:1.6.4.2) activities were assessed with Bioxytech kits GSH-400, GPx-340, and GR-340, respectively (OXIS International, Portland, OR, USA). SOD (EC:1.15.1.1) activity was assessed with a Superoxide Dismutase Assay Kit (Cayman Chemical, Ann Arbor, MI, USA). Liver contents of &#945;and &#947;-tocopherol were quantified by HPLC <ns0:ref type='bibr' target='#b61'>(Sobczak, Skop &amp; Kula, 1999)</ns0:ref>, while that of thiobarbituric acidreactive substances (TBARS) was assessed as described by <ns0:ref type='bibr' target='#b45'>Ohkawa, Ohishi &amp; Yagi (1979)</ns0:ref> and expressed in malondialdehyde (MDA) units. Serum total cholesterol (Tot-Ch), HDL-cholesterol (HDL-Ch), and triglyceride (TG) levels were determined using commercial kits <ns0:ref type='bibr'>respectively)</ns0:ref> from Randox Laboratories (Crumlin, UK), while LDL-cholesterol (LDL-Ch) was assessed with a model Synchron CX9 Pro analyzer (Beckman-Coulter).</ns0:p></ns0:div> <ns0:div><ns0:head>Statistics</ns0:head><ns0:p>Data are presented as the mean &#177; SD if applicable. Body weight data were first analyzed by a two-way analysis of variance (ANOVA) with TE dose (0, 8, or 80 mg/kg BW ) as the main factor and repeated measure on time, followed by the Tukey test for unequal sample sizes. Blood serum lipid titers were compared by a one-way ANOVA followed by the Dunnett test. The occurrence of abnormal values of blood serum enzyme activities and lipid profile indices was compared by the one-tailed z-test for two proportions. All other data were analyzed by a one-way ANOVA with weekly TE dose as the main factor, followed by the Tukey test when appropriate.</ns0:p><ns0:p>Comparisons with data from our previous study <ns0:ref type='bibr' target='#b54'>(Sadowska-Kr&#281;pa et al., 2017)</ns0:ref> were made using Student's t-test for independent variables, as indicated in the text. Associations between variables were assessed using the Spearman rank correlation test. In all cases, p &#8804; 0.05 was considered significant. All the statistical analyses were run using the Statistica v. 12.5 software package (StatSoft, Tulsa, OK, USA). Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Serum total testosterone level and body and liver weights</ns0:head><ns0:p>At the end of the study, the mean serum TT level in low-dose TE-treated (EndTr+TE8) rats exceeded only marginally and nonsignificantly that in the TE-untreated rats, while that in their high TE dose-treated counterparts (EndTr+TE80) was 10-fold higher. There was no difference in BW gain between the rats given no or low-dose TE treatment, whereas both these groups showed considerably higher BW gain than the EndTr+TE80 group. Mean liver weight and LW/BW ratio in the EndTr+TE8 rats were significantly higher, while the mean LW but not mean LW/BW ratio was significantly lower in the EndTr+TE80 rats than in the TE-untreated rats. The final BW and the LW/BW ratio were significantly lower in the high-dose-than in the low-dose TE-treated rats (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). Across all three EndTr groups combined, the final BW, LV, and LV/BW ratio correlated negatively with the weekly TE dose: R S = -0.65, p&lt; 0.001, R S = -0.47, p &lt;0.01, and R S = -0.37, p &lt; 0.05, respectively; N = 31 for all.</ns0:p></ns0:div> <ns0:div><ns0:head>Tissue antioxidant enzymatic and nonenzymatic indices of liver status</ns0:head><ns0:p>TE treatment resulted in a slight drop in mean SOD activity and a marked lowering of mean CAT activity (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). These activities also showed a significant negative correlation with the weekly TE dose across all three EndTr groups combined (R S = -0.61 and R S = -0.78, respectively; p &lt; 0.001, N = 31 for both). In contrast, there was no sizable TE treatment-related difference in mean GPx and GR activities between these groups and no sizable tendency for a correlation with weekly TE dose across the EndTr study cohort (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>).</ns0:p><ns0:p>Both TE-treated groups showed somewhat lower liver GSH content than that in the TEuntreated group, which difference reached significance for the low-dose TE treatment. No tangible difference was found between the respective &#61537;or &#61543;-tocopherol levels. As compared with hepatic TBARS content in the TE-untreated rats, that in the low-dose TE-treated rats was but nonsignificantly higher (+15%), while that in the other TE-treated group was significantly and much (+48%) higher (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Across all three EndTr groups combined, the TBARS content positively correlated with the TE dose received (R S = 0.51, p &lt; 0.01, N = 31).</ns0:p></ns0:div> <ns0:div><ns0:head>Blood serum enzymatic indices of liver status</ns0:head><ns0:p>There was no significant difference in serum AST or ALT activity between the various EndTr groups. Across all three EndTr groups combined, these activities did not or but poorly correlated with the weekly TE dose (R S = 0.20, p = 0.27, and R S = 0.36, p = 0.046, respectively, N = 31 for both). The rats given high-dose TE treatment showed significantly higher serum ALP and GGT activities than their TE-untreated counterparts (Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>). These activities correlated well with the weekly TE dose across the three EndTr groups (R S = 0.61, p &lt; 0.001, and R S = 0.69, p &lt; 0.001, respectively, N = 31 for both). There was no correlation between any two of these indices within this cohort (R S &#8804; 0.30, p &#8805; 0.10, N = 31).</ns0:p><ns0:p>The occurrence of above-normal AST activity was high in the TE-untreated EndTr rats and even higher in their TE-treated counterparts. The occurrence of excessive activities of ALT and GGT but not ALP tended to increase in the TE-untreated EndTr rats and was significantly elevated in the TE-treated rats TE (Table <ns0:ref type='table' target='#tab_3'>4</ns0:ref>). However, even the maximum activities exceeded the upper limit of the respective reference range but moderately: AST -by 48%, ALT -by 37%, ALP -by 6%, and GGT -by 65%.</ns0:p></ns0:div> <ns0:div><ns0:head>Blood serum lipid profile</ns0:head><ns0:p>Across the entire cohort of endurance-trained rats, weekly TE dose showed significant negative correlation with serum HDL-Ch level and Tot-Ch/HDL-Ch ratio (R S = -0.77, p &lt; 0.001, N = 31, and R S = -0.51, p &lt; 0.01, respectively), and a tendency for weak correlation with TG but not LDL-Ch level (R S = -0.31, p = 0.09, and R S = 0.15, p = 0.41, respectively, N = 31 for both).</ns0:p><ns0:p>Mean values of all tested lipid indices except HDL-Ch tended to be lower in the TE-untreated EndTr rats than in their UTr counterparts, but the difference reached significance only for TG level and neared significance for the TG/HDL ratio (Table <ns0:ref type='table' target='#tab_4'>5</ns0:ref>). Both TE-treated EndTr groups compared to their TE-untreated counterpart showed slightly and nonsignificantly lower mean Tot-Ch but not mean LDL-Ch level, and significantly lower mean HDL-Ch level. Mean Tot-Ch/HDL-Ch and LDL-Ch/HDL ratios were significantly higher in the EndTr+TE80 rats than those in their TE-untreated counterparts and showed a similar tendency in the EndTr+TE8 rats. The latter showed a nonsignificantly higher mean TG level than their TE-untreated counterparts, while there was a tendency for a reverse difference between them and the EndTr+TE80 rats. Due to no significant difference in mean HDL-Ch level between the TE-treated groups, the mean TG/HDL-Ch ratio was significantly higher (+63%) in the low-dose TE-treated, but not in the EndTr+TE80 rats (+20%) than in their TE-untreated counterparts (Table <ns0:ref type='table' target='#tab_4'>5</ns0:ref>).</ns0:p><ns0:p>For lack of established reference ranges for blood lipids in Wistar rats, we estimated these ranges as the mean &#61617; 2S.D. of the levels found in the previously mentioned additional group of Manuscript to be reviewed matched TE-untreated UTr rats. Except for an abnormally low TG level and TG/HDL-Ch ratio in a single rat, no out-of-range value was found in the TE-untreated EndTr group. In contrast, the TE-treated EndTr rat groups, and mainly that given the higher TE dose, showed an increased occurrence of below-normal TG, Tot-Ch, and especially HDL-Ch levels, occasionally associated with abnormally high LDL-Ch/HDL-Ch ratio (Table <ns0:ref type='table'>6</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The main finding of this work is that testosterone supplementation enhanced hepatic stress and adversely altered liver pro-oxidant/antioxidant balance in EndTr adolescent male rats. These effects were evidenced by the increased occurrence of elevated blood GGT, AST and ALT activities, worsened blood lipid profile, reduced liver SOD and CAT activities and GSH content, and elevated liver TBARS content. The higher TE dose significantly lowered BW gain and LW as compared to those in TE-untreated EndTr rats, but caused no substantial shift in the LW/BW ratio (-5%, p = 0.66) and thus no apparent hepatotoxicity in EndTr rats. Earlier, we found a significantly reduced LW/BW ratio in high-dose TE-treated adolescent UTr rats (Sadowska-Kr&#281;pa et al., 2017), which may have been due to the start of TE treatment at a younger age.</ns0:p><ns0:p>The training was performed at an intensity that allows maximal fat oxidation <ns0:ref type='bibr' target='#b49'>(Purdom et al., 2018)</ns0:ref>, and the mean BW gains were less in all three EndTr groups than in the respective UTr groups (see <ns0:ref type='bibr' target='#b54'>Sadowska-Kr&#281;pa et al., 2017)</ns0:ref>. Notably, mean BW gain was identical for the TEuntreated and low-dose TE-treated groups in both the endurance-trained and UTr rat cohorts, indicating no interference of this treatment with food intake and somatic growth. The lowered BW gain in the EndTr+TE80 rats may also have resulted from reduced appetite and food intake.</ns0:p><ns0:p>Such effects causing inadequate compensation of energy expenditure were commonly found in treadmill-trained male rats <ns0:ref type='bibr' target='#b25'>(Harpur, 1980;</ns0:ref><ns0:ref type='bibr' target='#b41'>Molano et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b20'>Foletto et al., 2015)</ns0:ref>. However, reduced food intake was seen as well in long-term stanozolol-treated sedentary male rats <ns0:ref type='bibr' target='#b70'>(Yu-Yahiro et al., 1989)</ns0:ref>. Another cause of reduced weight gain could be androgen-induced loss of adipose tissue (mostly visceral) and liver fat through various mechanisms <ns0:ref type='bibr' target='#b70'>(Yu-Yahiro et al., 1989;</ns0:ref><ns0:ref type='bibr'>De Pergola, 2000;</ns0:ref><ns0:ref type='bibr' target='#b28'>Hoyos et al., 2012)</ns0:ref>. Elevated serum AST, ALT, ALP, and GGT are well-known markers of AAS hepatotoxicity <ns0:ref type='bibr' target='#b65'>(Urhausen, Torsten &amp; Wilfried, 2003;</ns0:ref><ns0:ref type='bibr' target='#b46'>Ozer et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b60'>Singh, Bhat &amp; Sharma, 2011)</ns0:ref>. However, serum ALT and AST may also come from injured skeletal muscles <ns0:ref type='bibr' target='#b46'>(Ozer et al., 2008)</ns0:ref>. Exercise Manuscript to be reviewed training alone can elevate serum ALT and AST, but not GGT, in both men <ns0:ref type='bibr' target='#b47'>(Pettersson et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b50'>Romagnoli et al., 2014)</ns0:ref> and male rats <ns0:ref type='bibr' target='#b48'>(Pey et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b10'>Chang et al., 2013)</ns0:ref>. We found no significant difference between our TE-untreated EndTr rats and matching UTr rats in any of the four markers but AST activity that was higher in the former (p = 0.024, Student's t-test); for the UTr rats' data, see <ns0:ref type='bibr' target='#b54'>Sadowska-Kr&#281;pa et al. (2017)</ns0:ref>. In the present study, raised serum AST, ALT, and GGT but not ALP activities were found in a sizable subset of the EndTr+TE8 rats and most of the EndTr+TE80 rats. However, the mean AST and ALT activities in the latter were only higher by 1/3 than those in the TE-untreated UTr rats (Sadowska-Kr&#281;pa et al., 2017). Even smaller and nonsignificant were the relative increases in the mean AST (+6%) and ALT activity (+23%) in the EndTr+TE80 rats as compared to those in their TE-untreated counterparts, while the respective increase in the mean GGT activity was fairly robust (+57%). Our data on the effects of the lower TE dose are in line with those reported by others. Namely, no sizable increase in serum AST, ALT, ALP, or GGT was found in adolescent male rats given 12 weeks of moderate-intensity EndTr and five intragastric doses weekly of 2 mg/kg BW of fluoxymesterone, methylandrostanolone, or stanozolol during the last eight weeks <ns0:ref type='bibr' target='#b41'>(Molano et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b48'>Pey et al., 2003)</ns0:ref>. Notably, these AAS are much more hepatotoxic than testosterone <ns0:ref type='bibr' target='#b26'>(Hartgens &amp; Kuipers, 2004;</ns0:ref><ns0:ref type='bibr' target='#b52'>Russmann, Kullak-Ublick &amp; Grattagliano, 2009;</ns0:ref><ns0:ref type='bibr' target='#b8'>B&#252;ttner &amp; Thieme, 2010)</ns0:ref>.</ns0:p><ns0:p>We have earlier found significant increases in the mean serum level of AST, ALT, and ALP, but not GGT, in 5-week-old UTr rats given 6-week high-dose TE-treatment <ns0:ref type='bibr' target='#b54'>(Sadowska-Kr&#281;pa et al., 2017)</ns0:ref>. In the present study, 60% of the TE-untreated EndTr rats showed elevated serum AST levels indicating an exercise-related leakage of the enzyme from skeletal muscles. Unexpectedly, there was no significant TE-treatment-related increase in mean AST and ALT levels, while the high-dose TE treatment-related increase in mean ALP level was nearly identical to that in the UTr rats. However, contrary to the latter, the EndTr+TE80 rats showed a much higher mean GGT level than their TE-untreated counterparts. Serum ALT and ALP levels correlated positively with TE dosage in both the EndTr (see the Results section) and the UTr study cohort (R S = 0.70, p &lt; 10 -3 , and R S = 0.50, p &lt; 10 -2 , respectively, N = 37 for both, see Supplemental Files, UTr_cohort_ser_enz_vs_TE_dose.xlsx). In contrast, weekly TE dose positively correlated with GGT but not AST level in the EndTr rats (this study), while the reverse was right in the UTr rats (R S = 0.06, p = 0.72, N = 34, and R S = 0.74, p &lt; 10 -3 , N = 37, respectively, see Supplemental Files, UTr_cohort_ser_enz_vs_TE_dose.xlsx). This disparity may relate to the slightly different Being fairly ubiquitous (Bataller-Sifr&#233;, Guiral-Olivan &amp; Bataller-Alberola, 2011), GGT alone has insufficient specificity as a serum marker of liver injury. In humans, it is usually raised in liver pathologies involving cholestasis and jaundice, including those caused by AAS <ns0:ref type='bibr' target='#b65'>(Urhausen, Torsten &amp; Wilfried, 2003;</ns0:ref><ns0:ref type='bibr' target='#b39'>Lumia &amp; McGinnis, 2010)</ns0:ref>. In rats, it is supposedly a better cholestasis marker than serum ALP but less reliable than in other species <ns0:ref type='bibr' target='#b46'>(Ozer et al., 2008)</ns0:ref>. We found elevated serum ALP activity in only two out of 12 EndTr+TE80 rats, but only one of them showed moderately elevated serum GGT activity. Notably, testosterone or its esters rarely cause adverse hepatobiliary effects, except possibly in aging <ns0:ref type='bibr' target='#b43'>(Nucci et al., 2017)</ns0:ref>.</ns0:p><ns0:p>Cell membrane-bound GGT is a vital part of hepatic antioxidant lines that sustain cellular GSH and cysteine homeostasis <ns0:ref type='bibr' target='#b71'>(Zhang, Forman &amp; Choi, 2005)</ns0:ref>. Its link with serum GGT is not known. Serum GGT was proposed as an aggregate marker of organismal oxidative stress caused by various diseases and environmental chemicals <ns0:ref type='bibr' target='#b36'>(Lee &amp; Jacobs, 2009;</ns0:ref><ns0:ref type='bibr' target='#b10'>Chang et al., 2013)</ns0:ref>. The TE treatment-related differences in serum GGT and the occurrence of excessive serum GGT levels were much larger in the EndTr cohort than those found earlier (see <ns0:ref type='bibr' target='#b54'>Sadowska-Kr&#281;pa et al., 2017)</ns0:ref> in the UTr cohort. However, there was no significant association between the levels of serum GGT and serum ALP, ALT, or AST. Hence, a significant part of the rise in serum GGT activity might not be due to liver stress or damage. Instead, it may indicate increased oxidative stress occurring in multiple organs.</ns0:p><ns0:p>Mean liver TBARS content was only slightly higher in the TE-untreated EndTr rats than in their UTr counterparts <ns0:ref type='bibr' target='#b54'>(Sadowska-Kr&#281;pa et al., 2017)</ns0:ref>; this could be related to the constitutively high liver metabolic activity and the corresponding oxidative stress. However, the relative differences in liver TBARS content between the EndTr+TE8 and EndTr+TE80 rats and their TEuntreated counterparts were modest (+15 and +48%, respectively) compared to those in their sedentary counterparts (+56 and +78%, respectively, see <ns0:ref type='bibr' target='#b54'>Sadowska-Kr&#281;pa et al., 2017)</ns0:ref>. Hence, the absolute mean TBARS levels were nearly equal in the corresponding TE-treated UTr and EndTr rat groups. Though the present data confirm the pro-oxidant action of supraphysiological TE doses, they also suggest an attenuation of the added oxidative stress in the EndTr rats.</ns0:p><ns0:p>Decreased activities of liver CAT and SOD in high-dose TE-treated rats and negative correlations of these enzyme activities with weekly TE doses proved a harmful action of massive testosterone supplementation on liver antioxidant enzymes in adolescent EndTr rats. Even more significant relative declines, including those in GPx and GR activities, were found in the heart of EndTr male adolescent rats given testosterone propionate doses that produced much higher serum TT levels. Their associated relative increases in left heart ventricle TBARS content exceeded these in the liver. However, the maximum absolute mean TBARS contents found in the two organs were nearly identical to the respective maximum found in the soleus muscle and far above that in the extensor digitorum longus <ns0:ref type='bibr' target='#b53'>(Sadowska-Krepa et al., 2013)</ns0:ref>. This similarity may be related to the fact that the soleus muscle, the myocardium, and the liver, but not the extensor digitorum longus, rely almost entirely on oxidative metabolism in exercise.</ns0:p><ns0:p>While we found decreased hepatic GSH content in our TE-treated EndTr rats, stanozolol treatment was reported to increase hepatic GSH content in endurance-trained rats <ns0:ref type='bibr' target='#b48'>(Pey et al., 2003)</ns0:ref>. The cause of the difference may be distinct pharmacological profiles of stanozolol and testosterone <ns0:ref type='bibr'>(Fernandez et al., 1994;</ns0:ref><ns0:ref type='bibr' target='#b26'>Hartgens &amp; Kuipers, 2004;</ns0:ref><ns0:ref type='bibr' target='#b52'>Russmann, Kullak-Ublick &amp; Grattagliano, 2009;</ns0:ref><ns0:ref type='bibr' target='#b8'>B&#252;ttner &amp; Thieme, 2010)</ns0:ref>, but also younger age and thus different reactivity of our rats at the beginning of androgen treatment. The present data contrast also with those from adolescent UTr rats, in which the same TE doses significantly elevated liver SOD activity <ns0:ref type='bibr' target='#b54'>(Sadowska-Kr&#281;pa et al., 2017)</ns0:ref>. It is likely that long-term TE treatment of adolescent male EndTr rats perturbed their development and/or boosted oxidative stress beyond the capacity of hepatic defenses. Of note, mean liver activities of SOD, CAT and GPx were higher (p &#8804; 0.035, onetailed t-test) in the TE-untreated EndTr rats than in their UTr counterparts <ns0:ref type='bibr' target='#b54'>(Sadowska-Kr&#281;pa et al., 2017)</ns0:ref>, and a similar tendency was found for GR (p = 0.093, one-tailed t-test). These findings implied that the training alone boosted the antioxidant defenses. A similar effect on liver SOD but not CAT and GPx activities was found in male rats of similar age, which were given 16-week EndTr of similar intensity <ns0:ref type='bibr' target='#b63'>(Song, Igawa &amp; Horii, 1996)</ns0:ref>. In our study, the positive effect of the training on liver SOD and CAT, but not GR and GPx activities, was dose-dependently reduced by concurrent TE treatment. This decline is consistent with enhanced liver oxidative stress adolescent UTr rats <ns0:ref type='bibr' target='#b54'>(Sadowska-Kr&#281;pa et al., 2017)</ns0:ref> and prompt deactivation of CAT and SOD by oxygen free radicals <ns0:ref type='bibr' target='#b55'>(Salo et al., 1990;</ns0:ref><ns0:ref type='bibr' target='#b17'>Escobar, Rubio &amp; Lassi, 1996)</ns0:ref>.</ns0:p><ns0:p>GSH is the most abundant antioxidant and the key scavenger of reactive oxygen and nitrogen species in the liver <ns0:ref type='bibr' target='#b52'>(Russmann, Kullak-Ublick &amp; Grattagliano, 2009;</ns0:ref><ns0:ref type='bibr' target='#b38'>Li et al., 2015)</ns0:ref>. In our studies, its content did not differ between the TE-untreated EndTr and UTr rats. However, in contrast to what we found in the UTr rats study <ns0:ref type='bibr' target='#b54'>(Sadowska-Kr&#281;pa et al., 2017)</ns0:ref>, TE treatment suppressed hepatic GSH content in EndTr rats, suggesting increased GSH use. GSH is also vital for sustaining reduced forms of some exogenous antioxidants, including the essential lipophilic antioxidant vitamin E <ns0:ref type='bibr' target='#b56'>(Scholz et al., 1989)</ns0:ref>. Neither hepatic &#61537;-tocopherol nor &#947;-tocopherol pool was significantly affected by TE treatment in EndTr rats, showing the efficacy of GSH in maintaining appropriate levels of these protectants against free-radical mediated liver damage <ns0:ref type='bibr' target='#b37'>(Leo, Rosman &amp; Lieber, 1993)</ns0:ref>. Interestingly, liver TBARS content negatively correlated with hepatic &#61537;-tocopherol (R S = -0.48, p &lt; 0.01, N = 31) but not &#947;-tocopherol content (R S = -0.30, p = 0.11, N = 31) within the entire EndTr cohort. This link may reflect the use of &#61537;-tocopherol for scavenging reactive oxygen species formed, e.g., due to &#61538;-oxidation of fatty acids, and hence for breaking chain propagation and maintaining an adequate redox balance <ns0:ref type='bibr' target='#b42'>(Niki, 2014)</ns0:ref>.</ns0:p><ns0:p>The EndTr-related shifts in blood lipid profile found in this study are usually linked to reduced atherogenicity in both humans <ns0:ref type='bibr' target='#b57'>(Shephard &amp; Johnson, 2015;</ns0:ref><ns0:ref type='bibr' target='#b51'>Ruegsegger &amp; Booth, 2018)</ns0:ref> and rats <ns0:ref type='bibr' target='#b7'>(Burneiko et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b33'>Kazeminasab et al., 2017)</ns0:ref>. The changes in blood lipid profile caused by concurrent TE treatment evidenced a reversal of the beneficial effects of the training and worsening of some training-unaffected characteristics except for the tendency of TG level and TG/HDL ratio to drop with the high TE dosage. The latter was likely the result of long-term action of supraphysiological serum TT level on male adipose tissue metabolism and the ensuing decreased body and liver fat contents and availability.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>The present results show that long-term systemic high-dose testosterone treatment harms liver antioxidant defense systems and function in adolescent male rats undergoing endurance training.</ns0:p><ns0:p>Namely, it abolishes or markedly attenuates most studied metabolic benefits from the training, causing a negative shift in liver pro-oxidative/antioxidative balance evidenced by reduced SOD and CAT activities, raised hepatic TBARS level, and elevated serum GGT activity. These changes suggest increased oxidative stress that likely occurs in other organs as well and may increase morbidity later in life. The same may occur in human male adolescents using massive testosterone or other AAS supplementation as a shortcut to improved sports performance and/or a more muscular physical appearance. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Selected blood serum lipid levels and lipid ratios in adolescent male rats given 6-week EndTr without or with concurrent testosterone enanthate treatment and in their naive counterparts. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020) Manuscript to be reviewed mean age of the two rat cohorts at the start of TE treatment, or a training-related change in resistance of the circulating enzymes' sources, or both.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Comparison of body weight, liver weight and blood testosterone level between adolescent male rats given 6-week EndTr without or with concurrent weekly testosterone enanthate treatment.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Manuscript to be reviewed</ns0:cell></ns0:row><ns0:row><ns0:cell cols='5'>BW, body weight; LW, liver weight; EndTr, endurance training; TE8, 8 mg/kg/week of</ns0:cell></ns0:row><ns0:row><ns0:cell cols='5'>intramuscular testosterone enanthate; TE80, 80 mg/kg/week of intramuscular testosterone</ns0:cell></ns0:row><ns0:row><ns0:cell cols='5'>enanthate; TT, total blood serum testosterone. Data are mean &#177; standard deviation; rat</ns0:cell></ns0:row><ns0:row><ns0:cell cols='5'>numbers are shown in parentheses. * p&lt;0.05, ** p&lt;0.01, *** p&lt;0.001 vs. the respective</ns0:cell></ns0:row><ns0:row><ns0:cell>EndTr group value;</ns0:cell><ns0:cell>##</ns0:cell><ns0:cell>p&lt;0.01,</ns0:cell><ns0:cell>###</ns0:cell><ns0:cell>p&lt;0.001 vs. the respective EndTr+TE8 group value;</ns0:cell></ns0:row><ns0:row><ns0:cell>Tukey's test.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Liver levels of selected antioxidant enzymes, non-enzymatic antioxidants and TBARs in adolescent male rats given 6-week endurance training without or with concurrent testosterone enanthate treatment.</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='4'>SOD, superoxide dismutase; CAT, catalase; GPx, glutathione peroxidase; GR, glutathione</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>reductase; GSH, reduced glutathione; TBARs, thiobarbituric acid-reactive substances (lipid</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>peroxidation products); EndTr, endurance training; TE8, 8 mg/kg BW /week of intramuscular</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>testosterone enanthate; TE80, 80 mg/kg BW /week of intramuscular testosterone enanthate.</ns0:cell><ns0:cell>a</ns0:cell></ns0:row><ns0:row><ns0:cell>per mg of protein in liver homogenate supernatant,</ns0:cell><ns0:cell>b</ns0:cell><ns0:cell cols='2'>per g of liver wet weight; * p&lt;0.05, **</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>p&lt;0.01, *** p&lt;0.001 vs. the respective EndTr group value;</ns0:cell><ns0:cell>&#8225;</ns0:cell><ns0:cell>0.05&lt;p&#8804;0.08 vs. the respective</ns0:cell></ns0:row><ns0:row><ns0:cell>EndTr+TE8 group value; Tukey's test.</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)Manuscript to be reviewed</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Comparison of blood serum AST, ALT, ALP and GGT activities between adolescent male rats given 6-week endurance training without or with concurrent testosterone enanthate</ns0:figDesc><ns0:table><ns0:row><ns0:cell>treatment.</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='3'>AST, aspartate aminotransferase; ALT, alanine aminotransferase; ALP, alkaline phosphatase;</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>GGT, &#947;-glutamyltransferase. EndTr, endurance training; TE8, 8 mg/kg BW /week of</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>intramuscular testosterone enanthate; TE80, 80 mg/kg BW /week of intramuscular testosterone</ns0:cell></ns0:row><ns0:row><ns0:cell>enanthate. * p&lt;0.05, *** p&lt;0.001 vs. the respective EndTr group value;</ns0:cell><ns0:cell>&#8225;</ns0:cell><ns0:cell>0.05&lt;p&#8804;0.08 vs.</ns0:cell></ns0:row><ns0:row><ns0:cell>the respective EndTr+TE8 group value; Tukey's test.</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020) Manuscript to be reviewed 2 PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 4 (on next page)</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Occurrence of above-normal activities of blood serum AST, ALT, ALP and GGT in adolescent male rats given 6-week endurance training without or with concurrent testosterone enanthate treatment.AST, aspartate aminotransferase; ALT, alanine aminotransferase; ALP, alkaline phosphatase; GGT, &#947;-glutamyltransferase. EndTr, endurance training; TE8, 8 mg/kg BW /week of intramuscular testosterone enanthate; TE80, 80 mg/kg BW /week of intramuscular testosterone enanthate. Based on data from age-matched TE-untreated sedentary male Wistar rats (UTr, N=11) from the same breeding colony (Cmd:(WI)WU outbred stock) and kept under same conditions; taken from Sadowska-Kr&#281;pa et al., 2017, with permission. &#182; 0.06&#8804;p&#8804;0.08, &#167; p&lt;0.05, &#167; &#167; p&lt;0.01, &#167; &#167; &#167; p&lt;0.001 vs. the respective UTr group value (0/11, 0% for AST, ALT and ALP, and 0/10, 0% for GGT); * p&lt;0.05, *** p&lt;0.001 vs. the respective EndTr group value;</ns0:figDesc><ns0:table /><ns0:note>a ## p&lt;0.01 vs. the respective EndTr+TE8 group value; the one-tailed z-test for two proportions. PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head /><ns0:label /><ns0:figDesc>UTr, age-matched drug-naive untrained (sedentary) male Wistar rats from the same outbred stock (WI(WU)Cmd); EndTr, endurance training; TE8, 8 mg/kg BW /week of intramuscular testosterone enanthate; TE80, 80 mg/kg BW /week of intramuscular testosterone enanthate; Tot-Ch, total blood serum cholesterol; LDL-Ch, low-density lipoprotein cholesterol; HDL-Ch, high-density lipoprotein cholesterol; TG, triglycerides. &#182; 0.06&lt;p&#8804;0.08, * p&lt;0.05, *** p&lt;0.001 vs. the respective EndTr group value, Dunnett's test. Tot-Ch/HDL-Ch 2.99&#177;0.48 2.62&#177;0.32 3.27&#177;0.87 &#182; 3.43&#177;0.68 * F 3,38 =3.56, p=0.023 LDL-Ch/HDL-Ch 1.39&#177;0.39 1.09&#177;0.26 1.62&#177;0.70 &#182; 1.75&#177;0.54 * F 3,38 =3.55, p=0.023 42&#177;0.61 &#182; 1.67&#177;0.48 2.72&#177;1.14 * 2.01&#177;0.75 F 3,38 =3.56, p=0.023</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell cols='2'>Rat group</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Blood serum lipid</ns0:cell><ns0:cell>UTr</ns0:cell><ns0:cell>EndTr</ns0:cell><ns0:cell>EndTr+TE8</ns0:cell><ns0:cell>EndTr+TE80</ns0:cell><ns0:cell>ANOVA results</ns0:cell></ns0:row><ns0:row><ns0:cell>or lipid ratio</ns0:cell><ns0:cell>N=11</ns0:cell><ns0:cell>N=10</ns0:cell><ns0:cell>N=9</ns0:cell><ns0:cell>N=12</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Tot-Ch [mg/dl]</ns0:cell><ns0:cell>87&#177;10</ns0:cell><ns0:cell>79&#177;7</ns0:cell><ns0:cell>75&#177;10</ns0:cell><ns0:cell>71&#177;10</ns0:cell><ns0:cell>F 3,38 =6.19, p=0.002</ns0:cell></ns0:row><ns0:row><ns0:cell>LDL-Ch [mg/dl]</ns0:cell><ns0:cell>40&#177;9</ns0:cell><ns0:cell>33&#177;7</ns0:cell><ns0:cell>36&#177;11</ns0:cell><ns0:cell>36&#177;8</ns0:cell><ns0:cell>F 3,38 =1.32, p=0.28</ns0:cell></ns0:row><ns0:row><ns0:cell>HDL-Ch [mg/dl]</ns0:cell><ns0:cell>30&#177;3</ns0:cell><ns0:cell>30&#177;3</ns0:cell><ns0:cell>24&#177;4 ***</ns0:cell><ns0:cell cols='2'>21&#177;3 *** F 3,38 =23.4, p&lt;10 -3</ns0:cell></ns0:row><ns0:row><ns0:cell>TG [mg/dl]</ns0:cell><ns0:cell>71&#177;16 *</ns0:cell><ns0:cell>50&#177;14</ns0:cell><ns0:cell>61&#177;18</ns0:cell><ns0:cell>42&#177;15</ns0:cell><ns0:cell>F 3,38 =7.31, p&lt;10 -3</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>TG/HDL-Ch 2.2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)Manuscript to be reviewed</ns0:note></ns0:figure> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:note> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:note> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:03:46526:1:2:NEW 30 Sep 2020)</ns0:note> </ns0:body> "

"Re: PeerJ MS #46526 September 23, 2020 Prof. Cristina Nogueira Academic Editor PeerJ Dear Professor Nogueira, Enclosed, please find the revised version of the manuscript entitled: “High-dose testosterone supplementation disturbs liver pro-oxidant/antioxidant balance and function in adolescent male Wistar rats undergoing moderate-intensity endurance training” by E. Sadowska-Krępa, B. Kłapcińska, A. Nowara, S. Jagsz, I. Szołtysek-Bołdys, M. Chalimoniuk, J. Langfort, and S.J. Chrapusta. We would like to thank the reviewers of our MS for their time and the efforts to help us improve the paper. Below, please find our point-by-point answers to their comments. We hope that you and the reviewers will find the critiques answered satisfactorily, and we are kindly asking you to consider the revised manuscript for publication in the PeerJ. Looking forward to hearing from you, I remain, Sincerely, Stanisław Chrapusta Department of Experimental Pharmacology Mossakowski Medical Research Centre Polish Academy of Sciences 5 Pawińskiego St., 02-106 Warsaw, Poland Reply to Reviewer 1 (Anonymous) Basic reporting Reviewer’s comment: “1. The manuscript is clearly written and is comprehensible. The introduction is sufficient to orient towards the aims and objectives of the work.” Experimental design Reviewer’s comment: “1. The research question is well-stated and the methods are sufficiently elaborated. 2. Proper statistics have been applied.” Validity of the findings Reviewer’s comment: “1. Is it known what could be a possible trigger for oxidative stress in liver after high testosterone supplementation?” Authors’ reply: As testosterone can increase the liver metabolic rate acting through its specific receptors, this action may affect the equilibrium between reactive oxygen species production (due to electron leakage from the respiratory chain) and antioxidant defense lines, resulting in aggravation of oxidative stress. On the other hand, excess of this hormone, similar to other steroid hormones and xenobiotics, undergoes detoxification in the liver. Interactions of testosterone with other metabolites during detoxification phase I may affect the activity of the enzymes involved and perturb mitochondrial function by uncoupling oxidative phosphorylation and thus potentiate the generation of reactive oxygen species and enhance oxidative stress. Since some low molecular antioxidants, e.g., GSH, are also involved in detoxification phase II (conjugation), their increased consumption may negatively affect the cellular redox environment, increasing the chances for oxidative stress potentiation. Moreover, at the concentrations of testosterone achieved after administration of supraphysiological doses of its esters, one may also expect various effects exerted through other effector molecules, for which this hormone is not a specific ligand. Some of these effects may involve the formation of more reactive oxygen species and potentiate the overall oxidative stress burden. Reviewer’s comment: “2. Given the known role of Androgen receptor signaling in regulating lipid and glucose homeostasis through liver cells, the authors should discuss the effects of supraphysiological levels of testosterone in the light of their results. What about the insulin sensitivity at high testosterone supplementation? It may also pose detrimental effects.” Authors’ reply: We are well aware of the potential of androgen receptor signaling to affect lipid and glucose homeostasis through liver cells, e.g., to decrease insulin sensitivity at supraphysiological testosterone levels. However, androgen signaling through the respective specific receptor systems in either the cell nucleus or cell membrane is not the only one that is likely active in situations created by the use of supraphysiological testosterone doses. There is also a considerable chance lof involvement of other steroid receptor systems. This is because, at its supraphysiological levels, testosterone may effectively compete with some non-androgenic endogenous ligands for their specific binding sites. Another essential factor in animal or human studies is the aromatization of testosterone to estrogens in the various organs, including the liver, which is essential for physiological actions of testosterone in the liver concerning both lipid and glucose homeostasis but may become a confounding factor at supraphysiological testosterone levels. We are also aware that testosterone increases insulin receptor expression and insulin sensitivity in liver cells at physiological concentrations, whereas supraphysiological testosterone levels can considerably suppress insulin sensitivity. Testosterone effects on hepatic lipid homeostasis are multifaceted and involve alterations in lipid uptake, storage, and catabolism, as well as regulation of adipocyte differentiation. Notably, full androgen effects on both lipid and glucose homeostasis require systemic androgen administration that indicates a contribution of extrahepatic factors. In this study, we did not intend to test the effects of supraphysiological testosterone doses on glucose homeostasis or lipid homeostasis, which represent quite complex issues and much different from the actual aim of our work. Therefore we assessed no index of the glucose homeostasis, while the serum lipid profile was limited to a few primary indices that were only needed to verify whether the treatment employed resulted in the effects consistent with earlier studies. Trying to satisfy the above request of the Reviewer would make us speculating extensively without the support of real data. We believe this would be unwarranted and of no actual benefit for the paper. Reviewer’s comment: “3. Testosterone can have effects on multiple signaling pathways and organs, but since this paper is more focused on oxidative stress and liver injury, authors should check how Nrf2 signaling (which is a master regulator of antioxidant defenses) is affected. We see that high dose TE leads to increased lipid oxidation (TBARS) together with a decrease in antioxidant defenses like CAT, it would be interesting to know if this is due to down-modulation of cellular defenses or exhaustion of resources.” Authors’ reply: The study we report on in the present MS was purely observational/descriptive. It was meant to illustrate the spectrum of testosterone-induced hepatic oxidative stress symptoms and selected associated phenomena in endurance-trained rats and wasn’t aimed at elucidating the underlying mechanisms. We believe that speculating on the latter in this MS would be of little use. It has already been shown by others that chronic supplementation with moderate testosterone ester doses, due most likely to its activating effect on the Nrf2-ARE pathway and the resulting reduction of oxidative stress, alleviates morphological symptoms of aging in the rat kidney (Zhang et al., Sci. Rep. 2018; 8: 10726) and liver (Zhang et al., Sci. Rep. 2019; 9: 18619), and improves some motor behaviors in aging rats (Zhang et al., Behav. Brain Res. 2013; 252: 388-395). However, we fully agree with this Reviewer’s suggestion regarding the direction that the continuation of this research should eventually follow. It would also be interesting to see whether the apparent beneficial Nrf2-mediated effect of moderate testosterone doses on aging-related morphological and other alterations would be annihilated at supraphysiological hormone doses. Comments for the author Reviewer’s comment: “1. The discussion is too elaborate, cutting it short wherever possible would make the manuscript more coherent.” Authors’ reply: We have tried our best to satisfy this recommendation in the revised MS. Reviewer’s comment: “2. Line 211 replace ‘that in’ with than.” Authors’ reply: We cannot see the Reviewer’s point here. In the reviewed MS, there were two occurrences of ‘that in’ in line 211 (line 215 in the revised MS). However, replacing any one or both of those occurrences with ‘than’ would make the sentence incomprehensible. The check we ran on the sentence in question using the Grammarly® Grammar Checker showed no problem there. On the same page of the reviewed MS, there was a third occurrence of ‘that in’ in line 228 (presently line 232 in the revised MS) in the phrase “…somewhat lower liver GSH content than that in the TE-untreated group,…“. That one could be removed but not replaced as postulated by the Reviewer without destroying the meaning of the sentence, but this alteration is rather a matter of choice and not correctness. We have eliminated this occurrence of ‘that in’ in line 232 of the revised MS. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Reply to the Reviewer Gustavo Cassol Reviewer: Gustavo Cassol Basic reporting “The English language used in the manuscript is clear, mainly in the discussion. Your introduction is very good, however it is necessary to insert the article reference at lines 62-63 and 115-116 and remove website. I also suggest that you improve the description at lines 62-63 and 115-116 to provide trustworthiness for your study (specifically, you should insert the websites in supplementary data)” Authors’ reply: The three references in question are not scientific articles and were only available at the quoted WWW sites; hence, there was no possibility to reference them differently. Despite trying hard, we could not find any appropriate scientific article reference (in a printed or electronic journal version) that could be used to satisfy the Reviewer’s request. Moreover, it appeared that the first one of the three WWW references in the Introduction (Lasato V. Endurance training for bodybuilders) could not be accessed any more due to a problem with the host server of http://mindandmuscle.net/articles/endurance-training-for-bodybuilders; therefore, we have replaced it with another WWW reference (see line 61). We have also re-edited the sentence listing the two other WWW references in the Introduction (see line 115 in the revised version of our MS) and transferred the respective website addresses to the Supplementary files. Experimental design Reviewer’s comment: “If the testosterone dilution at line 135 are included in another study, please cite him in this section.” Authors’ reply: A detailed description of testosterone enanthate dilution was not included in an earlier study. Therefore we have expanded the respective description slightly in the Materials and Methods section of the revised MS; see lines 135-140. Reviewer’s comment: “Considering the methods section, experimental design, a suggestion is to group information from line 159-161 with line 146 to the information not to get lost.” Authors’ reply: We have followed this recommendation in the revised version of the MS; see lines 148-152 in the revised MS. Reviewer’s comment: “In the same section, the authors have data of food or water consumption? If do not, a suggestion to the authors is to use in next studies the control of water and food consumption weekly or, if it is possible, daily. This data control can help to better understand the BW of groups EndTr, mainly with the use of testosterone protocol.” Authors’ reply: Alas, we did not collect these data in the present study. We agree that monitoring water and food consumption would be of benefit in studies performed in adolescent (that is, still quickly growing) rats, especially when trying to understand the effects of experimental manipulations (e.g., exercise training or metabolism-affecting hormonal treatment regimens) on body weight. We will consider taking appropriate measures in our future studies in this model. Reviewer’s comment: “For observation, another suggestion to next studies is to change bedding three times a week.” Authors’ reply: Of course, we will consider this suggestion in our future studies. Validity of the findings Reviewer’s comment: “The manuscript “High-dose testosterone supplementation disturbs liver pro-oxidant/antioxidant balance and function in adolescent male Wistar rats undergoing moderate intensity endurance training (#46526)” presents a very important data about the use of testosterone in the adolescent phase. This data can contribute to evidence the precautions about the use of testosterone.” Comments for the author Reviewer’s comment: “To value your paper, another suggestion is to create a figure that explains your results and summarizes the discussion theory, if it is possible, insert in the article or supplementary data.” Authors’ reply: This study was mostly observational/descriptive and of quite a simple scheme, and wasn’t aimed at identification or verification of the mechanisms involved in the changes observed. Hence, we believe that there would be no actual benefit from adding such a figure as it would not help to see or understand better anything beyond what can be seen in the tables. - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Docosahexaenoic acid (DHA) is an essential human nutrient that may promote neural health and development. DHA occurs naturally in milk in concentrations that are influenced by many factors, including the dietary intake of the cow and the rumen microbiome. We reviewed the literature of milk DHA content and the biohydrogenation pathway in rumen of dairy cows aim to enhance the DHA content. DHA in milk is mainly derived from two sources: &#945;-linolenic acid (ALA) occurring in the liver and consumed as part of the diet, and overall dietary intake. Rumen biohydrogenation, the lymphatic system, and blood circulation influence the movement of dietary intake of DHA into the milk supply. Rumen biohydrogenation reduces DHA in ruminal environmental and limits DHA incorporation into milk. The fat-1 gene may increase DHA uptake into the body but this lacks experimental confirmation. Additional studies are needed to define the mechanisms by which different dietary sources of DHA are associated with variations of DHA in milk, the pathway of DHA biohydrogenation in the rumen, and the function of the fat-1gene on DHA supply in dairy cows.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>INTRODUCTION</ns0:head><ns0:p>Some researchers reported that milk fat could increase triglycerides in blood. However, many researches showed milk fat had no adverse effects on the concentrations of fasting blood lipids, glucose, and insulin <ns0:ref type='bibr'>(Benatar, Sidhu &amp; Stewart, 2013;</ns0:ref><ns0:ref type='bibr'>Engel Elhauge &amp; Tholstrup, 2017)</ns0:ref>. And even some study showed benefit for blood pressure supplement with milk fat <ns0:ref type='bibr'>(Rietsema et al., 2019)</ns0:ref>. Substances found in enriched milk, including medium and odd chain SFA (saturated fatty acid), globular phospholipids, unsaturated fatty acids, branched-chain fatty acids, natural trans fatty acids, vitamins K1 and K2, and calcium, have been found to have positive health effects <ns0:ref type='bibr'>(Mozaffarian &amp; Wu, 2018)</ns0:ref>. Among them, conjugated linoleic acid (CLA), which is peculiarly originated from the rumen (Jaglan, 2019), and omega-3 polyunsaturated fatty acids (n-3 PUFA) have been found to show health benefits to humans <ns0:ref type='bibr'>(Swanson, Block &amp; Mousa, 2012)</ns0:ref>. Docosahexaenoic acid (DHA, C22:6n-3) is an n-3 PUFA found in the mammalian central nervous system <ns0:ref type='bibr'>(G&#225;zquez, 2017)</ns0:ref>, making up 10% to 15% of the total cerebral fatty acids (about 10 &#181;mol/g brain). Some bacteria and lower eukaryotes can produce DHA de novo via a polyketide synthase pathway <ns0:ref type='bibr'>(Kabeya et al., 2018)</ns0:ref> but humans lack the key fat desaturase enzyme for synthesizing DHA (especially &#8710;12 and &#8710;13/n-3 desaturase). 2008 FAO/WHO (2008) recommended a daily intake of DHA+EPA of 300 mg for lactating women, recent studies shown a daily intake of 100 mg DHA for infants and 250 mg/day for adolescents DHA+ Eicosapentaenoic acid (EPA, C20:5n-3) <ns0:ref type='bibr'>(Saini and Keum 2018;</ns0:ref><ns0:ref type='bibr'>Saini et al. (2018)</ns0:ref>. The American Heart Association recommends an intake of 2-4 g/day of DHA+EPA for hypertriglyceridemia patients <ns0:ref type='bibr'>(Michael et al., 2011</ns0:ref><ns0:ref type='bibr'>). Gebauer et al., (2006)</ns0:ref> recommended an intake of approximately 500 mg/d of EPA+DHA to reduce the risk of cardiovascular disease.</ns0:p><ns0:p>However, most populations only get approximately 100 mg of DHA+EPA per day, which is much lower than the recommendations <ns0:ref type='bibr'>(Afshin et al., 2019)</ns0:ref>.</ns0:p><ns0:p>The human body can synthesize DHA in extremely limited amounts using &#945;-linolenic acid (ALA, C18:3n-3) (Plourde &amp;amp; <ns0:ref type='bibr'>Cunnane, 2007)</ns0:ref>, and only approximately 0-4% of dietary ALA may be converted to DHA <ns0:ref type='bibr'>(Burdge &amp;amp;</ns0:ref><ns0:ref type='bibr'>Wootton, 2002)</ns0:ref>, so DHA needs to be supplemented <ns0:ref type='bibr'>(Hashimoto et al., 2017)</ns0:ref>.</ns0:p><ns0:p>Milk is a possible dietary source of DHA, dietary source of DHA, but its concentration is particularly low <ns0:ref type='bibr'>(Bai et al., 2018;</ns0:ref><ns0:ref type='bibr'>Ishaq &amp; Nawaz, 2018;</ns0:ref><ns0:ref type='bibr'>Shingfield, Bonnet &amp; Scollan, 2013)</ns0:ref>. The DHA content of milk is influenced by the rumen microbiota, endogenous synthesis, and dietary intakes of DHA by dairy cows. The rumen biohydrogen content limits the efficient dietary incorporation of DHA into milk and the pathway of DHA hydrogen in the rumen is still unclear. Fat-1 gene was also used to increase DHA in milk <ns0:ref type='bibr' target='#b1'>(Wu et al., 2012)</ns0:ref>, but researches is limited. We mainly analyzed the literature and defined factors affecting the conversion of dietary DHA into milk and explored strategies to increase the DHA content in milk.</ns0:p></ns0:div> <ns0:div><ns0:head>Methodology</ns0:head><ns0:p>The scholarly articles in this review were obtained from web of knowledge, google scholar Baidu scholar and subject-specific professional websites, the date from 1999-2019. The keywords 'dairy cow', PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed 'dairy cattle', 'rumen', 'bacteria', 'biohydrogenation' 'DHA', 'microalgae' and 'fish oil' were used in </ns0:p></ns0:div> <ns0:div><ns0:head>SOURCES OF DHA IN MILK</ns0:head><ns0:p>DHA in milk comes from three major sources: those synthesized from endogenous ALA, those synthesized by the microorganisms in the rumen and intestines of cows, and those converted from the diet.</ns0:p></ns0:div> <ns0:div><ns0:head>Metabolic Conversion of ALA to DHA</ns0:head><ns0:p>DHA can be synthesized from ALA through metabolic pathways in the liver (Figure <ns0:ref type='figure'>1</ns0:ref>) <ns0:ref type='bibr'>(Kabeya et al., 2018;</ns0:ref><ns0:ref type='bibr'>Kim et al., 2014)</ns0:ref>. The process occurs in the endoplasmic reticulum and peroxisome, which are organelles. ALA is desaturated to stearidonic acid in the endoplasmic reticulum (C18:4n-3) catalyzed in a rate-limiting reaction by &#8710;6 desaturase and then converted to tetracosahexaenoic acid (C24:6n-3). Tetracosahexaenoic acid is then transferred into peroxisome where it undergoes &#946;-oxidation to form DHA. The reaction sequence for converting ALA to eicosatetraenoic acid (C20:4n-3) is as follows: ALA &#8594; eicosatrienoic acid (C20:3n-3) &#8594; C20:4n-3 <ns0:ref type='bibr'>(Kabeya et al., 2018)</ns0:ref>. &#8710;6 and &#8710;5 desaturases are the key enzymes in the metabolic pathways <ns0:ref type='bibr'>(Missotten et al., 2009)</ns0:ref> and the activity of these two desaturate enzymes can determine the amount of DHA synthesized. For example, the expressions of &#8710;6 and &#8710;5 desaturase in human subjects are positively correlated with SFA and PUFA but negatively correlated with linoleic acid (LA) and ALA in foods <ns0:ref type='bibr' target='#b2'>(Xiang et al., 2006)</ns0:ref>. Omega-6 polyunsaturated fatty acids (n-6 PUFA) are essential in human and animal diets <ns0:ref type='bibr'>(Saini &amp; Keum, 2018)</ns0:ref>. Changing the ratio of n-3:n-6 PUFA in the diet can influence the expression of &#8710;6 desaturase enzyme in rats <ns0:ref type='bibr'>(Missotten et al., 2009;</ns0:ref><ns0:ref type='bibr'>Neuringer, Anderson &amp; Connor, 1988)</ns0:ref>. <ns0:ref type='bibr'>Missotten et al., (2009)</ns0:ref> added fish oil and linseed oil to pig diets and determined the expressions of &#8710;6 and &#8710;5 desaturase in the liver, subcutaneous fat, and the longissimus dorsi muscle. The addition of fish oil increased the expression of &#8710;5 desaturase only in the longissimus dorsi muscle, but not in the liver or subcutaneous fat; the addition of linseed oil had no effect on the expression of &#8710;5 desaturase in all three tissues; the expression of &#8710;6 desaturase in all three tissues was not affected by either type of oil <ns0:ref type='bibr'>(Missotten et al., 2009)</ns0:ref>. Studies in rats have shown that protein <ns0:ref type='bibr'>(Narce et al., 1988)</ns0:ref> and micromineral <ns0:ref type='bibr'>(Johnson et al., 1989)</ns0:ref> depletion in the diet reduced the activity of the &#8710;6 desaturase enzyme. There have been no reports on the effect of dietary fat on the expression of &#8710;6 and &#8710;5 desaturases in cows.</ns0:p></ns0:div> <ns0:div><ns0:head>Synthesis of DHA by rumen microorganisms</ns0:head><ns0:p>Microorganisms, including microbes in the ocean and environment, are able to synthesize DHA de novo via a polyketide synthase pathway <ns0:ref type='bibr'>(Kabeya et al., 2018;</ns0:ref><ns0:ref type='bibr'>Dongming, Jackson, &amp; Quinn, 2015;</ns0:ref><ns0:ref type='bibr'>Xue et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Diverse and interdependent populations of bacteria, protozoa, and fungi inhabit the rumen of dairy cattle <ns0:ref type='bibr'>(Russell &amp; Rychlik, 2001)</ns0:ref> but no studies have been conducted to date that show the relationship between rumen microbes and DHA metabolism. Some articles have indicated that microbes in the rumen may synthesize DHA <ns0:ref type='bibr'>&amp; Shingfield, 2011)</ns0:ref>. The DHA in the chyme came from the rumen and originated from synthesis by rumen microorganisms or from the blood circulation into salivary secretions.</ns0:p><ns0:p>Additional research may need to focus on the identification of DHA-producing bacteria in the rumen. Increasing the content of DHA-producing bacteria present may increase DHA synthesis in the rumen, which results in more DHA in milk. In addition, there may exist interrelationships in DHA synthesis between microbial species with a functional network <ns0:ref type='bibr'>(Mora&#239;s &amp; Mizrahi, 2019)</ns0:ref>, which should be explored.</ns0:p></ns0:div> <ns0:div><ns0:head>Dietary DHA</ns0:head><ns0:p>An increase in dietary DHA can significantly increase the bodily content of DHA and the subsequent milk content of DHA <ns0:ref type='bibr'>(Scollan et al., 2001a;</ns0:ref><ns0:ref type='bibr'>Vahmani, Fredeen &amp; Glover, 2013)</ns0:ref>. Currently, the major dietary DHA sources for cows are fish oil and microalgae products.</ns0:p></ns0:div> <ns0:div><ns0:head>Fish oil</ns0:head><ns0:p>Fish oils contain a variety of n-3 PUFA, of which EPA and DHA are the most abundant <ns0:ref type='bibr'>(Mahla et al., 2017)</ns0:ref>.</ns0:p><ns0:p>Studies have been conducted on supplementing the diets of dairy cattle with fish oil (Table <ns0:ref type='table' target='#tab_2'>1</ns0:ref>) and most studies indicate that this practice could reduce milk fat. The study conducted by <ns0:ref type='bibr'>Pirondini et al. (2015)</ns0:ref> showed no negative effects of fish oil (0.8% dry matter) on milk fat when cattle were provided a low starch diet. The type of diet fed, including the percentage of forage <ns0:ref type='bibr'>(Shingfield et al., 2003)</ns0:ref> and type of forage <ns0:ref type='bibr'>(Chilliard, Ferlay &amp; Doreau, 2001)</ns0:ref>, plays an important role in milk fat concentrations. The supplementation of fish oil alone or fish oil combined with other oils (such as extruded soybean, canola oil) all resulted in improved DHA concentrations in milk <ns0:ref type='bibr'>(Vahmani, Fredeen &amp; Glover, 2013;</ns0:ref><ns0:ref type='bibr'>AbuGhazaleh et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b0'>Ramaswamy et al., 2001;</ns0:ref><ns0:ref type='bibr'>Vafa et al., 2012;</ns0:ref><ns0:ref type='bibr'>Whitlock et al., 2002)</ns0:ref>. <ns0:ref type='bibr'>Kairenius et al. (2015)</ns0:ref>, supplemented with fish oil at doses of 75, 150 and 300g/day (around 0.4, 0.8 and 1.88% diet) which increased the DHA concentration in milk (0.03, 0.05 and 0.10 g/100g total milk fatty acid or 0.22, 0.39 and 0.67 g/day in milk). Other studies have shown a positive correlation for DHA content between dietary intake and milk</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed concentrations <ns0:ref type='bibr'>(Lacasse et al., 2002)</ns0:ref>. However, increased supplementation had no constant linear relationship between dietary DHA intakes and DHA concentrations in milk. <ns0:ref type='bibr'>Donovan et al. (2000)</ns0:ref> showed that supplementation with fish oil at 0, 1 and 2 % of total diet increased DHA concentrations in milk, but that the concentration decreased with 3 % of total diet fish oil supplementation. <ns0:ref type='bibr'>Kairenius et al. (2015)</ns0:ref> reported no difference between the control group and 75 g/day supplementation group for DHA concentrations (0.03 to 0.03 g/100g total milk fatty acid or 0.22 to 0.22 g/day in milk). There may be a liner relationship between fish oil supplementation and milk DHA within certain range, which may be between 0.4% to 3%.</ns0:p><ns0:p>The DHA content of milk is also affected by the host's metabolism and the biohydrogenation pathway in the rumen. In theory, minimizing the effects of rumen biohydrogenation in the rumen could increase the DHA content of milk <ns0:ref type='bibr'>(Casta Eda-Guti&#233;rrez et al., 2007)</ns0:ref>. However, Lacasse et al. ( <ns0:ref type='formula'>2002</ns0:ref>) reported that supplementation with fish oil or rumen-protected fish oil at the same doses in the diet made no difference in the DHA concentration of milk. This effect may be due to the reduced digestibility of DHA in rumen-protected fish oil.</ns0:p><ns0:p>Dietary supplementation of fish oil can increase the DHA content of milk, but the effect of DHA intake is affected by many factors that need to be quantitatively defined.</ns0:p></ns0:div> <ns0:div><ns0:head>Microalgae</ns0:head><ns0:p>Microalgae are microscopic photosynthetic organisms found in marine and fresh waters that are used as an animal feed <ns0:ref type='bibr'>(Priyadarshani &amp; Rath, 2012)</ns0:ref>. Microalgae are a good source of protein, carbohydrates, and long chain PUFA, some of which are rich in DHA <ns0:ref type='bibr'>(Ryckebosch et al., 2014)</ns0:ref>. Microalgae have been shown to improve the DHA content in milk when used as an additive to dairy cattle feed <ns0:ref type='bibr'>(Altomonte et al., 2018)</ns0:ref>. The effects of microalgae supplementation on the fatty acid profile of milk are summarized in Table <ns0:ref type='table' target='#tab_4'>2</ns0:ref>. Supplementation with microalgae has been shown to improve the DHA concentration of milk with a negative effect on the overall fat content of milk. Microalgae supplementation has a liner relationship with the DHA content of milk <ns0:ref type='bibr'>(Altomonte et al., 2018;</ns0:ref><ns0:ref type='bibr'>Boeckaert et al., 2008;</ns0:ref><ns0:ref type='bibr'>Foug&#232;re, Delavaud &amp; Bernard, 2018;</ns0:ref><ns0:ref type='bibr'>P&#243;ti et al., 2015)</ns0:ref> and fish oil has been shown to have the same effect. Three microalgae feeding styles were utilized (microalgae, rumen protect microalgae, and microalgae oil) and each produced unique results. The feeding of rumen-protected microalgae can improve the concentration of milk DHA markedly, compared to feeding microalgae alone <ns0:ref type='bibr'>(Franklin et al., 1999)</ns0:ref>. Rumen-protected microalgae can reduce the biohydrogenation of DHA Manuscript to be reviewed dependent on the species of microalgae and its processing methods. There are many kinds of microalgae that can be used in animal diets with substantially different levels of DHA <ns0:ref type='bibr'>(Madeira et al., 2017)</ns0:ref> that can be influenced by the way they are processed. Protecting microalgae from rumen degradation can preserve approximately 45% of the DHA content versus un-protected microalgae <ns0:ref type='bibr'>(Stamey et al., 2012)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Transport ratio of DHA in milk</ns0:head><ns0:p>The efficiency of DHA incorporation from the feed into milk was low, as showed in table 3. The incorporation efficiency of DHA can be calculated as the ratio of milk DHA content to dietary DHA intake. Fish oil supplementation increased the DHA content in milk by approximately 6.86% (range from 1.35% to 14.4%),</ns0:p><ns0:p>while microalgae supplementation increased it approximately 7.08% (range from 1.09% to 14.0%). The efficiency can be influenced by many factors. The biohydrogenation of DHA in the rumen increases the amount of DHA lost by the body (Figure <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>) <ns0:ref type='bibr'>(Kairenius et al., 2018;</ns0:ref><ns0:ref type='bibr'>Kim et al., 2008;</ns0:ref><ns0:ref type='bibr'>Mattos et al., 2004;</ns0:ref><ns0:ref type='bibr'>Scollan et al., 2001;</ns0:ref><ns0:ref type='bibr'>Shingfield et al., 2003;</ns0:ref><ns0:ref type='bibr'>Shingfield et al., 2012;</ns0:ref><ns0:ref type='bibr'>Shingfield et al., 2011;</ns0:ref><ns0:ref type='bibr'>USA, 2001;</ns0:ref><ns0:ref type='bibr'>Wachira et al., 2000)</ns0:ref>. Therefore, reducing the biohydrogenation of DHA in the rumen is important for improving the DHA concentration of milk.</ns0:p></ns0:div> <ns0:div><ns0:head>TRANSPORTATION OF DIETARY DHA INTO MILK</ns0:head></ns0:div> <ns0:div><ns0:head>Ruminal Biohydrogenation</ns0:head><ns0:p>Ruminal biohydrogenation limits the transportation of dietary DHA into milk and is influenced by rumen <ns0:ref type='bibr'>(2015)</ns0:ref> showed that pyridostigmine bromide could decrease the lipase activity and the immunization against lipase may also inhibit the decomposition of triacylglycerols, just like the immunization against rumen urease inhibits ureolysis in the rumen <ns0:ref type='bibr' target='#b5'>(Zhao et al., 2015)</ns0:ref>. Manuscript to be reviewed oil at a ratio of 1:1 reduced the hydrogenation of DHA, but increased the hydrogenation of ALA in the rumen.</ns0:p><ns0:formula xml:id='formula_0'>Butyrivibrio</ns0:formula><ns0:p>However, <ns0:ref type='bibr'>Kairenius et al. (2018)</ns0:ref> reported that dietary addition of linseed oil or sunflower seed oil could promote the biohydrogenation of DHA, EPA, and ALA compared with fish oil alone. We determined that biohydrogenase is not fatty-acid specific and competition exists among unsaturated fatty acids. Short-chain unsaturated fatty acids may tend to be biohydrogenated more readily than long-chain PUFA. Therefore, understanding the mechanisms of biohydrogenation for unsaturated fatty acids and the interactions among these fatty acids in the rumen will help develop dietary strategies to reduce DHA biohydrogenation.</ns0:p></ns0:div> <ns0:div><ns0:head>Biohydrogenation Pathways of DHA in Rumen</ns0:head><ns0:p>Studies on the DHA biohydrogenation pathway in the rumen are limited. <ns0:ref type='bibr'>In 2007</ns0:ref><ns0:ref type='bibr'>, Jenkins et al. (2007)</ns0:ref> speculated that the first step in the process of DHA biohydrogenation is to convert DHA to a C22:6 isomer that is then hydrogenated to C22:5 fatty acid. However, <ns0:ref type='bibr'>Kairenius, Toivonen &amp; Shingfield (2011)</ns0:ref> showed that the C22:6 isomer was not detectable in the DHA hydrogenation process, likely due to its short lifetime or the limitation of the analytic method <ns0:ref type='bibr'>(Escobar et al., 2016)</ns0:ref>. According to a report by <ns0:ref type='bibr'>Toral et al. (2018)</ns0:ref>, some enzymes may exist relating to hydrogenation, isomerization, and migration in the EPA hydrogenation pathway. However, the specific enzymes have not been identified yet, and further studies should focus on the enzymes that regulate the DHA hydrogenation pathway in the rumen.</ns0:p></ns0:div> <ns0:div><ns0:head>OTHER FACTOR</ns0:head></ns0:div> <ns0:div><ns0:head>Fat-1 gene modification</ns0:head><ns0:p>The Fat-1 gene is present in Caenorhabditis elegans, a free-living nematode. Spychalla, Kinney &amp; Browse Manuscript to be reviewed fat-1, then transfected pef-gfp-fat-1 into cow fetal fibroblast cells and determined the fatty acid profile. They found that the expression of fat-1 gene could increase the DHA concentration in the cells. The birth of transgenic cows that carried and expressed the mammalianized fat-1 gene (mfat-1) <ns0:ref type='bibr' target='#b1'>(Wu et al., 2012)</ns0:ref> and a transgenic cow showed increased n-3 PUFA profiles and reduced n-6 PUFA in their tissues and milk <ns0:ref type='bibr'>(Liu et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b1'>Wu et al., 2012)</ns0:ref>. The effect of the fat-1 gene on the conversion of n-6 to n-3 PUFA was also confirmed in a transgenicpig model <ns0:ref type='bibr'>(Kang et al., 2004;</ns0:ref><ns0:ref type='bibr'>Li et al., 2018)</ns0:ref>. These findings need to be validated in a large cohort of transgenic animals to support these conclusions.</ns0:p></ns0:div> <ns0:div><ns0:head>CONCLUSIONS</ns0:head><ns0:p>The literature is limited regarding the conversion of ALA to DHA in tissues and its effect on DHA content in milk. Many studies have focused on increasing the DHA concentration in milk by manipulation of the DHA supply in the diet. Many dietary factors can influence DHA's passage into milk and their effects need to be quantitated. The majority of dietary DHA is biohydrogenated in the rumen. It is extremely important to reduce our reliance on rumen biohydrogenation and find alternative means for synthesizing DHA.</ns0:p><ns0:p>The fat-1 gene from nematodes is highly effective in converting n-6 PUFA to n-3 PUFA. Since the gene does not exist in mammals, transgenic techniques have been applied, which have been successful in cows, pigs and mice. Thus, it may be worthwhile to examine enlarging the transgenic population. From the joint FAO/WHO expert consultation on fats and fatty acids in human nutrition, 10-14.</ns0:p><ns0:p>Petri Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:p>C=control. T1, 2, 3=treatments.</ns0:p><ns0:p>RPA: rumen protected algae; RUA: rumen unprotected algae.</ns0:p><ns0:p>ND: Not detected.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed DHA intake: reported in the article or calculation: dry matter intake&#215;fatty content of diet&#215;DHA content.</ns0:p><ns0:p>Fatty acid&#8776;triacylglycerols + diacylglycerols + monoacylglycerols + free fatty acids.</ns0:p><ns0:p>Milk fatty acid =milk fat content&#215;99.13% <ns0:ref type='bibr'>(MacGibbon &amp; Taylor 2006)</ns0:ref>.</ns0:p><ns0:p>Milk DHA yield: reported in the article or calculation: milk fatty yield&#215;DHA content.</ns0:p><ns0:p>Efficiency: milk DHA/ diet DHA.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>the search. All of the articles included in this review were peer-reviewed. The article chose in this paper should show the relation between DHA with dairy cow bacteria or rumen biohydrogenation. The qualitative and quantitative articles were reviewed in this paper. The qualitative articles provide insights into problems by helping to understand the reason and opinions. The quantitative articles use measurable data to express facts and discover research patterns.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>in the rumen.Stamey, Shepherd, Veth &amp; Corl (2012) supplemented with 150 g/day of microalgae and 194 g/day of microalgae oil, respectively, and found that the microalgae oil supplementation produced a lower milk fat content, DHA concentration and efficient transport of dietary DHA into milk compared with supplementation of microalgae. The DHA in microalgae oil is able to be biohydrogenated in the rumen more easily than microalgae, although DHA is chosen as a source of dietary DHA more often.Moate et al. (2013) reported that there is an exact linear relationship between microalgae intake and the DHA content of milk. However, no experiments have revealed the range in which microalgae supplementation has a linear relationship with the DHA concentration of milk.An increased concentration of DHA in milk depends on the DHA content in dietary microalgae and isPeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure2shows how dietary DHA is moved through the body into the milk. The majority of dietary DHA is hydrogenated in the rumen, with 60-98% of DHA transformed in the rumen to the corresponding geometric isomers via cis-trans isomerization of double bonds in DHA(NRC, 2001; Scollanet al. 2001; Kim et al. 2008; Kim et al. 2008; Shingfield et al 2011; Shingfield et al 2012; Kairenius et al 2018 ). Intact DHA (or by-pass) flows into the small intestine where approximately 70-100% is absorbed(Doreau et al. 1994; Wachira et al. 2000; NRC 2001; Scollanet al. 2001; Mattos et al. 2004). It is then absorbed via the lymphatic system into the blood circulation system(Doreau &amp; Ferlay, 1994; Scollan et al., 2001b; USA, 2001; Wachira et al., 2000) and is transported via the blood into various tissues and organs of the body, including the brain (Al-Ghannami, Al-Adawi &amp; Ghebremeskel, 2019), bones(Saini &amp; Keum, 2018), and the reproductive system(Gholami et al., 2010), where it is used for tissue repair or energy supply via the &#946;-oxidative pathway. Only 13-25% of DHA absorbed from the small intestine is transported into milk through the mammary gland cells(Shingfield, Bonnet &amp; Scollan, 2013).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>microbes. Rumen microorganisms include bacteria, protozoa, and fungi. Bacteria play an important role in the biohydrogenation process(Louren, Ramos-Morales, and Wallace, 2010). DHA has two dietary forms: free fatty acids and triacylglycerols. Triacylglycerols must be converted into free fatty acids and then must undergo biohydrogenation by the rumen microbes. Thus, two kinds of microorganisms exist with lipolytic effects and biohydrogenation properties.The lipolytic effect of triacylglycerols mainly depended on the lipase, Anaerovibrio lipolyticus, which isPeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020) Manuscript to be reviewed a prominent ruminal lipase-producing bacterium (Hungate, 1966). Three putative lipase genes were identified from the draft genome of Anaerovibrio lipolyticus (alipA, alipB, alipC) (Priv&#233; et al., 2013) and had greater hydrolytic activity against caprylate (C8:0), laurate (C12:0), and myristate (C14:0). Butyrivibrio fibrisolvens, Propionibacterium (Edwards et al., 2012) Clostridium, Propionibacterium, Staphylococcus (Edwards et al., 2013), and Pseudomonas aeruginosa (Priji et al., 2017) are among the bacteria that have the ability to decompose triacylglycerols. Sargolzehi et al.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>2012) proposed that DHA and other unsaturated fatty acids could lengthen the bacteria's lag phase. It is well known that rumen bacteria release hydrogens and secrete isomerases, which may hydrogenate the double bonds in unsaturated fatty acids. The biohydrogenase in the rumen is a major factor regulating the biohydrogenation of PUFA. Further studies should focus on the relationship between rumen microbes, DHA, and biohydrogenase.The formation of DHA can also be influenced by the intake of LA. LA can be converted into highlyunsaturated fatty acids (HUFA) in vivo. LA and ALA share the same family of enzymes in the formation of HUFA (Fleming &amp; Kris-Etherton, 2014), and compete with one another for enzyme uptake (Gibson, Muhlhausler &amp; Makrides, 2015). Increasing the intake of LA may reduce the formation of DHA from ALA. A study showed that high LA diet could reduce the content of DHA in milk (Aprianita et al. 2014). However, DHA synthesis by ALA in tissues is very low and yet not reported in dairy cows. Ruminal biohydrogenation process is well-studied and understood. The content of unsaturated fatty acids in the diet can influence the biohydrogenation of DHA in the rumen, to various effects. In an in vitro study, Chow et al. (2004) found that adding LA and ALA could reduce the biohydrogenation of DHA, which was confirmed in an in vitro experiment (Wasowska et al., 2006). Shingfield et al. (2011) found that dietary supplementation of both fish oil and linseed PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>Aldai et al. (2018) investigated the biohydrogenation process of DHA in in vitro fermentation using sheep rumen fluid as the inoculator, and determined the metabolites of DHA at 0, 1-, 2-, 3-, and 6-hours after fermentation. They found that DHA was initially transformed into mono trans methylene interrupted DHA and monoconjugated DHA. Nevertheless, the DHA hydrogenation process started from the isomer formation. Jeyanathan, et al. (2016) used in vitro anaerobic fermentation with a single strain of Butyrivibrio proteoclasticus P18 to explore the biohydrogenation process of DHA during fermentation and showed the product in the DHA biohydrogenation pathway. This experiment showed that 12 kinds of DHA intermediates (C22:5, C22:4, C22:3 and C22:2 isomers) were transformed in 48h. Toral et al. (2018) found that Docosapentaenoic acid may be a major DHA intermediate product. DHA intermediates and the hydrogenation pathway in the rumen are illustrated in Figure 3.The literature is lacking for enzymes that may regulate the DHA hydrogenation pathway in the rumen.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>( 1997 )</ns0:head><ns0:label>1997</ns0:label><ns0:figDesc>first reported the fat-1 gene in Caenorhabditis elegans, and specifically expressed the gene in Arabidopsis, confirming the cDNA (complementary DNA) sequence of the fat-1 gene. The translation product of the fat-1 gene is n-3 PUFA dehydrogenase, which can catalyze the formation of the corresponding n-3 PUFA using 18-20 carbon n-6 PUFA as the substrate (Kang, 2005). The expression of the fat-1 gene can promote the synthesis of n-3 PUFA in nematodes. Liu et al. (2017) constructed the eukaryotic expression vector pef-gfp-PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>Neuringer M, Anderson GJ, Connor WE. 1988. The essentiality of n-3 fatty acids for the development and function of the retina and brain. Annual Review of Nutrition, 8 (1), 517. DOI 10.1146/annurev.nu.08.070188.002505. Organization WH. 2008. Interim summary of conclusions and dietary recommendations on total fat &amp; fatty acids.</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head /><ns0:label /><ns0:figDesc>independently. For example, Bianchi et al. (2014) found that Cellulophaga can produce DHA. Cellulophaga</ns0:figDesc><ns0:table><ns0:row><ns0:cell>belongs to phylum Bacteroidetes which is the most abundant phylum in the rumen of older dairy cows (Jami et</ns0:cell></ns0:row><ns0:row><ns0:cell>al., 2013), and infers that there may be a kind of microbe (belong to phylum Bacteroidetes) in the rumen that can</ns0:cell></ns0:row><ns0:row><ns0:cell>produce DHA. Yarrowia lipolytica is a yeast widely distributed in the natural environment that can also produce</ns0:cell></ns0:row><ns0:row><ns0:cell>DHA (Dongming, Jackson &amp;amp; Quinn, 2015; Damude et al., 2006; Gong et al., 2014), however, it is not clear</ns0:cell></ns0:row><ns0:row><ns0:cell>if yeast living in the rumen can produce DHA (Prakasan et al., 2013). In an in vivo experiment with dairy cows,</ns0:cell></ns0:row><ns0:row><ns0:cell>the animals were fed diets containing linseeds or no linseeds, and no DHA at all, but DHA was subsequently</ns0:cell></ns0:row><ns0:row><ns0:cell>found in the duodenal chyme (0.07 g/d and 0.08 g/d, respectively) (Shingfield K J , Lee M R F , Humphries D J</ns0:cell></ns0:row><ns0:row><ns0:cell>, et al. Effect of linseed oil and fish oil alone or as an equal mixture on ruminal fatty acid metabolism in growing</ns0:cell></ns0:row><ns0:row><ns0:cell>steers fed maize silage-based diets[J]. Journal of Animal Science, 2011, 89(11):3728-41) (Kairenius, Toivonen</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head /><ns0:label /><ns0:figDesc>sp. is a genus of an important microbe that hydrogenates PUFA in the rumen; it includes</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Butyrivibrio fibrisolvens (B. fibrisolvens), and Butyrivibrio proteoclasticus (B. proteoclasticus). B. fibrisolvens</ns0:cell></ns0:row><ns0:row><ns0:cell>can produce isomerase and change the PUFA structure (for example, converting LA into CLA) (Kepler et al.,</ns0:cell></ns0:row><ns0:row><ns0:cell>1966). Trans-11 vaccenic acid (C18:1), converted from LA, can be hydrogenated to stearic acid (C18:0) by B.</ns0:cell></ns0:row></ns0:table><ns0:note>proteoclasticus(Jenkins et al., 2007). However, some studies show that B. fibrisolvens failed to successfully induce DHA hydrogenation in the rumen(Jeyanathan, et al., 2016; Maia et al., 2007). B. proteoclasticus could hydrogenate DHA(Jeyanathan et al., 2016) in vitro in a growth medium containing autoclaved ruminal fluid.Bacterial species, such as Acetobacter(Bainbridge, et al., 2016) and Bacillus(Petri et al., 2014), but not Butyrivibrio sp., can affect DHA biohydrogenation. However, an experiment by Sakurama et al. (2014) reported that no bacteria (100 strains of anaerobic bacteria were used, Acetobacter was included) metabolized DHA.Dietary PUFA has been shown to strongly influence microbial profiles in the rumen. Many studies have shown that DHA intake in a reduction of B. fibrisolvens in the rumen in a dose-dependent manner(Shingfield et al., 2012; Maia et al., 2010; Shinji et al., 2009). Abughazaleh &amp; Ishlak (2014) reported that supplement with DHA could reduce the abundance of B. proteoclasticus, but other experiments have shown no effect. Shingfield et al.</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>RM, Mapiye C, Dugan ME, Mcallister TA. 2014. Subcutaneous adipose fatty acid profiles and related rumen bacterial populations of steers fed red clover or grass hay diets containing flax or sunflower-seed. Plos One, 9 (8):e104167 DOI 10.1371/journal.pone.0104167. Pi Y, Gao ST, Ma L, Zhu YX, Wang JQ, Zhang JM, Xu JC, Bu DP. 2016. Effectiveness of rubber seed oil and flaxseed oil to enhance the &#945;-linolenic acid content in milk from dairy cows. Journal of Dairy Science, 99 (7):5719-5730 DOI 10.3168/jds.2015-9307. Pirondini M, Colombini S, Mele M, Malagutti L, Rapetti L, Galassi G, Crovetto GM. 2015. Effect of dietary starch concentration and fish oil supplementation on milk yield and composition, diet digestibility, and methane emissions in lactating dairy cows. Journal of Dairy Science, 98 (1):357-372. DOI 10.3168/jds.2014-8092. The effects of dietary supplementation of fish oil on milk fat content</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Plourde M, Cunnane SC. 2007. Extremely limited synthesis of long chain polyunsaturates in adults: implications</ns0:cell></ns0:row><ns0:row><ns0:cell>for their dietary essentiality and use as supplements. Applied Physiology, Nutrition, and Metabolism, 32</ns0:cell></ns0:row><ns0:row><ns0:cell>(4):619-634 DOI 10.1139/H07-034.</ns0:cell></ns0:row><ns0:row><ns0:cell>P&#243;ti P, Pajor F, Bodn&#225;r &#193;, Penksza K. K&#246;les P. 2015. Effect of micro-alga supplementation on goat and cow</ns0:cell></ns0:row><ns0:row><ns0:cell>milk fatty acid composition. Chilean Journal of Agricultural Research, 75 (2):259-263 DOI 10.4067/S0718-</ns0:cell></ns0:row><ns0:row><ns0:cell>58392015000200017.</ns0:cell></ns0:row><ns0:row><ns0:cell>Prakasan P, Unni KN, Sajith S. Sailas B. 2013. Candida tropicalis bpu1, a novel isolate from the rumen of the</ns0:cell></ns0:row><ns0:row><ns0:cell>malabari goat, is a dual producer of biosurfactant and polyhydroxybutyrate. Yeast, 30 (3):103-110 DOI</ns0:cell></ns0:row><ns0:row><ns0:cell>10.1002/yea.2944.</ns0:cell></ns0:row><ns0:row><ns0:cell>Priji P, Sajith S, Unni KN, Anderson RC, Benjamin S. 2017. Pseudomonas sp. Bup6, a novel isolate from</ns0:cell></ns0:row><ns0:row><ns0:cell>malabari goat produces an efficient rhamnolipid type biosurfactant. Journal of Basic Microbiology, 57</ns0:cell></ns0:row><ns0:row><ns0:cell>(1):21-33 DOI 10.1002/jobm.201600158.</ns0:cell></ns0:row><ns0:row><ns0:cell>Priv&#233; F, Kaderbhai NN, Girdwood S, Worgan HJ, Pinloche E, Scollan ND, Huws SA, Newbold CJ. 2013.</ns0:cell></ns0:row><ns0:row><ns0:cell>Identification and characterization of three novel lipases belonging to families ii and v from anaerovibrio</ns0:cell></ns0:row><ns0:row><ns0:cell>lipolyticus 5st. Plos One, 8 (8) DOI 69076.10.1371/journal.pone.0069076.</ns0:cell></ns0:row><ns0:row><ns0:cell>Priyadarshani I, Rath, B. 2012. Commercial and industrial applications of micro algae-a review. J algal biomass</ns0:cell></ns0:row><ns0:row><ns0:cell>utln, 3 (4), 89-100.</ns0:cell></ns0:row><ns0:row><ns0:cell>Qin L, Xu J, Han S, Zheng Z, Zhao Y, Szeto IM. 2015. Dairy consumption and risk of cardiovascular disease:</ns0:cell></ns0:row><ns0:row><ns0:cell>an updated meta-analysis of prospective cohort studies. Asia Pacific Journal of Clinical Nutrition, 24 (1):90-</ns0:cell></ns0:row></ns0:table><ns0:note>1 PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>The effects of dietary supplementation of microalgae on milk fat content</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Fatty acid&#8776;triacylglycerols + diacylglycerols + monoacylglycerols + free fatty acids. Milk</ns0:cell></ns0:row><ns0:row><ns0:cell>fatty acid =milk fat content&#215;99.13% ( MacGibbon &amp; Taylor 2006) . C=control. T1, 2,</ns0:cell></ns0:row><ns0:row><ns0:cell>3=treatments. RPA: rumen protected algae; RUA: rumen unprotected algae. ND: Not</ns0:cell></ns0:row><ns0:row><ns0:cell>detected.</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)Manuscript to be reviewed 1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>The effects of dietary supplementation of microalgae on milk fat content</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Treatment</ns0:cell><ns0:cell>Microalgae supplement (g/d)</ns0:cell><ns0:cell>Diet DHA intake (g/d)</ns0:cell><ns0:cell>Milk fatty acid (%)</ns0:cell><ns0:cell>DHA content in milk g/d</ns0:cell><ns0:cell>Increase of DHA content in control group) (g/d) milk (compared with</ns0:cell><ns0:cell>Reference</ns0:cell></ns0:row><ns0:row><ns0:cell>C=basal diet</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>4.75</ns0:cell><ns0:cell>0.13</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>Boeckaert et al., 2008</ns0:cell></ns0:row><ns0:row><ns0:cell>T=basal diet + RPA</ns0:cell><ns0:cell>899</ns0:cell><ns0:cell>43.7</ns0:cell><ns0:cell>2.18</ns0:cell><ns0:cell>1.45</ns0:cell><ns0:cell>1.32</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>C=basal diet</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>0.05</ns0:cell><ns0:cell>3.36</ns0:cell><ns0:cell>0.70</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>Foug&#232;re, Delavaud &amp; Bernard, 2018</ns0:cell></ns0:row><ns0:row><ns0:cell>T=basal diet + RUA</ns0:cell><ns0:cell>310</ns0:cell><ns0:cell>115</ns0:cell><ns0:cell>2.62</ns0:cell><ns0:cell>13.6</ns0:cell><ns0:cell>12.9</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>C=basal diet</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>ND</ns0:cell><ns0:cell>4.75</ns0:cell><ns0:cell>0.10</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>P&#243;ti et al., 2015</ns0:cell></ns0:row><ns0:row><ns0:cell>T=basal diet + RUA</ns0:cell><ns0:cell>150</ns0:cell><ns0:cell>ND</ns0:cell><ns0:cell>3.46</ns0:cell><ns0:cell>0.14</ns0:cell><ns0:cell>0.04</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>C=basal diet</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>3.67</ns0:cell><ns0:cell>0.00</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>Franklin, et al., 1999</ns0:cell></ns0:row><ns0:row><ns0:cell>T1=basal diet + RPA</ns0:cell><ns0:cell>910</ns0:cell><ns0:cell>29.2</ns0:cell><ns0:cell>2.92</ns0:cell><ns0:cell>5.15</ns0:cell><ns0:cell>5.15</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>T2=basal diet + RUA</ns0:cell><ns0:cell>910</ns0:cell><ns0:cell>35.9</ns0:cell><ns0:cell>2.92</ns0:cell><ns0:cell>3.23</ns0:cell><ns0:cell>3.23</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>C=basal diet</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>3.47</ns0:cell><ns0:cell>0.10</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>Stamey et al., 2012</ns0:cell></ns0:row><ns0:row><ns0:cell>T1= basal diet + 0.5&#215;RUA</ns0:cell><ns0:cell>150</ns0:cell><ns0:cell>21.6</ns0:cell><ns0:cell>3.97</ns0:cell><ns0:cell>0.50</ns0:cell><ns0:cell>0.40</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>T2= basal diet + 1&#215;RUA</ns0:cell><ns0:cell>300</ns0:cell><ns0:cell>43.2</ns0:cell><ns0:cell>3.27</ns0:cell><ns0:cell>0.59</ns0:cell><ns0:cell>0.49</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>T3= basal diet + 1&#215;RUA oil</ns0:cell><ns0:cell>194</ns0:cell><ns0:cell>27.4</ns0:cell><ns0:cell>3.27</ns0:cell><ns0:cell>0.30</ns0:cell><ns0:cell>0.20</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>C=basal diet</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>4.93</ns0:cell><ns0:cell>0.44</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>Moate et al. 2013</ns0:cell></ns0:row><ns0:row><ns0:cell>T1=basal diet + RUA</ns0:cell><ns0:cell>125</ns0:cell><ns0:cell>25.0</ns0:cell><ns0:cell>3.75</ns0:cell><ns0:cell>3.51</ns0:cell><ns0:cell>3.07</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>T2=basal diet + RUA</ns0:cell><ns0:cell>250</ns0:cell><ns0:cell>50.0</ns0:cell><ns0:cell>3.67</ns0:cell><ns0:cell>5.09</ns0:cell><ns0:cell>4.65</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>T3=basal diet + RUA</ns0:cell><ns0:cell>375</ns0:cell><ns0:cell>75.0</ns0:cell><ns0:cell>3.80</ns0:cell><ns0:cell>7.70</ns0:cell><ns0:cell>7.26</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>C=basal (diet + Hydrogenated palm oil fat</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>3.90</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>Moran et al., 2018</ns0:cell></ns0:row><ns0:row><ns0:cell>T=basal diet + RUA</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>17.8</ns0:cell><ns0:cell>3.81</ns0:cell><ns0:cell>1.32</ns0:cell><ns0:cell>1.32</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='5'>2 Fatty acid&#8776;triacylglycerols + diacylglycerols + monoacylglycerols + free fatty acids.</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>3 Milk fatty acid =milk fat content&#215;99.13%(MacGibbon &amp; Taylor 2006).PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Efficiency of dietary incorporation of DHA into milk DHA intake: reported in the article or calculation: dry matter intake&#215;fatty content of diet&#215;DHA content. Fatty acid&#8776;triacylglycerols + diacylglycerols + monoacylglycerols + free fatty acids. Milk fatty acid =milk fat content&#215;99.13% ( MacGibbon &amp; Taylor 2006) . Milk DHA yield: reported in the article or calculation: milk fatty yield&#215;DHA content. Efficiency: milk DHA/ diet DHA</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:48138:1:1:NEW 31 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Efficiency of dietary incorporation of DHA into milk</ns0:figDesc><ns0:table><ns0:row><ns0:cell>DHA source</ns0:cell><ns0:cell>DHA in take (g/d)</ns0:cell><ns0:cell>Milk DHA yield (g/d)</ns0:cell><ns0:cell>Efficiency (%)</ns0:cell><ns0:cell>Reference</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>14.30</ns0:cell><ns0:cell>0.57</ns0:cell><ns0:cell>3.99</ns0:cell><ns0:cell>Donovan et al., 2000</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>50.66</ns0:cell><ns0:cell>1.97</ns0:cell><ns0:cell>3.89</ns0:cell><ns0:cell>Donovan et al., 2000</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>92.63</ns0:cell><ns0:cell>1.25</ns0:cell><ns0:cell>1.35</ns0:cell><ns0:cell>Donovan et al., 2000</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>21.27</ns0:cell><ns0:cell>2.49</ns0:cell><ns0:cell>11.7</ns0:cell><ns0:cell>Abughazaleh et al., 2002</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>12.20</ns0:cell><ns0:cell>1.46</ns0:cell><ns0:cell>12.0</ns0:cell><ns0:cell>Abughazaleh et al., 2002</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>11.07</ns0:cell><ns0:cell>1.59</ns0:cell><ns0:cell>14.4</ns0:cell><ns0:cell>Whitlock et al., 2002</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>9.07</ns0:cell><ns0:cell>0.97</ns0:cell><ns0:cell>10.7</ns0:cell><ns0:cell>Whitlock et al., 2002</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>31.71</ns0:cell><ns0:cell>2.18</ns0:cell><ns0:cell>6.87</ns0:cell><ns0:cell>Vafa et al., 2012</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>12.87</ns0:cell><ns0:cell>0.84</ns0:cell><ns0:cell>6.53</ns0:cell><ns0:cell>Vafa et al., 2012</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>24.66</ns0:cell><ns0:cell>1.68</ns0:cell><ns0:cell>6.81</ns0:cell><ns0:cell>Vahmani et al., 2013</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>17.55</ns0:cell><ns0:cell>0.40</ns0:cell><ns0:cell>2.28</ns0:cell><ns0:cell>Pirondini et al., 2015</ns0:cell></ns0:row><ns0:row><ns0:cell>Fish oil</ns0:cell><ns0:cell>18.53</ns0:cell><ns0:cell>0.34</ns0:cell><ns0:cell>1.83</ns0:cell><ns0:cell>Pirondini et al., 2015</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae</ns0:cell><ns0:cell>35.94</ns0:cell><ns0:cell>3.23</ns0:cell><ns0:cell>8.99</ns0:cell><ns0:cell>Franklin et al., 1999</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae</ns0:cell><ns0:cell>43.68</ns0:cell><ns0:cell>1.45</ns0:cell><ns0:cell>3.32</ns0:cell><ns0:cell>Boeckaert et al., 2009</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae</ns0:cell><ns0:cell>25.00</ns0:cell><ns0:cell>3.51</ns0:cell><ns0:cell>14.0</ns0:cell><ns0:cell>Moate et al., 2013</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae</ns0:cell><ns0:cell>50.00</ns0:cell><ns0:cell>5.09</ns0:cell><ns0:cell>10.2</ns0:cell><ns0:cell>Moate et al., 2013</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae</ns0:cell><ns0:cell>75.00</ns0:cell><ns0:cell>7.70</ns0:cell><ns0:cell>10.3</ns0:cell><ns0:cell>Moate et al., 2013</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae</ns0:cell><ns0:cell>21.61</ns0:cell><ns0:cell>0.50</ns0:cell><ns0:cell>2.31</ns0:cell><ns0:cell>Stamey et al,. 2012</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae</ns0:cell><ns0:cell>43.23</ns0:cell><ns0:cell>0.59</ns0:cell><ns0:cell>1.36</ns0:cell><ns0:cell>Stamey et al,. 2012</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae oil</ns0:cell><ns0:cell>27.41</ns0:cell><ns0:cell>0.30</ns0:cell><ns0:cell>1.09</ns0:cell><ns0:cell>Stamey et al,. 2012</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae</ns0:cell><ns0:cell>17.82</ns0:cell><ns0:cell>1.32</ns0:cell><ns0:cell>7.41</ns0:cell><ns0:cell>Moran et al,. 2017</ns0:cell></ns0:row><ns0:row><ns0:cell>Microalgae</ns0:cell><ns0:cell>115.5</ns0:cell><ns0:cell>13.6</ns0:cell><ns0:cell>11.8</ns0:cell><ns0:cell>Foug&#232;re et al. 2018</ns0:cell></ns0:row></ns0:table></ns0:figure> </ns0:body> "

"Response to Reviewer Comments Dear Editor and Reviewers: Thank you for your letter and for the reviewers’ comments concerning our manuscript entitled “DHA Content in Milk and Biohydrogenation Pathway in Rumen: A Review” (#2020:04:48138:0:4:REVIEW). Those comments are all valuable and very helpful for revising and improving our paper. We have revised our paper point by point with the comments of the reviewer which we hope meet with approval. In order to make it clear, the revised part was highlight in yellow and further explanations were typed in blue. Revised portions were also highlight in yellow in the paper. The main corrections in the paper and the responds to the reviewer’s comments are as following: Referee: 1 The Manuscript 48138v1 is a review on DHA content in milk and biohydrogenation pathway in rumen. The manuscript is a review but it is difficult to understand exactly what is the objective of the review? It is difficult to find a reflection or input from the authors in each of their results and discussion paragraphs.  [Response] The objective of the review is as following: We analyzed the literature and defined factors affecting the conversion of dietary DHA into milk and explored strategies to increase the DHA content in milk. And mainly talk about the DHA biohydrogenation in rumen The review lack of structure and it is difficult to understand its rationale. For example, suddenly Fat-1 gene appears in the end of the document, but this is not explained in the introduction? It just seems that authors just enumerated results from different documents but they do not discussed them with profound criticism. The manuscript should be revised for its English style. [Response] According to your suggestion, we have remained a part of paragraphs. And the English style was also revised. I have added the explain of Fat-1 gene in the introduction, as following: Fat-1 gene was also used to increase DHA in milk (Wu et al., 2012), but researches is limited. Abstract Lines 27-29 please rewrite and improve English structure, [Response] This sentence has been revised as following: We reviewed the literature of milk DHA content and the biohydrogenation pathway in rumen of dairy cows aim to enhance the DHA content. Introduction Line 49, delete, why will you have subtitles in the introduction? [Response] We have deleted the subtitles “DHA in milk” in the introduction. Lines 42-48 please update references; there is a continuous debate on the pros and cons from consuming milk fatty acids [Response] We have updated references and revised as following: Some researchers reported that milk fat could increase triglycerides in blood. However, many researches showed milk fat had no adverse effects on the concentrations of fasting blood lipids, glucose, and insulin (Benatar, Sidhu & Stewart, 2013; Engel Elhauge & Tholstrup, 2017). And even some study showed benefit for blood pressure supplement with milk fat (Rietsema et al., 2019). Line 72 should say Methods or Methodology [Response] “Review methodology” has been revised to “methodology” Lines 73-79 provide range of dates or months you used for your search, provide data bases used i.e., scopus, web of knowledge, google scholar? [Response] We have added the information as following The scholarly articles in this review were obtained from web of knowledge, google scholar Baidu scholar and subject-specific professional websites, the date from 1999-2019. What do you mean by qualitative and quantitative articles? [Response] Qualitative articles focused on proving the view, while quantitative articles focused on providing data. Tables 1 and 2. What is milk fatty acid (%), is it milk fat content? Please change accordingly [Response] We have added the calculation method, as following: Fatty acid≈triacylglycerols + diacylglycerols + monoacylglycerols + free fatty acids Milk fatty acid =milk fat content×99.13% (MacGibbon & Taylor 2006) Check the use of decimals in your tables, also if control diets do not have fish oil or algae then use a “–“ which means the same and use it in all places where you do not have data. For decimals use 3 digits, for example 345, 3.45, 0.34 [Response] We have added the introduction of “milk fat content” and revised the data in the table 1 and 2. See details in the revised tables. Referee: 2 Line 31-33: Please, revise sentence. Rumen biohydrogenation reduces DHA in ruminal environmental and limits DHA incorporation into milk. [Response] The sentence has been revised as following: Rumen biohydrogenation reduces DHA in ruminal environmental and limits DHA incorporation into milk. Line 38: Please, list keywords in alphabetical order. [Response] The order of keywords has been revised as following: α-linolenic acid; biohydrogenation; cows; Docosahexaenoic acid; fat-1 gene; ruminal microorganism. Line 41: The introduction is very well-written. I would suggest to improve this first part of the introduction with additional information about specific CLA/LA benefits to human health, which can be increased in milk by marine origin oils in ruminant feeds. [Response] We have added the information about specific CLA/LA benefits to human health as following: Among them, conjugated linoleic acid (CLA), which is peculiarly originated from the rumen (Jaglan et al., 2019, and omega-3 polyunsaturated fatty acids (n-3 PUFA) have been found to show health benefits to humans (Swanson, Block & Mousa, 2012). Line 44: SFA - Please, define abbreviation. [Response] The define abbreviation of SFA have been added. Line 48: CVD - This abbreviation is not cited in other parts of the review. I recommend to remove it. [Response] The abbreviation CVD have been removed. Line 55-56: It’s not clear to what age or life phase the intake of 250 mg of DHA and EPA is recommended (Saini and Keum, 2018). Please, state why there is a different recommendation than the proposed by Saini et al 2018 (100 mg/d DHA for infants and 250 mg/d DHA for adolescents). [Response] The sentence has been revised as following: 2008 FAO/WHO (2008) recommended a daily intake of DHA+EPA of 300 mg for lactating women, recent studies shown a daily intake of 100 mg DHA for infants and 250 mg/day for adolescents DHA+ Eicosapentaenoic acid (EPA, C20:5n-3) (Saini and Keum 2018; Saini et al. (2018). Line 57-58: “A higher intake 58 of DHA is recommended for the treatment of disease.” - This phrase provides a poor statement. I suggest to remove it or insert it in the next sentence. [Response] This phrase have been removed. Line 66: I do not recommend to state milk as a popular dietary source of DHA, since the most recognized sources of DHA are marine products such as fish, fish oil and algae. As you said, DHA concentratoin in milk is particularly low. I suggest to reference milk as an alternative, possible, optional or promissor DHA dietary source. [Response] “Popular” has been revised to “possible”. Line 69: In my point of view, the term “convert/conversion into” is not adequate to the process. To reach milk, dietary DHA must escape ruminal biohydrogenation process, being intacted. The verb 'to convert' means to modify, to transform, what does not happen to dietary DHA that reachs milk. Please, use the term 'incorporation' or similars in all sentences. [Response] “Conversion” has been revised to “incorporation” Line 74: Please, revise whether the term should be “cattle diet”. [Response] “Diet cattle” has been revised to “dairy cattle”. Line 83: Here, the term “conversion” is used properly. [Response] Thanks for your approval. Line 104-114: The information in the cited articles must be revised (Aprianita et al. 2014/Livingstone et al. 2015). The reduction in DHA content in milk fat by LA supplementation is primarily due to effects in ruminal biohydrogenation process, and not due to organism synthesis of DHA in tissues. As stated previously, DHA synthesis by ALA in tissues is very low and yet not reported in dairy cows. However, ruminal biohydrogenation process is well-studied and understood. It is reported the BH of DHA may be increased in diets rich in C18 PUFA, reducing its content in milk (Kairenius et al., 2018). I recommend to rewrite this information and if possible, include it afterwards, in ruminal biohydrogenation process part. [Response] We have has revised this information of ruminal biohydrogenation process part as following: The formation of DHA can also be influenced by the intake of LA. LA can be converted into highly unsaturated fatty acids (HUFA) in vivo. LA and ALA share the same family of enzymes in the formation of HUFA (Fleming & Kris-Etherton, 2014), and compete with one another for enzyme uptake (Gibson, Muhlhausler & Makrides, 2015). Increasing the intake of LA may reduce the formation of DHA from ALA. A study showed that high LA diet could reduce the content of DHA in milk (Aprianita et al. 2014). However, DHA synthesis by ALA in tissues is very low and yet not reported in dairy cows. Ruminal biohydrogenation process is well-studied and understood. The content of unsaturated fatty acids in the diet can influence the biohydrogenation of DHA in the rumen, to various effects. In an in vitro study, Chow et al. (2004) found that adding LA and ALA could reduce the biohydrogenation of DHA, which was confirmed in an in vitro experiment (Wasowska et al., 2006). Shingfield et al. (2011) found that dietary supplementation of both fish oil and linseed oil at a ratio of 1:1 reduced the hydrogenation of DHA, but increased the hydrogenation of ALA in the rumen. However, Kairenius et al. (2018) reported that dietary addition of linseed oil or sunflower seed oil could promote the biohydrogenation of DHA, EPA, and ALA compared with fish oil alone. We determined that biohydrogenase is not fatty-acid specific and competition exists among unsaturated fatty acids. Short-chain unsaturated fatty acids may tend to be biohydrogenated more readily than long-chain PUFA. Therefore, understanding the mechanisms of biohydrogenation for unsaturated fatty acids and the interactions among these fatty acids in the rumen will help develop dietary strategies to reduce DHA biohydrogenation. Line 128: Please, I recommend to correct the reference. This article does not support the statement (Kairenius, Toivonen & Shingfield, 2011). [Response] It was a mistake, and we have corrected the reference, as following: (Shingfield et al., 2011) Line 132: Please, revise term ”to” to “the”. [Response] “To” has been revised to “the” as following: Line 177: Please, correct the text to “concentrations of DHA”. [Response] We have corrected it. Line 181: Please, correct the text. Change “with” to “of” microalgae [Response] We have corrected it. Line 181-182: “The microalgae group showed 182 less efficient transport of dietary DHA into milk.” Is this phrase from the previously cited study? Please, rewrite it to make it clear. [Response] This phrase has been revised as following: Stamey, Shepherd, Veth & Corl (2012) supplemented with 150 g/day of microalgae and 194 g/day of microalgae oil, respectively, and found that the microalgae oil supplementation produced a lower milk fat content, DHA concentration and efficient transport of dietary DHA into milk compared with supplementation of microalgae. Line 183-183: Table 2 was already cited in text and do not need to be recited. Please, insert a reference to justify the statement that microalgae free-oil is more biohydrogenated than the oil fed in a microalgae. Also, rewrite the previous sentence. [Response] We got this view from the article of “Stamey, Shepherd, Veth & Corl (2012)” which mentioned above. The efficient transport of dietary DHA from microalgae oil into milk is low, but the efficiency is influenced by a lot of factors. So, we have removed this paragraph “The DHA in microalgae oil is able to be biohydrogenated in the rumen more easily than microalgae, although DHA is chosen as a source of dietary DHA more often (Table 2). Line 193-196: I’m not sure how this information was calculated, since this data is not in the published paper (Sinedino et al., 2017). Please, explain how numbers 2,86 and 3,44 were found. Also, the affirmation that multiparous cows can transfer more dietary DHA into milk than primiparous cows is not commented by the author. Multiparous cows yielded more milk, so depending on how you calculate the data, this difference is going to be there. As far as I'm concerned, the paper does not inform the individual content of DHA in milk of primiparous and multiparous cows. [Response] This paper (Sinedino et al., 2017) was planned to show that milk yield and fatty content of primiparous and multiparous cows respectively, and shared the same fatty acid content. So, we got the numbers 2.86 and 3.44. But after a discussion we have removed this paragraph “The effect of microalgae supplementation in the diet in relation to the DHA content in milk is also influenced by the lactation state of dairy cows. Sinedino et al. (2017) supplemented 100 g/d of microalgae product (containing 10 g DHA) in primary and multiparous cows, and observed that the DHA content in the primary cows was 2.86 g/d, lower than 3.44 g/d in the multiparous cows. Thus, multiparous cows can transfer more dietary DHA into milk than primary cows.” Line 199: Table S1 - I’m not sure, but I think this table was not available for me. Please, follow the recommendation suggested in Table 1 and 2. If the data is not in the paper and was calculated, please provide the equation used below the table. [Response] This part has been revised and added table 3, as following: The efficiency of DHA incorporation from the diet into milk was low, as show in table 3. The incorporation efficiency of DHA can be calculated as the ratio of milk DHA content to dietary DHA intake. Fish oil supplementation increased the DHA content in milk by approximately 6.91% (range from 1.36% to 14.45%), while microalgae supplementation improved DHA content in milk approximately 7.13% (range from 1.09% to 14.16%). The efficiency can be influenced by many factors in cow body. Line 206-207: Please, insert a reference or clarify that this is a speculation. [Response] This part has been revised, as mentioned above. Line 208: Please, correct term to “transportation”. [Response] We have corrected it. Line 221: Figure 2 was already cited and does not need to be recited. [Response] We have removed it. Line 232-233: Please, revise sentence. [Response] The sentence has been revised, as following: The lipolytic effect of triacylglycerols mainly depended on the lipase, Anaerovibrio lipolyticus, which is a prominent ruminal lipase-producing bacterium (Hungate, 1966). Line 241: Please, revise term “impotent”. [Response] We have revised it. Line 252: Please, revise the term “intakes”. [Response] We have revised it. Line 253-254: Please, revise sentence. [Response] the sentence has been revised, as following: Abughazaleh & Ishlak (2014) reported that supplement with DHA could reduce the abundance of B. proteoclasticus, but other experiments have shown no effect. Line 260: I suggest to improve this paragraph including the revised paragraph of ALA and DHA supplementation (comment 12). [Response] This part has been revised (comment 12). Line 263: This paper does not support the statement. Please, correct reference. (Kairenius, Toivonen & Shingfield (2011)). [Response] The reference has been revised, as following: Shingfield et al. (2011) Line 265: Please, correct “additions” to “addition”. [Response] “Additions” has been revised to “addition” Line 286: Docospentaenoic acid does not need to be written with a capital letter. [Response] We have revised it. Line 308-309: Please, revise sentence. I believe it is the conversion of ALA to DHA in animal tissues. [Response] We have corrected it, as following: the conversion of ALA to DHA in animal tissues. Line 321: In the references section, please, correct the term “dio” to “doi”. [Response] “Dio” has been revised to “doi” in references. Table 1: Please, revise text to “milk fat content”. The information provided is not the milk fatty acid content. This information needs to be revised, since milk fat content is different from milk fatty acid content, so the form DHA content in milk (g/d) was calculated may be inadequate. Please, after revised, describe in details below the table how the calculus was done, to avoid doubts. [Response] We have added the information of “milk fat content” and revised the data as following: Table 1. The effects of dietary supplementation of fish oil on milk fat content Treatment Fish oil addition Diet DHA intake (g/d) Milk fatty acid conten (%) DHA content in milk (g/d) Increase of DHA content in milk (compared with control group) (g/d) Reference C=basal diet - - 3.52 0.26 - Vahmani, Fredeen & Glover, 2013 T=basal diet + RUFO 200 g/d 24.7 3.37 1.68 1.42 Ca=basal diet - - 4.30 - - Pirondini et al., 2015 Ta=basal diet + RUFO 0.80 % 17.6 4.51 0.40 0.40 Cb=basal diet 0% - 4.40 0.12 Tb=basal diet + RUFO 0.80% 18.53 3.90 0.34 0.22 C=basal diet - 0.21 3.46 0.40 - AbuGhazaleh et al., 2002 T1=basal diet +RUFO 2.00 % 21.3 3.22 2.49 2.09 T2=basal diet +RUFO 1.00 % 12.2 3.45 1.46 1.06 C = basal diet - ND 3.28 ND - Ramaswamy et al., 2001 T = basal diet + RUFO 2.00 % ND 2.56 ND - C=basal diet - 0.35 3.40 0.47 - Vafa et al., 2012 T1=basal diet + RUFO 2.00 % 31.7 2.30 2.18 1.71 T2=basal diet + RUFO 1.00 % 12.9 2.45 0.84 0.37 Ca=basal diet - - 3.48 0.56 - Whitlock et al., 2002 Ta1=basal diet +RUFO 2.00 % 11.1 2.87 1.59 1.03 Ta2=basal diet +RUFO 1.00 % 9.07 3.11 0.97 0.41 Cb = basal diet - - 4.36 0.12 - Tb = basal diet + RUFO 0.80 % 18.5 3.87 0.34 0.22 C = basal diet - ND 3.27 0.30 - Kairenius et al., 2015 T1 = basal diet + RUFO 75.0 g/d ND 3.23 0.28 -0.08 T2 = basal diet + RUFO 150 g/d ND 3.14 0.42 0.12 T3 = basal diet + RUFO 300 g/d ND 3.33 0.59 0.29 C = basal diet - ND ND 0.74 - Lacasse et al., 2002 T1 = basal diet + RUFO 3.70 % ND ND 1.03 0.29 T2 = basal diet + RPFO 1.80 % ND ND 0.89 0.15 T3 = basal diet + RPFO 3.70 % ND ND 1.04 0.30 C=basal diet - - 2.94 0.19 - Donovan et al., 2000 T1=basal diet +RUFO 1.00 % 14.30 2.77 0.57 0.38 T2=basal diet +RUFO 2.00 % 50.66 2.35 1.97 1.78 T3=basal diet +RUFO 3.00 % 92.63 2.28 1.25 1.06 C = basal diet - ND 3.34 ND - Baer et al., 2001 T = basal diet + RUFO 2.00 % ND 2.27 ND - C = basal diet - ND 4.56 0.00 - Shingfield et al.,2006 T = basal diet + RUFO 1.50 % ND 2.87 0.54 0.54 Fatty acid≈triacylglycerols + diacylglycerols + monoacylglycerols + free fatty acids Milk fatty acid =milk fat content×99.13% (MacGibbon & Taylor 2006) C=control; T1, 2, 3=treatments; Ca,b= controls in article; Ta,b= treatments in article RPFO: rumen protected fish oil; RUFO: rumen unprotected fish oil ND: Not detected Table 2: Please, revise text to “milk fat content”. The information provided is not the milk fatty acid content. As said for table 1, we recommend you to follow the same suggestions. [Response] We have added the information of “milk fat content” and revised the data as following: Table 2. The effects of dietary supplementation of microalgae on milk fat content Treatment Microalgae addition (g/d) Diet DHA intake (g/d) Milk fatty acid (%) DHA content in milk g/d Increase of DHA content in milk (compared with control group) (g/d) Reference C=basal diet - - 4.75 0.13 - Boeckaert et al., 2008 T=basal diet + RPA 899 43.7 2.18 1.45 1.32 C=basal diet - 0.05 3.36 0.70 - Fougère, Delavaud & Bernard, 2018 T=basal diet + RUA 310 115 2.62 13.6 12.9 C=basal diet - ND 4.75 0.10 - Póti et al., 2015 T=basal diet + RUA 150 ND 3.46 0.14 0.04 C=basal diet - - 3.67 0.00 - Franklin, et al., 1999 T1=basal diet + RPA 910 29.2 2.92 5.15 5.15 T2=basal diet + RUA 910 35.9 2.92 3.23 3.23 C=basal diet - - 3.47 0.10 - Stamey et al., 2012 T1= basal diet + 0.5×RUA 150 21.6 3.97 0.50 0.40 T2= basal diet + 1×RUA 300 43.2 3.27 0.59 0.49 T3= basal diet + 1×RUA oil 194 27.4 3.27 0.30 0.20 C=basal diet - - 4.93 0.44 - Moate et al. 2013 T1=basal diet + RUA 125 25.0 3.75 3.51 3.07 T2=basal diet + RUA 250 50.0 3.67 5.09 4.65 T3=basal diet + RUA 375 75.0 3.80 7.70 7.26 C=basal (diet + Hydrogenated palm oil fat - - 3.90 - - Moran et al., 2018 T=basal diet + RUA 100 17.8 3.81 1.32 1.32 Fatty acid≈triacylglycerols + diacylglycerols + monoacylglycerols + free fatty acids Milk fatty acid =milk fat content×99.13% (MacGibbon & Taylor 2006) Ca, b=control. Ta, b, 1, 2, 3=treatments. RPA: rumen protected algae; RUA: rumen unprotected algae ND: Not detected "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Marine sediments contain a high diversity of micro-and macro-organisms which are important in the functioning of biogeochemical cycles. Traditionally, anthropogenic perturbation has been investigated by identifying macro-organism responses along gradients. Environmental DNA (eDNA) analyses have recently been advocated as a rapid and cost-effective approach to measuring ecological impacts and efforts are underway to incorporate eDNA tools into monitoring. Before these methods can replace or complement existing methods, robustness and repeatability of each analytical step has to be demonstrated. One area that requires further investigation is the selection of sediment DNA extraction method. Environmental DNA sediment samples were obtained along a disturbance gradient adjacent to a Chinook (Oncorhynchus tshawytscha) salmon farm in Otanerau Bay, New Zealand. DNA was extracted using four extraction kits (Qiagen DNeasy PowerSoil, Qiagen DNeasy PowerSoil Pro, Qiagen RNeasy PowerSoil Total RNA/DNA extraction/elution and Favorgen FavorPrep Soil DNA Isolation Midi Kit) and three sediment volumes (0.25 g, 2 g, and 5 g). Prokaryotic and eukaryotic communities were amplified using primers targeting the 16S and 18S ribosomal RNA genes, respectively, and were sequenced on an Illumina MiSeq. Diversity and community composition estimates were obtained from each extraction kit, as well as their relative performance in established metabarcoding biotic indices. Differences were observed in the quality and quantity of the extracted DNA amongst kits with the two Qiagen DNeasy PowerSoil kits performing best. Significant differences were observed in both prokaryotes and eukaryotes (p &lt; 0.001) richness among kits. A small proportion of amplicon sequence variants (ASVs) were shared amongst the kits (~ 3%) although these shared ASVs accounted for the majority of sequence reads (prokaryotes: 59.9%, eukaryotes: 67.2%). Differences were observed in the richness and relative abundance of taxonomic classes revealed with each kit.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Multivariate analysis showed that there was a significant interaction between 'distance' from the farm and 'kit' in explaining the composition of the communities, with the distance from the farm being a stronger determinant of community composition. Comparison of the kits against the bacterial and eukaryotic metabarcoding biotic index suggested that all kits showed similar patterns along the environmental gradient. Overall, we advocate for the use of Qiagen DNeasy PowerSoil kits for use when characterizing prokaryotic and eukaryotic eDNA from marine farm sediments. We base this conclusion on the higher DNA quality values and richness achieved with these kits compared to the other kits/amounts investigated in this study. The additional advantage of the PowerSoil Kits is that DNA extractions can be performed using an extractor robot, offering additional standardization and reproducibility of results.</ns0:p></ns0:div> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Marine sediments harbor diverse biological communities that are vital in maintaining biogeochemical cycles, food webs and ecosystem functioning. However, these communities can be significantly impacted by anthropogenic activities <ns0:ref type='bibr'>(Snelgrove, 1997;</ns0:ref><ns0:ref type='bibr'>Dell'Anno et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Studies assessing the effects of human induced perturbations on the benthic environment have traditionally involved the analysis of communities of macro-organisms <ns0:ref type='bibr'>(Papageorgiou, Sigala &amp; Karakassis, 2009;</ns0:ref><ns0:ref type='bibr' target='#b20'>Keeley, Forrest &amp; Macleod, 2013;</ns0:ref><ns0:ref type='bibr' target='#b0'>Aguado-Gim&#233;nez et al., 2015)</ns0:ref>. Micro-and meio-benthic organisms have received less attention partly due to the challenges associated with morphologically identifying the immense diversity of these organisms. Developments in environmental genomics now allow communities to be more accurately characterized. These techniques are currently being touted as cost-effective and sensitive methodologies to monitor entire biological communities in marine sediments, especially along gradients of anthropogenic disturbances <ns0:ref type='bibr'>(Pawlowski et al., 2016b;</ns0:ref><ns0:ref type='bibr' target='#b29'>Laroche et al., 2016</ns0:ref><ns0:ref type='bibr' target='#b28'>Laroche et al., , 2018;;</ns0:ref><ns0:ref type='bibr' target='#b6'>Aylagas et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b11'>Borja, 2018;</ns0:ref><ns0:ref type='bibr' target='#b23'>Keeley, Wood &amp; Pochon, 2018;</ns0:ref><ns0:ref type='bibr'>Cordier, 2020)</ns0:ref>.</ns0:p><ns0:p>Environmental genomic techniques, which enable a broad range of taxonomic groups to be characterized from environmental DNA (eDNA), have become more prevalent in the last decade <ns0:ref type='bibr'>(Taberlet et al., 2018)</ns0:ref>. The DNA in these samples originates from a combination of microbes, organisms body parts or cells contained in faeces, epidermal mucus, urine, saliva and gametes of larger organisms <ns0:ref type='bibr'>(Rees et al., 2014;</ns0:ref><ns0:ref type='bibr'>Taberlet et al., 2018)</ns0:ref>. While eDNA-based techniques (e.g. metabarcoding) are now used extensively in ecological studies <ns0:ref type='bibr' target='#b8'>(Bohmann et al., 2014)</ns0:ref>, they are also considered for routine biomonitoring purposes <ns0:ref type='bibr' target='#b5'>(Aylagas et al., 2020)</ns0:ref>. The delay in their incorporation into monitoring regimes is due, in part, to the need for each step of the process (e.g. sediment collection, DNA extraction, PCR amplification, etc.) to be demonstrated as robust and repeatable <ns0:ref type='bibr'>(Darling et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Environmental DNA methodologies have the potential for monitoring of a variety of disturbance gradients but an eDNA application that is close to uptake and implementation is the use of metabarcoding for monitoring benthic impacts of fish farming <ns0:ref type='bibr' target='#b5'>(Aylagas et al., 2020)</ns0:ref>. Sea-cagebased fish farms are inevitably associated with elevated fluxes of organic waste, often culminating in severe localized benthic enrichment (i.e. anoxic and azoic conditions directly beneath the farms), which gradually decreases with distance from the fish cages <ns0:ref type='bibr'>(Brooks &amp; Mahnken, 2003a,b)</ns0:ref>. Routine monitoring of the benthic environment is usually required by regulation and traditional monitoring methods typically involve measuring the chemical properties of sediment and microscopic analysis of macrofaunal diversity <ns0:ref type='bibr'>(Keeley, Macleod &amp; Forrest, 2012)</ns0:ref>. In New Zealand for example, these parameters are incorporated into an Enrichment Stage (ES) index <ns0:ref type='bibr'>(Keeley, Macleod &amp; Forrest, 2012;</ns0:ref><ns0:ref type='bibr'>Keeley et al., 2012;</ns0:ref><ns0:ref type='bibr'>MPI, 2018)</ns0:ref>, which provides regulators and producers with an integrated, weight-of-evidence-based measure of environmental impact. Morphological approaches, however, are often timeconsuming, expensive, and require a high level of taxonomic expertise that is shrinking globally <ns0:ref type='bibr' target='#b16'>(Jones, 2008)</ns0:ref>. These limitations have led to numerous metabarcoding investigations describing the ecological responses of a wide range of organisms associated with enrichment states, including bacteria <ns0:ref type='bibr'>(Fodelianakis et al., 2015;</ns0:ref><ns0:ref type='bibr'>Dowle et al., 2015;</ns0:ref><ns0:ref type='bibr'>Verhoeven et al., 2018;</ns0:ref><ns0:ref type='bibr'>Stoeck et al., 2018a), foraminifera (He et al.;</ns0:ref><ns0:ref type='bibr'>Pawlowski et al., 2014</ns0:ref><ns0:ref type='bibr'>Pawlowski et al., , 2016a;;</ns0:ref><ns0:ref type='bibr'>Pochon et al., 2015)</ns0:ref>, ciliates <ns0:ref type='bibr'>(Stoeck et al., 2018b)</ns0:ref>, metazoans <ns0:ref type='bibr' target='#b33'>(Lejzerowicz et al., 2015)</ns0:ref>, or a combination of multitrophic taxa <ns0:ref type='bibr' target='#b23'>(Keeley, Wood &amp; Pochon, 2018;</ns0:ref><ns0:ref type='bibr'>Fr&#252;he et al., 2020)</ns0:ref>. Although all of these studies have revealed consistent organismal responses to fish farm enrichment, indicating that metabarcoding is a cost-effective tool for routine monitoring, they have all used different sediment collection methods, varying amounts of starting material (from 0.25 g to 10 g of sediment), and a variety of DNA extraction kits. The succesful uptake of metabarcoding tools for commercial monitoring of fish farms requires a fully standardized and validated laboratory workflow. There is a need to evaluate the effects that DNA extraction methods have on the detection of bioindicator taxa and the entire community diversity.</ns0:p><ns0:p>One of the complexities with analysis of sediment samples is that they are remarkably variable in chemical composition and physical properties across spatial scales. This variability can have an impact on the absorption of eDNA, with clays and humic acids having a strong binding capacity for DNA molecules <ns0:ref type='bibr'>(Dell'Anno, Stefano &amp; Danovaro, 2002)</ns0:ref>. Other factors such as temperature and porewater pH have an impact on the retention and stability of DNA <ns0:ref type='bibr' target='#b36'>(Levy-Booth et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b35'>Torti, Lever &amp; J&#248;rgensen, 2015)</ns0:ref>. This has led to a multitude of specific protocols that aim to optimize the extraction process for different sediment types <ns0:ref type='bibr' target='#b17'>(Kallmeyer &amp; Smith, 2009;</ns0:ref><ns0:ref type='bibr' /> PeerJ reviewing PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed <ns0:ref type='bibr'>Morono et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b35'>Lever et al., 2015)</ns0:ref>. These methods rely on disrupting the cell membranes by either physical (e.g. bead-beating, freeze-thaw; <ns0:ref type='bibr'>MacGregor et al., 1997;</ns0:ref><ns0:ref type='bibr'>Haile, 2012;</ns0:ref><ns0:ref type='bibr'>Pearman et al., 2016), chemical (e.g. solvents;</ns0:ref><ns0:ref type='bibr'>Pitcher, Saunders &amp; Owen, 1989)</ns0:ref> or enzymatic <ns0:ref type='bibr'>(Holben et al., 1988)</ns0:ref> means. More recently, commercial DNA extraction kits have been used as an alternative to manual extraction protocols <ns0:ref type='bibr' target='#b28'>(Lear et al., 2018)</ns0:ref>. There are drawbacks to commercial kits in that the protocols are often inflexible and the reagents are proprietary, but they streamline the oftenlaborious task of manual extracts and tend to avoid the use of organic solvents <ns0:ref type='bibr' target='#b35'>(Lever et al., 2015)</ns0:ref>.</ns0:p><ns0:p>Previous research has shown that the quantity and quality of the extracted DNA can vary between methods <ns0:ref type='bibr' target='#b25'>(Knauth, Schmidt &amp; Tippk&#246;tter, 2013;</ns0:ref><ns0:ref type='bibr' target='#b34'>Lekang, Thompson &amp; Troedsson, 2015;</ns0:ref><ns0:ref type='bibr'>Hermans, Buckley &amp; Lear, 2018;</ns0:ref><ns0:ref type='bibr' target='#b3'>Armbrecht et al., 2020)</ns0:ref>. Extraction methods have also been shown to affect detected bacterial composition with various phyla being either over or under represented <ns0:ref type='bibr'>(Luna, Dell'Anno &amp; Danovaro, 2006;</ns0:ref><ns0:ref type='bibr'>Carrigg et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b15'>Holmsgaard et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b34'>Lekang, Thompson &amp; Troedsson, 2015;</ns0:ref><ns0:ref type='bibr'>Hermans, Buckley &amp; Lear, 2018)</ns0:ref>. This has important implications for molecular-based biomonitoring, as results need to be comparable spatially and temporally, and should be repeatable and provide a true representation of the community in a sample. The majority of benthic marine studies that have targeted both prokaryotic and eukaryotic organisms have typically used kits that necessitate &gt;2 g of sediment for DNA extraction <ns0:ref type='bibr' target='#b28'>(Lear et al., 2018)</ns0:ref>. If the same results can be obtained with smaller volumes of starting material, then this will allow the extraction process to be automated (e.g. using a sample prep robot), which would standardize and greatly expedite the process and make it more cost-effective for routine monitoring.</ns0:p><ns0:p>The sampling described in this study was part of a long term (8 years) research project, which aimed to validate a metabarcoding-based protocol for assessing and monitoring the benthic impacts of salmon farming in New Zealand <ns0:ref type='bibr' target='#b5'>(Pochon et al., 2020)</ns0:ref>. While interesting ecological inferences can be gained from studying impact gradients around fish farms those results will be presented elsewhere. The current study focusses on the first step in the workflow optimization process by investigating the effect of DNA extraction kits and sediment quantities on prokaryotic and eukaryotic assemblages along an organic enrichment gradient adjacent to fish farms. The null hypothesis of the experiment was that distinct extraction kits and sediment quantities would not affect the quality or quantity of extracted DNA, detected prokaryotic and eukaryotic assemblages, and therefore -metabarcoding-based benthic health assessment.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head><ns0:p>Sediment eDNA samples were collected in November 2015 as part of a regular compliance monitoring program for New Zealand King Salmon (NZKS) at a Chinook (Oncorhynchus tshawytscha) salmon farm located in Otanerau Bay (41&#61616;10'11''S, 174&#61616;19'16''E), Marlborough Sounds, New Zealand (Figure <ns0:ref type='figure' target='#fig_4'>1</ns0:ref>). The farm location is characterized as a 'low flow' area, having a mean current velocity of approximately 6 cm s &#8722;1 and a water depth of 34-35 m. Sampling started directly alongside the pen and radiated outwards along an enrichment gradient with samples collected at 50 and 150 m, and at a control site located 625 m from the farm. Bulk sediment at each side was collected using a Van-Veen grab with sediment biogeochemical properties at each station in Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>. Three distinct surface-sediment samples (c. 40 g per grab)</ns0:p><ns0:p>were collected from the top 1-2 cm of each grab surface using a sterile spatula and placed in DNA/RNAse-free collection tubes (50 mL). Sediment samples were immediately placed on ice and transported to the Cawthron laboratory where they were stored at -80&#61616;C until DNA extraction.</ns0:p><ns0:p>Each step of the following molecular analyses was conducted in separate sterile laboratories dedicated to these steps, with sequential workflow to ensure no cross-contamination. Rooms dedicated to DNA extraction, amplification set-up and template addition were equipped with laminar flow cabinets with HEPA filtration and room-wide ultra-violet sterilization which was switched on for &gt;15 min before and after each use. Aerosols barrier tips (Axygen, CA, USA) were used throughout.</ns0:p><ns0:p>Each of the 12 sediment samples were homogenized using sterile stainless steel grinding beads in the 1600 MiniG &#174; tissue homogenizer (1,500 RPM, 2 min). From these homogenized samples five sub-samples representing three distinct sediment volumes (0.25 g, 2 g, and 5 g) were <ns0:ref type='table' target='#tab_1'>PeerJ reviewing PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:ref> Manuscript to be reviewed extracted using four DNA extraction kits (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). Amongst the many kits available on market, we selected these four specific kits for the following reasons. Qiagen Power Soil kits (Q.PS and Q.PS.Pro) integrates a patented Inhibition Removal Technology &#174; that works particularly well for eDNA isolation from challenging samples such as enriched soils. This likely explains why the majority of soil eDNA studies use Qiagen kits <ns0:ref type='bibr' target='#b28'>(Lear et al., 2018)</ns0:ref> and justifies our emphasis on Qiagen Power Soil kits in this study. Second, the Qiagen RNeasy PowerSoil Total RNA/DNA extraction/elution kit (QIA2) is the most commonly used kit in previous fish farm studies <ns0:ref type='bibr'>(Pawlowski et al., 2014;</ns0:ref><ns0:ref type='bibr'>Dowle et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b33'>Lejzerowicz et al., 2015;</ns0:ref><ns0:ref type='bibr'>Pochon et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b23'>Keeley, Wood &amp; Pochon, 2018)</ns0:ref>, but this DNA/RNA co-extraction protocol is comparatively very time-consuming and involves dangerous chemicals such as phenol-chloroform. Third, to our knowledge there are only two commercial soil kits that allow extraction of up to 10 g of material, the Qiagen PowerMax Soil kit and the Favorgen Soil Midi-prep kit <ns0:ref type='bibr'>(Young et al., 2014)</ns0:ref>. Cost-considerations are essential for routine monitoring, and therefore we chose to test the latter kit, being significantly cheaper than the former kit. DNA was extracted using a QIAcube automated sample prep robot (Qiagen Instruments, Switzerland) for the Qiagen DNeasy PowerSoil Kit (Q.PS) and Qiagen DNeasy PowerSoil Pro Kit (Q.PS.Pro) kits, while extraction was done manually for the remaining kits, according to the manufacturer's instructions. The quality and purity of isolated DNA were measured using a Nanophotometer NP80 (Implen, Munich, Germany). This instrument is equipped with an automatic quality control software that enables the detection of impurities and/or air bubbles within extracted samples.</ns0:p><ns0:p>Polymerase chain reactions (PCR) were performed on all extracted samples (n=60) and targeted two genes. Prokaryotic communities were amplified using a 16S rRNA gene (V3-V4 region) with the primer set 341F: 5'-CCT ACG GGN GGC WGC AG-3' <ns0:ref type='bibr'>(Herlemann et al., 2011)</ns0:ref> and 805R: 5'-GAC TAC HVG GGT ATC TAA TCC-3' <ns0:ref type='bibr' target='#b24'>(Klindworth et al., 2013)</ns0:ref>. Eukaryotic communities were targeted using the primer set Uni18SF: 5'-AGG GCA AKY CTG GTG CCA GC-3' and Uni18SR: 5'-GRC GGT ATC TRA TCG YCT T-3' <ns0:ref type='bibr'>(Zhan et al., 2013)</ns0:ref>, which amplified the 18S rRNA gene (V4 region). Both the prokaryotic and eukaryotic primers had an Illumina overhang adapter present as per the Illumina 16S library preparation manual. Amplifications were undertaken in an Eppendorf Mastercycler (Eppendorf, Hamburg, Germany)</ns0:p><ns0:p>PeerJ reviewing <ns0:ref type='table' target='#tab_1'>PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:ref> Manuscript to be reviewed in a total volume of 50 &#61549;L using MyFi TM PCR Master Mix (Bioline Meridian Bioscience), 2 &#956;L of each primer (10 &#956;M stock) and 2 &#956;L of template eDNA. The PCR cycles for the 16S rRNA gene amplification were as follows: 95 &#61616;C for 5 min followed by 35 cycles of 94 &#61616;C (30 s), 54 &#61616;C (30 s) and 72 &#61616;C (45 s) with a final extension at 72 &#61616;C for 7 min. Amplifications for the 18S rRNA gene were 95 &#61616;C for 5 min followed by 37 cycles of: 94 &#61616;C (30 s), 54 &#61616;C (30 s) and 72 &#61616;C (45 s) with a final extension at 72 &#61616;C for 7 min. Negative PCR controls were included in each PCR run. Amplicon PCR products were purified using AMPure&#174; XP PCR Purification beads (Agencourt&#174;, MA, USA) and quantified using a Qubit&#174; Fluorometer (Life Technologies, Carlsbad, CA, USA). An additional water control was added to test for potential contamination during the following sequencing workflow. All negatives were subsequently sequenced. Products (n=68; 60 samples plus 5 PCR blanks and 3 water blanks) were diluted (3 ng &#956;L -1 ) and sent to Auckland Genomics (University of Auckland) for final library construction. Dual indices were added to the amplicons via a second round of PCR amplification as detailed in the Illumina 16S library preparation manual. Subsequent to the second round of amplification, 5 &#956;L of each sample (including all controls) was pooled and a single clean-up was undertaken. A bioanalyzer was used to check the quality of the library which was then diluted 4 nM and denatured. The library was diluted to a final loading concentration of 7 &#61554;M with a 15% spike of PhiX. Pairedend sequences (2 x 250 bp) were generated on an Illumina MiSeq instrument. Raw sequences were deposited in the NCBI short read archive under accession: PRJNA657189 Reads were demultiplexed using the MiSeq Reporter (v2) based on the Nextera TM dual-indexing.</ns0:p><ns0:p>Primers were removed from the sequences using cutadapt <ns0:ref type='bibr'>(version 1.8;</ns0:ref><ns0:ref type='bibr'>(Martin, 2011)</ns0:ref>, allowing a maximum error rate of 0.1. Sample reads were processed using the DADA2 program <ns0:ref type='bibr'>(Callahan et al., 2016)</ns0:ref> implemented in QIIME2 version 2018.11 <ns0:ref type='bibr'>(Bolyen et al., 2019</ns0:ref>) using default parameters. The reads were truncated at 228 and 216 bp for the forward and reverse 16S rRNA gene sequences, and 225 and 216 bp for the 18S rRNA gene sequences, and the maxEE value (expected error rate) was set to 20. The sequences were merged into Amplicon Sequence Variants (ASVs) with a minimum overlap of 10 bp and no mismatches. Chimeras were detected and removed using the removeBimeraDenovo script in DADA2. Taxonomic assignments were undertaken in DADA2 based on the rdp <ns0:ref type='bibr'>(Wang et al., 2007)</ns0:ref> algorithm against the SILVA 132 database <ns0:ref type='bibr'>(Pruesse et al., 2007)</ns0:ref>. In the prokaryotic dataset, ASVs assigned to eukaryotes, chloroplasts and mitochondria were removed prior to further analysis. Code for the analysis can be found at: https://github.com/olar785/Optimizing-DNA-extraction-methods-for-assessingorganic-enrichment-in-marine-farm-sediments/blob/master/Q2_DADA2_pipeline.sh and the taxonomy for each ASV sequence can be found in Table <ns0:ref type='table'>S2</ns0:ref>.</ns0:p><ns0:p>The output from DADA2 was imported into phyloseq (McMurdie &amp; Holmes, 2013) within R software <ns0:ref type='bibr'>(R Core Team, 2020)</ns0:ref>. To remove possible contamination from the data we used the maximum sequence count for each ASV present in the controls as a basis for subtraction <ns0:ref type='bibr' target='#b7'>(Bell et al., 2019)</ns0:ref>. Thus, any ASV in the dataset with fewer reads than found in the controls was assumed to be contamination and removed from analysis. ASVs that had read numbers higher than the threshold had their read counts reduced by the threshold number to take into account the contamination. To allow comparison between samples, rarefaction plots were constructed with ggrare <ns0:ref type='bibr' target='#b18'>(Kandlikar et al., 2018)</ns0:ref> and ggplot2 (Wickham, 2016) and subsequently reads were subsampled to 4,400 per sample for prokaryotes and 10,000 per sample for eukaryotes (Figure <ns0:ref type='figure' target='#fig_4'>S1</ns0:ref>). Richness values were tested for normality (shapiro.test) and homogeneity of variance (bartlett.test) and subsequently a square root transformation was undertaken to meet these assumptions. Differences in richness (square root transformed) were assessed using two-way analysis of variance (ANOVA), with kit (5 levels) and distance (4 levels) as factors. Pairwise post-hoc tests were undertaken using the Tukey Honestly Significant Difference (HSD) test.</ns0:p><ns0:p>Shared ASVs were assessed in phyloseq and plotted with VennDiagram (Chen &amp; Boutros, 2011).</ns0:p><ns0:p>Multivariate analysis was undertaken on both datasets using the rarefied samples. Non-metric multidimensional scaling (nMDS) was undertaken to visualize the 2D representation of the community structure. Statistical differences were tested using permutational multivariate analysis of variance (PERMANOVA, <ns0:ref type='bibr' target='#b2'>(Anderson, Gorley &amp; Clarke, 2008</ns0:ref>)) based on Bray-Curtis dissimilarities of the square root transformed data using PRIMER <ns0:ref type='bibr' target='#b2'>(Anderson, Gorley &amp; Clarke, 2008)</ns0:ref>. The experimental design consisted of two crossed factors: Kit and Distance; five levels for factor Kit (Q.PS, Q.PS.Pro, QIA2, FAV2 and FAV5) and 4 levels for Distance (Pen, 50 m, 150 m and Control). To assess the taxonomic composition of the communities, ASVs were merged at class level. To assess the effect of kit on benthic health assessments the denovo indices, the bacterial Metabarcoding Biotic Index (b-MBI) and the eukaryotic Metabarcoding Biotic Index (e-MBI) were calculated using pre-defined molecular Eco-Groups at the ASV level following <ns0:ref type='bibr' target='#b23'>Keeley, Wood and Pochon (2018)</ns0:ref>. Figures were constructed in R using the package ggplot2 (Wickham, 2016) and ampvis2 <ns0:ref type='bibr' target='#b1'>(Andersen et al., 2018)</ns0:ref>.</ns0:p><ns0:p>Code for the statistical analysis can be found at: https://github.com/jkpearmanbioinf/FishFarmAnalysis/blob/master/KitComparison.notebook.Rm d</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>DNA quality was generally highest for samples extracted with the Q.PS kit (Table <ns0:ref type='table'>S3</ns0:ref>). The Q.PS.Pro kit yielded similar albeit more scattered absorbance values, and a lower overall DNA concentration compared to the Q.PS kit. Both the QIA2 and the FAV2 kits had low A260/A230 ratios indicating contamination by compounds that absorb in the A230 range (e.g. Ethylenediaminetetraacetic acid (EDTA), carbohydrates). The FAV5 and QIA2 kits yielded the highest overall DNA concentration estimates, although they failed most of the automatic quality controls (Table <ns0:ref type='table'>S3</ns0:ref>). Lower DNA concentrations after PCR cleanup were noted for the FAV2, FAV5 and QIA2 kits in the eukaryotic samples compared with the Q.PS and Q.PS.Pro kits (Table <ns0:ref type='table'>S3</ns0:ref>).</ns0:p><ns0:p>High-Throughput Sequencing resulted in a total of 3,337,510 prokaryotic sequences (915,508 after filtering; Table <ns0:ref type='table'>S4</ns0:ref>) and 6,318,916 eukaryotic sequences (4,382,737 after filtering; Table <ns0:ref type='table'>S4</ns0:ref>).</ns0:p><ns0:p>Replicates for FAV2 at 150 m for the prokaryotic dataset were removed from the dataset as they did not meet the rarefaction thresholds. Following bioinformatics analyses using DADA2, a total of 14,427 and 11,177 ASVs were identified for prokaryotic and eukaryotic communities, respectively.</ns0:p><ns0:p>There was a statistical difference in the observed richness amongst kits for the eukaryotic (F = 7.442, p &lt; 0.001) dataset, while there was a significant interaction in the prokaryotic dataset (F= 7.575; p &lt; 0.001). Pairwise tests showed that there was has a higher diversity retrieved in the Q.PS and Q.PS.Pro kits in the pen compared with other kits in the prokaryotic dataset (Figure Manuscript to be reviewed 2A) with the majority of the other comparisons were non-significant. The FAV2 kit had a significantly lower diversity than the other kits in the eukaryotic dataset (Figure <ns0:ref type='figure' target='#fig_5'>2B</ns0:ref>). Similar trends were observed when investigating the Shannon diversity for the prokaryotes (F = 13.87, p &lt; 0.001, Figure <ns0:ref type='figure' target='#fig_5'>S2</ns0:ref>). There was a significant trend for the eukaryotes (F = 2.723, p = 0.039, Figure <ns0:ref type='figure' target='#fig_5'>S2</ns0:ref>) although no pairwise comparisons were significant.</ns0:p><ns0:p>Only a small proportion of the ASVs were shared amongst all kits (prokaryotes: 3.5% eukaryotes: 3.2%), however these shared ASVs accounted for 59.9 % of prokaryotic and 67.1% of eukaryotic reads (Figure <ns0:ref type='figure' target='#fig_6'>3</ns0:ref>). This indicates that the majority of the ASVs that are not shared are of low abundance. In the prokaryotic dataset, the Q.PS.Pro kit had the greatest proportion of unique (not observed in any other kit) ASVs accounting for 66.5% of the total prokaryotic diversity retrieved by the kit (Figure <ns0:ref type='figure' target='#fig_6'>3A</ns0:ref>). The lowest proportion of unique ASVs was observed in the FAV5 (43.9%) and FAV2 (44.3%) kits for the prokaryotic dataset. For the eukaryotic dataset, all kits had a similar number of unique ASVs, ranging from 51% in the Q.PS.Pro kit to 56.2% in the QIA2 kit (Figure <ns0:ref type='figure' target='#fig_6'>3B</ns0:ref>).</ns0:p><ns0:p>In general, all kits detected the same dominant classes of both prokaryotes and eukaryotes.</ns0:p><ns0:p>However, the relative abundance of these groups differed when all distances from the farm were combined (Figure <ns0:ref type='figure' target='#fig_7'>4</ns0:ref>, Figure <ns0:ref type='figure' target='#fig_6'>S3</ns0:ref>). The dominant prokaryotic class Bacteroidia yielded similar percentages of read abundances across all kits (Figure <ns0:ref type='figure' target='#fig_7'>4A</ns0:ref>). Nonetheless, there were differences at the family level, with Flavobacteriaceae having lower relative abundances in the Q.PS (12.2%) and Q.PS.Pro (7.4%) kits compared with the other kits (FAV2: 24.7%; FAV5:18.7% and QIA2: 22.1%) while Bacteroidetes BD2-2 had higher relative abundances in these kits (Q.PS: 9% and Q.PS.Pro: 8.3%) than the others (FAV2: 3.7%; FAV5:3.4% and QIA2: 3.7%). Campylobacteria was the second most abundant class across kits except for the Q.PS and Q.PS.Pro kits (Figure <ns0:ref type='figure' target='#fig_7'>4A</ns0:ref>). Fusobacteria and Deltaproteobacteria had higher relative abundances in the Q.PS and Q.PS.Pro kits compared with the other three kits. Differences in the relative abundance of reads in the eukaryotic dataset was more variable at the class level between kits (Figure <ns0:ref type='figure' target='#fig_7'>4B</ns0:ref>). The apicomplexan class Conoidasida had a higher relative read abundance in the FAV2 and FAV5 kits and was especially low in the Q.PS kit. In contrast, Chromadorea (Nematoda), was lower in these kits (FAV2 and FAV5) compared with the other kits especially Q.PS and Q.PS.Pro (Figure Manuscript to be reviewed 4B). While ASVs belong to fish were not a substantial proportion of the dataset they were detected as would be expected with higher read numbers underneath the pens. Furthermore, there were differences in the number of ASVs found per class across kits in both the 16S rRNA and 18S rRNA gene datasets (Table <ns0:ref type='table'>S5 and S6</ns0:ref>, respectively). Similar patterns were observed for the community structure (Figure <ns0:ref type='figure' target='#fig_8'>5</ns0:ref>) amongst kits with distance from the farm (i.e. decrease in organic enrichment levels) being a stronger determinant than kit. Strong and consistent clustering of replicate samples and kits were observed amongst collection sites, from highly enriched sediments adjacent to fish farm pens through to the unenriched control sites, particularly in the prokaryotic dataset (Figure <ns0:ref type='figure' target='#fig_8'>5A</ns0:ref>). Although similar patterns were observed for eukaryotes, the clusters appeared to be more diffused compared to prokaryotes (Figure <ns0:ref type='figure' target='#fig_8'>5B</ns0:ref>). Both the prokaryote (F=1.71; p &lt; 0.001) and eukaryote (F=1.36; p &lt; 0.001) PERMANOVA results confirmed that there was significant interaction between kits and distance (Table <ns0:ref type='table'>S7</ns0:ref>). Pairwise comparisons indicated that at each distance there was no significant difference amongst kits (with 3 exceptions; see Table <ns0:ref type='table'>S7</ns0:ref>). For factor kit pairwise comparisons indicated that the Q.PS and Q.PS.Pro kits were better at differentiating the environmental gradient with pairwise comparisons significantly different amongst distances for these two kits (Table <ns0:ref type='table'>S7</ns0:ref>).</ns0:p><ns0:p>The bacterial Metabarcoding Biotic Index (b-MBI) and eukaryotic Metabarcoding Biotic Index (e-MBI) were calculated and multivariate analysis on the weighted abundances of the five eco-groups was undertaken. Multivariate analysis indicated strong and consistent clustering of replicates and samples from different kits for each distance along the gradient especially in for the b-MBI (Figure <ns0:ref type='figure' target='#fig_9'>6</ns0:ref>). PERMANOVA results indicated that there were significant differences for in the b-MBI (F= 13.22; p &lt;0.001) and e-MBI (F= 4.54; p = 0.002) with kit. However, pairwise comparisons showed no significant differences. For distance there were significant differences in both the b-MBI (F= 421.08; p &lt;0.001) and e-MBI (F= 64.33; p &lt;0.001) with all distances being significantly different.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>For molecular methods to be used reliably in monitoring potential degradation of benthic habitats, samples should be representative of the targeted community and the DNA sufficiently pure to ensure that inhibitors do not affect the analysis <ns0:ref type='bibr'>(McKee, Spear &amp; Pierson, 2015)</ns0:ref>. The use of DNA extraction kits is highly desirable as it standardizes this process and, in some instances, allows the automatization of extraction using robotics. The aim of the study was to explore how the application of four different extraction kits (all commonly used in soil/sediment studies) impacted the composition and structure of prokaryotic and eukaryotic communities in marine surface sediments derived via metabarcoding. In addition, with each kit allowing different amounts of starting material, three different weights of sediment were used (two different weights were tested for the Favorgen kit).</ns0:p><ns0:p>We used benthic sediment samples along an enrichment gradient associated to salmon farms as a study case, and investigated the quantity and quality of DNA extracted using five different extraction kits. In general, the three kits using higher volumes of sediment (QIA2, FAV2 and FAV5) retrieved higher concentrations of eDNA. However, this higher quantity of DNA was often offset with a lower overall quality, with the Q.PS and Q.PS.Pro kits having the largest number of samples that passed the automatic quality control on the nanophotometer. The QIA2 and FAV2 kits had comparatively low A260/A230, indicating potential contaminants such as humic compounds which absorb in the A230 spectrum <ns0:ref type='bibr'>(Yeates et al., 1998)</ns0:ref>. The presence of humic acids in sediment samples is a known concern as it can complex with DNA <ns0:ref type='bibr' target='#b26'>(Lakay, Botha &amp; Prior, 2007)</ns0:ref> and interfere with subsequent PCR amplification. DNA from all samples was successfully amplified, although PCRs were noted to be less efficient for the kits using higher volumes, indicating that the potential contaminants did not inhibit PCR reactions completely but further studies would be required to assess what was causing the low A260/230 ratios.</ns0:p><ns0:p>We expected that the higher weights of sediment would result in a higher diversity of ASVs. However, the kits using higher starting weights of sediment (QIA2, FAV2 and FAV5) in general revealed lower prokaryotic diversity than the Q.PS and Q.PS.Pro kits, although the significance of these results varied and, except for FAV2, were not observed for the eukaryotes. The lack of correlation between starting material and diversity has previously been reported by <ns0:ref type='bibr'>Carrigg et al., (2007)</ns0:ref>. The current study assessed two weights using the same kit for the Favorgen kit only, and found no significant difference in the richness between weights. However, further studies using a variety of kits and more weights would be required to confirm this trend. Inefficiencies in the extraction kits using large sediment weights could explain this observation with the possibility PeerJ reviewing PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed that humic acids and other contaminants are binding to the silica filters and reducing the concentration of DNA bound to the filters <ns0:ref type='bibr' target='#b37'>(Lloyd, Macgregor &amp; Teske, 2010)</ns0:ref>. If the latter hypothesis is true, then the obvious limitation is that research practitioners aiming to appropriately capture micro-patchiness and/or spatial heterogeneity of biological assemblages (i.e. beta diversity) in marine sediments, will have to adapt their sampling size accordingly. For this reason, previous fish farm studies have advocated for the collection of at least 3 to 5 independent replicate samples per station <ns0:ref type='bibr'>(Pawlowski et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b33'>Lejzerowicz et al., 2015;</ns0:ref><ns0:ref type='bibr'>Pochon et al., 2015)</ns0:ref>. In this respect, the detection of higher diversity in the Q.PS and Q.PS.Pro kits has a further advantage as the small volumes used in the Q.PS and Q.PS.Pro kits mean samples can be processed using automated equipment (e.g. QIAcube, Qiagen). The automated methodologies limit the human involvement (i.e., variability) in the procedure and are thus beneficial for monitoring purposes where replicability is vital.</ns0:p><ns0:p>Only a small percentage of ASVs were shared between all kits in both the prokaryotic and eukaryotic datasets. However, these shared ASVs accounted for a substantial (i.e. &gt;60%) portion of the total number of reads. This suggests that all kits are detecting the core communities and that the main differences in detection are in rare and low abundance ASVs, as has been shown in previous environmental metabarcoding studies <ns0:ref type='bibr'>(Pedros-Alio, 2006;</ns0:ref><ns0:ref type='bibr'>Lynch &amp; Neufeld, 2015)</ns0:ref>. It should be noted that while PCR and sequencing controls were undertaken to detect potential contamination in those steps, no extraction controls were used in this experiment. Therefore, we cannot exclude the possibility that a small proportion of the shared ASVs recovered here are due to residual contamination from kits or equipment, and extraction controls should be sequenced in future studies to evaluate this possibility. The higher number of unique ASVs in the Q.PS and Q.PS.Pro kits could suggest that these kits are able to retrieve a larger number of rare ASVs.</ns0:p><ns0:p>However, this may also, in part, be due to stochastic differences in eDNA distribution within sediments rather than extraction differences. The rare ASVs could possibly be found with all kits if increased sequencing depth or further replication (either extraction or PCR replicates) were undertaken. Previous research has shown that increasing replication can give a more reliable estimation of diversity <ns0:ref type='bibr' target='#b27'>(Lanz&#233;n et al., 2017)</ns0:ref>. Kits that require fewer replicates to retrieve a similar diversity are likely to be more cost efficient and thus more suitable for high throughput monitoring applications. These data indicate that the Q.PS and Q.PS.Pro kits provide the best estimation of prokaryotic and eukaryotic community diversity.</ns0:p><ns0:p>Multivariate analysis indicated that while there was a significant interaction between kit and distance from the pens, all the kits showed a similar pattern with different communities along the transect. However pairwise comparisons indicated that the Q.PS and Q.PS.Pro kits had more significant differences amongst distances. Despite a similar trend amongst the kits, there were distinct differences in the relative abundance of taxa. This suggests that there are likely to be taxon-specific variations in cell lysis between the kits, especially in the eukaryotic dataset. This finding is in agreement with other studies that have found a similar trend <ns0:ref type='bibr'>(Carrigg et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b34'>Lekang, Thompson &amp; Troedsson, 2015;</ns0:ref><ns0:ref type='bibr'>Ram&#237;rez, Graham &amp; D'Hondt, 2018)</ns0:ref>. This could be further tested by using positive extraction controls such as a known mock prokaryotic community, allowing for the assessment of lysis efficiencies amongst kits <ns0:ref type='bibr'>(Hermans, Buckley &amp; Lear, 2018)</ns0:ref>. In terms of marine monitoring of prokaryotes, the differential lysis of particular groups could affect the classification of samples if taxonomic approaches such as the microgAMBI or Indicator Values (IndVal) are to be used <ns0:ref type='bibr' target='#b6'>(Aylagas et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b11'>Borja, 2018)</ns0:ref>. For example, in this dataset Flavobacteriaceae have higher relative abundances in the QIA2, FAV2 and FAV5 kits. This family is classified as tolerant to pollution in the microgAMBI and substantial differences in the relative abundances between kits may impact the conclusions from taxonomy-based approaches. Differences in taxonomy could also further impact conclusions that are based on inferring function based on taxonomic composition using molecular approaches such as Paprica <ns0:ref type='bibr' target='#b12'>(Bowman &amp; Ducklow, 2015;</ns0:ref><ns0:ref type='bibr' target='#b28'>Laroche et al., 2018)</ns0:ref>. For the eukaryotic dataset the DNA sample will combine a complex mix of extracellular DNA released by macrofaunal organisms, DNA from living organisms (ranging from microeukaryotes up to meiofauna and larger depending on sample size), and fragments of dead organisms. Interestingly, Conoidasida, Novel Apicomplexa Class I and Syndinales are parasitic taxa of invertebrate and vertebrate macro-organism. In the case of Conoidasida and Syndiniales these taxa were more abundant in the kits using larger weights of sediment. This may be due to the fact that these larger weights of sediment would have increased probabilities to sample specimens or fragments of these larger organisms which occur at lower densities in the sediment. Manuscript to be reviewed More recently, de novo approaches such as b-MBI and e-MBI which work at the ASV level have been developed to assess marine ecosystem health without the restraint of relying on taxonomic classifications <ns0:ref type='bibr' target='#b23'>(Keeley, Wood &amp; Pochon, 2018)</ns0:ref>. Multivariate analysis of these de novo approaches indicated that there was a significant difference in the proportion of ASVs assigned to each eco-group. However, pairwise comparisons showed that there was no significant pairwise comparisons amongst the kits and, in similarity with the community composition, the organic enrichment gradient observed with distance from the farm was a stronger determinant of the resulting assessment of health. This suggests that the type of kit used will have limited impact on the management decisions obtained across defined ecological gradients.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Extracted DNA from commercial kits should be of high quantity and provide a repeatable representation of the community in a sample. In this study, we showed that all investigated kits showed a similar pattern of community change along the disturbance gradient away from the fish farm pens, and that the inferred metabarcoding-based biotic indices were also similar amongst kits. This indicated that the organic enrichment gradient had a higher impact on prokaryotic and eukaryotic composition and biotic indices than any individual extraction kit. Further, only a small percentage of ASVs were shared between all kits in both the prokaryotic and eukaryotic datasets. However, these shared ASVs accounted for a substantial amount of total read number, suggesting that the core communities were captured in the DNA extracted by all kits. Nevertheless, while lower overall quantities of DNA were obtained from the Qiagen Power Soil (Q.PS) and Qiagen Power Soil Pro (Q.PS.Pro) kits, likely due to the lower volume of sediment used, the quality of the extracted DNA was higher. This could lead to less inhibition in the proceeding PCR steps. The Q.PS and Q.PS.Pro also had the highest number of unique ASVs.</ns0:p><ns0:p>In conclusion, we advocate for the use of the Q.PS.Pro kit for sampling prokaryotic and eukaryotic communities in marine benthic environments associated with marine aquaculture.</ns0:p><ns0:p>While the Q.PS and Q.PS.Pro kit had similar results, the recent discontinuation of the former kit rules out the use of this kit in the future. We base this conclusion on the higher DNA quality values and richness achieved with this kit. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure 1</ns0:note><ns0:note type='other'>Figure 2</ns0:note><ns0:note type='other'>Figure 3</ns0:note><ns0:note type='other'>Figure 4</ns0:note><ns0:note type='other'>Figure 5</ns0:note><ns0:note type='other'>Figure 6</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Sampling sites around the Otanerau salmon farm in the Marlborough Sounds, New Zealand</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2: Number of amplicon sequence variants for different DNA extraction kits</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3: Shared amplicon sequence variants amongst kits.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4: Relative abundance of sequence reads for the 10 most abundant classes.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 5 :</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5: Non metric multi-dimensional scaling plots for the prokaryotic and eukaryotic community structures</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 6 :</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6: Non metric multi-dimensional scaling plots of the bacterial and eukaryotic metabarcoding biotic index</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Kits used in this study and sediment weights used with each kit.Kits used in this study and sediment weights used with each kit.Manuscript to be reviewed</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Kit name</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:note></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:08:51916:1:2:NEW 28 Sep 2020)</ns0:note> </ns0:body> "

"We would like to thank the editor and reviewers for their work on this manuscript. Please find below the detailed responses to their comments. Editor comments (Owen Wangensteen) Both reviewers have provided a list of minor revisions that would need to be addressed, point by point. I agree with the suggestion that the manuscript would benefit from adding a paragraph to explain the finding of a big fraction of metabarcoding reads coming from metazoans and their parasites, as pointed out by the reviewers. I think that this discussion could be framed out by explaining that what we call 'environmental DNA' from the sediments is actually a complex mix of trace (extra-organismal) DNA (released by macrofaunal organisms), plus a big component of community (genomic) DNA from living organisms (including bacteria and microeukaryotes, but also meiofaunal and even bigger organisms). I think that these sentences could help readers to understand a lot of things that are going on during the DNA extraction and PCR amplification of sediment DNA. I am looking forward to the revised version of this interesting manuscript. Authors: Thank you for these comments. We have added into the discussion some lines as suggested above to put especially the eukaryotic differences into more context. L458-466 Reviewer 1 (Reindert Nijland) Basic reporting With this manuscript, Pearman et al. are presenting their very interesting results on studying biodiversity in marine sediment, comparing a relevant selection of different DNA isolation kits along a sampling gradient. The manuscript is well written with a clear structure and sufficient context and references provided. The scripts and data analysis procedures are clearly described and/or made available. I was unfortunately unable to access the PRJNA657189 dataset at NCBI SRA, I assume this has not yet been made publicly available?  Authors: Sorry the reviewer could not access the data. The reviewer is correct that the NCBI SRA data had yet to be made publicly available but we had tried to provide a link so the reviewers could link to it. We have now released the data. Experimental design The research question is well defined, relevant & meaningful. The methods followed are mostly described with sufficient detail. Some unclarities are still present. According to the manufacturer, the Favorgen mini kit that is said to have been used is only suitable for up to 0,5g sediment. As the authors have tested this kit with 2g and 5g, I assume they instead have used the midi version of this kit? Please correct throughout the manuscript and supplementary data.  Authors: Thank you for pointing this out. It has been changed to ‘midi’ in the manuscript. The other quibble here is that, although the volume of the used PCR-primers is mentioned, the concentration is not stated. Please add the used primer concentration. Authors: We have now added the concentration of the primers. L219 I have several points regarding the experimental design. These might be hard to correct now, but would be something to take in to consideration in future experiments. If the authors agree with the points below, it would also be beneficial to add these suggestions to the discussion as to guide future research from anybody reading this manuscript.  Authors: We agree with the specific comments made by the reviewer and while unfortunately we were unable to go back and undertake the changes suggested we have addressed the points in the manuscript as suggested. The DNA concentration and quality directly after the isolation was measured with a nanophotometer. For accurate DNA concentration using a fluorometric approach such as a Qubit (used elsewhere in the experiments) would be much more accurate. Although initial differences in DNA concentration are unlikely to have a major effect on the observed diversity after metabarcode amplification, measurement of these metrics should still be performed using the most appropriate method available. It will also provide additional information on the DNA quality and contamination.  Authors: The reason we used the IMPLEN nanophotometer NP80 was because it gave the 260/230 and 260/280 ratios as well as quality control measures indicating potential contamination, which is not achievable with a Qubit. We believe that the nanophotometer that was used in the experiment provide sufficiently accurate results to be able to investigate the differences amongst kits. Another improvement could be the use of a isolation controls. This will provide valuable insights in the DNA contamination present in the sampling equipment and the so called kit-contamination. Especially when comparing different kits this would have been interesting. Especially in experiments using eDNA (with usually very low concentrations of target DNA) this would be very valuable.  Authors: We agree that extraction controls are a good way to assess potential contamination through the pipeline and have added in a brief statement to this effect in the discussion. We also apologise but we missed this out in the bioinformatics step in regards to the treatment of the PCR and water controls. We have now added this in. L424-429 Finally, for the mentioned difference/bias in extraction efficiency for different species (l.418-420), an inclusion of extraction controls using e.g. zymo microbial standards would have provided valuable information about this bias for the DNA isolation kits used.  Authors: we have added into the discussion of the manuscript the possibility of using microbial controls as a further way to assess lysis. L447-449 Validity of the findings The findings described in this manuscript are well described and all statistical methods used described in clear detail. Some processed data is provided in the supplemental materials. A table with the sequences of all identified ASV’s is not given, and would be an interesting addition to the supplemental data. Authors: We have produced a table giving the ASV sequence and the associated taxonomy. Now Table S2. Also, as mentioned above, the raw short read data could not be retrieved from NCBI.  Authors: See above answer. The conclusions are clear and based on the data obtained in this study. I would say that even more emphasis could be placed on the fact could that all kits are able to show similar core communities and as such, also the gradient present is at the research site is resolved regardless of the kit used.  Authors: We have rearranged the conclusions to place more emphasis on the fact that similar patterns were observed and that there was a core community present in all kits that accounted for a large proportion of the reads. It is mentioned that less pure DNA could lead to effects such as PCR inhibition. As the Favorgen kit was clearly producing less pure DNA (line 372-378, Table S2), was such an effect also observed in the PCR results? E.g. in less efficient amplification/lower overall yield/smearing or less pronounced bands after PCR? It would be interesting to report on this if such effects were observed.  Authors: There was definitely some lower efficiency in the amplification of the 18S with these kits. We have added a couple of columns into Table S3 (previously S2) to give the DNA concentration after PCR (and cleanup) and added a sentence to the results and discussion. L298-300 Comments for the Author From the abundance plot (fig 4) for the eukaryotes, it is apparent that the classes listed in the top 10 most abundant reads only represent very small organisms. To me, it seems highly likely these small organisms are present on and inside the sampled sediment and mostly were alive and intact during sampling, just like the bacteria that were identified. As such, I would not consider this an eDNA study, and would describe this as a study of microbiome and bulk benthos. For an eDNA sample, especially taken at a fully stocked fish pen, I would at least expect high numbers of reads for the animalia, more specifically the exact fish species present in the pen. I am curious is fish DNA was found at all in this study.  Authors: We agree that the majority of the reads that were found belonged to small organisms that were most likely living in the sediment sampled. We realise that the term eDNA is still currently evolving its definition but we are using the term as defined by Rees et al 2014 and Taberlet et al 2018 (L89-91) and we believe that it is the most succinct and appropriate term for our study especially as no sieving/sorting of the sample was undertaken which is often the case with bulk studies. We did indeed have fish sequences present in the dataset (20 ASVs), although the taxonomic assignments were not sufficient to identify the family the fish belonged to. While relative read abundances were not high in the data they were considerably higher in the pen compared with elsewhere which as the reviewer suggested would be expected. L345-346 Although I understand this paper is mainly about the difference between the DNA isolation kits, the obtained results related to the Enrichment State index and the findings in a ecological context are also of relevance. It is clear from e.g. fig. 2 that the CTL site has a much higher biodiversity compared to the site directly near the fish pen. I would suggest to either shortly discuss these results in the manuscript, or, alternatively, mention more clearly why these are deliberately not discussed. Authors: We agree with the reviewer that the ecological context of the results is of interest. We are currently in the process of writing a manuscript that focusses more on the ecological data with a temporal aspect included. We believed that there was too much data to publish in a single manuscript and thus separated the data into a more methodological paper (this one) and one that is more ecological in its analysis. To avoid overlap between the two we thus decided to just add a sentence into the manuscript to say that the ecological patterns would be described elsewhere. L153-155 Also, the use of bacteria at class level in my opinion is unlikely to give a real meaningful picture of the ecology, as there is a very high functional diversity of bacterial strains inside the observed classes. Clearly using bacterial diversity is able to show a gradient, and this might be sufficient in the context of the ES index. It would be worthwhile to shortly discuss this issue in the manuscript to clarify the intention of measuring bacterial diversity.  Authors: We totally agree that for ecological analysis the class level would blur meaningful patterns that could be observed and that analysis should be undertaken at a lower taxonomic level. In fact, the b-MBI and e-MBI are now calculated using pre-defined molecular Eco-Groups at the ASV level (Pochon et al. 2020), following the same approach as described in Keeley et al. (2018). In the abstract, line 45-46, “to” should be removed.  Authors: Removed Reviewer 2 (Anonymous) Basic reporting no comment  Experimental design no comment  Validity of the findings no comment  Comments for the Author In this paper, the authors present the comparison of different sediment DNA extraction methods evaluating their efficiency in the context of using sediment DNA metabarcoding to assess the organic enrichment associated with salmon farms activities. The topic is timely and of great importance for future developments of DNA-based biomonitoring. The reported value of 3% of shared ASVs between the kits shows to which extend this aspect is important for any kind of comparative studies.  The paper is well written and, in my opinion, does not contain any technical or analytical flaws. However, there are few important points that should be taken in consideration while preparing the revised version: 1) The title does not really reflect the content of the paper. The authors do not optimize any DNA extraction method but rather compare the existing protocols. Moreover, the wording “marine farm sediments” sounds very unclear. I would suggest something like. “Comparing sediment DNA extraction methods for assessing organic enrichment associated with marine aquaculture” Authors: Changed as suggested. 2) The authors should carefully revise the statements concerning the composition of eukaryotic assemblage obtained from sediment DNA. In fact, the figure 4 shows that among the 10 most abundant classes within eukaryotes, there are several metazoan groups (nematodes, copepods, polychaetes). There are certainly not the micro-eukaryotes and their presence in eDNA dataset can be affected by the volume of extracted sediment. By the way, the apicomplexans that also very abundant in the sediment DNA data are mainly parasites of invertebrates. So, the eukaryotic DNA in marine sediments is dominated by metazoans and their parasites. This aspect might be worth discussing in the paper. Authors: We have removed reference to the assessment of eukaryotic micro-organisms in the manuscript. In the discussion we have reinforced the idea that the samples are made up of a complex mix of DNA from various sources including living and dead cells from organisms across a variety of sizes. We have further discussed the higher number of parasitic in the kits with larger sediment weights could be down to the increased prevalence of invertebrate and vertebrate hosts which occur at lower densities in the sediments. L458-466 3) The impact of the weight of the sediment on DNA diversity is based on comparison of different type and brand of kits. These results need to be confirmed by the analysis of different sediment weights using the same kit or at least the same brand of kit. Those that have done these analyses with Qiagen PowerMax Soil kit will probably disagree with your conclusions. Authors: We have added in that while there were no significant differences between the Favorgen kits, further work using a variety of kits and weights would be required to confirm the trend. L403-405 4) As far as I understood, all kits provided DNA that could be amplified during this study. So, the discussion about the low quality of DNA generated by some kits (FAV 2 and FAV5) and potential inhibition should be moderated as long as there is no strong evidence for such inhibition. Otherwise, the producers of these kits could feel unfairly treated. Authors: Indeed, all samples could be amplified during this study. We have added in a sentence saying that all samples could be amplified and further studies would be required to assess the cause of the low ratios. L391-396 5) The authors omit at least two important papers about DNA extraction from marine sediment. These papers have to be referenced and their results discussed in the paper: • Lekang et al. Aquatic Microbial Ecology 2015 • Hermans et al. Mol Ecol Res 2018 Authors: Now added. The authors could also mention the papers that focus on ancient sediment DNA, which present several extraction protocols that can be used for recent and fossil sediments: • Epp et al. Meth Mol Biol 2019 • Haile, Meth Mol Biol 2012 • Armbrecht et al. Mol Ecol Res 2020 Authors: Added. Minor points: Line 26 – “selection of sediment extraction weight and the DNA extraction method” sounds somehow weird – could be replaced by “selection of sediment DNA extraction method” (which anyway contains sediment weight) Authors: Changed as suggested. Line 45 – “with the to distance” – something is lacking here Authors: We have removed the to which was not needed. Line 359 – benthic health? Authors: Changed to “potential degradation of benthic habitats”. Line 420 – taxon-specific Authors: Changed. Line 435 – the factor kit ? Authors: Changed to amongst the kits. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background: The present study aimed to prepare effective silk derived formulations in combination with plant extract (Aloe vera gel) to speed up the wound healing process in diabetic mice. Methods: Diabetes was induced in albino mice by using alloxan monohydrate. After successful induction of diabetes in mice, excision wounds were created via biopsy puncture (6 mm). Wound healing effect of silk sericin (5 %) and silk fibroin (5 %) individually and in combination with 5 % Aloe vera gel was evaluated by determining the percent wound contraction, healing time and histological analysis.</ns0:p><ns0:p>Results: The results indicated that the best biocompatible silk combination was of 5 % silk fibroin and 5 % Aloe vera gel in which wounds were healed in 13 days with wound contraction: 98.33&#177; 0.80 %. In contrast, the wound of the control group (polyfax) healed in 19 days having 98.5&#177;0.67 % contraction. Histological analysis revealed that the wounds which were treated with silk formulations exhibited an increased growth of blood vessels, collagen fibers, and much reduced inflammation. Conclusion: It can be concluded that a combination of Bombyx mori silk and Aloe vera gel is a natural biomaterial that can be utilized in wound dressings and to prepare more innovative silk based formulations for speedy recovery of chronic wounds.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>INTRODUCTION</ns0:head><ns0:p>Cutaneous wound healing is a programmed, multifaceted and sequential biological process that relies on the interaction between a large number of cells and molecular factors to repair the barrier function of the skin <ns0:ref type='bibr' target='#b56'>(Paquette &amp; Falanga, 2002;</ns0:ref><ns0:ref type='bibr' target='#b50'>Mart&#237;nez-Mora et al., 2012)</ns0:ref>. A 'wound' is the disruption of normal skin physiology, while 'wound healing' is the process the body pursues to restore skin stability <ns0:ref type='bibr' target='#b65'>(Sugihara et al., 2000)</ns0:ref>. Ideal healing of a skin wound requires synchronized incorporation of all molecular and biochemical events of cell proliferation, migration, deposition of extracellular matrix and remodeling <ns0:ref type='bibr' target='#b16'>(Das &amp; Baker, 2016)</ns0:ref>. However, this orderly advancement of the healing process is compromised in chronic, non-healing wounds <ns0:ref type='bibr' target='#b26'>(Falanga, 2005)</ns0:ref>. Chronic wounds normally occur in diabetic patients due to their impaired wound healing process <ns0:ref type='bibr' target='#b61'>(Spampinato et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b27'>Farman et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Diabetes is a prevalent health challenge that impacts people worldwide. It is recognized as a group of varied disorders with the common elements of glucose intolerance, hyperglycemia caused by insulin shortage, reduced efficacy of insulin action, or both <ns0:ref type='bibr'>(Albert &amp; Zimmet, 1998;</ns0:ref><ns0:ref type='bibr' target='#b7'>Atlas, 2015)</ns0:ref>. Non-healing chronic wounds are considered as one of the most serious complications of diabetes. Such complications are associated with an increased risk of bacterial infection, blood vessel and nerve injury, and ultimately amputation of limbs and other organs <ns0:ref type='bibr' target='#b46'>(Masood et al., 2019)</ns0:ref>.</ns0:p><ns0:p>The wound healing process in diabetic patients is profoundly slow as compared to healthy individuals, hence prolonged healing duration increases the risk of wound associated infections Manuscript to be reviewed <ns0:ref type='bibr' target='#b51'>(Menke et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b19'>Dehghani et al., 2020)</ns0:ref>. The current wound healing investigations signify the therapeutic potential of formulations in modulating the wound healing process and reducing suffrage of patients <ns0:ref type='bibr' target='#b54'>(Nithya et al., 2011)</ns0:ref>. Scientists have tried different chemicals and herbal formulations to speed up wound healing in diabetic patients but there were certain limitations and the results were not much persuasive.</ns0:p><ns0:p>There is a long, rich history of utilization of natural materials in the biomedical industry. Amongst many naturally occurring materials, silk obtained from silkworms is considered as an exceptional biomaterial which has a wide range of medical applications <ns0:ref type='bibr'>(Jastrzebska et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b21'>Tahir et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b21'>Elahi et al., 2020)</ns0:ref>. It is classified as a 'model biomaterial' due to its remarkable mechanical strength <ns0:ref type='bibr' target='#b72'>(Vollrath &amp; Porter, 2006;</ns0:ref><ns0:ref type='bibr' target='#b68'>Tahir et al., 2019)</ns0:ref>, impressive biocompatibility with skin tissues, negligible immunogenicity <ns0:ref type='bibr' target='#b47'>(MacIntosh et al., 2008)</ns0:ref> and minimal bacterial adhesion <ns0:ref type='bibr' target='#b10'>(Cassinelli et al., 2006)</ns0:ref>. Mounting evidence of preclinical research demonstrates excellent wound healing properties of silk proteins since the 1990s <ns0:ref type='bibr' target='#b64'>(Shailendra &amp; Das, 2019)</ns0:ref>. Silk (particularly silkworm silk) started its journey in the biomedical industry when it was first used to suture skin wounds <ns0:ref type='bibr' target='#b2'>(Altman et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Silk is the strongest and most flexible naturally occurring fiber. It is smooth, shiny and soft in texture unlike most of the synthetic fibers <ns0:ref type='bibr' target='#b2'>(Altman et al., 2003)</ns0:ref>. There are two proteins fibroin (80%) and sericin (20%) present in the silk thread which is secreted by Bombyx mori's silk glands <ns0:ref type='bibr'>(Pornanong, 2012;</ns0:ref><ns0:ref type='bibr' target='#b23'>El-Fakharany., 2020)</ns0:ref>. The middle and posterior silk glands of B mori larvae produce a fibroin layer and three layers of sericin respectively <ns0:ref type='bibr'>(Zhou et al., 2000)</ns0:ref>. Sericin and fibroin play an active role in accelerating wound healing <ns0:ref type='bibr' target='#b41'>(Li et al., 2020)</ns0:ref>. The wound healing potential of sericin in cell culture and animal models is well reported <ns0:ref type='bibr' target='#b4'>(Aramwit &amp; Sangcakul, 2007)</ns0:ref>. Successful trials with fibroin based biomaterials, for example sponges <ns0:ref type='bibr'>(Roh et</ns0:ref> PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed <ns0:ref type='bibr'>al., 2006)</ns0:ref>, hydrogels <ns0:ref type='bibr' target='#b29'>(Fini et al., 2005)</ns0:ref>, films <ns0:ref type='bibr' target='#b65'>(Sugihara et al., 2000)</ns0:ref> and nanofibers mats <ns0:ref type='bibr' target='#b62'>(Schneider et al., 2009)</ns0:ref> have been conducted with impressive results. It has also been reported that silk based wound dressings stimulate cell proliferation and recruitment of cells such as keratinocytes in the wound bed to accelerate the wound healing process <ns0:ref type='bibr' target='#b13'>(Chouhan &amp; Mandal, 2020)</ns0:ref>. Scientists have prepared, silk fibroin/keratin-based biofilms to control the release rate of elastase enzyme in the chronic wound milieu <ns0:ref type='bibr' target='#b58'>(Roh et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b70'>Vasconcelos et al., 2010)</ns0:ref>.</ns0:p><ns0:p>&#61623; As silk fibroin and sericin exhibit unique biological and physical properties, they are extensively explored by researchers in the biomedical industry for their utilization in wound healing materials. The current study attempts to evaluate the silk-based formulations in treating inducedskin wounds in diabetic mice model. The objectives of this study were to extract pure silk fibroin and silk sericin from silkworm cocoons and to prepare silk-based formulations in combination with plant extract i.e., Aloe vera gel. Furthermore, in vivo wound healing potential of silk based formulations in artificially wounded diabetic mice model was evaluated.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>MATERIALS AND METHODS</ns0:head></ns0:div> <ns0:div><ns0:head>Ethical statement</ns0:head><ns0:p>All animal trial techniques were directed as per local and worldwide controls. The nearby direction is the Wet op de dierproeven (Article 9) of Dutch Law (International) and</ns0:p><ns0:p>The Institutional Bioethics Committee at Government College University Lahore, Pakistan (No. GCU/IIB/21 dated: 08-01-2019).</ns0:p></ns0:div> <ns0:div><ns0:head>Rearing of mice in animal house</ns0:head><ns0:p>The Swiss albino mice weighing around 29-30 g and 8 weeks old were obtained from the the Animal House, Department of Zoology, Government College University Lahore, Pakistan and used as experimental models. They were reared in standard plastic cages of length 10 inches, height 7 inches and width 5 inches in the same Animal House of Zoology Department, Government College University Lahore. Six mice were reared per cage under standard laboratory conditions (temperature 19-21 &#176;C, humidity 45-65 % and 12 h light-dark cycle). They were fed standard animal diet and tap water in the cage. Mice were acclimatized for one week before the experimental procedures. The weight of each mouse was measured and noted throughout the experiment.</ns0:p></ns0:div> <ns0:div><ns0:head>Diabetes induction</ns0:head><ns0:p>A single dose of alloxan monohydrate (CAT A7413-10G, Signa-Alrich, Germany) was injected intraperitoneally to induce diabetes.. The dosage of alloxan monohydrate was freshly prepared in saline solution at a dosage of 200 mg/kg body weight <ns0:ref type='bibr' target='#b0'>(Ahmadi et al., 2012)</ns0:ref>. All animals were fed with glucose solution (10 %) after receiving an injection of alloxan monohydrate to prevent them from sudden hypoglycemic state <ns0:ref type='bibr' target='#b69'>(Vanitha et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b9'>Bouzghaya et al., 2020)</ns0:ref>. After 24 hrs of induction of diabetes, blood samples were collected by pricking the tail tip of the mice. Manuscript to be reviewed meter and test strips). Animals with a blood glucose level of &#8805;250 mg/dl were considered diabetic and were selected for further experimentation <ns0:ref type='bibr'>(Chen et al., 2015)</ns0:ref>. Mice were given free access to food and water during the study and they were kept in standard plastic cages at room temperature in the animal house of the Zoology department. Blood glucose levels of all albino mice were recorded before starting of the experiment. Only those mice who have normal blood glucose levels were used for further study and those having high blood glucose levels were excluded from the study <ns0:ref type='bibr' target='#b17'>(Dra et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Creation of skin excision wound in mice</ns0:head><ns0:p>Mice were randomly divided into six groups with each group consisting of 6 male mice. Animals were anesthetized intraperitoneally with ketamine (100 mg/kg) and Xylazine (10 mg/kg) in saline before wound induction. The dorsal fur of mice was shaved completely by using an electrical hand shaver. Two full thickness excision wounds were created on the dorsum of each mouse by using a 6 mm biopsy punch device. These surgical interventions were carried out under sterile conditions. The total surgical time was 15-20 minutes for each mouse. All animals received their respective treatments once a day from post wounding day till complete healing.</ns0:p><ns0:p>Body weight, skin color and skin irritation were observed and recorded daily.</ns0:p></ns0:div> <ns0:div><ns0:head>Extraction of sericin from cocoons</ns0:head><ns0:p>Silk cocoons of B. mori (silkworm) were kindly supplied by the Sericulture section of Forestry department, Punjab, Pakistan. These cocoons were sliced into small pieces. For sericin extraction, 5 g of silk cocoon pieces were immersed in 100 ml of distilled water and autoclaved at 121 &#176;C and 15 lb per square inch pressure for 1hr. After 1hr the sericin solution was allowed to cool at room temperature and then filtered through a filter paper. The filtration process removed impurities from the sericin solution. The filtered sericin solution was subjected to PeerJ reviewing <ns0:ref type='table' target='#tab_3'>PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:ref> Manuscript to be reviewed lyophilizer (freeze drying) at -82 &#176;C for 72 hrs to obtain sericin powder <ns0:ref type='bibr' target='#b44'>(Mart&#237;nez et al., 2017)</ns0:ref>.</ns0:p><ns0:p>Extraction procedures of sericin and fibroin were carried out separately by utilizing fresh silk cocoons each time.</ns0:p></ns0:div> <ns0:div><ns0:head>Extraction of fibroin</ns0:head><ns0:p>Degumming: Silk cocoons synthesized by B. mori silkworms were soaked in warm water to loosen the threads. Silk threads from several cocoons were then unwound to obtain silk fibers.</ns0:p><ns0:p>Raw silk fibers were then degummed in 0.5 % NaHCO 3 at 100 &#176;C for 1 hr, rinsed thrice with distilled water and then dried overnight in oven (60-80 &#176;C) <ns0:ref type='bibr' target='#b36'>(Ju et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b21'>Tahir et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Dissolution of silk fibers: 80mg of degummed silk was dissolved for 6-8 hrs at 80&#176;C with constant stirring in a solvent system of calcium chloride: ethanol: distilled water in a molar ratio of 1:2:8 <ns0:ref type='bibr' target='#b73'>(Wang &amp; Zhang, 2013;</ns0:ref><ns0:ref type='bibr' target='#b74'>Yi et al., 2018)</ns0:ref>. Urea (8 M) was also added to calcium chloride solvent to achieve a 100 % dissolution of silk fibers <ns0:ref type='bibr' target='#b52'>(Min &amp; Lee, 2004)</ns0:ref>.</ns0:p><ns0:p>Dialysis: After dissolution, the remnants of chemicals were removed through dialysis with a cellulose dialysis membrane in distilled water for 3 days. After dialysis the silk fibroin solution was sonicated at 20 kHz: 400 W for 1 hr and then lyophilized to obtain silk fibroin powder <ns0:ref type='bibr' target='#b31'>(Ha &amp; Park, 2003;</ns0:ref><ns0:ref type='bibr'>Siavashani et al., 2020)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>SEM analysis of silk fibroin and silk sericin:</ns0:head><ns0:p>Powdered samples of silk fibroin and silk sericin were subjected to SEM (Scanning Electron Microscopy) (FEI NOVA 450 NanoSEM) (voltage 1000 kV) available at LUMS (Lahore University of Management Sciences).SEM analysis was done to estimate the approximate sizes of silk fibroin and sericin particles. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Extraction of Aloe vera gel</ns0:head><ns0:p>Fresh Aloe vera gel was extracted from the leaves of the plant. The pulp was scraped out from the leaves and blended into a smooth paste using a high-speed blender. The extracted gel was transferred into an airtight container and refrigerated (4 &#176;C). This extraction was carried out under sterile conditions.</ns0:p></ns0:div> <ns0:div><ns0:head>GC-MS analysis of Aloe vera gel</ns0:head><ns0:p>Aloe vera gel (5 ml) extracted from the leaves was analyzed by GC-MS (Gas chromatography-Mass spectrometry) on a GC-MS equipment at Department of Chemistry, GC University Lahore. GC-MS analysis was performed to detect the bioactive compounds present in the Aloe vera gel. The parameters used in GC-MS analysis were Retention time (RT), I Time, F Time, Area, Area %, Height, Height %, A/H and Base (m/z).</ns0:p></ns0:div> <ns0:div><ns0:head>Preparation of formulations</ns0:head><ns0:p>Gel formulations were prepared for four treatment groups. There were two control groups i.e., positive control in which wounds were treated with polyfax and negative control in which wounds were washed with saline solution (0.9 %) daily. All the groups are shown below: Manuscript to be reviewed</ns0:p><ns0:formula xml:id='formula_0'>T1 5 % Sericin</ns0:formula></ns0:div> <ns0:div><ns0:head>C2</ns0:head><ns0:p>Negative control (Saline solution)</ns0:p></ns0:div> <ns0:div><ns0:head>Sericin (5%)</ns0:head><ns0:p>The gel was prepared by dissolving 0.1 g sodium carboxy-methyl-cellulose Na-CMC in distilled water to form a homogenous solution. Sericin solution (5 %) was prepared in distilled water. Sericin solution was added to the Na-CMC solution with constant stirring until it became a homogenous gel <ns0:ref type='bibr'>(Ersel et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b53'>Nishida et al., 2011)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Fibroin (5%)</ns0:head><ns0:p>Fibroin gel was also prepared by adopting the method outline above. Na-CMC (0.1 g) was dissolved in distilled water to form a homogeneous solution. The fibroin solution (5%) was prepared in distilled water and added to the Na-CMC solution with constant stirring until the solution became thick and homogenous <ns0:ref type='bibr' target='#b53'>(Nishida et al., 2011)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Sericin (5%) and Aloe vera gel (5%)</ns0:head><ns0:p>Sericin solution (5%) was prepared in distilled water, mixed with 5% Aloe vera gel and vortexed for 1 minute. The solution was stored in falcon tubes at low temperature (4 &#176;C) to prevent the growth of micorganisms.</ns0:p></ns0:div> <ns0:div><ns0:head>Fibroin (5%) and Aloe vera gel (5%)</ns0:head><ns0:p>Fibroin solution (5%) was prepared in distilled water and mixed with 5% Aloe vera gel.</ns0:p><ns0:p>The solution was vortexed for 1 minute and stored at low temperature (4 &#176;C) in falcon tubes.</ns0:p></ns0:div> <ns0:div><ns0:head>Application of gel formulations on wounds</ns0:head><ns0:p>The diabetic mice were subjected to their respective treatments till complete wound healing. The formulations were applied evenly on the wound surface daily.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Percent wound contraction</ns0:head><ns0:p>After wound creation, the wound margins were traced at 2 days interval on transparent graph paper. Measurements were continued until the complete (98-99 %) wound restoration.</ns0:p><ns0:p>After 2 days interval, the healed area was calculated. The contraction was represented as percent wound contraction and epithelialization time was observed after complete healing <ns0:ref type='bibr' target='#b43'>(Lodhi et al., 2016)</ns0:ref>.</ns0:p><ns0:p>The rate of healing as percentage contraction was calculated using the formula:</ns0:p><ns0:p>= Initial wound area-Wound area on a specific day x 100</ns0:p></ns0:div> <ns0:div><ns0:head>Initial wound area</ns0:head></ns0:div> <ns0:div><ns0:head>Histological evaluations</ns0:head><ns0:p>Skin sample of one mouse from each group was acquired at post wounding day 5 and 10.</ns0:p><ns0:p>The central portion of tissue was fixed in 10 % buffered formalin (pH=7). Thin sections were prepared using a microtome and stained with hematoxylin-eosin and Masson's trichrome method. Wound healing effects were examined histologically under a light microscope using low power magnification <ns0:ref type='bibr' target='#b4'>(Aramwit &amp; Sangcakul, 2007)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Euthanization and Dissection of animals</ns0:head><ns0:p>For euthanization, mice were placed in beakers and euthanized with a large piece of cotton soaked in chloroform. Beaker was covered properly with an aluminum foil. The mice were euthanized within 10-15 minutes. All euthanized mice were dissected and then skin samples were collected for histological evaluation.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical evaluations</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>For statistical analysis, the normality of the data was assessed using Shapiro-Wilk's test.</ns0:p><ns0:p>One-way ANOVA was conducted out to compare percent wound contraction in control and treatment groups, followed by Tukey's post-hoc test using SPSS software (version 20). All data were expressed as the mean &#177; SEM.</ns0:p></ns0:div> <ns0:div><ns0:head>RESULTS</ns0:head></ns0:div> <ns0:div><ns0:head>SEM analysis of silk fibroin and silk sericin</ns0:head><ns0:p>The scanning electron micrographs (SEM) showed 240-300 nm sized silk fibers of sonicated samples (Figure <ns0:ref type='figure'>1</ns0:ref>). SEM micrographs of silk sericin at 1 &#181;m and 2 &#181;m scale bar are shown in Figure <ns0:ref type='figure'>2</ns0:ref>. Results of SEM indicated that the size of the of silk sericin particles is approximately 102.5 nm when observed at a 1 &#181;m scale bar.</ns0:p></ns0:div> <ns0:div><ns0:head>GC-MS analysis of Aloe vera gel</ns0:head><ns0:p>A total of seventeen compounds were detected in Aloe vera gel by GC-MS analysis (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>).</ns0:p><ns0:p>Five major compounds (2,4:3,5:6,7-Tri-O-benzylidene-1-deoxy-d-gluco-d-gulo-heptitol, stannane bisdiphenyl, isopropyl myristate, 9-Octadecenoic acid and 10-Octadecenoic acid) identified in Aloe vera gel. Their molecular formula, molecular weight (MW), retention time (RT) and peak area (%) are presented in Table <ns0:ref type='table' target='#tab_2'>2</ns0:ref>. Detail of major and minor compounds (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref> and Table <ns0:ref type='table' target='#tab_2'>2</ns0:ref>) detected through GC-MS analysis Aloe vera gel will be helpful in future wound healing studies and they may be utilized individually or in combinations to treat chronic wounds.</ns0:p></ns0:div> <ns0:div><ns0:head>Assessment of wound contraction</ns0:head><ns0:p>Healing area of wounds in treatment and control groups at day 11 is presented in figure <ns0:ref type='figure' target='#fig_7'>3</ns0:ref> and at different days as percent wound contraction in Figure <ns0:ref type='figure' target='#fig_8'>4</ns0:ref>. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Percent wound contraction at various days</ns0:head><ns0:p>Overall, there was significant difference in percent wound contraction between the treatment and control groups at day 3 (F 5,30 = 3.391; P=0.015), day 7 (F 5,30 =7.561; P&lt;0.001) and day 11(F 5,30 =29.19; P&lt;0.01).</ns0:p><ns0:p>There is a non-significant variation in percent wound contraction between T1 (5 % sericin) and C1 (positive control; polyfax) (P&gt;0.05 ANOVA) at day 3. However, there was a significant difference in percent wound contraction on day 3 between T3 (5 % fibroin) and C1</ns0:p><ns0:p>(positive control; polyfax) (P=0.043 ANOVA).</ns0:p><ns0:p>At day 7 results of Tukey's test indicated that group C1 (positive control; polyfax) differs non-significantly from T1 (5% sericin) (P&gt;0.05 ANOVA) and T2 (5 % sericin and 5 % Aloe vera) (P&gt;0.05 ANOVA). On the other hand, there was a significant difference between T3 (5 % fibroin) and C1 (positive control; polyfax) (P=0.037).</ns0:p><ns0:p>At day 11 results of Tukey's test showed that group C1 (positive control; polyfax) differs significantly from T3 (5% fibroin) (P=0.013 ANOVA) and T4 (5 % fibroin and 5 % Aloe vera gel) (P&lt;0.01 ANOVA) in percent wound contraction (Figure <ns0:ref type='figure' target='#fig_8'>4</ns0:ref>). However, the group C1 (positive control; polyfax) differs non-significantly from T1 (5 % sericin) (P&gt;0.05 ANOVA) and T2 (5 % sericin and 5 % Aloe vera) (P&gt;0.05 ANOVA).</ns0:p></ns0:div> <ns0:div><ns0:head>Histological analysis</ns0:head><ns0:p>Images of wound size in different treatment and control groups at post wounding day 10 is shown in Figure <ns0:ref type='figure' target='#fig_9'>5</ns0:ref>. Best histological results were observed in group T4 (5 % fibroin and 5 % Aloe vera gel) in which the formation of the new epidermis was initiated and dermis with blood vessels and hair follicles were observed at post wounding day 10. However, histological results</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed from group C1 (positive control; polyfax) showed the formation of collagen fibers and formation of thin epithelium and dermis at post wounding day 10. Healing of wound was incomplete until day 10 in positive control. In the group C2 (negative control; saline solution) there were inflammatory cells and adipose tissues at post wounding day 10.</ns0:p><ns0:p>Histological examination of wounded tissues from group T1 (5 % sericin) showed the formation of the new epithelial layer. The wound was not completely epithelialized till day 10 and inflammatory cells were also observed. The histology of wound at 100 X of group T2 (i.e., 5 % sericin and 5 % Aloe vera gel) showed adipose tissues and new epithelium and formation of new blood vessels and dermis at day 10. The histology of wound from group T3 (5 % fibroin) showed an uneven epidermal surface. However, the epidermal surface became even and no ulceration was observed on day 10 (Figure <ns0:ref type='figure' target='#fig_9'>5</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>DISCUSSION</ns0:head><ns0:p>In the present study, the potential of silk-based formulations to accelerate the wound healing process in diabetic mice was investigated. The results of this study indicated that silk sericin and fibroin when blended with Aloe vera gel quicken the healing process without causing any allergic reactions.</ns0:p><ns0:p>The wounds treated with 5% silk fibroin and 5% Aloe vera gel showed 85 % healing in 11 days, however; wounds treated with 5 % silk sericin and 5 % Aloe vera gel showed 85 % healing in 15 days. The results of wound healing treated with 5% silk sericin and 5 % Aloe vera gel are comparable with findings of <ns0:ref type='bibr' target='#b4'>Aramwit and Sangcakul (2007)</ns0:ref> that 8 % sericin cream significantly reduced wound healing time. Conversely, wounds treated with cream base healed in 15 days. Moreover, <ns0:ref type='bibr' target='#b40'>Lamboni et al. (2015)</ns0:ref> also reported that the incorporation of silk sericin in wound healing materials forms an exceptional biomaterial that stimulates re-epithelialization by Silk based films are considered safe and non-immunogenic biomaterial. The application of silk-based formulation on the skin does not affect serum profile since silk biofilm possess admirable biocompatibility with skin tissues. As it is infection-resistant in nature, it is regarded as an innovative wound coagulant biomaterial <ns0:ref type='bibr' target='#b55'>(Padol et al., 2011)</ns0:ref>. The current study also indicated that silk proteins (sericin and fibroin) based formulations do not cause any skin irritation, infection, or allergy when applied topically on wounds of diabetic mice. Manuscript to be reviewed healing activity and biocompatibility. In the present study, sericin and fibroin were applied individually as well as in combination with Aloe vera gel on excision wounds in diabetic mice.</ns0:p><ns0:p>The results indicated that 5 % fibroin when mixed with 5 % Aloe vera gel showed the best results among all treatment groups. Healing time till 85% wound contraction was reduced as compared to the control group (polyfax) 15-17 days. These findings suggest that silk can be amalgamated with other natural products like plant extracts to make it biogenic and to improve its medicinal properties.</ns0:p><ns0:p>Aloe vera is a medicinal plant that is widely being explored by scientists for its natural healing ability for skin and other delicate tissues <ns0:ref type='bibr' target='#b35'>(Jadhav et al., 2020)</ns0:ref>. Earlier studies showed that one or more components of Aloe vera stimulate wound healing in different animal models <ns0:ref type='bibr' target='#b30'>(Gallagher and Gray, 2003)</ns0:ref>. <ns0:ref type='bibr' target='#b14'>Chithra et al. (1998)</ns0:ref> analyzed the effects of Aloe vera gel on full thickness wounds in diabetic rats. Their results revealed that treatment with Aloe vera gel speeds up the wound healing process by increasing the rate of collagen synthesis, affecting fibroplasia and wound size reduction. In another study, <ns0:ref type='bibr' target='#b48'>Maenthaisong et al. (2007)</ns0:ref> evaluated the effectiveness of Aloe vera in burn wounds. Aloe vera was observed to increase the rate of reepithelialization and reduce the wound healing period for burn wounds. The results of the current research have also showed that the treatment groups in which silk protein (fibroin) was combined with Aloe vera gel showed greater wound healing potential as compared to a positive control (polyfax). This combination of silk and plant extract was also observed to be most biocompatible as compared to other treatment groups because no inflammation or ulceration was observed on the skin of diabetic mice during the experiment.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>The results of this study suggests that silk based formulations can be utilized in wound healing materials because they are biocompatible, non-immunogenic and reduce wound healing time. This potential of silk-based formulations prepared in combination with Aloe vera gel have not previously been explored. Although the current research demonstrated the potential of silk derived formulations for wound healing in diabetic mice, the underlying molecular factors and events influencing wound healing are yet to be explored. Still, further studies need to be conducted to pinpoint how silk proteins influence the molecular events involved in the wound healing process. Improving wound healing treatments will improve the quality of life of diabetic patients suffering from chronic wounds along with a reduction in their health care costs. Manuscript to be reviewed List of major and minor compounds detected through the GC-MS analysis of Aloe vera gel.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed List of five major compounds with their retention time (RT) and peak area (%) detected through the GC-MS study of Aloe vera gel.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>Blood glucose level was measured with an electronic glucometer (On-call extra blood glucosePeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020) Manuscript to be reviewed improving the rate of migration, adhesion, growth of keratinocytes, fibroblasts and increased production of collagen at the wound site. In a clinical trial, Aramwit et al. (2013) utilized 8 % sericin combined with silver sulfadaizine cream (standard antibiotic cream) to treat open wounds caused by second-degree burns. Outcomes of the study showed that the average healing time of wounds was significantly shorter in the treatment group compared to the control group (silver sulfadaizine without sericin).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Kanokpanont</ns0:head><ns0:label /><ns0:figDesc>et al. (2013) created a silk fibroin based bi-layered wound dressing. Silk fibroin woven fabric coated with wax was taken as a non-adhesive layer whereas the sponge composed of silk sericin and glutaraldehyde-crosslinked silk fibroin/gelatin was fabricated as a bioactive layer. Treatment of wounds with bi-layered wound dressings exhibited the greater potential of wound reduction, increased epithelialization, and collagen formation when compared with clinically available wound dressings. Hence this bi-layered wound dressing is considered as an excellent candidate for healing full-thickness skin wounds. Similarly, in another experiment Baygar (2020) investigated the synergistic effect of propolis and biogenic metallic nanoparticles in combination with silk sutures for biomedical use. It was observed that silk sutures coated with propolis and biogenic AgNPs showed potent antibacterial potential besides providing wound PeerJ reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figures legends Figure 1. SEM micrographs of silk fibroin Figure 2. SEM micrographs of silk sericin Figure 3. Wound healing process in different treatment groups at post wounding day 11.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4: Comparison of percent wound contraction between treatment and control</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5. HE staining showing the histological changes in diabetic mice skin at postwounding day 10 in different treatment groups. Magnifications of 10X. Scale bar = 100 &#956;m.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 5 HE</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 : List of major and minor compounds detected through the GC-MS analysis of Aloe vera gel.</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>PeerJ</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>Compound name</ns0:cell><ns0:cell /><ns0:cell>Molecular</ns0:cell><ns0:cell>Molecular</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>formula</ns0:cell><ns0:cell>weight</ns0:cell></ns0:row><ns0:row><ns0:cell>1</ns0:cell><ns0:cell cols='2'>2,4:3,5:6,7-Tri-O-benzylidene-1-deoxy-d-</ns0:cell><ns0:cell>C 28 H 28 O 6</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>gluco-d-gulo-heptitol</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell>Glycine</ns0:cell><ns0:cell /><ns0:cell>C 36 H 69 NO 6 Si 3</ns0:cell></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell>Di-1,3-xylyl-24-crown-6,</ns0:cell><ns0:cell>5,5'-dimethyl-2,2'-</ns0:cell><ns0:cell>C 32 H 44 O 8</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>bis(2-propenyloxy)</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>4</ns0:cell><ns0:cell cols='2'>Decyl .alpha.-d-galactoside, 2,4,6-detrioxy-3-</ns0:cell><ns0:cell>C 37 H 50 O 3 S 2</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>O-benzyl-4,6-S-dibenzylthio</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>5</ns0:cell><ns0:cell cols='2'>1,5-Anhydro-2,3-dibenzoyl-4,6-O-dibenzyl-d-</ns0:cell><ns0:cell>C 34 H 32 O 7</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>glutitol</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>6</ns0:cell><ns0:cell>Colchicine</ns0:cell><ns0:cell /><ns0:cell>C 31 H 31 NO 7</ns0:cell></ns0:row><ns0:row><ns0:cell>7</ns0:cell><ns0:cell cols='2'>Stannane, bis (pentafluorophenyl) diphenyl</ns0:cell><ns0:cell>C 24 H 10 F 10 Sn</ns0:cell></ns0:row><ns0:row><ns0:cell>8</ns0:cell><ns0:cell>Inositol</ns0:cell><ns0:cell /><ns0:cell>C 24 H 60 O 6 Si 6</ns0:cell></ns0:row><ns0:row><ns0:cell>9</ns0:cell><ns0:cell>Galactonic acid</ns0:cell><ns0:cell /><ns0:cell>C 24 H 60 O 7 Si 6</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>10 Myo-Inositol</ns0:cell><ns0:cell /><ns0:cell>C 24 H 60 O 6 Si 6</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>11 Isopropyl Myristate</ns0:cell><ns0:cell /><ns0:cell>C 17 H 34 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>12 9-Octadecenoic acid</ns0:cell><ns0:cell /><ns0:cell>C 21 H 38 O 4</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>13 Dodecanoic acid</ns0:cell><ns0:cell /><ns0:cell>C 15 H 30 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>14 Hexadecanoic acid, methyl ester</ns0:cell><ns0:cell>C 17 H 34 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>15 10-Octadecenoic acid</ns0:cell><ns0:cell /><ns0:cell>C 19 H 36 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>16 Pentadecanoic acid, 14-methyl-, methyl ester</ns0:cell><ns0:cell>C 17 H 34 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>17 12-Octadecenoic acid, methyl ester</ns0:cell><ns0:cell>C 19 H 36 O 2</ns0:cell></ns0:row></ns0:table><ns0:note>1 reviewing PDF | (2020:04:47956:1:1:NEW 19 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 2 : List of five major compounds with their retention time (RT) and peak area (%) detected through the GC-MS study of Aloe vera gel. No RT Name of the compound Molecular formula Molecular weight</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Peak area</ns0:cell></ns0:row><ns0:row><ns0:cell>(%)</ns0:cell></ns0:row></ns0:table></ns0:figure> </ns0:body> "

"GC UNIVERSITY LAHORE DEPARTMENT OF ZOOLOGY Dr. Shaukat Ali, Assistant Professor, Department of Zoology, Government College University, Lahore, Pakistan Emails: [email protected]. Ph: +92-305-4190596 Thursday, July 02, 2020. Responses to Reviewers for MS. ID. #2020:04:47956 Title: Silk derived formulations for accelerated wound healing in diabetic mice Dear and respected Prof. Dr. Gwyn Gould, Editor, Peer J, Thank you for the opportunity to submit a revised version of the manuscript. As requested, we provide here a rebuttal to the reviewers’ comments, as well as a detailed description of how we have met their suggestions for improvement. Please note that we have made required changes (highlighted in red in text). Thanks again for your consideration. Shaukat Editor comments (Gwyn Gould) As you will see, there is a disparity between the two reviewers. While reviewer-2 raises some minor points, there are substantive concerns raised by reviewer-1, who did not recommend acceptance of the manuscript in this form. Therefore, I felt that you should be given an opportunity to address the issues raised by reviewer-1, in particular the comment regarding the model (point 1) is worrisome. You must address each of these issues systematically in any revision, which will also require tobe re-reviewed. The level of rigour must be increased throughout - note the comments regarding Figures 1, 2 and 3, and Table 3. Reviewer 1 (Lucia Lozano) Basic reporting The manuscript by Tariq et al entitled “Silk derived formulations for accelerated wound healing in diabetic mice” examines the potential of doping silk fibroin and sericin hydrogles with Aloe vera to generate a potential wound treatment product. The manuscript contains a range of data sets but fails to reach the minimum scientific rigour required by this journal. I have got the following specific comments that may help to further improve the manuscript: Selection (many more problems): (1) The in vivo study is flawed. Rodent wound healing is by contraction. In the absence of the splint model the data are misleading. Please see: Adv Wound Care (New Rochelle). 2013 May; 2(4): 142–148.doi: 10.1089/wound.2012.0424 Excellent points. We are happy to mention that most of the researchers select rodents as their model because they are low-cost and are very easy to train and handle. However the potential criticism faced by these models is that the rodent wound healing is by contraction. Conversely, healing in humans is more through re-epithelialization. The use of splints which are fixed in the skin using sutures minimizes wound healing by contraction, yet, this splint model is not without drawbacks i.e. the problem of maintaining and applying the dressing and splint, while keeping infection control at the wound site (1,3,4). Some possible reported disadvantages of splint model may include (2,3, 5): Inflammation at the wound site while anchoring the sutures. The diffusion of the treatment into the systemic circulation or between the wounds. As mentioned in our article, this experiment was conducted on diabetic albino mice which are not considered a true replicate for wound healing in human beings. Diabetic mice are more susceptible to develop infection at the wound site from any pathogen or foreign particle. Furthermore, the major goal of our experiment was to involve less painful, frequent procedures to evaluate the efficacy of silk proteins on diabetic wounds in mice. Therefore, protocol followed in this experiment was kept simple and surgical procedures were not highly sophisticated. References: 1-Mendes, J. J., Leandro, C. I., Bonaparte, D. P., & Pinto, A. L. (2012). A rat model of diabetic wound infection for the evaluation of topical antimicrobial therapies. Comparative medicine, 62(1), 37-48. 2-Dunn, L., Prosser, H. C., Tan, J. T., Vanags, L. Z., Ng, M. K., & Bursill, C. A. (2013). Murine model of wound healing. JoVE (Journal of Visualized Experiments), (75), e50265. 3-Galiano, R. D., Michaels, V, J., Dobryansky, M., Levine, J. P., & Gurtner, G. C. (2004). Quantitative and reproducible murine model of excisional wound healing. Wound repair and regeneration, 12(4), 485-492. 4-Scherer, S. S., Pietramaggiori, G., Mathews, J. C., Chan, R., Fiorina, P., & Orgill, D. P. (2008). Wound healing kinetics of the genetically diabetic mouse. Wounds: a compendium of clinical research and practice, 20(1), 18-28. 5-Galiano, R. D., Tepper, O. M., Pelo, C. R., Bhatt, K. A., Callaghan, M., Bastidas, N., ... & Gurtner, G. C. (2004). Topical vascular endothelial growth factor accelerates diabetic wound healing through increased angiogenesis and by mobilizing and recruiting bone marrowderived cells. The American journal of pathology, 164(6), 1935-1947. (2) Results: Figure 2. I am not convinced this is silk. This looks like salt crystals. Authors also mix up scales. SEM does not appear to be in the nanometer range as described in the body of the manuscript. Excellent point We are sorry but we are pleased to report that we have made this figure very clear now (new figure 1) in our revised manuscript. We would like to mention that this seems like salt crystals but this is silk actually. It may appears so because it has gone through several phases of extraction i.e., degumming, dissolution, dialysis and then sonication as illustrated in this figure: (3) Results: Figure 3. Duplication of images (left and right hand side). Top left figure panel: 102 nm is incorrect. Excellent point. We have made it correct now in our revised manuscript. (4) Results: Table 3 needs to be converted into a bar chart. Excellent suggestion. We are very pleased to report that we have made new figure (new figure 3) of table 3 data in our revised manuscript. (5) Discussion Line 256 following: Based on Table 3 not obvious how day 11 and 15 were selected and seems arbitrary. Excellent point. We are sorry we were not crystal clear. These days were selected randomly in order to show comparison between different treatments based on maximum healing of wounds. (6) Mice: The wound area was not shaved properly. What was the sex of the animals? We are sorry but we did not add preliminary figure in manuscript but we would like to mention that wound area was shaved with electric hand shaver. We tried to remove maximum fur from the wound site as shown in the figure below. The mice used for this study were male. (7) The vast majority of references are outdated. For example, the introduction cites the 2003 Altman review despite numerous timely and up-to-date reviews published over the past 5 years. Excellent point. We are happy to report that we have added recent references in our revised manuscript. (8) Remove Figure 1 because it does not have any content. We have removed figure1 from our revised manuscript. (9) Figure scale bars are absent or too small. Excellent point. We are pleased to report that we have modified figures and now made them very clear in our revised manuscript. (10) Figure 4. Overall appears sloppy: Too small, the annotations are not clear, scale bars are missing etc. Excellent point. We are pleased to report that we have modified figures and now made them very clear in our revised manuscript. (11) Results: All figure legends need to be expanded to include more key information. Excellent point. We are pleased to report that we have modified figures and now made them very clear in our revised manuscript. (12) The manuscript would benefit from English language editing (e.g. abstract “finest biocompatibility”; “wounds in control group (polyfax) were healed” etc. We are very happy to report that we have corrected all mistakes. Furthermore, we are also pleased to mention that we have gone through the manuscript and revised it very carefully and corrected the grammatical and typo mistakes. Experimental design Please see Basic Reporting Validity of the findings Please see Basic Reporting Comments for the Author Please see Basic Reporting Reviewer 2 (Anonymous) Basic reporting In general, language used is clear and professional English is used. Sufficient background information is provided with proper citations except for some parts under methodology (shown in the manuscript as track changes). Proper article structure is used with figures, tables and raw data. We thank this Reviewer for his/her positive detailed analysis of the manuscript. Following comments are Keep a space between a numerical value and units for further improvement Excellent point. We are happy to report that we have added the space between values and units in our revised manuscript. Additional reference is requested under methodology Excellent point. We are happy to report that we have added recent references in methodology section in our revised manuscript. Some figures need revisions (font size of labels, additional labels in Figure 4, comment on Figure 5 T4 day 11 panel). Excellent point. We are pleased to report that we have modified figures and now made them very clear in our revised manuscript. We have reconstructed the figure 4 and figure 5 in our revised manuscript. Experimental design Research question is Ethical standards Experiments conducted have used accepted standards. well were addressed maintained. We thank this Reviewer for his/her positive detailed analysis of the manuscript. Following comments are for further Originality could be more emphasized- focusing on to wound healing in diabetes. improvement One objective may be removed (shown in manuscript with track changes) Excellent point. We are happy to report that we have focused on the wound healing in our revised manuscript. We have deleted the suggested objective in revised manuscript. Comments-on extraction of sericin and measurement of wound contraction need to be addressed. Excellent points. We have removed the suggested objective in our revised manuscript. We are pleased to mention that we have addressed all suggested comments in our revised manuscript. Validity of the findings In general results are supported with relevant figures and tables Conclusions match with research question We thank this Reviewer for his/her positive detailed analysis of the manuscript. Comment on figure 5 T4 panel need to be addressed (shown in manuscript with track changes) Excellent point. We are pleased to report that we have modified figures and now made them very clear in our revised manuscript. We have reconstructed the figure 4 and figure 5 in our revised manuscript. Usefulness of tables 1 and 2 are not well documented. We have provided table 1 and table 2 with major and minor compounds detected through the GC-MS analysis of Aloe vera gel. These compounds individually or combinations may be used for wound healing in future studies. Comments for the Author Comments are covered by 3 areas above We thank this Reviewer for his/her positive detailed analysis of the manuscript. Best wishes. Dr. Shaukat Ali "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background: The present study aimed to prepare effective silk derived formulations in combination with plant extract (Aloe vera gel) to speed up the wound healing process in diabetic mice. Methods: Diabetes was induced in albino mice by using alloxan monohydrate. After successful induction of diabetes in mice, excision wounds were created via biopsy puncture (6mm). Wound healing effect of silk sericin (5%) and silk fibroin (5%) individually and in combination with 5% Aloe vera gel was evaluated by determining the percent wound contraction, healing time and histological analysis.</ns0:p><ns0:p>Results: The results indicated that the best biocompatible silk combination was of 5 % silk fibroin and 5 % Aloe vera gel in which wounds were healed in 13 days with wound contraction: 98.33&#177; 0.80%. In contrast, the wound of the control group (polyfax) healed in 19 day shaving 98.5&#177;0.67% contraction. Histological analysis revealed that the wounds which were treated with silk formulations exhibited an increased growth of blood vessels, collagen fibers, and much reduced inflammation. Conclusion: It can be concluded that a combination of Bombyx mori silk and Aloe vera gel is a natural biomaterial that can be utilized in wound dressings and to prepare more innovative silk based formulations for speedy recovery of chronic wounds.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>INTRODUCTION</ns0:head><ns0:p>Cutaneous wound healing is a programmed, multifaceted and sequential biological process that relies on the interaction between a large number of cells and molecular factors to repair the barrier function of the skin <ns0:ref type='bibr' target='#b71'>(Paquette &amp; Falanga, 2002;</ns0:ref><ns0:ref type='bibr' target='#b62'>Mart&#237;nez-Mora et al., 2012)</ns0:ref>. A 'wound' is the disruption of normal skin physiology, while 'wound healing' is the process the body pursues to restore skin stability <ns0:ref type='bibr'>(Sugihara et al., 2000)</ns0:ref>. Ideal healing of a skin wound requires synchronized incorporation of all molecular and biochemical events of cell proliferation, migration, deposition of extracellular matrix and remodeling <ns0:ref type='bibr' target='#b21'>(Das &amp; Baker, 2016)</ns0:ref>. However, this orderly advancement of the healing process is compromised in chronic, non-healing wounds <ns0:ref type='bibr' target='#b34'>(Falanga, 2005)</ns0:ref>. Chronic wounds normally occur in diabetic patients due to their impaired wound healing process <ns0:ref type='bibr' target='#b77'>(Spampinato et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b35'>Farman et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Diabetes is a prevalent health challenge that impacts people worldwide. It is recognized as a group of varied disorders with the common elements of glucose intolerance, hyperglycemia caused by insulin shortage, reduced efficacy of insulin action, or both <ns0:ref type='bibr'>(Albert &amp; Zimmet, 1998;</ns0:ref><ns0:ref type='bibr' target='#b11'>Atlas, 2015)</ns0:ref>. Non-healing chronic wounds are considered as one of the most serious complications of diabetes. Such complications are associated with an increased risk of bacterial infection, blood vessel and nerve injury, and ultimately amputation of limbs and other organs <ns0:ref type='bibr'>(Masood et al., 2019)</ns0:ref>.</ns0:p><ns0:p>The wound healing process in diabetic patients is profoundly slow as compared to healthy individuals, hence prolonged healing duration increases the risk of wound associated Manuscript to be reviewed infections <ns0:ref type='bibr'>(Menkeet al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b25'>Dehghani et al., 2020)</ns0:ref>.The current wound healing investigations signify the therapeutic potential of formulations in modulating the wound healing process and reducing suffrage of patients <ns0:ref type='bibr' target='#b69'>(Nithya et al., 2011)</ns0:ref>. Scientists have tried different chemicals and herbal formulations to speed up wound healing in diabetic patients but there were certain limitations and the results were not much persuasive.</ns0:p><ns0:p>There is a long history of utilization of natural materials in the biomedical industry. Amongst many naturally occurring materials, silk obtained from silkworms is considered as an exceptional biomaterial which has a wide range of medical applications <ns0:ref type='bibr'>(Jastrzebska et al., 2015;</ns0:ref><ns0:ref type='bibr'>Tahir et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b29'>Elahi et al., 2020)</ns0:ref>. It is classified as a 'model biomaterial' due to its remarkable mechanical strength <ns0:ref type='bibr' target='#b89'>(Vollrath &amp; Porter, 2006;</ns0:ref><ns0:ref type='bibr' target='#b84'>Tahir et al., 2019)</ns0:ref>, impressive biocompatibility with skin tissues, negligible immunogenicity <ns0:ref type='bibr' target='#b59'>(MacIntosh et al., 2008)</ns0:ref> and minimal bacterial adhesion <ns0:ref type='bibr' target='#b14'>(Cassinelli et al., 2006)</ns0:ref>. Mounting evidence of preclinical research demonstrates excellent wound healing properties of silk proteins since the 1990s <ns0:ref type='bibr' target='#b79'>(Shailendra &amp; Das, 2019)</ns0:ref>. Silk (particularly silkworm silk) started its journey in the biomedical industry when it was first used to suture skin wounds <ns0:ref type='bibr' target='#b6'>(Altman et al., 2003)</ns0:ref>.</ns0:p><ns0:p>Silk is the strongest and most flexible naturally occurring fiber. It is smooth, shiny and soft in texture unlike most of the synthetic fibers <ns0:ref type='bibr' target='#b6'>(Altman et al., 2003)</ns0:ref>. There are two proteins fibroin (80%) and sericin (20%) present in the silk thread which is secreted by Bombyx mori's silk glands <ns0:ref type='bibr'>(Pornanong, 2012;</ns0:ref><ns0:ref type='bibr' target='#b31'>El-Fakharany., 2020)</ns0:ref>. The middle and posterior silk glands of B mori larvae produce a fibroin layer and three layers of sericin respectively <ns0:ref type='bibr' target='#b92'>(Zhou et al., 2000)</ns0:ref>.</ns0:p><ns0:p>Sericin and fibroin play an active role in accelerating wound healing <ns0:ref type='bibr' target='#b52'>(Li et al., 2020)</ns0:ref>.The wound healing potential of sericin in cell culture and animal models is well reported <ns0:ref type='bibr' target='#b7'>(Aramwit &amp; Sangcakul, 2007)</ns0:ref>. Successful trials with fibroin based biomaterials, for example sponges <ns0:ref type='bibr'>(Roh et</ns0:ref> PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed <ns0:ref type='bibr'>al., 2006</ns0:ref><ns0:ref type='bibr'>al., ), hydrogels (Finiet al., 2005))</ns0:ref>, films <ns0:ref type='bibr'>(Sugihara et al., 2000)</ns0:ref> and nanofibers mats <ns0:ref type='bibr' target='#b78'>(Schneider et al., 2009)</ns0:ref> have been conducted with impressive results. It has also been reported that silk based wound dressings stimulate cell proliferation and recruitment of cells such as keratinocytes in the wound bed to accelerate the wound healing process <ns0:ref type='bibr' target='#b16'>(Chouhan &amp; Mandal, 2020)</ns0:ref>. Scientists have prepared, silk fibroin/keratin-based biofilms to control the release rate of elastase enzyme in the chronic wound milieu <ns0:ref type='bibr'>(Rohet al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b87'>Vasconcelos et al., 2010)</ns0:ref>.</ns0:p><ns0:p>&#61623; As silk fibroin and sericin exhibit unique biological and physical properties, they are extensively explored by researchers in the biomedical industry for their utilization in wound healing materials. The current study attempts to evaluate the silk-based formulations in treating inducedskin wounds in diabetic mice model. The objectives of this study were to extract pure silk fibroin and silk sericin from silkworm cocoons and to prepare silk-based formulations in combination with plant extract i.e., Aloe vera gel. Furthermore, in vivo wound healing potential of silk based formulations in artificially wounded diabetic mice model was also evaluated.</ns0:p></ns0:div> <ns0:div><ns0:head>MATERIALS AND METHODS</ns0:head></ns0:div> <ns0:div><ns0:head>Ethical statement</ns0:head><ns0:p>All animal trial techniques were directed as per local and worldwide controls. The nearby direction is the Wet op de dierproeven (Article 9) of Dutch Law (International) as detailed in our previous studies <ns0:ref type='bibr' target='#b2'>(Ali et al., 2020a;</ns0:ref><ns0:ref type='bibr' target='#b3'>Ali et al., 2020b;</ns0:ref><ns0:ref type='bibr' target='#b42'>Hussain et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b9'>Ara et al., 2020;</ns0:ref><ns0:ref type='bibr'>Ali et al., 2019;</ns0:ref><ns0:ref type='bibr'>Khan et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b66'>Mumtaz et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b65'>Mughal et al., 2019;</ns0:ref><ns0:ref type='bibr'>Dar et al., 2019)</ns0:ref> and</ns0:p><ns0:p>The Institutional Bioethics Committee at Government College University Lahore, Pakistan (No. GCU/IIB/21 dated: 08-01-2019).</ns0:p></ns0:div> <ns0:div><ns0:head>Rearing of mice in animal house</ns0:head><ns0:p>The Swiss albino mice weighing around 29-30g and 8 weeks old were obtained from the Animal House, Department of Zoology, Government College University Lahore, Pakistan and used as experimental models. They were reared in standard plastic cages of length 10 inches, height 7 inches and width 5 inches in the same Animal House facility of Zoology Department, Government College University Lahore. Six mice were reared per cage under standard laboratory conditions (temperature 19-21 &#176;C, humidity 45-65 % and 12h light-dark cycle). They were fed standard animal diet and tap water in the cage. Mice were acclimatized for one week before the experimental procedures. The weight of each mouse was measured and noted throughout the experiment.</ns0:p></ns0:div> <ns0:div><ns0:head>Diabetes induction</ns0:head><ns0:p>Alloxan and streptozotocin both are widely used diabetogenic agents, but alloxan was preferred over streptozotocin because it was easily available here at low cost. A single dose of alloxan monohydrate (CAT A7413-10G, Signa-Alrich, Germany) was injected intraperitoneally to induce type 1 diabetes. The dosage of alloxan monohydrate was freshly prepared in saline solution at a dosage of 200mg/kg body weight <ns0:ref type='bibr' target='#b0'>(Ahmadi et al., 2012)</ns0:ref>. All animals were fed with Manuscript to be reviewed glucose solution (10%) after receiving an injection of alloxan monohydrate to prevent them from sudden hypoglycemic state <ns0:ref type='bibr' target='#b86'>(Vanitha et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b13'>Bouzghaya et al., 2020)</ns0:ref>. After 24 hrs of induction of diabetes, blood samples were collected by pricking the tail tip of the mice. Blood glucose level was measured with an electronic glucometer (On-call extra blood glucose meter and test strips). Animals with a blood glucose level of &#8805;250 mg/dl were considered diabetic and were selected for further experimentation <ns0:ref type='bibr' target='#b15'>(Chen et al., 2015)</ns0:ref>. Mice were given free access to food and water during the study and they were kept in standard plastic cages at room temperature in the Animal House facility. Blood glucose levels of all albino mice were recorded before starting of the experiment. Only those mice that have normal blood glucose levels were used for further study and those having high blood glucose levels were excluded from the study <ns0:ref type='bibr'>(Dra et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Creation of skin excision wound in mice</ns0:head><ns0:p>Mice were randomly divided into six groups with each group consisting of 6male mice.</ns0:p><ns0:p>Animals were anesthetized intraperitoneally with ketamine (100 mg/kg) and Xylazine (10 mg/kg) in saline before wound induction. The dorsal fur of mice was shaved completely by using an electrical hand shaver. Two full thickness excision wounds were created on the dorsum of each mouse by using a 6mm biopsy punch device. These surgical interventions were carried out under sterile conditions. The total surgical time was 15-20 minutes for each mouse. All animals received their respective treatments once a day from post wounding day till complete healing.</ns0:p><ns0:p>Body weight, skin color and skin irritation were observed and recorded daily.</ns0:p></ns0:div> <ns0:div><ns0:head>Extraction of sericin from cocoons</ns0:head><ns0:p>Silk cocoons of B. mori (silkworm) were kindly supplied by the Sericulture section of Forestry department, Punjab, Pakistan. These cocoons were sliced into small pieces. For sericin PeerJ reviewing <ns0:ref type='table' target='#tab_5'>PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:ref> Manuscript to be reviewed extraction, 5g of silk cocoon pieces were immersed in 100 ml of distilled water and autoclaved at 121 &#176;C and 15 lb per square inch pressure for 1hr. After 1hr the sericin solution was allowed to cool at room temperature and then filtered through a filter paper. The filtration process removed impurities from the sericin solution. The filtered sericin solution was subjected to lyophilizer (freeze drying) at -82 &#176;C for 72 hrs to obtain sericin powder <ns0:ref type='bibr' target='#b56'>(Mart&#237;nez et al., 2017)</ns0:ref>. Extraction procedures of sericin and fibroin were carried out separately by utilizing fresh silk cocoons each time.</ns0:p></ns0:div> <ns0:div><ns0:head>Extraction of fibroin</ns0:head><ns0:p>Degumming: Silk cocoons synthesized by B. mori silkworms were soaked in warm water to loosen the threads. Silk threads from several cocoons were then unwound to obtain silk fibers.</ns0:p><ns0:p>Raw silk fibers were then degummed in 0.5% NaHCO 3 at 100&#176;C for 1hr, rinsed thrice with distilled water and then dried overnight in oven (60-80&#176;C) <ns0:ref type='bibr' target='#b46'>(Ju et al., 2016;</ns0:ref><ns0:ref type='bibr'>Tahir et al., 2020)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Dissolution of silk fibers:</ns0:head><ns0:p>Degummed silk (80 mg) was dissolved for 6-8 hrs at 80&#176;C with constant stirring in a solvent system of calcium chloride: ethanol: distilled water in a molar ratio of 1:2:8 <ns0:ref type='bibr' target='#b90'>(Wang &amp; Zhang, 2013;</ns0:ref><ns0:ref type='bibr' target='#b91'>Yi et al., 2018)</ns0:ref>. Urea (8 mM) was also added to calcium chloride solvent to achieve 100% dissolution of silk fibers <ns0:ref type='bibr' target='#b64'>(Min &amp; Lee, 2004)</ns0:ref>.</ns0:p><ns0:p>Dialysis: After dissolution, the remnants of chemicals were removed through dialysis with a cellulose dialysis membrane in distilled water for 3days. After dialysis the silk fibroin solution was sonicated at 20 kHz: 400W for 1hr and then lyophilized to obtain silk fibroin powder <ns0:ref type='bibr' target='#b40'>(Ha &amp; Park, 2003;</ns0:ref><ns0:ref type='bibr'>Siavashani et al., 2020)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>SEM analysis of silk fibroin and silk sericin:</ns0:head><ns0:p>Powdered samples of silk fibroin and silk sericin were subjected to SEM (Scanning Electron Microscopy) (FEI NOVA 450 Nano SEM) (voltage 1000 kV) available at LUMS (Lahore University of Management Sciences). SEM analysis was done to estimate the approximate sizes of silk fibroin and sericin particles.</ns0:p></ns0:div> <ns0:div><ns0:head>Extraction of Aloe vera gel</ns0:head><ns0:p>Fresh Aloe vera gel was extracted from the leaves of the plant. The pulp was scraped out from the leaves and blended into a smooth paste using a high-speed blender. The extracted gel was transferred into an airtight container and refrigerated (4&#176;C). This extraction was carried out under sterile conditions.</ns0:p></ns0:div> <ns0:div><ns0:head>GC-MS analysis of Aloe vera gel</ns0:head><ns0:p>Aloe vera gel (5 ml) extracted from the leaves was analyzed by GC-MS (Gas chromatography-Mass spectrometry) on a GC-MS equipment at Department of Chemistry, GC University Lahore. GC-MS analysis was performed to detect the bioactive compounds present in the Aloe vera gel. The parameters used in GC-MS analysis were Retention time (RT), I Time, F Time, Area, Area %, Height, Height %, A/H and Base (m/z).</ns0:p></ns0:div> <ns0:div><ns0:head>Preparation of formulations</ns0:head><ns0:p>Gel formulations were prepared for four treatment groups. There were two control groups i.e., positive control in which wounds were treated with polyfax (Polyfax is a skin ointment with active ingredients Bacitracin zinc and Polymiyxin B sulphate. Both of these ingredients are antibacterial. This ointment is used for the treatment of infected surgical cuts, burns, infected wounds, infected ulcers on skin etc) and negative control in which wounds were washed with saline solution (0.9 %) daily. All the groups are shown below:</ns0:p></ns0:div> <ns0:div><ns0:head>T1</ns0:head><ns0:p>5% Sericin </ns0:p></ns0:div> <ns0:div><ns0:head>C2</ns0:head><ns0:p>Negative control (Saline solution)</ns0:p></ns0:div> <ns0:div><ns0:head>Sericin (5%)</ns0:head><ns0:p>The gel was prepared by dissolving 0.1g sodium carboxy-methyl-cellulose Na-CMC in distilled water to form a homogenous solution. Sericin solution (5%) was prepared in distilled water. Sericin solution was added to the Na-CMC solution with constant stirring until it became a homogenous gel <ns0:ref type='bibr' target='#b33'>(Ersel et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b67'>Nishida et al., 2011)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Fibroin (5%)</ns0:head><ns0:p>Fibroin gel was also prepared by adopting the method outline above. Na-CMC (0.1g) was dissolved in distilled water to form a homogeneous solution. The fibroin solution (5%) was prepared in distilled water and added to the Na-CMC solution with constant stirring until the solution became thick and homogenous <ns0:ref type='bibr' target='#b67'>(Nishida et al., 2011)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Sericin (5%) and Aloe vera gel (5%)</ns0:head><ns0:p>Sericin solution (5%) was prepared in distilled water, mixed with 5% Aloe vera gel and vortexed for 1 minute. The solution was stored in falcon tubes at low temperature (4&#176;C) to prevent the growth of microorganisms.</ns0:p></ns0:div> <ns0:div><ns0:head>Fibroin (5%) and Aloe vera gel (5%)</ns0:head><ns0:p>Fibroin solution (5%) was prepared in distilled water and mixed with 5% Aloe vera gel.</ns0:p><ns0:p>The solution was vortexed for 1 minute and stored at low temperature (4&#176;C) in falcon tubes.</ns0:p></ns0:div> <ns0:div><ns0:head>Application of gel formulations on wounds</ns0:head><ns0:p>The diabetic mice were subjected to their respective treatments till complete wound healing. The formulations were applied evenly on the wound surface daily.</ns0:p></ns0:div> <ns0:div><ns0:head>Percent wound contraction</ns0:head><ns0:p>After wound creation, the wound margins were traced at 2 days interval on transparent graph paper. Measurements were continued until the complete (98-99%) wound restoration.</ns0:p><ns0:p>After 2 days interval, the healed area was calculated. The contraction was represented as percent wound contraction and epithelialization time was observed after complete healing <ns0:ref type='bibr' target='#b55'>(Lodhi et al., 2016)</ns0:ref>.</ns0:p><ns0:p>The rate of healing as percentage contraction was calculated using the formula:</ns0:p><ns0:p>= Initial wound area-Wound area on a specific day x 100</ns0:p></ns0:div> <ns0:div><ns0:head>Initial wound area</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Histological evaluations</ns0:head><ns0:p>Skin sample of one mouse from each group was acquired at post wounding day 5 and 10.</ns0:p><ns0:p>The central portion of tissue was fixed in 10% buffered formalin (pH=7). Thin sections were prepared using a microtome and stained with hematoxylin-eosin and Masson's trichrome method. Wound healing effects were examined histologically under a light microscope using low power magnification <ns0:ref type='bibr' target='#b7'>(Aramwit &amp; Sangcakul, 2007)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Euthanization and Dissection of animals</ns0:head><ns0:p>For euthanization, mice were placed in beakers and euthanized with a large piece of cotton soaked in chloroform. Beaker was covered properly with an aluminum foil. The mice were euthanized within 10-15 minutes. All euthanized mice were dissected and then skin samples were collected for histological evaluation.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical evaluations</ns0:head><ns0:p>For statistical analysis, the normality of the data was assessed using Shapiro-Wilk's test.</ns0:p><ns0:p>One-way ANOVA was conductedout to compare percent wound contractionin control and treatment groups, followed by Tukey's post-hoc test using SPSS software (version 20). All data were expressed as the mean &#177; SEM.</ns0:p></ns0:div> <ns0:div><ns0:head>RESULTS</ns0:head></ns0:div> <ns0:div><ns0:head>TEM analysis of silk fibroin and silk sericin</ns0:head><ns0:p>The transmission electron micrographs (TEM) showed 240-300 nm sized silk fibers of sonicated samples (Figure <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>). TEM micrographs of silk sericin at 2 &#181;m scale bar are shown in Figure <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>.</ns0:p><ns0:p>Results of TEM indicated that the size of the of silk sericin particles is approximately 102.5 nm.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>GC-MS analysis of Aloe vera gel</ns0:head><ns0:p>A total of seventeen compounds were detected in Aloe vera gel by GC-MS analysis (Table <ns0:ref type='table' target='#tab_2'>1</ns0:ref>).</ns0:p><ns0:p>Five major compounds (2,4:3,5:6,7-Tri-O-benzylidene-1-deoxy-d-gluco-d-gulo-heptitol, stannane bis diphenyl, isopropyl myristate, 9-Octadecenoic acid and 10-Octadecenoic acid)identified in Aloe vera gel. Their molecular formula, molecular weight (MW), retention time (RT) and peak area (%) are presented in Table <ns0:ref type='table' target='#tab_4'>2</ns0:ref>.Detail of major and minor compounds (Table <ns0:ref type='table' target='#tab_5'>1 and Table 2</ns0:ref>) detected through GC-MS analysis of Aloe vera gel will be helpful in future wound healing studies and they may be utilized individually or in combinations for preparing more effective gel formulations to treat chronic wounds.</ns0:p></ns0:div> <ns0:div><ns0:head>Assessment of wound contraction</ns0:head><ns0:p>Healing area of wounds in treatment and control groups at day 11 is presented in figure <ns0:ref type='figure' target='#fig_7'>2</ns0:ref> and at different days as percent wound contraction in Figure <ns0:ref type='figure' target='#fig_8'>3</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Percent wound contraction at various days</ns0:head><ns0:p>Overall, there was significant difference in percent wound contraction between the treatment and control groups at day 3 (F 5,30 = 3.391; P=0.015), day 7 (F 5,30 =7.561; P&lt;0.001) and day 11(F 5,30 =29.19; P&lt;0.01). There is a non-significant variation in percent wound contraction between T1 (5% sericin) and C1 (positive control; polyfax) (P&gt;0.05 ANOVA) at day 3.</ns0:p><ns0:p>However, there was a significant difference in percent wound contraction on day 3 between T3 (5% fibroin) and C1 (positive control; polyfax) (P=0.043 ANOVA).</ns0:p><ns0:p>At day 7 results of Tukey's test indicated that group C1 (positive control; polyfax) differs non-significantly from T1 (5% sericin) (P&gt;0.05 ANOVA) and T2 (5% sericin and 5%Aloe vera)(P&gt;0.05 ANOVA).On the other hand, there was a significant difference between T3 (5% Manuscript to be reviewed fibroin) and C1 (positive control; polyfax) (P=0.037). At day 11 results of Tukey's test showed that group C1 (positive control; polyfax) differs significantly from T3 (5% fibroin) (P=0.013 ANOVA) and T4 (5% fibroin and 5% Aloe veragel) (P&lt;0.01 ANOVA) in percent wound contraction (Figure <ns0:ref type='figure' target='#fig_8'>3</ns0:ref>). However, the group C1 (positive control; polyfax) differs nonsignificantly from T1 (5% sericin) (P&gt;0.05 ANOVA) and T2 (5% sericin and 5% Aloe vera) (P&gt;0.05 ANOVA).</ns0:p></ns0:div> <ns0:div><ns0:head>Histological analysis</ns0:head><ns0:p>Images of wound size in different treatment and control groups at post wounding day 10 is shown in Figure <ns0:ref type='figure' target='#fig_9'>4</ns0:ref>. Best histological results were observed in group T4 (5% fibroin and 5%</ns0:p><ns0:p>Aloe vera gel) in which the formation of the new epidermis was initiated and dermis with blood vessels and hair follicles were observed at post wounding day 10. However, histological results from group C1 (positive control; polyfax) showed the formation of collagen fibers and formation of thin epithelium and dermis at post wounding day 10. Healing of wound was incomplete untilday 10 in positive control. In the group C2 (negative control; saline solution) there were inflammatory cells and adipose tissues at post wounding day 10.</ns0:p><ns0:p>Histological examination of wounded tissues from group T1 (5% sericin) showed the formation of the new epithelial layer. The wound was not completely epithelialized till day 10 and inflammatory cells were also observed. The histology of wound at 100X of group T2 (i.e.,5% sericin and 5% Aloe vera gel) showed adipose tissues and new epithelium and formation of new blood vessels and dermis at day 10. The histology of wound from group T3 (5% fibroin)</ns0:p><ns0:p>showed an uneven epidermal surface. However, the epidermal surface became even and no ulceration was observed on day 10 (Figure <ns0:ref type='figure' target='#fig_9'>4</ns0:ref>). Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>DISCUSSION</ns0:head><ns0:p>In the present study, the potential of silk-based formulations to accelerate the wound healing process in diabetic mice was investigated. The results of this study indicated that silk sericin and fibroin when blended with Aloe vera gel quicken the healing process without causing any allergic reactions.</ns0:p><ns0:p>The wounds treated with 5% silk fibroin and 5% Aloe vera gel showed 85% healing in 11 days, however; wounds treated with 5% silk sericin and 5% Aloe vera gel showed 85 % healing in 15 days. The results of wound healing treated with 5% silk sericin and 5%Aloe vera gel are comparable with findings of <ns0:ref type='bibr' target='#b7'>Aramwit and Sangcakul (2007)</ns0:ref> Silk based films are considered safe and non-immunogenic biomaterial. The application of silk-based formulation on the skin does not affect serum profile since silk biofilm possess admirable biocompatibility with skin tissues. As it is infection-resistant in nature, it is regarded as an innovative wound coagulant biomaterial <ns0:ref type='bibr' target='#b70'>(Padol et al., 2011)</ns0:ref>. The current study also The results indicated that 5% fibroin when mixed with 5% Aloe vera gel showed the best results among all treatment groups. Healing time till 85% wound contraction was reduced as compared to the control group (polyfax) 15-17 days. These findings suggest that silk can be amalgamated with other natural products like plant extracts to make it biogenic and to improve its medicinal properties.</ns0:p><ns0:p>Aloe vera is a medicinal plant that is widely being explored by scientists for its natural healing ability for skin and other delicate tissues <ns0:ref type='bibr'>(Jadhavet al., 2020)</ns0:ref>. Earlier studies showed that one or more components of Aloe vera stimulate wound healing in different animal models Manuscript to be reviewed <ns0:ref type='bibr' target='#b39'>(Gallagher and Gray, 2003)</ns0:ref>. <ns0:ref type='bibr' target='#b17'>Chithra et al. (1998)</ns0:ref> analyzed the effects of Aloe vera gel on full thickness wounds in diabetic rats. Their results revealed that treatment with Aloe vera gel speeds up the wound healing process by increasing the rate of collagen synthesis, affecting fibroplasia and wound size reduction. In another study, <ns0:ref type='bibr'>Maenthaisonget al. (2007)</ns0:ref> evaluated the effectiveness of Aloe vera in burn wounds. Aloe vera was observed to increase the rate of reepithelialization and reduce the wound healing period for burn wounds. The results of the current research have also showed that the treatment groups in which silk protein (fibroin) was combined with Aloe vera gel showed greater wound healing potential as compared to a positive control (polyfax). This combination of silk and plant extract was also observed to be most biocompatible as compared to other treatment groups because no inflammation or ulceration was observed on the skin of diabetic mice during the experiment.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>The results of this study suggests that silk based formulations can be utilized in wound healing materials because they are biocompatible, non-immunogenic and reduce wound healing time. This potential of silk-based formulations prepared in combination with Aloe vera gel has not previously been explored. Although the current research demonstrated the potential of silk derived formulations for wound healing in diabetic mice, the underlying molecular factors and events influencing wound healing are yet to be explored. Still, further studies need to be conducted to pinpoint how silk proteins influence the molecular events involved in the wound healing process. Improving wound healing treatments will improve the quality of life of diabetic patients suffering from chronic wounds along with a reduction in their health care costs. C1=Positive control (Polyfax); C2=Negative control (Saline solution); T1=5% Sericin; T2=5%</ns0:p><ns0:p>Sericin and 5%Aloe vera gel; T3=5% Fibroin; T4=5% Fibroin and 5%Aloe vera gel. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed List of major and minor compounds detected through the GC-MS analysis of Aloe vera gel.</ns0:p><ns0:note type='other'>Figure 1</ns0:note><ns0:note type='other'>Figure 2</ns0:note><ns0:note type='other'>Figure 3</ns0:note><ns0:note type='other'>Figure 4</ns0:note><ns0:p>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed List of five major compounds with their retention time (RT) and peak area (%) detected through the GC-MS study of Aloe vera gel.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>that 8% sericin cream significantly reduced wound healing time. Conversely, wounds treated with cream base healed in 15 days. Moreover,<ns0:ref type='bibr' target='#b51'>Lamboni et al. (2015)</ns0:ref> also reported that the incorporation of silk sericin in wound healing materials forms an exceptional biomaterial that stimulates re-epithelialization by improving the rate of migration, adhesion, growth of keratinocytes, fibroblasts and increased production of collagen at the wound site.In a clinical trial, Aramwitet al. (2013) utilized 8% sericin combined with silver sulfadaizine cream (standard antibiotic cream) to treat open wounds caused by second-degree burns. Outcomes of the study showed that the average healing time of wounds was significantly shorter in the treatment group compared to the control group (silver sulfadaizine without sericin).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)Manuscript to be reviewed indicated that silk proteins (sericin and fibroin) based formulations do not cause any skin irritation, infection, or allergy when applied topically on wounds of diabetic mice.<ns0:ref type='bibr' target='#b47'>Kanokpanont et al. (2013)</ns0:ref> created a silk fibroin based bi-layered wound dressing. Silk fibroin woven fabric coated with wax was taken as a non-adhesive layer whereas the sponge composed of silk sericin and glutaraldehyde-crosslinked silk fibroin/gelatin was fabricated as a bioactive layer. Treatment of wounds with bi-layered wound dressings exhibited the greater potential of wound reduction, increased epithelialization, and collagen formation when compared with clinically available wound dressings. Hence this bi-layered wound dressing is considered as an excellent candidate for healing full-thickness skin wounds. Similarly, in another experiment<ns0:ref type='bibr' target='#b12'>Baygar (2020)</ns0:ref> investigated the synergistic effect of propolis and biogenic metallic nanoparticles in combination with silk sutures for biomedical use. It was observed that silk sutures coated with propolis and biogenic AgNPs showed potent antibacterial potential besides providing wound healing activity and biocompatibility. In the present study, sericin and fibroin were applied individually as well as in combination with Aloe vera gel on excision wounds in diabetic mice.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figures legends Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figures legends Figure 1. Electron micrographs of silk fibroin and sericin. A. Electron micrograph of</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Wound healing process in different treatment groups at post wounding day</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. Comparison of percent wound contraction between treatment and control</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. H &amp; E staining showing the histological changes in diabetic mice skin at postwounding day 10 in different treatment groups. Magnifications of 10X. Scale bar = 100 &#956;m.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Electron micrographs of silk fibroin and sericin.</ns0:figDesc><ns0:graphic coords='26,42.52,204.37,525.00,393.75' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Wound healing process in different treatment groups at post wounding day 11.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. Comparison of percent wound contraction between treatment and control groups.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. H &amp; E staining showing the histological changes in diabetic mice skin at postwounding day 10 in different treatment groups.</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 1 : List of major and minor compounds detected through the GC-MS analysis of Aloe vera gel.</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>PeerJ</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>Compound name</ns0:cell><ns0:cell /><ns0:cell>Molecular</ns0:cell><ns0:cell>Molecular</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>formula</ns0:cell><ns0:cell>weight</ns0:cell></ns0:row><ns0:row><ns0:cell>1</ns0:cell><ns0:cell cols='2'>2,4:3,5:6,7-Tri-O-benzylidene-1-deoxy-d-</ns0:cell><ns0:cell>C 28 H 28 O 6</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>gluco-d-gulo-heptitol</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell>Glycine</ns0:cell><ns0:cell /><ns0:cell>C 36 H 69 NO 6 Si 3</ns0:cell></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell>Di-1,3-xylyl-24-crown-6,</ns0:cell><ns0:cell>5,5'-dimethyl-2,2'-</ns0:cell><ns0:cell>C 32 H 44 O 8</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>bis(2-propenyloxy)</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>4</ns0:cell><ns0:cell cols='2'>Decyl .alpha.-d-galactoside, 2,4,6-detrioxy-3-</ns0:cell><ns0:cell>C 37 H 50 O 3 S 2</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>O-benzyl-4,6-S-dibenzylthio</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>5</ns0:cell><ns0:cell cols='2'>1,5-Anhydro-2,3-dibenzoyl-4,6-O-dibenzyl-d-</ns0:cell><ns0:cell>C 34 H 32 O 7</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>glutitol</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>6</ns0:cell><ns0:cell>Colchicine</ns0:cell><ns0:cell /><ns0:cell>C 31 H 31 NO 7</ns0:cell></ns0:row><ns0:row><ns0:cell>7</ns0:cell><ns0:cell cols='2'>Stannane, bis (pentafluorophenyl) diphenyl</ns0:cell><ns0:cell>C 24 H 10 F 10 Sn</ns0:cell></ns0:row><ns0:row><ns0:cell>8</ns0:cell><ns0:cell>Inositol</ns0:cell><ns0:cell /><ns0:cell>C 24 H 60 O 6 Si 6</ns0:cell></ns0:row><ns0:row><ns0:cell>9</ns0:cell><ns0:cell>Galactonic acid</ns0:cell><ns0:cell /><ns0:cell>C 24 H 60 O 7 Si 6</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>10 Myo-Inositol</ns0:cell><ns0:cell /><ns0:cell>C 24 H 60 O 6 Si 6</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>11 Isopropyl Myristate</ns0:cell><ns0:cell /><ns0:cell>C 17 H 34 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>12 9-Octadecenoic acid</ns0:cell><ns0:cell /><ns0:cell>C 21 H 38 O 4</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>13 Dodecanoic acid</ns0:cell><ns0:cell /><ns0:cell>C 15 H 30 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>14 Hexadecanoic acid, methyl ester</ns0:cell><ns0:cell>C 17 H 34 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>15 10-Octadecenoic acid</ns0:cell><ns0:cell /><ns0:cell>C 19 H 36 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>16 Pentadecanoic acid, 14-methyl-, methyl ester</ns0:cell><ns0:cell>C 17 H 34 O 2</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>17 12-Octadecenoic acid, methyl ester</ns0:cell><ns0:cell>C 19 H 36 O 2</ns0:cell></ns0:row></ns0:table><ns0:note>1 reviewing PDF | (2020:04:47956:2:0:NEW 28 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 2 : List of five major compounds with their retention time (RT) and peak area (%) detected through the GC-MS study of Aloe vera gel. No RT Name of the compound Molecular formula Molecular weight</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Peak area</ns0:cell></ns0:row><ns0:row><ns0:cell>(%)</ns0:cell></ns0:row></ns0:table></ns0:figure> </ns0:body> "

" GC UNIVERSITY LAHORE DEPARTMENT OF ZOOLOGY Dr. Shaukat Ali, Assistant Professor, Department of Zoology, Government College University, Lahore, Pakistan Emails: [email protected]. Ph: +92-305-4190596 Thursday, January 19, 2023. Responses to Reviewers for MS. ID. #2020:04:47956:1:1: REVIEW. Title: Silk derived formulations for accelerated wound healing in diabetic mice Dear and respected Prof. Dr. Gwyn Gould, Editor, Peer J, Thank you for the opportunity to submit a re-revised version of the manuscript. As requested, we provide here a rebuttal to the reviewers’ comments, as well as a detailed description of how we have met their suggestions for improvement. Please note that we have made required changes (highlighted in red in text). Thanks again for your consideration. Shaukat Editor comments (Gwyn Gould) Thanks for your patience. One (re)-reviewer still felt strongly that we should reject. I felt this possibly harsh, so in the interest of fairness I ended up seeking further opinions on this article which has caused a little delay; I hope you will indulge this as the reviewers are helpful. They are positive and the suggestion of all three is that publication is warranted should you be able to make some minor amendments. Please take careful note of the issues raised by reviewer-3 (SEM info, scale bars/clarity on the SEM figure and the labels on the H&E stains should be improved). Reviewer-5's comments need to be fully and carefully addressed, but these do not involve experimental work. If you can clearly address these points and return the manuscript, I should be able to make a final decision without re-review fairly quickly. Excellent suggestion. We are very happy to report that we have corrected all mistakes. We have revised improved the figures. Furthermore, we are also pleased to mention that we have gone through the manuscript and revised it very carefully and corrected the grammatical and typo mistakes. Reviewer 1 (Anonymous) Basic reporting Addressing point 1 is beyond the scope of a revision. The model system is not robust and thus not of the required standard for Peer J. Thank you very much for your positive assessment. Experimental design See above Validity of the findings n/a Comments for the Author Addressing point 1 is beyond the scope of a revision. The model system is not robust and thus not of the required standard for Peer J. Thank you very much for your positive assessment. Reviewer 3 (Anonymous) Basic reporting The article entitled 'Silk derived formulations for accelerated wound healing in diabetic mice” by Tariq et al is written in clear English. Thank you very much for your positive assessment. The language needs some improvement, but the formulated hypothesis and scientific method to address research question are clear and well structured. Excellent suggestion. We are very happy to report that we have corrected all mistakes. Furthermore, we are also pleased to mention that we have gone through the manuscript and revised it very carefully and corrected the grammatical and typo mistakes. Experimental design In vivo study design is fairly solid with five treatment groups and a negative control. Moreover, given the ethical constrains, six animals per treatment group are convincing numbers 'N' to conclude the rigor and strength of the findings based on statistical grounds. Method has sufficient detail and where aver possible well supported by relevant reference. Thank you very much for your positive assessment. Validity of the findings Although the silk proteins are known to induce beneficial wound healing effect however combination with medicinal plant extract in this current study has significantly improved wound healing in diabetic rodent model. Findings are strong and may eventually seek applications in pharma industry and medical sciences. Thank you very much for your positive assessment. Comments for the Author I reviewed the article entitled “Silk derived formulations for accelerated wound healing in diabetic mice” by Tariq et al. In this manuscript, the authors have developed a new wound healing formulation by combining silk derived proteins, fibroin and sericin and aloe vera plant extract (gel). They then examined wound healing potential of this formulation in vivo on the chemically induced diabetic mouse model. The findings suggested that the combination of fibroin and Aloe vera gel provides beneficial wound healing effects as opposed to fibroin alone or a combination of sericin and aloe vera gel. Thank you very much for your positive assessment. Although, as authors indicated, the wound healing effect conferred by the cocoon’s derived silk proteins is well known, however, the idea of combining silk protein with the extract of naturally existing medicinal plants and subsequently, testing the formulation on diabetic mouse model is very promising, which may eventually contribute to the fields of pharma industry and medical sciences. Thank you very much for your positive assessment. As such the SEM images (fig 1 and fig 2) look suboptimal. I would suggest combining both figures as one with the same scale bar. If possible another confirmatory test could be done to show that the extracted proteins are indeed silk fibers. Since both proteins are available commercially, maybe a head to head western blot comparison or an in vitro cell based motility assay (doi: 10.1371/journal.pone.0042271) could be sufficient to show authenticity of the extracted proteins. Excellent suggestions. We are very happy to report that we have made substantially improved figures in our revised manuscript. Authors should indicate statistical significance (p value) on the bars of figure 4 showing comparison of at least control versus silk protein and aloe vera formulations treated groups. Excellent suggestions. We are very happy to report that we have made substantially improved figures in our revised manuscript. Labels within the H&E stained images are not readable, the authors should increase font size to make it visible. Excellent suggestions. We are very happy to report that we have made substantially improved figures in our revised manuscript. Reviewer 4 (Anonymous) Basic reporting The authors have successfully addressed all the queries raised by the other reviewers about the manuscript 'Silk derived formulations for accelerated wound healing in diabetic mice'. I have no further queries. Thank you very much for your positive assessment. Experimental design The experimental designs are looking good. Thank you very much for your positive assessment. Validity of the findings The conclusions are well stated and relevant to the current scenario of the field. Thank you very much for your positive assessment. Comments for the Author No further comments. Thank you very much for your positive assessment. Reviewer 5 (Anonymous) Basic reporting Interesting question, how different silk components act together with Aloe extracts in diabetic wound healing. Silk proteins are being reported as effective wound healers in different research articles. Similarly the efficacy of Aloe vera extract in skin injuries, accidental wounds, cuts and burns is also well documented by many researchers. It has antifungal and antimicrobial effects and accelerates wound healing in many animal models. In the current study, we mixed both of these in order to evaluate their combined effect on wound healing in diabetic mice. The manuscript is a revised version, which was clearly improved based on the reviewer’s comments. Thank you very much for your positive assessment Still the references are in inconsistent formats and partially incomplete eg. Still the references are in inconsistent formats and partially incomplete eg. Bouzghaya, S., Amri, M. and Homblé, F., 2020. Improvement of Diabetes Symptoms and Complications by an Aqueous Extract of Linum usitatissimum (L.) Seeds in Alloxan-Induced Diabetic Mice. Journal of Medicinal Food 00(0):1-6. REV:Missing details Cassinelli, C., Cascardo, G., Morra, M., Draghi, L., Motta, A. &Catapano, G., 2006. Physical-chemical and biological characterization of silk fibroin-coated porous membranes for medical applications.Int J Artif Organs., 29(9):881-92 . REV:Only first page Acta biomaterialia., 48:157-174. REV: Unclear Journal name We are pleased to mentioned that we have formatted all references according to the journal guidelines Experimental design Alloxan and streptozotocin are the most popular diabetogenic agents used for models, it is not mentioned why alloxan was used in this model and which type of diabetes does this represent. Excellent point. We are happy to mention that Alloxan is commonly injected to induce Type 1 diabetes in experimental animals. It is readily available here and also inexpensive that is why it was used in this study. A non-splinted excision model was used in mice. It should be mentioned what Polyfax is (antibiotic ointment) Excellent point. We are pleased to report that we have mentioned that Polyfax is a skin ointment with active ingredients Bacitracin zinc and Polymiyxin B sulphate. Both of these ingredients are antibacterial. This ointment is used for the treatment of infected surgical cuts, burns, infected wounds, infected ulcers on skin etc. Validity of the findings I cannot find all the underlying data, only single examples of in vivo and histology figures are given. We are happy to mention that we provided the data as supplementary data in addition to in vivo and histology figures. Although the figures might have been improved, they are still of low quality. Fig 1 and 2 do not give a clear information, which comes also from the very limited figure legends. Quality of histology is limited. Excellent suggestions. We are very happy to report that we have made substantially improved figures in our revised manuscript. It is unclear for which purpose the tables with MS results are shown, because there was no research question associated and also no discussion presented. Although, there was no research question associated with GC-MS, this was only performed to analyze the Aloe vera gel and to detect the bioactive compounds present in it. A detailed list of bioactive compounds present in Aloe vera gel will be helpful in future studies for preparing more effective gel formulations. Comments for the Author Best wishes. Dr. Shaukat Ali "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. The emergence of a novel coronavirus (SARS-CoV-2) associated with severe acute respiratory disease has prompted efforts to understand the genetic basis for its unique characteristics and its jump from non-primate hosts to humans. Tests for positive selection can identify apparently nonrandom patterns of mutation accumulation within genomes, highlighting regions where molecular function may have changed during the origin of a species. Several recent studies of the SARS-CoV-2 genome have identified signals of conservation and positive selection within the gene encoding Spike protein based on the ratio of synonymous to nonsynonymous substitution. Such tests cannot, however, detect changes in the function of RNA molecules. Methods. Here we apply a test for branch-specific oversubstitution of mutations within narrow windows of the genome without reference to the genetic code. Results. We recapitulate the finding that the gene encoding Spike protein has been a target of both purifying and positive selection.</ns0:p><ns0:p>In addition, we find other likely targets of positive selection within the genome of SARS-CoV-2, specifically within the genes encoding Nsp4 and Nsp16. Homology-directed modeling indicates no change in either Nsp4 or Nsp16 protein structure relative to the most recent common ancestor. These SARS-CoV-2-specific mutations may affect molecular processes mediated by the positive or negative RNA molecules, including transcription, translation, RNA stability, and evasion of the host innate immune system. Our results highlight the importance of considering mutations in viral genomes not only from the perspective of their impact on protein structure, but also how they may impact other molecular processes critical to the viral life cycle.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>An important challenge in understanding zoonotic events is identifying the genetic changes that allow a pathogen to infect a new host. Such information can highlight molecular processes in both the pathogen and host that have practical value. The recent outbreak of SARS-CoV-2, a novel coronavirus, provides both a challenge and an opportunity to learn more about the specific adaptations that enable the virus to thrive in human hosts and that endow it with traits distinct from previously described coronaviruses <ns0:ref type='bibr' target='#b1'>(Andersen et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b62'>Morens et al., 2020)</ns0:ref>. Formal tests for natural selection are a powerful tool in this endeavor because they can be applied in an unbiased manner throughout the viral genome: evidence of negative selection can reveal regions of the genome that are broadly constrained functionally and thus unlikely to contribute to species-specific traits, while evidence of branch-specific positive selection can identify candidate regions of the genome where molecular processes may have diverged from that of other species.</ns0:p><ns0:p>Several recent studies have tested for natural selection in the SARS-CoV-2 genome based on the ratio of synonymous to non-synonymous (dN/dS) substitutions relative to other coronaviruses <ns0:ref type='bibr' target='#b81'>(Tang et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b11'>Chaw et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b50'>Li et al., 2020a)</ns0:ref>. The most prominent signal to emerge from these studies is a mix of positive and purifying selection within the gene encoding the Spike glycoprotein, which mediates invasion of host cells by binding to the angiotensin-converting enzyme 2 (ACE2) receptor in host cells <ns0:ref type='bibr' target='#b22'>(Gallagher &amp; Buchmeier, 2001;</ns0:ref><ns0:ref type='bibr' target='#b82'>Tortorici &amp; Veesler, 2019)</ns0:ref>. This finding makes good biological sense, because structural changes in the spike protein are common and are known to influence the ability of the virus to infect new hosts and jump between species <ns0:ref type='bibr' target='#b36'>(Hulswit, de Haan &amp; Bosch, 2016)</ns0:ref>. A single nucleotide polymorphism <ns0:ref type='bibr'>(SNP)</ns0:ref> that results in an amino acid substitution in Spike protein (A&gt;G at 23,403 bp; D614G) has PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020) increased in frequency during the global pandemic more rapidly than other SNPs <ns0:ref type='bibr' target='#b44'>(Korber et al., 2020)</ns0:ref>, leading to speculation that it is an adaptation that alters the interaction between Spike and ACE2, FURIN and TMPRSS2 <ns0:ref type='bibr' target='#b15'>(Eaaswarkhanth, Al Madhoun &amp; Al-Mulla, 2020)</ns0:ref>.</ns0:p><ns0:p>Beyond mutations that alter Spike protein, however, there exists little understanding of positive selection within the SARS-CoV-2 genome and how this may have shaped viral traits. Few convincing signals of positive selection exist for any of the other viral proteins <ns0:ref type='bibr' target='#b9'>(Cagliani et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b85'>Velazquez-Salinas et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b11'>Chaw et al., 2020)</ns0:ref>. For RNA viruses, however, critical aspects of the life cycle rely on molecular processes that are not reflected in protein sequence. In particular, in positive-strand RNA viruses such as coronaviruses, the single RNA molecule that constitutes the genome is first transcribed and translated to produce the replicase polyprotein 1a and 1ab that is cleaved into multiple non-structural proteins, some of which participate in the assembly of a cellular structure known as the replicase-transcriptase complex (RTC), where the proper environment for viral replication and transcription is created. Then, the RNA-dependent-RNA-polymerase (RdRp or Nsp12) produces negative sense genomic and subgenomic RNAs that are used as template strands that are then transcribed in the opposite direction to make more positive-sense viral genomes and a variety of RNA molecules that are translated into structural proteins for packaging <ns0:ref type='bibr' target='#b16'>(Fehr &amp; Perlman, 2015;</ns0:ref><ns0:ref type='bibr' target='#b43'>Kim et al., 2020)</ns0:ref>. Although the viral proteins that help mediate these processes are visible to tests for selection that rely on dN/dS ratios, the RNA molecules with which they interact are not. This leaves the operation of natural selection on important molecular functions within the viral life cycle largely unexamined.</ns0:p><ns0:p>In order to test for positive selection on RNA function independent of its role in coding for amino acids, we utilized a test for positive selection, adaptiPhy <ns0:ref type='bibr' target='#b6'>(Berrio, Haygood &amp; Wray, 2020)</ns0:ref>, that identifies an excess of nucleotide substitutions within a defined window in the genome relative to neutral expectation using a likelihood ratio framework <ns0:ref type='bibr' target='#b90'>(Wong &amp; Nielsen, 2004;</ns0:ref><ns0:ref type='bibr' target='#b29'>Haygood et al., 2007)</ns0:ref>. This test infers regions of the genome that were likely targets of branch-specific positive selection in several Sarbecovirus species from bat, pangolin, and human hosts. Our results recapitulate results from dN/dS-based tests that highlight S, the gene encoding Spike protein, as a prominent target of natural selection within the SARS-CoV-2 genome <ns0:ref type='bibr' target='#b9'>(Cagliani et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b11'>Chaw et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b50'>Li et al., 2020a)</ns0:ref>. Importantly, we also identify genomic regions not previously reported to be targets of positive selection. Based on structural modeling PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed of RNA and protein, we argue that these newly identified regions of positive selection may affect species-specific RNA, rather than protein, function. These genomic regions are candidates for understanding the molecular mechanisms that endow SARS-CoV-2 with some of its unique biological properties.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sequence Alignment</ns0:head><ns0:p>To identify branch specific positive selection, it is necessary to obtain a query and a reference alignment. We downloaded six high quality reference genomes from the subgenus Sarbecovirus (Table <ns0:ref type='table'>1</ns0:ref>). Next, we used MAFFT <ns0:ref type='bibr' target='#b39'>(Katoh &amp; Standley, 2013)</ns0:ref> plugin in Geneious Prime v.2.1 <ns0:ref type='bibr'>(Kearse et al., 2012)</ns0:ref> with default settings to build a sequence alignment. Next, we refined the alignment using a gene by gene procedure. More specifically, each coding sequence annotation (i.e. ORF1a, ORF1b, ORF3a, S, M, N, etc) is selected and realigned using the Realign Region tool implemented in Geneious Prime v.2.1 <ns0:ref type='bibr'>(Kearse et al., 2012)</ns0:ref> using the MAFFT <ns0:ref type='bibr' target='#b39'>(Katoh &amp; Standley, 2013)</ns0:ref> option.</ns0:p></ns0:div> <ns0:div><ns0:head>Testing for Positive Selection</ns0:head><ns0:p>Although adaptiPhy was originally designed to investigate regions of complex genomes under positive selection, it can be used to identify regions of a viral sequence alignment where the foreground branch is evolving at faster rates than the expectation from the background species.</ns0:p><ns0:p>We performed a selection analysis on sliding windows of 300 bp with a step of 150 bp along a sequence alignment of 5 reference genome sequences of coronaviruses of the subgenus Sarbecovirus and two sequences of Pangolin Coronavirus recently published <ns0:ref type='bibr' target='#b52'>(Liu, Chen &amp; Chen, 2019;</ns0:ref><ns0:ref type='bibr' target='#b7'>Lam et al., 2020)</ns0:ref>. This procedure generates partitions where a tree topology can be fitted.</ns0:p><ns0:p>To investigate the extent of positive selection or branches with long substitution rates along the SARS-CoV-2 genome, we used a branch-specific method known as adaptiPhy that was initially developed in 2007 <ns0:ref type='bibr' target='#b29'>(Haygood et al., 2007)</ns0:ref> and recently improved <ns0:ref type='bibr' target='#b6'>(Berrio, Haygood &amp; Wray, 2020)</ns0:ref>. This computational methodology makes use of a likelihood ratio test based on the maximum likelihood estimates obtained from HyPhy v2.5 <ns0:ref type='bibr' target='#b72'>(Pond, Frost &amp; Muse, 2005;</ns0:ref><ns0:ref type='bibr' target='#b74'>Pond et al., 2020)</ns0:ref>. The branch of interest (e.g., SARS-CoV-2 branch) is used as the foreground and the rest of the alignment is used as the background. To obtain data from nucleotide substitutions alone, we used msa_split from PHAST <ns0:ref type='bibr' target='#b35'>(Hubisz, Pollard &amp; Siepel, 2011)</ns0:ref> to remove insertions PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed and any sequence gaps that were present in the genomes of the background virus species relative to the SARS-CoV-2 genome. The assumption for the background species is the same for both the null and alternative models; specifically, only neutral evolution and negative (purifying) selection are permitted. While in the foreground, the assumptions are the same as for the background in the null model. In the alternative model, all three types of evolution are permitted (neutral evolution, negative selection, and positive selection) in the foreground of the following topology: (((((SARS_CoV_2, Bat_CoV_RaTG13), Pa_CoV_Guangdong), Pa_CoV_Guangxi_P4L), (Bat_CoV_LYRa11, SARS_CoV)), Bat_CoV_BM48). This method is highly sensitive and specific and can differentiate between positive selection and relaxation of constraint <ns0:ref type='bibr' target='#b6'>(Berrio et al. 2020)</ns0:ref>. AdaptiPhy requires at least 3 kb reference alignment for each species that is used as a putatively neutral proxy for computing substitution rates. Viruses' genomes lack non-functional regions, therefore, the most reasonable proxy for neutral evolution has to be found in the regions outside the query window. To do this, we concatenated twenty regions of 300 bp of the viral genome alignment that were drawn randomly with replacement from the entire genome alignment. Then, for each query alignment, we built a reference alignment of 6 kb as it produces a stable evolutionary standard of recombination rates. To control for the stochasticity of the evolutionary process, we run each query against ten bootstrapped samples of reference alignments. Finally, we used a custom R script to compute the likelihood ratio, which was used as a test statistic for a chi-squared test with one degree of freedom to calculate a P-value for each query. Then, we corrected the distribution of all P-values per query region using the p.adjust() R function with the fdr method. Next, we classified a query window to be under positive selection if the P-adjusted value was &lt; 0.05. We were unable to successfully run adaptiPhy on two windows because the outgroup species (Bat_CoV_BM48) contained a deletion of 406 bp relative to SARS-CoV-2, which spans the entire ORF8.</ns0:p><ns0:p>To visualize the strength of selection comprehensively, we computed the statistic &#950; (zeta), representing the evolutionary rate. To calculate this rate, we compared the substitution rate in the query with their respective reference alignments. The distribution of substitution rates for each branch and nodes in each query and reference sequence was calculated using phyloFit <ns0:ref type='bibr' target='#b35'>(Hubisz, Pollard &amp; Siepel, 2011)</ns0:ref>. Then, the ratio of substitution rate in the query is divided by the substitution rate in the reference. This parameter, '&#950;', is analogous to &#969; (omega), the ratio of dN/dS, where a value of &#969;&lt;1 indicates constraint or negative selection; a value of &#969;=1 indicates neutrality; and a value of &#969;&gt;1 indicates positive selection <ns0:ref type='bibr' target='#b90'>(Wong &amp; Nielsen, 2004)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Testing for Conservation</ns0:head><ns0:p>To test for conservation, we used the phastCons computational method from PHAST <ns0:ref type='bibr'>(Siepel et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b35'>Hubisz, Pollard &amp; Siepel, 2011)</ns0:ref>. To run this tool, we used the models obtained with phyloFit for the reference alignments and then, we generated an average estimate of the conserved and non-conserved states of the models with phyloBoot <ns0:ref type='bibr' target='#b35'>(Hubisz, Pollard &amp; Siepel, 2011)</ns0:ref>. Finally, we run the final analysis using phastCons on the query alignments using the previous models to generate phastCons values for each base-pair along the sequence. To plot these we took the average from each alignment and plot it using the library Gviz and Bioconductor <ns0:ref type='bibr' target='#b28'>(Hahne &amp; Ivanek, 2016)</ns0:ref> in R.</ns0:p></ns0:div> <ns0:div><ns0:head>Testing for Recombination</ns0:head><ns0:p>Inference of branch specific selection can be confounded by recombination given that a single phylogenetic tree may not explain the evolution of viruses. Recombination is common in coronaviruses <ns0:ref type='bibr' target='#b33'>(Hon et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b24'>Graham &amp; Baric, 2010;</ns0:ref><ns0:ref type='bibr' target='#b48'>Lau et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b34'>Hu et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b51'>Li et al., 2020b;</ns0:ref><ns0:ref type='bibr' target='#b7'>Lam et al., 2020)</ns0:ref> and it should be accounted for as an alternative explanation of selection at the nucleotide level. Here, we screened for evidence of recombination by estimating phylogenetic trees in sliding windows of 500 bp and a step of 150 along coronavirus alignment using RaXML-NG v0.9 <ns0:ref type='bibr' target='#b45'>(Kozlov et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Evaluating polymorphic diversity in the pandemics of 2020</ns0:head><ns0:p>We downloaded complete sequences of SARS-CoV-2 genomes from the NCBI Virus database (https://www.ncbi.nlm.nih.gov/labs/virus/vssi/#/virus?SeqType_s=Nucleotide). As of June 26, 2020, we obtained and aligned 5597 SARS-CoV-2 genomes sequenced worldwide. To align these sequences, we used MAFFT <ns0:ref type='bibr' target='#b39'>(Katoh &amp; Standley, 2013)</ns0:ref> plugin from Geneious Prime 2.1 <ns0:ref type='bibr'>(Kearse et al., 2012)</ns0:ref>, eliminating 597 sequences with the highest number of differences and ambiguities relative to the reference sequence (RefSeq: NC_045512.2), for a total of 5,000 sequences. Next, we estimated the frequency of SNP variants using the Find Variations/SNPs tool with a minimum coverage of 4,900 sequences and a minimum frequency of 0.01, to identify nucleotide variants among a subset of high quality sequenced genomes in order to evaluate ongoing evolution in the regions under positive selection.</ns0:p></ns0:div> <ns0:div><ns0:head>Analysis of RNA and Protein structures</ns0:head><ns0:p>PeerJ reviewing <ns0:ref type='table'>PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:ref> Manuscript to be reviewed</ns0:p><ns0:p>To investigate potential structural changes in Nsp4 and Nsp16 at both the RNA and protein level, we performed minimum free energy (MFE) prediction analysis using the RNAfold WebServer <ns0:ref type='bibr' target='#b25'>(Gruber et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b53'>Lorenz et al., 2011)</ns0:ref> and consensus homology modeling using PHYRE2's intensive mode <ns0:ref type='bibr' target='#b42'>(Kelley et al., 2016)</ns0:ref>. These analyses were performed for both Nsp4 and Nsp16 sequences for SARS-CoV-2, Bat-CoV_RaTG13, Pan-CoV-Guangdong, and SARS-CoV.</ns0:p><ns0:p>RNAfold uses a loop-based energy model and a dynamic programming algorithm to predict the structure of the sequence such that the free energy of the structure is minimized. The RNAfold WebServer generates graphical outputs for both the MFE and Centroid structures, which display the base pairing probabilities by color (blue = 0, red = 1). These two MFE structures correspond to the MFE and the Centroid traces in the mountain plot, which is a positional representation of the secondary structure. In our figures, we show the MFE structure prediction.</ns0:p><ns0:p>PHYRE2 aligns input protein sequences using Position-Specific Iterated BLAST (PSI-BLAST) against sequences of experimentally resolved protein structures. A 3D model of the input sequence is then constructed based on homology-matched templates, optimizing for greatest sequence coverage and highest confidence. Regions of the input sequence without a matching template sequence are modeled ab initio and with Poing, a multi-template modelling tool.</ns0:p><ns0:p>Pairwise comparisons of predicted protein structures were visualized using PyMOL software <ns0:ref type='bibr' target='#b14'>(DeLano, 2002)</ns0:ref>. Alignment and structural comparisons performed by FATCAT <ns0:ref type='bibr' target='#b93'>(Ye &amp; Godzik, 2004)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Positive and negative selection are highly localized within coronavirus genomes</ns0:head><ns0:p>We tested for branch-specific selection on nucleotide sequences in coronavirus genomes, focusing on six species from the Sarbecovirus Subgenus (Coronaviridae family) and Bat-CoV-BM48-31/BGR/2008 as an outgroup. Using 300 bp windows with a step size of 150 bp, we scanned the genome alignment for concentrations of fixed mutations that exceed the neutral expectation based on the genome as whole relative to that particular window's evolutionary history among the seven species. This test identifies regions of the genome showing the most extreme divergence in nucleotide sequence on a particular branch relative to its specific background rate of evolution across the entire phylogeny and without reference to the genetic code. Manuscript to be reviewed species and others that are recapitulated in multiple species. The latter finding suggests that some segments of the viral genome have repeatedly experienced adaptive modification. In general, the distribution of positive selection is more similar in closely related species than in divergent ones <ns0:ref type='bibr'>(Figs 1A and 1B)</ns0:ref>, suggesting that some molecular functions have been altered over an interval that extends beyond the origin of a single species but not across the entire Sarbecovirus radiation.</ns0:p><ns0:p>Next, we identified regions of the genome that are highly conserved across the Sarbecovirus genomes examined in this study using PhastCons <ns0:ref type='bibr'>(Siepel et al., 2005)</ns0:ref> (Fig <ns0:ref type='figure' target='#fig_11'>2A</ns0:ref>). As with positive selection, conservation is highly localized <ns0:ref type='bibr'>(Figs 2A and 2B)</ns0:ref>. Based on a criterion of PhastCons &gt; 0.9, we found high levels of conservation in regions encoding seven proteins: 3CL-Pro, Nsp6, Nsp8, Nsp9, Nsp10, Nsp11, RdRp, ORF3a (Protein 3a), Nucleocapsid phosphoprotein (NC), and Envelope (E) (Figs <ns0:ref type='figure' target='#fig_11'>2A-D</ns0:ref>). These loci of exceptional sequence conservation highlight critical molecular features: NC and E are essential structural proteins of the coronavirus capsid, while the other proteins regulate a variety of molecular process during viral replication <ns0:ref type='bibr' target='#b80'>(Tan et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b54'>Lu et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b61'>Minakshi et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b19'>Freundt et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b21'>Fuchs, 2012;</ns0:ref><ns0:ref type='bibr' target='#b94'>Yue et al., 2018)</ns0:ref>.</ns0:p><ns0:p>Because new mutations emerge and new strains replace older ones, we next investigated how much the specific strain used to represent SARS-CoV-2 influences test results. We re-ran the tests for positive selection using a strain of SARS-CoV-2 that contains four derived SNPs that commonly co-occur in currently circulating strains. Using this strain did not change the distribution of inferred regions of positive selection during the origin of SARS-CoV-2 (S6 Fig).</ns0:p><ns0:p>We also generated two artificial genomes where we added four and nine mutations in the vicinity of site 14,408 to test the sensitivity of the test. We found that as zeta increased within the window, the test turned significant when more than five mutations are added (S1 Fig) <ns0:ref type='figure'>.</ns0:ref> It is important to note that the exact number of mutations that produce a significant test result may differ in other regions of the genome, depending on the degree of sequence conservation among species. Manuscript to be reviewed the dN/dS ratio to test for selection on protein function <ns0:ref type='bibr' target='#b81'>(Tang et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b11'>Chaw et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b50'>Li et al., 2020a)</ns0:ref>. Interestingly, we observed that the specific regions showing signatures of positive selection differed between species (Figs <ns0:ref type='figure' target='#fig_10'>1B and 1C</ns0:ref>). In SARS-CoV-2, we detected signals of positive selection in four segments of the S gene. First, the region encoding the entire receptor binding domain (RBD) shows an extended signal (Figs 1B-C and 3A); as others have noted, structural changes in this region may improve binding to human ACE2 <ns0:ref type='bibr'>(Wang et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b91'>Wrapp et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b87'>Wang, Liu &amp; Gao, 2020)</ns0:ref>. The second segment encodes another externally facing region, the S1 subunit N-terminal (NTD) domain, which includes the first disulfide bond (amino acids 13 -113) and several glycosylation sites. The third signal of positive selection within S is located around the derived furin cleavage site (amino acids 664 -812) that has been found to be essential for infection of lung cells <ns0:ref type='bibr' target='#b32'>(Hoffmann, Kleine-Weber &amp; P&#246;hlmann, 2020)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>The gene encoding Spike protein is under persistent positive selection</ns0:head><ns0:p>The fourth signal is located in a segment encoding the S2 and S2' subunits that includes the Heptad repeat 2 (amino acids 1114 -1213). These heptad repeats were previously associated with episodes of selection for amino acids that increase the stability of the six-helix bundle formed by both heptad repeats in MERS and other coronaviruses <ns0:ref type='bibr' target='#b18'>(Forni et al., 2015)</ns0:ref>; they are also thought to determine host expansions and therefore, facilitate virus cross-species transmission <ns0:ref type='bibr' target='#b24'>(Graham &amp; Baric, 2010)</ns0:ref>.</ns0:p><ns0:p>The distribution of inferred positive selection in the S gene of SARS-CoV differed from that of SARS-CoV-2 described above. Notably, there was no signal in the ACE2 binding domain (Figs Manuscript to be reviewed Viral-Replication-Transcription Complex (RTC) to the modified endoplasmic reticulum membranes in the host cell <ns0:ref type='bibr' target='#b65'>(Oostra et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b27'>Hagemeijer et al., 2011</ns0:ref><ns0:ref type='bibr' target='#b26'>Hagemeijer et al., , 2014;;</ns0:ref><ns0:ref type='bibr' target='#b79'>Snijder, Decroly &amp; Ziebuhr, 2016)</ns0:ref>. The SARS-CoV-2 Nsp4 protein differs from that of closely related sarbecoviruses by two nearly adjacent amino acids: V380A and V382I. Although this region of the genome as a whole is not highly conserved (Fig 2 <ns0:ref type='figure'>)</ns0:ref>, both of these positions are V residues in all of the in-group species we examined except SARS-CoV-2 (Fig 3B <ns0:ref type='figure' target='#fig_11'>and S2A</ns0:ref>). This signal is too weak to be scored as positive selection using dN/dS-based tests <ns0:ref type='bibr' target='#b81'>(Tang et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b11'>Chaw et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b50'>Li et al., 2020a)</ns0:ref> and indeed may not affect protein function given the biochemically similar side-chains of the amino acids involved.</ns0:p><ns0:p>The second signal of positive selection outside of the S gene lies within Nsp16. This gene encodes a 2'-O-methyltransferase that modifies the 5'-cap of viral mRNAs <ns0:ref type='bibr' target='#b13'>(Decroly et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b8'>Bouvet et al., 2010)</ns0:ref> and assists in evasion of the innate immune system of host cells <ns0:ref type='bibr' target='#b97'>(Z&#252;st et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b60'>Menachery, Debbink &amp; Baric, 2014;</ns0:ref><ns0:ref type='bibr' target='#b64'>Nelemans &amp; Kikkert, 2019)</ns0:ref>. Of note, this is the only signal of positive selection within the SARS-CoV-2 genome that lacks any nonsynonymous substitutions (Fig 3C <ns0:ref type='figure'>)</ns0:ref>, and thus could not have been detected by any test that relies on the dN/dS ratio. All of the nucleotide substitutions in Nsp16 during the origin of SARS-CoV-2 are synonymous, while the Nsp16 genes of SARS-CoV-2, Bat-Cov-RaTG13, and Pan-CoV-GD (Guangdong) all encode identical proteins (Figs <ns0:ref type='figure'>3C and S3A</ns0:ref>). This suggests a complex mechanism of selection in the form of purifying selection at the protein level and branch-specific positive selection at the nucleotide level. Ancestral state reconstruction of Nsp16 indicates that 20 synonymous substitutions likely occurred in the lineage leading to SARS-CoV-2 after the split from the common ancestor with BatCoV-RaTG13, while 19 substitutions are synonymous substitutions that occurred in the lineage leading to Bat-CoV-RaTG13 (Supplementary Data).</ns0:p><ns0:p>Eleven of these twenty substitutions are concentrated within the region scoring high for positive selection in SARS-CoV-2 and twelve within the positively selected region in Bat-CoV-RaTG13.</ns0:p><ns0:p>As a consequence, we hypothesized that the Nsp16 RNA secondary structure may differ among species in ways that affect molecular functions mediated directly (although not solely) by RNA, such as replication, transcription, translation, or evasion of the host immune system. To investigate this possibility, we first compared the secondary structure and minimum free energy </ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>CoV-RaTG13, Pan-CoV-GD, and SARS-CoV using RNAfold <ns0:ref type='bibr' target='#b25'>(Gruber et al., 2008)</ns0:ref>. Both the predicted secondary structures and mountain plots, which show the free energy predictions along the length of the sequence by position, reveal differences in RNA folding dynamics across the four species (S2B and S3B Figs). Analysis of the reconstructed sequence of the SARS-CoV-2 + Bat-CoV-RaTG13 ancestor reveal that most of these differences evolved during the origin of SARS-CoV-2 (S4 Fig). These differences among species in predicted secondary structures within Nsp4 and Nsp16 stand in contrast to the 5' UTR, which is thought to fold into a stable secondary structure that is markedly conserved among Sarbecovirus species (S5 Fig) <ns0:ref type='figure'>.</ns0:ref> Though the accuracy of MFE predictions is too low to conclusively determine whether there are real between-species differences in the RNA structures of these loci <ns0:ref type='bibr' target='#b58'>(Mathews, 2005)</ns0:ref>, these observations suggest that the signal of positive selection within Nsp16 in the SARS-CoV-2 genome may reflect changes in RNA, rather than protein, function that are unique to this species of coronavirus.</ns0:p><ns0:p>While the focus here is on SARS-CoV-2, it is worth noting that we also detected signals of <ns0:ref type='bibr'>, 2015)</ns0:ref>, assists in the assembly of the double membrane vesicles of the RTC system <ns0:ref type='bibr' target='#b26'>(Hagemeijer et al., 2014)</ns0:ref>, and antagonizes the host innate immune response <ns0:ref type='bibr' target='#b84'>(Tsuchida, Kawai &amp; Akira, 2009;</ns0:ref><ns0:ref type='bibr' target='#b20'>Frieman et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b59'>Matthews et al., 2014)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Recombination does not account for most signals of positive selection</ns0:head><ns0:p>Recombination from another species can be a confounding factor in the inference of positive selection using the framework employed here, because the inserted genomic segment may be more divergent than the rest of the foreground genome is from nearby background species.</ns0:p></ns0:div> <ns0:div><ns0:head>Several instances of recombination have been reported in coronaviruses, including SARS-CoV-2</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed <ns0:ref type='bibr' target='#b33'>(Hon et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b7'>Lam et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b7'>Boni et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b50'>Li et al., 2020a)</ns0:ref>, making it important to distinguish regions of recombination from positive selection. The two processes produce distinct genetic signatures, with recombination the result of a single event (possibly later further recombined) and positive selection as detected here the result of multiple independent mutations that were fixed over an extended interval and are spatially concentrated. In order to test for regions of the SARS-CoV-2 that contain recombined segments from other species, we estimated the phylogenetic history of 500 bp segments of the genome with a step size of 150 bp among the aligned genomes of the seven species examined in this study. We used RaXML-NG v0.9 <ns0:ref type='bibr' target='#b45'>(Kozlov et al., 2019)</ns0:ref> to reconstruct topology for each segment independently and searched for cases where the topology differed from the expected topology based on the entire genome: (Bat-CoV-BM48, ((Bat-CoV-LYRa11, SARS-CoV), (Pa-CoV-GX, (Pa-CoV-GD, (SARS-CoV-2, Ba-CoV-RaTG13)))). Recombination from a divergent species should produce an incongruent topology in one or more adjacent windows, revealing a recombined region and its approximate breakpoints. We identified 12 regions where the topology differed from the expected (Fig <ns0:ref type='figure' target='#fig_12'>4</ns0:ref>). Of note, these regions are somewhat more concentrated in the part of the genome that encodes structural proteins. Consistent with a previous report <ns0:ref type='bibr' target='#b50'>(Li et al., 2020a)</ns0:ref>, we observed overlap between regions scoring high for positive selection and recombination in S, the gene encoding Spike protein <ns0:ref type='bibr'>(Fig 4M)</ns0:ref>, specifically the region that encodes for the ACE2 binding domain and a region that includes the furin-cleavage site ( <ns0:ref type='figure' target='#fig_12'>Figs 4F-G</ns0:ref>). Importantly, however, none of the putatively recombined regions overlap with the windows scoring high for positive selection within the genes encoding Nsp4 and Nsp16 proteins in SARS-CoV-2.</ns0:p></ns0:div> <ns0:div><ns0:head>Recent changes in allele frequency may result from positive selection and hitch-hiking</ns0:head><ns0:p>To gain insight into the evolutionary mechanisms that have shaped genetic variation more recently within the SARS-CoV-2 genome, we compiled a list of known mutations, based on 5,000 accessions sequenced since the beginning of the current pandemic (see Methods). As expected, the vast majority of variants are singletons, representing either mutations that are not </ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>We next investigated the likely consequences for altered molecular function due to each of these four high-frequency derived SNPs. Two are located within regions of the genome that are highly conserved among Sarbecovirus species (Figs <ns0:ref type='figure' target='#fig_11'>2B-C</ns0:ref>). The first is a C&gt;U substitution at position 241 in the 5'UTR, a region of the genome where RNA secondary structure is highly conserved across Coronavirus species <ns0:ref type='bibr' target='#b57'>(Madhugiri et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b75'>Rangan et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b0'>Alhatlani, 2020)</ns0:ref>. Using RNAfold <ns0:ref type='bibr' target='#b25'>(Gruber et al., 2008)</ns0:ref> we found that this C&gt;U transition had no impact on the stem-loop structure established for SARS-CoV (S5 Fig) <ns0:ref type='figure'>.</ns0:ref> The other mutation in a conserved region of the genome is a nonsynonymous substitution in the RdRp gene (14,408; P323L) at the interface domain, which is thought to mediate protein-protein interactions <ns0:ref type='bibr' target='#b66'>(Pachetti et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b31'>Hillen et al., 2020)</ns0:ref>. Because proline residues can influence secondary structure, we used PHYRE2 to predict the impact of the P232L mutation on protein structure. Comparison of the two predicted structures using FATCAT shows they are nearly identical (Table <ns0:ref type='table'>S1</ns0:ref>). The other two highfrequency derived SNPs are located in regions that are neither highly conserved nor highly divergent. One is a synonymous SNP in Nsp3 (3,037) and the other a nonsynonymous SNP in S <ns0:ref type='bibr'>(23,403; D614G)</ns0:ref>. This last SNP effectively removes a charged side-chain between the receptor binding domain and the furin cleavage site of S, a region of recurrent positive selection among the Sarbecovirus species we examined. Thus, of the four high-frequency derived SNPs, the nonsynonymous substitution in S the most plausible candidate for altering molecular function and thus becoming a target of natural selection.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>A crucial feature contributing to the global spread of COVID-19 is that viral shedding starts before the onset of symptoms <ns0:ref type='bibr' target='#b30'>(He et al., 2020)</ns0:ref>; in contrast, shedding began two to ten days after the onset of symptoms during the SARS epidemic of 2003 <ns0:ref type='bibr' target='#b68'>(Peiris et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b71'>Pitzer, Leung &amp; Lipsitch, 2007)</ns0:ref>. This striking difference suggests that one or more molecular mechanisms during host cell invasion, virus replication, or immune avoidance may have changed during the origin of SARS-CoV-2. Mutations contributing to viral transmission would likely be favored by natural selection, making tests for positive selection a useful tool for identifying candidate genetic changes responsible for the unique properties of SARS-CoV-2. Here, we searched for regions of possible positive selection within the genomes of six coronavirus species, including SARS-CoV and SARS-CoV-2. The method we used tests for an excess of branch-specific nucleotide PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed substitutions within a defined window relative to a neutral expectation for divergence in that window and without regard to the genetic code <ns0:ref type='bibr' target='#b90'>(Wong &amp; Nielsen, 2004;</ns0:ref><ns0:ref type='bibr' target='#b29'>Haygood et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b6'>Berrio, Haygood &amp; Wray, 2020)</ns0:ref>.</ns0:p><ns0:p>Several prior studies have identified S, the gene encoding the Spike glycoprotein, as a target of recurrent positive selection in coronavirus genomes, including SARS-CoV-2, based on &#969;, the ratio of synonymous to nonsynonymous substitutions <ns0:ref type='bibr' target='#b1'>(Andersen et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b9'>Cagliani et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b81'>Tang et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b3'>Armijos-Jaramillo et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b50'>Li et al., 2020a)</ns0:ref>. S thus serves as a positive control for our ability to detect signals of positive selection using a different approach, which considers mutations without respect to the genetic code and uses a likelihood ratio framework to identify regions of elevated, branch-specific nucleotide substitution rates relative to a model that allows only drift <ns0:ref type='bibr' target='#b90'>(Wong &amp; Nielsen, 2004;</ns0:ref><ns0:ref type='bibr' target='#b29'>Haygood et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b6'>Berrio, Haygood &amp; Wray, 2020)</ns0:ref>. Consistent with this expectation, we found that portions of the gene encoding Spike showed a striking elevation of sequence divergence relative to the rest of the genome on the branches leading to all six species examined. The specific regions of S containing high divergence differs markedly, however, among species <ns0:ref type='bibr'>(Fig 1B)</ns0:ref>. In SARS-CoV and Bat-CoV-LYRa11, these regions include the N-terminal region, which contains glycosylation sites important for viral camouflage <ns0:ref type='bibr' target='#b89'>(Watanabe et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b92'>Yang et al., 2020)</ns0:ref> and a site of proteolytic cleavage that allows entry into the host cell <ns0:ref type='bibr' target='#b5'>(Belouzard, Chu &amp; Whittaker, 2009)</ns0:ref> For coronaviruses this is a notable limitation, given that many aspects of the lifecycle involve RNA function <ns0:ref type='bibr' target='#b57'>(Madhugiri et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b96'>Ziv et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b0'>Alhatlani, 2020)</ns0:ref>. In addition, the secondary structure of some segments within the RNA genome is well conserved among coronavirus species, which implies a functional role <ns0:ref type='bibr' target='#b75'>(Rangan et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b76'>Sanders et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b37'>Huston et al., 2020a)</ns0:ref>. Indeed, the SARS-CoV-2 genome is reported to contain more wellstructured regions than any other known virus, including both coding and noncoding regions of the genome <ns0:ref type='bibr' target='#b37'>(Huston et al., 2020a)</ns0:ref>. We therefore examined nucleotide substitutions within regions of putative positive selection in Nsp4 and Nsp16 for their likely impact on both protein and RNA structure (S2 and S3 Figs).</ns0:p><ns0:p>In the case of Nsp4 protein, two nearly adjacent nonsynonymous substitutions at residues 380 and 382 occurred on the branch leading to SARS-CoV-2 (Fig <ns0:ref type='figure'>3B</ns0:ref>). These both involve changing side chains with similar biochemical properties, respectively valine to alanine and valine to isoleucine. Homology-directed modeling of protein structure suggests that these two amino acid substitutions have very little impact on either secondary or tertiary structure when comparing the SARS-CoV-2 protein orthologue to those of the other species examined (S2A Fig) <ns0:ref type='figure'>.</ns0:ref> In the case of Nsp16 protein, no nonsynonymous substitutions evolved on the branch leading to SARS-CoV-2.</ns0:p><ns0:p>Thus, the signal of positive selection within Nsp4 is unlikely to reflect changes in protein structure or function, while the signal within Nsp16 cannot affect either because the encoded polypeptide is identical <ns0:ref type='bibr'>(Fig 3C and S3A Fig)</ns0:ref>.</ns0:p><ns0:p>With highly similar and identical protein structures predicted for Nsp4 and Nsp16, respectively, we considered the possibility that the signals of positive selection instead reflect changes in RNA structure and function. Previous studies found that neither the Nsp4 nor Nsp16 regions stand out as particularly well folded regions of the genome, although Nsp16 does contain a single wellfolded region and Nsp4 two moderately well folded regions <ns0:ref type='bibr' target='#b75'>(Rangan et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b38'>Huston et al., 2020b)</ns0:ref>. Further, both genes show significantly decreased sequence divergence among coronavirus species within predicted double-stranded region <ns0:ref type='bibr' target='#b75'>(Rangan et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b76'>Sanders et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b37'>Huston et al., 2020a)</ns0:ref>. Indeed, the well-folded region within Nsp16 is the only such region in the SARS-CoV-2 genome that is also well conserved among related coronaviruses <ns0:ref type='bibr' target='#b76'>(Sanders et al., 2020)</ns0:ref>. These published observations suggest possible functional roles for folded structures within Nsp4 and Nsp16. While we have not taken a robust experimental approach to determine Unfortunately, little is currently known about the molecular functions of secondary structures in coronavirus genomes. Most of the attention has been directed towards the 5' UTR, 3' UTR, and frameshift element at the junction between ORF1a and ORF1b, which together contain the most well-folded regions in the SARS-CoV-2 genome <ns0:ref type='bibr'>(Andrews et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b76'>Sanders et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b37'>Huston et al., 2020a)</ns0:ref>. Thus, it is not possible at this time to link structural and thermodynamic features within Nsp4 and Nsp16 that are unique to SARS-CoV-2 to specific molecular functions.</ns0:p><ns0:p>As discussed above, however, published evidence suggests that RNA secondary structures within these regions of the genome may be functional <ns0:ref type='bibr' target='#b75'>(Rangan et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b76'>Sanders et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b37'>Huston et al., 2020a)</ns0:ref>. These functions could, in principle, affect genome or transcript function, or both.</ns0:p><ns0:p>Plausible possibilities include secondary structures that recruit specific RNA-binding proteins to mediate transcriptional regulation or transcript processing <ns0:ref type='bibr' target='#b69'>(Pirakitikulr et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b67'>Pan et al., 2020)</ns0:ref>, that mediate looping for other reasons <ns0:ref type='bibr' target='#b23'>(Gebhard, Filomatori &amp; Gamarnik, 2011;</ns0:ref><ns0:ref type='bibr' target='#b96'>Ziv et al., 2020)</ns0:ref>, or that simply facilitate or impede processivity of the replication or translation machinery <ns0:ref type='bibr' target='#b56'>(MacFadden et al., 2018)</ns0:ref>.</ns0:p><ns0:p>To investigate what evolutionary mechanisms are shaping the genetic variation at the population level, we examined known mutations among 5,000 accessions from NCBI. Given that the effective population size of SARS-CoV-2 is likely very large, the alternative allele distribution Manuscript to be reviewed et al., 2020), which suggests that positive selection on one of them may have driven the other three to high frequency due to hitch-hiking. Based on molecular modeling, the high-frequency derived mutation in S is the most plausible to be under positive selection, while the other three may be elevated due to hitch-hiking.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Scans for positive selection typically focus on changes in protein function and far less often consider the possibility of adaptive change in RNA function. By shining a light on regions of the SARS-CoV-2 genome that appear to be under positive selection yet are unlikely to alter protein function, our results illustrate the value of evaluating the potential for adaptive changes in secondary structures within the genomes of RNA viruses. In particular, we identify Nsp4 and Nsp16 as regions of the SARS-Cov-2 genome that may contain mutations that contribute to the unique biological and epidemiological features of this recently emerged pathogen.</ns0:p><ns0:p>While it is tempting to speculate about the possible adaptive role of changes in RNA structure within these accelerated regions, we suggest that this is best done in the context of relevant experimental results. For example, it might be informative to modify the primary sequence of the genome so as to encode the same protein sequence while altering or disrupting secondary structure within Nsp4 or Nsp16, then assay the consequences for viral replication and for specific molecular functions. We hope that our results inspire these or other experiments aimed at better understand the evolving functions of RNA secondary structure within the SARS-CoV-2 genome. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Fig 1A shows windows of inferred positive selection (red dots) on the branch leading to each species. The results reveal several signals of positive selection that are unique to a single PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>In all ingroup species examined we detected signals of positive selection within the S gene, which encodes the Spike protein. With the exception of Pa-CoV-Gx, this was the most prominent signal in the entire genome (Fig 1A). This finding confirms previous studies that used PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>1B and 1C). Moreover, a signal was present throughout the N-terminal domain and in the boundary region between the S1 and the S2 subunits (Fig 1), a region that includes the proteolytic cleavage<ns0:ref type='bibr' target='#b55'>(M de Haan et al., 2004)</ns0:ref>. Interestingly, this region evolved a novel furin cleavage site in SARS-CoV-2 that may increase the cleavage efficiency and cell-cell fusion activity and changes in the virulence of the virion as seen in mutant studies of SARS-CoV and SARS-CoV-2<ns0:ref type='bibr' target='#b17'>(Follis, York &amp; Nunberg, 2006;</ns0:ref><ns0:ref type='bibr' target='#b32'>Hoffmann, Kleine-Weber &amp; P&#246;hlmann, 2020)</ns0:ref>.Genes encoding Nsp4 and Nsp16 contain branch-specific signals of positive selectionWe also detected two shorter signals of positive selection within the SARS-CoV-2 genome that are located outside of the S gene, in pp1ab and pp1a(Fig 1A). Interestingly, both encode small proteins that contribute to viral replication. The first is Nsp4, which encodes a membrane-bound protein with a cytoplasmic C-terminal domain; it is thought to anchor the PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>MFE) of RNA in the vicinity of Nsp4 and Nsp16 among the genomes of SARS-CoV-2, Bat-PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>positive selection outside of the S gene in the other Sarbecovirus genomes examined here. The distribution of positive selection in the genome of SARS-CoV, for instance, shows some similarities to, but also notable differences from, that of SARS-Cov-2 (Fig 1). In both species, S and Nsp16 contain signals of positive selection, although in distinct regions of the two genes (Fig 1). In addition, the genome of SARS-CoV contains signals of positive selection in Nsp2, Nsp3, and ORF3a, none of which shows elevated rates of substitution in SARS-CoV-2. The first two genes encode proteins with important roles in viral replication: Nsp2 may disrupt intracellular signaling in the host cell (Cornillez-Ty et al., 2009) while Nsp3 cleaves itself, Nsp1, and Nsp2 from the replicase polyproteins (B&#225;ez-Santos, St. John &amp; Mesecar</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>segregating or sequencing errors. The density distribution of polymorphisms (regardless of frequency) is elevated within 2-3 kb at both ends the SARS-CoV-2 genome (Fig 2D) and the site-frequency spectrum is strongly left-skewed (S6 Fig).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>(Fig 1C and 3A). In contrast, signals of positive selection in SARS-CoV-2 and Bat-CoV-RaTG13 are concentrated in the domain that mediates binding to the host receptor ACE2 (Fig 1C and 3A). These distinct distributions suggest that modifications in different aspects of Spike function took place as various coronaviruses adapted to novel hosts. In particular, the concentration of derived amino acid substitutions in the receptor binding domain of Spike (Figs 1B and 1C) in SARS-CoV-2 and Bat-CoV-RaTG13 may reflect selection for amino acid substitutions that result in higher affinity for ACE2 protein in different host species. Importantly, we also detected signals of positive selection in two additional regions of the SARS-CoV-2 genome, specifically within the genes encoding Nsp4 and Nsp16 (Figs 1A and 2A). Of note, the Nsp16 region also shows a parallel signal of positive selection on the branch leading to SARS-CoV. To our knowledge, this is the first report of possible adaptive change in molecular function during the evolutionary origin of SARS-CoV-2 outside of the gene encoding Spike protein. Prior scans for positive selection within the SARS-CoV-2 genome used elevated &#969; as the signal of positive selection, which restricts attention to positive selection based on changes in protein function.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)Manuscript to be reviewed between-species differences in RNA secondary structure, our in silico minimum free energy(MFE) predictions suggest that the likely secondary structure of the RNA genome in the region of the Nsp4 and Nsp16 genes may differ among the six coronavirus species we examined (S2B and S2B Figs, top rows). The MFE predictions also indicate differences among species in entropy across the regions containing the signals of positive selection, indicating possible differences in the stability of the folded molecule (S2B and S3B Figs, bottom rows). Together, these results indicate that the folded regions of Nsp4 and Nsp16 in the SARS-Cov-2 genome may differ in shape from those of related coronaviruses.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>S6 Fig) suggests that most SNPs are not subject to positive selection and that negative selection prevents most new mutations from rising in frequency due to drift, although this may change as additional whole genomes are examined. However, we did observe four SNPs that are present at high alternative allele frequency (AAF &gt; 0.6) (Fig 2C), a situation that can reflect positive selection, drift, or hitch-hiking. Interestingly, all four of these SNPs are in tight LD (Toyoshima PeerJ reviewing PDF | (2020:09:52881:1:1:NEW 1 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> </ns0:body> "

"The Department of Biology Duke University Box 90338 Durham, NC, USA 27708 9/30/2020 Dear Dr. Orlov, Attached is a revision of manuscript (#2020:09:52881:0:1:REVIEW), entitled, 'Positive selection within the genomes of SARS-CoV-2 and other Coronaviruses independent of impact on protein function' submitted to PeerJ. We appreciate the constructive and insightful feedback that the reviewers provided. Both reviewers were excited by our analysis but also raised several significant questions. In particular, reviewer 1 suggested to make a clear distinction of the superiority of our method and PAML, while Reviewer 2 suggested to tone down our conclusions regarding the RNAfold predictions. We provide point-by-point responses to each of the concerns raised by the reviewers. We hope that the changes we have made in response have considerably strengthened our submission and address the concerns raised by both reviewers and the editor. Sincerely, Alejandro Berrio Telephone: 919-660-7372, Fax: 919-660-7293 www.biology.duke.edu Below we include the reviewer’s original comments in plain text and our responses in blue italics. --- Editor comments (Yuriy Orlov) MINOR REVISIONS Two reviewers suggest minor revision mainly on text presentation. I worry about the limited data used for analysis. New full genome sequences for SARS-CoV-2 coming recently increasing the statistical base for analysis. Please during revision ensure the result on selection remains the same taking into account new sequences or tone down your conclusion. Thank you for raising this concern. For the between-species comparisons, we used all of the available full genome reference sequences of closely related species to SARS-CoV-2 that we are aware of. Where we did not use all of the available full genome sequences was for the population analysis of SARS-CoV-2. However, this is a minor part of the study and none of our main conclusions come from those analyses. We therefore followed the suggestion to tone down the conclusion of this section by adding a caveat at line 487. Reviewer 1 (Ranajit Das) Basic reporting Overall the manuscript is very well written, clear and easy to understand. The manuscript, when published, will definitely greatly aid in the ongoing research pertaining to the evolution and adaptability of SARS-CoV-2. However, I felt that the authors could have included more references in the manuscript, especially in the Introduction section. Also, some sentences are long and could have been broken into two to improve understanding. Thank you we appreciate the positive and constructive feedback Experimental design The method section is very well written with sufficient details. One query that I have is branch-specific dN/dS implemented in PAML package can also perform selection tests. It is unclear to me why the authors did not use this popular package. The authors should clearly mention the technical and biological superiority of their method over more commonly used Branch-specific dN/dS approach implemented in PAML. This is an important point, and we apologize for not making the choice of method clearer. PAML is indeed the 'industry standard' for dN/dS tests. However, dN/dS approaches cannot test for positive selection on functions mediated *directly* by RNA due to the lack of a genetic code to classify substitutions as synonymous or nonsynonymous. To test for positive selection on RNA function requires a method that does not rely on the genetic code. We developed adaptiPhy precisely for this purpose. We have added text to the Introduction (line 84) to clarify this point. We hope that this new text, coming directly after the existing text on lines 79-82, will now make the point more clearly. We also added clarification in the Results (lines 293-294) and Discussion (line 463). Validity of the findings The data are robust and statistically sound. All conclusions are well stated and linked to the original research questions. Comments for the Author 1. The first paragraph of the Introduction section should have a reference. Done, we added two references to this paragraph 2. Lines 63-64: 'A single nucleotide polymorphism (SNP)...' - Mention the nucleotide and amino acid substitution related to this SNP Done 3. Line 85: 'Here we utilize a test for positive selection...' - Is there a name for this test? If so, can you mention it here and describe why it is superior to other similar tests? Done, we modified this line and the following in order to name and reference adaptiPhy in line 84 through 88. 4. Line 104: Please elaborate the gene by gene alignment procedure We elaborated and provided an additional sentence explaining this specific procedure 5. Lines 147-152: Can you compare and contrast Zeta obtained from PhyloFit with Omega, generated in brach-specific dN/dS implemented in PAML? Indeed, the parameter “ζ” (zeta) is analogous to ω (omega), the ratio of dN/dS, where a value of ω<1 indicates constraint or negative selection; a value of ω=1 indicates neutrality; and a value of ω>1 indicates positive selection (Wong & Nielsen, 2004). We rewrote this paragraph for highlighting the fact that zeta is analogous to omega and how is calculated. 6. Line 223: I could not find Protein 3a annotated in Fig. 2. Is it annotated in a different name? Indeed, here we also used annotations from USCIS browser which had a different name some of the genes. Protein 3a actually corresponds to ORF3a and we made changes in the text for consistency 7. Lines 230-233: Fig. 1A- For human SARS-CoV2, the signal of positive selection is not as prominent as in bats and pangolin. I would call it an intermediate signal between Pa-CoV-Gx and human SARS-CoV. Then how can you call it a 'prominent' signal? This is indeed an important point, by comparing the signal in spike across viruses, the signal for SARS-CoV-2 is not as prominent as in Bat-CoV-RaTG13, Pa-CoV-GD and SARS-CoV. Here we are looking to describe the signal of selection within each of the species considered. In this case, the signal in spike for SARS-CoV-2 is the highest relative to the remainder of its genome. We slightly modified this sentence to clarify this point. 8. From Fig. 1B it seems like the fourth signal near C-terminal domain is unique to SARS-CoV2. Is that true? If so, can you discuss the potential reason(s)? Certainly, that is true. We discussed reasons for this in line 260-264, this region contains the Heptad repeat 2 which has been found to be associated with increased the stability in MERS and it can facilitate cross species transmission (Forni et al., 2015; Graham & Baric, 2010). 9. Please annotate the ACE2 binding domain in Fig. 1B and IC Done 10. Please annotate and demarcate ORF1a and ORF1b clearly in Fig. 1A ORF1a and ORF1b correspond to pp1a and pp1ab. For consistency, we changed these annotation names within the text. 11. Lines 275-277: 'Of note, this is the only...non-synonymous substitutions' - It is unclear to me if there is no non-synonymous substitution, then how did you conclude it to be a signal of positive selection? Please explain. This question is related to earlier comment regarding the use of PAML and dN/dS ratios to test for positive selection. The approach we used does not rely on classifying mutations as synonymous vs nonsynonymous. We hope that this point has now been clarified in the Introduction (see earlier response). In addition, we made a clarification here (lines 293-294). The point we are making here is that mutation might alter RNA function without altering the function of a protein encoded by that region of the genome. In other words, a synonymous substitution could still alter RNA function. 12. Lines 279-281: 'This suggests a complex...positive selection at the nucleotide level' - How is this possible? Please explain this. Indeed, this is a very complex scenario, and perhaps rarely seen. To explain – consider a hypothetical protein sequence that is highly conserved and has no changes across multiple species (which is seen in cases of purifying selection). Because we know that mutations occur at a fixed rate in the genome, it is expected that after some time, these mutations will accumulate and eventually change the amino acid sequences of a protein. Purifying selection prevents changes at the protein level from increasing in frequency in the population, and only synonymous substitutions will be allowed at this locus. In the case described in this paper, we see not only an accumulation of these synonymous mutations in the nucleotide sequence in Nsp4 and Nps16 for SARS-CoV-2, but more synonymous mutations than we would expect given the background mutation rate in the rest of the genome. So it appears selection is acting on these loci even though there are no structural changes at the protein level. 13. Please avoid using adjectives such as 'Surprised'. Good point, we rephrased this sentence to avoid the use of this adjective 14. Line 352: 'However, we did observe four SNPs...' - Please highlight these SNPs in Fig. 2C. By eyeballing, at least two of these SNPs does not seem to have AAF>0.6. We highlighted these SNPs and added a dashed line at AAF = 0.6 to label this arbitrary threshold. 15. Also, two of these SNPs lie within areas with signals of strong purifying selection. It is unclear to me how hitchhiking is possible for these SNPs. Hitchhiking, by definition can operate on neutral sites or sites with slight negative selection. Please explain with references. We partially discuss this point in the results section. In order to improve point in the discussion, we moved a paragraph from the results section to the discussion and added some discussion and references. Reviewer 2 (Anonymous) Basic reporting The manuscript is excellently written - really well done. Thank you we appreciate the positive feedback Experimental design One small question on the stability of predictions - more below in the General Comments. Validity of the findings One concern about the validity of the RNAfold predictions - more information in the General Comments Comments for the Author This manuscript reports the use of a new analysis method to identify selection pressures on the evolution of coronavirus genomes that recapitulates and enriches-upon/complements other results from protein-centered approaches. This is a well-crafted study (and extremely well-written manuscript) that provides interesting results that focus on evolutionary pressures that shape the RNA molecules comprising the viral genomic material. By focusing on features other than protein coding potential, the authors unlock insights into other aspects of coronavirus biology: e.g. functional RNA secondary structure. The results, particularly the identification and clustering of sites of positive and purifying selection, are of immense importance to the community and would make this a valuable contribution when published. The implications of RNA structure are absolutely worth discussing, however, the analyses of secondary structure presented here are (I believe) too speculative/preliminary for inclusion as a published Result. Thanks so much. We have toned down the results in regards of the RNA structure to note that they are speculative. We still discuss these results and therefore we reference them in the supplement. Major Points: 1) As a non-specialist, it seems surprising that significant evolutionary pressures can be identified with an analysis of an alignment with so few genome sequences. Apologies if I missed this in the manuscript, but, it would be good to have an idea of how robust the identified sites are. For example, if you select different sequences from the same species (with some internal variation) to include in the analysis, would the results be the same: i.e. how volatile would the results be for resampled sequences? Indeed, this is a great question. Within-species tests for selection generally require much larger numbers. However, between-species tests for selection use different signals of selection and are often carried out with as few as 3-5 species. Regarding the choice of different sequences from within the same species, you make a very good point. During the preparation of this work we used at least three different strains, one of which contained all four mutations in strong LD that was later found to be the strain with D614G mutation; we found no differences in the distribution of positive selection when different strains were used to represent SARS-CoV-2. In order to demonstrate the consistency of our results, we did an additional analysis were we added mutations around the mutation at SNP 14,408 (figure below). Since our test detects over-substitution within a specific window, we don’t expect our results to change unless a specific strain of SARS-CoV-2 contain an excess of substitutions (more than five) around a specific window (line 232-242) 2) There are two analyses of conserved/functional RNA structural motifs available for SARS-CoV-2: described in the Rangan et al paper, and in the preprint from Andrews et al, both cited in the manuscript. The sites of unusual selection identified in SARS-CoV-2 that were identified could be cross-referenced to structural motifs identified in these studies and that are available from the Das or Moss labs, respectively. For the Andrews, et al dataset, for example, selection sites can be loaded as a track on the RNAStructuromeDB SARS-CoV-2 genome (https://structurome.bb.iastate.edu/sars-cov-2) to aid in the analysis. Indeed, the RNAStructuromeDB SARS-CoV-2 genome data is very promising and it can aid in our analysis as long as they have comparative results. Unfortunately, the Structurome is only focusing in SARS-CoV-2 data. We hope that our work would encourage those efforts. 3) The results based off of the RNAfold predictions (e.g. lines 361-363 and 448-455) are not robust enough for making conclusions about potential structural differences between viruses. Minimum free energy predictions can be extremely volatile and may vary wildly based on the sequence length selected for inclusion. Importantly, they are also sensitive to even small sequence variations. For RNAs < ~700 nt RNAfold is expected to predict ~70% of base pairs correctly for an average RNA – but this value can vary greatly depending on the target. If the authors want to perform a rigorous analysis of RNA structure they can attempt to use the available biochemical and in silico structural results for the S region to build a model for this domain of SARS-CoV-2 and attempt to predict the effect of variations in sequence with respect to this model. While interesting, however, I would recommend potentially removing these analyses from the Results section but to discuss the potential roles of RNA structure in these processes in the Discussion, which is already done. I’d not delay the publication of this paper for these analyses, but perhaps include them in a follow-up publication. To address reviewer concerns about the robustness of our in silico RNA structure prediction results, we have toned down the conclusions we draw from the MFE predictions and moved these results to supplementary information. We agree that in vivo experiments like those performed by Huston, et. al are ideal for studying between-species differences in RNA structure, and we hope our preliminary in silico results provide justification for future avenues of study on this topic. Minor Points: Line 107: This sentence would flow better if 'Despite' was replaced with 'Although”. Done "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Research on the gut microbiome of host organisms has rapidly advanced with next generation sequencing (NGS) and high-performance computing capabilities. Nonetheless, gut microbiome research has focused on mammalian organisms in laboratory settings, and investigations pertaining to wild fish gut microbiota remain in their infancy. We applied a procedure (available at https://github.com/bngallo1994to be released upon publication) for sampling of the fish gut for use in NGS to describe microbial community structure. Our approach allowed for high bacterial OTU diversity coverage (&gt;99.7%, Good's Coverage) that led to detection of differences in gut microbiota of an invasive (Round Goby) and native (Yellow Bullhead) collected from the upper St. Lawrence River, an environment where the gut microbiota of fish had not previously been tested. Additionally, results revealed habitat level differences in in gut microbiota using two distance metrics (Unifrac, Bray-Curtis) between nearshore littoral and offshore profundal collections of Round Goby.</ns0:p><ns0:p>Species and habitat level differences in intestinal microbiota may be of importance in understanding individual and species variation and its importance in regulating fish health and physiology.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Bacterial communities inhabiting the alimentary canal of organisms, often referred to as the host's 'gut microbiome', have become a focal area of research over the last decade <ns0:ref type='bibr'>(Gallo et al. 2020)</ns0:ref>. Studies show that gut microbiota can greatly influence host growth and development <ns0:ref type='bibr' target='#b39'>(Lozupone et al. 2012)</ns0:ref>, behavior <ns0:ref type='bibr' target='#b28'>(Johnson and Foster 2018)</ns0:ref>, and immune system function <ns0:ref type='bibr' target='#b10'>(Colombo et al. 2015)</ns0:ref>. To date, the majority of gut microbiome research has focused on mammals as model organisms for understanding vertebrate microbial communities <ns0:ref type='bibr'>(Sullam et al. 2012)</ns0:ref>. Mammals though, comprise a relatively small proportion of the total vertebrate diversity, whereas fish represent ~50% <ns0:ref type='bibr'>(Sullam et al. 2012)</ns0:ref>. Nonetheless, little is known surrounding the ecology of host-borne microbes in fish, particularly what factors drive patterns of bacterial colonization and community assemblage <ns0:ref type='bibr' target='#b67'>(Tarnecki et al. 2017)</ns0:ref>. Because an organism's gut microbiome can influence many aspects of host physiology, describing the relative abundance of various microbes is an important first step in delineating organism and/or communities that either benefit or harm the host.</ns0:p><ns0:p>Several factors are known to modulate gut microbiota composition in fishes, including host species/genetics <ns0:ref type='bibr' target='#b36'>(Li et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b32'>Li et al. 2014)</ns0:ref>, feeding habits <ns0:ref type='bibr' target='#b44'>(Michl et al. 2017)</ns0:ref>, trophic levels <ns0:ref type='bibr' target='#b37'>(Liu et al. 2016)</ns0:ref>, disease prevalence in the host population <ns0:ref type='bibr'>(Hennersdorf et al. 2016)</ns0:ref>, and environmental variables including habitat and husbandry practices <ns0:ref type='bibr' target='#b13'>(Dehler et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b71'>Wu et al. 2012)</ns0:ref>. Recent research on euryhaline fish has indicated that habitat salinity also plays a significant role influencing the dominant gut microbiota <ns0:ref type='bibr' target='#b60'>(Schmidt et al. 2015)</ns0:ref>. Additionally, laboratory studies investigating the gut microbiota of Zebrafish Danio rerio demonstrate taxonomic similarities despite being raised in different aquaculture facilities <ns0:ref type='bibr'>(Roeselers et al. 2011</ns0:ref>). However, Zebrafish gut microbiota was also shown to differ temporally during ontogeny, highlighting the dynamic nature of gut-borne microbial communities <ns0:ref type='bibr'>(Stephens et al. 2016</ns0:ref>).</ns0:p><ns0:p>Additional research is warranted to understand how gut microbial communities develop in nature in order to elucidate the beneficial and deleterious interactions between gut microbes and fish host.</ns0:p><ns0:p>The objective of this study was to adapt a mammalian-based gut microbiome sampling and sequencing protocol to explore the gut microbiota from two fish species from the upper St.</ns0:p><ns0:p>Lawrence River. We collected fish mucosal digesta to test for differences in the autochthonous gut microbiome of Round Goby (Neogobius melanostomus) and Yellow Bullhead (Ameiurus natalis). Yellow Bullhead, a native species to the upper St. Lawrence River, consumes small fish and crustaceans <ns0:ref type='bibr' target='#b61'>(Stegemann 1989</ns0:ref>) whereas the invasive Round Goby diet is often dominated by invasive Zebra Mussels Dreissena polymorpha <ns0:ref type='bibr' target='#b52'>(Ray and Corkum 1997)</ns0:ref>. Furthermore, Round Goby generally prefer hard substrate in both shallow and deepwater habitats <ns0:ref type='bibr' target='#b9'>(Charlebois et al. 2001)</ns0:ref> while Yellow Bullhead prefer soft substrates in vegetated areas of shallow lakes, reservoirs, and streams <ns0:ref type='bibr' target='#b61'>(Stegemann 1989</ns0:ref>). These diet and habitat differences, in addition to known interspecies variation in fish gut microbiota <ns0:ref type='bibr' target='#b36'>(Li et al. 2012</ns0:ref>) provide a scenario for testing expected differences with the NGS workflow.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head><ns0:p>Data Collection &amp; Field Processing. -Collection of fish took place on the upper St. Lawrence River and its tributaries in Clayton, NY (Fig. <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>). All specimens were collected through volunteer angling, baited minnow traps, or fine mesh hoopnets. Capture date, total length (mm), and total weight (g) were recorded for each captured fish (Supplementary Table <ns0:ref type='table'>S1</ns0:ref>). Euthanasia of animals followed approved protocols outlined by the American Veterinary Association (AVMA) and the American Fisheries Society (AFS) through an overdose of Tricaine methansulfonate (400+ mg/L) or blunt cranial concussion (State University of New York College of Environmental Science and Forestry's Institutional Animal Care and Use Committee protocol #180202). All fish were euthanized within approximately 3 hours of capture, and minnow traps / hoopnets were allowed to soak for a maximum of 18-24 hours. Fish gut microbiota comparisons involved eight Round Goby captured at Governors Island (shallow littoral: &lt;2m water depth) and seven Round Goby at the Eagle Wings Islands (deepwater profundal: &gt;15m water depth). Seven Yellow Bullhead were also sampled in French Creek (coastal wetland tributary: &lt;1m water depth). Round Goby samples from the two separate habitats (Governors Island and Eagle Wings Islands) were combined for inter-species gut microbiota analysis but analyzed separately when testing for inter-habitat gut microbiota associations.</ns0:p><ns0:p>After euthanasia, the integument of each fish was surface sterilized by rinsing in a bath of 95% ethanol prior to dissection. All sample collection methods took place at room temperature (~ 20&#730;C). Fish were dissected with a posterior incision near the pectoral fin origin to the urogenital opening. Approximately 25 mg of hindgut tissue was aseptically removed from each fish using flame-sterilized dissecting scissors and/or scalpels. Digesta was manually cleared from the intestinal tract. Samples were then gently washed with a stream of sterile 0.05M phosphatebuffered saline (PBS) removing residual digesta while leaving autochthonous bacteria in the hindgut. All samples were stored in 1.75 mL of nucleic acid preservation buffer (NAP; 0.019 M ethylenediaminetetraacetic acid (EDTA) disodium salt dihydrate, 0.018 M sodium citrate trisodium salt dehydrate, 3.8 M ammonium sulfate, pH 5.2) allowing for ambient room temperature storage in sterile 2.0 mL microcentrifuge tubes <ns0:ref type='bibr' target='#b6'>(Camacho-Sanchez et al. 2013)</ns0:ref>.</ns0:p><ns0:p>Samples were stored for 4-8 weeks prior to DNA extraction. Previous examination of NAP buffer showed similar, if not superior, bacterial DNA preservation compared to commonly employed commercial buffers in comparative microbiome analyses <ns0:ref type='bibr' target='#b43'>(Menke et al. 2017)</ns0:ref>.</ns0:p><ns0:p>Laboratory Processing.-DNA was extracted using the E.Z.N.A &#174; Tissue DNA Kit (Omega Bio-Tek, Norcross, GA) following the manufacturers protocol, except that an overnight (15-17 hours) tissue lysis step was employed to assist in complete intestinal tissue digestion. Extracted DNA was stored at -20&#730;C until PCR was performed. To selectively amplify bacterial DNA PeerJ reviewing PDF | (2020:02:45747:1:1:NEW 1 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed extracted from the hindgut samples, PCR was conducted using 16S V6-V8 rRNA primers (B969F and BA1406R <ns0:ref type='bibr' target='#b11'>(Comeau et al. 2011)</ns0:ref>; Integrated DNA Technologies, Coralville, Iowa 52241) fused with unique barcodes and Illumina&#174; adapter sequences. Employing this method (primers fused with NGS barcodes and adaptor sequences) resulted in significant cost savings and eliminated further sample processing and amplification steps (see <ns0:ref type='bibr' target='#b12'>Comeau et al. 2017)</ns0:ref>. The PCR master mix was created following <ns0:ref type='bibr' target='#b12'>Comeau et al. (2017)</ns0:ref> with the slight modification of using Q5&#174; High-Fidelity Taq polymerase (New England Biolabs, Ipswich, MA 01938). The PCR cycling protocol was as follows: initial denaturation of 95&#730;C for 30 seconds, followed by 35 cycles of 95&#730;C for 30 seconds, 55&#730;C for 30 seconds, 72&#730;C for 30 seconds, and a final extension step of 72&#730;C for 5 minutes. PCR amplicons (~600 bp) were verified by gel electrophoresis on a 2% agarose gel. Amplicon cleanup and NGS preparation took place using the Agencourt AMPure XP PCR purification kit (Agencourt Biosciences, Beverly, MA) and following manufacturer's protocol. NGS libraries were quantified via the Quant-iT dsDNA HS Assay (Invitrogen, Carlsbad, CA) following the assay's standard protocol. Fluorescence was read on a Biotek&#174; Synergy 2 plate reader (Agilent Technologies, Santa Clara, CA) and samples were subsequently converted from ng*&#181;l -1 to nM. The NGS library was diluted to a final concentration of 4nM and the normalized libraries were pooled. For loading on the sequencer, 5&#181;l of the library pool was added to 5&#181;l freshly prepared 0.2M sodium hydroxide, mixed well, and incubated at ambient temperature for 5 minutes. This was followed by an addition of 990&#181;l of pre-chilled Illumina&#174; HT1 buffer, creating a final 20pM library concentration. The prepared library was sequenced on an Illumina&#174; MiSeq TM (San Diego, CA) using 2x300 v3 chemistry and a 10% PhiX spike at the SUNY Molecular Analysis Core (SUNYMAC) at SUNY Upstate Medical University (http://www.upstate.edu/sunymac/).</ns0:p><ns0:p>Dataset organization for Analyses.-For all described analyses, Round Goby and Yellow Bullhead samples were organized into two distinct datasets: (1) gut microbiota vs. fish species (15 Round Goby vs. 7 Yellow Bullhead) and (2) gut microbiota vs. fish habitat (7 Eagle Wings Islands Round Goby vs. 8 Governors Island Round Goby). All quality filtering, OTU clustering, and multivariate comparison procedures were identical between group analyses.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:02:45747:1:1:NEW 1 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed Sequenced Data Processing and Analysis. -Raw reads have been deposited with links to BioProject accession number PRJNA528762 in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/). Sequenced libraries were demultiplexed in MiSeq TM Reporter v2.6 and FASTQ files were processed using USEARCH v.11.0.667 <ns0:ref type='bibr' target='#b14'>(Edgar 2013)</ns0:ref>.</ns0:p><ns0:p>FASTQ sequences were stitched and filtered to the approximate size of the V6-V8 region of the bacterial 16S rRNA gene (400-600 bp length; <ns0:ref type='bibr' target='#b12'>Comeau et. al 2017)</ns0:ref>. USEARCH was used to trim primer regions and remove chimeric and low-quality sequences. Next, reads were merged based on similarity (400-600 bp in length, had &#8804;5 nucleotide differences, and were &#8805;90% similar).</ns0:p><ns0:p>Sequences were filtered with the maximum expected errors per sequence &#8804;0.5. These cutoffs followed default or more stringent parameters as outlined in the USEARCH guide (https://www.drive5.com/usearch/). Filtered reads were subsequently preclustered by size (99% similarity, maximum differences &#8804;4) and then clustered into Operational Taxonomic Units (OTUs) based on 97% similarity using the UPARSE algorithm <ns0:ref type='bibr' target='#b14'>(Edgar 2013)</ns0:ref>. USEARCH filtering and subsequent OTU clustering was conducted with singleton data (OTUs with single DNA sequence occurrence), as procrustes analysis revealed non-significant differences between singleton and non-singleton multivariate ordinations (package 'vegan', function 'protest()', Procrustes analysis: SS = 2.47 x 10 -4 (Species Comparison) &amp; 1.66 x 10 -4 (Habitat Comparison), P &#8804; 0.001 (Species Comparison) &amp; P &#8804; 0.001 (Habitat Comparison); Supplemental Fig. <ns0:ref type='figure' target='#fig_3'>S2 &amp; S3</ns0:ref>). All USEARCH scripts utilized in these analyses can be retrieved from our GitHub page (https://github.com/bngallo1994to be released upon publication).</ns0:p><ns0:p>The USEARCH generated OTU tables were modified into a shared compatible file and uploaded into Mothur v.1.39.5 <ns0:ref type='bibr'>(Schloss et al. 2009</ns0:ref>). Rarefaction files were subsequently created using the Mothur MiSeq TM Standard Operating Procedure (https://www.mothur.org/wiki/MiSeq_SOP). OTU tables were modified to make rarefaction files to estimate species richness. Because of error rates, singleton calls using NGS platforms can be interpreted as potential sequencing artifacts <ns0:ref type='bibr'>(Brown et al. 2015)</ns0:ref>. Nonetheless, subsequent analysis from the most dominant OTU's in each dataset revealed negligible differences in community structure between singleton-included and excluded microbiota matrices (data not shown). Rarefaction curves utilizing singleton OTUs thus served as a maximum estimate of total species richness are presented in this manuscript.</ns0:p><ns0:p>The SILVA 138 high quality ribosomal RNA database was used to determine the identity of the most abundant OTUs in each fish species <ns0:ref type='bibr' target='#b49'>(Quast et al. 2013)</ns0:ref>. We queried all OTU16S rRNA sequences using SILVA's Alignment, Classification and Tree Service (ACT) web module (https://www.arb-silva.de/aligner/) <ns0:ref type='bibr' target='#b48'>(Pruesse et al. 2012)</ns0:ref>. OTU sequences were classified with a minimum query sequence identity of 95% and 10 neighbors per query sequence</ns0:p><ns0:p>The SILVA generated taxa information was subsequently combined with the USEARCH OTU table and sample metadata into a single phyloseq class object using the bioconductor Rarefaction analyses were paired with the calculation of Good's Coverage using the Chao method to provide a description of rarefaction in terms of the total sampled OTU diversity <ns0:ref type='bibr' target='#b19'>(Good 1953;</ns0:ref><ns0:ref type='bibr' target='#b7'>Chao 1984;</ns0:ref><ns0:ref type='bibr' target='#b31'>Larsen 2014)</ns0:ref>. Datasets were rarefied to normalized sequencing depth for comparisons of microbial relative abundances between samples. The instantaneous slope of each rarefaction curve was determined at this normalized depth <ns0:ref type='bibr' target='#b26'>(Hurlbert 1971)</ns0:ref>. To estimate OTU loss through normalization, we also compared the normalized species richness to the observed richness collected at each sample's maximum sequencing depth <ns0:ref type='bibr' target='#b8'>(Chao and Jost 2012)</ns0:ref>. These analyses quantitatively assessed our ability to detect a representative coverage of microbial DNA from wild caught Round Goby and Yellow Bullhead.</ns0:p><ns0:p>A number of &#945;-diversity metrics were also calculated for all Round Goby and Yellow Bullhead samples. The Observed, Chao1, and Shannon indices were calculated to estimate &#945;diversity between the two fish species and within Round Goby by habitat. Significance between groups was tested from each index with Wilcoxon rank-sum tests (Mann-Whitney) using the <ns0:ref type='bibr' target='#b47'>Benjamini and Hochberg (1995)</ns0:ref> p-value correction method.</ns0:p><ns0:p>Non-metric multidimensional scaling (NMDS) was employed to visualize dissimilarity in datasets between samples. NMDS (R package 'vegan', function 'metaMDS') ordination was computed for both normalized habitat and species datasets. NMDS scaling <ns0:ref type='bibr' target='#b30'>(Kruskal 1964</ns0:ref>) was used to visualize the Bray-Curtis dissimilarity <ns0:ref type='bibr' target='#b3'>(Bray and Curtis 1957)</ns0:ref> between samples using default permutations (n=20) in the 'metaMDS' function in the vegan. Permutational multivariate analysis of variance using distance matrices (PERMANOVA, package 'vegan', function 'adonis'; 999 permutations) was employed to assess significant differences (&#945; = 0.05) between the two datasets: (species comparison = Round Goby and Yellow Bullhead; habitat comparison = Round Goby shallow and deeper profundal habitat). Due to the sample size differing by one individual, we assumed a balanced design and followed the recommendations of <ns0:ref type='bibr' target='#b2'>Anderson and Walsh (2013)</ns0:ref>; PERMANOVA remains robust in the presence of heterogeneity of group dispersion.</ns0:p><ns0:p>In addition to NMDS, &#946;-diversity was compared between fish species and habitat using pairwise weighted UniFrac distances <ns0:ref type='bibr' target='#b38'>(Lozupone and Knight 2005)</ns0:ref>. Unifrac distances were calculated between all combinations of Round Goby and Yellow Bullhead (for the species comparison) and Governor's Island and Eagle Wings Round Goby (for the habitat comparison).</ns0:p><ns0:p>Similar to the NMDS ordinations, weighted Unifrac distances were visualized using Principal Coordinate Analysis (PCoA) while retaining the first two axes. Welch's two sample t-tests were conducted to determine if weighted Unifrac distances between sample groups was significant.</ns0:p><ns0:p>These distances were subsequently plotted (&#177; SE) to visualize differences in gut microbiota by fish species and habitat.</ns0:p><ns0:p>Predictions of microbial community functions were assessed using the 'Tax4Fun' <ns0:ref type='bibr' target='#b1'>(A&#223;hauer et al. 2015)</ns0:ref> and 'themetagenomics' <ns0:ref type='bibr'>(Woloszynek et al. 2017</ns0:ref>) R packages. 16S rRNA marker gene functions were linked to SILVA database Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologs (KOs) using the MoP-Pro approach to determine predictive function relative gene abundance for each gut microbiota sample <ns0:ref type='bibr' target='#b0'>(A&#223;hauer and Meinicke 2013)</ns0:ref>.</ns0:p><ns0:p>The top 20 KO's were then screened <ns0:ref type='bibr'>(Yang et al. 2019</ns0:ref>) and plotted on bar graphs to related relative gene abundance vs. fish species or capture location (for Round Goby). Orthologs that did not link to a specified level one KEGG pathway were excluded from the analyses, and the next PeerJ reviewing PDF | (2020:02:45747:1:1:NEW 1 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed most abundant was substituted. Functions were combined based on level one as defined by the KEGG pathways output. Significance testing comparing the gut microbiota samples was performed using Welch's two sample t-tests.</ns0:p><ns0:p>Supplementary Data Processing and Analysis Information.-All procedures including tissue sampling, DNA extraction, PCR, amplicon cleanup, NGS library preparation, and downstream FASTQ processing as well as all code are detailed on our GitHub page (https://github.com/bngallo1994to be released upon publication).</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>NGS Sequencing</ns0:head><ns0:p>Species and habitat comparison datasets yielded 3.01 and 1.90 million paired-end sequenced reads, respectively, each passing our pre-defined USEARCH quality filter. Final reads clustered into 1,266 OTUs and 574 OTUs in species and habitat comparison OTU tables, respectively. Rarefaction analyses (Fig. <ns0:ref type='figure' target='#fig_2'>2A</ns0:ref> &amp; 3A) indicated plateauing of OTU detection at approximately 20,000-30,000 reads/sample, but novel OTU's were still detected at upwards of 100,000 reads / sample, especially in Yellow Bullhead. The mean number of reads/sample &#177; SE was 136,959 &#177; 776 with a mean of 126,739 &#177; 967 for Round Goby and 158,858 &#177; 1,283 in Yellow Bullhead. Analysis of rarefaction data using Good's Coverage at the normalized sequencing depth indicated samples represented &gt; 99.7% coverage of OTU diversity in both datasets (Tables 1).</ns0:p><ns0:p>Slope analysis of normalized rarefaction curves indicated high rates of microbe OTU detection at low sequencing depth and low novel OTU detection at higher sequencing depth.</ns0:p><ns0:p>Discovery rates of OTUs/1000 sequences show the slope of the normalized rarefaction curves were between 0.091-2.66 OTUs/1000 sequences between both datasets. Further validation of our high OTU coverage was seen comparing the OTU species richness at the normalized sequencing depth to maximum sequencing depth for each sample. The calculated highest sequencing depth provided an average &#177; SE increase of 32 &#177; 14 OTUs and 11 &#177; 4 OTUs for the species and habitat datasets respectively (Supplemental Tables <ns0:ref type='table'>S2 &amp; S3</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:02:45747:1:1:NEW 1 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Comparing Round Goby and Yellow Bullhead Gut Microbiota (SPECIES) and Round Goby Microbiota at the Eagle Wings Islands and Governor's Island (HABITAT)</ns0:head><ns0:p>Permutational analysis of variance (PERMANOVA) on the species comparison NMDS ordination (Fig. <ns0:ref type='figure' target='#fig_2'>2B</ns0:ref>) indicated a significant difference between Round Goby and Yellow Bullhead gut microbial communities (PERMANOVA: Pseudo F = 7.88, df = 1, P = 0.003, r 2 = 0.28, NMDS stress = 0.14). Two distinct groups are evident with 95% confidence ellipses displaying little overlap (Fig. <ns0:ref type='figure' target='#fig_2'>2B</ns0:ref>). Similar patterns were observed with the weighted Unifrac PCoA ordination (Axes 1 + 2 accounting for over 73% of total data variation (Supplemental Fig</ns0:p></ns0:div> <ns0:div><ns0:head>S3)).</ns0:head><ns0:p>OTU identification in both Round Goby and Yellow Bullhead also showed differences in the bacterial composition of dominant microbes in each of the fish species. Parsing the present microbiota by relative abundance, the top 10 OTUs (Fig. <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>) using the SILVA database showed Aeromonas spp. (OTU1, 66.9 &#177; 8.7%), Cetobacterium spp. (OTU2, 10.1 &#177; 6.4%), and Streptococcus spp. (OTU5, 4.4 &#177; 3.3%), as the most abundant taxa in the gut microbiota of Round Goby. While Cetobacterium spp. (OTU2, 39.7&#177; 14.7%), Clostridium sensu stricto 1 (OTU7, 25.7 &#177; 8.7% and Aeromonas spp. (OTU1, 14.8 &#177; 9.4%) were the most abundant bacteria in Yellow Bullhead.</ns0:p></ns0:div> <ns0:div><ns0:head>Similar analyses comparing Round Goby sampled between Governors Island and the</ns0:head><ns0:p>Eagle Wings Islands (Fig. <ns0:ref type='figure' target='#fig_3'>3B</ns0:ref>) also revealed differences in their gut microbial composition (PERMANOVA: Pseudo F = 2.63, df = 1, P = 0.03, r 2 = 0.17, NMDS stress = 0.04). PCoA ordinations showed similarity to the NMDS plot (supplemental Figure <ns0:ref type='figure' target='#fig_4'>S4</ns0:ref>), and the plotted principal components accounted for over 89% of the data's variation. Additionally, differences were observed in the dominant gut microbiota from Round Goby at each location (Fig. <ns0:ref type='figure' target='#fig_5'>5</ns0:ref>). The Eagle Wing's Round Goby gut samples were dominated by Aeromonas spp. (OTU1, 88.9 &#177; 4.0% ), Shewanella spp. (OTU8, 4.2 &#177; 2.7%), and Corynebacterium spp. (OTU14, 1.1 &#177; 0.7%) while Governors Island Round Goby guts were largely colonized by Aeromonas spp. (OTU1, 47.3 &#177; 12.4%), Cetobacterium spp. (OTU2, 18.6 &#177; 11.6%) and Streptococcus spp. (OTU3, 8.1 &#177; 6.1%) bacteria. In both comparisons, the Top 10 dominant bacteria accounted for over 89% of the total microbiota observed.</ns0:p><ns0:p>Despite the observed differences in the dominant taxa between and within sampled fish gut microbiota, no significant differences existed for any &#945;-diversity metrics, including Observed, Chao1, and Shannon (P-values &gt; 0.08) among species (Fig. <ns0:ref type='figure' target='#fig_6'>6</ns0:ref>) or the habitat comparison (P-values &gt; 0.46; Fig. <ns0:ref type='figure'>7</ns0:ref>). UniFrac distances however, revealed higher variance in the gut bacterial community between species (RG: t = -4.11, df = 293.37, P &lt; 0.001 &amp; YB: t = 3.20, df = 84.47, P = 0.002) compared to within species (Fig. <ns0:ref type='figure' target='#fig_7'>8</ns0:ref>). For Round Goby, additional Unifrac distance testing indicated a significant difference in bacterial community variation between habitats (t = 11.30 df = 50.49, P &lt; 0.001). Round Goby from the deepwater habitat (Eagle Wings Islands) demonstrated the least variation in gut microbial composition while those from the nearshore littoral Governors Island had the greatest amount (Fig. <ns0:ref type='figure' target='#fig_8'>9</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Comparing Round Goby and Yellow Bullhead Gut Microbiota Predicted Functions using Tax4Fun</ns0:head><ns0:p>Predictions of microbial community functions using KEGG Orthologs (KO) indicated no significant differences in predicted microbial functions associated with our species and habitat comparisons. Mapping of the Top 20 KO's that matched to KEGG pathways revealed only slight differences in microbial community gene abundances linked with environmental information processing, cellular processes, metabolic pathways, and genetic information processing (Fig. <ns0:ref type='figure' target='#fig_1'>10</ns0:ref> + 11). There were no significant differences in the top 20 KO's for the species comparison for environmental information processing (t = 0.28, df = 9.22, P = 0.79), cellular processes (t = 0.18, df = 10.07, P = 0.86), metabolic pathways (t = 0.58, df = 19.75, P = 0.57), and genetic information processing (t = -0.19, df = 9.36, P = 0.86). Similar conclusions were drawn from analysis of the top 20 KO's for the habitat comparison for Round Goby (environmental information processing: t = -1.86, df = 7.00, P = 0.11; cellular processes: t = 0.18, df = 10.07, P = 0.86; metabolic pathways: t = 1.93, df = 7.13, P = 0.09; genetic information processing: t = 1.75, df = 7.05, P = 0.12). This all stands in contrast to the aforementioned significant differences in overall gut microbiota both between and within species as seen through our &#946;-diversity analyses.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion.</ns0:head><ns0:p>Our data revealed fish gut microbiota differences between invasive Round Goby and native Yellow Bullhead in the upper St. Lawrence River. Our findings add to previous research that describes microbial community dissimilarities in various fish species employing a range of sequencing methods (Denaturing Grade Gel Electrophoresis <ns0:ref type='bibr' target='#b36'>(Li et al. 2012)</ns0:ref>; Pyrosequencing (Li PeerJ reviewing PDF | (2020:02:45747:1:1:NEW 1 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed et al. 2014)) as well as amplifying different variable regions of the 16S rRNA gene (V4 region; <ns0:ref type='bibr' target='#b37'>Liu et al. 2016)</ns0:ref>. Both NMDS and PCoA analyses support overall microbial composition differences between these fish species and results from the SILVA database indicated dominance of specific bacterial genera in each species' gut microbiome. Additional hypothesis testing using PERMANOVAs and weighted Unifrac distances further verified that significant differences in &#946;diversity were present both between Round Goby and Yellow Bullhead, and within Round Goby caught at the Eagle Wings and Governor's Island.</ns0:p><ns0:p>The observed prominence of Aeromonas spp., Cetobacterium spp., and Clostridium spp.</ns0:p><ns0:p>in the fish gut is consistent with reports by others including Aeromonas spp. <ns0:ref type='bibr'>(Wu et al. 2013;</ns0:ref><ns0:ref type='bibr'>Li et al. 2016)</ns0:ref>, Cetobacterium spp. <ns0:ref type='bibr' target='#b33'>(Li et. al 2015)</ns0:ref>, and Aeromonas spp. and C. somerae <ns0:ref type='bibr' target='#b31'>(Larsen et al. 2014</ns0:ref>). In addition to microbial differences noted between fish species, we also report interspecies variation in gut microbiota between the same species (Round Goby) captured in different habitats separated by a water depth gradient. Simulation analysis from <ns0:ref type='bibr' target='#b2'>Anderson and Walsh (2013)</ns0:ref> suggests PERMANOVA analysis is robust even with heterogeneity of variance between groups under a balanced design. Larger scale sampling from multiple locations with a balanced sampling design is recommended to better understand patterns of within species differences in microbiome among habitats. Future studies should take into account size and/or age bias with Round Goby, given the differences in average size of the captured Round Goby by habitat (150mm at Governor's Island vs. 113mm at the Eagle Wings). Previous research on Zebrafish has indicated that gut microbiota can vary with age/development <ns0:ref type='bibr'>(Stephens et al. 2016)</ns0:ref> and by seasonal sampling <ns0:ref type='bibr' target='#b53'>(Naviner et al. 2006)</ns0:ref>. All fish associated with this study were captured within an 11-day period during the fall of 2017, however observed differences in gut microbiota may not be present throughout all seasons. These variables will need to be controlled in future studies that increase sampling frequency spatiotemporally to extend our finding in a simple case.</ns0:p><ns0:p>The presence of specific and novel OTUs is particularly interesting when hypothesizing the microbiota's role in the gut community and its effect on fish hosts. For example, some species of Aeromonas act as opportunistic pathogens and cause various hemorrhagic fish diseases like furunculosis <ns0:ref type='bibr' target='#b24'>(Hidalgo et al. 2012)</ns0:ref>. Although Aeromonas spp. were routinely detected in fish guts in this study, we observed no obvious tissue hemorrhaging. However, we were unable to resolve Aeromonas sequences to the species level and were not able to determine if the specific Aeromonas bacteria present were known fish pathogens. This was most likely due to high heterogeneity of the 16S gene in Aeromonas bacteria <ns0:ref type='bibr' target='#b27'>(Janda and Abbott 2007)</ns0:ref>.</ns0:p><ns0:p>Sequencing with additional universal gene primers (e.g., cpn60 <ns0:ref type='bibr' target='#b45'>(Mi&#241;ana-Galbis et al. 2009</ns0:ref>) may help reveal species delineation in Aeromonas bacteria. Additional microbial genera detected in this study are also known to be beneficial and/or detrimental to their hosts. For example, bacteria of the genera Clostridium produce various essential fatty acids and vitamins <ns0:ref type='bibr' target='#b54'>(Ring&#248; et al. 1995;</ns0:ref><ns0:ref type='bibr' target='#b21'>Givens 2014</ns0:ref>) despite some species like Clostridium difficile, which can opportunistically cause pseudomembranous colitis <ns0:ref type='bibr' target='#b29'>(Kelly et al. 1994)</ns0:ref>. Moreover, the bacterium Cetobacterium somerae, the most abundant genera discovered in the gut microbiome of Yellow Bullhead in our study, is known to synthesize vitamin B12 in the fish gut <ns0:ref type='bibr' target='#b68'>(Tsuchiya et al. 2007</ns0:ref>). Regardless, 16S predictive functions derived from our Tax4Fun analyses were unable to identify microbiota functional patterns between Round Goby and Yellow Bullhead and within Round Goby by sampled habitat. In order to gain a better understanding of potential gut microbiota function in the fish gut, sampling with shotgun sequence metagenomic analyses could be implemented with parallel 16S amplicon sequencing analysis. The 16S amplicon sequencing would help delineate relative abundance of microbiota, and metagenomic analysis would define individual microbes' complete genomes. Together these approaches may provide a more complete picture regarding the metabolic, pathogenic, and other characteristics associated with bacteria sampled from the fish gut. The need for metagenomic analysis in has been called for in recent reviews on the fish gut microbiome <ns0:ref type='bibr' target='#b67'>(Tarnecki et al. 2017;</ns0:ref><ns0:ref type='bibr'>Gallo et al. 2020</ns0:ref>) and implementation will almost certainly provide a better understanding on gut microbial functions that may significantly influence fish health.</ns0:p><ns0:p>In addition to the demonstration of microbial differences across species, NGS has the potential to detect minute differences in microbial communities within species. We employed an NGS workflow to investigate differences in gut microbiota in Round Goby samples from different habitats separated by less than 750 meters. Evidence for environmental differences in fish gut microbiota has been previously noted in the Atlantic salmon parr gut microbiome <ns0:ref type='bibr' target='#b13'>(Dehler et al. 2017)</ns0:ref> and in wild vs. aquaculture-reared fine flounder <ns0:ref type='bibr' target='#b51'>(Ram&#237;rez and Romero 2017)</ns0:ref>. Although our design did not take into account potential diet and habitat variation between the two samples of Round Goby, our data does support within-species differences at fine-spatial scales. A previous study in a nearby area of the St. Lawrence River indicated significant differences in total phosphorus and crustacean zooplankton abundance between shallow and PeerJ reviewing PDF | (2020:02:45747:1:1:NEW 1 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed deepwater stations <ns0:ref type='bibr' target='#b17'>(Farrell et al. 2010</ns0:ref>). These differences possibly extend to benthic invertebrates, including dressenid mussels known as important forage for Round Goby. Both Round Goby habitats were sampled at different depths (Governors Island: &lt;2m; Eagle Wings Islands: &gt;15m) and significant gut microbial community differences were noted, specifically with Aeromonas spp. (&gt;80% total Eagle Wings Islands reads vs. ~50% of Governors Island reads). Nonetheless, &#945;-diversity metrics indicated no differences in gut microbiota abundance in both our habitat and species comparisons. These analyses support that despite overall differences in the taxonomy of the bacteria, the diversity and evenness of the microbial communities within compared groups remained similar. Future analysis derived from NGS microbial data coupled with biological (e.g., host diet, host habitat) and environmental factors (e.g., pressure, temperature, and light penetration) would help further define gut community structure differences observed between habitats and fish species.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In this study, we employed an NGS workflow and sampled gut microbiota for the first time from fishes along the upper St. Lawrence River. We implement analyses to test both interand intraspecific differences. We describe significant species level microbial community differences between an invasive (Round Goby) and native (Yellow Bullhead) fish species. We also describe significant differences between Round Goby sampled in different habits separated by only ~750 meters. This detailed workflow may help facilitate greater application of gut microbiome research and allow for the examination of numerous basic and applied questions (for examples see <ns0:ref type='bibr'>Gallo et al. 2020)</ns0:ref>. As NGS technologies and knowledge of host-microbe interactions continue to grow, investigations into the gut microbiome will undoubtedly improve our understanding of fish ecology and their conservation and management. The research methods developed and applied here are intended to promote such investigations, and aid researchers interested in studying gut microbiota. Ellipses on the NMDS plot denote 95% confidence intervals. The NMDS ordination revealed a significant difference (P = 0.003) between the two species.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:02:45747:1:1:NEW 1 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed The UniFrac analysis revealed higher variation in gut microbial communities between species than within species. Differences between letters above each barplot denote a significant difference in UniFrac distance (P-value &lt; 0.05).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:02:45747:1:1:NEW 1 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 10</ns0:note><ns0:p>Relative Gene Abundance of predicted microbial community functions from the species comparison, calculated using Tax4Fun and the Top 20 level one pathway KEGG Orthologs.</ns0:p><ns0:p>There were no significant species differences in microbial community functions pertaining to Environmental Information Processing (A), Cellular Processes (B), Metabolism (C) or Genetic Information Processing (D) for all measured level one KEGG Ortholog pathways (P-values = 0.79, 0.86, and 0.57, respectively).</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 11</ns0:head><ns0:p>Relative Gene Abundance of predicted microbial community functions from the habitat comparison, calculated using Tax4Fun and the Top 20 level one pathway KEGG Orthologs.</ns0:p><ns0:p>There were no significant habitat differences in microbial community functions pertaining to Environmental Information Processing (A), Cellular Processes (B), Metabolism (C) or Genetic Information Processing (D) for all measured level one KEGG Ortholog pathways (P-values = 0.11, 0.09, and 0.12, respectively).</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>package 'Phyloseq' (McMurdie and Holmes 2013). Two phyloseq objects were created -one for the Round Goby vs. Yellow Bullhead Species comparison, and one for the Governor's Island vs. Eagle Wings comparison for Round Goby. Additionally, we analyzed the top 10 OTUs from each dataset at normalized sequencing depth (species comparison: 41,250 sequences/sample; habitat comparison: 40,972 sequences/sample) to determine their average relative abundance in Round Goby and Yellow Bullhead. Using the same strategy, we determined the identity and relative abundance of the top 10 OTUs within each Round Goby habitat group (Eagle Wings Islands vs. Governors Island).To estimate the microbial community coverage, OTU tables and rarefaction data files were analyzed using the entropart (v 1.5-3; Marcon 2018), ggplot2 (v 3.0.0; Wickham 2016), and vegan (v 2.5.2;<ns0:ref type='bibr' target='#b46'>Oksanen et al. 2018</ns0:ref>) packages of the R statistical software (R Core team 2017).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 Rarefaction</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 Rarefaction</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 6 &#945;</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 8 Pairwise</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 9 Pairwise</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Figure 9</ns0:figDesc></ns0:figure> </ns0:body> "

" Brian F. Leydet Jr. State University of New York College of Environmental Science and Forestry 1 Forestry Drive Syracuse, NY 13210 315-470-6942 [email protected] Craig Nelson Academic Editor; PeerJ Journal June 25th 2020 Dear Dr. Craig Nelson, On behalf of all the authors, I am pleased to submit revisions to our manuscript now entitled “Use of next generation sequencing to compare simple habitat and species level differences in the gut microbiota of an invasive and native freshwater fish species” by Benjamin D. Gallo, Brian F. Leydet Jr., and John M. Farrell for consideration for publication in the journal PeerJ. My fellow authors and myself want to thank you for reviewing our submitting manuscript. We also want to thank the three reviewers for their meticulous analysis of our original submission. We have responded to all three reviewers’ comments and concerns and have edited the manuscript accordingly. We have significantly modified our original submission from its initial form and have shiftend the focus of the manuscript. It was pointed out that our initial submission which emphasized an method lacked side-by-side comparisons experiments. We agree a direct comparison of this method to the many methods available would be of interest (and benefit to the field as you mention) however this was not our goal. To clarify our approach, we have deemphasized the SOP and now focus on our results while still providing a detailed protocol as a method for others to follow. We have significantly expanded on alpha/beta diversity metrics as request by reviewers and additional taxonomic and compositional analyses. These analyses added additional support to our initial results and we believe our expanded analyses provide novel findings for the field. We agree with all the reviewers that future investigation into room temperature preservation of gut microbiota is warranted, but this was outside the initial scope of this study and funding. However we believe these results and detailed protocols would be of interest and serve as a resource to readers of PeerJ and microbiome researcher in the Fisheries sciences. Please find, following this letter our point-by-point responses to each reviewer’s comments/concerns. Regards, Brian F. Leydet Jr, MPH, PhD 110 Illick Hall • 1 Forestry Drive •Syracuse, New York 13210 • 315-470-6942 • [email protected] www.esf.edu Reviewer: 1 Comments to the Author Basic reporting The overall manuscript is written ok. The structure could be improved with a more in depth literature review as noted. Some incorrect uses of references. Please check references and perhaps add some additional ones focused specifically on fish microbiomes. For the last paragraph of the introduction, I would encourage having a couple of overview sentences describing the general sampling strategy to test your hypotheses. The figures and tables are ok. The author cites the github page in the abstract but the link shows that nothing is listed. This needs to be made publically available or at least available to reviewers during the review stage. Thank you for your feedback and we have taken the manuscript based on yours and the other 2 reviewers comments and added additional detail, analyses and refocused the paper. We believe this revised manuscript has significantly improved. We have also used appropriate literature and added our now published fish microbiome review paper in Fisheries. Additionally, the mentioned github material was provided to PeerJ at submission in a dropbox link. We have provided an updated link for the resubmission as well. ---------- Experimental design Primary research aim: The primary research question was to what extent a new storage buffer enabled the preservation of the gut microbiome of the fish. The author claims the buffer can be used to store samples for 4-8 weeks without cold storage but does not actually test this. The main point of the article is that they've developed a method to enable collection and storage of gut microbiomes from the field. Scope cont.: It would make for a more compelling manuscript to describe the extent of fish diversity which would benefit from this. In other words, of the 35000 fish species, how many of them are located in remote locations where sampling is perhaps even impossible. I realize it would be difficult to give absolute numbers here but it would be useful to consider describing this a little more in the introduction. The authors decided to focus on the validation of the technique, but did not test this thus the investigation was not rigorous. The authors may perform this analysis and submit findings in a revision. We agree a direct comparison of this method to the many methods available would be of interest (and benefit to the field as you mention) however this was not our goal. To clarify our approach, we have deemphasized the SOP and now focus on our results while still providing a detailed protocol as a method for others to follow. We employed a published NGS protocol to study the gut microbiome in two fishes from the St. Lawrence River and hope that this can serve as a resource in advancing NGS in fisheries science. ---------- Validity of the findings For microbiome analyses, the author omits alpha diversity from the comparisons between species and comparisons in habitat for the gobies. This should be performed and compared using a non-parametric pairwise comparison e.g. Mann-Whitney. This would likely reveal the bullhead fish having higher richness and within gobies likely no differences in richness when comparing the sites. These metrics have been added. There were no significant differences among the 3 Alpha diversity measures when comparing species and habitat using Wilcoxon-ranked sum tests (e.g., Mann Whitney). ---------- For both figure 2 and figure 3, the author compares the species and habitats using NMDS. While this is a fine measure, I would suggest and encourage the authors to explore additional beta diversity comparison methods which take into account phylogenetic differences in the microbial community (e.g. Unifrac distances). At the very least, utilizing methods such as Jaccard and or Bray-Curtis would enable additional comparisons which might further support the observations made. We have added additional analyses that support NMDS findings. ---------- Figures 4 and 5 could be combined into one figure with two panels. Its not appropriate to just pick the top 3 OTUs. Also note that compositionality makes it impossible to determine true biomass or even changes or differences in communities. For instance, its possible that Aeromonas is higher in gut samples from Eagle Wings compared to Governors Island, but its equally likely that there are simply more other types of taxa in Governor’s Island and Aeromonas is the same. To deal with this problem, one can use ranks or ratios. See, https://doi.org/10.1016/j.annepidem.2016.03.003 Thank you for the comment we have extended out analyses to the top 10 bacterial genera which comprise ~89% of the total abundance in fish in our study. We feel this more accurately addresses the reviewer’s concerns. ---------- Comments for the author Developing new collection methods is important and while you have shown that you can distinguish a species effect and habitat effect based on samples collected with your method, you do not actually verify or test the method itself. If the focus of the manuscript is to be on the method, you will have to perform experiments which justify the buffer use. This could include a time series of a few samples processed with different storage methods. You can then compare both alpha and beta diversity changes. Alternatively, the dataset in itself has relevant biological findings which could also be a main focus rather than the storage method. That being said, it would still be important to justify this storage method and confirm that the differences in community structure are not simply from a storage effect. Thank you for your comments and we have clarified our initial intent of this pilot study in the resubmitted manuscript. Specifically, as you state we sought determine the ability to detect species/habitat effect on fish gut microbiome in 2 fishes in the Upper St Lawrence River. ---------- Line by Line to Reviewer 1 1. Line 42: The github page listed in the abstract is not available. If you’ve done a special computational method to process the data, its highly recommended to be available during the review process. Response: The Github page would be made publicly available upon publication. The contents of the Github page are available to view by the reviewers at the following URL: https://www.dropbox.com/sh/gkbd92g4bf29nc8/AACOUEBBrfNcGsW-w3EC36taa?dl=0 ---------- 2. Line 44: “Our approach allowed for high bacterial OTU diversity coverage (99.7%)”
In the abstract, there were a few points of confusion. For instance, its not clear what the following statement is referring to. If the goal is to justify you are assessing the majority of microbial diversity in the dataset, you should state that and reference it as a Good’s coverage metric. Response: The aforementioned statement has been amended to inform the reader that the diversity coverage of 99.7% was calculated using Good’s Coverage. Additionally, the remaining lines of the abstract have been amended to shift the focus of our manuscript more towards our collected data / results instead of focusing on the SOP because direct comparison studies are not feasible at this time. ---------- 3. Line 56-57: Incorrect use of reference. This reference is a review article for fish gut microbiomes. It does not distinguish between mammal guts and fish guts. Response: The reference has been changed to Sullam et al. 2012. This article states that the majority of microbiome work has focused on mammals (in the papers introduction). ---------- 4. Line 59: Grammatical: run-on, end sentence at Sullam and begin a new one. Response: Fixed as requested. ---------- 5. Line 68: Additional references for influence of habitat on freshwater fish microbiome: https://doi.org/10.1002/mbo3.716 #algal blooms from different nutrient sources https://doi.org/10.1111/mec.13177 #salinity https://doi.org/10.1186/s40168-016-0190-1 #captive vs wild Response: The manuscript concerning salinity influence on fish gut microbiota was added at line 68. The other two list papers were omitted as they focused on fecal microbiota from fish, which is different from gut-derived microbiota (as described in humans in Gevers et al. 2014 (doi: 10.1016/j.chom.2014.02.005) . We did not want to mislead readers by combining information on gut and fecal microbiomes. ---------- 6. Line 76: There have been a few storage studies to date, check out https://msystems.asm.org/content/1/3/e00021-16.short Response: We have shifted the focal point of the manuscript to focus on the sequencing results and subsequent data analysis from the collected Round Goby and Yellow Bullhead instead of our use of room temperature preservation methods. Test the efficacy of our preservation methods to others is outside of the scope of this project. ---------- 7. Line 84: “St. Lawrence River, prefers small...” Does the fish prefer to live with these animals or eat these animals? Response: The Yellow Bullhead consumes small fish and crustaceans. The sentence has been changed to reflect this. ---------- 8. Line 99: 8 -> eight. Response: Fixed as requested. ---------- 9. Line 106: Did you clamp down the ends of the GI? Response: The ends of each fish’s GI tract were not clamped down during surface sterilization. We sought to remove all digesta and non-gut tissue associated microbes from the GI tract, prompting us to keep both ends of the GI tract open. ---------- 10. Line 113-119: The NA preservation buffer is described, but there are not citations as to this being used previously. Response: The citation for Camacho-Sanchez et al. 2013 at the end of the NAP description provides previous application of the NAP buffer for ambient temperature preservation of mammalian DNA. ---------- 11. Line 121: There are many controls which could be used to test your overall extraction pipeline, library prep, and storage but there are none listed. Did the author include controls in the experiment and if not why? Response: We used extensive laboratory controls to verify no bacterial contamination occurred during DNA extraction and PCR prep/cleanup. Library prep controls were also used (10% PhiX spike) and stringent measures were used for raw sequence cleanup and analysis to insure legitimacy to our data. We are confident our provided results are true to what was initially sampled from each fish. ---------- 12. Line 167: The 97% clustering methods for OTU picking are outdated. There are several newer ‘ASV’ methods which are preferred including dada2 (most popular) and deblur. Response: We agree that there are multiple ways to identify and group microbial sequences. However the use of OTU’s for identifying amplicons has been commonly used and is still being used in recently published microbiology / molecular biology manuscripts (for example: https://www.nature.com/articles/s41467-019-08925-4#Sec8). Additionally, many papers have questioned the benefits of using ASV’s compared to OTU’s. There have been instances where it has been found that ASV’s may increase sensitivity, but at the cost of specificity (https://doi.org/10.1371/journal.pone.0227434) and alpha diversity metrics can be considerably different based on what pipeline is used (htpp://doi.org/10.7717/peerj.5364). We agree both OTU and ASV approaches have their pros/cons and for this pilot study chose to group via OTU. ---------- 13. Line 185-187: This is an inappropriate use of BLAST. Please use either SILVA (most prominent) or Greengenes (more outdated) to annotate your sequences. It is very straightforward to do this and would improve your overall manuscript along with insights into the taxonomic distributions. https://www.arb-silva.de/ Response: Thank you for pointing this out. We have redone our taxonomic analysis using the most recent version of the SILVA database (SILVA 138). Using SILVA we were also able to examine a greater number of taxa that we have included in the results. ---------- 14. Line 191: Its unclear why the authors have chosen to look at just 3 OTUs out of the ~40,000 reads. Response: We have expanded our manuscript and analyses to cover the top 10 OTUs. Based on relative abundance, the top 10 microbiota we analyzed covered >89% of the sequenced reads. ---------- 15. Line 263: The comparison between gobies collected from the two locations should be interpreted with caution. A rejection of the null hypothesis could be explained by two reasons: the centroid locations differ or the total dispersion or variation within groups differ. In this case, since the one group type is amongst the other, the interpretation would suggest that its actually the dispersion that is driving the differences. This is in itself an interesting finding and could change the direction of the manuscript. One could ask, why does it appear deep living gobies have a more stable microbiome and has this been seen in the literature? Are there differences in the life history between deep vs shallow which may explain this? Response: In the third paragraph of the Discussions section, we address this issue. Based on the results from Anderson and Walsh (2013), PERMANOVA remains robust with heterogeneity of variance (i.e. unequal dispersion of samples in NMDS ordination plot) as long as there is a balanced design. Our design is not balanced (8 Governor’s Island gobies vs. 7 Eagle Wings gobies), but one could argue a difference of 1 is close to balanced. The NMDS ordination in the manuscript was plotted using Bray-Curtis distances. We additionally ran a PCoA with UniFrac distances as suggested by reviewers which returned similar results. Additionally, the Unifrac distances were significantly larger when comparing gut microbiota between Eagle Wings and Governor’s Island Round Goby. These analyses combined suggest a true difference in these goby populations based on their habitat. We agree that a larger and exact equal sampling design would certainly make the conclusions drawn from the PERMANOVA more robust. We agree that it is interesting as to why the microbiota variance were limited in the deepwater Eagle Wings Round Goby. We were unable to find any literature on Round Goby gut microbiome differences based on water depth so it is a novel observation. . ---------- 16. Line 274: The authors are misinterpreting their results. Because they did not compare to a standard sampling/collection method, its impossible to make a statement as to how much of they actual microbial diversity they assessed. If microbes continue to grow in solution or nucleases are not effectively disabled, then its very possible that certain microbes could have been degraded and never sequenced. This paper for instance shows that in just a few days at room temperature (no storage solution albeit), microbial communities can change rapidly. DOI: 10.1128/mSystems.00199-16
 Response: As mentioned above (under comment #6), we have shifted the focus of our manuscript away from our SOP and sample storage at room temperature. We have chosen to highlight our data from the gut microbiota from a native (Yellow Bullhead) and invasive (Round Goby) species of fish found in the Upper St. Lawrence River. Our data reveals both species and habitat level differences in gut microbiota that may lead to numerous experiments studying Yellow Bullhead, Round Goby, and other freshwater fish gut microbiota along the St. Lawrence River. We agree that a side-by-side comparison study could further support this method but was outside of the scope of this project. We chose to employ a published mammalian method for gut microbiome research in fish which was able to discern both species and habitat differences. ---------- 17. Line 281-282: There was no assessment of DNA quality or microbial quality. Response: We have removed this statement from the manuscript. We cannot determine the quality of our preserved DNA or microbiota, but as described in out methods we used extremely stringent measures in filtering the sequenced amplicons to ensure validity of our findings. ---------- 18. Figure 1. It would be great to include a cross section depth profile of the environment to show the differences in depth between the sites. In addition, it would be helpful to show the sample numbers and fish species taken from each site. The author could use PhyloPic for outlines of the species. Response: Unfortunately, a cross sectional depth map does not exist for our sampled sites. We have included a supplemental table (Table S1) that outlines the number of samples taken from each site with additional sample metadata (fish length, weight, etc.). PhyloPic unfortunately does not carry outlines for Round Goby and Yellow Bullhead. ---------- 19. Figure 2A. The rarefaction curve appears to show the bullheads have higher alpha diversity than the gobies. It is really hard to see the color differences. I would suggest using different line types (... or --- or ___) to separate the species. In addition, it would be useful to separate the gobies by location of sampling with colors or shapes. The author does not show alpha diversity measures at all. Response: We have included new figures outlining alpha diversity measures in the new manuscript. ---------- 20. Figure 2B. It is not clear to what extent you rarified. Also, again, it would be helpful to label the gobies by depth by either changing the shape or color so one can observe broadly in context to the other fish if differences occur. Response: The rarefaction curves included in these figures show the total sequencing depth for each sample to give a visual as to the sequencing coverage for each sample (and how/where the novel OUT plateau’s occur). We have additionally changed the coloring code for all our rarefaction and NMDS plots to help the viewer better differentiate samples by species or habitat. ---------- 21. Figure 3 shows potential differences between depths of habitat for gobies.
Figure 3a. again, please include alpha diversity comparisons
Figure 3b. The clustering of the eagle wings site (deep water) is very tight, demonstrating low overall variation. The shallow site has a much higher variation. Althought he NMDS shows they are significantly different, the interpretation should be cautious and focus on why a shallow site may have a higher variation rather than compositional differences. Response: We have included new figures outlining alpha diversity measures in the new manuscript. Additionally, we addressed the interpretation of the NMDS plot in the discussion section & specifically in comment #15 above. ---------- 22. Figure 4. The author makes species level claims of the bacteria using a BLAST search which is not appropriate due to fact the reads are short amplicons. If the author really wants to justify and make species level claims, it’s important to do that using targeted qPCR methods for specific genes or by performing whole genome shotgun sequencing of the metagenomic communities followed by assembly and annotation. If the goal here is to show the distribution of various taxa within the fish. Response: We have omitted species level claims from our analysis. The highest level of taxonomic ranking we use is genera (based on results from the SILVA database as recommended you recommended). ---------- Reviewer(s)' Comments to Author: Reviewer: 2 Basic Reporting: Only one point that needs to be clarified in the introduction and discussion is what the authors suggested from this study. If this manuscript aims to provide an overview of the gut microbiome composition and structure in two selected fish species (an exploratory study) the data that have been presented are relevant. However, from some part of the manuscript (i.e. line 79-82), it seems that authors suggesting the methodology used in this study as a standard SOP for all fish related gut microbiome analysis, which I believe is an oversimplification. Just as an example, although NAP buffer showed some promising results in one study for mammalian samples (Camacho 2013), it does not mean it provides the same good preservation picture for fish gut digesta. So, I believe unless you a clear comparison of the current state of art approach like snap frozen, RNALater, Omnigen buffer, Zymo storage buffer, etc, the conclusion that the author made in this manuscript is not robust enough. The same for DNA extraction. Because a direct comparison of NGS prep and methods is not feasible at this time, we have refocused the manuscript on our data comparing the gut microbiota of Round Goby and Yellow Bullhead. Our initial intentions for this study were exploratory, and we sought to survey the gut microbiota of fish from the Upper St. Lawrence River. Based on our available resources, we had no choice but to utilize room temperature preservation of gut microbiota following a published method employed in other systems (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5281576/), and testing this to numerous other methods (commercial storage buffer, snap freezing in liquid nitrogen, etc.) was outside of the scope of this study. Nonetheless, we believe our results and subsequent analysis provide new information and detailed protocols that will benefit the fish gut microbiome research community. Our revised manuscript deemphasizes the SOP and highlights our fish species and habitat level findings. ---------- Experimental Design: 1. One important point to mention for this section is the low number of fish selected for this analysis. I believe this is one of the key limitations of the manuscript that should be mentioned in the discussion section( e.g why this sample size). We agree with the reviewer that our sample size was small. Because of the nature of this study and resources available at the time these were the number we had. We agree that increased sampling would strengthen this study but observations indicate differences despite small samples sizes in multiple analyses, therefore we believe the results we present are valid. ---------- 2. Another type of analysis that could have added more information and insight to this manuscript is to use the functional prediction tool on their 16S dataset to have also an overview of the functional profile of the fish gut microbial communities. I suggest that given to reliable bioinformatics tools that are available for this purpose, the authors follow up on that and add the relevant multivariate analysis and discussion, too. We have included functional predictive analyses using the Tax4Fun open-source R package and our taxonomic callings derived from the SILVA database. No new inferences resulted from the additional analysis, but this in itself is intriguing given the significant differences in beta diversity between fish species and within species by habitat. We agree that this will be an important tool in fish microbiome research and applying it in this study will hopefully lead to additional and larger studies applying these methods/analyses to understand the functional role of the fish microbiome in physiology. ---------- Validity of the findings Given the high interindividual variation in animals such as fish, choosing a proper sample size is a critical factor for the microbiome analysis. While the methodology used in this manuscript followed the state of art approaches, the small sample size selected in this study could be a problem for reproducing the same findings by another research. Please see our response to small sample size above. ---------- ---------- Reviewer: 3 Basic Reporting: Concerning your interest for additional information on factors that influence the fish gut microbiome, we have included additional citations in the introduction. Additionally, we point you to the recently published review Gallo et al. 2020 (https://doi.org/10.1002/fsh.10379) that goes into detail about factors/influences on the fish gut microbiome. We have also improved the introduction section to eliminate redundancy and facilitate the ease of reading. We have chosen to not modify our title as our resubmitted manuscript has shifted away from highlighting the SOP (because we were/are unable to test direct protocol comparisons) and focused instead on our species and habitat level results. We are hopeful our findings and detailed protocols (which will be made publicly available) will add to the fish gut microbiome field. ---------- Experimental Design: The section material and method are very clear, however, along with the description there is some lack of information that requires description: It is important to describe the sampling time and the season. In the case of environmental studies of the gut microbiome in fish, the season time has shown to have a very important effect on the feeding behavior of the animals. As well, if the animals were sampled at different days or different sampling times, they could have been affected by the digestion process as the animals in nature compared with cultured fish have their feed all time. As well, to know the size of the animals caught would be very helpful in order to have an idea of the life stage of the animals studied which complements the fact of their different trophic feeding behavior. We now include a metadata table (Supplementary Table S1) describing all the relevant information pertaining to capture and sampling of the fish in our study. We did not record exact sampling time of day when capturing fish samples, but we did record the sampling date. Important to note that from capture to euthanasia/processing was less than 3 hours. Concerning your comment about gut microbiome turnover throughout the day, we were unable to find any specific instances in the literature that examined microbiota turnover within this fine timescale (e.g. hours). It is true that the gut microbiome can be influenced by seasonal variation (such as in the mouse gut microbiome (doi: 10.1038/ismej.2015.53)). There are also instances where there is very little change in gut microbiota between seasons, as seen in farmed Atlantic Salmon (doi: 10.1111/j.1365-2109.2011.02805.x). Most of this is likely linked with the animal’s diet. Nonetheless, it would be difficult to distinguish these differences based on the individual digestive processes going on within individual fish without controlled experiments. Additionally, given our focus on the autochthonous bacterial community, we flush out all gut digesta, which may help eliminate individual fish diet bias. ---------- The paragraph between line 189 to 191, the statement of the Atlantic salmon: This statement requires to be rephrased. The information is a little confusing. Inline 54, eliminating the word can. In the sampling procedure, did you consider sampling some water? We have also removed our statement about Atlantic salmon initially at line 189-191. We did not sample water as part of this study – instead focusing solely on the fish gut microbiome. ---------- Validity of the Findings: 1)if the 2 euthanasia protocols used in the sampling time could affect the gut microbiome composition. It has been shown that the psychical stress caused by human handling can affect the gut microbiome in fish. Concerning your euthanasia comment, we followed protocols that are commonplace in the fish gut microbiome field. We have also included in the methods section of our manuscript that all fish were euthanized within approximately 3 hours of capture. Baited minnow traps / hoopnets were used to capture some fish, but nets were only allowed to soak for a maximum of 18-24 hours. We did not take into account the physical stress of handling the fish prior to euthanasia, but we tried to keep handling to a minimum and treated all fish in the same fashion to eliminate such bias. When reviewing the literature regarding this concern, we found that influences of external stress (such as change in pH) can influence the skin and gut microbiota of fish (doi: 10.1038/srep32032) but fish were only measured at time points of 0, 7, and 14 days. This study also indicated that the fecal/gut microbiome may have higher resilience to resist changes to pH compared to cutaneous/skin microbiota. We could not find examples in the literature that took into account the effect of stress on the fish gut microbiota on time scales of less than 24 hours. ---------- 2) The possible effect due to washing and removal of the digestive feed on the DNA extraction as well need to be considered. It has been shown that this could cause some troubles in the bacterial DNA extraction in gut microbiome studies. We focus on the autochthonous community of microbiota in the fish gut, and we treated all of our samples identically in this manner to reduce sample bias. Difficulty may exist with bacterial DNA extraction from intestinal mucosa, so we extracted DNA from the entire washed integument tissue, which helped prevent issues with DNA extraction. Additionally, we followed protocols similar to that used in previously published articles focusing on the autochthonous gut microbiome of fish ( https://doi.org/10.1111/j.1365-2761.2009.01052.x). In reviewing the literature on this subject, we were unable to find information suggesting that washing/digesta removal may influence DNA extraction. It likely would, however, remove organic inhibitors in the digesta to the extraction process. ---------- How could it be explained why the microbial composition in the governor’s islands is so disperse compared to the eagle wings? It is unknown as to why the microbial composition is so dispersed at Governor’s Island vs. Eagle Wings. We believe diet and/or water temperature may be contributing factors to the given differences. The shallow water Governor’s Island Gobies may have access to a more varied diet and warmer water temperatures in the shallower water may promote the growth of more varied microbiota. We have added literature (Farrell et al. 2010) that describes shallow to deep profundal benthic habitat difference in this section of the St. Lawrence River. This experiment was meant to be exploratory in nature, and therefore we could not fully address these and similar questions with our results. It certainly warrants follow-up investigations though to determine additional factors driving differences in the Round Goby gut microbiome. ---------- As well, why is it so abundant the presence of bacterial strains like Aeromonas and Clostridium that has been associated with fish disease? Regarding the reviewer’s comments on the presence of potential disease causing bacterial genera we agree this is perplexing. However, there is evidence that some species of Aeromonas may be commensals in the fish gut, helping play roles with digestion (doi:10.1111/j.1365-2109.2010.02546.x). Clostridium species have also been linked with heightened growth performance in shellfish (https://doi.org/10.1016/j.fsi.2017.03.048). There are potentially many commensal bacteria that fall into these genera and this study was unable to differentiate specific Aeromonas and Clostridium species. Additionally, these bacteria may be opportunistic, and presence may not always correlate with disease or gross manifestation of disease. ---------- The possible differences between Round Goby at different depths should consider the effect of the two different sample points besides the depth. It will be very interesting to study if the NAP buffer will give the same results in the same samples at 4 weeks or 8 weeks prior to DNA extraction. Evidence from the initial publication on NAP Buffer (https://doi.org/10.1111/1755-0998.12108) indicates the solution can successfully preserve high molecular weight DNA for up to 10 months. Albeit working on a shorter time scale, literature evidence also supports high quality preservation of fecal microbiota for at least 10 days (https://doi.org/10.3389/fmicb.2017.00102). We therefore believe that there would be very little difference in microbiota between samples at 4 and 8-week time points. Nonetheless, we agree that your proposed study is necessary before validating our claim. NAP buffer has also been shown to out perform other methods of DNA storage in a side-by-side microbiome comparison study (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5281576/). We have added this reference to our paper. ---------- Prior to reading the manuscript, I thought the results section of the paper was going to be promising and relevant, but it is somehow light information. It would be better if the richness and diversity identified were presented on a table with other diversity indexes like Shannon, Simpson, etc. As well, a description of which bacteria genus shared between fish species and within species should be presented. How many OTUs they share as well. Figures 2 and 3: a) rarefaction curves require the legend reflecting sample label. We have included additional alpha diversity analyses (and subsequent plots) depicting the variation of gut microbiota within each of our sampled groups. And we have also completed PCoA analysis at your request to complement our initial NMDS. The PCoA’s (calculated using UniFrac distances) were very similar in shape and ordination to that of our NMDS plots. Pairwise UniFrac distances also indicate that there are significant differences between Round Goby vs. Yellow Bullhead and within Round Goby by habitat. All further suggesting differences we observed are true. We hope this addresses the reviewers concern. ---------- In the supplemental figure S2, the final word to describe will be location or habitat?. Finally, PCO plot graph seems better to describe the differences between species and habitat instead of a NMDS. The R2 and stress value is not the strongest in both compared factors. . We initially describe Governor’s Island as a shallow water habitat while the Eagle Wing’s is deepwater profundal, but throughout the manuscript we refer to the comparison by location instead of habitat, so we keep that naming convention for figure S2. As mentioned previously, we included PCoA plots in addition to our initial NMDS ordinations, and results were found comparable. We also agree our R2 values are low, but the inclusion of additional analyses/tests support our findings. Concerning our NMDS stress values, it is to our knowledge that stress values above 0.2 are deemed suspect, stress values between 0.1 and 0.2 are deemed fair, and stress below 0.05 denotes great fit (see Numerical Ecology by Legendre and Legendre 2012 (ISBN: 9780444538680) for further information on NMDS stress calculations). Our computed NMDS stress values were both well below 0.2, and therefore we consider these to be appropriate analyses for our data. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Research on the gut microbiome of host organisms has rapidly advanced with next generation sequencing (NGS) and high-performance computing capabilities. Nonetheless, gut microbiome research has focused on mammalian organisms in laboratory settings, and investigations pertaining to wild fish gut microbiota remain in their infancy. We applied a procedure (available at https://github.com/bngallo1994) for sampling of the fish gut for use in NGS to describe microbial community structure. Our approach allowed for high bacterial OTU diversity coverage (&gt;99.7%, Good's Coverage) that led to detection of differences in gut microbiota of an invasive (Round Goby) and native (Yellow Bullhead) collected from the upper St. Lawrence River, an environment where the gut microbiota of fish had not previously been tested. Additionally, results revealed habitat level differences in in gut microbiota using two distance metrics (Unifrac, Bray-Curtis) between nearshore littoral and offshore profundal collections of Round Goby. Species and habitat level differences in intestinal microbiota may be of importance in understanding individual and species variation and its importance in regulating fish health and physiology.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Bacterial communities inhabiting the alimentary canal of organisms, often referred to as the host's 'gut microbiome', have become a focal area of research over the last decade <ns0:ref type='bibr'>(Gallo et al. 2020)</ns0:ref>. Studies show that gut microbiota can greatly influence host growth and development <ns0:ref type='bibr' target='#b39'>(Lozupone et al. 2012)</ns0:ref>, behavior <ns0:ref type='bibr' target='#b27'>(Johnson and Foster 2018)</ns0:ref>, and immune system function <ns0:ref type='bibr' target='#b10'>(Colombo et al. 2015)</ns0:ref>. To date, the majority of gut microbiome research has focused on mammals as model organisms for understanding vertebrate microbial communities <ns0:ref type='bibr'>(Sullam et al. 2012)</ns0:ref>. Mammals though, comprise a relatively small proportion of the total vertebrate diversity, whereas fish represent ~50% <ns0:ref type='bibr'>(Sullam et al. 2012)</ns0:ref>. Nonetheless, little is known surrounding the ecology of host-borne microbes in fish, particularly what factors drive patterns of bacterial colonization and community assemblage <ns0:ref type='bibr' target='#b68'>(Tarnecki et al. 2017)</ns0:ref>. Because an organism's gut microbiome can influence many aspects of host physiology, describing the relative abundance of various microbes is an important first step in delineating organism and/or communities that either benefit or harm the host.</ns0:p><ns0:p>Several factors are known to modulate gut microbiota composition in fishes, including host species/genetics <ns0:ref type='bibr' target='#b36'>(Li et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b32'>Li et al. 2014)</ns0:ref>, feeding habits <ns0:ref type='bibr' target='#b44'>(Michl et al. 2017)</ns0:ref>, trophic levels <ns0:ref type='bibr' target='#b37'>(Liu et al. 2016)</ns0:ref>, disease prevalence in the host population <ns0:ref type='bibr'>(Hennersdorf et al. 2016)</ns0:ref>, and environmental variables including habitat and husbandry practices <ns0:ref type='bibr' target='#b13'>(Dehler et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b73'>Wu et al. 2012)</ns0:ref>. Recent research on euryhaline fish has indicated that habitat salinity also plays a significant role influencing the dominant gut microbiota <ns0:ref type='bibr' target='#b62'>(Schmidt et al. 2015)</ns0:ref>. Additionally, laboratory studies investigating the gut microbiota of Zebrafish Danio rerio demonstrate taxonomic similarities despite being raised in different aquaculture facilities <ns0:ref type='bibr'>(Roeselers et al. 2011</ns0:ref>). However, Zebrafish gut microbiota was also shown to differ temporally during ontogeny, highlighting the dynamic nature of gut-borne microbial communities <ns0:ref type='bibr'>(Stephens et al. 2016</ns0:ref>).</ns0:p><ns0:p>Additional research is warranted to understand how gut microbial communities develop in nature in order to elucidate the beneficial and deleterious interactions between gut microbes and fish host.</ns0:p><ns0:p>The objective of this study was to adapt a mammalian-based gut microbiome sampling and sequencing protocol to explore the gut microbiota from two fish species from the upper St.</ns0:p><ns0:p>Lawrence River. We collected fish mucosal digesta to test for differences in the autochthonous gut microbiome of Round Goby (Neogobius melanostomus) and Yellow Bullhead (Ameiurus natalis). Yellow Bullhead, a native species to the upper St. Lawrence River, consumes small fish and crustaceans <ns0:ref type='bibr' target='#b63'>(Stegemann 1989</ns0:ref>) whereas the invasive Round Goby diet is often dominated by invasive Zebra Mussels Dreissena polymorpha <ns0:ref type='bibr' target='#b53'>(Ray and Corkum 1997)</ns0:ref>. Furthermore, Round Goby generally prefer hard substrate in both shallow and deepwater habitats <ns0:ref type='bibr' target='#b9'>(Charlebois et al. 2001)</ns0:ref> while Yellow Bullhead prefer soft substrates in vegetated areas of shallow lakes, reservoirs, and streams <ns0:ref type='bibr' target='#b63'>(Stegemann 1989</ns0:ref>). These diet and habitat differences, in addition to known interspecies variation in fish gut microbiota <ns0:ref type='bibr' target='#b36'>(Li et al. 2012</ns0:ref>) provide a scenario for testing expected differences with the NGS workflow.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head><ns0:p>Data Collection &amp; Field Processing. -Collection of fish took place on the upper St. Lawrence River and its tributaries in Clayton, NY (Fig. <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>). All specimens were collected through volunteer angling, baited minnow traps, or fine mesh hoopnets and under permit from the New York State Department of Environmental Conservation (license #354). Capture date, total length (mm), and total weight (g) were recorded for each captured fish (Supplementary Table <ns0:ref type='table'>S1</ns0:ref>). Euthanasia of animals followed approved protocols outlined by the American Veterinary Association (AVMA) and the American Fisheries Society (AFS) through an overdose of Tricaine methansulfonate (400+ mg/L) or blunt cranial concussion (State University of New York College of Environmental Science and Forestry's Institutional Animal Care and Use Committee protocol #180202). All fish were euthanized within approximately 3 hours of capture and minnow traps / hoopnets were allowed to soak for a maximum of 18-24 hours. There was no mixing of species or within species by sampling location prior to euthanasia to ensure no sharing of water and potential transfer of microbiota. Fish gut microbiota comparisons involved eight Round Goby captured at Governors Island (shallow littoral: &lt;2m water depth) and seven Round Goby at the Eagle Wings Islands (deepwater profundal: &gt;15m water depth). Seven Yellow Bullhead were also sampled in French Creek (coastal wetland tributary: &lt;1m water depth). Due to sampling habitat limitations for Yellow Bullhead, sampling took place within only one site, and thus Yellow Bullhead were only utilized for inter-species analyses. Round Goby samples from the two separate habitats (Governors Island and Eagle Wings Islands) were combined for interspecies gut microbiota analysis but analyzed separately when testing for inter-habitat gut microbiota associations.</ns0:p><ns0:p>After euthanasia, the integument of each fish was surface sterilized by rinsing in a bath of 95% ethanol prior to dissection. All sample collection methods took place at room temperature (~ 20&#730;C). Fish were dissected with a posterior incision near the pectoral fin origin to the urogenital opening. Approximately 25 mg of hindgut tissue was aseptically removed from each fish using flame-sterilized dissecting scissors and/or scalpels. Digesta was manually cleared from the intestinal tract. Samples were then gently washed with a stream of sterile 0.05M phosphatebuffered saline (PBS) removing residual digesta while leaving autochthonous bacteria in the hindgut. All samples were stored in 1.75 mL of nucleic acid preservation buffer (NAP; 0.019 M ethylenediaminetetraacetic acid (EDTA) disodium salt dihydrate, 0.018 M sodium citrate trisodium salt dehydrate, 3.8 M ammonium sulfate, pH 5.2) allowing for ambient room temperature storage in sterile 2.0 mL microcentrifuge tubes <ns0:ref type='bibr' target='#b6'>(Camacho-Sanchez et al. 2013)</ns0:ref>.</ns0:p><ns0:p>Samples were stored for 4-8 weeks prior to DNA extraction. Previous examination of NAP buffer showed similar, if not superior, bacterial DNA preservation compared to commonly employed commercial buffers in comparative microbiome analyses <ns0:ref type='bibr' target='#b43'>(Menke et al. 2017)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:02:45747:2:0:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Laboratory Processing.-DNA was extracted using the E.Z.N.A &#174; Tissue DNA Kit (Omega Bio-Tek, Norcross, GA) following the manufacturers protocol, except that an overnight (15-17 hours) tissue lysis step was employed to assist in complete intestinal tissue digestion. Extracted DNA was stored at -20&#730;C until PCR was performed. To selectively amplify bacterial DNA extracted from the hindgut samples, PCR was conducted using 16S V6-V8 rRNA primers (B969F and BA1406R <ns0:ref type='bibr' target='#b11'>(Comeau et al. 2011)</ns0:ref>; Integrated DNA Technologies, Coralville, Iowa 52241) fused with unique barcodes and Illumina&#174; adapter sequences. Employing this method (primers fused with NGS barcodes and adaptor sequences) resulted in significant cost savings and eliminated further sample processing and amplification steps (see <ns0:ref type='bibr' target='#b12'>Comeau et al. 2017</ns0:ref>). The PCR master mix was created following <ns0:ref type='bibr' target='#b12'>Comeau et al. (2017)</ns0:ref> with the slight modification of using Q5&#174; High-Fidelity Taq polymerase (New England Biolabs, Ipswich, MA 01938). The PCR cycling protocol was as follows: initial denaturation of 95&#730;C for 30 seconds, followed by 35 cycles of 95&#730;C for 30 seconds, 55&#730;C for 30 seconds, 72&#730;C for 30 seconds, and a final extension step of 72&#730;C for 5 minutes. PCR amplicons (~600 bp) were verified by gel electrophoresis on a 2% agarose gel. Amplicon cleanup and NGS preparation took place using the Agencourt AMPure XP PCR purification kit (Agencourt Biosciences, Beverly, MA) and following manufacturer's protocol. NGS libraries were quantified via the Quant-iT dsDNA HS Assay (Invitrogen, Carlsbad, CA) following the assay's standard protocol. Fluorescence was read on a Biotek&#174; Synergy 2 plate reader (Agilent Technologies, Santa Clara, CA) and samples were subsequently converted from ng*&#181;l -1 to nM. The NGS library was diluted to a final concentration of 4nM and the normalized libraries were pooled. For loading on the sequencer, 5&#181;l of the library pool was added to 5&#181;l freshly prepared 0.2M sodium hydroxide, mixed well, and incubated at ambient temperature for 5 minutes. This was followed by an addition of 990&#181;l of pre-chilled Illumina&#174; HT1 buffer, creating a final 20pM library concentration. The prepared library was sequenced on an Illumina&#174; MiSeq TM (San Diego, CA) using 2x300 v3 chemistry and a 10% PhiX spike at the SUNY Molecular Analysis Core (SUNYMAC) at SUNY Upstate Medical University (http://www.upstate.edu/sunymac/).</ns0:p><ns0:p>Dataset organization for Analyses.-For all described analyses, Round Goby and Yellow Bullhead samples were organized into two distinct datasets: (1) gut microbiota vs. fish species (15 Round Goby vs. 7 Yellow Bullhead) and (2) gut microbiota vs. fish habitat (7 Eagle Wings Islands Round Goby vs. 8 Governors Island Round Goby). All quality filtering, OTU clustering, and multivariate comparison procedures were identical between group analyses.</ns0:p><ns0:p>Sequenced Data Processing and Analysis. -Raw reads have been deposited with links to BioProject accession number PRJNA528762 in the NCBI BioProject database (https://www.ncbi.nlm.nih.gov/bioproject/). Sequenced libraries were demultiplexed in MiSeq TM Reporter v2.6 and FASTQ files were processed using USEARCH v.11.0.667 <ns0:ref type='bibr' target='#b14'>(Edgar 2013)</ns0:ref>.</ns0:p><ns0:p>FASTQ sequences were stitched and filtered to the approximate size of the V6-V8 region of the bacterial 16S rRNA gene (400-600 bp length; <ns0:ref type='bibr' target='#b12'>Comeau et. al 2017)</ns0:ref>. USEARCH was used to trim primer regions and remove chimeric and low-quality sequences. Next, reads were merged based on similarity (400-600 bp in length, had &#8804;5 nucleotide differences, and were &#8805;90% similar).</ns0:p><ns0:p>Sequences were filtered with the maximum expected errors per sequence &#8804;0.5. These cutoffs followed default or more stringent parameters as outlined in the USEARCH guide (https://www.drive5.com/usearch/). Filtered reads were subsequently preclustered by size (99% similarity, maximum differences &#8804;4) and then clustered into Operational Taxonomic Units (OTUs) based on 97% similarity using the UPARSE algorithm <ns0:ref type='bibr' target='#b14'>(Edgar 2013)</ns0:ref>. USEARCH filtering and subsequent OTU clustering was conducted with singleton data (OTUs with single DNA sequence occurrence), as procrustes analysis revealed non-significant differences between singleton and non-singleton multivariate ordinations (package 'vegan', function 'protest()', Procrustes analysis: SS = 2.47 x 10 -4 (Species Comparison) &amp; 1.66 x 10 -4 (Habitat Comparison), P &#8804; 0.001 (Species Comparison) &amp; P &#8804; 0.001 (Habitat Comparison); Supplemental Fig. <ns0:ref type='figure' target='#fig_5'>S2 &amp; S3</ns0:ref>). All USEARCH scripts utilized in these analyses can be retrieved from our GitHub page (https://github.com/bngallo1994)</ns0:p><ns0:p>The USEARCH generated OTU tables were modified into a shared compatible file and uploaded into Mothur v.1.39.5 <ns0:ref type='bibr'>(Schloss et al. 2009</ns0:ref>). Rarefaction files were subsequently created using the Mothur MiSeq TM Standard Operating Procedure (https://www.mothur.org/wiki/MiSeq_SOP). OTU tables were modified to make rarefaction files to estimate species richness. Because of error rates, singleton calls using NGS platforms can be interpreted as potential sequencing artifacts <ns0:ref type='bibr'>(Brown et al. 2015)</ns0:ref>. Nonetheless, subsequent analysis from the most dominant OTU's in each dataset revealed negligible differences in community structure between singleton-included and excluded microbiota matrices (data not shown). Rarefaction curves utilizing singleton OTUs thus served as a maximum estimate of total species richness are presented in this manuscript.</ns0:p><ns0:p>The SILVA 138 high quality ribosomal RNA database was used to determine the identity of the most abundant OTUs in each fish species <ns0:ref type='bibr' target='#b50'>(Quast et al. 2013)</ns0:ref>. We queried all OTU16S rRNA sequences using SILVA's Alignment, Classification and Tree Service (ACT) web module (https://www.arb-silva.de/aligner/) <ns0:ref type='bibr' target='#b49'>(Pruesse et al. 2012)</ns0:ref>. OTU sequences were classified with a minimum query sequence identity of 95% and 10 neighbors per query sequence</ns0:p><ns0:p>The SILVA generated taxa information was subsequently combined with the USEARCH OTU table and sample metadata into a single phyloseq class object using the bioconductor To estimate the microbial community coverage, OTU tables and rarefaction data files were analyzed using the entropart (v 1.5-3; Marcon 2018), ggplot2 (v 3.0.0; Wickham 2016), and vegan (v 2.5.2; <ns0:ref type='bibr' target='#b46'>Oksanen et al. 2018</ns0:ref>) packages of the R statistical software (R Core team 2017).</ns0:p><ns0:p>Rarefaction analyses were paired with the calculation of Good's Coverage using the Chao method to provide a description of rarefaction in terms of the total sampled OTU diversity <ns0:ref type='bibr' target='#b18'>(Good 1953;</ns0:ref><ns0:ref type='bibr' target='#b7'>Chao 1984;</ns0:ref><ns0:ref type='bibr' target='#b31'>Larsen 2014)</ns0:ref>. Datasets were rarefied to normalized sequencing depth for comparisons of microbial relative abundances between samples. The instantaneous slope of each rarefaction curve was determined at this normalized depth <ns0:ref type='bibr' target='#b25'>(Hurlbert 1971)</ns0:ref>. To estimate OTU loss through normalization, we also compared the normalized species richness to the observed richness collected at each sample's maximum sequencing depth <ns0:ref type='bibr' target='#b8'>(Chao and Jost 2012)</ns0:ref>. These analyses quantitatively assessed our ability to detect a representative coverage of microbial DNA from wild caught Round Goby and Yellow Bullhead.</ns0:p><ns0:p>A number of &#945;-diversity metrics were also calculated for all Round Goby and Yellow Bullhead samples. The Observed, Chao1, Shannon, and Simpson indices were calculated to estimate &#945;-diversity between the two fish species and within Round Goby by habitat.</ns0:p><ns0:p>Significance between groups was tested from each index with Wilcoxon rank-sum tests (Mann-Whitney) using the <ns0:ref type='bibr' target='#b47'>Benjamini and Hochberg (1995)</ns0:ref> p-value correction method.</ns0:p><ns0:p>Non-metric multidimensional scaling (NMDS) was employed to visualize dissimilarity in datasets between samples. NMDS (R package 'vegan', function 'metaMDS') ordination was computed for both normalized habitat and species datasets. NMDS scaling <ns0:ref type='bibr' target='#b30'>(Kruskal 1964</ns0:ref>) was used to visualize the Bray-Curtis dissimilarity <ns0:ref type='bibr' target='#b3'>(Bray and Curtis 1957)</ns0:ref> between samples using default permutations (n=20) in the 'metaMDS' function in the vegan. Permutational multivariate analysis of variance using distance matrices (PERMANOVA, package 'vegan', function 'adonis'; 999 permutations) was employed to assess significant differences (&#945; = 0.05) between the two datasets: (species comparison = Round Goby and Yellow Bullhead; habitat comparison = Round Goby shallow and deeper profundal habitat). Due to the sample size differing by one individual, we assumed a balanced design and followed the recommendations of <ns0:ref type='bibr' target='#b2'>Anderson and Walsh (2013)</ns0:ref>; PERMANOVA remains robust in the presence of heterogeneity of group dispersion.</ns0:p><ns0:p>In addition to NMDS, &#946;-diversity was compared between fish species and habitat using pairwise weighted UniFrac distances <ns0:ref type='bibr' target='#b38'>(Lozupone and Knight 2005)</ns0:ref>. Unifrac distances were calculated between all combinations of Round Goby and Yellow Bullhead (for the species comparison) and Governor's Island and Eagle Wings Round Goby (for the habitat comparison).</ns0:p><ns0:p>Similar to the NMDS ordinations, weighted Unifrac distances were visualized using Principal Coordinate Analysis (PCoA) while retaining the first two axes. Welch's two sample t-tests were conducted to determine if weighted Unifrac distances between sample groups was significant.</ns0:p><ns0:p>These distances were subsequently plotted (&#177; SE) to visualize differences in gut microbiota by fish species and habitat.</ns0:p><ns0:p>Predictions of microbial community functions were assessed using the 'Tax4Fun' <ns0:ref type='bibr' target='#b1'>(A&#223;hauer et al. 2015)</ns0:ref> and 'themetagenomics' <ns0:ref type='bibr'>(Woloszynek et al. 2017</ns0:ref>) R packages. 16S rRNA marker gene functions were linked to SILVA database Kyoto Encyclopedia of Genes and Genomes (KEGG) orthologs (KOs) using the MoP-Pro approach to determine predictive function relative gene abundance for each gut microbiota sample <ns0:ref type='bibr' target='#b0'>(A&#223;hauer and Meinicke 2013)</ns0:ref>.</ns0:p><ns0:p>The top 20 KO's were then screened <ns0:ref type='bibr'>(Yang et al. 2019</ns0:ref>) and plotted on bar graphs to related relative gene abundance vs. fish species or capture location (for Round Goby). Orthologs that did not link to a specified level one KEGG pathway were excluded from the analyses, and the next most abundant was substituted. Functions were combined based on level one as defined by the KEGG pathways output. Significance testing comparing the gut microbiota samples was performed using Welch's two sample t-tests.</ns0:p><ns0:p>Supplementary Data Processing and Analysis Information.-All procedures including tissue sampling, DNA extraction, PCR, amplicon cleanup, NGS library preparation, and downstream FASTQ processing as well as all code are detailed on our GitHub page (https://github.com/bngallo1994).</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>NGS Sequencing</ns0:head><ns0:p>Species and habitat comparison datasets yielded 3.01 and 1.90 million paired-end sequenced reads, respectively, each passing our pre-defined USEARCH quality filter. Final reads clustered into 1,266 OTUs and 574 OTUs in species and habitat comparison OTU tables, respectively. Rarefaction analyses (Fig. <ns0:ref type='figure' target='#fig_4'>2A</ns0:ref> &amp; 3A) indicated plateauing of OTU detection at approximately 20,000-30,000 reads/sample, but novel OTU's were still detected at upwards of 100,000 reads / sample, especially in Yellow Bullhead. The mean number of reads/sample &#177; SE was 136,959 &#177; 776 with a mean of 126,739 &#177; 967 for Round Goby and 158,858 &#177; 1,283 in Yellow Bullhead. Analysis of rarefaction data using Good's Coverage at the normalized sequencing depth indicated samples represented &gt; 99.7% coverage of OTU diversity in both datasets (Tables 1).</ns0:p><ns0:p>Slope analysis of normalized rarefaction curves indicated high rates of microbe OTU detection at low sequencing depth and low novel OTU detection at higher sequencing depth.</ns0:p><ns0:p>Discovery rates of OTUs/1000 sequences show the slope of the normalized rarefaction curves were between 0.091-2.66 OTUs/1000 sequences between both datasets. Further validation of our high OTU coverage was seen comparing the OTU species richness at the normalized sequencing depth to maximum sequencing depth for each sample. The calculated highest sequencing depth provided an average &#177; SE increase of 32 &#177; 14 OTUs and 11 &#177; 4 OTUs for the species and habitat datasets respectively (Supplemental Tables <ns0:ref type='table'>S2 &amp; S3</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:02:45747:2:0:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Comparing Round Goby and Yellow Bullhead Gut Microbiota (SPECIES) and Round Goby Microbiota at the Eagle Wings Islands and Governor's Island (HABITAT)</ns0:head><ns0:p>Permutational analysis of variance (PERMANOVA) on the species comparison NMDS ordination (Fig. <ns0:ref type='figure' target='#fig_4'>2B</ns0:ref>) indicated a significant difference between Round Goby and Yellow Bullhead gut microbial communities (PERMANOVA: Pseudo F = 7.88, df = 1, P = 0.003, r 2 = 0.28, NMDS stress = 0.14). Two distinct groups are evident with 95% confidence ellipses displaying little overlap (Fig. <ns0:ref type='figure' target='#fig_4'>2B</ns0:ref>). Similar patterns were observed with the weighted Unifrac PCoA ordination (Axes 1 + 2 accounting for over 73% of total data variation (Supplemental Fig</ns0:p></ns0:div> <ns0:div><ns0:head>S3)).</ns0:head><ns0:p>OTU identification in both Round Goby and Yellow Bullhead also showed differences in the bacterial composition of dominant microbes in each of the fish species. Parsing the present microbiota by relative abundance, the top 10 OTUs (Fig. <ns0:ref type='figure'>4</ns0:ref>) using the SILVA database showed Aeromonas spp. (OTU1, 66.9 &#177; 8.7%), Cetobacterium spp. (OTU2, 10.1 &#177; 6.4%), and Streptococcus spp. (OTU5, 4.4 &#177; 3.3%), as the most abundant taxa in the gut microbiota of Round Goby. While Cetobacterium spp. (OTU2, 39.7&#177; 14.7%), Clostridium sensu stricto 1 (OTU7, 25.7 &#177; 8.7% and Aeromonas spp. (OTU1, 14.8 &#177; 9.4%) were the most abundant bacteria in Yellow Bullhead.</ns0:p></ns0:div> <ns0:div><ns0:head>Similar analyses comparing Round Goby sampled between Governors Island and the</ns0:head><ns0:p>Eagle Wings Islands (Fig. <ns0:ref type='figure' target='#fig_5'>3B</ns0:ref>) also revealed differences in their gut microbial composition (PERMANOVA: Pseudo F = 2.63, df = 1, P = 0.03, r 2 = 0.17, NMDS stress = 0.04). PCoA ordinations showed similarity to the NMDS plot (supplemental Figure <ns0:ref type='figure'>S4</ns0:ref>), and the plotted principal components accounted for over 89% of the data's variation. Additionally, differences were observed in the dominant gut microbiota from Round Goby at each location (Fig. <ns0:ref type='figure' target='#fig_6'>5</ns0:ref>). The Eagle Wing's Round Goby gut samples were dominated by Aeromonas spp. (OTU1, 88.9 &#177; 4.0% ), Shewanella spp. (OTU8, 4.2 &#177; 2.7%), and Corynebacterium spp. (OTU14, 1.1 &#177; 0.7%) while Governors Island Round Goby guts were largely colonized by Aeromonas spp. (OTU1, 47.3 &#177; 12.4%), Cetobacterium spp. (OTU2, 18.6 &#177; 11.6%) and Streptococcus spp. (OTU3, 8.1 &#177; 6.1%) bacteria. In both comparisons, the Top 10 dominant bacteria accounted for over 89% of the total microbiota observed.</ns0:p><ns0:p>Despite the observed differences in the dominant taxa between and within sampled fish gut microbiota, no significant differences existed for any &#945;-diversity metrics, including the Observed, Chao1, Shannon, and Simpson indices (P-values &gt; 0.18) among species (Fig. <ns0:ref type='figure' target='#fig_7'>6</ns0:ref>).</ns0:p><ns0:p>Similar trends were seen within Round Goby through the habitat comparison (P-values &gt; 0.23; Fig. <ns0:ref type='figure' target='#fig_8'>7</ns0:ref>). UniFrac distances however, revealed higher variance in the gut bacterial community between species (RG: t = -4.11, df = 293.37, P &lt; 0.001 &amp; YB: t = 3.20, df = 84.47, P = 0.002) compared to within species (Fig. <ns0:ref type='figure'>8</ns0:ref>). For Round Goby, additional Unifrac distance testing indicated a significant difference in bacterial community variation between habitats (t = 11.30 df = 50.49, P &lt; 0.001). Round Goby from the deepwater habitat (Eagle Wings Islands) demonstrated the least amount of variation in gut microbial composition while those from the nearshore littoral Governors Island had the greatest amount of variation (Fig. <ns0:ref type='figure' target='#fig_9'>9</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Comparing Round Goby and Yellow Bullhead Gut Microbiota Predicted Functions using Tax4Fun</ns0:head><ns0:p>Predictions of microbial community functions using KEGG Orthologs (KO) indicated no significant differences in predicted microbial functions associated with our species and habitat comparisons. Mapping of the Top 20 KO's that matched to KEGG pathways revealed only slight differences in microbial community gene abundances linked with environmental information processing, cellular processes, metabolic pathways, and genetic information processing (Fig. <ns0:ref type='figure' target='#fig_3'>10</ns0:ref> + 11). There were no significant differences in the top 20 KO's for the species comparison for environmental information processing (t = 0.28, df = 9.22, P = 0.79), cellular processes (t = 0.18, df = 10.07, P = 0.86), metabolic pathways (t = 0.58, df = 19.75, P = 0.57), and genetic information processing (t = -0.19, df = 9.36, P = 0.86). Similar conclusions were drawn from analysis of the top 20 KO's for the habitat comparison for Round Goby (environmental information processing: t = -1.86, df = 7.00, P = 0.11; cellular processes: t = 0.18, df = 10.07, P = 0.86; metabolic pathways: t = 1.93, df = 7.13, P = 0.09; genetic information processing: t = 1.75, df = 7.05, P = 0.12). This all stands in contrast to the aforementioned significant differences in overall gut microbiota both between and within species as seen through our &#946;-diversity analyses.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion.</ns0:head><ns0:p>Our data revealed fish gut microbiota differences between invasive Round Goby and native Yellow Bullhead in the upper St. Lawrence River. Our findings add to previous research that describes microbial community dissimilarities in various fish species employing a range of Manuscript to be reviewed sequencing methods (Denaturing Grade Gel Electrophoresis <ns0:ref type='bibr' target='#b36'>(Li et al. 2012)</ns0:ref>; Pyrosequencing <ns0:ref type='bibr' target='#b32'>(Li et al. 2014</ns0:ref>)) as well as amplifying different variable regions of the 16S rRNA gene (V4 region; <ns0:ref type='bibr' target='#b37'>Liu et al. 2016)</ns0:ref>. Both NMDS and PCoA analyses support overall microbial composition differences between these fish species and results from the SILVA database indicated dominance of specific bacterial genera in each species' gut microbiome. Additional hypothesis testing using PERMANOVAs and weighted Unifrac distances further verified that significant differences in &#946;diversity were present both between Round Goby and Yellow Bullhead, and within Round Goby caught at the Eagle Wings and Governor's Island.</ns0:p><ns0:p>The observed prominence of Aeromonas spp., Cetobacterium spp., and Clostridium spp.</ns0:p><ns0:p>in the fish gut is consistent with reports by others including Aeromonas spp. <ns0:ref type='bibr'>(Wu et al. 2013;</ns0:ref><ns0:ref type='bibr' target='#b35'>Li et al. 2016)</ns0:ref>, Cetobacterium spp. <ns0:ref type='bibr' target='#b33'>(Li et. al 2015)</ns0:ref>, and Aeromonas spp. and Cetobacterium somerae <ns0:ref type='bibr' target='#b31'>(Larsen et al. 2014</ns0:ref>). In addition to microbial differences noted between fish species, we also report interspecies variation in gut microbiota between the same species (Round Goby) captured in different habitats separated by a water depth gradient. Simulation analysis from <ns0:ref type='bibr' target='#b2'>Anderson and Walsh (2013)</ns0:ref> suggests PERMANOVA analysis is robust even with heterogeneity of variance between groups under a balanced design. Larger scale sampling from multiple locations with a balanced sampling design is recommended to better understand patterns of within species differences in microbiome among habitats. Future studies should take into account size and/or age bias with Round Goby, given the differences in average size of the captured Round Goby by habitat (150mm at Governor's Island vs. 113mm at the Eagle Wings). Previous research on Zebrafish has indicated that gut microbiota can vary with age/development <ns0:ref type='bibr'>(Stephens et al. 2016)</ns0:ref> and by seasonal sampling <ns0:ref type='bibr' target='#b54'>(Naviner et al. 2006)</ns0:ref>. All fish associated with this study were captured within an 11-day period during the fall of 2017, however observed differences in gut microbiota may not be present throughout all seasons. These variables will need to be controlled in future studies that increase sampling frequency spatiotemporally to extend our finding in a simple case.</ns0:p><ns0:p>The presence of specific and novel OTUs is particularly interesting when hypothesizing the microbiota's role in the gut community and its effect on fish hosts. For example, some species of Aeromonas act as opportunistic pathogens and cause various hemorrhagic fish diseases like furunculosis <ns0:ref type='bibr' target='#b23'>(Hidalgo et al. 2012)</ns0:ref>. Although Aeromonas spp. were routinely detected in fish guts in this study, we observed no obvious tissue hemorrhaging. However, we were unable to resolve Aeromonas sequences to the species level and were not able to determine if the specific Aeromonas bacteria present were known fish pathogens. This was most likely due to high heterogeneity of the 16S gene in Aeromonas bacteria <ns0:ref type='bibr' target='#b26'>(Janda and Abbott 2007)</ns0:ref>.</ns0:p><ns0:p>Sequencing with additional universal gene primers (e.g., cpn60 <ns0:ref type='bibr' target='#b45'>(Mi&#241;ana-Galbis et al. 2009</ns0:ref>) may help reveal species delineation in Aeromonas bacteria. Additional microbial genera detected in this study are also known to be beneficial and/or detrimental to their hosts. For example, bacteria of the genera Clostridium produce various essential fatty acids and vitamins <ns0:ref type='bibr' target='#b55'>(Ring&#248; et al. 1995;</ns0:ref><ns0:ref type='bibr' target='#b20'>Givens 2014</ns0:ref>) despite some species like Clostridium difficile, which can opportunistically cause pseudomembranous colitis <ns0:ref type='bibr' target='#b28'>(Kelly et al. 1994)</ns0:ref>. Moreover, the bacterium Cetobacterium somerae, the most abundant genera discovered in the gut microbiome of Yellow Bullhead in our study, is known to synthesize vitamin B12 in the fish gut <ns0:ref type='bibr' target='#b69'>(Tsuchiya et al. 2007)</ns0:ref>. Regardless, 16S predictive functions derived from our Tax4Fun analyses were unable to identify microbiota functional patterns between Round Goby and Yellow Bullhead and within Round Goby by sampled habitat. In order to gain a better understanding of potential gut microbiota function in the fish gut, sampling with shotgun sequence metagenomic analyses could be implemented with parallel 16S amplicon sequencing analysis. The 16S amplicon sequencing would help delineate relative abundance of microbiota, and metagenomic analysis would define individual microbes' complete genomes. Together these approaches may provide a more complete picture regarding the metabolic, pathogenic, and other characteristics associated with bacteria sampled from the fish gut. The need for metagenomic analysis in has been called for in recent reviews on the fish gut microbiome <ns0:ref type='bibr' target='#b68'>(Tarnecki et al. 2017;</ns0:ref><ns0:ref type='bibr'>Gallo et al. 2020</ns0:ref>) and implementation will almost certainly provide a better understanding on gut microbial functions that may significantly influence fish health.</ns0:p><ns0:p>In addition to the demonstration of microbial differences across species, NGS has the potential to detect minute differences in microbial communities within species. We employed an NGS workflow to investigate differences in gut microbiota in Round Goby samples from different habitats separated by less than 750 meters. Evidence for environmental differences in fish gut microbiota has been previously noted in the Atlantic salmon parr gut microbiome <ns0:ref type='bibr' target='#b13'>(Dehler et al. 2017)</ns0:ref> and in wild vs. aquaculture-reared fine flounder <ns0:ref type='bibr' target='#b52'>(Ram&#237;rez and Romero 2017)</ns0:ref>. Although our design did not take into account potential diet and habitat variation between the two samples of Round Goby, our data does support within-species differences at fine-spatial scales. A previous study in a nearby area of the St. Lawrence River indicated significant differences in total phosphorus and crustacean zooplankton abundance between shallow and deepwater stations <ns0:ref type='bibr' target='#b16'>(Farrell et al. 2010</ns0:ref>). These differences possibly extend to benthic invertebrates, including dressenid mussels known as important forage for Round Goby. Both Round Goby habitats were sampled at different depths (Governors Island: &lt;2m; Eagle Wings Islands: &gt;15m) and significant gut microbial community differences were noted, specifically with Aeromonas spp. (&gt;80% total Eagle Wings Islands reads vs. ~50% of Governors Island reads). Nonetheless, &#945;-diversity metrics indicated no differences in gut microbiota abundance in both our habitat and species comparisons. These analyses support that despite overall differences in the taxonomy of the bacteria, the diversity and evenness of the microbial communities within compared groups remained similar. The similarity in &#945;-diversity metrics especially within the species comparison may point to limited ecological niches for microbiota to inhabit in the fish gut. Therefore even though the microbiota identity differs between species, Bacteria having similar metabolic capacities / functions in the gut environment prevent large fluctuations in &#945;diversity between fish species. Future analysis derived from NGS microbial data coupled with biological (e.g., host diet, host habitat) and environmental factors (e.g., pressure, temperature, and light penetration) would help further define gut community structure differences observed between habitats and fish species.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In this study, we employed an NGS workflow and sampled gut microbiota for the first time from fishes along the upper St. Lawrence River. We implement analyses to test both interand intraspecific differences. We describe significant species level microbial community differences between an invasive (Round Goby) and native (Yellow Bullhead) fish species. We also describe significant differences between Round Goby sampled in different habits separated by only ~750 meters. This detailed workflow may help facilitate greater application of gut microbiome research and allow for the examination of numerous basic and applied questions (for examples see <ns0:ref type='bibr'>Gallo et al. 2020)</ns0:ref>. As NGS technologies and knowledge of host-microbe interactions continue to grow, investigations into the gut microbiome will undoubtedly improve our understanding of fish ecology and their conservation and management. The research methods Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 8</ns0:note><ns0:p>Pairwise UniFrac distances calculated from the OTU's derived from the species comparison.</ns0:p><ns0:p>The UniFrac analysis revealed higher variation in gut microbial communities between species than within species. Differences between letters above each barplot denote a significant difference in UniFrac distance (P-value &lt; 0.05).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:02:45747:2:0:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 10</ns0:note><ns0:p>Relative Gene Abundance of predicted microbial community functions from the species comparison, calculated using Tax4Fun and the Top 20 level one pathway KEGG Orthologs.</ns0:p><ns0:p>There were no significant species differences in microbial community functions pertaining to Environmental Information Processing (A), Cellular Processes (B), Metabolism (C) or Genetic Information Processing (D) for all measured level one KEGG Ortholog pathways (P-values = 0.79, 0.86, and 0.57, respectively).</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 11</ns0:head><ns0:p>Relative Gene Abundance of predicted microbial community functions from the habitat comparison, calculated using Tax4Fun and the Top 20 level one pathway KEGG Orthologs.</ns0:p><ns0:p>There were no significant habitat differences in microbial community functions pertaining to Environmental Information Processing (A), Cellular Processes (B), Metabolism (C) or Genetic Information Processing (D) for all measured level one KEGG Ortholog pathways (P-values = 0.11, 0.09, and 0.12, respectively).</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>package 'Phyloseq' (McMurdie and Holmes 2013). Two phyloseq objects were created -one for the Round Goby vs. Yellow Bullhead Species comparison, and one for the Governor's Island vs. Eagle Wings comparison for Round Goby. Additionally, we analyzed the top 10 OTUs from each dataset at normalized sequencing depth (species comparison: 41,250 sequences/sample; habitat comparison: 40,972 sequences/sample) to determine their average relative abundance in Round Goby and Yellow Bullhead. Using the same strategy, we determined the identity and relative abundance of the top 10 OTUs within each Round Goby habitat group (Eagle Wings Islands vs. Governors Island).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:02:45747:2:0:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:02:45747:2:0:NEW 24 Sep 2020)Manuscript to be reviewed developed and applied here are intended to promote such investigations, and aid researchers interested in studying gut microbiota.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 2 Rarefaction</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 3 Rarefaction</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 6 &#945;</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 7 &#945;</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 9 Pairwise</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Figure 9</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='34,42.52,275.62,525.00,349.50' type='bitmap' /></ns0:figure> </ns0:body> "

"Brian F. Leydet Jr. State University of New York College of Environmental Science and Forestry (SUNY-ESF) 1 Forestry Drive Syracuse, NY 13210 315-470-6942 [email protected] Craig Nelson Academic Editor; PeerJ Journal September 24th 2020 Dear Dr. Craig Nelson, I am pleased to submit revisions to our manuscript entitled “Use of next generation sequencing to compare simple habitat and species level differences in the gut microbiota of an invasive and native freshwater fish species” by Benjamin D. Gallo, Brian F. Leydet Jr., and John M. Farrell for consideration for publication in the journal PeerJ. My fellow authors and myself want to thank you for reviewing our submitted manuscript. We also want to thank the reviewers for their meticulous analysis of our original submission. We have responded to all the reviewers’ comments and concerns and have edited the manuscript accordingly. Please find, following this letter our point-by-point responses to each reviewer’s comments/concerns. Regards, Brian F. Leydet Jr, MPH, PHD Assistant Professor Epidemiology & Disease Ecology Dept. Environmental and Forest Biology SUNY – College of Environmental Science and Forestry 1 Forestry Drive Syracuse, NY 13210 Office: 315-470-6942 Email: [email protected] https://leydetlabesf/weebly.com/ Reviewer(s)' Comments to Author: Reviewer: 1 Comments to the Author Basic reporting The overall manuscript is good. The structure could be improved with a more in-depth literature review as noted. Some incorrect uses of references and is important homogenizes the terms like gut microbiota or gut microbiome along the document. Please check references and perhaps add some additional ones focused specifically on fish microbiomes in wild based on trophic habit and feeding strategies (i.e. The gut microbiome and degradation enzyme activity of wild freshwater fishes influenced by their trophic levels by Liu et al 2016). The tables and figures are ok. The github page in the abstract cited by the author shows that nothing is listed. This needs to be available to reviewers during the review stage. Thank you for your feedback based upon our revisions. Concerning your comments on homogenizing “gut microbiome” and gut microbiota” terminology, we have carefully gone through the manuscript and verified that the correct term is used in each instance. Gut microbiota details specific microorganisms within an organisms gut, skin, etc. Microbiome, on the other hand, refers to all the genomes of microorganisms in a specific habitat (see https://www.fiosgenomics.com/microbiome-vs-microbiota/) for more information. The terms are very similar but there are small differences that prevents us from using them interchangeably in the manuscript. Concerning our incorrect use of references, we ask that the reviewer points out specific cases in which we misused a specific reference. Additionally Liu et al. 2016 is already referenced on line 69. The exact URL for the github is still hidden to the public until the article is published, but the data / code used in this study was made available to the reviewers via a dropbox link provided to PeerJ upon manuscript submission (https://www.dropbox.com/sh/k6swfxt3mwq5d0u/AAB4XHM6UFjXl_Szxg5-sBtYa?dl=0). ---------- Experimental design The primary research aim should be very clear: you proposed a gut microbiome analysis comparing two different species (feeding strategies and locations-which this part is missing), and only compare habitat within the same fish species (RG).  We have amended our methods section to clearly state that Yellow Bullhead were only collected for inter-species gut microbiome analysis, as sampling limitations led to collection of Yellow Bullhead’s from only one location. Round Goby are ubiquitous throughout the Upper St. Lawrence River, and thus provided a greater opportunity for sampling from different habitats in the main river basin (i.e., shallow river channel vs. deepwater profundal). When they sampling the fish, they say the animals were euthanized within ~ 3 hours of capture; did they were kept together in the same container sharing the water during that time individually until euthanize and dissection?  Fish were brought back to the lab in water collected at the sampling site, and then were euthanized as described in the manuscript. Round Goby and Yellow Bullhead were not mixed, therefore there was no sharing of water between species or even within species by sampling location. We have added a sentence to reflect this in the manuscript. Back in the preservation method, although NAP buffer showed some promising results in one study for mammalian samples (Camacho 2013), it does not mean it provides the same good preservation picture for fish gut digesta.  Although the NAP buffer has not been previously documented to preserve gut microbiota from fish, the Menke et al. 2017 (DOI: 10.3389/fmicb.2017.00102) paper points to its efficacy for storing fecal microbiota from sheep, thus NAP showed promise for storing both mammalian and bacterial DNA, and we concluded it would be a good choice for our study. Comparing the ability of difference DNA storage buffers was not the focus of the current manuscript and has been addressed by others. ---------- Line-by-Line Review: Line 173: correct the upperSt; Response: There is no mention of the upper St. Lawrence River at line 173. We have reviewed the document and verified that the St. Lawrence River is punctuated correctly. ---------- Line 318: punctuations; Response: We have revised the sentence at lines 317-318 to better summarize the findings in Figure 9. ---------- Lines 443 and 727: correct parenthesis; Response: There is no text on line 443, and there is no line 727 in the document. Could you please clarify what lines you are specifically referring to? ---------- Line 732: never mention Cetobacterium somerae in the results (check this part) Response: Similar to our previous response, there is no line 732 in the document. Cetobacterium somerae is mentioned three times in the results section (Lines 298, 300, 312). ---------- For evenness should be calculated Shannon-evenness not only Shannon index line 781 Response: The Shannon index takes into account both species abundance and evenness (http://www.tiem.utk.edu/~gross/bioed/bealsmodules/shannonDI.html) and we chose to use this as it provides a better representation of differences in community structure ---------- Table 1 & 2 indicated in line 389 only shows one complete data set of coverage (description as well only say Table 1) Response: We only have one table in this manuscript – detailing the Good’s Coverage Index calculation for our species and habitat comparisons. No data is missing from the submitted table. ---------- Validity of the findings The calculation of alpha and beta diversity improves the results in the manuscript. There is some suggestion about how the alpha diversity index are presented. It would be better if the index results (figure 6 and 7) were presented on a table and diversity index like Simpson, and evenness index like Shannon-evenness could be added to it. How could you explain that the two different species didn’t show any significant difference among the 3 alpha diversity indexes? Figure 3AB: What would be the main reason that samples of the eagle wings are less disperse than the governors island. It will be interesting determining the number of OTUs shares between habitat and species, as well which genera are the ones that are unique in each fish species. Response: We have included the Simpson diversity index in our analysis, and we have included the alpha-diversity calculations in table format (supplemental tables). We have forgone the addition of Shannon-evenness, as the Shannon index itself takes into account species evenness, and the Shannon evenness only serves to normalize the Shannon index on a scale of 0 to 1. We have updated our explanation of why we believe alpha diversity is similar while beta diversity remains significantly different. In summation, we believe this may be a function of available ecological niche’s that microbiota inhabit in the species we investigated. Although further studies are required to validate this hypothesis. Concerning your comment about Figure 3AB, we briefly speak to our potential thoughts about the low dispersion in the Eagle Wings gobies at lines 413-422. Here we also speak to some major differences in observed microbiota between the Gobies at a fine spatial scale (namely Aeromonas spp. abundance). Teasing apart finer details between these locations was not within the scope of this study although follow-up experiments could target these questions. ---------- Comments for the Author With the changes made on the original manuscript clarify better the aim of it. The authors focused on pinpoint that there is significant difference between gut microbiome. Adding the PCO ordination, you can distinguish better a species effect and habit effect on GO based on samples collected with your method. Response: Thank you for your review and subsequent comments. We look forward to the final submission of this manuscript for publication. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Phascolosoma (P.) varians, a sipunculan species known from the Greater Caribbean, was designated as a synonym of Phascolosoma (P.) nigrescens, which was originally described from Fiji. Their synonymy was primarily based upon an interpretation that these two species were morphologically indistinguishable. After its designation as a synonym, no further detailed analyses of morphological or molecular characteristics were performed to corroborate the assumed widespread distribution of Phascolosoma (P.) nigrescens. In this study, Phascolosoma (P.) varians is redescribed, and notable differences between this species and its proposed senior synonym are presented. These two species differ in the shape of their hooks, the spatial attachment of nephridia to the body wall, and the morphology of the contractile vessel. Additionally, there is high genetic divergence between nucleotide sequences within their respective cytochrome c oxidase subunit 1 (COI) genes, which supports the morphological data. Herein, the synonymy of Phascolosoma (P.) varians with Phascolosoma (P.) nigrescens is rejected due to morphological and molecular differences. Furthermore, the assumed widespread distribution of Phascolosoma (P.) nigrescens is still considered as questionable.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The phylum Sipuncula comprised of 320 species as recorded by <ns0:ref type='bibr' target='#b45'>Stephen &amp; Edmonds (1972)</ns0:ref>, but after numerous revisions over a period of approximately twenty years by Edward and Norma Cutler, the total number was reduced to 149 valid species <ns0:ref type='bibr' target='#b11'>(Cutler, 1994)</ns0:ref>. The reduced number of sipunculan taxa may call into question previous records, lead to possible taxonomic errors among field investigators, and suggest that most, if not all, species have been accounted for. However, after 1994, 13 new species have been described <ns0:ref type='bibr' target='#b24'>(Kawauchi &amp; Rice, 2009;</ns0:ref><ns0:ref type='bibr' target='#b20'>Hylleberg, 2013;</ns0:ref><ns0:ref type='bibr' target='#b35'>Saiz et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b43'>Silva-Morales et al., 2019)</ns0:ref>. Importantly, in the Greater Caribbean region alone, 38 valid species have been recorded, of which 40% correspond to species with type localities outside of the Greater Caribbean, with 7 of those species belonging to Phascolosomatidae <ns0:ref type='bibr' target='#b30'>(Quiroz-Ruiz &amp; Londo&#241;o-Mesa, 2015)</ns0:ref>.</ns0:p><ns0:p>Reduction in the number of species by <ns0:ref type='bibr' target='#b11'>Cutler (1994)</ns0:ref> was performed by proposing extensive lists of synonyms, and when utilized by subsequent investigators, those lists have most likely led to a number of incorrect species identifications. For example, in the Greater Caribbean, P. (P.) nigrescens has been reported by <ns0:ref type='bibr' target='#b14'>Cutler &amp; Schulze (2004)</ns0:ref> from Barbados, <ns0:ref type='bibr' target='#b41'>Schulze &amp; Rice (2004)</ns0:ref> from Belize, <ns0:ref type='bibr' target='#b38'>Schulze (2005)</ns0:ref> from Panama, and Frontana-Uribe et al. <ns0:ref type='bibr'>(2018)</ns0:ref> from the Mexican Caribbean. These records may reflect the fact that <ns0:ref type='bibr' target='#b11'>Cutler (1994)</ns0:ref> considered the distribution of P. (P.) nigrescens as widespread and circumtropical, found generally between 30&#176; N and 30&#176; S in shallow waters of the Indian, Pacific, and Atlantic oceans.</ns0:p><ns0:p>The extensive synonymization approach by Cutler was proposed in part by an assumption that many sipunculan species have wide geographic distributions. Those with wide distributions were thought to be possible due to the high dispersal capability of species with teleplanic pelagosphera larvae, which were inferred to remain in the water column for up to six months base upon laboratory experiments <ns0:ref type='bibr' target='#b32'>(Rice, 1976)</ns0:ref>. Phascolosoma (Phascolosoma) varians has a Category 4 developmental pattern <ns0:ref type='bibr' target='#b31'>(Rice, 1970)</ns0:ref>: Indirect development with two pelagic larval stages, trochophore and planktotrophic pelagosphera. Planktotrophic pelagosphera larvae can be either short-lived (weeks) forms or larger long-lived (months) teleplanic larvae, as in P. (P.) varians <ns0:ref type='bibr' target='#b10'>(Boyle &amp; Rice, 2014)</ns0:ref>. The teleplanic larvae of the Phascolosomatidae are characterized by having cuticular papillae <ns0:ref type='bibr' target='#b37'>(Scheltema &amp; Rice 1990</ns0:ref>).</ns0:p><ns0:p>However, recent molecular analyses revealed potential taxonomic problems at the species level, where small morphological differences also were shown to correspond with distinct species, thus rejecting previously assumed wide distributions for some of those species <ns0:ref type='bibr' target='#b44'>(Staton &amp; Rice, 1999;</ns0:ref><ns0:ref type='bibr' target='#b22'>Kawauchi &amp; Giribet, 2010;</ns0:ref><ns0:ref type='bibr' target='#b39'>Schulze et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b23'>Kawauchi &amp; Giribet, 2014;</ns0:ref><ns0:ref type='bibr' target='#b21'>Johnson et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b43'>Silva-Morales et al., 2019)</ns0:ref>. Because of this, <ns0:ref type='bibr' target='#b25'>Kawauchi, Sharma &amp; Giribet (2012)</ns0:ref> proposed to clarify the taxonomic status of each species through a meticulous case-by-case analysis, integrating molecular data while considering that some species names that are currently hidden under synonyms deserve to be restored. In regards to molecular data, the mitochondrial cytochrome oxidase c subunit I (COI) an efficient identification tool for metazoan species, making it the core fragment for DNA barcoding <ns0:ref type='bibr' target='#b18'>(Hebert, Ratnasingham &amp; de Waard, 2003)</ns0:ref>. <ns0:ref type='bibr' target='#b26'>Keferstein (1865)</ns0:ref> described Phascolosoma (Phascolosoma) varians from St. Thomas, West Indies, and P. (P.) nigrescens from Fiji. <ns0:ref type='bibr' target='#b12'>Cutler &amp; Cutler (1983;</ns0:ref><ns0:ref type='bibr'>1990)</ns0:ref> reviewed the subgenus Phascolosoma (Phascolosoma), and redesignated 13 species, previously described and recorded from all around the world, as synonyms of P. (P.) nigrescens. The identification key by <ns0:ref type='bibr' target='#b11'>Cutler (1994)</ns0:ref> indicates that the diagnostic characters of P. (P.) nigrescens include the following: a distinct clear streak in particular hooks with observable swelling in the middle of vertical and horizontal portions. Phascolosoma (P.) varians was one of multiple species included as a junior synonym of P. (P.) nigrescens.</ns0:p><ns0:p>Herein, a detailed redescription of P. (P.) varians based upon topotypic specimens and additional material from other Caribbean localities is provided. Furthermore, P. (P.) varians is reinstated due to both morphological and molecular differences that distinguish it from its proposed senior synonym, P. (P.) nigrescens.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head><ns0:p>Specimens from the collections of the Marine Invertebrate Museum (UMML), Rosenstiel School of Marine and Atmospheric Science, University of Miami; Invertebrate Collections of the Florida Museum of Natural History (UF), University of Florida; and the Reference Collection of Benthos (ECOSUR) of El Colegio de la Frontera Sur, Chetumal, Mexico were reviewed.</ns0:p><ns0:p>Redescription of the species was primarily based upon a topotypic specimen, but additional materials from other Caribbean localities were also assessed for species-specific variations. Standardized descriptions included external and internal anatomy. The descriptions of hooks and papillae followed the terminology proposed by <ns0:ref type='bibr' target='#b11'>Cutler (1994)</ns0:ref>. To measure the angle between the primary tooth and the hook, a line X was drawn perpendicular to the base through the most anterior part of the concave side, and a line Y was drawn from the tip until intersect X in the middle of the point (see <ns0:ref type='bibr'>Cutler 1994:161-162, fig. 44A)</ns0:ref>.</ns0:p><ns0:p>Hooks and papillae were extracted with fine forceps for examination under an Olympus CH30 compound light microscope. Hooks were excised from three different regions (proximal, median and distal) of the ringed area of the introvert. Papillae were described from three different regions (anterior, median and posterior) of the trunk, and also from the distal introvert. Furthermore, these structures were examined using SEM to achieve a more detailed examination. For SEM preparation, the complete introvert was dehydrated through a series of increasing concentrations of hexamethyldisilazane (HMDS). Once air-dried, the introvert was mounted on an aluminum stub and coated with gold for observation with a JEOL JSM-6010Plus-LA scanning electron microscope at the Scanning Electron Microscopy Laboratory (LMEB), ECOSUR-Chetumal. Digital photographs of selected internal and external features were obtained with a Canon X6 digital camera mounted on a Leica MZ75 dissecting stereomicroscope. All images were rendered from a series of optical focal planes with HeliconFocus v6.7.1 (HeliconSoft 2007) to improve the depth of field for each specimen or set of specimens that were photographed.</ns0:p><ns0:p>For molecular analyses, eight COI sequences with an alignment length of 541 bp, from specimens identified as Phascolosoma (P.) nigrescens were retrieved from GenBank. One of them from Barbados (DQ300139), two from Florida (DQ300142, AY161122), one from Broome, Australia (DQ300143), two from New Caledonia (JN865121, JN865122), one from Israel (DQ300140), and another from South Africa (DQ300141). Also, a COI sequence from Phascolosoma (P.) granulatum Leuckart, 1828 (DQ300138) and two sequences from Phascolosoma (P.) agassizii Keferstein, 1866 (JQ904338, JQ904337) were included for comparison.</ns0:p><ns0:p>All sequences were aligned using the ClustalW method. Selection of the best model of substitution was determined according to the lowest Bayesian Information Criterion scores (BIC). From the BIC results, the Tamura 3-parameter <ns0:ref type='bibr' target='#b46'>(Tamura 1992</ns0:ref>) model with a discrete Gamma distribution (+G) with five categories, assuming a fraction of sites is evolutionarily invariable (+I), was selected to construct a tree by maximum likelihood analysis. The Kimura 2parameter model <ns0:ref type='bibr' target='#b27'>(Kimura 1980</ns0:ref>) was used to estimate the average evolutionary divergence over sequence pairs within and between species. All analyses were carried out with Mega 7 <ns0:ref type='bibr'>(Kumar, Stecher &amp; Tamura, 2015)</ns0:ref>. the base of the hook; secondary tooth rounded; internal clear streak (apical canal) expanded near to midpoint of vertical and middle horizontal portions of hook. Hooks of median region with a larger secondary tooth (Fig. <ns0:ref type='figure' target='#fig_2'>2B, G</ns0:ref>), distal hooks (Fig. <ns0:ref type='figure' target='#fig_2'>2C</ns0:ref>) with principal tooth smaller than its base, almost 25% less. Proximal hooks with external border bent squarely; hooks of the median region of the introvert with progressively rounder bent border; distal hooks with evenly rounded external border.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Systematics</ns0:head><ns0:p>SEM revealed growth stages of hooks and papillae (Fig. <ns0:ref type='figure' target='#fig_2'>2H</ns0:ref>); smaller in the proximal introvert and proximal trunk and larger at the distal introvert and distal trunk. Introvert papillae with three stages of development. First stage: the smallest, spherical with a ring of short apical protrusions (Fig. <ns0:ref type='figure' target='#fig_2'>2K</ns0:ref>) 'dome shape' (fide <ns0:ref type='bibr' target='#b11'>Cutler 1994)</ns0:ref>. Second stage: medium size, appearance of two units, the smallest with a ring of short apical protrusions, and a broad base (Fig. <ns0:ref type='figure' target='#fig_2'>2J</ns0:ref>) 'mammillate form' (fide <ns0:ref type='bibr' target='#b11'>Cutler 1994)</ns0:ref>. Third stage: largest, conical (Fig. <ns0:ref type='figure' target='#fig_2'>2I</ns0:ref>) 'cone shape' (fide Cutler 1994).</ns0:p><ns0:p>Internal anatomy (Fig. <ns0:ref type='figure' target='#fig_2'>2D</ns0:ref>). A pair of nephridia occupying 80% of trunk length, open at the same level as anus. Longitudinal musculature divided into 23 individual and anastomosed bands in the median trunk. Two pairs of retractor muscles; ventral pair attached to 8 longitudinal bands starting from the third band after ventral nerve cord (Fig. <ns0:ref type='figure' target='#fig_2'>2E</ns0:ref>), dorsal pair attached to 5 longitudinal bands starting from the fifth band after ventral nerve cord. Contractile vessel without swelling or villi. Spindle muscle attached posteriorly.</ns0:p><ns0:p>Habitat. In coralline rock and hard bottom, 1 to 30 m depth.</ns0:p><ns0:p>Distribution. Greater Caribbean from Florida to Venezuela.</ns0:p><ns0:p>Remarks. <ns0:ref type='bibr' target='#b26'>Keferstein (1865)</ns0:ref> described Phascolosoma (Phascolosoma) varians from St. Thomas, West Indies and P. (P.) nigrescens from Fiji. Although Keferstein's descriptions were well illustrated, Selenka (1883) produced an improved set of drawings from the type materials (Fig. <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>). <ns0:ref type='bibr' target='#b26'>Keferstein (1865)</ns0:ref> recognized each species as follows: Phascolosoma varians with a body three to four times as long as thick; introvert as long or longer than the body; closely spaced rows of hooks, highly variable in number (12-90), which often only cover the anteriormost part of the trunk; hooks very broad, with an upper right-angled tip (0.072 mm high, 0.092 mm wide); with 20-28 short tentacles, standing in two rows at the side; longitudinal muscles about thirty, but in many cases anastomosed as longitudinal strands; contractile vessel simple, without lateral sags; nephridia very long, attached in the anterior third by a mesentery. Phascolosoma nigrescens has a trunk about four times as long as thick; introvert longer than trunk; numerous hooks forming rings situated very close to each other in the anterior end of the trunk; hooks flattened with an lower right-angled tip (0.084 mm high, 0.084 mm wide); over twenty tentacles in several rows; muscles separated in about 24 longitudinal strands with few anastomosed bands; contractile vessel on the esophagus with many small, lateral sags; nephridia attached along almost their entire length by a wide mesentery. <ns0:ref type='bibr' target='#b13'>Cutler &amp; Cutler (1990)</ns0:ref> reviewed the subgenus Phascolosoma (Phascolosoma), and designated P. (P.) varians, together with 9 other species from different regions of the world, as junior synonyms of P. (P.) nigrescens. At that time, <ns0:ref type='bibr' target='#b13'>Cutler &amp; Cutler (1990)</ns0:ref> suggested there were 'no consistent differences' between these two species. Their decision appears to be primarily based upon variation associated with hook morphology. According to <ns0:ref type='bibr' target='#b13'>Cutler &amp; Cutler (1990)</ns0:ref>: 'One possible hypothesis is that hook morphology is determined by more than one pair of genes and that allelic frequencies vary from place to place. The alleles for sharp angle and large secondary tooth occur at a high frequency in the Caribbean and a low frequency in the Indo-West Pacific. . . P. varians is the junior name because it was described later on the page'. No molecular evidence was ever provided in support of the allelic hypothesis, or any other genetic differences supporting proposed junior synonyms. Subsequently, <ns0:ref type='bibr' target='#b11'>Cutler (1994)</ns0:ref> published his synonymy upon further consideration of the morphological differences between P. (P.) nigrescens and P. (P.) varians.</ns0:p><ns0:p>Herein, reexamination and redescription of P. (P.) varians, revealed clear morphological differences concerning its previously designated senior synonym. The most important features that distinguish these two species include the shape of the hooks, the attachment of nephridia to the body wall, and morphology the contractile vessel. Phascolosoma (P.) varians has hooks with a rounded secondary tooth; the base of the hook is broader than high; most of the anterior hooks (Fig. <ns0:ref type='figure' target='#fig_2'>2A and 2F</ns0:ref>) possess a distal tip at a 90&#186; angle with respect to the perpendicular axial line of the hook; the contractile vessel is simple; nephridia are attached to body wall in the anterior third. P (P.) nigrescens has hooks with a square secondary tooth; the base of hook is as broad as high; most of the anterior hooks possess a distal tip with less than a 90&#186; angle with respect to the perpendicular axial line of the hook; a contractile vessel on the esophagus with many small, lateral sags; nephridia are attached almost along their entire length.</ns0:p><ns0:p>The wavy contour of the nuchal organ and specific attachments of the retractor muscles were not described for both species by Keferstein in 1865, nevertheless, these features are now described. <ns0:ref type='bibr' target='#b26'>Keferstein (1865)</ns0:ref> refers to 'tentacles in two rows or many rows', which may explain the wavy contour of the nuchal organs I observed. The differences between the number of tentacles is not useful for separating these species because they appear to vary with the development stage of the specimen, and that variation overlaps between these species. Because of the difficulty of establishing the exact number of longitudinal muscle bands, this characteristic should be considered cautiously. Additionally, the number of rings of hooks is variable between these species, and the loss of rings is not uncommon. Papillae are also inappropriate characters for distinguishing these species as their differences are minor across most of the body surface. Phascolosoma (Phascolosoma) granulatum was included for comparison in the molecular analyses. The species can be easily distinguished from P. (P.) varians for having hooks with a basal triangle and lacking bands of pigmentation in the introvert, while P. (P.) varians lacks a basal triangle in the hooks and the bands of pigmentation are conspicuous.</ns0:p></ns0:div> <ns0:div><ns0:head>Molecular analyses</ns0:head><ns0:p>Herein, the synonymy of Phascolosoma (P.) varians with Phascolosoma (P.) nigrescens is rejected due to morphological differences. Additionally, there is a high genetic divergence between nucleotide sequences within their respective cytochrome c oxidase subunit 1 (COI) genes, which supports the morphological data.</ns0:p><ns0:p>The first three sequences (Fig. <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>) (top-down) correspond to Phascolosoma (P.) varians from the Greater Caribbean. This species had been determined as Phascolosoma (P.) nigrescens by past authors and registered as such it in GenBank. These sequences were grouped with a low intraspecific variation of 2.6%. The localities of those sequences are Florida and Barbados; preserved specimens from the same localities were revised morphologically to support the correct identification of the species.</ns0:p><ns0:p>The two sequences of Phascolosoma (P.) nigrescens from New Caledonia constitute a group clearly separated from Phascolosoma (P.) varians from the Greater Caribbean (genetic mean distance 24%). There are two crucial facts to consider. First: New Caledonia is the closest locality to Fiji, the type locality of P. (P.) nigrescens. The high genetic divergences between the specimens from New Caledonia and those from the Greater Caribbean supports the morphological differences between both species and reinforce the reinstatement of P. (P.) varians. Second: the intraspecific variation between both sequences is very high (18%), almost the same value of the interspecific variation of the other groups in this analysis. This value suggests that it is highly likely that these two sequences represent different morphotypes, and either one of them would correspond with Phascolosoma (P.) nigrescens.</ns0:p><ns0:p>The values of the genetic distance between Phascolosoma (P.) nigrescens from Israel, South Africa and, Broome, Australia, varies from 18 to 26% regarding Phascolosoma (Phascolosoma) varians from the Greater Caribbean. These values are similar to the results of <ns0:ref type='bibr' target='#b43'>Silva-Morales et al. (2019)</ns0:ref>, where they found a genetic distance of 19% between Antillesoma antillarum (Greater Caribbean) and A. mexicanum (Southern Mexican Pacific). The present analysis reveals that Phascolosoma (Phascolosoma) nigrescens is a species complex resulting from the incipient morphological analysis. This study shows that Phascolosoma (P.) varians from the Greater Caribbean is well differentiating morphologically and genetically of Phascolosoma (P.) nigrescens; however, a detailed morphological revision of this species complex is needed.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The genetic analysis suggests the following considerations: 1) the specimens from Israel, South Africa and Broome, Australia identified as Phascolosoma (P.) nigrescens correspond to different species. It is very likely that other species from those regions, considered synonyms, would need to be reinstated following redescription, or described and established as new species. 2) It will be necessary to resolve a potential species complex of Phascolosoma (P.) nigrescens by combining molecular and morphological data. Neither one of these considerations were resolved in the present study, as they were beyond the original scope of this investigation.</ns0:p><ns0:p>The assumed wide distribution of Sipuncula taxa is attributed to the development of the teleplanic larvae in some species, such as Phascolosoma (Phascolosoma) varians. Although it is well accepted that the free-swimming larval stage with its prominent locomotive organ (known as a metatroch) confers the ability to disperse, allowing an increase in geographic range and providing for genetic exchange between populations <ns0:ref type='bibr' target='#b33'>(Rice, 1981)</ns0:ref>, it is not necessarily the rule. <ns0:ref type='bibr' target='#b44'>Staton &amp; Rice (1999)</ns0:ref> described the case of a species with teleplanic larvae with a limited distribution. They found distinct genetic differences within and between larval and adult stages of Apionsoma (A.) misakianum <ns0:ref type='bibr'>(Ikeda, 1904)</ns0:ref> from northern and southern regions of Florida and the Bahamas using allozymes. They did not find any indication of 'hybrids' occurring between them, suggesting a potential oceanic boundary was present between populations with teleplanic pelagosphera larvae, and thus a possible Apionsoma species-complex in the region. They did not perform a morphological analysis of the adults at that time, but the larve exhibited two distinct coloration patterns. <ns0:ref type='bibr' target='#b22'>Kawauchi &amp; Giribet (2010)</ns0:ref> rejected the cosmopolitanism of Phascolosoma (P.) perlucens Baird, 1868, by analyzing molecular and morphological data of specimens from many localities around the world. They detected four different lineages, and identified variation in hook morphologies between different localities that correlated with a high genetic diversity between populations. Also, their results suggested a probable lack of gene flow between the geographically distinct lineages. <ns0:ref type='bibr' target='#b39'>Schulze et al. (2012)</ns0:ref> analyzed molecular sequence data and developmental features of three 'cosmopolitan' species, Phascolosoma (P.) agassizii <ns0:ref type='bibr'>Keferstein, 1866</ns0:ref><ns0:ref type='bibr'>, Thysanocardia nigra (Ikeda, 1904)</ns0:ref>, and Themiste (T.) pyroides <ns0:ref type='bibr'>(Chamberlin, 1920)</ns0:ref>. For each one of the three species, they found significant differences between previously assumed con-specific populations from the Sea of Japan and the Northeast Pacific region, with respect to egg size, developmental mode and developmental timing. The populations of all three species were remarkably distinct genetically and suggested that gene flow between the two regions was extremely unlikely. Furthermore, <ns0:ref type='bibr' target='#b23'>Kawauchi &amp; Giribet (2014)</ns0:ref> analyzed the genetic data from four genes of Sipunculus (S.) nudus Linnaeus, 1766 with specimens from multiple localities worldwide. As with Phascolosoma perlucens (see above), these two investigators again found high levels of genetic differentiation between distantly related populations, suggesting in this case there were five distinct lineages, three of which could be distinguished morphologically. In the last two studies, neither a new species was described, nor an available name reinstated.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>High genetic divergence between specimens identified as P. P. nigrescens from the Greater Caribbean and a region close to its type locality correlate with morphological differences found between P. (P.) varians and P. (P.) nigrescens. Herein, the synonymy of Phascolosoma (P.) varians with Phascolosoma (P.) nigrescens is rejected, and as a consequence, Phascolosoma (P.) varians is reinstated.</ns0:p><ns0:p>Based upon these findings, and other studies, some of which are discussed here, the diversity of sipunculans is most likely underestimated. Thus, a combination of morphological and molecular data, along with other important information from the fields of development, ecology and oceanography, will help us determine a more realistic number of extant sipunculans species worldwide. Maximum likelihood analysis of cytochrome c oxidase subunit 1 (COI) DNA.</ns0:p><ns0:p>Phascolosoma (P.) varians from the Greater Caribbean shows a clear genetic distinction from all specimens identified as Phascolosoma (P.) nigrescens from eastern and western regions of the Pacific Ocean. Tree reconstruction was generated from a ClustalW alignment of COI sequences amplified from 11 sipunculan specimens. Species names (specimens) and GenBank accession numbers are listed at the branch tips. Individuals and conspecific groups are marked with vertical bars, and their corresponding geographic regions, to the right of species names. This analysis was performed using Tamura 3-parameter with a discrete Gamma distribution with five rate categories, assuming a certain fraction of sites is evolutionarily invariable (T92+G+I).</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Family</ns0:head><ns0:label /><ns0:figDesc>figs. 1-32. Physcosoma varians ten Broeke 1925: 85. Phascolosoma (Phascolosoma) varians: Stephen &amp; Edmonds 1972: 327-328, fig. 39I. Phascolosoma nigrescens Cutler 1994 (partim): 179-181; Cutler &amp; Schulze 2004: 226; Schulze 2005: 526; Frontana-Uribe et al. 2018:174, fig. 5a-b; (non Keferstein, 1865).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> </ns0:body> "

" El Colegio de la Frontera Sur (ECOSUR) Unidad Chetumal Centenario Avenue, km 5.5, Postal Code 77014, Chetumal, Quintana Roo, Mexico. Tel: 01 (983) 835 0440 Fax: 01 (983) 835 0454 September 22, 2020 Dear Editors Dear Editors, I thank the reviewers for their generous comments on the manuscript and I have edited the manuscript to address their concerns. I am very sure that the manuscript is now suitable for publication in PeerJ. Marine Biologist Itzahí Silva Morales Graduate Student of El Colegio de la Frontera Sur (ECOSUR) Reviewer 1 (Anonymous) Basic Reporting: There are issues with use of the English language throughout the manuscript, which includes elements of grammar, word usage, word agreement, sentence structure, insertion of terms, and the clarity of particular statements. These are expected from an Author with English as a second language. Therefore, because of the language issues, the Reviewer has taken a focused interest in improving the manuscript in a non-conventional manner. There are many instances where a line-by-line review of grammatical errors and statement clarity issues would require considerable time, and many pages of review notes to be submitted. Therefore, this Reviewer has edited the Word.docx version of the original manuscript with Tracked Changes throughout most of the text, and has placed a number of comments and suggestions along the margin. Note: the Author may, or may not, accept or use the recommended Tracked Changes, but it is the Reviewer’s opinion that such recommendations will significantly improve the manuscript. Literature sources are sufficient for this study and the extensive background required to make the case for reinstatement of a species that was previously synonymized with another species. Author should recheck the References section for accuracy and formatting, and see comments in the margin of the Tracked Changes document (e.g. Quatrefages vs. de Quatrefages; Broeke vs. ten Broeke, etc.). Regarding the Material Examined section, Reviewer did not review this. The structure of the manuscript meets professional standards and general PeerJ formatting. However, the figure captions have also been extensively edited with Tracked Changes by the Reviewer to comply with PeerJ figure caption formats, and they were edited for a more specific, detailed and thorough description of the primary data presented in each of the four figures. I have accepted all grammar and style recommendations. I am sure this manuscript has improved substantially. Experimental design: This manuscript is original research, and it meets the Aims & Scope of PeerJ, particularly in the areas of Biological Sciences, as a data-driven Research Article, and on its methodological soundness. This manuscript goes far in its effort to examine previous research, provide a comprehensive set of specimen observations, with corresponding genetic support for those observations, and aims to correct notable errors by previous workers on this particular topic. The question is clear, the methods utilized to answer the question are appropriate, and the work therein builds upon previous efforts to answer similar concerns by other investigators who have pursued this same question. There certainly is a gap in our knowledge of species distinctions and the connectivity of assumed con-specific populations. More of this work will be required going forward. And, the Author has made a strong case for such efforts here. Note: The Reviewer would like to see the Author develop a more comprehensive Introduction section by adding pertinent background on the relevance of using COI sequences (e.g. a Barcode gene) for identifying and distinguishing species within the target group, and other metazoan groups outside Sipuncula, with examples. And, address whether COI alone is sufficient, or should it be complemented with other genetic markers to strengthen the results. Additionally, there should be more introductory information on sipunculan life histories, in particular the types of larvae within the clade, and the limitations of different larval modes (e.g. lecithotrophic, planktotrophic, teleplanic) to disperse and connect species populations, as suggested by Cutler & Cutler (1990), who have made this manuscript necessary. These two issues, larvae as vectors of connectivity, and genetic markers of species identification, should then be revisited in the Discussion section with more detail than first provided by the Author. The Reviewer finds no outstanding issues with technical standards as presented, and the methods described are both appropriate and replicable, as required for similar studies on sipunculan taxonomy that must be performed in the future. As noted above, the Reviewer has performed edits, added comments and posed questions that will clarify particular methods and data presentation materials – to improve access to specific details by the Author’s readership. Agreed. I completed the introduction with two paragraphs. One with information about the COI and other about the Sipunculan life histories. The discussion was enhanced too. 1) Page 4, Line 64: Provide references for this statement, if true. The references are included later in line 70: “…in the Greater Caribbean, Phascolosoma (P.) nigrescens has been reported by Cutler & Schulze (2004) from Barbados, Schulze & Rice (2004) from Belize, Schulze (2005) from Panama, and Frontana-Uribe et al. (2018) from the Mexican Caribbean”. 2) Page 4, Line 77: Please recheck this number (also in a similar statement in the ‘Remarks). This Reviewer counts only 10 from Cutler and Cutler, 1990 and 3 more from Cutler and Cutler, 1983. Of course, you're right, so I've added the reference of Cutler & Cutler 1983, and the number and was corrected. 3) Page 5. Line 104-105: What type of microscope was used here? A dissecting stereomicroscope? Compound light microscope? Model number and manufacturer? The complete information was provided. 4) Page 5, Line 114: What type of microscope (model and manufacturer)? The complete information was provided. 5) Page 5, Line 116: What were the lengths (bp) of the COI fragments used? What region of the COI gene was aligned? Did you perform any PCR on specimens to purify a COI sequence . . . or only use GenBank sequence Data? The length of the COI fragments used was included. I only use GenBank sequence Data 6) Page 6. Line 149: Please check the References section: this references is listed as “de Quatrefages” And should be listed as “Quatrefages, M. A. de. 1865. . . .” The correct form is “de Quatrefages”. 7) Page 6. Line 151: Why did you place these referenced in this order? They are not listed in this order within the Stephen and Edmonds (1972) text on page327. Also, did you only review Ten Broeke 1925 for Phycosoma varians? There are potentially additional references not listed here. The order of the references was corrected. I didn’t include all the references listed in Stephen & Edmonds (1972), only the studies that recorded Phascolosoma varians or Phascolosoma nigrescens in the Greater Caribbean. The other references recorded Phascolosoma varians in Alaska, Japan and Funafuti. 8) Page 6. Line 155-156: Rice & Macintyre (1982) did not list Phascolosma nigrescens in their study, which was prior to Cutler, 1994. Why is this listed here? They did include Phascolosoma varians in their study, but Cutler (1994) did not list that study in his synonomy of P. Nigrescens. I changed the list. All records of Phascolosoma varians in the Greater Caribbean must be included in the references despite Cutler (1994) did not include it. 9) Page 11. Line 339: Please check this number. From Table 1 in Cutler and Cutler, 1990, there are 10 species listed as proposed taxonomic changes to become synonymous with P. P. Nigrescens. You are right. The number was corrected. 10) Page 12. Line 370. Figure 4 shows only four distinct groups of P. P. Nigrescens. Where are the other two groups? Are you stating that two groups that are labeled as P. P. varians are included in the “six distinct groups” that were previously labeled as specimens of P. P. nigrescens? If so, please clarify in the text. Or perhapse this is an error, and the sentence should state “four distinct groups”? The whole section was rewritten. 11) Page 12. Line 371. This is not clear. Are the two sequences from New Caledonia 18% distant from the next closeset branch (Broome Australia) or . . . 18% from the three P. P. varians from the Greater Caribbean? Please clarify the exact comparison represented by the 18% mean distance measure, in the text. The whole section was rewritten. 12) --- 13) Page 12. Line 372: Please add distance measure values (XX.X%) on the corresponding cladogram branches in Fig. 4, for which those meaures were calculated by your ML analysis. I chose to use only the scale line. This is enough. 14) This Reviewer suggests adding some discussion text here (with references) about sipunculan larval life history patterns and the limitations of those larvae for extensive genetic connectivity among distant populations. This would build upon statements in the introduction and transition smoothly with the last paragraph below, in this Discussion section. In particular, it could be inferred that relatively small, pappilated teleplanic larvae of P. nigrescens would not easily disperse between major ocean basins around the central band of the planet - as would be required by the hypothesis and/or synonymy as proposed by Cutler and Cutler (1990). Elaboration on teleplanic larvae was included in the introduction and discussion. 15) This paper was published in 2013. Please change date in the References section to match with this in-text reference. I reviewed the reference again. The year is 2014. Recommendations on figures: Reviewer recommends that the author should mark (with arrows or letters) the ‘introvert’, ‘anus’, ‘trunk’ and ‘introvert-trunk boundary’. I added the locations of anus because it is important, but the rest of the marks I do not consider necessary. Reviewer recommends that the author arrange the papillar images (B-F) in order from anterior to posterior along the body and place letters along the body in order, and/or adjacent to the regions where each image shows the corresponding pattern of papillae. The current order will be confusing to readers and should follow the body plan in one direction, not jumping back and forth among regions. The papillar images were ordered from anterior to posterior body as you suggest. Question: are the hooks in F and G both from the anterior of the introvert? They exhibit very different morphology, which should be clearly explained in the Discussion section. I corrected this mistake. These hooks correspond to median region of introvert. I added a part in the descriptions to clarify that: “Proximal hooks with external border bent squarely; hooks of the median region of the introvert with progressively rounder bent border; distal hooks with evenly rounded external border”. Reviewer 2. Mario H. Londoño Mesa Basic reporting - English must be improve. Maybe, to be read for an English spoken person. Taxonomy has its own style and way to say things. So, sometimes ideas are not well written or lack of correct grammar. - Literature is enough. Just one reference cited is lacking in the section. - The document attached has many recommendations, changes, suggestions, questions, etc. that could improve the paper. Nevertheless, the document needs more than that. It needs more argumentation and to clarify many ideas. The document is accepted with major changes and revisions. I will need to revise a new version. Experimental design See comments done in the document. Validity of the findings Document needs strong argumentation for being clearer in both morphological and molecular findings and analysis. In the document, I have put several changes, suggestions, etc. in these sections. As it is used in taxonomy, the discussion presented here could be divided in two. The first part must me fused to remarks (morphological analysis), and the second part must be fused to molecular analysis. Thus, all the information will be more compacted and inclusive. In molecular findings, the discussion and analysis are far to be clear. I recommend, if the molecular section does not improve, could be deleted since in the present state, does not give relevant information to the reinstatement of the species. On the other hand, morphological argumentation is still weak. Author has to include information about the characters in other close species, as well as the discussion about that the characters chosen are very stable and informative. Comments for the Author The document needs a new version and new revision. Please, check the English, but particularly, check the telegraphic style in the redescription. If author does not attend some comments, they have to be explained why they were not included in the new version. All comments are done in the word file. The manuscript was revised and improved by an English spoken person. 1) Page 4. Line 45: Genetic is not the same as molecular Of course, you're right. Changed to the correct word. 2) Page 4. Line 48: Are explained? Right. This is explained in the Remarks and Discussion sections. 3) Page 4. Line 58: Was not Cutler & Culter, 1990? The idea says “.. after Edward and Norma Cutler revisions..” The wording was corrected. 4) Page 4. Line 58: Or since 2009? Why is since 1994 without the reference from 1994? The wording was corrected. 5) Page 4. Line 61: Greater or Great? Why not Grand? I used Greater because it is used before names of some cities to refer to both the city itself and the area around it and Grand is refers to important and large in degree. 6) Page 4. Line 64: This research? Or that with the reduction? In the later case, I suggest to use “Such approach....” 7) The wording was corrected. 8) Page 4. Line 71-72: Is this correct following the author instructions? Three last names? From how many you have to put et al.? check The submissions guidelines of PeerJ indicates: “For three or fewer authors, list all author names (e.g. Smith, Jones & Johnson, 2004). For four or more, abbreviate with ‘first author’ et al. (e.g. Smith et al., 2005)”. 9) Page 4. Line 74: Hidden under... Agree. The words were changed. 10) Page 4. Line 79: Visible? The sentence was corrected with the word “distinct”. 11) Page 5. Line 82. Very? How much? Author must avoid to use this kind of words that implies an imprice cualification. Agree. The word very was used by Cutler (1994), but the correct form is only “widespread”. 12) Page 5. Line 87. A redescription must be detailed. Descriptions of sipunculans are generally short and incomplete, so I emphasize the word “detailed”. 13) Page 5. Line 88. But topotypic material is also from the Ceribbean. Re-writer sentence. Of course. The sentence was re-written. 14) Page 5. Line 98: From other Caribbean localities Agree. It was added. 15) Page 5. Line 100. Proposed Agree. It was added. 16) Page 5. Line 102. Middle point? Yes. The terminology is correct. 17) Page 5. Line 103. This could be indicated in, at least, one figure. This is not necessary. 18) Page 5. Line 104-105. Compound. Right. The sentence was completed. 19) Page 5. Line 105. This terminology apply for the body. The correct terminology for an “apendix”, like the introvert, is proximal, middle and distal. Distal is near the mouth. The terminology was corrected. 20) Page 5. Line 116: DNA or RNA? I specified “COI” sequences. 21) Page 5. Line 117: Could be more precise at least on this, because the Caribbean also is in the Western Atlantic. So, if you are trying to solve the problem on distribution, this could be important. Done. The localities were specified. 22) Page 6. Line 122. As sister/out groups? Use precise terminology Strictly, this is not a phylogenetic tree. The use of a “sister group” or “outgroup” is a matter of cladistics, and not a valid concept for this tree. 23) Page 6. Line 125: Thus This sentence was corrected. I used “From the BIC results” 24) Page 6. Line 126-127: gramar This sentence was corrected. 25) Page 6. Line 130: Check this... three authors? Et al.? The submission guidelines of PeerJ indicate: “For three or fewer authors, list all author names (e.g. Smith, Jones & Johnson, 2004). For four or more, abbreviate with ‘first author’ et al. (e.g. Smith et al., 2005)”. 26) Page 6. Line 138: Not in references This is the authority of the species, not a cited reference. 27) Page 6. Line 149: Becuse it is a referencie, you must use coma between the name and the reference. Otherwise, it could be understood as the author of the species, which is wrong. It is indeed the author of the species. The text was reformatted so that there’s no ambiguity between the author of the species and the authors of the records. 28) Page 6. Line 149: Check if “de” must be included. The correct form is “de Quatrefages”. 29) Page 6. Line 159: Is there any order in the localities? I recomend to use a geographical order from North to South and West to East. Or alfabetical? Any suggested order is accpetable, but use any. Even, inside each country. The order is geographical. Coasts of the countries first, islands second 30) Page 7. Line 161. If you say Mexico, Mexican Caribbean, you have to say here, USA, Florida. Check this in order to have all standardized. Of course. The names of localities were standardized. 31) Page 7. Line 161: It could be reduced as (2), indicating in methods that this means number of specimens. Thus, you could save space in the paragraph deleting all the “specimens”. This recommendation is related to the author's writing style. I chose the original version. 32) Page 7. Line 163: You could also reduce this as 05.04.1966 (DD.MM.YYYY). You could mention this in methods. This recommendation is related to the author's writing style. I chose the original version. 33) Page 7. Line 170: Recommend to avoid using italics. Only use it for genus and species names. I used italics because there were many localities. With this format, it is easier to read and understand. 34) Page 7. Line 177: If you use accent here, you have to use it in México, Panamá, etc... Standardize. Agreed. The style was standardized. 35) Page 9. Line 248: Caribbean? Nicaraguan Caribbean? Use the same structure for all the localities Done. 36) Page 9. Line 250: This is in Colombia, no in Nicaragua. Corrected. 37) Page 9. Line 254: You have to precise what is “West Indies”. It is more than these islands. Maybe the use of Greater and Lesser Antilles is more adequate; even more correct, these two islands belongs to the Lucayan Archipelago. Check and correct. Corrected. I opted to use only the names of the Islands or countries. 38) Page 9. Line 280: I found that the acronym is UFFLMNH. Check this. I followed the guidelines of the University of Florida in their website: “UF is the official abbreviation for referencing specimens housed at the Florida Museum of Natural History and should be acknowledged in each publication”. ADD LINK 39) Page 10. Line 289: “In length” or “long”. And how much “in width” or “wide”? Corrected. “In length” instead “length”. Width is an irrelevant character. 40) Page 10. Line 290: at random, randomly... etc. Corrected. Randomly instead dispersedly. 41) Page 10. Line 290: in body is region, not zone Corrected. Regions instead zone. 42) Page 10. Line 294: It is one specimen.. how many bands? This must be precise The coloration pattern in Sipuncula is irrelevant. To count the total number of bands is subjective. I added the “ill defined” adjective for more clarity of the description. 43) Page 10. Line 294: I think this is wrong. Introvert, as an appendix, does not have posterior end, because the “posterior region” is not an end (it continues with the trunk). You have to say “proximal” or “distal” region. Which is this? Done. Distal instead posterior end. 44) Page 10. Line 299: In descriptions you do not suppose things. The descriptions of Cutler included this type of comments. Abrasion is the likely hypothesis. 45) Page 10. Line 299: Telegraphic descriptions do not use verb to be. Re-write the sentence Done. 46) Page 10. Line 300: (Fig. 2A,F,G) Corrected. 47) Page 10. Line 300: it must be one or the other, but two terms is not used. You have to use the standardized way to name structures. If there is other terms, you have to discusse this in the section, not here. I corroborated this. In the literature the term distal tip is commonly used, the word main tooth, was eliminated. 48) Page 10. Line 300: confuse: 90º with perpendicular (45º)?? Not understable This sentence was corrected. 49) Page 10. Line 304: Main tooth? Distal tip? Confuse I corroborate this. In the literature the term distal tip is commonly used, the word main tooth, was eliminated. 50) Page 10. Line 304: I could say this in proportions. I think any form is correct. 51) Page 10. Line 305: All this paragraph needs to be re-write in telegraphic style and more clear. Using Cutler terminology you have to realize that a basic squeme is needed to explain this better. Otherwise, this “rare” terminology makes the paragraph not clear. The whole paragraph was corrected. 52) Page 10. Line 307: Superlative always has “the”: the smallest, the largest, ... Of course, you're right. Corrected. 53) Page 10. Line 313: Not in telegraphic style Corrected. 54) Page 10. Line 314-315: Since the description is made using only one specimen (UF 332) range in nombre is imposible. How many bands does the 332 have exactly? Corrected. 55) Page 11. Line 320: Including Antilles, or as you say West Indies. Remember that the Greater Caribbean is not only the continental shelf.. it includes also all the Greater and Lesser Antilles I chose the original redaction. 56) Page 11. Line 324: Improved the drawings? Of course, you're right. Corrected. 57) Page 11. Line 326: Narrow? Corrected. 58) Page 11. Line 326: How much is very? Corrected 59) Page 11. Line 327: Is this seen in the additional material or in the Kaferstein material? Keferstein material. 60) Page 11. Line 328: Arranged I chose the word “standing”. “Arranged” is related to hooks, not to tentacles. 61) Page 11. Line 329: Well-developed Corrected 62) Page 11. Line 330: Is this meaning “without many small, lateral sags”? The contrary of the next descrption? Write both descriptions in comparable style. Corrected. 63) Page 11. Line 330: How much is very? Not specify by Kefesrtein. 64) Page 11. Line 331: In the previous species you say body. Is it the same? You have to write both with the same terminology and order of information, in order to be comparable. Corrected. 65) Page 11. Line 333: Is this the same as closely or narrowly? If yes, do not repeat information. Corrected. 66) Page 11. Line 334: In a right-angle too? Or how? Comparable information Corrected. 67) Page 11. Line 335: Well-developed Corrected. 68) Page 11. Line 340: There are more than one premise! The sentence was corrected. 69) Page 11. Line 340-343: If you put this between quotation marks you to not have to put it in italics too. Just one thing for distinguish their words. Suggest just quotations. This correction is related to the author's writing style. I chose the original version. 70) Page 11. Line 347: It is presented morphological differences between these two species. But what about the other species that author included in the tree? You have to be more convincent telling reader that these characters have highly taxonomic importance and stability, explaining them how are in other species. How are these characters in, at least, the most close species (phylogenetically, geographically or morphologically)? I think the reinstatement is still weak in arguments. I disagree. The arguments described in this study are a combination of morphological and molecular data. The other reviewer said: Literature sources are sufficient for this study and the extensive background required to make the case for reinstatement of a species that was previously synonymized with another species. This manuscript goes far in its effort to examine previous research, provide a comprehensive set of specimen observations, with corresponding genetic support for those observations, and aims to correct notable errors by previous workers on this particular topic. The question is clear, the methods utilized to answer the question are appropriate, and the work therein builds upon previous efforts to answer similar concerns by other investigators who have pursued this same question. There certainly is a gap in our knowledge of species distinctions and the connectivity of assumed con-specific populations. More of this work will be required going forward. And, the Author has made a strong case for such efforts here. 71) Page 11. Line 353: Square? Corrected. 72) Page 11. Line 358: For both species? Clarify Corrected. 73) Page 11. Line 359: Not to use contraction style. Corrected. 74) Page 12. Line 368: I see molecular analysis not clear, not well explained. It is not easy no follow the explanations with the tree. Recommend to reconsider if it is needed this molecular analysis since it does not explaing in a proper way, the reinstatement of the species. There is not clear evidence with sequences, with distances from other material, more that few numbers given in the two paragraphs. Author(s) must think if not taking into account the molecular analysis, the results are the same. Better than to improve the molecular discussion, is to improve the morphologica discussion. All this section was rewritten. The wording was improved. 75) Page 12. Line 370: I do not know if I am understanding the tree, but the author are naming 7 groups, with al l the species. From them, only 4 have P. (P). nigrescens. All this section was rewritten. The wording was improved. 76) Page 12. Line 372-374: Not clear. These two groups are the most distant clades. So, whay to talk about them?➝ All this section was rewritten. The wording was improved. 77) Page 12. Line 375: ??? Corrected. 78) Page 12. Line 375: This is risky. You have to have sequences from Fiji to be sure, otherwise to say “probable” is not the correct way Sometimes it is impossible to obtain specific data, but we can and should work with the data you have available. 79) Page 12. Line 378: ??? Corrected. 80) Page 12. Line 379: But the Pacific specimens are very far in the tree. This is sure, also because this Pacific is the northern Pacific, not even the Tropical Pacific. All this section was rewritten. The wording was improved. 81) Page 12. Line 380: Wasn`t this the sister group (for you, the comparison group)? So, was it a good group for this? You have to discuse also the behavoior of the sister/out groups. The tree does not show a relevant outgroup The morphological differences between Phascolosoma (P.) varians and Phascolosoma (P.) granulatum were added. 82) Page 12. Line 391: This paragraph presents conclusions, that could be at the end of discussion. The change of position of this paragraph does not improve it. Starting the discussion with this paragraph allows you to understand the following paragraphs. 83) Page 12. Line 393: Different species from P. (P.) nigrescens or different species between them? Be more precise. Re-specifying that they are different from the synonymy and P. P. nigrescens is redundant. 84) Page 12. Line 393: How much? The word “very” is very imprecise!!! In this section, use of the word is valid. 85) Page 12. Line 395: This is the first time this concept appears in the document. Why it was not included in the introduction, objectives, etc.? I consider it as very important to include in all document in order to justify the molecular analysis, form example. Who else is considering this species a speciescomplex? Why? Etc. But it is mentioned as a “potential” species complex. 86) Page 12. Line 398-399: Grammar All this paragraph was re-written and enhanced. 87) Page 13. Line 400-403: I tried to improve the sentece, but it needs grammar revision. This sentence was corrected. 88) Page 13. Line 404: Cosmopolitism? Cosmopolitanism is the correct word in English. 89) Page 13. Line 406-407: Grammar The sentence was corrected. 90) Page 13. Line 408: Ufff... depending on the sequences used. But if it was made with DNA, it not easy to come to this conclusion. Without answer. 91) Page 13. Line 428-429: The real sipunculan diversity. I corrected the sentence with: “extant sipunculans species worldwide”. 92) Page 13. Line 434: Sadly, she is gone! You have to indicate it. This is inappropriate "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. High heel shoes (HHS) can affect human postural control because elevated heel height (HH) may result in plantar flexed foot and limit ankle joint range of motion during walking. Effects of HH and HHS wearing experience on postural stability during selfinitiated and externally triggered perturbations are less examined in the literature. Hence, the objective of the present study is to investigate the influences of HH on human postural stability during dynamic perturbations, perceived stability, and functional mobility between inexperienced and experienced HHS wearers. Methods. A total of 41 female participants were recruited (21 inexperienced HHS wearers and 20 experienced HHS wearers). Sensory organization test (SOT), motor control test (MCT), and limits of stability (LOS) were conducted to measure participant's postural stability by using computerized dynamic posturography. Functional reach test and timed up and go test were performed to measure functional mobility. The participants' self-perceived stability was assessed by visual analog scale. Four pairs of shoes with different HH (i.e., 0.8, 3.9, 7.0, and 10.1 cm) were applied to participants randomly. Repeated measures analysis of variance was conducted to detect the effects of HH and HHS wearing experience on each variable. Results. During selfinitiated perturbations, equilibrium score remarkably decreased when wearing 10.1 cm compared with flat shoes and 3.9 cm HHS. The contribution of vision to postural stability was larger in 10.1 cm HHS than in flat shoes. The use of ankle strategy worsened when HH increased to 7 cm. Similarly, the directional control of the center of gravity (COG) decreased for 7 cm HHS in LOS. Experienced wearers showed significantly higher percentage of ankle strategy and COG directional control than novices. Under externally triggered perturbations, postural stability was substantially decreased when HH reached 3.9 cm in MCT. No significant difference was found in experienced wearers compared with novices in MCT. Experienced wearers exhibited considerably better functional mobility and perceived stability with increased HH. Conclusions. The use of HHS may worsen dynamic</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head n='1.'>Introduction</ns0:head><ns0:p>High heel shoes (HHS) have been widely used among women in several centuries; 37% to 69% of women wear HHS daily <ns0:ref type='bibr'>(American Podiatric Medical Association, 2003)</ns0:ref>. HHS are featured with heel evaluation, rigid heel cap and curved plantar region, which interfere with natural foot motion <ns0:ref type='bibr' target='#b8'>(Cronin, 2014)</ns0:ref>. A more plantar flexed and supinated foot position can alter the distribution of plantar pressure, affect muscle activities around ankle joints, and limit the range of motion (ROM) of the ankle during standing and walking <ns0:ref type='bibr' target='#b27'>(Ko et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b29'>Luximon et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b42'>Simonsen et al., 2012)</ns0:ref>. A number of studies have documented that the effects of HHS are not localized to the ankle; instead, a 'chain reaction' of kinematic effects travels up the lower limb and disturbs the displacement of the center of mass (COM) <ns0:ref type='bibr' target='#b4'>(Chien et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b8'>Cronin, 2014;</ns0:ref><ns0:ref type='bibr' target='#b40'>Schroeder &amp; Hollander, 2018)</ns0:ref>. These biomechanical alterations can decrease perceived stability, impair postural control, and increase the risks of falling among HHS wearers <ns0:ref type='bibr' target='#b29'>(Luximon et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b49'>Wan et al., 2019)</ns0:ref>. The rate of high heels-related injuries increased from 7.1% to 14.1% during the 11-year period from 2002 to 2012. Most of the injuries were sprains or strains occurred to either the ankle or foot body regions <ns0:ref type='bibr'>(Barnish &amp; Barnish, 2009;</ns0:ref><ns0:ref type='bibr'>Moore et al., 2015)</ns0:ref>.</ns0:p><ns0:p>One of the risk factors on high heels-related injuries is decreased postural stability among HHS wearers <ns0:ref type='bibr' target='#b49'>(Wan et al., 2019)</ns0:ref>. Postural control is the ability to stabilize and restore the body's COM relative to the base of support (BOS) during self-initiated and externally triggered perturbations <ns0:ref type='bibr' target='#b21'>(Horak, 2006;</ns0:ref><ns0:ref type='bibr' target='#b50'>Winter, 1995)</ns0:ref>. To maintain postural stability, a complex motor skill based on the interaction of proprioceptive, visual, and vestibular system is utilized in this process PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed <ns0:ref type='bibr' target='#b30'>(Mancini &amp; Horak, 2010)</ns0:ref>. Wearing HHS can cause biomechanical constrains and disturb human movement strategies through reduced BOS and elevated heel height (HH) <ns0:ref type='bibr' target='#b4'>(Chien et al., 2013)</ns0:ref>.</ns0:p><ns0:p>The HHS wearers tend to apply different movement strategies (e.g., ankle and hip strategy) to maintain the stability of the body's equilibrium with regard to elevated HH during standing, walking, and dynamic perturbations.</ns0:p><ns0:p>A number of studies found that different HH can influence postural stability through interfering with the stabilization of COM with respect to the BOS. Different sensory and movement strategies are also involved in the process of postural control in HHS wearers. Recent studies have examined that HHS wearers had significantly worse standing balance starting at 7 cm HH by analyzing the center of pressure (COP) magnitude in quiet stance and limits of stability test (LOS) <ns0:ref type='bibr' target='#b7'>(Choi &amp; Cho, 2006;</ns0:ref><ns0:ref type='bibr' target='#b16'>Gerber et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b31'>Mika et al., 2016)</ns0:ref>. During extrinsic perturbations, previous studies demonstrated that HHS can impair human balance (e.g., sinusoidal oscillations and waist pulling) <ns0:ref type='bibr' target='#b7'>(Choi &amp; Cho, 2006;</ns0:ref><ns0:ref type='bibr' target='#b44'>Sun et al., 2017)</ns0:ref>. When HH increased to 10 cm, increased use of ankle strategy, slow center of gravity (COG) movement velocity, and decreased body equilibrium were observed with increased HH <ns0:ref type='bibr' target='#b17'>(Hapsari &amp; Xiong, 2016;</ns0:ref><ns0:ref type='bibr' target='#b46'>Truszczy&#324;ska et al., 2019)</ns0:ref>. However, no difference in the interaction of sensory systems was found in postural control among HHS wearers with increased HH <ns0:ref type='bibr' target='#b17'>(Hapsari &amp; Xiong, 2016)</ns0:ref>.</ns0:p><ns0:p>It will be worthwhile to detect how sensory systems interact during postural control, and to what extend can HH affect movement strategy and influence human overall postural control accordingly.</ns0:p><ns0:p>HHS experience might be another vital factor that can influence HHS wearers' postural stability as well. Previous research has shown significant muscular alterations, such as overwork muscle activities in medial gastrocnemius and peroneus longus, shortened calf muscles, and increased Achilles tendon stiffness after long-term use of HHS <ns0:ref type='bibr' target='#b9'>(Cronin et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b10'>Csapo et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b24'>Kermani et al., 2018)</ns0:ref>. These muscular accommodations around ankle joints can affect the efficient use of ankle strategies to return the body to equilibrium during standing <ns0:ref type='bibr' target='#b6'>(Chien et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b35'>Rahimi et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b49'>Wan et al., 2019)</ns0:ref>. However, Xiong and Hapsari found no significant PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed difference in self-initiated standing balance and functional mobility between experienced HHS wearers and inexperienced HHS wearers, although the experienced group showed higher directional control of COG in LOS <ns0:ref type='bibr' target='#b17'>(Hapsari &amp; Xiong, 2016)</ns0:ref>. Therefore, whether HHS wearing experience can influence human postural stability and functional mobility remains unclear.</ns0:p><ns0:p>Hence, the current study aims to investigate the effects of <ns0:ref type='bibr'>HH (i.e.,</ns0:ref><ns0:ref type='bibr'>0.8,</ns0:ref><ns0:ref type='bibr'>3.9,</ns0:ref><ns0:ref type='bibr'>7.0,</ns0:ref><ns0:ref type='bibr'>and 10.1 cm)</ns0:ref> and HHS experience on postural stability during dynamic perturbations, perceived stability, and functional mobility in women. We hypothesized that human postural stability could decrease with increasing HH, and HHS experience could improve performance in postural control and functional mobility test.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.'>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>Participants</ns0:head><ns0:p>A total of 41 female participants were recruited from the local university and communities (21 inexperienced HHS wearers and 20 experienced HHS wearers). All participants had a shoe size of EU 36-39 and self-reported to be free from lower limb injuries for a minimum of six months prior to the study. Participants with any history of musculoskeletal, cardiovascular, neurological, and vestibular abnormalities were excluded from the experiment. Anthropometrics were measured prior to the experiment (i.e., body height, weight, foot length, and arch height).</ns0:p><ns0:p>The measurements of foot length and arch height were taken under two conditions: 10% and 90% weightbearing loads <ns0:ref type='bibr' target='#b52'>(Zifchock et al., 2017)</ns0:ref>. Arch height flexibility (AHF) was defined as the changes in arch height from 10% to 90% weightbearing conditions, normalized to 80% body weight. Experienced HHS wearers were those who had worn narrow-heeled shoes with a minimum HH of 4 cm more than twice per week and at least eight hours per day for one year.</ns0:p><ns0:p>Inexperienced HHS wearers were participants wearing HHS less than once per week <ns0:ref type='bibr' target='#b17'>(Hapsari &amp; Xiong, 2016;</ns0:ref><ns0:ref type='bibr' target='#b49'>Wan et al., 2019)</ns0:ref>. The study was approved by the ethics committee of Shanghai University of <ns0:ref type='bibr'>Sport (Number: 2018074)</ns0:ref>, and all subjects were provided written consents prior to the experiment. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Experimental shoes</ns0:head><ns0:p>Experimental shoes with HH of 0.8, 3.9, 7.0, and 10.1 cm were used in the study (Figure <ns0:ref type='figure'>1</ns0:ref>). All the experimental shoes were manufactured by the same manufacturer. The shoe style and materials were maintained the same to minimize confounding variance. Except for the 0.8 cm HHS as the baseline condition, the three other types of HHS were featured with narrow-heeled shoes (12.5 mm*12.0 mm). Participants were allowed to familiarize themselves with the most suitable experimental shoes with shoe size ranging from EU 36-39 prior to the experiment. The four HHS testing conditions were assigned to participants in random order.</ns0:p><ns0:p>Insert Figure <ns0:ref type='figure'>1</ns0:ref> here</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Data collection</ns0:head></ns0:div> <ns0:div><ns0:head n='2.3.1'>Postural control</ns0:head><ns0:p>NeuroCom Balance Manager System (Version 9.3, Natus Medical Incorporated, USA) SMART EquiTest was used to assess postural stability by measuring the participants' COG alignment at a sampling frequency of 100 Hz after they were familiar with the experimental HHS <ns0:ref type='bibr' target='#b3'>(Chander et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b17'>Hapsari &amp; Xiong, 2016)</ns0:ref>. Computerized dynamic posturography has been proven to be a 'gold standard' for assessing postural stability with high reliability and validity <ns0:ref type='bibr' target='#b18'>(Harro &amp; Garascia, 2019)</ns0:ref>. Prior to the test, participants were secured with a protective vest from falling off the instrumentation. They were instructed to stand on the two force plates (23 cm*46 cm) with feet aligned with the platform axis as the initial position. SOT and LOS were used to test the participants' standing balance during self-initiated perturbations, whereas postural stability during externally triggered perturbations was tested by motor control test (MCT).</ns0:p><ns0:p>Participants were asked to stand still with their feet fixed in the initial position. A five-minute rest was allowed between three tests to prevent potential fatigue.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.1.1'>Sensory organization test (SOT)</ns0:head><ns0:p>SOT utilizes the sway-referencing capabilities of the visual surroundings and the support surface to evaluate the integration of the sensory systems in postural control by selectively disrupting somatosensory and/or visual information. Moderate to excellent reliability has been Manuscript to be reviewed established in SOT among healthy adults <ns0:ref type='bibr'>(Ford-smith et al., 1995;</ns0:ref><ns0:ref type='bibr' target='#b18'>Harro &amp; Garascia, 2019;</ns0:ref><ns0:ref type='bibr' target='#b47'>Tsang et al., 2004)</ns0:ref>, and among patients with multiple sclerosis <ns0:ref type='bibr' target='#b19'>(Hebert &amp; Manago, 2017)</ns0:ref>and transtibial amputation <ns0:ref type='bibr' target='#b23'>(Jayakaran et al., 2011)</ns0:ref>. The six testing conditions in SOT are described in Table 1 <ns0:ref type='bibr' target='#b51'>(Yin &amp; Wang, 2020)</ns0:ref>. Each testing condition was repeated three times. All the testing orders were randomly assigned to the participants <ns0:ref type='bibr' target='#b11'>(Dickin, 2010)</ns0:ref>. The equilibrium and composite scores (0-100) represent the ability of the participants to maintain postural stability in each condition and overall postural control, respectively. The strategy scores (0-100) quantify the relative amount of movement about the ankle and hip strategies that participants used in maintaining postural stability. A strategy score approaching 100 indicates that ankle strategy is more dominant in maintaining balance, whereas a score closest to 0 suggests that the participant uses hip strategy dominantly to stabilize her body under each trial. Somatosensory (SOM), vestibular (VEST), and visual scores (VIS) (0-100) in sensory analysis quantify the participants' ability to integrate proprioception, vestibulum, and vision information that contribute to balance, respectively.</ns0:p><ns0:p>Insert Table <ns0:ref type='table' target='#tab_1'>1 here</ns0:ref> </ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.1.2'>Motor control test (MCT)</ns0:head><ns0:p>Postural stability under support surface perturbations was assessed by MCT (Figure <ns0:ref type='figure'>2</ns0:ref>). The two force plates with translation capabilities in backward and forward directions can create six perturbing conditions which are small backward translation (SBT), medium backward translation (MBT), large backward translation (LBT), small forward translation (SFT), medium forward translation (MFT), and large forward translation (LFT). Each testing condition was repeated three times. The six testing conditions were assigned in random order. The displacement of the support surface is scaled to the participant's height during each translation. The outcome measures were composite latency and amplitude scaling. Composite latency measures the reaction time from the initiation of translation of the platform to the displacement of COG in milliseconds. Amplitude scaling is measured for right leg in units of angular momentum and normalized to body height and weight, which quantifies the force generated from the lower limb PeerJ reviewing <ns0:ref type='table' target='#tab_2'>PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:ref> Manuscript to be reviewed in response to the external perturbations <ns0:ref type='bibr' target='#b48'>(Vanicek et al., 2013)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Insert Figure 2 here</ns0:head></ns0:div> <ns0:div><ns0:head n='2.3.1.3'>Limits of stability test (LOS)</ns0:head><ns0:p>LOS quantifies the ability of participants to intentionally displace their COG within the BOS.</ns0:p><ns0:p>In LOS, a computerized screen was placed in front of the participants. They were instructed to lean their body on the sagittal plane in each direction to reach to the target location displayed on the screen as quick as possible upon hearing an auditory cue. Then, participants were required to remain in that position for 10 s. The outcome measures were COG movement velocity and directional control (DCL). COG movement velocity in degree per second (&#176;/s) represents the average COG movement speed from the initial place to the target position. Directional control was calculated as the amount of the COG movement toward the intended direction minus the amount of off-axis movement <ns0:ref type='bibr' target='#b51'>(Yin &amp; Wang, 2020)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.2'>Functional mobility test</ns0:head><ns0:p>After postural control tests, functional reach test (FRT) and timed up and go test (TUGT) were performed to measure functional mobility. FRT measures the maximum forward reach of the participants. Participants were instructed to lean their body forward as far as possible without stepping or reaching for assistance. Three trials were conducted for data normalization purposes.</ns0:p><ns0:p>In TUGT, participants were requested to sit on a standard chair with their back against the chair, arms resting on the chair's arms. They were instructed to walk a 3 m straight line, make turns, walk back to the chair and sit down. Participants were asked to walk at their comfortable speed.</ns0:p><ns0:p>The time between the participants' buttocks leaving and touching the seat surface was recoded.</ns0:p><ns0:p>The fastest among the three testing trials was used for data analysis <ns0:ref type='bibr' target='#b38'>(Schoppen et al., 1999)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.3'>Perceived stability</ns0:head><ns0:p>Thereafter, the participants were instructed to quantify their perceived stability in FRT on a visual analog scale (VAS). The scores range from 0-100. The VAS score of 0 indicates that the participants were perceived as unstable, whereas a score of 100 suggests the most stable situation that can be perceived. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>Statistical analysis</ns0:head><ns0:p>All data were presented as mean &#177; standard deviation (SD). The normal distribution of data was examined by the Shapiro-Wilk test. Repeated measurement of ANOVA (HH * HHS wearing experience) was conducted to detect the effects of HH and HHS wearing experience on each variable. Simple main effect analysis was used for post hoc comparisons. Significance was set at an alpha level of p = 0.05. Partial eta-squared (&#627; 2 ) effect size, 95% confidence interval (CI), and F-statistic were reported. Statistical analysis was performed using SPSS 22.0 statistical software package (SPSS Inc., Chicago, USA).</ns0:p></ns0:div> <ns0:div><ns0:head n='3.'>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>Demographic characteristics of the participants</ns0:head><ns0:p>Table <ns0:ref type='table'>2</ns0:ref> illustrates the characteristics of the participants. No significant differences were observed in age, height, weight, body mass index (BMI), foot length 10% weightbearing, foot length 90% weightbearing and AHF between the two groups. The experienced group showed significantly higher HHS wearing frequency than the inexperienced group (p &lt;0.001).</ns0:p></ns0:div> <ns0:div><ns0:head>Insert Table 2 here</ns0:head></ns0:div> <ns0:div><ns0:head n='3.2'>SOT</ns0:head><ns0:p>The descriptive data of SOT are shown in Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>. No statistically significant interaction was found between the HH and HHS wearing experience on the outcome measures of SOT (Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>). The main effect of HH was significant for the equilibrium score in C1 (F(3,38)=8.342, p &lt; 0.001, &#627; 2 =0.202), C2 (F(3,38)=14.498, p &lt; 0.001, &#627; 2 =0.202), C3 (F(3,38)=10.428, p &lt; 0.001, &#627; 2 =0.202), and C5 (F(3,38)=10.920, p &lt; 0.001, &#627; 2 =0.202). No significant effect of HHS wearing experience was found on the equilibrium score. Post hoc analysis revealed significantly lower equilibrium score in 10.1 cm than 7 cm HHS among experienced HHS wearers in C2 (p=0.035, 95% CI=0.143-5.590).</ns0:p><ns0:p>The main effect of HH was significant for the strategy score in six conditions <ns0:ref type='bibr'>(F(3,38)</ns0:ref> Manuscript to be reviewed in C3 (F(1,40)=10.841, p=0.002, &#627; 2 =0.218), C5 (F(1,40)=4.977, p=0.032, &#627; 2 =0.022), and C6 (F(1,40)=5.857, p=0.020, &#627; 2 =0.132). The strategy score decreased significantly when HH increased to 7 cm compared with flat shoes among experienced HHS wearers in C5 (p=0.001, 95% CI=0.997-4.036). In C3, the experienced HHS wearers demonstrated significantly higher strategy score than inexperienced HHS wearers in flat shoes (t=&#8722;2.231, p=0.033), 3.9 cm (t=&#8722;2.404, p=0.023), and 10.1 cm HHS (t=&#8722;3.327, p=0.002; Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>).</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref> illustrates that the main effect of HH was significant for sensory analysis score in SOM (F(3,38)=3.059, p=0.031, &#627; 2 =0.099) and VIS (F(3,38)=4.270, p=0.010, &#627; 2 =0.099), but the main effect of wearing experience was undetected. Post hoc analysis showed that the sensory analysis score declined significantly in VIS when wearing 10.1 cm HHS compared with flat shoes in inexperienced wearers (p=0.008, 95% CI=1.470-12.244).</ns0:p></ns0:div> <ns0:div><ns0:head>Insert Table 3 here</ns0:head></ns0:div> <ns0:div><ns0:head n='3.3'>MCT</ns0:head><ns0:p>No significant interaction between the HH and wearing experience was detected on outcome measures of MCT. As shown in Table <ns0:ref type='table'>4</ns0:ref>, the main effect of HH was significant for the composite latency (F(3,38)=3.121, p=0.044, &#627; 2 =0.080), whereas no significant difference was detected in the pairwise comparison. The HH revealed a significant main effect on amplitude scaling in SBT (F(3,38)=7.004, p &lt; 0.001, &#627; 2 =0.163), MBT (F(3,38)=3.630, p=0.015, &#627; 2 =0.092), SFT (F(3,38)=15.604, p &lt; 0.001, &#627; 2 =0.302), MFT (F(3,38)=24.919, p &lt; 0.001, &#627; 2 =0.409), and LFT (F(3,38)=9.522, p &lt; 0.001, &#627; 2 =0.209). No significant main effect was investigated for HHS wearing experience on amplitude scaling in six perturbing conditions. In MFT, the amplitude scaling was significantly higher when HH increased to 7 cm compared with flat shoes among experienced wearers (p=0.013, 95% CI=&#8722;2.193-0.207).</ns0:p></ns0:div> <ns0:div><ns0:head>Insert Table 4 here</ns0:head></ns0:div> <ns0:div><ns0:head n='3.4'>LOS</ns0:head><ns0:p>As shown in Table <ns0:ref type='table'>5</ns0:ref>, no statistically significant interaction was found between the HH and HHS wearing experience on COG movement velocity, whereas the two-way interaction was significant on directional control (F(3,38)=7.790, p &lt; 0.001, &#627; 2 =0.166). The main effect of HH PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020) was significant for COG movement velocity (F(3,38)=20.770, p &lt; 0.001, &#627; 2 =0.347) and directional control (F(3,38)=75.478, p &lt; 0.001, &#627; 2 =0.659). The significant main effect of wearing experience was also determined for directional control (F(1,40)=5.114, p=0.029, &#627; 2 =0.116). The results of post hoc analysis showed that COG movement velocity decreased significantly when wearing 3.9 cm HHS compared with 10.1 cm HHS among experienced wearers (p=0.001, 95% CI=0.310&#176;/s-1.480&#176;/s). Experienced HHS wearers exhibited significantly higher COG directional control than inexperienced wearers when wearing 10.1 cm HHS (t=-3.391, p=0.002).</ns0:p></ns0:div> <ns0:div><ns0:head>Insert Table 5 here</ns0:head></ns0:div> <ns0:div><ns0:head n='3.5'>Functional mobility</ns0:head><ns0:p>Table <ns0:ref type='table'>6</ns0:ref> illustrates that the two-way interaction (HH * wearing experience) was significant for FRT distance (F(3,38)=3.858, p=0.016, &#627; 2 =0.090) and TUGT time (F(3,38)=9.883, p &lt; 0.001, &#627; 2 =0.202). The main effect of HH was significant for FRT distance (F(3,38)=94.859, p &lt; 0.001, &#627; 2 =0.709) and TUGT time (F(3,38)=127.372, p &lt; 0.001, &#627; 2 =0.766). Significant main effect of wearing experience was also determined for FRT distance (F(1,40)=10.840, p=0.002, &#627; 2 =0.217) and TUGT time (F(1,40)=10.639, p=0.0021, &#627; 2 =0.214). With respect to the results of the pairwise comparison, generally, functional mobility decreased as HH increased. FRT distance was significantly shorter in 10.1 HHS than in flat shoes (p &lt; 0.001, 95% CI=3.170-8.973 cm), 3.9 cm (p &lt; 0.001, 95% CI=4.254-8.146 cm), and 7 cm HHS (p &lt; 0.001, 95% CI=2.675-6.225 cm) among experienced wearers. TUGT time showed a significant difference when wearing different HHS in experienced and inexperienced wearers. Experienced wearers performed longer FRT distance than inexperienced wearers in 3.9 cm (t=&#8722;2.714, p=0.010), 7 cm (t=&#8722;2.805, p=0.003) and 10.1 cm HHS (t=&#8722;4.524, p &lt; 0.001). Similarly, TUGT time in experienced wearers was significantly shorter than inexperienced HHS wearers in 3.9 cm (t=3.528, p=0.010), 7 cm (t=3.117, p=0.003), and 10.1 cm HHS (t=3.698, p=0.001).</ns0:p></ns0:div> <ns0:div><ns0:head>Insert Table 6 here</ns0:head></ns0:div> <ns0:div><ns0:head n='3.6'>Perceived stability</ns0:head><ns0:p>The main effect of HH (F(3,38)=26.911, p &lt; 0.001, &#627; 2 =0.415) and wearing experience Manuscript to be reviewed (F(1,40)=11.517, p=0.001, &#627; 2 =0.027) was significant for perceived stability. No significant twoway interaction was detected on perceived stability. The perceived stability was decreased with increased HH. Specificity, the perceived stability reduced significantly in 7 cm HHS relative to flat shoes (p=0.001, 95% CI=5.530-26.049) and 3.9 cm HHS (p=0.029, 95% CI=0.940-23.060) among experienced wearers. The inexperienced wearers also perceived significantly decreased stability with increased HH similar to the experienced wearers (Table <ns0:ref type='table'>6</ns0:ref>). The experienced wearers perceived significantly higher stability than inexperienced wearers in 3.9 cm (t=&#8722;3.538, p=0.002), 7 cm (t=&#8722;3.719, p=0.001), and 10.1 cm HHS (t=&#8722;2.656, p=0.011).</ns0:p></ns0:div> <ns0:div><ns0:head>Insert Table 6 here</ns0:head></ns0:div> <ns0:div><ns0:head n='4.'>Discussion</ns0:head><ns0:p>The main purpose of the study is to evaluate the effects of HH and HHS wearing experience on human postural stability under dynamic perturbations. During self-initiated standing perturbations, HHS wearers exhibited decreased equilibrium and strategy scores in 10.1 cm HHS, compared with flat shoes and 3.9 and 7 cm HHS. Vision played a vital role in the integration of the sensory systems in the postural control process with elevated HH. With respect to the control of the COG movement, the COG movement velocity and directional control declined in 10.1 cm HHS compared with flat shoes and 3.9 cm HHS. During external support surface perturbations, the postural latencies tended to delay with elevated HH. Amplitude scaling increased when HH increased to 3.9 cm compared with flat shoes. Similarly, impaired functional mobility can be detected in 3.9 cm HHS contrary to flat shoes. However, experienced HHS wearers did not show significant higher composite equilibrium scores than novices as the authors hypothesized. No difference in the somatosensory function and postural responses under external perturbations was found between the two groups. Experienced wearers utilized higher proportion of ankle strategy and COG directional control in maintaining postural stability. They perceived higher stability and performed better functional mobility than inexperienced HHS wearers.</ns0:p><ns0:p>In SOT, decreased equilibrium and strategy scores were found in 10.1 cm HHS, compared with flat shoes and 3.9 and 7 cm shoes. The ability to integrate the sensory systems to maintain Manuscript to be reviewed the stability of the body's equilibrium was impaired in 10.1 HHS. HHS wearers intended to use a larger portion of vision than proprioception in the postural control process when wearing 10.1 cm HHS. However, the anticipatory postural reactions from proprioceptive receptors played a vital role in maintaining balance, especially in the absence of vision <ns0:ref type='bibr' target='#b31'>(Mika et al., 2016)</ns0:ref>. In SOT, the elevated HH may simulate an unstable condition. The sensory condition is more challenged because the support surface and vision are sway referenced. Humans can increase sensory weighting to vestibular and vision information for postural orientation when surrounded by these sway-referenced vision and unstable surfaces <ns0:ref type='bibr' target='#b21'>(Horak, 2006)</ns0:ref>. Our study demonstrated that hip strategy was adopted more than ankle strategy by HHS wearers with increased HH under interfered conditions. With the increase in HH, the distance of the ankle and hip joints from the line of gravity is reduced <ns0:ref type='bibr' target='#b43'>(Stefanyshyn et al., 2000)</ns0:ref>. HHS wearers cannot exert torque at the ankles to rapidly move the body's COM <ns0:ref type='bibr' target='#b22'>(Horak &amp; Kuo, 2000;</ns0:ref><ns0:ref type='bibr' target='#b49'>Wan et al., 2019)</ns0:ref>. A higher percentage of hip strategy is used to generate a larger torque about the hip joint to realign the COG in response to higher HH <ns0:ref type='bibr' target='#b48'>(Vanicek et al., 2013)</ns0:ref>. The early activation of the hip flexors may be involved in response to the translation of support surface <ns0:ref type='bibr' target='#b22'>(Horak &amp; Kuo, 2000)</ns0:ref>. Our study's results are in line with Xiong's study, in which the hip strategy was used because the ankle strategy failed to maintain balance when wearing HHS <ns0:ref type='bibr' target='#b17'>(Hapsari &amp; Xiong, 2016)</ns0:ref>. The ankle strategy is the first postural control strategy adopted by humans to counteract small perturbations of the COG. On the contrary, hip strategy is used in response to larger perturbations. Human often utilize the combination of ankle and hip strategies for postural correction under external perturbations. The proportion of the strategies that distributed in the postural correction is organized by central nervous system (CNS), based on somatosensory input <ns0:ref type='bibr' target='#b41'>(Shumway-Cook &amp; Horak, 1986)</ns0:ref>. Our study showed that the HHS wearing experience had no significant effect on the overall human postural control. Human postural control is considered a complex motor skill with respect to the support surface, visual environment, and cognitive process (Shumway-Cook <ns0:ref type='bibr' target='#b41'>&amp; Horak, 1986)</ns0:ref>. Experienced wearers were found to adapt to walking regularity more flexibly under cognitive load than HHS novices <ns0:ref type='bibr' target='#b37'>(Schaefer &amp; Lindenberger, 2013)</ns0:ref>. Significant different Manuscript to be reviewed muscle efforts were exerted in HHS experts compared with novices <ns0:ref type='bibr' target='#b43'>(Stefanyshyn et al., 2000)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Studies have shown that wearing experience can influence the ankle ROM and muscle strength.</ns0:head><ns0:p>A more supinated position was found in HHS experts compared with novices. The higher ankle ROM of inversion and plantarflexion might affect efficient force conduction on foot arch and increase the risk of anterior talofibular ligament sprains in experienced HHS wearer <ns0:ref type='bibr' target='#b12'>(Ebbeling et al., 1994;</ns0:ref><ns0:ref type='bibr' target='#b25'>Kim et al., 2013)</ns0:ref>. The long-term adaptation of the supinated position in HHS experts would shorten the length of muscle fibers, decrease the amount of cross bridges of the muscle fibers and disturb the function of calf muscles ultimately <ns0:ref type='bibr' target='#b45'>(Timmins et al., 2016)</ns0:ref>. The muscle performance of calf muscles might be affected on account of the increased concentric contraction power in ankle inversion. The increased mediolateral instability would induce the changes in power production owning to the habitual use of narrow heels in experts <ns0:ref type='bibr' target='#b43'>(Stefanyshyn et al., 2000)</ns0:ref>. In addition, the muscle performance of calf muscles may be affected on account of the decreased plantarflexion torque and higher reduction on plantarflexion power in experienced HHS wearers <ns0:ref type='bibr' target='#b13'>(Farrag &amp; Elsayed, 2016)</ns0:ref>. Generally, HHS experience might further influence muscle activities and cognitive processing. However, the ability to integrate the sensory systems in postural control was not altered; this finding is supported by Xiong's study <ns0:ref type='bibr' target='#b17'>(Hapsari &amp; Xiong, 2016)</ns0:ref>.</ns0:p><ns0:p>With regard to MCT, the amplitude scaling increased significantly when HH reach 3.9 cm. Although the composite latency was 4.06% lower in 10.1 HH than in 3.9 cm HH, no significantly delayed postural latency in response to external perturbations was found in our study. Similarly, previous studies have shown no significant difference in postural reaction time when wearing flip-flops, clog style Crocs, and Vibram Five-Fingers <ns0:ref type='bibr' target='#b3'>(Chander et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Footwear design characteristics may influence human postural reaction because elevated HH can disturb the ROM of ankle joints and affect human postural control in response to forward translations accordingly. When HH reached 3.9 cm, the increased amplitude scaling suggested that HHS wearers may alter motor output strategies to maintain postural stability under perturbations. In the motor output process, the gastrocnemius medialis (GM), gastrocnemius PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020) lateralis (GL), tibialis anterior (TA), and vastus lateralis (VL) were found to exert more effort when wearing 7 cm HHS compared to flat shoes <ns0:ref type='bibr' target='#b17'>(Hapsari &amp; Xiong, 2016)</ns0:ref>. The threshold of afferent discharge of muscle spindle was raised. The HHS wearers' postural control can be affected for the somatosensory alternation around the ankle and foot <ns0:ref type='bibr' target='#b15'>(Gefen et al., 2002)</ns0:ref>.</ns0:p><ns0:p>However, no adverse effect on postural reaction was found even in 10.1 cm HHS. This finding suggested that the delay of latency was often associated with neurological disorders and anatomical constraints, other than the footwear design <ns0:ref type='bibr' target='#b36'>(Redfern et al., 2001)</ns0:ref>. Previous studies demonstrated that HHS can impair human balance during other extrinsic perturbations (e.g., sinusoidal oscillations and waist pulling) <ns0:ref type='bibr' target='#b7'>(Choi &amp; Cho, 2006;</ns0:ref><ns0:ref type='bibr' target='#b44'>Sun et al., 2017)</ns0:ref>. <ns0:ref type='bibr'>Sun et al. found</ns0:ref> that the COP displacement increased, and the COP trajectory transferred to the medial foot significantly during AP and ML perturbations when wearing 6.6 cm compared with 0.8 cm HH.</ns0:p><ns0:p>However, the study did not control the shoe design and applied three types of HHS in the experiment <ns0:ref type='bibr' target='#b44'>(Sun et al., 2017)</ns0:ref>. Choi and Cho compared human balance control of HHS wearers in barefoot and high-heeled posture when experiencing a waist-pull perturbation by quantifying the displacement and velocity of the COP. Results suggested that human balance control was approximately twice worse in HHS than barefoot, and the perturbation amplitude was not attributed to the participants' body weight and height <ns0:ref type='bibr' target='#b7'>(Choi &amp; Cho, 2006)</ns0:ref>. Experienced HHS wearers exhibited no improvement in postural control under dynamic perturbations. They applied different muscle activation patterns compared with inexperienced wearers. Experienced wearers exerted significantly more muscle activities on GM and less muscular effort on VL, TA, and erector spinae than novices in SOT <ns0:ref type='bibr' target='#b17'>(Hapsari &amp; Xiong, 2016)</ns0:ref>. During HHS walking, substantial increases in muscle fascicle strains and muscle activation were found in experienced HHS wearers compared with barefoot walking during the stance phase <ns0:ref type='bibr' target='#b9'>(Cronin et al., 2012)</ns0:ref>.</ns0:p><ns0:p>Experienced wearers may regulate the flexibility of the neuromuscular system to adapt to possible perturbations (e.g., walking and external perturbations) and can vary according to different HHs <ns0:ref type='bibr' target='#b1'>(Alkjaer et al., 2012)</ns0:ref>.</ns0:p><ns0:p>Our study investigated that the COG movement velocity and directional control in LOS Manuscript to be reviewed significantly decreased in 10.1 cm compared with that in 3.9 cm HHS. Consistent with the previous study, when HH increased to 10 cm, slower COG movement velocity was observed in 10 cm than in 4cm HH in LOS <ns0:ref type='bibr' target='#b31'>(Mika et al., 2016)</ns0:ref>. The increased HH may induce the fear of falling in HHS wearers. The HHS wearers manifested slow COG movement velocity, declined COG excursions, and worst directional control, particularly in the forward and backward directions <ns0:ref type='bibr' target='#b17'>(Hapsari &amp; Xiong, 2016)</ns0:ref>. The experienced HHS wearers showed higher percentage of directional control in 10.1 cm HHS. It may be due to the motor learning effects in the experienced wearer, resulting in superior ankle strategy in maintaining postural stability <ns0:ref type='bibr' target='#b37'>(Schaefer &amp; Lindenberger, 2013)</ns0:ref>. Nonetheless, another study suggested that the increased muscular coactivation around the ankle joint could enhance joint stiffness during HHS walking.</ns0:p><ns0:p>The walking balance may be improved through altered muscle activation patterns <ns0:ref type='bibr' target='#b1'>(Alkjaer et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b33'>Nielsen &amp; Kagamihara, 1993)</ns0:ref>. The effects of muscle activation patterns on the postural control process in LOS among HHS wearers remain unclear.</ns0:p><ns0:p>The functional mobility was impaired when HH reached 3.9 cm. A number of studies have shown that walking in HHS may affect neuromechanics and kinematics of the lower limbs when HH increased to 4 cm HH <ns0:ref type='bibr' target='#b32'>(Naik et al., 2017)</ns0:ref>. When walking in 4 and 10 cm HHS compared with flat shoes, the postural stability may be decreased on the account of high joint stiffness evaluated by muscle pair synchronization around the knee joint <ns0:ref type='bibr' target='#b34'>(Pratihast et al., 2018)</ns0:ref>. Accordingly, the TUGT completion time was longer for impaired postural stability and reduced perceived stability, consistent with previous findings <ns0:ref type='bibr' target='#b2'>(Arnadottir &amp; Mercer, 2000)</ns0:ref>. Our study found that the experienced HHS wearers had significantly shorter TUGT completion time and FRT distance than the novices. Long-time use of HHS has been suggested to shorten the gastrocnemius muscle fascicles and increase the Achilles tendon stiffness, thereby contributing to a restricted ankle ROM and reduced functional reach mobility <ns0:ref type='bibr' target='#b10'>(Csapo et al., 2010)</ns0:ref>. <ns0:ref type='bibr'>Cronin et al.</ns0:ref> suggested that experienced HHS wearers may have increased muscle fascicle strains and lower limb muscle activation than inexperienced wearers during HHS walking. This finding indicates chronic adaptations in muscle-tendon structure related to HHS <ns0:ref type='bibr' target='#b9'>(Cronin et al., 2012)</ns0:ref>. The experienced Manuscript to be reviewed wearers could apply altered movement strategies to increase effort on muscular control around the knee and ankle joints, so as to obtain postural stability during HHS walking. However, high muscle activities may contribute to muscle inefficiency and raised energy cost during walking, thereby leading to muscle strains, muscle fatigue, and pain <ns0:ref type='bibr' target='#b8'>(Cronin, 2014;</ns0:ref><ns0:ref type='bibr' target='#b10'>Csapo et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b12'>Ebbeling et al., 1994)</ns0:ref>.</ns0:p><ns0:p>Although we found better functional mobility and higher perceived stability in experienced HHS wearer, no significant increase in overall postural control was detected in long-time HHS users in SOT. In functional tests, important resources, such as biomechanical constraints (e.g., strength and limits of stability), cognitive processing (e.g., learning and attention), movement strategies (e.g., anticipatory and voluntary), and sensory strategies (e.g., sensory integration and reweighting), are required for postural control. Thus, the loss of somatosensory in the foot and higher sensory weighting in vision cannot completely predict the deficiencies in functional mobility because the function depends on the aforementioned resources likewise <ns0:ref type='bibr' target='#b21'>(Horak, 2006;</ns0:ref><ns0:ref type='bibr' target='#b22'>Horak and Kuo, 2000)</ns0:ref>. In terms of HH, we assume that the decreased perceived comfort and loss of joint position may lead to low perceived stability, compromising functional mobility accordingly <ns0:ref type='bibr' target='#b20'>(Hong et al., 2005;</ns0:ref><ns0:ref type='bibr'>Lee &amp; Hong, 2005)</ns0:ref>.</ns0:p><ns0:p>The limitation of the study is that the results may not be extrapolated to all HHS populations from different ages and health statuses, considering that we only recruited healthy young females in our study. Besides, the neuromuscular mechanism of postural control in HHS wearers is still unknown. The effects of HH and long-term use of HHS on lower limb muscle activities, muscle coordination, and Hoffmann reflex need to be further studied to elucidate how CNS controls motor output in the postural control process. Furthermore, to provide evidence-based information for clinicians, more cohort studies can be conducted to explore the relationship between wearing experience and HHS-related injuries such as metatarsalgia and ankle sprain.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.'>Conclusions</ns0:head><ns0:p>Perceived stability and functional mobility decreased when wearing HHS. The vision system had high weight in maintaining postural stability when HH increased to 10.1 cm. During Manuscript to be reviewed dynamic perturbations, higher percentage of ankle strategies and motor control strategies was exhibited when wearing 3.9 cm HHS compared with flat shoes. In terms of HHS experience, experienced HHS wearers used higher proportion of ankle strategy and COG directional control in postural control than novices. In addition, experienced wearers perceived higher postural stability and showed better functional mobility. It is recommended that on evaluating the postural stability of HHS wearers, sensory organization ability, ankle strategy and COG directional control could be considered to be useful in developing a safety system and prevent HHS wearers from falling.</ns0:p></ns0:div> <ns0:div><ns0:head>Acknowledgment</ns0:head><ns0:p>Yiyang Chen contributed to conceptualization, methodology, formal analysis, investigation, and writing -Original Draft. Lin Wang contributed to conceptualization, methodology, and supervision. Jing Xian Li participated in conceptualization and writing -Review &amp; Editing.</ns0:p><ns0:p>The authors appreciate the kind participation of all the subjects. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='38,42.52,178.87,525.00,328.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='39,42.52,178.87,525.00,299.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head /><ns0:label /><ns0:figDesc>=5.601, p=0.002, &#627; 2 =0.126). The main effect of wearing experience was also significant</ns0:figDesc><ns0:table><ns0:row><ns0:cell>=12.234, p &lt; 0.001, &#627; 2 =0.176; F(3,38)=29.763, p &lt; 0.001, &#627; 2 =0.271; F(3,38)=21.591, p &lt;</ns0:cell></ns0:row><ns0:row><ns0:cell>0.001, &#627; 2 =0.356; F(3,38)=3.125, p=0.036, &#627; 2 =0.074; F(3,38)=10.598, p &lt; 0.001, &#627; 2 =0.214;</ns0:cell></ns0:row><ns0:row><ns0:cell>F(3,38)</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 : Six testing conditions of SOT.</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell cols='2'>Condition Eyes</ns0:cell><ns0:cell cols='3'>Support Surface Visual Surroundings Anticipated Sensory Systems</ns0:cell></ns0:row><ns0:row><ns0:cell>1</ns0:cell><ns0:cell>Open</ns0:cell><ns0:cell>Fixed</ns0:cell><ns0:cell>Fixed</ns0:cell><ns0:cell>Somatosensory</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell cols='2'>Closed Fixed</ns0:cell><ns0:cell>Fixed</ns0:cell><ns0:cell>Somatosensory</ns0:cell></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell>Open</ns0:cell><ns0:cell>Fixed</ns0:cell><ns0:cell>Sway referenced</ns0:cell><ns0:cell>Somatosensory</ns0:cell></ns0:row><ns0:row><ns0:cell>4</ns0:cell><ns0:cell>Open</ns0:cell><ns0:cell cols='2'>Sway referenced Fixed</ns0:cell><ns0:cell>Vision and vestibular</ns0:cell></ns0:row><ns0:row><ns0:cell>5</ns0:cell><ns0:cell cols='3'>Closed Sway referenced Fixed</ns0:cell><ns0:cell>Vestibular</ns0:cell></ns0:row><ns0:row><ns0:cell>6</ns0:cell><ns0:cell>Open</ns0:cell><ns0:cell cols='2'>Sway referenced Sway referenced</ns0:cell><ns0:cell>Vestibular</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 3 : 2 Comparison of outcome measures (means &#177; SD) in SOT for four HHS in inexperienced and experienced groups.</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell cols='3'>Inexperienced HHS wearers (N=21)</ns0:cell><ns0:cell /><ns0:cell cols='3'>Experienced HHS wearers (N=20)</ns0:cell><ns0:cell /><ns0:cell>p values</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.8 cm</ns0:cell><ns0:cell>3.9 cm</ns0:cell><ns0:cell>7 cm</ns0:cell><ns0:cell>10.1 cm</ns0:cell><ns0:cell>0.8 cm</ns0:cell><ns0:cell>3.9 cm</ns0:cell><ns0:cell>7 cm</ns0:cell><ns0:cell>10.1 cm</ns0:cell><ns0:cell>Within groups</ns0:cell><ns0:cell>Between groups</ns0:cell><ns0:cell>Two-way interaction</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Equilibrium score</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>C1</ns0:cell><ns0:cell>93.02&#177;3.72</ns0:cell><ns0:cell cols='3'>93.40&#177;2.82 92.46&#177;3.36 91.52&#177;2.40</ns0:cell><ns0:cell>93.58&#177;2.54</ns0:cell><ns0:cell>93.57&#177;2.03</ns0:cell><ns0:cell>92.80&#177;2.61</ns0:cell><ns0:cell>91.37&#177;2.39</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>0.735</ns0:cell><ns0:cell>0.877</ns0:cell></ns0:row><ns0:row><ns0:cell>C2</ns0:cell><ns0:cell>90.76&#177;2.58</ns0:cell><ns0:cell cols='3'>91.20&#177;4.21 89.44&#177;4.24 87.86&#177;4.25</ns0:cell><ns0:cell>91.37&#177;2.76</ns0:cell><ns0:cell>91.55&#177;2.59</ns0:cell><ns0:cell>90.83&#177;1.71</ns0:cell><ns0:cell>87.97&#177;4.65</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>0.473</ns0:cell><ns0:cell>0.672</ns0:cell></ns0:row><ns0:row><ns0:cell>C3</ns0:cell><ns0:cell>89.89&#177;4.42</ns0:cell><ns0:cell cols='3'>89.91&#177;3.99 88.86&#177;4.59 86.52&#177;4.34</ns0:cell><ns0:cell>91.25&#177;3.21</ns0:cell><ns0:cell>91.08&#177;2.76</ns0:cell><ns0:cell>89.57&#177;4.01</ns0:cell><ns0:cell>87.95&#177;4.61</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>0.226</ns0:cell><ns0:cell>0.921</ns0:cell></ns0:row><ns0:row><ns0:cell>C4</ns0:cell><ns0:cell cols='4'>85.35&#177;10.46 88.19&#177;9.99 87.78&#177;7.44 89.95&#177;3.40</ns0:cell><ns0:cell>88.93&#177;8.69</ns0:cell><ns0:cell>89.62&#177;6.08</ns0:cell><ns0:cell>90.00&#177;4.83</ns0:cell><ns0:cell>89.55&#177;4.78</ns0:cell><ns0:cell>0.187</ns0:cell><ns0:cell>0.340</ns0:cell><ns0:cell>0.425</ns0:cell></ns0:row><ns0:row><ns0:cell>C5</ns0:cell><ns0:cell cols='4'>80.11&#177;10.37 79.56&#177;9.39 81.14&#177;6.44 80.56&#177;4.78</ns0:cell><ns0:cell>81.82&#177;7.81</ns0:cell><ns0:cell>79.62&#177;9.01</ns0:cell><ns0:cell>80.78&#177;5.45</ns0:cell><ns0:cell>81.42&#177;6.27</ns0:cell><ns0:cell>0.563</ns0:cell><ns0:cell>0.763</ns0:cell><ns0:cell>0.799</ns0:cell></ns0:row><ns0:row><ns0:cell>C6</ns0:cell><ns0:cell cols='4'>72.97&#177;10.87 76.81&#177;9.46 77.25&#177;9.37 80.90&#177;5.23</ns0:cell><ns0:cell cols='2'>76.70&#177;12.27 75.65&#177;9.80</ns0:cell><ns0:cell cols='2'>79.10&#177;11.12 85.01&#177;4.80</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>0.358</ns0:cell><ns0:cell>0.292</ns0:cell></ns0:row><ns0:row><ns0:cell>COMP</ns0:cell><ns0:cell>83.52&#177;7.35</ns0:cell><ns0:cell cols='3'>84.86&#177;5.94 84.86&#177;5.70 84.52&#177;3.16</ns0:cell><ns0:cell>85.85&#177;6.33</ns0:cell><ns0:cell>85.20&#177;4.70</ns0:cell><ns0:cell>85.95&#177;4.84</ns0:cell><ns0:cell>85.15&#177;5.09</ns0:cell><ns0:cell>0.776</ns0:cell><ns0:cell>0.463</ns0:cell><ns0:cell>0.533</ns0:cell></ns0:row><ns0:row><ns0:cell>Strategy score</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>C1</ns0:cell><ns0:cell>95.06&#177;2.47</ns0:cell><ns0:cell cols='3'>84.86&#177;5.94 84.86&#177;5.70 84.52&#177;3.16</ns0:cell><ns0:cell>95.58&#177;1.34</ns0:cell><ns0:cell>95.90&#177;1.18</ns0:cell><ns0:cell>94.98&#177;1.73</ns0:cell><ns0:cell>94.13&#177;1.82</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>0.318</ns0:cell><ns0:cell>0.900</ns0:cell></ns0:row><ns0:row><ns0:cell>C2</ns0:cell><ns0:cell>93.90&#177;2.34</ns0:cell><ns0:cell cols='3'>93.40&#177;2.82 92.46&#177;3.36 91.52&#177;2.40</ns0:cell><ns0:cell>94.78&#177;1.64</ns0:cell><ns0:cell>94.92&#177;1.57</ns0:cell><ns0:cell>93.92&#177;1.39</ns0:cell><ns0:cell>90.98&#177;3.55</ns0:cell><ns0:cell>&lt;0.001</ns0:cell><ns0:cell>0.145</ns0:cell><ns0:cell>0.701</ns0:cell></ns0:row><ns0:row><ns0:cell>C3</ns0:cell><ns0:cell>94.17&#177;2.01</ns0:cell><ns0:cell cols='3'>91.20&#177;4.21 89.44&#177;4.24 87.86&#177;4.25</ns0:cell><ns0:cell cols='3'>95.30&#177;1.11* 95.37&#177;1.11* 94.22&#177;2.03</ns0:cell><ns0:cell cols='2'>93.17&#177;1.91* &lt;0.001</ns0:cell><ns0:cell>0.002</ns0:cell><ns0:cell>0.278</ns0:cell></ns0:row><ns0:row><ns0:cell>C4</ns0:cell><ns0:cell>89.24&#177;3.40</ns0:cell><ns0:cell cols='3'>89.91&#177;3.99 88.86&#177;4.59 86.52&#177;4.34</ns0:cell><ns0:cell>90.58&#177;2.44</ns0:cell><ns0:cell>90.70&#177;2.78</ns0:cell><ns0:cell>90.03&#177;2.30</ns0:cell><ns0:cell>89.73&#177;2.73</ns0:cell><ns0:cell>0.036</ns0:cell><ns0:cell>0.104</ns0:cell><ns0:cell>0.837</ns0:cell></ns0:row><ns0:row><ns0:cell>C5</ns0:cell><ns0:cell>85.05&#177;4.37</ns0:cell><ns0:cell cols='3'>88.19&#177;9.99 87.78&#177;7.44 89.95&#177;3.40</ns0:cell><ns0:cell>87.22&#177;2.76</ns0:cell><ns0:cell>85.50&#177;5.02</ns0:cell><ns0:cell>84.70&#177;3.42</ns0:cell><ns0:cell cols='2'>84.68&#177;2.18* &lt;0.001</ns0:cell><ns0:cell>0.032</ns0:cell><ns0:cell>0.061</ns0:cell></ns0:row><ns0:row><ns0:cell>C6</ns0:cell><ns0:cell>84.44&#177;4.33</ns0:cell><ns0:cell cols='3'>79.56&#177;9.39 81.14&#177;6.44 80.56&#177;4.78</ns0:cell><ns0:cell>86.87&#177;3.55</ns0:cell><ns0:cell cols='2'>87.10&#177;2.54* 85.27&#177;5.16</ns0:cell><ns0:cell cols='2'>85.02&#177;4.80* 0.002</ns0:cell><ns0:cell>0.020</ns0:cell><ns0:cell>0.235</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Sensory analysis score</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>SOM</ns0:cell><ns0:cell>97.86&#177;3.14</ns0:cell><ns0:cell cols='3'>97.62&#177;3.32 96.81&#177;3.09 96.19&#177;3.93</ns0:cell><ns0:cell>97.90&#177;2.29</ns0:cell><ns0:cell>98.05&#177;1.82</ns0:cell><ns0:cell>98.05&#177;2.39</ns0:cell><ns0:cell>96.40&#177;3.95</ns0:cell><ns0:cell>0.031</ns0:cell><ns0:cell>0.450</ns0:cell><ns0:cell>0.756</ns0:cell></ns0:row><ns0:row><ns0:cell>VIS</ns0:cell><ns0:cell>91.71&#177;9.56</ns0:cell><ns0:cell cols='3'>94.48&#177;9.42 94.90&#177;6.06 98.57&#177;3.60</ns0:cell><ns0:cell>95.20&#177;9.05</ns0:cell><ns0:cell>95.95&#177;6.08</ns0:cell><ns0:cell>97.10&#177;4.12</ns0:cell><ns0:cell>97.95&#177;4.37</ns0:cell><ns0:cell>0.010</ns0:cell><ns0:cell>0.247</ns0:cell><ns0:cell>0.484</ns0:cell></ns0:row><ns0:row><ns0:cell>VEST</ns0:cell><ns0:cell cols='4'>86.10&#177;10.24 85.10&#177;9.08 87.62&#177;5.95 88.24&#177;4.89</ns0:cell><ns0:cell>87.45&#177;7.57</ns0:cell><ns0:cell>85.10&#177;9.57</ns0:cell><ns0:cell>87.15&#177;4.98</ns0:cell><ns0:cell>89.20&#177;6.70</ns0:cell><ns0:cell>0.097</ns0:cell><ns0:cell>0.781</ns0:cell><ns0:cell>0.872</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot' n='3'>Note: SOM, somatosensory score; VIS, visual score; VEST, vestibular score; *, Inexperienced vs. experienced HHS wearers, p &lt; 0.05.4 PeerJ reviewing PDF | (2020:07:50629:1:1:NEW 23 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"School of Kinesiology Shanghai University of Sport 188 Hengren Road Shanghai, China, 200438 Tel : (86) 21 5125 3426 Fax : (86) 21 5125 3470 Email: [email protected] September 15, 2020 Dear reviewers and editors, On behalf of our research team, I would like to take this opportunity to kindly thank you for offering your time to review our manuscript and give generous comments. Accordingly, we have revised the manuscript based on these comments and have attached it for consideration. Revisions were used red font in the manuscript. We have also included our responses to the various points raised by the reviewer below. We look forward to hearing from you. Thank you. Yours sincerely, Yiyang Chen for Prof. Lin Wang, MB, PhD #1 reviewer General comment This manuscript describes a study that investigated the impact of heel height and experience of wearing high-heeled shoes (HHS) on postural stability and functional performance parameters. Two groups of female participants (experienced and inexperienced HHS wearers) were recruited, and outcome measures were recorded while wearing shoes with four different heel heights (0.8, 3.9, 7.0, and 10.1 cm). The authors concluded that heel height greater than 3.9 cm could significantly impact the dynamic postural control and functional mobility, while experience may not have as much impact. The study topic is interesting and adds valuable information to the current pool of knowledge. The manuscript is well structured and clearly written. However, proofreading is essential to correct multiple grammatical and typographical errors and sentence structure inaccuracies. Overall, the introduction is well referenced, and the flow of ideas and context is smooth and coherent. The study objectives and hypothesis are clearly written and are relevant to the methodology described. Study design is robust, and methodology is detailed and clear. The discussion is clear of ambiguity and extensive irrational speculations, and the interpretation of the results was logical and supported by suitable references. However, few amendments could enhance clarity and improve quality of the manuscript. Please refer to the specific comments below We thank the reviewer for your suggestions. The comments are valuable for promoting the quality of our manuscript. Specific comments Line 21: please correct grammar. Past tense should be used to describe methodology. Thank you for the correction. We corrected the mistake. (line 21) Line 25: Visual Analogue Scale (VAS) is typically used to assess pain. However, it could be used for different purposes like you did here. Unfortunately, with the current sentence structure, it is unclear that you used the VAS to self-assess the participants' perceived stability. Please revise and amend appropriately. Agreed. We rewrote the sentence as ‘The participants’ self-perceived stability was assessed by visual analog scale.’ (line 25-26) Line 30: 'The vision system had higher weight in 10.1 cm ...'. This is ambiguous and unclear. Please revise. Thank you for the comments. We rewrote the sentence as ‘The contribution of vision to postural stability was larger in 10.1 cm HHS than in flat shoes.’ (line 30-31) Examples of typographical errors: Lines 30, 47, 82, 107, ... We sorry for the mistake. We corrected and checked throughout the manuscript. (line 30; 50; 86; 90; 111; 130; 142;144; 168; 191; 193; 210 etc) Line 53: '....mass (COM; ....'. Abbreviations should not be included between the same brackets as citations. This mistake is repeated several times in the manuscript. Please revise and correct. Thank you for your kind suggestion. We corrected the formatting issue in the manuscript. (line 57; line 70; line 79; line 81; line 161; line 380) Line 108-109: the minimum hours of wearing the HHS for the experienced group could be as low as 16h/week, which I think is very low. Other studies used a minimum of 18-40h/week with higher frequency per week for the habitual HHS users (Cronin el 2012. Long-term use of high-heeled shoes alters the neuromechanics of human walking; Eric et al 2012. Walking on High Heels Changes Muscle Activity and the Dynamics of Human Walking Significantly; Csapo et al 2013. On muscle, tendon and high heels; Farrag and Elsayed 2016. Habitual Use of High-Heeled Shoes Affects Isokinetic Soleus Strength More Than Gastrocnemius in Healthy Young Females). Please explain the reason for using such low habituation time frame for the experienced HHS users. We set the inclusion standard based on Xiong and Wan’s study, as both of the studies are aimed to investigate the effects of HHS wearing experience on standing balance. While most of the HHS-related studies, including participants with higher HHS wearing time are aimed to detect the effects of wearing experience on postural control during walking. The authors chose an inclusion criteria based on the similar experimental design and objective. To the best of our knowledge, most studies did not mention which type of high heel shoes that the experienced wearers are used to wear. In our study, we emphasized and included the participants only accustomed to wear narrow-heeled shoes, which we think it is a challenge for HHS wearers. (Wan FKW, Yick KL, Yu WWM. 2019. Effects of heel height and high-heel experience on foot stability during quiet standing. Gait & Posture 68:252–257; Hapsari VD, Xiong S. 2016. Effects of high heeled shoes wearing experience and heel height on human standing balance and functional mobility. Ergonomics 59(2):249–264) Line 177: this is not the correct description of the TUG test. Please revise and correct. Thank you for the correction. We corrected and rewrote this part. (Line 194-199) Line 313: 'Significant different muscle efforts were exerted in HHS experts compared with novices (Stefanyshyn et al., 2000)'. This statement is very important, and further elaboration about the influence of HHS habituation on muscle performance, particularly around the ankle joint, is necessary for interpretation of the results. Please refer to these articles for further information: 'Farrag A, Elsayed W. Habitual Use of High-Heeled Shoes Affects Isokinetic Soleus Strength More Than Gastrocnemius in Healthy Young Females. Foot Ankle Int. 2016;37(9):1008-1016.' and 'Kim, Y et al. (2013). Changes in Ankle Range of Motion and Muscle Strength in Habitual Wearers of High-Heeled Shoes. Foot & Ankle International, 34(3), 414–419'. Agreed. We expanded the discussion on muscle performance. (line 345-359) Figures 2-4 are complicated and not easy to understand because of the letter coding used to indicate significance. I strongly recommend presenting the data in tables instead of figures. I believe it would be clearer and much easier to understand. Thank you for the great suggestions. We replaced the figures to tables. (Table 5,6) #2 reviewer General comments This study aimed to investigate the influence of heel height and high-heeled shoes wearing experience on the postural stability and functional mobility. Different heel height shoes were worn in experienced and inexperienced females to perform sensory organization test, motor control test and limits of stability test. Interesting findings were presented, however, there are still several points were not clearly clarified, and these issues should be addressed before a further recommendation could be made. Thank you for your suggestions. Your comments provide valuable recommendations to improve the quality of the manuscript. Specific comments 1. Line 38, in the conclusions of Abstract, authors repeated the key findings of the current study, just wondering if any practical or clinical implications could be made from findings of this study. Thank you for your suggestion. We added the potential practical implications in the conclusions of Abstract and Conclusions. It is indeed one of the limitations of our study. We added a few points in the limitations of Discussion. (line 42-44; line 458-461) 2. Line 53-54, formatting issue, please check and revise throughout the manuscript. Thank you for your kind suggestion. We corrected the formatting issue in the manuscript. (line 57; line 70; line 79; line 81; line 161; line 380 etc) 3. Line 56-58, this statement is not clear, also grammar mistake, please correct. Agreed. We checked and rewrote the sentence. (line 60-63) 4. Line 88-90, the statement is not clear, please rewrite. We rewrote the sentence. (line 93-94) 5. Line 143-147, authors used 0-100 to define the strategy scores to quantify the hip and ankle strategy, any reference to support this scoring system, and what is the reliability and repeatability of this scoring system. Thank you for the comments. For the ankle strategy, the test-retest reliability coefficients for the strategy scores indicated excellent reliability in adults with a transtibial amputation (ICC › 0.75) (Jayakaran et al., 2011). Besides, for the equilibrium scores, excellent test-retest reliability was found in healthy older adults (ICC = 0.9) (Harro & Garascia, 2019). We added the reliability of the sensory organization test and the scoring system of the ankle strategy in the manuscript. (line 149-152) 6. Line 152, the Motor control test (MCT), the test protocol is not clear from the current text description, kindly suggest adding the Figure to assist illustration of the test. Agreed. We added a figure for better illustrating the MCT. (Figure 2) 7. Line 156, how was the ‘amplitude’ scaled? By what parameters? We added the definition of amplitude scaling and how it measured in the manuscript. (line 175-177) 8. Line 198, authors presented the demographic information in the Table 2, please also include other anthropometrics, such as leg length, foot length and width, which might also affect the stability and postural control. Agreed. The results of foot length and arch height are presented in Table 2. Studied have shown that the arch height flexibility is related to human postural control. We also calculated and reported the arch height flexibility in Results. The results showed that there is no significant difference in the foot structure parameters between the two groups. (line 114-117; Table 2) 9. Line 286-287, it is an interesting statement here that experienced HHS wears did not show ‘better’ postural control than inexperienced wearers. Please elaborate more details on this point. And how to define the ‘better’ in postural control? Thank you for the comments. We have clarified and replaced the ‘better’ to ‘significant higher composite equilibrium scores’. (line 309-312) 10. Line 299-301, authors mentioned more hip strategy was adopted than the ankle strategy. It is an interesting and key statement here, please discuss more on this point, as the current description is not clear. Agreed. We added and discussed more on the hip and ankle strategy. (line 327-332; line 334-340) 11. Line 341-343, authors discussed that the balance control is not sensible to the body weight and height. Same as #8 comment, wondering the leg length, foot length and width may affect the postural control. Thank you for the comments. We agreed that the weight, height and foot structures might influence human postural control. In our study, the displacement of the support surface is normalized to the participants’ height during each translation in the MCT to exclude the influence of height. Like our respond to #8 comment, no significant difference has been found in arch height, foot length and arch height flexibility between the two groups. 12. Line 408, how to define the ‘better’? please use academic expression. We thank the reviewer for the correction. We replaced the ‘better’ to the ‘higher proportion of ankle strategy’ specifically. Revisions are made throughout the manuscript. (line 40; line 313; line 404; line 454; line 456) 13. Line 411, authors did not include any test or discussion on the falling risk with high heel shoes. Suggestions shall originate from the main content of the study. Please revise. Thank you for the suggestions. We revised this part and suggested that, when evaluating the postural stability of HHS wearers, sensory organization ability, ankle strategy and COG directional control could be considered to be useful in developing a safety system and prevent HHS wearers from falling. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Skin mucus in fish is considered the first barrier between the organism and the environment, partly because it can prevent microorganisms from colonizing the skin. During copulation in sharks, the male bites the female generating wounds, which are then highly likely to become infected by opportunistic bacteria in the water or the male shark's mouth. The role of skin mucus in protecting fish against pathogens is not well understood. Describing the microbial component of epithelial mucus may allow future understanding of this first line of defense in sharks. In this study, we analyzed mucus and tissue samples obtained from 19 individuals of two shark species and a stingray: the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus). We also collected water samples from the area where the animals were found. Total DNA was extracted from all samples, and the bacterial 16S rRNA gene (region V3-V4) was amplified and sequenced on the Ion Torrent Platform (amplicon sequencing). We analyzed sequences and present a summary of the bacterial diversity in the epithelial mucus of these elasmobranch species. Bacterial diversity (order and family) was high, particularly in tissue and mucus samples in all three species, and order and family composition were more similar between the two shark species for both tissue and mucus. Alpha-diversities in orders and families (expShannon and Simpson) were comparatively high and non-significantly different between elasmobranch species or types of samples. We found potentially pathogenic bacteria in water samples such as Pasteurella spp., Haemophilus spp. and Halomonas spp. but these were not found in the tissue or mucus samples from any species. We found some bacterial groups such as Flavobacterium, Pseudoalteromonas, Lactobacillus and Bacillus that could play a role protecting the animals from pathogenic infection. This is, to our knowledge, the first study focusing on elasmobranch microbiomes. Future studies are needed to describe the functional role of these bacteria and their potential as beneficial symbionts in ray and shark mucus and tissue, as well as to understand changes to microbiome communities as a result of changing environmental conditions including increasing temperatures and ocean acidification.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Skin mucus in fish is considered the first barrier between the organism and the environment, partly because it can prevent microorganisms from colonizing the skin.</ns0:p><ns0:p>During copulation in sharks, the male bites the female generating wounds, which are then highly likely to become infected by opportunistic bacteria in the water or the male shark's mouth. The role of skin mucus in protecting fish against pathogens is not well understood.</ns0:p><ns0:p>Describing the microbial component of epithelial mucus may allow future understanding of this first line of defense in sharks. In this study, we analyzed mucus and tissue samples obtained from 19 individuals of two shark species and a stingray: the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus). We also collected water samples from the area where the animals were found. Total DNA was extracted from all samples, and the bacterial 16S rRNA gene (region V3-V4) was amplified and sequenced on the Ion Torrent Platform (amplicon sequencing). We analyzed sequences and present a summary of the bacterial diversity in the epithelial mucus of these elasmobranch species. Bacterial diversity (order and family) was high, particularly in tissue and mucus samples in all three species, and order and family composition were more similar between the two shark species for both tissue and mucus. Alpha-diversities in orders and families (expShannon and Simpson) were comparatively high and non-significantly different between elasmobranch species or types of samples. We found potentially pathogenic bacteria in water samples such as Pasteurella spp., Haemophilus spp. and Halomonas spp. but these were not found in the tissue or mucus samples from any species. We found some bacterial groups such as Flavobacterium, Pseudoalteromonas, Lactobacillus and Bacillus that could play a role protecting the animals from pathogenic infection. This is, to our knowledge, the first study focusing on elasmobranch microbiomes. Future studies are needed to describe the functional role of these bacteria and their potential as beneficial symbionts in ray and shark mucus and tissue, as well as to understand changes to microbiome communities as Introduction The immune system of fish includes, as a first barrier, the mucosal immune system. This system protects fish physically, chemically, and biologically from threats or pathogens found in their habitat <ns0:ref type='bibr' target='#b62'>(Subramanian, MacKinnon &amp; Ross, 2007;</ns0:ref><ns0:ref type='bibr'>Subramanian, Ross &amp; Mackinnon, 2008;</ns0:ref><ns0:ref type='bibr' target='#b54'>Raj et al., 2011)</ns0:ref>. The mucosal immune system is subdivided into three subgroups that correspond to the locations where the mucus is secreted: the gut, the gills and the skin <ns0:ref type='bibr' target='#b56'>(Salinas, Zhang &amp; Sunyer, 2011)</ns0:ref>. Skin mucus is considered a first barrier of protection because it can prevent microorganisms from colonizing the skin <ns0:ref type='bibr' target='#b21'>(Cone, 2009)</ns0:ref>. Some studies suggest that this mucus is constantly renewed, reducing the pathogenic load found on the surface of the fish <ns0:ref type='bibr' target='#b46'>(Nagashima et al., 2003)</ns0:ref>. The mucus is secreted in higher quantities as a response to threat <ns0:ref type='bibr' target='#b44'>(Mittal &amp; Datta Munshi, 1974;</ns0:ref><ns0:ref type='bibr' target='#b27'>Gostin, Neagu &amp; Vulpe, 2011;</ns0:ref><ns0:ref type='bibr' target='#b53'>Rai et al., 2012)</ns0:ref>, and the viscose substance consists of molecules that may help in healing and protecting the skin <ns0:ref type='bibr' target='#b15'>(Cameron &amp; Endean, 1973;</ns0:ref><ns0:ref type='bibr' target='#b3'>Al-Hassan et al., 1985)</ns0:ref>, including the secretion of antimicrobial and regenerative substances <ns0:ref type='bibr' target='#b31'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. The epithelial mucus is sometimes considered an ideal surface for bacterial adhesion. In fact, the accumulation of microorganisms appears to take place during the lifetime of the individual <ns0:ref type='bibr' target='#b31'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, leading to the establishment of the microbiota in fish skin. However, it is also recognized that the mucus has a concentration of molecules that prevent the adhesion of pathogenic bacteria (Crouse-Eisnor, <ns0:ref type='bibr' target='#b23'>Cone &amp; Odense, 1985)</ns0:ref>. As such, the role or the relationship between the mucus and environmental bacteria is not clear <ns0:ref type='bibr' target='#b40'>(Luer, 2012)</ns0:ref>. It has been suggested that bacteria found in this layer may play three possible roles <ns0:ref type='bibr' target='#b57'>(Salminen et al., 2010)</ns0:ref>: a) bacteria may stimulate mucus and antimicrobial compound production, b) bacteria may activate and help modulate the immune response in the fish, and c) the interaction between different types of bacteria may actively exclude or compete with potentially pathogenic bacteria. The mucus layer in sharks and rays has been poorly studied. However, it is known that mucus from stingray skin appear to accelerate the healing processes of wounds, and that bacteria found in the mucus present antibacterial activity against human pathogens <ns0:ref type='bibr' target='#b41'>(Luer et al., 2014)</ns0:ref>. Reproductive behavior in this group is characterized by aggressiveness during courtship and copulation <ns0:ref type='bibr' target='#b50'>(Pratt &amp; Carrier, 2001;</ns0:ref><ns0:ref type='bibr' target='#b18'>Carrier, Pratt &amp; Martin, 2015)</ns0:ref>. In sharks, the male bites the female on her dorsal or pectoral fins generating wounds in those areas <ns0:ref type='bibr' target='#b50'>(Pratt &amp; Carrier, 2001)</ns0:ref>. Polyandry, a mating system in which one female mates with multiple males, is very common in some species <ns0:ref type='bibr' target='#b58'>(Saville et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b16'>Carrier et al., 2003)</ns0:ref>. This behavior drives competition between males and avoidance in females <ns0:ref type='bibr' target='#b34'>(Klimley, 1980;</ns0:ref><ns0:ref type='bibr' target='#b26'>Gordon, 1993;</ns0:ref><ns0:ref type='bibr' target='#b50'>Pratt &amp; Carrier, 2001)</ns0:ref>. There are also morphological characteristics related to this trait. Sexual dimorphism occurs in shark species in which the males' teeth are shaped so they can easily grab the female in order to remain close to her while mating. Females have thicker dermal denticles (tooth-like structures that provide hydrodynamics and protection) than males as protection against these bites <ns0:ref type='bibr' target='#b17'>(Carrier, Musick &amp; Heithaus, 2012)</ns0:ref>. In the case of rays, the females prick the male with their caudal spine <ns0:ref type='bibr' target='#b50'>(Pratt &amp; Carrier, 2001)</ns0:ref>. It has been shown in some stingray species that when many males are involved in the mating process, a few may die in the process <ns0:ref type='bibr' target='#b25'>(Gilad et al., 2008)</ns0:ref>. In spite of these apparently aggressive behaviors, copulation is necessary and the wounds provoked in the process are highly likely to become infected <ns0:ref type='bibr' target='#b24'>(Daly-Engel et al., 2010)</ns0:ref> due to opportunistic bacteria in the water and in the oral cavity of males. Due to the high concentration of pathogenic microorganisms found in the aquatic environment <ns0:ref type='bibr' target='#b42'>(Magnadottir, 2010)</ns0:ref>, it is important to determine the microbiota component of the epithelial mucus, the skin tissue, and to understand whether the bacteria found in these are similar or different from those found in the water surrounding the animals. Doing so will begin to allow us to understand the role of mucus in the protection against pathogens. In this study, we present a summary of the bacterial diversity in the epithelial mucus from three elasmobranch species, the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus) <ns0:ref type='bibr' target='#b39'>(Last et al., 2016)</ns0:ref>. We also hypothesize about the possible role of some of the bacteria found in the mucus and in the skin.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sample collection</ns0:head><ns0:p>Mucus and skin tissue samples were obtained from 19 healthy individuals; 14 of them were obtained from animals captured in Bimini, Bahamas (25&#61616;43&#61602;59 N, 79&#61616;14&#61602;60 W): four corresponded to juvenile nurse sharks (Ginglymostoma cirratum), six to juvenile lemon sharks (Negaprion brevirostris), and four to adult southern stingrays (Hypanus americanus). Samples from an additional five adult nurse sharks were collected at Oceanario from Islas del Rosario (CEINER), in the Colombian Caribbean (10&#61616;10&#61602;30 N, 75&#61616;45&#61602;00 W). For each individual, we obtained a sample of skin tissue and mucus, following sampling protocols approved by the Animal Care Committee of Universidad de los Andes (CICUAL) (Bogota, Colombia). The skin tissue sample was taken from the posterior part of the dorsal fin (1 cm 3 or less) and the mucus from the skin surface, using a 1.5 ml microcentrifuge tube to scrape the skin surface, ideally filling at least half of the tube. A water sample was also collected in a 15 ml tube from the place where each individual was captured. Thus, three samples were associated with each individual, for a total of 57 samples. The individuals were captured and raised slightly to the surface of the water, so that the samples could be taken outside the water, while the animal could continue to breathe. Skin samples were preserved in ethanol 90%. All samples were maintained at 4&#186; C for less than one week, until processing. DNA Extraction and PCR amplification DNA was extracted from all samples collected. The Tissue and Cells DNA Isolation Kit (MoBio Laboratories, Inc.) was used for all samples, following the manufacturer instructions. In all cases, the entire sample was used. Water samples were filtered and concentrated before extraction. The primers 515f and 806r were used in order to amplify the region V3-V4 from the bacterial and archaea 16S rRNA gene. PCR amplification conditions were as follows: an initial denaturation at 94 &#176;C for 3 minutes, followed by 35 cycles of denaturing at 94&#176;C for 45 seconds, annealing for 45 seconds at 50&#176;C and extension for 45 seconds at 72&#176;C, followed by a final extension of 20 minutes at 72&#176;C. Successful amplification was confirmed on 1% agarose gel. Ion torrent library preparation, quantification and sequencing From the 57 samples, 32 were used to construct libraries (Supplementary Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). Samples were chosen depending on their final DNA concentration, once the PCR products were cleaned using magnetic beads and run on 1.5% agarose gel. Only the samples that had a clear strong band were used for library construction. Two libraries, each with 16 barcodes, were prepared using the protocol Ion Xpress&#8482; Plus gDNA Fragment Library Preparation (Life Technologies). Libraries were quantified with the Qubit kit. Templates were prepared following the Ion PGM&#8482; Template OT2 200 Kit (Life Technologies) protocols. Libraries were prepared for sequencing using the protocol Ion PGM&#8482; Sequencing 200 Kit v2 (Life Technologies). Libraries were loaded on two Ion 316 chips and sequenced in the Ion Torrent PGM (Life Technologies). Bioinformatic and statistical analyses Sequences were separated by barcodes directly by the Ion Torrent PGM and saved by the ion reporter in different files; sequence quality was analyzed using FastQC <ns0:ref type='bibr' target='#b5'>(Andrews, 2014)</ns0:ref>. The file format was changed from FASTQ to Fasta. All analyses were performed on the Galaxy online platform <ns0:ref type='bibr' target='#b1'>(Afgan et al. 2016)</ns0:ref> following one amplicon data workflow on Mothur v.1.28.0 <ns0:ref type='bibr' target='#b59'>(Schloss et al., 2009)</ns0:ref>. Demultiplexing was conducted by comparing the mapping file of the chip with the files containing the sequences. This workflow started by merging all read files into group files. Group files were identified as samples from each of the three elasmobranch species and also as type of sample (tissue mucus or water). The next step of the workflow identified unique sequences and generated a file with these sequences and a second file in which the number of each unique representative sequence was kept. Following this, reads were filtered based on quality and length. Parameters to remove low quality sequences was for those with less than 20 Phred score and shorter than 50 bp. Reads were then aligned to the Silva V4 reference database (Balvoclute &amp; Huson, 2017), followed by a step to remove poorly aligned sequences. Finally, reads were clustered based on their degree of similarity and classified into OTUs. Statistical analyses were conducted using the taxonomic categories 'order' and 'family' and a cutout of presence of at least 0.2 % was applied for order and of 0.17% was applied for family. Any data below this cutout point was reviewed by eye but was not included in the statistical analyses. R (R Development Core Team, 2010) was used <ns0:ref type='bibr' target='#b70'>(Wickham, 2009)</ns0:ref>, to estimate &#61537; diversity and richness (Simpson, Exponential Shannon and Chao 1, rarefaction curves) (package VEGAN and rareNMtests) <ns0:ref type='bibr' target='#b48'>(Oksanen et al., 2011)</ns0:ref>, and to estimate &#61538; diversity (Bray-Curtis dissimilarity index and a Principal Component Analysis (PCoA)). A Shapiro-Wilk normality test was conducted to evaluate normality among samples belonging to each elasmobranch species or to each category of sample type before performing any statistical tests. Venn diagrams (package DVenn) were used to visualize shared OTUs among elasmobranch species and among sample types. Since some results fell outside the normality assumption, a Kruskal-Wallis test was used to evaluate whether &#61537; diversity was significantly different among elasmobranch species or among sample type. These tests were visualized as boxplots.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The 32 samples used to build the libraries included a mucus or tissue sample for each of the individuals sampled and only four of the 19 samples from water (Supplementary Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). The other samples had low concentrations of bacterial DNA that could not be used for NGS sequencing analysis. A total of 219,162 reads were obtained from the Ion Torrent PGM. After read quality control, 22,803 reads were used in the following steps and in the Mothur workflow. Of these, 3,639 (16% total reads) were assigned taxonomically to OTU against the SilvaV4 database while 19,164 were left unassigned (84% total reads); sequences assigned taxonomically belonged to 18 mucus, 10 tissue and 4 water samples. Most reads were identified as belonging to the kingdom Bacteria (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). Only very small amounts of reads belonging to the kingdom Archaea were found (&lt; 2%) in only one mucus sample from one nurse shark. Among the Archaea, the orders identified were Micrarchaeles, Cenarchaeales, Halobacteriales, and Methanobacteriales. Thirty-seven orders and 25 families were shared between samples from the three elasmobranch species and the water samples, and 17 orders and 25 families were solely found in elasmobranch samples. Twenty-seven orders and 26 families were found only in the water samples (Figure <ns0:ref type='figure'>1</ns0:ref>). Fifty-four orders and 44 families were shared among all elasmobranch species, 28 orders and 29 families were shared between the nurse shark and the lemon shark, and less than 20 orders and families were shared between the two shark species and the southern stingray (Figure <ns0:ref type='figure' target='#fig_1'>2a and 2b</ns0:ref>). Forty-five orders and 27 families were shared between all sample types (water, mucus and tissue), 47 orders and 49 families were shared between sample types mucus and tissue, and less than 20 orders and families were shared between tissue or mucus and water samples (Figure <ns0:ref type='figure' target='#fig_1'>2c and 2c</ns0:ref>). Also, among elasmobranch species and types of samples, similar orders and families were found in every sample and with a similar distribution (Figure <ns0:ref type='figure'>3a 3b, 3c and 3d</ns0:ref>). The highest abundance was of the order Actinomycetales and the family Nocardiaceae (genus Rhodococcus), with a slightly greater abundance of reads obtained from the lemon shark and less abundance for reads obtained from the southern stingray. Mucus and tissue samples had a higher number of reads than water samples. The percentage for each order and family identified from the total reads (sequences) obtained and analyzed is shown in Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>. Only a few sequences were assigned to the species or genus levels. Most of them were assigned to higher taxonomic levels. However, among the genus and species identified, several reported bacterial fish pathogens, symbionts and commensals were found in the mucus, tissue, and water samples (Table <ns0:ref type='table' target='#tab_0'>1 and Supplementary Table 2</ns0:ref>). It is interesting to note that some fish pathogens were only found in the water and not in the mucus/tissue samples, such as Pasteurella spp., Haemophilus spp. and Halomonas spp. Alpha-diversity was similar among species and among types of samples (Table <ns0:ref type='table'>2a and 2b</ns0:ref>). This is surprising considering that diversity in water samples would be expected to be lower than diversity found in the tissue and mucus. However, there was high variation within each sample type, with samples having 10 times the number of different orders or families found in other samples from the same type. Something similar was found for the samples from each species, meaning that there was high heterogeneity in samples used in this study. Alpha-diversity was non significantly different among species or among type of samples (Figure <ns0:ref type='figure' target='#fig_2'>4</ns0:ref>). In the rarefaction curves, order and family richness followed a similar pattern for both elasmobranch species and type of sample, obtaining greater richness in the lemon shark, followed by the nurse shark and the southern stingray (Figure <ns0:ref type='figure' target='#fig_3'>5a and 5b</ns0:ref>), and showing greater richness in mucus samples, followed by tissue and water samples (Figure <ns0:ref type='figure' target='#fig_3'>5c and 5d</ns0:ref>). The Bray-Curtis dissimilarity index, used as a Beta-diversity estimate, revealed greater dissimilarity (0.45) between the microbiome communities (for order and family) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark (Figure <ns0:ref type='figure'>6</ns0:ref>). When each sample was used to calculate the Bray-Curtis dissimilarity index, patterns of bacterial community dissimilarity, at both order and family level, were less clear, but it appears that mucus and tissue samples from sharks and the southern stingray appeared to be less dissimilar from each other than when compared with the water samples (Figure <ns0:ref type='figure' target='#fig_4'>7a and 7b</ns0:ref>). The PCA showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due a to similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2) (Figure <ns0:ref type='figure'>8</ns0:ref>). Discussion Bacteria found on fish skin and in their mucus may be part of the first barrier of defense against pathogens. This is, to our knowledge, the first study investigating the microbiome of the skin and mucus of elasmobranch fish and, from a conservation perspective, knowledge of the microbiome composition and function may be an important approach to understanding how these organisms may be affected in the long term by environmental change; for example, climate change or ocean acidification <ns0:ref type='bibr' target='#b8'>(Bahrndorff et al., 2016)</ns0:ref>. Thus, this study may be useful as baseline information on microbiome communities in this fish, and future studies may find this information useful for evaluating changes in microbiome communities over time under changing conditions. Nevertheless, depending on the characteristics and populations of these animals, the composition and role of the whole microbiome may vary. In general, there are few taxonomically identified sequences compared to the total (only 16%). This may be the result of the shorter length of the sequences, the kits used in sequencing (to make libraries of short sequences), and the low concentration of DNA found in some of the original samples. However, our results are relevant to understanding the microbiome communities in elasmobranch fish and they suggest that skin tissue and mucus microbiomes of the three elasmobranch species were similar in composition. Also, although some orders and families were shared with the water samples, more OTUs were indeed shared between the two shark species and to a lesser extent with the southern stingray. Alpha-diversity was similar among samples from the three species and among types of samples. However, there was high variation in the Alphadiversity among samples within each species or within each sample type. This could have been caused by the storage conditions of some samples or due to the loss of DNA from some samples during the different steps of library preparation. Also, selective PCR amplification could generate higher amplification of some OTUs and not others. The richness of species was higher in mucus samples and in lemon shark samples. Composition of mucus samples and tissue samples from sharks tended to be more similar to each other than to the southern stingray or the water samples. In this study, the bacterial diversity in the mucus and tissue included a wide range of orders, families and genus that have been described as pathogens, non-pathogens, and some that have scarcely been studied in relation to potential or confirmed hosts. Most OTUs identified belonged to the kingdom Bacteria, with a very small proportion of Archaea. However, some of the Archaea identified in a mucus sample belonging to a nurse shark included Cenarchaeales which have been found to be symbionts of one marine sponge that lives at very low temperatures <ns0:ref type='bibr' target='#b51'>(Preston et al., 1996)</ns0:ref>. Interestingly, a high proportion of Actinomycetales of the family Nocardiacea (genus Rhodococcus) were found in mucus and tissue samples and influenced the community composition of all our samples, as showed in the PCA. Although Actinomycetales and particularly Rhodococcus can be found in environmental samples from soil and water, some strains have been isolated from marine environments which produce antimicrobial compounds against pathogenic bacterial and fungus, particularly against some pathogenic strains of E. coli and Pseudomonas sp. <ns0:ref type='bibr' target='#b71'>(Yellamanda et al., 2016)</ns0:ref>. The phylum Actinobacteria, to which the order Actinomycetales belongs, has also been found in the skin microbiota of bony fish (Osteichthyes) <ns0:ref type='bibr' target='#b38'>(Larsen et al., 2013)</ns0:ref>. Although we focused our analysis of microbiome community diversity and composition of the orders and families identified, we also investigated the characteristics of genera and species found in this study because, although a smaller number of reads were identified to the genus or species level, some interesting data was obtained. Within the bacterial genera found only in water samples, three have been described as pathogens for fish, including Pasteurella spp., Haemophilus spp. and Halomonas spp. <ns0:ref type='bibr' target='#b14'>(Bullock, 1961;</ns0:ref><ns0:ref type='bibr' target='#b32'>Hawke et al., 1987;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. There is also a species only found in water samples, Acinetobacter johnsonii, which has been described as a fish pathogen <ns0:ref type='bibr' target='#b35'>(Kozi&#324;ska et al., 2014)</ns0:ref>. Other sequenced bacteria present in the results of water samples, such as Moraxella sp., are opportunistic bacteria and have been found in other animals, for example in mammals <ns0:ref type='bibr' target='#b69'>(Whitman, 2015)</ns0:ref>. Some of the 143 genera found only in the elasmobranch samples may also play a role as pathogens; Alteromonas <ns0:ref type='bibr' target='#b11'>(Boone &amp; Bryant, 1980)</ns0:ref>, Mycobacterium, Nocardia, Shewanella, Staphylococcus and Chryseobacterium have been reported as pathogens for various fish species <ns0:ref type='bibr' target='#b31'>(Hansen &amp; Olafsen, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. Syntrophobacter is another genera present in mucus and skin samples and considered a possible pathogen for fish, due to the fact that bacteria that belong to this group, degrade propionate, a corticoid used in healing skin <ns0:ref type='bibr' target='#b61'>(Schulze et al., 2006)</ns0:ref>. However, many species of Flavobacterium, Pseudoalteromonas, Lactobacillus and Bacillus, also found only in elasmobranch samples, are considered symbionts of marine fish <ns0:ref type='bibr' target='#b4'>(Anand et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b41'>Luer et al., 2014)</ns0:ref>. Some species of Flavobacterium have been studied as commensal to fish, and have shown antimicrobial activity against fish pathogens from the genus Vibrio <ns0:ref type='bibr' target='#b37'>(Lal &amp; Tabacchioni, 2009)</ns0:ref>. Bacillus polymyxa, found in mucus and skin samples in this study, has been isolated from fish guts and some strains of this species synthesize antibiotics <ns0:ref type='bibr' target='#b49'>(Olmos, 2014)</ns0:ref>. Similarly, Bacillus subtilis has been suggested as a probiotic involved in the optimization of fish feeding <ns0:ref type='bibr' target='#b43'>(Merrifield &amp; Rodiles, 2015)</ns0:ref>. Finally, various bacteria sequenced from mucus and skin samples are considered normal biota of fish gills or skin (i.e., Xanthomonadales, Caulobacteriales <ns0:ref type='bibr' target='#b65'>(Sugita et al., 1996)</ns0:ref>). Three genera found in mucus and tissue samples (Streptococcus, Pseudomonas and Vibrio) are sometimes reported as pathogens and sometimes reported as symbionts. For example, S. parauberis produces streptococcosis in some fish <ns0:ref type='bibr' target='#b6'>(Austin, 2005;</ns0:ref><ns0:ref type='bibr' target='#b47'>Nho et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but other Streptococcus spp. inhibit the growth of pathogenic bacteria <ns0:ref type='bibr' target='#b31'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Similarly, Pseudomonas putrefaciens acts as a pathogen for fish <ns0:ref type='bibr' target='#b0'>(Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but P. fluorescens inhibits growth of pathogens <ns0:ref type='bibr'>(Subramanian, Ross &amp; MacKinnon, 2008)</ns0:ref> and has been isolated from healthy salmon eggs and mucus <ns0:ref type='bibr' target='#b20'>(Cipriano &amp; Dove, 2011;</ns0:ref><ns0:ref type='bibr' target='#b2'>Akinyemi et al., 2016)</ns0:ref>. Finally, Vibrio have been reported several times as an important pathogen for marine life because of its great capacity for survival and of acclimation in its host, as it hydrolyzes urea and uses it as a source of carbon and nitrogen <ns0:ref type='bibr' target='#b31'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Many species have been described as infectious for Negaprion brevirostris, especially when they are physically injured <ns0:ref type='bibr' target='#b28'>(Grimes et al., 1984a;</ns0:ref><ns0:ref type='bibr' target='#b29'>Grimes, Gruber &amp; May, 1985)</ns0:ref>; others are associated to the mortality of sharks in captivity <ns0:ref type='bibr' target='#b30'>(Grimes et al., 1984b)</ns0:ref>, and others to infections caused by hooks <ns0:ref type='bibr' target='#b12'>(Borucinska et al., 2002)</ns0:ref>. There are some species that, depending on the strain, are pathogenic or not, such as V. alginolyticus and V. parahemoliticus <ns0:ref type='bibr' target='#b7'>(Austin &amp; Austin, 2007;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>. Other species, such as Vibrio alginolyticus and V. fluviales, are considered pathogenic for fish <ns0:ref type='bibr' target='#b73'>(Zorrilla et al., 2003)</ns0:ref>; Vibrio fortis has been reported as a sea horse pathogen <ns0:ref type='bibr' target='#b67'>(Wang et al., 2016)</ns0:ref>; Vibrio shilonii has been found to cause coral bleaching <ns0:ref type='bibr' target='#b36'>(Kushmaro et al., 2001)</ns0:ref>. There are various bacteria identified in the mucus samples that are considered in other studies as symbionts or pathogens for other animals or humans. For example, some species of Bacteroides have been described as human pathogens in periodontal disease and Prevotella copri, found in mucus and skin samples have been identified as pathogens in intestinal inflammation. Additionally, species from Helcoccocus have also been described as pathogens for humans <ns0:ref type='bibr' target='#b19'>(Chow &amp; Clarridge, 2014)</ns0:ref>. Many species of Chlamydiae are reported as pathogens for birds and mammals <ns0:ref type='bibr' target='#b69'>(Whitman, 2015)</ns0:ref> and Enterococcus cecorum has been reported as a pathogen in chicken <ns0:ref type='bibr' target='#b33'>(Jung &amp; Rautenschlein, 2014)</ns0:ref>. As examples of symbiosis of species of bacteria (found in samples for this study) with humans or other animals, it is worth mentioning Lactobacillus zeae, which has been found to serve as protective biota for nematodes <ns0:ref type='bibr' target='#b72'>(Zhou et al., 2014)</ns0:ref>; Butyrivibrio and Selenomonas are found in the gastrointestinal tract of ruminants; Faecalibacterium prausnitzii, Peptoniphilus, Ruminococcus, Megamonas <ns0:ref type='bibr' target='#b19'>(Chow &amp; Clarridge, 2014)</ns0:ref> and Butyricimonas <ns0:ref type='bibr' target='#b68'>(Wexler, 2007)</ns0:ref> are normal important bacteria in the human gut microbiota. Other species sequenced from mucus samples were Sulcia muelleri <ns0:ref type='bibr' target='#b45'>(Moran, Tran &amp; Gerardo, 2005)</ns0:ref>, Baumannia cicadellinicola <ns0:ref type='bibr' target='#b22'>(Cottret et al., 2010)</ns0:ref> and Carsonella ruddii <ns0:ref type='bibr' target='#b66'>(Thao et al., 2000)</ns0:ref>, which have been described in symbiotic association with insects. A very interesting case is Janthinobacterium lividum, which has been found in the skin of some amphibians and appears to prevent infection by Batrachochytrium dendrobatidis <ns0:ref type='bibr' target='#b13'>(Brucker et al., 2008)</ns0:ref>. These are startling examples that may be related to the findings of this study; however, more in-depth research should be conducted to identify the pathogenicity or symbiosis properties specifically in elasmobranch or fish. According to this information, the role of the mucus and the bacteria associated to it may depend on numerous variables, including the virulence and pathogenicity of each microorganism <ns0:ref type='bibr' target='#b31'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Opportunistic bacteria can acquire virulence determinants with environmental changes by different means, for example, by a) increasing their numbers by exploiting the higher production of mucus (glycoproteins) induced by presence of toxic substances in the water <ns0:ref type='bibr' target='#b31'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, by b) shifting from a non-infectious state to an infectious one through an activation caused by a physical or chemical change in the environment <ns0:ref type='bibr' target='#b31'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, or by c) Reaching the dermal layer to infect the host taking advantage of a degree of reduction of the defensive mucus layer, caused by the presence of abrasive substances in the surroundings of the fish <ns0:ref type='bibr' target='#b10'>(Benhamed et al., 2014)</ns0:ref>. These three opportunities for the bacteria to infect the hosts not only benefit these microorganisms but they also affect the host by reducing their physiological condition <ns0:ref type='bibr' target='#b6'>(Austin, 2005)</ns0:ref>, and may explain the finding of the reported bacterial pathogens on the skin of healthy animals. The orders, families, and genera considered fish pathogens found in the water samples but absent in the elasmobranch samples, allows this research to present an interesting assumption. We suggest that there may be specific antimicrobial activity in the skin environment, or partial control against infections that exists in low concentration in the mucus, but this might be also a result of the low number of samples and replicates analyzed <ns0:ref type='bibr' target='#b55'>(Rakers et al., 2010)</ns0:ref>. However, it is very likely that difficulties in sampling -for example, handling the sharks and stingrays-, that prevent us from collecting a larger skin or mucus sample and that this in itself could be biasing our results. The simultaneous presence of pathogens and possible symbionts varied between samples; however, the role of each genus or species should be verified for each of the host species considered in this analysis. According to these results, we suggest that the role of the epithelial microbiota may be considered as a first line of defense against infectious organisms but it could also be a potential threat for the injured host. This could depend on the whole combination of bacteria and their interaction between them in each host. As mentioned earlier, each fish may accumulate a specific community of microorganisms in its life span depending on the environments it inhabits during its development and growth <ns0:ref type='bibr' target='#b31'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. This study represents the first contribution to describing shark and ray skin and mucus microbiomes. The next steps to further understand the role of bacterial communities in skin and mucus of elasmobranchs require functional metagenomics and metabolomics analyses to unveil the role of these bacteria. Conclusions This study presents a first intent at studying and describing tissue and mucus microbiota from two shark species and a stingray. Orders and families were highly diverse and similar between species and types of samples and more orders and families were found in tissue and mucus when compared to water samples. The order Actinomycetales was found in a very high percentage (&gt;50%) of tissue and mucus samples and could represent bacteria that may have antimicrobial activity. This is baseline information that could help in future monitoring of microbiota change in elasmobranch species that may be caused by climate change and ocean acidification. <ns0:ref type='figure'>6</ns0:ref>. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order and family) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Manuscript to be reviewed Figure <ns0:ref type='figure'>8</ns0:ref>. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due a to similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Manuscript to be reviewed Manuscript to be reviewed</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of OTU's shared among elasmobranch samples (mucus and tissue), and water samples. Also, OTU&#180;s unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) and families (b) shared between and among elasmobranch species and those unique to each species. Orders (c) and families (d) shared between and among sample types and those unique to each sample type. Figure 3. Bacterial order (a) and family (b) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (c) and family (d) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity (Exponential Shannon and Simpson) was non significantly different among species for orders (a and b) or families (c and d) or among sample type for orders (e and f) and families (g and h).Figure 5. Rarefaction curves showing order (a) and family (b) richness found among elasmobranch species and showing order (c) and family (d) found among sample types Figure6. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order and family) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure7. Bray-Curtis dissimilarity index calculated at both order (a) and family (b) level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of OTU's shared among elasmobranch samples (mucus and tissue), and water samples. Also, OTU&#180;s unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) and families (b) shared between and among elasmobranch species and those unique to each species. Orders (c) and families (d) shared between and among sample types and those unique to each sample type. Figure 3. Bacterial order (a) and family (b) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (c) and family (d) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity (Exponential Shannon and Simpson) was non significantly different among species for orders (a and b) or families (c and d) or among sample type for orders (e and f) and families (g and h).Figure 5. Rarefaction curves showing order (a) and family (b) richness found among elasmobranch species and showing order (c) and family (d) found among sample types Figure6. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order and family) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure7. Bray-Curtis dissimilarity index calculated at both order (a) and family (b) level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of OTU's shared among elasmobranch samples (mucus and tissue), and water samples. Also, OTU&#180;s unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) and families (b) shared between and among elasmobranch species and those unique to each species. Orders (c) and families (d) shared between and among sample types and those unique to each sample type. Figure 3. Bacterial order (a) and family (b) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (c) and family (d) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity (Exponential Shannon and Simpson) was non significantly different among species for orders (a and b) or families (c and d) or among sample type for orders (e and f) and families (g and h).Figure 5. Rarefaction curves showing order (a) and family (b) richness found among elasmobranch species and showing order (c) and family (d) found among sample types Figure6. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order and family) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure7. Bray-Curtis dissimilarity index calculated at both order (a) and family (b) level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of OTU's shared among elasmobranch samples (mucus and tissue), and water samples. Also, OTU&#180;s unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) and families (b) shared between and among elasmobranch species and those unique to each species. Orders (c) and families (d) shared between and among sample types and those unique to each sample type. Figure 3. Bacterial order (a) and family (b) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (c) and family (d) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity (Exponential Shannon and Simpson) was non significantly different among species for orders (a and b) or families (c and d) or among sample type for orders (e and f) and families (g and h).Figure 5. Rarefaction curves showing order (a) and family (b) richness found among elasmobranch species and showing order (c) and family (d) found among sample types Figure6. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order and family) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure7. Bray-Curtis dissimilarity index calculated at both order (a) and family (b) level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 7 .</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of OTU's shared among elasmobranch samples (mucus and tissue), and water samples. Also, OTU&#180;s unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) and families (b) shared between and among elasmobranch species and those unique to each species. Orders (c) and families (d) shared between and among sample types and those unique to each sample type. Figure 3. Bacterial order (a) and family (b) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (c) and family (d) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity (Exponential Shannon and Simpson) was non significantly different among species for orders (a and b) or families (c and d) or among sample type for orders (e and f) and families (g and h).Figure 5. Rarefaction curves showing order (a) and family (b) richness found among elasmobranch species and showing order (c) and family (d) found among sample types Figure6. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order and family) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure7. Bray-Curtis dissimilarity index calculated at both order (a) and family (b) level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='21,-37.26,204.13,627.93,353.21' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Percentage of a) Orders and b) families found in the total number of reads analyzed in this study.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>Manuscript to be reviewed</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>% Order found</ns0:cell></ns0:row><ns0:row><ns0:cell>Order</ns0:cell><ns0:cell>in the total number of</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>analyzed reads</ns0:cell></ns0:row><ns0:row><ns0:cell>Brachyspirales</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>Cerasicoccales</ns0:cell><ns0:cell>0,122</ns0:cell></ns0:row><ns0:row><ns0:cell>Chthoniobacterales</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>Leptospirales</ns0:cell><ns0:cell>0,081</ns0:cell></ns0:row><ns0:row><ns0:cell>Micrarchaeles</ns0:cell><ns0:cell>1,985</ns0:cell></ns0:row><ns0:row><ns0:cell>Pedosphaerales</ns0:cell><ns0:cell>0,122</ns0:cell></ns0:row><ns0:row><ns0:cell>Pelagicoccales</ns0:cell><ns0:cell>0,162</ns0:cell></ns0:row><ns0:row><ns0:cell>Rhodothermales</ns0:cell><ns0:cell>0,284</ns0:cell></ns0:row><ns0:row><ns0:cell>Roseiflexales</ns0:cell><ns0:cell>0,162</ns0:cell></ns0:row><ns0:row><ns0:cell>Saprospirales</ns0:cell><ns0:cell>0,122</ns0:cell></ns0:row><ns0:row><ns0:cell>0319_7L14</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>04A5</ns0:cell><ns0:cell>0,122</ns0:cell></ns0:row><ns0:row><ns0:cell>11_24</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>A89</ns0:cell><ns0:cell>0,122</ns0:cell></ns0:row><ns0:row><ns0:cell>Acetothermales</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>Acholeplasmatales</ns0:cell><ns0:cell>0,729</ns0:cell></ns0:row><ns0:row><ns0:cell>Acidimicrobiales</ns0:cell><ns0:cell>0,162</ns0:cell></ns0:row><ns0:row><ns0:cell>Acidithiobacillales</ns0:cell><ns0:cell>0,081</ns0:cell></ns0:row><ns0:row><ns0:cell>Acidobacteriales</ns0:cell><ns0:cell>0,122</ns0:cell></ns0:row><ns0:row><ns0:cell>Actinomycetales</ns0:cell><ns0:cell>50,932</ns0:cell></ns0:row><ns0:row><ns0:cell>AF420338</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>AKAU3564</ns0:cell><ns0:cell>0,081</ns0:cell></ns0:row><ns0:row><ns0:cell>AKIW78</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>AKYG722</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>Alteromonadales</ns0:cell><ns0:cell>0,527</ns0:cell></ns0:row><ns0:row><ns0:cell>Anaeroplasmatales</ns0:cell><ns0:cell>0,567</ns0:cell></ns0:row><ns0:row><ns0:cell>ArcA07</ns0:cell><ns0:cell>0,608</ns0:cell></ns0:row><ns0:row><ns0:cell>Archaeoglobales</ns0:cell><ns0:cell>0,122</ns0:cell></ns0:row><ns0:row><ns0:cell>Arctic96B_7</ns0:cell><ns0:cell>0,081</ns0:cell></ns0:row><ns0:row><ns0:cell>Arctic96B-7</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>BA02</ns0:cell><ns0:cell>0,041</ns0:cell></ns0:row><ns0:row><ns0:cell>Bacillales</ns0:cell><ns0:cell>0,608</ns0:cell></ns0:row><ns0:row><ns0:cell>Bacteroidales</ns0:cell><ns0:cell>2,35</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2018:07:29887:1:1:NEW 4 Jul 2019) PeerJ reviewing PDF | (2018:07:29887:1:1:NEW 4 Jul 2019) Manuscript to be reviewed PeerJ reviewing PDF | (2018:07:29887:1:1:NEW 4 Jul 2019)</ns0:note></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2018:07:29887:1:1:NEW 4 Jul 2019)</ns0:note> <ns0:note place='foot' n='3'>PeerJ reviewing PDF | (2018:07:29887:1:1:NEW 4 Jul 2019)</ns0:note> </ns0:body> "

"Response to reviewers Reviewer: Ciara Keating (Tracked in the manuscript with green) Q/ Basic reporting The focus of the manuscript is very interesting, the role and composition of microorganisms in the skin mucosa of fish is rarely studied. However, the analyses used and the results and discussion need to be improved. The main aims and objectives could be made clearer and the advancement made through this research could be highlighted further. I liked Figure 1 - would be nice as a graphical abstract. The figures/tables shown could be improved.  In general there are very few grammatical errors. But watch out for double spaces after full stops. Check that the line spacing is the same between each sentence.  R/We thank the reviewer for her thorough work on reviewing our manuscript. we re-did all the analyses from the start and we focused on showing that this is, to our knowledge, the first study of its kind on skin and mucus microbiota of elasmobranchs. We also improved all figures an tables. Abstract Line 2: Remove the word “as”. R/This was deleted Line 11: 16S rRNA gene.  R/ Corrected Line 11-12: Next generation sequencing does not target the whole 16S rRNA gene. It is amplicon sequencing? What region of 16S was targeted using your specific bacterial primers? Was it a universal primer set? What sequencing technology? Pyrosequencing? Illumina Miseq?  R/ We included this information and now reads “Total DNA was extracted from all samples, and the bacterial 16s rRNA gene (region V3-V4) was amplified and sequenced on the Ion Torrent Platform (amplicon sequencing).” (Lines 12-14) The background sentences could be shortened. The abstract needs to be more conclusive and highlight the merit of the study.  R/This was improved. We had a complete editorial check. The final part of the abstract now reads: “Future studies are needed to describe the functional role of these bacteria and their potential as beneficial symbionts in ray and shark mucus and tissue, as well as to understand changes to microbiome communities as a result of changing environmental conditions including increasing temperatures and ocean acidification” (Lines 24-27) Introduction Line 44 – 47. The reference on line 44 can be removed as you can leave it at the end. R/ This was removed Line 50: Appears. R/Corrected Line 55: Definition of polyandry? R/This was included (Lines 61-62): Polyandry, a mating system in which one female mates with multiple males, is very common in some species Experimental design Methods Could be a bit clearer on how skin tissue samples were taken. Were the samples weighed? Was the same size/depth taken? These are all factors that will influence your DNA extraction and thus your sequencing results. How did you extract from the water samples? What method used?  R/This was completed (Lines 94-97): The skin tissue sample was taken from the posterior part of the dorsal fin (1 cm3 or less) and the mucus from the skin surface, using a 1.5 ml microcentrifuge tube to scrape the skin surface, ideally filling at least half of the tube. A water sample was also collected in a 15 ml tube from the place where each individual was captured. All samples were extracted using the same kit. However, we added information regarding extraction of water samples: Water samples were filtered and concentrated before extraction (Line 106). Line 96: These primers are a universal primer set which amplify bacteria and archaea. R/This was completed, it now reads: amplify the region V3-V4 from the bacterial and archaea 16s rRNA gene. (Lines 107-108). What error rate in the sequencing? How many sequences removed after quality control? R/This was included in a clearer way. Lines 134-140: Following this, reads were filtered based on quality and length. Parameters to remove low quality sequences was for those with less than 20 Phred score and shorter than 50 bp. Reads were then aligned to the Silva V4 reference database (Balvoclute & Huson, 2017), followed by a step to remove poorly aligned sequences. Finally, reads were clustered based on their degree of similarity and classified into OTUs. Statistical analyses were conducted using the taxonomic categories “order” and “family” and a cutout of presence of at least 0.2 % was applied for order and of 0.17% was applied for family. In the results section we included (lines 157-162): A total of 219,162 reads were obtained from the Ion Torrent PGM. After read quality control, 22,803 reads were used in the following steps and in the Mothur workflow. Of these, 3,639 (16% total reads) were assigned taxonomically to OUT against the SilvaV4 database while 19,164 were left unassigned (84% total reads); sequences assigned taxonomically belonged to 18 mucus, 10 tissue and 4 water samples. Line 101: Remove “The” and one “was”.  R/Corrected Line 104: Why were only 32 used? How did the DNA concentration determine what samples? Did some not amplify? Be more precise in your methods section. R/ From the 57 samples, 32 were used to construct libraries. Samples were chosen depending on their final DNA concentration, once the PCR products were cleaned using magnetic beads and run on 1.5% agarose gel. Only the samples that had a clear strong band were used for library construction (lines 114-116) Line 107: Quantified. R/Corrected Why pairwise dissimilarity performed? Why Horn? Would Bray-Curtis dissimilarity matrix not have been more appropriate? Also consider stats that include Unifrac and Weighted Unifrac to consider phylogenetic distances. Was the data rarified or transformed in any way? How many total sequences were found?  We re-did all the analyses and we included a whole new methods section (lines 140-151) and now reads: Any data below this cutout point was reviewed by eye but was not included in the statistical analyses. R (R Development Core Team, 2010) was used (Wickham, 2009), to estimate  diversity and richness (Simpson, Exponential Shannon and Chao 1, rarefaction curves) (package VEGAN and rareNMtests) (Oksanen et al., 2011), and to estimate  diversity (Bray-Curtis dissimilarity index and a Principal Component Analysis (PCoA)). A Shapiro-Wilk normality test was conducted to evaluate normality among samples belonging to each elasmobranch species or to each category of sample type before performing any statistical tests. Venn diagrams (package DVenn) were used to visualize shared OTUs among elasmobranch species and among sample types. Since some results fell outside the normality assumption, a Kruskal-Wallis test was used to evaluate whether  diversity was significantly different among elasmobranch species or among sample type. These tests were visualized as boxplots. N.B. You need to submit the raw sequences to Genbank and give the accession number. This will be done once the manuscript is accepted for publication Validity of the findings Results Line 139: Were they Archaea? Your primers target both. R/ We included information regarding Archaea found in this study (lines 164-167): Most reads were identified as belonging to the kingdom Bacteria (Table 1). Only very small amounts of reads belonging to the kingdom Archaea were found (< 2%) in only one mucus sample from one nurse shark. Among the Archaea, the orders identified were Micrarchaeles, Cenarchaeales, Halobacteriales, and Methanobacteriales. Your first paragraph reads more like a methods section. One sentence should suffice, total number of sequences how many Phyla/OTU identified etc.  R/ This was summarized (155-168): The 32 samples used to build the libraries included a mucus or tissue sample for each of the individuals sampled and only four of the 19 samples from water. The other samples had low concentrations of bacterial DNA that could not be used for NGS sequencing analysis. A total of 219,162 reads were obtained from the Ion Torrent PGM. After read quality control, 22,803 reads were used in the following steps and in the Mothur workflow. Of these, 3,639 (16% total reads) were assigned taxonomically to OTU against the SilvaV4 database while 19,164 were left unassigned (84% total reads); sequences assigned taxonomically belonged to 18 mucus, 10 tissue and 4 water samples. Most reads were identified as belonging to the kingdom Bacteria (Table 1). Only very small amounts of reads belonging to the kingdom Archaea were found (< 2%) in only one mucus sample from one nurse shark. Among the Archaea, the orders identified were Micrarchaeles, Cenarchaeales, Halobacteriales, and Methanobacteriales. Thirty-seven orders and 25 families were shared between samples from the three elasmobranch species and the water samples, and 17 orders and 25 families were solely found in elasmobranch samples. Twenty-seven orders and 26 families were found only in the water samples (Figure 1). The results and discussion section need a lot of improvement. You need to consider species richness/evenness/ - alpha-diversity/ beta-diversity. Perhaps look to other microbial ecology manuscripts to give ideas to strengthen the results and discussion sections. Figure 2 should be in terms of the relative abundance in % terms so you can compare across the samples. Focusing on phyla level does not really give a lot of information. Table 1 could be supplementary. Is , meaning a decimal place? 3,182 reads from 32 samples is very very low. Consider investigating the sequence analysis further. How many total reads per sample before and after QC? Error rate of platform? More in depth analysis needed. R/ This was completely changed after the re-analyses of all the data. See full results section, particularly Comments for the author In general I think this is an interesting manuscript but the methods section needs a lot more detail. I think your sequencing analyses should be repeated and more rigorous analyses performed. The presentation of the data could be improved. R/Thank you very much for your suggestions. We re-analysed all the data and re-did the figures and tables. Reviewer: Patrick Kearns (Changes tracked in blue) Basic reporting -While I did not factor this into my review, the paper needs a thorough editing. It is difficult to follow the author’s train of thought at times. R/ we did a thorough editorial check. -The methods, in particular the bioinformatics, are very unclear and need revision for clarity.  R/We re-analyzed all the data from the start. For new bioinformatic methods see lines 124 to 151. -Not a single statistic is used in this manuscript. It is hard to draw conclusions without some significance testing.  R/New statistical analyzes were performed. See lines 191 to 215. -Overall, the figures need polishing they look straight out of R.  R/All figures were re-done -Did the authors normalize their data for analyses? Given the very wide distribution of sequencing depth (fig 2), this should be done for beta diversity analyses.  R/This was done: See results section (lines 191-215) -My main concern with this study is the data and the massive loss of data the authors report. The authors report 219k raw reads (line 136) and following filtering they use ~3.6k. What happened to the rest of the data? Was this just a bad run? What did the authors do to filter the data? More information is needed to evaluate this data. R/This was now clearly explained at the start of the results (lines 157-162) Experimental design This is fine overall. A better description of the methods is needed however R/This was improved and are now clearer and easier to follow (lines 87-101) Validity of the findings The results are reasonable. But it is hard R/This was improved for clarity and easier following (lines 155-215) Comments for the author Line 80: please provide GPS coordinates for the sampled area. Also, a table would be nice summarizing the species and # samples.  R/We included coordinates for the sampling areas (Lines 87 to 92). We included a Supplementary Table 1 to show information of the samples used for library construction. Line 83: please provide GPS coordinates here too. R/This was done Line 87-88: how was the water collected and filtered.  R/included Line 91: how long were the samples kept at 4C? R/included (line 101) Line 95: I would suggest combine these two sentences into one Line 97: 515/806 only amplifies the V4 region of 16S. Also I suggest moving ‘region’ to after ‘v3-v4’ to make the sentence flow better. R/completed Line 97: capitalize the ‘s’ in 16S R/corrected Line 99: was this a single PCR reaction for each sample? R/clarified Line 101: this sentence needs to be rewritten. Also, outside of the water could the authors actually view skin metaG DNA on a gel? R/I don’t understand this question. We explained how we did this. Line 111: where was the sequencing performed? R/Clarified Line 114: what parameters were used to filter the data? R/This and the following questions changed since we re-did the complete analyses. Line 117: <20 sequences per sample doesn’t indicate poor quality, just poor sequencing depth. Do the authors mean a PHRED score <20? R/ See above Line 119: please elaborate on the methods used in QIIME R/See above Line 120: OTU does not mean taxonomy. Do the authors mean the clustered the reads in OTUs and the assigned taxonomy? What methods did they use? R/This whole analyses was changed. Line 131: did the authors deposit the sequences in a database (e.g. NCBI).  R/See above Line 120: what version of QIIME? R/See above Line 122: ggplot is only a plotting package, not for analyzing diversity. Did the authors calculate diversity? R/This whole section was changed due to changes in bioinformatic analyses. Line 124: I’m not sure what the authors are trying to say in this paragraph. They say MDS and then Horn similarity/PCoA. What analysis was used, make this clear. Also was the data normalized? R/This whole section was changed due to changes in bioinformatic analyses. Line 129-130: this likely isn’t needed.  R/corrected Line 140: should be ‘Bacterial’ not ‘Bacteria’.  R/corrected Line 156: species-level assignments are hard with this dataset given the small fragment length (~250bp). I would suggest the authors avoid this type of analysis.  R/We used order and family now. However we kept some information regarding species found. Line 161: did the authors try to add statistics to back this paragraph up? R/This whole section was changed due to changes in bioinformatic analyses. It would be nice to talk about fish species difference in results/methods.  R/This whole section was changed due to changes in bioinformatic analyses. Discussion: the authors should, if they are going to talk about genera, provide some data showing the genera and not rely on the text to inform the reader.  R/This whole section was changed due to changes in bioinformatic analyses. Line 287: the authors do not report diversity estimates anywhere in this paper.  R/This whole section was changed due to changes in bioinformatic analyses. Figures and tables Figure 1: In the caption, OTU’s should be OTUs. When the authors say OTUs at the phylum level, do them mean shared phyla? If so then they should revise the legend accordingly. R/corrected Figure 2: the color scheme on this is very taxing on the eyes, the colors are too similar to discern between the phyla present. I would suggest using a different palette and simplifying it to smaller number of taxa. R/corrected What does the y-axis mean? Number of reads? R/corrected The depth of sequencing is clearly different between samples so it makes comparing between samples impossible. I would suggest the authors that the output from the QIIME script “summarize_taxa.py” and use the relative abundances to make this plot. R/corrected Also, the phylum level is very coarse. It tells the reader very little about the system given the diversity of functions bacteria are capable of in a single phylum. I would suggest the authors do this at the order or family level to provide more information about the data. R/corrected What do the boxes around the bars mean? R/corrected Figure 3: is this a PCA or PCoA? The axes say PCoA, the legend says PCA and the methods say PCA. What method was used? R/corrected "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>However, the role of skin mucus in protecting fish against pathogens is not well understood. During copulation in sharks, the male bites the female generating wounds, which are then highly likely to become infected by opportunistic bacteria from the water or from the male shark's mouth. Describing the microbial component of epithelial mucus may allow future understanding of this first line of defense in sharks. In this study, we analyzed mucus and skin samples obtained from 19 individuals of two shark species and a stingray: the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus). Total DNA was extracted from all samples, and the bacterial 16S rRNA gene (region V3-V4) was amplified and sequenced on the Ion Torrent Platform (amplicon sequencing). Bacterial diversity (order) was higher in skin and mucus than in water. Order composition was more similar between the two shark species.</ns0:p><ns0:p>Alpha-diversities in orders (expShannon and Simpson) were high in all samples and there were non-significant differences between elasmobranch species or types of samples. We found orders of potentially pathogenic bacteria in water samples collected from the area where the animals were found, such as Pasteurellales (i.e. genus Pasteurella spp. and Haemophilus spp.) and Oceanospirillales (i.e. genus Halomonas spp.) but these were not found in the skin or mucus samples from any species. Some bacterial orders, such as Flavobacteriales, Vibrionales (i.e. genus Pseudoalteromonas), Lactobacillales and Bacillales, However in a co-occurrence analyses, no strong relationship was found among these orders but strong relationships were found among the order Trembayales, previously described as endosymbionts of insects, Fusobacteriales, previously described in the human gut, and some previously described marine environmental Bacteria and Archaea, including Elusimicrobiales, Thermoproteales, Deinococcales and Desulfarculales. This is, to our knowledge, the first study focusing on elasmobranch microbiomes. Future studies are</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The first barrier of protection against microorganisms in fish is the mucosal immune system <ns0:ref type='bibr' target='#b21'>(Cone, 2009)</ns0:ref>. This system protects fish physically, chemically, and biologically from threats or pathogens found in their habitat <ns0:ref type='bibr' target='#b66'>(Subramanian, MacKinnon &amp; Ross, 2007;</ns0:ref><ns0:ref type='bibr'>Subramanian, Ross &amp; Mackinnon, 2008;</ns0:ref><ns0:ref type='bibr' target='#b57'>Raj et al., 2011)</ns0:ref>. The mucosal immune system is subdivided into three subgroups that correspond to the locations where the mucus is secreted: the gut, the gills and the skin <ns0:ref type='bibr' target='#b59'>(Salinas, Zhang &amp; Sunyer, 2011)</ns0:ref>. Some studies suggest that this mucus is constantly renewed, reducing the pathogenic load found on the surface of the fish <ns0:ref type='bibr' target='#b48'>(Nagashima et al., 2003)</ns0:ref>. The mucus is secreted in higher quantities as a response to threat <ns0:ref type='bibr' target='#b46'>(Mittal &amp; Datta Munshi, 1974;</ns0:ref><ns0:ref type='bibr' target='#b28'>Gostin, Neagu &amp; Vulpe, 2011;</ns0:ref><ns0:ref type='bibr' target='#b56'>Rai et al., 2012)</ns0:ref>, and the viscose substance consists of molecules that may help in healing and protecting the skin <ns0:ref type='bibr' target='#b15'>(Cameron &amp; Endean, 1973;</ns0:ref><ns0:ref type='bibr' target='#b3'>Al-Hassan et al., 1985)</ns0:ref>, including the secretion of antimicrobial and regenerative substances <ns0:ref type='bibr' target='#b32'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. The epithelial mucus is sometimes considered an ideal surface for bacterial adhesion. In fact, the accumulation of microorganisms appears to take place during the lifetime of the individual <ns0:ref type='bibr' target='#b32'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, leading to the establishment of the microbiota in fish skin. However, it is also recognized that the mucus has a concentration of molecules that prevent the adhesion of pathogenic bacteria (Crouse-Eisnor, <ns0:ref type='bibr' target='#b23'>Cone &amp; Odense, 1985)</ns0:ref>. As such, the role or the relationship between the mucus and environmental bacteria is not clear <ns0:ref type='bibr' target='#b42'>(Luer, 2012)</ns0:ref>. It has been suggested that bacteria found in this layer may play three possible roles <ns0:ref type='bibr' target='#b60'>(Salminen et al., 2010)</ns0:ref>: a) bacteria may stimulate mucus and antimicrobial compound production, b) bacteria may activate and help modulate the immune response in the fish, and c) the interaction between different types of bacteria may actively exclude or compete with potentially pathogenic bacteria. The mucus layer in sharks and rays has been poorly studied. However, it is known that mucus from stingray skin appear to accelerate the healing processes of wounds, and that bacteria found in the mucus present antibacterial activity against human pathogens <ns0:ref type='bibr' target='#b43'>(Luer et al., 2014)</ns0:ref>. Reproductive behavior in this group is characterized by aggressiveness during courtship and copulation <ns0:ref type='bibr' target='#b52'>(Pratt &amp; Carrier, 2001;</ns0:ref><ns0:ref type='bibr' target='#b18'>Carrier, Pratt &amp; Martin, 2015)</ns0:ref>. In sharks, the male bites the female on her dorsal or pectoral fins generating wounds in those areas <ns0:ref type='bibr' target='#b52'>(Pratt &amp; Carrier, 2001)</ns0:ref>. Polyandry, a mating system in which one female mates with multiple males, is very common in some species <ns0:ref type='bibr' target='#b61'>(Saville et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b16'>Carrier et al., 2003)</ns0:ref>. This behavior drives competition between males and avoidance in females <ns0:ref type='bibr' target='#b36'>(Klimley, 1980;</ns0:ref><ns0:ref type='bibr' target='#b27'>Gordon, 1993;</ns0:ref><ns0:ref type='bibr' target='#b52'>Pratt &amp; Carrier, 2001)</ns0:ref>. There are also morphological characteristics related to this trait. Sexual dimorphism occurs in shark species in which the male&#180;s teeth are shaped so they can easily grab the female in order to remain close to her while mating. Females have thicker dermal denticles (tooth-like structures that provide hydrodynamics and protection) than males as protection against these bites <ns0:ref type='bibr' target='#b17'>(Carrier, Musick &amp; Heithaus, 2012)</ns0:ref>. In the case of rays, the females prick the male with their caudal spine <ns0:ref type='bibr' target='#b52'>(Pratt &amp; Carrier, 2001)</ns0:ref>. It has been shown in some stingray species that when many males are involved in mating, a few may die in the process <ns0:ref type='bibr' target='#b26'>(Gilad et al., 2008)</ns0:ref>. In spite of these apparently aggressive behaviors, copulation is necessary and the wounds provoked are highly likely to become infected <ns0:ref type='bibr' target='#b24'>(Daly-Engel et al., 2010)</ns0:ref> due to opportunistic bacteria in the water and in the oral cavity of males. Because of the high concentration of pathogenic microorganisms found in the aquatic environment <ns0:ref type='bibr' target='#b44'>(Magnadottir, 2010)</ns0:ref>, it is important to determine the microbiota component of the epithelial mucus, the skin, and to understand whether the bacteria found in these are similar or different from those found in the water surrounding the animals. This will help to understand the role of mucus in the protection against pathogens. In this study, we characterized the bacterial diversity in the epithelial mucus in three elasmobranch species, the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus) <ns0:ref type='bibr' target='#b41'>(Last et al., 2016)</ns0:ref>. We also hypothesize about the possible role of some of the bacteria found in the mucus and in the skin.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sample collection</ns0:head><ns0:p>Mucus and skin tissue samples were collected from 19 apparently healthy individuals (no visible wounds, normal swimming activity); 14 of them from animals captured in Bimini, Bahamas (25&#61616;43&#61602;59 N, 79&#61616;14&#61602;60 W): four corresponded to juvenile nurse sharks (Ginglymostoma cirratum), six to juvenile lemon sharks (Negaprion brevirostris), and four to adult southern stingrays (Hypanus americanus). Samples from an additional five adult nurse sharks were collected at Oceanario from Islas del Rosario (CEINER), in the Colombian Caribbean (10&#61616;10&#61602;30 N, 75&#61616;45&#61602;00 W). For each individual, we obtained a sample of skin tissue and mucus, following sampling protocols approved by the Animal Care Committee of Universidad de los Andes (CICUAL) (Bogota, Colombia). The skin tissue sample was cut, using a sterile blade for each specimen, from the posterior part of the dorsal fin (1 cm 3 or less) and the mucus from the skin surface, using a sterile 1.5 ml microcentrifuge tube to scrape the skin surface, ideally filling at least half of the tube. Animals were manipulated for approximately 5 minutes and immediately released. A water sample was also collected in sterile 15 ml tube from the place where each individual was captured. Thus, three samples were associated with each individual, for a total of 57 samples. The individuals were captured and raised slightly above the surface of the water, so that the samples could be taken outside the water, while the animal could continue breathing. Skin samples were preserved in ethanol 90%. All samples were maintained at 4&#186; C for less than one week, until processing. DNA Extraction and PCR amplification DNA was extracted from the entire sample collected for all samples. The Tissue and Cells DNA Isolation Kit (MoBio Laboratories, Inc.) was used, following the manufacturer instructions. Water samples were filtered through a 0.8 &#61549;m cellulose nitrate filter before DNA extraction. The primers 515f and 806r were used in order to amplify the region V4 from the bacterial and archaea 16S rRNA gene using the primers 515F (5&#180;-GTGCCAGCMGCCGCGGTAA-3&#180;) and 806R (5&#180;GGACTAHVGGGTWTCTAAT-3&#180;) <ns0:ref type='bibr' target='#b14'>(Caporaso et al., 2010)</ns0:ref>. PCR amplification conditions were as follows: an initial denaturation at 94 &#176;C for 3 minutes, followed by 35 cycles of denaturing at 94 &#176;C for 45 seconds, annealing for 45 seconds at 50 &#176;C and extension for 45 seconds at 72 &#176;C, followed by a final extension of 20 minutes at 72 &#176;C. Successful amplification was confirmed on 1 % agarose gel.</ns0:p></ns0:div> <ns0:div><ns0:head>Ion torrent library preparation, quantification and sequencing</ns0:head><ns0:p>From the 57 samples, 32 were used to construct libraries (Supplementary Table <ns0:ref type='table'>1</ns0:ref>). Samples were chosen depending on their final DNA concentration, once the PCR products were cleaned using magnetic beads and run on a 1.5% agarose gel. Only the samples that had a clear strong band were used for library construction. Two libraries, each with 16 barcodes, were prepared using the protocol Ion Xpress&#8482; Plus gDNA Fragment Library Preparation (Life Technologies). Libraries were quantified with the Qubit kit. Templates were prepared following the Ion PGM&#8482; Template OT2 200 Kit (Life Technologies) protocols. Libraries were prepared for sequencing using the protocol Ion PGM&#8482; Sequencing 200 Kit v2 (Life Technologies). Libraries were loaded on two Ion 316 chips and sequenced in the Ion Torrent PGM (Life Technologies). 16S datasets used in this manuscript with accompanying metadata has been submitted to Dryad as DOI https://doi.org/105061/dryad.b5mkkwh8j Bioinformatic and statistical analyses Sequences were separated by barcodes directly by the Ion Torrent PGM and saved by the ion reporter in different files; sequence quality was analyzed using FastQC <ns0:ref type='bibr' target='#b5'>(Andrews, 2014)</ns0:ref>. The file format was changed from Fastq to Fasta. All analyses were performed on the Galaxy online platform <ns0:ref type='bibr' target='#b1'>(Afgan et al. 2016)</ns0:ref> following one amplicon data workflow on Mothur v.1.28.0 <ns0:ref type='bibr' target='#b62'>(Schloss et al., 2009)</ns0:ref>. Demultiplexing was conducted by comparing the mapping file of the chip with the files containing the sequences. This workflow started by merging all read files into group files. Group files were identified as samples from each of the three elasmobranch species and also as type of sample (skin, mucus or water). The next step of the workflow identified unique sequences and generated a file with these sequences and a second file in which the number of each unique representative sequence was kept. Following this, reads were filtered based on quality and length. Parameters to remove low quality sequences (quality control) was for those with less than 20 Phred score and shorter than 50 bp. (minimum length) followed by a step to remove poorly aligned sequences and chimeric sequences. Finally, reads were clustered based on their degree of similarity, with a minimum of 97% identity threshold and aligned to the Silva V4 reference database <ns0:ref type='bibr' target='#b54'>(Quast et al., 2013)</ns0:ref>, followed by a classification step into taxonomic categories (Order, family, genus and species when possible). Afterwards, statistical analyses were conducted using the taxonomic category 'order' and a cutout of presence of at least 0.2 % was applied. Any data below this cutout point was reviewed by eye but was not included in the statistical analyses. R (R Development Core Team, 2010) was used <ns0:ref type='bibr' target='#b74'>(Wickham, 2009)</ns0:ref>, to estimate &#61537; diversity and richness (Simpson, Exponential Shannon, rarefaction curves) (package VEGAN and rareNMtests) <ns0:ref type='bibr' target='#b50'>(Oksanen et al., 2015)</ns0:ref>, and to estimate &#61538; diversity (Bray-Curtis dissimilarity index and a Principal Component Analysis (PCoA)). A Shapiro-Wilk normality test was conducted to evaluate normality among samples belonging to each elasmobranch species (Supplementary Table <ns0:ref type='table'>1</ns0:ref>), including the additional category of adults on juvenile for nurse sharks, or to each category of sample type before performing any statistical tests. Since results fell outside the normality assumption, a Kruskal-Wallis test was used to evaluate whether &#61537; diversity was significantly different among elasmobranch species or among sample type. Venn diagrams (package DVenn) were used to visualize shared orders among elasmobranch species and among sample types. In order to find co-occurrence between different bacterial and/or Archaea orders a correlation matrix was created in R using the Spearman&#180;s co-efficient as in <ns0:ref type='bibr' target='#b34'>Ju et al (2013)</ns0:ref>. Correlations had to be stronger than 0.6 with a p-value &lt; 0.01 to be considered to have a significant co-occurrence with other orders. All orders, including those with less than 0.2% presence were included in the co-ocurrence analysis. A chord plot was created to visualize the relations between the different orders.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The 32 samples used to build the libraries included a mucus or tissue sample for each of the individuals sampled and only four of the 19 samples from water (Supplementary Table <ns0:ref type='table'>1</ns0:ref>). The other samples, including 15 water samples, had low DNA concentrations that could not be used for NGS sequencing analysis, characterized by weak or no bands amplified. A total of 219,162 reads were obtained from the Ion Torrent PGM. After read quality control, 22,803 reads were used in the following steps and in the Mothur workflow. Of these, 3,639 (16% total reads) were assigned taxonomically against the SilvaV4 database while 19,164 were left unassigned (84% total reads); sequences assigned taxonomically belonged to 18 mucus, 10 skin and 4 water samples. A total of 25 phyla, 81 orders, 76 families and 33 genera were assigned (Figure <ns0:ref type='figure' target='#fig_4'>1</ns0:ref>), but analyses were restricted to order, since this was the category with higher levels of taxonomic assignments. Most reads were identified as belonging to the kingdom Bacteria (Supplementary Table <ns0:ref type='table'>2</ns0:ref>). Only very small amounts of reads belonging to the kingdom Archaea were found (&lt; 2%) in only one mucus sample from one nurse shark. Among the Archaea, the orders identified were Micrarchaeles, Cenarchaeales, Halobacteriales, and Methanobacteriales. Thirty-seven orders were shared between samples from the three elasmobranch species and the water samples, and 17 were solely found in elasmobranch samples. Twenty-seven orders were found only in the water samples (Figure <ns0:ref type='figure' target='#fig_4'>1</ns0:ref>). Fifty-four were shared among all elasmobranch species, 28 and were shared between the nurse shark and the lemon shark, and 25 were shared between the two shark species and the southern stingray (Figure <ns0:ref type='figure' target='#fig_1'>2a</ns0:ref>). Forty-five orders were shared between all sample types (water, mucus and skin), 47 were shared between mucus and skin, and less than 20 were shared between tissue or mucus and water samples (Figure <ns0:ref type='figure' target='#fig_1'>2b</ns0:ref>). Also, among elasmobranch species and types of samples, similar orders were found in every sample and with a similar distribution (Figure <ns0:ref type='figure'>3a and 3b</ns0:ref>). The highest abundance was of the order Actinomycetales and the family Nocardiaceae (i.e.genus Rhodococcus), with a slightly greater abundance of reads obtained from the lemon shark and less abundance for reads obtained from the southern stingray. Mucus and skin samples had a higher number of reads than water samples (Supplementary Figure <ns0:ref type='figure' target='#fig_4'>1</ns0:ref>). Alpha-diversity was similar among species and among types of samples (Table <ns0:ref type='table'>1a and 1b</ns0:ref>). However, there was high variation within each sample type, with some samples having 10 times the number of different orders found in other samples from the same type. Something similar was found for the samples from each species, meaning that there was high heterogeneity in samples used in this study (rarefaction curves for each species and sample type, Supplementary Figure <ns0:ref type='figure' target='#fig_1'>2</ns0:ref>). Alpha-diversity was non significantly different among species or among type of samples (Figure <ns0:ref type='figure'>4a</ns0:ref>, 4b, 4c and 4d, Supplementary Table <ns0:ref type='table'>3</ns0:ref>). In the rarefaction curves, order richness followed a similar pattern for both elasmobranch species and type of sample, obtaining greater richness in the lemon shark, followed by the nurse shark and the southern stingray (Figure <ns0:ref type='figure' target='#fig_3'>5a</ns0:ref>), and showing greater richness in mucus samples, followed by skin and water samples (Figure <ns0:ref type='figure' target='#fig_3'>5b</ns0:ref>). The Bray-Curtis dissimilarity index, used as a Beta-diversity estimate, revealed greater dissimilarity (0.45) between the microbiome communities found in tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the skin and mucus of the lemon shark and nurse shark (Figure <ns0:ref type='figure' target='#fig_5'>6</ns0:ref>). When each sample was used to calculate the Bray-Curtis dissimilarity index, patterns of bacterial community dissimilarity were less clear, but it appears that mucus and skin samples from sharks and the southern stingray were less dissimilar from each other than when compared with the water samples (Figure <ns0:ref type='figure'>7</ns0:ref>). The percentage for each order identified from the total reads (sequences) obtained for each sample and analyzed is shown in Supplementary Table <ns0:ref type='table'>1</ns0:ref> and Supplementary Figure <ns0:ref type='figure' target='#fig_4'>1</ns0:ref>. Few sequences were assigned to the species or genus levels. Most of them were assigned to higher taxonomic levels (order). However, among the genus and species identified, several reported bacterial fish pathogens, symbionts and commensals were found in the mucus, tissue, and water samples (Supplementary Table <ns0:ref type='table'>2 and Supplementary Table 4</ns0:ref>). It is interesting to note that some fish pathogens were only found in the water and not in the mucus/tissue samples, such as the order Pastereullales (i. e. Pasteurella spp., Haemophilus spp) and Oceanospirillales (i.e. Halomonas spp.)</ns0:p><ns0:p>The PCA showed higher similarity between the bacterial orders found in the skin and mucus of the two shark species in comparison with those in the southern stingray. Similarities were due a to similar number and distribution of reads identified as belonging to the order Actinomycetales (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2) (Figure <ns0:ref type='figure' target='#fig_6'>8</ns0:ref>). In the PCA separating adults and juvenile nurse sharks, no clear differentiation patterns between microbiome community composition were detected at this time (Supplementary Figure <ns0:ref type='figure'>3</ns0:ref>). The co-occurrence analysis plot showed 104 out of all 202 recognized orders (including orders with less than 0.2% presence) (Supplementary Figure <ns0:ref type='figure'>4</ns0:ref>). Most of the correlations were between candidate orders, however orders such as Chlorobiales, Deinococcales Trembayales, Thermoproteales, Desulfarculales and Furobacteriales showed strong co-occurrence. Orders such as Actinomycetales and Bacteroidales, highly influential in the principal coordinate analysis, where not found in the co-occurrence analyses plot. Discussion This study provides initial but useful baseline information on microbiome communities in elasmobranch species from which changes in microbiome communities over time and under changing conditions can be evaluated. Nevertheless, depending on the characteristics and populations of these animals, the composition and role of the whole microbiome may vary. From a conservation perspective, knowledge of the microbiome composition and function may be an important approach to understanding how these organisms may be affected in the long term by environmental change; for example, climate change or ocean acidification <ns0:ref type='bibr' target='#b8'>(Bahrndorff et al., 2016)</ns0:ref>. In general, there were few taxonomically identified sequences compared to the total (only 16%). This may be the result of the shorter length of the sequences, the kits used in sequencing (to make libraries of short sequences), and differences in the DNA concentration at the start of the amplification and library preparation processes <ns0:ref type='bibr' target='#b64'>(Solonenko et al., 2013)</ns0:ref>. However, our results are relevant to understanding the microbiome communities in elasmobranch fish and they suggest that skin tissue and mucus microbiomes of the three elasmobranch species were similar in composition. Also, although some orders were shared with the water samples, more of them were shared between the two shark species and to a lesser extent with the southern stingray. Alpha-diversity was similar among samples from the three species and among types of samples. However, there was high variation in the Alpha-diversity among samples within each species or within each sample type, which was confirmed by the rarefaction curves ran for each species or type of sample. This could have been caused by the storage conditions of some samples or due to the loss of DNA from some samples during the different steps of library preparation. Also, selective PCR amplification could generate higher amplification of some bacteria and not others. The richness of species was higher in mucus samples and in lemon shark samples. Composition of mucus samples and skin samples from sharks tended to be more similar to each other than to the southern stingray or the water samples. In this study, the bacterial diversity in the mucus and tissue included a wide range of orders, that have been described as pathogens, non-pathogens, and some that have scarcely been studied in relation to potential or confirmed hosts. Most orders identified belonged to the kingdom Bacteria, with a very small proportion of Archaea. However, some of the Archaea identified in a mucus sample belonging to a nurse shark included Cenarchaeales, which have been found to be symbionts of one marine sponge that lives at very low temperatures <ns0:ref type='bibr' target='#b53'>(Preston et al., 1996)</ns0:ref>. Interestingly, a high proportion of Actinomycetales (i.e. genus Rhodococcus) were found in mucus and tissue samples and influenced the community composition of all our samples, as showed in the PCA. Although Actinomycetales can be found in environmental samples from soil and water, some strains have been isolated from marine environments and produce antimicrobial compounds against pathogenic bacterial and fungus, particularly against some pathogenic strains of E. coli and Pseudomonas sp. <ns0:ref type='bibr' target='#b75'>(Yellamanda et al., 2016)</ns0:ref>. The phylum Actinobacteria, to which the order Actinomycetales belongs, has also been found in the skin microbiota of bony fish (Osteichthyes) <ns0:ref type='bibr' target='#b40'>(Larsen et al., 2013)</ns0:ref>. Although we focused our analysis on microbiome community diversity and composition of the orders identified, we also investigated their characteristics and those of the genera within each order because, although a smaller number of reads were identified to the genus level, some interesting data was obtained. Within the bacterial order and genera found only in water samples, three have been described as pathogens for fish, including the order Pasteurellales (genus Pasteurella spp. and Haemophilus spp.) and of the order Oceanospirillales (genus Halomonas spp.) <ns0:ref type='bibr' target='#b13'>(Bullock, 1961;</ns0:ref><ns0:ref type='bibr' target='#b33'>Hawke et al., 1987;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. There was also a species only found in water samples, Acinetobacter johnsonii (order Pseudomonadales), which has been described as a fish pathogen <ns0:ref type='bibr' target='#b37'>(Kozi&#324;ska et al., 2014)</ns0:ref>. Other sequenced bacteria present in the results of water samples, such as Moraxella sp., are opportunistic bacteria and have been found in other animals, for example in mammals <ns0:ref type='bibr' target='#b73'>(Whitman, 2015)</ns0:ref>. Some orders found only in the elasmobranch samples may also play a role as pathogens; the order Alteromonadales (i.e. genera Alteromonas, Shewanella) <ns0:ref type='bibr' target='#b10'>(Boone &amp; Bryant, 1980)</ns0:ref>, Actinomycetales (i.e. genera Mycobacterium and Nocardia), Bacillales (i.e. Staphylococcus) and Flavobacteriales (i.e. Chryseobacterium) have been reported as pathogens for various fish species <ns0:ref type='bibr' target='#b32'>(Hansen &amp; Olafsen, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. The order Syntrophobacterales (i.e. genus Syntrophobacter) was also present in mucus and skin samples and considered a possible pathogen for fish, due to the fact that bacteria that belong to this group, degrade propionate, a corticoid used in healing skin <ns0:ref type='bibr' target='#b63'>(Schulze et al., 2006)</ns0:ref>. However, many other Flavobacteriales (i.e. Flavobacterium), Vibrionales (i.e. Pseudoalteromonas), Lactobacillales (i.e. Lactobacillus) and Bacillales (i.e. Bacillus), also found only in elasmobranch samples, are considered symbionts of marine fish <ns0:ref type='bibr' target='#b4'>(Anand et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b43'>Luer et al., 2014)</ns0:ref>. Some species of Flavobacterium have been studied as commensal to fish, and have shown antimicrobial activity against fish pathogens from the genus Vibrio <ns0:ref type='bibr' target='#b39'>(Lal &amp; Tabacchioni, 2009)</ns0:ref>. Bacillus polymyxa, found in mucus and skin samples in this study, has been isolated from fish guts and some strains of this species synthesize antibiotics <ns0:ref type='bibr' target='#b51'>(Olmos, 2014)</ns0:ref>. Similarly, Bacillus subtilis has been suggested as a probiotic involved in the optimization of fish feeding <ns0:ref type='bibr' target='#b45'>(Merrifield &amp; Rodiles, 2015)</ns0:ref>. Finally, various orders sequenced from mucus and skin samples are considered normal biota of fish gills or skin (i.e., Xanthomonadales, Caulobacteriales) <ns0:ref type='bibr' target='#b69'>(Sugita et al., 1996)</ns0:ref>. However, it is important to remember that pathogenicity may be related to particular strains <ns0:ref type='bibr' target='#b25'>(Fitzgerald &amp; Musser, 2001</ns0:ref>) so cautious is needed in the interpretation of these results. For example, three orders genera found in mucus and tissue samples Lactobacillales (i.e. Streptococcus and Enterococcus), Pseudomonadales (i.e. Pseudomonas) and Vibrionales (i.e. Vibrio) are sometimes reported as pathogens and sometimes reported as symbionts. For example, S. parauberis produces streptococcosis in some fish <ns0:ref type='bibr' target='#b6'>(Austin, 2005;</ns0:ref><ns0:ref type='bibr' target='#b49'>Nho et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but other Streptococcus spp. inhibit the growth of pathogenic bacteria <ns0:ref type='bibr' target='#b32'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Similarly, Pseudomonas putrefaciens acts as a pathogen for fish <ns0:ref type='bibr' target='#b0'>(Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but P. fluorescens inhibits growth of pathogens <ns0:ref type='bibr'>(Subramanian, Ross &amp; MacKinnon, 2008)</ns0:ref> and has been isolated from healthy salmon eggs and mucus <ns0:ref type='bibr' target='#b20'>(Cipriano &amp; Dove, 2011;</ns0:ref><ns0:ref type='bibr' target='#b2'>Akinyemi et al., 2016)</ns0:ref>. Finally, Vibrio have been reported several times as an important pathogen for marine life because of its great capacity for survival and of acclimation in its host, as it hydrolyzes urea and uses it as a source of carbon and nitrogen <ns0:ref type='bibr' target='#b32'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Many species have been described as infectious for Negaprion brevirostris, especially when they are physically injured <ns0:ref type='bibr' target='#b29'>(Grimes et al., 1984a;</ns0:ref><ns0:ref type='bibr' target='#b30'>Grimes, Gruber &amp; May, 1985)</ns0:ref>; others are associated to the mortality of sharks in captivity <ns0:ref type='bibr' target='#b31'>(Grimes et al., 1984b)</ns0:ref>, and others to infections caused by hooks <ns0:ref type='bibr' target='#b11'>(Borucinska et al., 2002)</ns0:ref>. There are some species that, depending on the strain, are pathogenic or not, such as V. alginolyticus and V. parahemoliticus <ns0:ref type='bibr' target='#b7'>(Austin &amp; Austin, 2007;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>. Other species, such as Vibrio alginolyticus and V. fluviales, are considered pathogenic for fish <ns0:ref type='bibr'>(Zorrilla et al., 2003)</ns0:ref>; Vibrio fortis has been reported as a sea horse pathogen <ns0:ref type='bibr' target='#b71'>(Wang et al., 2016)</ns0:ref>; Vibrio shilonii has been found to cause coral bleaching <ns0:ref type='bibr' target='#b38'>(Kushmaro et al., 2001)</ns0:ref>. There are various bacteria identified in the mucus samples that are considered in other studies as symbionts or pathogens for other animals or humans. For example, some species of the order Bacteroidales (i.e. Bacteroides) have been described as human pathogens in periodontal disease and Prevotella copri, found in mucus and skin samples have been identified as pathogens in intestinal inflammation. Additionally, bacteria from the order Clostridiales (i.e. Helcoccocus) have also been described as pathogens for humans <ns0:ref type='bibr' target='#b19'>(Chow &amp; Clarridge, 2014)</ns0:ref>. Also, many species within the order Chlamydiales are reported as pathogens for birds and mammals <ns0:ref type='bibr' target='#b73'>(Whitman, 2015)</ns0:ref>. As examples of symbiosis of species of bacteria (found in samples for this study) with humans or other animals, it is worth mentioning Lactobacillus zeae (order Lactobacillales), which has been found to serve as protective biota for nematodes <ns0:ref type='bibr' target='#b76'>(Zhou et al., 2014)</ns0:ref>; Butyrivibrio and Selenomonas (both from the order Clostridiales) are found in the gastrointestinal tract of ruminants; other members of the order Clostridiales, including Faecalibacterium prausnitzii, Peptoniphilus, Ruminococcus, Megamonas <ns0:ref type='bibr' target='#b19'>(Chow &amp; Clarridge, 2014)</ns0:ref> and Butyricimonas (from the order Bacteroidales) <ns0:ref type='bibr' target='#b72'>(Wexler, 2007)</ns0:ref> are normal important bacteria in the human gut microbiota. Other orders sequenced from mucus samples were Flavobacteriales such as Sulcia muelleri <ns0:ref type='bibr' target='#b47'>(Moran, Tran &amp; Gerardo, 2005)</ns0:ref>, Enterobacteriales such as Baumannia cicadellinicola <ns0:ref type='bibr' target='#b22'>(Cottret et al., 2010)</ns0:ref> and Trembayales such as Carsonella ruddii <ns0:ref type='bibr' target='#b70'>(Thao et al., 2000)</ns0:ref>, which have been described in symbiotic association with insects. A very interesting case is the order Burkholderiales (i.e. Janthinobacterium lividum), which has been found in the skin of some amphibians and appears to prevent infection by Batrachochytrium dendrobatidis <ns0:ref type='bibr' target='#b12'>(Brucker et al., 2008)</ns0:ref>. These are startling examples that may be related to the findings of this study; however, more in-depth research should be conducted to identify the pathogenicity or symbiosis properties specifically in elasmobranch or fish. Results from the co-occurrence analysis presented some interesting results but not clear patterns related to the PCA results or to other previously presented analyses. Strong co-occurences were found among orders such as Elusimicrobiales, Halanaenobiales, Synachococcales, Solibacterales which are defined as marine environmental bacteria, including some desulfurating bacteria, such as Desulfarculales, but also with bacterial order characterized by their presence in extreme habitats, such as Thermobaculales and Thermoproteales. This could suggest that either these are random co-occurrences among environmental bacteria that may be contaminants to the mucus and skin samples or that desulfuration may be an important metabolic path used by bacteria in these microbiome communities. Further research on this idea may be warranted. Interestingly, Fusobacteriales, a bacterial order which has been previously found in the human gut <ns0:ref type='bibr' target='#b65'>(Suau et al., 2001)</ns0:ref>, as well as Trembayales, an order of bacteria found to be endosymbionts of insects <ns0:ref type='bibr' target='#b70'>(Thao et al., 2000)</ns0:ref>, were also found in the co-occurrence analyses, suggesting a possibly relevant role in the skin and mucus microbiome communities of elasmobranch. According to this study, the role of the mucus and the bacteria associated to it may depend on numerous variables, including the virulence and pathogenicity of each microorganism <ns0:ref type='bibr' target='#b32'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Opportunistic bacteria can acquire virulence determinants with environmental changes by different means, for example, by a) increasing their numbers by exploiting the higher production of mucus (glycoproteins) induced by presence of toxic substances in the water <ns0:ref type='bibr' target='#b32'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, by b) shifting from a non-infectious state to an infectious one through an activation caused by a physical or chemical change in the environment <ns0:ref type='bibr' target='#b32'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, or by c) Reaching the dermal layer to infect the host taking advantage of a degree of reduction of the defensive mucus layer, caused by the presence of abrasive substances in the surroundings of the fish <ns0:ref type='bibr' target='#b9'>(Benhamed et al., 2014)</ns0:ref>. These three opportunities for the bacteria to infect the hosts not only benefit these microorganisms but they also affect the host by reducing their physiological condition <ns0:ref type='bibr' target='#b6'>(Austin, 2005)</ns0:ref>, and may explain the finding of the reported bacterial pathogens on the skin of healthy animals. The orders considered fish pathogens found in the water samples but absent in the elasmobranch samples, allows this research to present an interesting assumption. We suggest that there may be specific antimicrobial activity in the skin environment, or partial control against infections that exists in low concentration in the mucus, but this might be also a result of the low number of samples and replicates analyzed <ns0:ref type='bibr' target='#b58'>(Rakers et al., 2010)</ns0:ref>. However, it is very likely that difficulties in sampling -for example, handling the sharks and stingrays-, that prevent us from collecting a larger skin or mucus sample and that this in itself could be biasing our results. The simultaneous presence of pathogens and possible symbionts varied between samples; however, the role of each order and should be verified for each of the host species considered in this analysis. According to these results, we suggest that the role of the epithelial microbiota may be considered as a first line of defense against infectious organisms but it could also be a potential threat for the injured host. This could depend on the whole combination of bacteria and their interaction between them in each host. As mentioned earlier, each fish may accumulate a specific community of microorganisms in its life span depending on the environments it inhabits during its development and growth <ns0:ref type='bibr' target='#b32'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. This study represents the first contribution to describing shark and ray skin and mucus microbiomes. The next steps to further understand the role of bacterial communities in skin and mucus of elasmobranchs require functional metagenomics and metabolomics analyses to unveil the role of these bacteria. Conclusions This study presents the first description of skin and mucus microbiota from two shark species and a stingray. Orders were highly diverse and similar between species and types of samples and a higher number of orders were found in skin and mucus when compared to water samples. The order Actinomycetales was found in a very high percentage (&gt;50%) of skin and mucus samples and could represent bacteria that may have antimicrobial activity, however the co-occurrence analysis showed strong relationships among order previously found in the human gut, as endosymbionts of insects and among orders involved in metabolic paths related to desulfuration. This is baseline information that could help in future monitoring of microbiota change in elasmobranch species that may be caused by climate change and ocean acidification. <ns0:ref type='figure' target='#fig_5'>6</ns0:ref>. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure <ns0:ref type='figure'>7</ns0:ref>. Bray-Curtis dissimilarity index calculated for order for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure <ns0:ref type='figure' target='#fig_6'>8</ns0:ref>. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due a to similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure <ns0:ref type='figure' target='#fig_4'>1</ns0:ref>. Bacterial order composition found in each sample successfully amplified in this study. Supplementary Figure <ns0:ref type='figure' target='#fig_1'>2</ns0:ref>. Rarefaction curves showing order richness for all samples among each species of elasmobranch included in this study, as well as among all samples for each sample type. Manuscript to be reviewed</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Zorrilla I., Morinigo MA., Castro D., Balebona MC., Borrego JJ. 2003. Intraspecific characterization of Vibrio alginolyticus isolates recovered from cultured fish in Spain. Journal of Applied Microbiology 95:1106-1116. DOI: 10.1046/j.1365-2672.2003.02078.x. Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type. Figure3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for orders (a) Exponential Shannon and (b) Simpson or among sample type for orders (c) Exponential Shannon and (d) Simpson.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Rarefaction curves showing order (a) richness found among elasmobranch species and showing order (b) found among sample types Figure</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 6 Bray-</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 8 PCA</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8</ns0:figDesc></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2018:07:29887:2:2:NEW 27 Mar 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2018:07:29887:2:2:NEW 27 Mar 2020)</ns0:note> <ns0:note place='foot' n='3'>PeerJ reviewing PDF | (2018:07:29887:2:2:NEW 27 Mar 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Reviewer 1 (Ciara Keating) Basic reporting Thanks to the authors for making the suggested changes. I appreciate the effort that went into the reanalysing of the sequencing data and the manuscript has improved considerably. I have revised my suggestion however to still consist of major corrections based on these changes to further improve the quality of the manuscript – but these should not be too difficult to address but would represent more than minor changes. Your raw data needs to be submitted and given an accession number, it is possible to not make this public until the manuscript is published but it needs to be submitted before accepting for publication. Perhaps the editor can advise if you need to submit a letter if you want to avoid submission to a database for a specific reason? We submitted all our raw data to Dryad, a public database to submit raw genetic data. We mention this in the first page of our manuscript in this way: “16S datasets used in this manuscript with accompanying metadata has been submitted to Dryad as DOI https://doi.org/105061/dryad.b5mkkwh8j” and we also include this in the methods section (lines 131-132) 1) Can you include OTU-level analyses? 'were assigned taxonomically to OTU against the SilvaV4 database' OTUs are classified based on a cut off threshold -usually 97% similarity with each other. Is this what you did? The sequences of these OTUs are then aligned to the specific database you choose which is a separate step. Thus, OTUs are independent of the database and a true representation of your samples. Considering many OTUs could not be matched to the database including OTU-level analysis could provide a detailed picture of the microbiology of your samples. R/ We decided to restrict our analyses to the order level. We tried to find the information of OTU´s but in Mothur (in Galaxy) we were only able to compare each time to the Silva dataset. Maybe this has something to do with our somehow limited experience with this type of analyses, but that is why we ended up restricting the analyses to orders and we explained this in a better way in the methods (lines 145-153). -->The alpha and beta diversity measures in Table 2a and 2b don’t provide a lot of information. The authors discuss within the text but fail to address whether there are significant differences between the groups or samples? From Figure 4 it appears there is no significant difference? If so can add to Supplementary Information. Is there a difference between the water and the three fish types sampled? Also, was the data rarefied to the lowest sequencing depth sample? These would make more sense performed at OTU-level ie. Not taxonomically assigned to the database. R/we explained in a better way in the text in the results section out findings of non- significant differences found for the alpha-diversities and we kept the Table and Figures in a simpler version. In methods it now reads: “A Shapiro-Wilk normality test was conducted to evaluate normality among samples belonging to each elasmobranch species (Supplementary Table 1), including the additional category of adults on juvenile for nurse sharks, or to each category of sample type before performing any statistical tests. Since results fell outside the normality assumption, a Kruskal-Wallis test was used to evaluate whether  diversity was significantly different among elasmobranch species or among sample type.” (Lines 158-163) -->Rarefaction curves need to be for each individual sample and ideally at OTU level rather than taxonomic assignment to order or family level. R/We ran rarefaction curves including all samples for each species and for each type of sample. We included this as Supplementary Figure 2. We discuss these results on lines 206 to 208. -->Discuss diversity before discussing what is shared and any description of taxa found. R/ we included your suggestion in the discussion and it now reads: “This may be the result of the shorter length of the sequences, the kits used in sequencing (to make libraries of short sequences), and differences in the DNA concentration at the start of the amplification and library preparation processes (Solonenko et al., 2013). However, our results are relevant to understanding the microbiome communities in elasmobranch fish and they suggest that skin tissue and mucus microbiomes of the three elasmobranch species were similar in composition. Also, although some orders were shared with the water samples, more of them were shared between the two shark species and to a lesser extent with the southern stingray. Alpha-diversity was similar among samples from the three species and among types of samples. However, there was high variation in the Alpha-diversity among samples within each species or within each sample type, which was confirmed by the rarefaction curves ran for each species or type of sample. This could have been caused by the storage conditions of some samples or due to the loss of DNA from some samples during the different steps of library preparation. Also, selective PCR amplification could generate higher amplification of some bacteria and not others. The richness of species was higher in mucus samples and in lemon shark samples. Composition of mucus samples and skin samples from sharks tended to be more similar to each other than to the southern stingray or the water samples. ” (Lines 261-277) 2) Can you describe your sequencing QC measures, each step and the sequences left after each output? Were chimeric sequences removed? R/ These were included in the methods sections, and now reads “Following this, reads were filtered based on quality and length. Parameters to remove low quality sequences (quality control) was for those with less than 20 Phred score and shorter than 50 bp. (minimum length) followed by a step to remove poorly aligned sequences and chimeric sequences. Finally, reads were clustered based on their degree of similarity, with a minimum of 97% identity threshold and aligned to the Silva V4 reference database (Quast et al., 2013),” (lines 145-150) 3) Figures -->8 Figures is a lot to include. Are all these essential? Are all these necessary to back up your conclusions in the manuscript? R/ We kept the number of Figures but we simplified them only to include order. Table 1 is too large for inclusion within the manuscript. This could go in Supplementary Information along with the number of sequences that passed QC for each sample type. Can include a taxa plot (species above 1-2%) at family level for each individual sample instead of table? R/ Table 1 was moved to Supplementary Table 1 -->For the shared Venns display and discuss one level only – or else OTU and then family (instead of order and family as a lot of your OTUs could not be assigned). Describing both family and order is confusing in these cases and adds no extra value. In methods you say OTUs but you show only show taxa. R/ We now limited our analyses to orders, therefore simplifying the Figures presented in terms of quantity and clarity. -->Can PCA include all samples? PCA (Principle Component Analysis) and PCoA (Principal Coordinates Analysis) measures are different, which was used? R/We are including a new PCA with all the samples (including a separation between adult and juvenile nurse sharks). This is now Supplementary Figure 3. Experimental design No comment Validity of the findings No comment Comments for the Author Abstract: Line 11: Remove sentence about collecting water samples. R/done Line 18: change to ‘and there was no significant difference’. R/changed Line 21: Add the water collection sentence to here. Combine as one shorter sentence. E.g. sampling of the raw water revealed…..These were not observed in. R/ Line 21-23: What is the evidence for their function? “We found potentially pathogenic bacteria in water samples such as Pasteurella spp., Haemophilus spp. and Halomonas spp. but these were not found in the tissue or mucus samples from any species. We found some bacterial groups such as Flavobacterium, Pseudoalteromonas, Lactobacillus and Bacillus that could play a role protecting the animals from pathogenic infection”. -Can you back this up with further data? Perhaps a co-occurrence network analysis? R/part of this sentence was removed, since in the co-occurrence analyses further relationship among these orders was not found. Results: Why would you expect the water to have a lower diversity? Any evidence? Less DNA quantified? R/we had only four water samples. However, we said this with the total number of orders (27) in water compared to the numbers for other types of samples. (Line 192) Discussion: Line 326: Remove sentence re. startling examples. R/this was removed The discussion largely discusses genera identified but the results you display are not at genus level. R/This was completely changed to the use order and mentioning some genera in parenthesis. -->Some of the colours in your taxa plot colour scheme are too similar. The text for these colour codes needs to be increased in size. R/ colors were improved -->Figure 6 and 8 say Order and Family? Which one? R/ Now all Figures refer only to order -->Include the legend for the fish pictures in each figure where these are used. R/Fish legend was included in all figures Reviewer 3 (Anonymous) Basic reporting The English used in the manuscript is correct, but sometimes there are long sentences that impede to understand everything at the first reading. I suggest to authors to make a review by a native speaker R/The manuscript was reviewed again by a native speaker The references used in the article are very appropiated, and the structure of the article is correct for the publication. Experimental design The methodology used for perform the study is appropiated. Validity of the findings It is the first study assessing the microbiota of mucus and skin in 3 Elasmobranchs species, which is interesting to have a reference in future studies. Comments for the Author In the manuscript entitled “Description of the microbiota in epidermal mucus and skin of sharks and rays”, authors performed a description of the microbial communities from 3 Elasmobranch species. It is very interesting to have a reference for future studies, and thus this manuscript deserve to be published. However, it still needs some more work to clarify some aspects of the study. One of the main concern that I have is about the different samples belonging to the nurse sharks. There are two blocks of samples: wild juveniles and captive adults. Both factors (habitat and age) may influence the microbiome, so I think that it is not correct to include those two groups as the same kind of samples just because they belong to the same species. Actually, if it is the environment which shape microbial communities, we could expect more similarities between the two shark species sharing the environment in the sea, than among wild juveniles and captive adults of the same species. Those factors should be taken in consideration in the analyses, because I’m sure that they are going to explain a part of the variance in the nurse sharks. However, it won’t be possible to distinguish among both factors since there are just those 2 categories. I have major concerns with the statistical methods. Authors say that they performed Kruskal-Wallis tests, but they didn’t present results, in the general comparison nor in the group by group one. I guess that they decided if results were significant by looking at the box-plots, which is absolutely wrong. They speak about differences in diversity of different categories, but they don’t support this with statistics. In the Fig. 4 they say that there are no visual differences, but I don’t agree, since for example in E we could say that there is. But everything is speculation, if they don’t show the statistical results. Another minor question is that when presenting the study, authors say that they worked on the taxonomical categories of Order and Family. However, in the Figure 1 for example, but also in the Discussion, they include the Phyllum and / or the Genus. Everything should be consistent. If you decide to work just on Order and Family, then remove results apart. And if you decide to include them, then say from the beginning. R/ We limited ourselves now to only order for all statistic analyses. We included results from the Shapiro-Wilk normality test and results for the Kruskal- Wallis test to evaluate differences among Alpha-diversity indices. Also, we separated juveniles and adult nurse sharks and we included a PCA as supplementary Figure 3 to show that there are no clear patterns of differentiation between microbiome communities found in adults and juveniles, which may be possibly related to sample sizes of each group. More specific comments: L6: change to “from the water or from males’ mouth” L6: “The role…” this sentence should be placed at the beginning, before talking about sharks, and as a general feature of fish. “…from colonizing the skin. However, the role…” L9: “Tissues” is confounding. Authors has analysed just the skin, so I suggest to change tissue for skin all along the manuscript. R/changed L14: “we analysed sequences… species” this sentences could be removed. R/changed L16: “particularly” is in some group, not in all the fish samples. Maybe say the diversity was higher in fish than water. And remove “was high” if you don’t say in comparison to what? There are some reference values of diversity? R/Since there are no significant differences we decided not to include them in the abstract. L18: comparatively to what? L26: “changes in… conditions, including…” L32: I suggest, for more clarity, to start the introduction as follows: “The first barrier of protection against microorganisms in fish is the mucosal immune system” L71: remove “in the process” L76: “…mucus, and the skin tissue, to assess differences among the fish microbiome and this of the surrounding water.” L77: Change “Doing so…” to “This will help to understand the role…” L78: “…we characterized the bacterial…” L79: change from to in L87: how can you know that they are healthy individuals? In those fish captured in the ocean, it is not possible to know. Maybe you could say 'apparently healthy', or explain why you know they were healthy instead. L95: More details on the sampling should be given. For instance, how did you cut the skin? With sterile scissors or could have had contamination among samples? How long lasted the manipulation? Fish were immediately released? R/this was clarified in lines 98 to 101 L100: continue breathing R/included L104: “and PCR amplification” in italics. R/corrected L105: “from all the entire samples collected” Remove in L106 “In all cases…” R/done L106: remove “for all samples” r/done L107: at which diameter of filtration? What does it means concentrated? R/Included in line 111 L108: include the sequences of the primers, and a reference. R/included in line 113-114 L110: temperatures should be written as the first one: 94 ºC, 50 ºC. R/corrected L117: insert space 1.5 % R/corrected L133: (skin, mucus or water) R/corrected line 143 L140: comma after “family” R/This was changed since now all analyses refer to orders L146-152. It’s messy. You speak of normality, then Venn diagrams, and then Kruskal-Wallis. The normality analyses should be together with the Kruskal-Wallis since is part of the same. The Venn diagram is not a statistical analyses, is just a representation of descriptive data, so I don’t think that it is necessary to say here. Also, it is not clear if the K-W test was applied to all or only to the data that did not fit in a normal distribution. Finally, it is not necessary to say that data were visualized in box-plots since this is part of the K-W test. R/this was better organized, in lines 158 to 163 L179: It’s messy, the diversities are mixed. Say first the differences among fish and sample type, making the comparison of diversity among different samples, and then bacterial groups. R/ this was better organized, from lines 204-232. L193: which is the reason to expect a higher diversity in the fish than in the water? I think that is plausible to expect the opposite. R/This was corrected, there were no significant differences. L210: change “appeared to be” to “are” R/changed L221: The first speculative sentence should not be the beginning of the Discussion. It should be removed, or placed below, and start with “this is, to our knowledge…” R/This was re-written (lines 251-257) L239: I guess is the average of the alpha-diversity, if the variation intra category is not significantly lower than inter categories (statistics?) R/Yes, this was corrected L252: Cenarchaeales, which… R/corrected L258: change which to and R/corrected L264: analysis on microbiome R/Corrected L267: were obtained L279 and so on: In general, there is always a controversy in deciding if a bacterial taxon is pathogenic or not, because sometimes it depends not just in the species, but in the strain. Here for example, Bacillus include numerous keratinolytic groups, which may cause wounds in fish skin. R/This was exaplained L288: parenthesis R/corrected L371: “presents the first description of skin and mucus...” R/Corrected L642-643: It’s OTUs, no OTU’s R/Changed Fig. 2. In the text, the figures are cited in minuscule (2a, 2b…), but in the graphs they are in majuscule. Be consistent along the manuscript. In the name of the graphs, please include Fish species instead of species, because it could be confounded with bacterial species. Fig. 4. Statistical results are needed. R/Corrected Fig. 6. I don’t understand the legend and figure. It supposed to be the distance among different categories but I can’t see this in this graph, not differences among sample types. It’s like if they are mixed, is it the average? R/We mention this with looking at the scale on the side of the graph Fig. 7. The skin of the stingray is absent? R/samples did not work "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>However, the role of skin mucus in protecting fish against pathogens is not well understood. During copulation in sharks, the male bites the female generating wounds, which are then highly likely to become infected by opportunistic bacteria from the water or from the male shark's mouth. Describing the microbial component of epithelial mucus may allow future understanding of this first line of defense in sharks. In this study, we analyzed mucus and skin samples obtained from 19 individuals of two shark species and a stingray: the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus). Total DNA was extracted from all samples, and the bacterial 16S rRNA gene (region V3-V4) was amplified and sequenced on the Ion Torrent Platform (amplicon sequencing). Bacterial diversity (order) was higher in skin and mucus than in water. Order composition was more similar between the two shark species.</ns0:p><ns0:p>Alpha-diversities for OTUs (Shannon and Simpson) were high and there were nonsignificant differences between elasmobranch species or types of samples. We found orders of potentially pathogenic bacteria in water samples collected from the area where the animals were found, such as Pasteurellales (i.e. genus Pasteurella spp. and Haemophilus spp.) and Oceanospirillales (i.e. genus Halomonas spp.) but these were not found in the skin or mucus samples from any species. Some bacterial orders, such as Flavobacteriales, Vibrionales (i.e. genus Pseudoalteromonas), Lactobacillales and Bacillales were found only in mucus and skin samples. However, in a co-occurrence analyses, no significant relationship was found among these orders but significant relationships were found among the order Trembayales, previously described as endosymbionts of insects, Fusobacteriales, previously described in the human gut, and some previously described marine environmental Bacteria and Archaea, including Elusimicrobiales, Thermoproteales, Deinococcales and Desulfarculales. This is, to our knowledge, the first study focusing on elasmobranch microbiomes. Future studies are needed to describe the functional role of</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The first barrier of protection against microorganisms in fish is the mucosal immune system <ns0:ref type='bibr' target='#b26'>(Cone, 2009)</ns0:ref>. This system protects fish physically, chemically, and biologically from threats or pathogens found in their habitat <ns0:ref type='bibr' target='#b74'>(Subramanian, MacKinnon &amp; Ross, 2007;</ns0:ref><ns0:ref type='bibr'>Subramanian, Ross &amp; Mackinnon, 2008;</ns0:ref><ns0:ref type='bibr' target='#b65'>Raj et al., 2011)</ns0:ref>. The mucosal immune system is subdivided into three subgroups that correspond to the locations where the mucus is secreted: the gut, the gills and the skin <ns0:ref type='bibr' target='#b67'>(Salinas, Zhang &amp; Sunyer, 2011)</ns0:ref>. Some studies suggest that this mucus is constantly renewed, reducing the pathogenic load found on the surface of the fish <ns0:ref type='bibr' target='#b53'>(Nagashima et al., 2003)</ns0:ref>. The mucus is secreted in higher quantities as a response to threat <ns0:ref type='bibr' target='#b51'>(Mittal &amp; Datta Munshi, 1974;</ns0:ref><ns0:ref type='bibr' target='#b33'>Gostin, Neagu &amp; Vulpe, 2011;</ns0:ref><ns0:ref type='bibr' target='#b64'>Rai et al., 2012)</ns0:ref>, and the viscose substance consists of molecules that may help in healing and protecting the skin <ns0:ref type='bibr' target='#b18'>(Cameron &amp; Endean, 1973;</ns0:ref><ns0:ref type='bibr' target='#b3'>Al-Hassan et al., 1985)</ns0:ref>, including the secretion of antimicrobial and regenerative substances <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. The epithelial mucus is sometimes considered an ideal surface for bacterial adhesion. In fact, the accumulation of microorganisms appears to take place during the lifetime of the individual <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, leading to the establishment of the microbiota in fish skin. However, it is also recognized that the mucus has a concentration of molecules that prevent the adhesion of pathogenic bacteria (Crouse-Eisnor, <ns0:ref type='bibr' target='#b28'>Cone &amp; Odense, 1985)</ns0:ref>. As such, the role or the relationship between the mucus and environmental bacteria is not clear <ns0:ref type='bibr' target='#b47'>(Luer, 2012)</ns0:ref>. It has been suggested that bacteria found in this layer may play three possible roles <ns0:ref type='bibr' target='#b68'>(Salminen et al., 2010)</ns0:ref>: a) bacteria may stimulate mucus and antimicrobial compound production, b) bacteria may activate and help modulate the immune response in the fish, and c) the interaction between different types of bacteria may actively exclude or compete with potentially pathogenic bacteria. The mucus layer in sharks and rays has been poorly studied. However, it is known that mucus from stingray skin appear to accelerate the healing processes of wounds, and that bacteria found in the mucus present antibacterial activity against human pathogens <ns0:ref type='bibr' target='#b48'>(Luer et al., 2014)</ns0:ref>. Also, it has been found recently that the structure, geometry and arrangement of dermal denticles of the shark skin play an important role in allowing bacterial attachment and development of biofilms <ns0:ref type='bibr' target='#b23'>(Chien et al. 2020)</ns0:ref>. Reproductive behavior in this group is characterized by aggressiveness during courtship and copulation <ns0:ref type='bibr' target='#b59'>(Pratt &amp; Carrier, 2001;</ns0:ref><ns0:ref type='bibr' target='#b21'>Carrier, Pratt &amp; Martin, 2015)</ns0:ref>. In sharks, the male bites the female on her dorsal or pectoral fins generating wounds in those areas <ns0:ref type='bibr' target='#b59'>(Pratt &amp; Carrier, 2001)</ns0:ref>. Polyandry, a mating system in which one female mates with multiple males, is very common in some species <ns0:ref type='bibr' target='#b69'>(Saville et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b19'>Carrier et al., 2003)</ns0:ref>. This behavior drives competition between males and avoidance in females <ns0:ref type='bibr' target='#b41'>(Klimley, 1980;</ns0:ref><ns0:ref type='bibr' target='#b32'>Gordon, 1993;</ns0:ref><ns0:ref type='bibr' target='#b59'>Pratt &amp; Carrier, 2001)</ns0:ref>. There are also morphological characteristics related to this trait. Sexual dimorphism occurs in shark species in which the male&#180;s teeth are shaped so they can easily grab the female in order to remain close to her while mating. Females have thicker dermal denticles (tooth-like structures that provide hydrodynamics and protection) than males as protection against these bites <ns0:ref type='bibr' target='#b20'>(Carrier, Musick &amp; Heithaus, 2012)</ns0:ref>. In the case of rays, the females prick the male with their caudal spine <ns0:ref type='bibr' target='#b59'>(Pratt &amp; Carrier, 2001)</ns0:ref>. It has been shown in some stingray species that when many males are involved in mating, a few may die in the process <ns0:ref type='bibr' target='#b31'>(Gilad et al., 2008)</ns0:ref>. In spite of these apparently aggressive behaviors, copulation is necessary and the wounds provoked are highly likely to become infected <ns0:ref type='bibr' target='#b29'>(Daly-Engel et al., 2010)</ns0:ref> due to opportunistic bacteria in the water and in the oral cavity of males. Because of the high concentration of pathogenic microorganisms found in the aquatic environment <ns0:ref type='bibr' target='#b49'>(Magnadottir, 2010)</ns0:ref>, it is important to determine the microbiota component of the epithelial mucus, the skin, and to understand whether the bacteria found in these are similar or different from those found in the water surrounding the animals. This will help to understand the role of mucus in the protection against pathogens. In this study, we characterized the bacterial diversity in the epithelial mucus in three elasmobranch species, the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus) <ns0:ref type='bibr' target='#b46'>(Last et al., 2016)</ns0:ref>. We also hypothesize about the possible role of some of the bacteria found in the mucus and in the skin.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sample collection</ns0:head><ns0:p>Mucus and skin tissue samples were collected from 19 apparently healthy individuals (no visible wounds, normal swimming activity); 14 of them from animals captured in Bimini, Bahamas (25&#61616;43&#61602;59 N, 79&#61616;14&#61602;60 W): four corresponded to juvenile nurse sharks (Ginglymostoma cirratum), six to juvenile lemon sharks (Negaprion brevirostris), and four to adult southern stingrays (Hypanus americanus). Samples from an additional five adult nurse sharks were collected at Oceanario from Islas del Rosario (CEINER), in the Colombian Caribbean (10&#61616;10&#61602;30 N, 75&#61616;45&#61602;00 W). For each individual, we obtained a sample of skin tissue and mucus, following sampling protocols approved by the Animal Care Committee of Universidad de los Andes (CICUAL) (Bogota, Colombia). The skin tissue sample was cut, using a sterile blade for each specimen, from the posterior part of the dorsal fin (1 cm 3 or less) and the mucus from the skin surface, using a sterile 1.5 ml microcentrifuge tube to scrape the skin surface, ideally filling at least half of the tube. Animals were manipulated for approximately 5 minutes and immediately released. A water sample was also collected in sterile 15 ml tube from the sampling location of each individual. Thus, three samples were associated with each individual, for a total of 57 samples. The individuals were captured and raised slightly above the surface of the water, so that the samples could be taken outside the water, while the animal could continue breathing. Skin samples were preserved in ethanol 90%. All samples were maintained at 4 &#186;C for less than one week, until processing. DNA Extraction and PCR amplification DNA was extracted from the entire sample collected for all samples. The Tissue and Cells DNA Isolation Kit (MoBio Laboratories, Inc.) was used, following the manufacturer instructions. Water samples were filtered through a 0.8 &#61549;m cellulose nitrate filter before DNA extraction. The primers 515f and 806r were used in order to amplify the region V4 from the bacterial and archaea 16S rRNA gene using the primers 515F (5&#180;-GTGCCAGCMGCCGCGGTAA-3&#180;) and 806R (5&#180;GGACTAHVGGGTWTCTAAT-3&#180;) <ns0:ref type='bibr' target='#b17'>(Caporaso et al., 2010)</ns0:ref>. PCR amplification conditions were as follows: an initial denaturation at 94 &#176;C for 3 minutes, followed by 35 cycles of denaturing at 94 &#176;C for 45 seconds, annealing for 45 seconds at 50 &#176;C and extension for 45 seconds at 72 &#176;C, followed by a final extension of 20 minutes at 72 &#176;C. Successful amplification was confirmed on 1 % agarose gel.</ns0:p></ns0:div> <ns0:div><ns0:head>Ion torrent library preparation, quantification and sequencing</ns0:head><ns0:p>From the 57 samples, 32 were used to construct libraries (Supplementary Table <ns0:ref type='table'>1</ns0:ref>). Samples were chosen depending on their final DNA concentration, once the PCR products were cleaned using magnetic beads and run on a 1.5% agarose gel. Only the samples that had a clear strong band were used for library construction. Two libraries, each with 16 barcodes, were prepared using the protocol Ion Xpress&#8482; Plus gDNA Fragment Library Preparation (Life Technologies). Libraries were quantified with the Qubit kit. Templates were prepared following the Ion PGM&#8482; Template OT2 200 Kit (Life Technologies) protocols. Libraries were prepared for sequencing using the protocol Ion PGM&#8482; Sequencing 200 Kit v2 (Life Technologies). Libraries were pooled to equimolar concentration and loaded on two Ion 316 chips and sequenced in the Ion Torrent PGM (Life Technologies). 16S datasets used in this manuscript with accompanying metadata has been submitted to Dryad as DOI https://doi.org/105061/dryad.b5mkkwh8j Bioinformatic and statistical analyses Sequences were separated by barcodes directly by the Ion Torrent PGM and saved by the ion reporter in different files; sequence quality was analyzed using FastQC <ns0:ref type='bibr' target='#b5'>(Andrews, 2014)</ns0:ref>. The file format was changed from Fastq to Fasta. Demultiplexing was conducted by comparing the mapping file of the chip with the files containing the sequences. For the core diversity analysis, qiime <ns0:ref type='bibr'>(Bolyen et al. 2019)</ns0:ref> was used via command line using the moving pictures tutorial as reference. The files were imported as 'MultiplexedSingleEndBarcodeInSequence' and demultiplexed using 'cutadapt', eliminating sequences shorter than 50 bp. The sequences went through DADA2 <ns0:ref type='bibr' target='#b16'>(Callahan et al. 2016)</ns0:ref> for quality control to delete sequences with lower qscore than 20 and then the remaining sequences were aligned de novo with align-to-tree-mafft-fastree. In parallel the sequences were clustered into OTUs with 97% identity to perform non phylogenetic analysis. The rooted tree obtained with fasttree2 <ns0:ref type='bibr' target='#b61'>(Price et al. 2010)</ns0:ref> was used to perform an alpha rarefaction with a 1000 sequence depth. For taxonomic assignment, analyses were performed on the Galaxy online platform <ns0:ref type='bibr' target='#b1'>(Afgan et al. 2016)</ns0:ref> following one amplicon data workflow on Mothur v.1.28.0 <ns0:ref type='bibr' target='#b70'>(Schloss et al., 2009)</ns0:ref>. This workflow started by merging all read files into group files. Group files were identified as samples from each of the three elasmobranch species and also as type of sample (skin, mucus or water). The next step of the workflow identified unique sequences and generated a file with these sequences and a second file in which the number of each unique representative sequence was kept. Following this, reads were filtered based on quality and length. Parameters to remove low quality sequences (quality control) was for those with less than 20 Phred score and shorter than 50 bp. (minimum length) followed by a step to remove poorly aligned sequences and chimeric sequences. Finally, reads were clustered based on their degree of similarity, with a minimum of 97% identity threshold and aligned to the Silva V4 reference database <ns0:ref type='bibr' target='#b62'>(Quast et al., 2013)</ns0:ref>, followed by a classification step into taxonomic categories (order, family, genus and species when possible). Rstudio version 1.1.463 (R Development Core Team, 2010) was used <ns0:ref type='bibr' target='#b82'>(Wickham, 2009)</ns0:ref> for alpha (&#61537;) diversity analyses (Simpson and Shannon) (package VEGAN) which were conducted for OTUs, using the number of OTUs per sample, comparing among species (N. brevirostris, G. cirratum juveniles and adults and H. americanus) and among sample types (tissue, mucus and water). A Shapiro-Wilk normality test was conducted to evaluate normality among samples belonging to each elasmobranch species (Supplementary Table <ns0:ref type='table'>1</ns0:ref>), including the additional category of adults and juvenile for nurse sharks, or to each category of sample type before performing any statistical tests. Since results fell outside the normality assumption, a Kruskal-Wallis test was used to evaluate whether &#61537; diversity was significantly different among elasmobranch species or among sample type. To estimate beta (&#61538;) diversity (Bray-Curtis dissimilarity index and a Principal Component Analysis (PCA) the taxonomic category 'order' was used. Venn diagrams (package DVenn) were used to visualize shared orders among elasmobranch species and among sample types. In order to find co-occurrence between different bacterial and/or Archaea orders a correlation matrix was created in R using the Spearman&#180;s co-efficient as in <ns0:ref type='bibr' target='#b39'>Ju et al (2013)</ns0:ref>. Correlations had to be stronger than 0.6 with a p-value &lt; 0.01 to be considered to have a significant co-occurrence with other orders. All orders, including those with less than 0.2% presence were included in the co-ocurrence analysis. A chord plot was created to visualize the relations between the different orders.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The 32 samples used to build the libraries included a mucus or tissue sample for each of the individuals sampled and only four of the 19 samples from water (Supplementary Table <ns0:ref type='table'>1</ns0:ref>). The other samples, including 15 water samples, had low DNA concentrations that could not be used for NGS sequencing analysis, characterized by weak or no bands amplified. A total of 219,162 reads were obtained from the Ion Torrent PGM of which 55,642 were used for subsequent analyses following demultiplexing. After read quality control and chimera removal, 21,530 reads were used in the following steps for qiime and in the Mothur workflow. Of these, 17,685 were grouped as unique OTUs in qiime (most of them represented each by only one read, Supplementary Figure <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>) (82% total reads). In Mothur, 3,639 (16.9 % total reads) were assigned taxonomically against the SilvaV4 database while 19,164 were left unassigned (84% total reads); sequences assigned taxonomically belonged to 18 mucus, 10 skin and 4 water samples. A total of 25 phyla, 81 orders, 76 families and 33 genera were assigned (Figure <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>), but analyses were restricted to OTU and to the taxonomic category 'order', since this was the category with higher levels of taxonomic assignments. Most reads were identified as belonging to the kingdom Bacteria (Supplementary Table <ns0:ref type='table'>2</ns0:ref>). Only very small amounts of reads belonging to the kingdom Archaea were found (&lt; 2%) in only one mucus sample from one nurse shark. Among the Archaea, the orders identified were Micrarchaeles, Cenarchaeales, Halobacteriales, and Methanobacteriales. Thirty-seven orders were shared between samples from the three elasmobranch species and the water samples, and 17 were solely found in elasmobranch samples. Twenty-seven orders were found only in the water samples (Figure <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>). Fifty-four were shared among all elasmobranch species, 28 were shared between the nurse shark and the lemon shark, and 25 were shared between the two shark species and the southern stingray (Figure <ns0:ref type='figure' target='#fig_4'>2a</ns0:ref>). Forty-five orders were shared between all sample types (water, mucus and skin), 47 were shared between mucus and skin, and less than 20 were shared between tissue or mucus and water samples (Figure <ns0:ref type='figure' target='#fig_4'>2b</ns0:ref>). Also, among elasmobranch species and types of samples, similar orders were found in every sample and with a similar distribution (Figure <ns0:ref type='figure'>3a and 3b</ns0:ref>). The highest abundance was of the order Actinomycetales and the family Nocardiaceae (i.e.genus Rhodococcus), with a slightly greater abundance of reads obtained from the lemon shark and less abundance for reads obtained from the southern stingray.</ns0:p><ns0:p>Mucus and skin samples had a higher number of reads than water samples (Supplementary Figure <ns0:ref type='figure' target='#fig_1'>2</ns0:ref>). Phylogenetic diversity was used to build a rarefaction curve, following a phylogenetic aligned tree method, as it allowed a better visualization of data since most rarefaction curves were too similar to be distinguished. However, this methodology allowed clearer observation of the high heterogeneity found in samples used in this study, with some samples having much a higher number of total reads than others. Also, it showed that most if not all the samples did not reach an asymptote as showed in Supplementary Figure <ns0:ref type='figure'>3</ns0:ref>. For OTUs, Alpha-diversity was similar among species and among types of samples (Table <ns0:ref type='table'>1a and 1b</ns0:ref>). Alpha-diversity was non significantly different among species or among type of samples (Figure <ns0:ref type='figure' target='#fig_8'>4a, 4b, 4c and 4d</ns0:ref>). Using the taxonomic category 'order', the Bray-Curtis dissimilarity index, used as a &#61538; diversity estimate, revealed greater dissimilarity (0.45) between the microbiome communities found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the skin and mucus of the lemon shark and nurse shark (Figure <ns0:ref type='figure' target='#fig_9'>5</ns0:ref>). When each sample was used to calculate the Bray-Curtis dissimilarity index, patterns of bacterial community dissimilarity were less clear, but it appears that mucus and skin samples from sharks and the southern stingray were less dissimilar from each other than when compared with the water samples (Figure <ns0:ref type='figure' target='#fig_10'>6</ns0:ref>). The percentage for each order identified from the total reads (sequences) obtained for each sample and analyzed is shown in Supplementary Table <ns0:ref type='table'>2</ns0:ref> and Supplementary Figure <ns0:ref type='figure' target='#fig_1'>2</ns0:ref>. Few sequences were assigned to the species or genus levels. Most of them were assigned to higher taxonomic levels (order). However, among the genus and species identified, several reported bacterial fish pathogens, symbionts and commensals were found in the mucus, tissue, and water samples (Supplementary Table <ns0:ref type='table'>2 and Supplementary Table 4</ns0:ref>). It is interesting to note that some fish pathogens were only found in the water and not in the mucus/tissue samples, such as the order Pastereullales (i. e. Pasteurella spp., Haemophilus spp) and Oceanospirillales (i.e. Halomonas spp.) The PCA showed higher similarity between the bacterial orders found in the skin and mucus of the two shark species in comparison with those in the southern stingray. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2) (Figure <ns0:ref type='figure'>7</ns0:ref>). In the PCA separating adults and juvenile nurse sharks, no clear differentiation patterns between microbiome community composition were detected at this time (Supplementary Figure <ns0:ref type='figure' target='#fig_6'>4</ns0:ref>). The co-occurrence analysis plot showed 104 out of all 202 recognized orders (including orders with less than 0.2% presence) (Supplementary Figure <ns0:ref type='figure' target='#fig_9'>5</ns0:ref>). Most of the correlations were between candidate orders, however orders such as Chlorobiales, Deinococcales Trembayales, Thermoproteales, Desulfarculales and Furobacteriales showed strong co-occurrence. Orders such as Actinomycetales and Bacteroidales, highly influential in the principal coordinate analysis, where not found in the co-occurrence analyses plot.</ns0:p><ns0:p>PeerJ reviewing PDF | (2018:07:29887:3:0:NEW 16 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed Discussion This study provides initial but useful baseline information on microbiome communities in elasmobranch species from which changes in microbiome communities over time and under changing conditions can be evaluated. Nevertheless, depending on the characteristics and populations of these animals, the composition and role of the whole microbiome may vary. From a conservation perspective, knowledge of the microbiome composition and function may be an important approach for understanding how these organisms may be affected in the long term by environmental change; for example, climate change or ocean acidification <ns0:ref type='bibr' target='#b8'>(Bahrndorff et al., 2016)</ns0:ref>. In general, there were few taxonomically identified sequences compared to the total (only 16.9 % of the total reads) and as compared to OTUs grouped (82% of the total reads), This may be the result of the shorter length of the sequences, the kits used in sequencing (to make libraries of short sequences), and differences in the DNA concentration at the start of the amplification and library preparation processes <ns0:ref type='bibr' target='#b72'>(Solonenko et al., 2013)</ns0:ref>. Also, it has been suggested that the primers used in this study may amplify DNA from the host species (eukaryotic DNA), which would then reduce the total number of microbial reads that would have been included in our analysis <ns0:ref type='bibr' target='#b58'>(Parada et al., 2016)</ns0:ref>. However, our results are relevant to understand the microbiome communities in elasmobranch fish and they suggest that skin tissue and mucus microbiomes of the three elasmobranch species were similar in composition. Also, although some orders were shared with the water samples, more of them were shared between the two shark species and to a lesser extent with the southern stingray. Alpha-diversity for OTUs was similar among samples from the three species and among types of samples. However, there was high variation in the Alpha-diversity among samples within each species or within each sample type, which was confirmed by the rarefaction curve ran for all samples included in the study. This could be related with different number of reads obtained per sample, since alpha diversity indices can be sensitive to differences in sample sizes <ns0:ref type='bibr' target='#b9'>(Barrantes &amp; Sandoval, 2009)</ns0:ref>. This could have been caused by the storage conditions of some samples or due to the loss of DNA from some samples during the different steps of library preparation. Also, selective PCR amplification could generate higher amplification of some bacteria and not others. The richness of species was higher in mucus samples and in lemon shark samples. Composition of mucus samples and skin samples from sharks tended to be more similar to each other than to the southern stingray or the water samples. In this study, the bacterial diversity in the mucus and tissue included a wide range of orders, that have been described as pathogens, non-pathogens, and some that have scarcely been studied in relation to potential or confirmed hosts. Most orders identified belonged to the kingdom Bacteria, with a very small proportion of Archaea. However, some of the Archaea identified in a mucus sample belonging to a nurse shark included Cenarchaeales, which have been found to be symbionts of one marine sponge that lives at very low temperatures <ns0:ref type='bibr' target='#b60'>(Preston et al., 1996)</ns0:ref>. Interestingly, a high proportion of Actinomycetales (i.e. genus Rhodococcus) were found in mucus and tissue samples and influenced the community composition of all our samples, as showed in the PCA. Although Actinomycetales can be found in environmental samples from soil and water, strains have been isolated from marine environments and produce antimicrobial compounds against pathogenic bacterial and fungus, particularly against some pathogenic strains of E. coli and Pseudomonas sp. <ns0:ref type='bibr' target='#b83'>(Yellamanda et al., 2016)</ns0:ref>. The phylum Actinobacteria, to which the order Actinomycetales belongs, has also been found in the skin microbiota of bony fish (Osteichthyes) <ns0:ref type='bibr' target='#b45'>(Larsen et al., 2013)</ns0:ref>. Although we focused our analysis on microbiome community diversity and composition of the orders identified, we also investigated their characteristics and those of the genera within each order because, although a smaller number of reads were identified to the genus level, some interesting data was obtained. Within the bacterial order and genera found only in water samples, three have been described as pathogens for fish, including the order Pasteurellales (genus Pasteurella spp. and Haemophilus spp.) and of the order Oceanospirillales (genus Halomonas spp.) <ns0:ref type='bibr' target='#b15'>(Bullock, 1961;</ns0:ref><ns0:ref type='bibr' target='#b38'>Hawke et al., 1987;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. There was also a species only found in water samples, Acinetobacter johnsonii (order Pseudomonadales), which has been described as a fish pathogen <ns0:ref type='bibr' target='#b42'>(Kozi&#324;ska et al., 2014)</ns0:ref>. Other sequenced bacteria present in the results of water samples, such as Moraxella sp., are opportunistic bacteria and have been found in other animals, for example in mammals <ns0:ref type='bibr' target='#b81'>(Whitman, 2015)</ns0:ref>. Some orders found only in the elasmobranch samples may also play a role as pathogens; the order Alteromonadales (i.e. genera Alteromonas, Shewanella) <ns0:ref type='bibr' target='#b12'>(Boone &amp; Bryant, 1980)</ns0:ref>, Actinomycetales (i.e. genera Mycobacterium and Nocardia), Bacillales (i.e. Staphylococcus) and Flavobacteriales (i.e. Chryseobacterium) have been reported as pathogens for various fish species <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. The order Syntrophobacterales (i.e. genus Syntrophobacter) was also present in mucus and skin samples and considered a possible pathogen for fish, due to the fact that bacteria that belong to this group, degrade propionate, a corticoid used in healing skin <ns0:ref type='bibr' target='#b71'>(Schulze et al., 2006)</ns0:ref>. However, many other Flavobacteriales (i.e. Flavobacterium), Vibrionales (i.e. Pseudoalteromonas), Lactobacillales (i.e. Lactobacillus) and Bacillales (i.e. Bacillus), also found only in elasmobranch samples, are considered symbionts of marine fish <ns0:ref type='bibr' target='#b4'>(Anand et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b48'>Luer et al., 2014)</ns0:ref>. Some species of Flavobacterium have been studied as commensal to fish, and have shown antimicrobial activity against fish pathogens from the genus Vibrio <ns0:ref type='bibr' target='#b44'>(Lal &amp; Tabacchioni, 2009)</ns0:ref>. Bacillus polymyxa, found in mucus and skin samples in this study, has been isolated from fish guts and some strains of this species synthesize antibiotics <ns0:ref type='bibr' target='#b56'>(Olmos, 2014)</ns0:ref>. Similarly, Bacillus subtilis has been suggested as a probiotic involved in the optimization of fish feeding <ns0:ref type='bibr' target='#b50'>(Merrifield &amp; Rodiles, 2015)</ns0:ref>. Finally, various orders sequenced from mucus and skin samples are considered normal biota of fish gills or skin (i.e., Xanthomonadales, Caulobacteriales) <ns0:ref type='bibr' target='#b77'>(Sugita et al., 1996)</ns0:ref>. However, it is important to remember that pathogenicity may be related to particular strains <ns0:ref type='bibr' target='#b30'>(Fitzgerald &amp; Musser, 2001</ns0:ref>) so caution is needed in the interpretation of these results. For example, three orders genera found in mucus and tissue samples Lactobacillales (i.e. Streptococcus and Enterococcus), Pseudomonadales (i.e. Pseudomonas) and Vibrionales (i.e. Vibrio) are sometimes reported as pathogens and sometimes reported as symbionts. For example, S. parauberis produces streptococcosis in some fish <ns0:ref type='bibr' target='#b6'>(Austin, 2005;</ns0:ref><ns0:ref type='bibr' target='#b54'>Nho et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but other Streptococcus spp. inhibit the growth of pathogenic bacteria <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Similarly, Pseudomonas putrefaciens acts as a pathogen for fish <ns0:ref type='bibr' target='#b0'>(Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but P. fluorescens inhibits growth of pathogens <ns0:ref type='bibr'>(Subramanian, Ross &amp; MacKinnon, 2008)</ns0:ref> and has been isolated from healthy salmon eggs and mucus <ns0:ref type='bibr' target='#b25'>(Cipriano &amp; Dove, 2011;</ns0:ref><ns0:ref type='bibr' target='#b2'>Akinyemi et al., 2016)</ns0:ref>. Finally, Vibrio have been reported several times as an important pathogen for marine life because of its great capacity for survival and of acclimation in its host, as it hydrolyzes urea and uses it as a source of carbon and nitrogen <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Many species have been described as infectious for Negaprion brevirostris, especially when they are physically injured <ns0:ref type='bibr' target='#b34'>(Grimes et al., 1984a;</ns0:ref><ns0:ref type='bibr' target='#b35'>Grimes, Gruber &amp; May, 1985)</ns0:ref>; others are associated to the mortality of sharks in captivity <ns0:ref type='bibr' target='#b36'>(Grimes et al., 1984b)</ns0:ref>, and others to infections caused by hooks <ns0:ref type='bibr' target='#b13'>(Borucinska et al., 2002)</ns0:ref>. There are some species that, depending on the strain, are pathogenic or not, such as V. alginolyticus and V. parahemoliticus <ns0:ref type='bibr' target='#b7'>(Austin &amp; Austin, 2007;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>. Other species, such as Vibrio alginolyticus and V. fluviales, are considered pathogenic for fish in general <ns0:ref type='bibr' target='#b85'>(Zorrilla et al., 2003)</ns0:ref>; Vibrio fortis has been reported as a sea horse pathogen <ns0:ref type='bibr' target='#b79'>(Wang et al., 2016)</ns0:ref>; Vibrio shilonii has been found to cause coral bleaching <ns0:ref type='bibr' target='#b43'>(Kushmaro et al., 2001)</ns0:ref>. There are various bacteria identified in the mucus samples that are considered in other studies as symbionts or pathogens for other animals or humans. For example, some species of the order Bacteroidales (i.e. Bacteroides) have been described as human pathogens in periodontal disease and Prevotella copri, found in mucus and skin samples have been identified as pathogens in intestinal inflammation. Additionally, bacteria from the order Clostridiales (i.e. Helcoccocus) have also been described as pathogens for humans <ns0:ref type='bibr' target='#b24'>(Chow &amp; Clarridge, 2014)</ns0:ref>. Also, many species within the order Chlamydiales are reported as pathogens for birds and mammals <ns0:ref type='bibr' target='#b81'>(Whitman, 2015)</ns0:ref>. As examples of symbiosis of species of bacteria (found in samples for this study) with humans or other animals, it is worth mentioning Lactobacillus zeae (order Lactobacillales), which has been found to serve as protective biota for nematodes <ns0:ref type='bibr' target='#b84'>(Zhou et al., 2014)</ns0:ref>; Butyrivibrio and Selenomonas (both from the order Clostridiales) are found in the gastrointestinal tract of ruminants; other members of the order Clostridiales, including Faecalibacterium prausnitzii, Peptoniphilus, Ruminococcus, Megamonas <ns0:ref type='bibr' target='#b24'>(Chow &amp; Clarridge, 2014)</ns0:ref> and Butyricimonas (from the order Bacteroidales) <ns0:ref type='bibr' target='#b80'>(Wexler, 2007)</ns0:ref> are normal important bacteria in the human gut microbiota. Other orders sequenced from mucus samples were Flavobacteriales such as Sulcia muelleri <ns0:ref type='bibr' target='#b52'>(Moran, Tran &amp; Gerardo, 2005)</ns0:ref>, Enterobacteriales such as Baumannia cicadellinicola <ns0:ref type='bibr' target='#b27'>(Cottret et al., 2010)</ns0:ref> and Trembayales such as Carsonella ruddii <ns0:ref type='bibr' target='#b78'>(Thao et al., 2000)</ns0:ref>, which have been described in symbiotic association with insects. A very interesting case is the order Burkholderiales (i.e. Janthinobacterium lividum), which has been found in the skin of some amphibians and appears to prevent infection by Batrachochytrium dendrobatidis <ns0:ref type='bibr' target='#b14'>(Brucker et al., 2008)</ns0:ref>. These are startling examples that may be related to the findings of this study; however, more in-depth research should be conducted to identify the pathogenicity or symbiosis properties specifically in elasmobranch or fish. Results from the co-occurrence analysis presented some interesting results but not clear patterns related to the PCA results or to other previously presented analyses. Strong co-occurences were found among orders such as Elusimicrobiales, Halanaenobiales, Synachococcales, Solibacterales which are defined as marine environmental bacteria, including some desulfurating bacteria, such as Desulfarculales, but also with bacterial order characterized by their presence in extreme habitats, such as Thermobaculales and Thermoproteales. This could suggest that either these are random co-occurrences among environmental bacteria that may be contaminants to the mucus and skin samples or that desulfuration may be an important metabolic path used by bacteria in these microbiome communities. Further research on this idea may be warranted. Interestingly, Fusobacteriales, a bacterial order which has been previously found in the human gut <ns0:ref type='bibr' target='#b73'>(Suau et al., 2001)</ns0:ref>, as well as Trembayales, an order of bacteria found to be endosymbionts of insects <ns0:ref type='bibr' target='#b78'>(Thao et al., 2000)</ns0:ref>, were also found in the co-occurrence analyses, suggesting a possibly relevant role in the skin and mucus microbiome communities of elasmobranch. According to this study, the role of the mucus and the bacteria associated to it may depend on numerous variables, including the virulence and pathogenicity of each microorganism <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Opportunistic bacteria can acquire virulence determinants with environmental changes by different means, for example, by a) increasing their numbers by exploiting the higher production of mucus (glycoproteins) induced by presence of toxic substances in the water <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, by b) shifting from a non-infectious state to an infectious one through an activation caused by a physical or chemical change in the environment <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, or by c) Reaching the dermal layer to infect the host taking advantage of a degree of reduction of the defensive mucus layer, caused by the presence of abrasive substances in the surroundings of the fish <ns0:ref type='bibr' target='#b10'>(Benhamed et al., 2014)</ns0:ref>. These three opportunities for the bacteria to infect the hosts not only benefit these microorganisms but they also affect the host by reducing their physiological condition <ns0:ref type='bibr' target='#b6'>(Austin, 2005)</ns0:ref>, and may explain the finding of the reported bacterial pathogens on the skin of healthy animals. The orders considered fish pathogens found in the water samples but absent in the elasmobranch samples, allows this research to present an interesting assumption. We suggest that there may be specific antimicrobial activity in the skin environment, or partial control against infections that exists in low concentration in the mucus, but this might be also a result of the low number of samples and replicates analyzed <ns0:ref type='bibr' target='#b66'>(Rakers et al., 2010)</ns0:ref>. However, it is very likely that difficulties in sampling -for example, handling the sharks and stingrays-, prevented us from collecting a larger skin or mucus sample and that this in itself could be biasing our results. The simultaneous presence of pathogens and possible symbionts varied between samples; however, the role of each order should be verified for each of the host species considered in this analysis. According to these results, we suggest that the role of the epithelial microbiota may be considered as a first line of defense against infectious organisms but it could also be a potential threat for the injured host. This may be particularly relevant as a protective mechanism for sharks and rays that get hurt during copulation and that could otherwise die due to infected wounds. This could also depend on the whole combination of bacteria and their interaction between them in each host, as well as with the host cell and physiology, known as the 'holobiont' <ns0:ref type='bibr' target='#b22'>(Carthey et al., 2020)</ns0:ref>. As mentioned earlier, each fish may accumulate a specific community of microorganisms in its life span depending on the environments it inhabits during its development and growth <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. This particular accumulation and interaction between the microbiota and the host (holobiont) may also affect aspects such as survival and reproduction of the host, and may become relevant for conservation of these shark species in the near future <ns0:ref type='bibr' target='#b22'>(Carthey et al., 2020)</ns0:ref>. This study represents the first contribution to describing shark and ray skin and mucus microbiomes. The next steps to further understand the role of bacterial communities in skin and mucus of elasmobranchs require functional metagenomics and metabolomics analyses to unveil the role of these bacteria. Conclusions Figure <ns0:ref type='figure' target='#fig_9'>5</ns0:ref>. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure <ns0:ref type='figure' target='#fig_10'>6</ns0:ref>. Bray-Curtis dissimilarity index calculated for order for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure <ns0:ref type='figure'>7</ns0:ref>. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>. Bacterial order composition found in each sample successfully amplified in this Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 7</ns0:note><ns0:p>Principal component analysis (PCA) Figure <ns0:ref type='figure'>7</ns0:ref>. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2).</ns0:p><ns0:p>PeerJ reviewing PDF | (2018:07:29887:3:0:NEW 16 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type.Figure 3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.Figure5. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure6. Bray-Curtis dissimilarity index calculated for order for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure7. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure1. Bacterial order composition found in each sample successfully amplified in this study. SupplementaryFigure 2. Number of OTUs grouped and their frequency. Supplementary Figure 3. Faith's phylogenetic diversity index. Growth rate of the Faiths pd in place of standard rarefaction curve, showing fast increase of diversity with sequencing depth per sample (N#).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type.Figure 3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.Figure5. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure6. Bray-Curtis dissimilarity index calculated for order for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure7. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure1. Bacterial order composition found in each sample successfully amplified in this study. SupplementaryFigure 2. Number of OTUs grouped and their frequency. Supplementary Figure 3. Faith's phylogenetic diversity index. Growth rate of the Faiths pd in place of standard rarefaction curve, showing fast increase of diversity with sequencing depth per sample (N#).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type.Figure 3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.Figure5. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (for order) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure6. Bray-Curtis dissimilarity index calculated for order for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure7. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure1. Bacterial order composition found in each sample successfully amplified in this study. SupplementaryFigure 2. Number of OTUs grouped and their frequency. Supplementary Figure 3. Faith's phylogenetic diversity index. Growth rate of the Faiths pd in place of standard rarefaction curve, showing fast increase of diversity with sequencing depth per sample (N#).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 2 .Figure 3 Figure 3 .</ns0:head><ns0:label>233</ns0:label><ns0:figDesc>Figure 2. Orders shared</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. Alpha diversity of OTUs</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 5 Bray-</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 6 Bray-</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2018:07:29887:3:0:NEW 16 Jun 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2018:07:29887:3:0:NEW 16 Jun 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Reply to reviewers: Reviewer 1: We would really like to thank reviewer 1 for her thorough suggestions and comments and for keeping that positive attitude to help us through this process. We were able finally to do the alpha diversity analyses using OTUs and I think this time we got the rarefaction curve done in the correct way. I am really sorry for being so slow, we really had to train more on our bioinformatics, but I think this time we got it (Hopefully!). R/Line 499: Bioinformatics method – in your results you have the numbers of reads and how many remained after QC. Please add to this section. A lot of reads didn’t pass the QC. Mothur should tell you how many samples remain after each QC step and chimera removal please include if possible. A/We carefully redid the steps of the QC and how many reads we kept for the OUT analyses and how many were finally assigned taxonomically. We were careful to explain this in more detail new additions to the methodology (lines 139 to 162). We also included more detail in the results (lines 187 to 197) R/Comment in the discussion about the high error rate and relate to the literature on the platform and other studies. I believe these primers (Caporaso) when used for salmon pick up a lot of host DNA and so have a high error rate so could you comment on the source of the read loss (ie chimeras, read length, host DNA contamination etc). We included this in the discussion and now reads: “In general, there were few taxonomically identified sequences compared to the total (only 16.9 % of the total reads) and as compared to OTUs grouped (82% of the total reads), This may be the result of the shorter length of the sequences, the kits used in sequencing (to make libraries of short sequences), and differences in the DNA concentration at the start of the amplification and library preparation processes (Solonenko et al., 2013). Also, it has been suggested that the primers used in this study may amplify DNA from the host species (eukaryotic DNA), which would then reduce the total number of microbial reads that would have been included in our analysis (Parada et al., 2016).” (lines 274-281). R/Recommended revision: Sentences in discussion discussing error rate where you already discuss low % of assigned species. More detail on QC. A/See above A/I don’t agree with having diversity measures to order level I think it is too high. In the previous version there was inconsistency between figures and text showing different levels so understandably choosing one level is easiest and is clearer, but for these analyses the standard is OTU-level or genus maybe family-level. For example, in the results it is stated ‘Alpha-diversity was similar among species and among types of samples’ I’m highlighting this as I think that is likely you are just not looking deep enough and missing something interesting in your study. Unfortunately, many of your reads did not assign at genus/family level. As you state only 16% of your reads were assigned taxanomically. Recommended revision: Test alpha-diversity at OTU level. R/ we re-run the alpha diversity analyses using OTUs instead of order or family. The results were still the same but we definitely had more depth in the analyses. We explain this in the methodology (Lines 164 to 168). We also included a new Figure 4 with these results and in the results section, we explain these results (lines 225-227). We discuss about our results (no significant differences) in the discussion section (lines 285-290). R/The rarefaction results I would like to see at read-level to see the variation per group but also per sample. Especially given how many reads were removed through QC. From reading the manuscipt there’s no way of knowing if this is even per sample. The rarefaction at this level is crucial here. In fact you mention ‘samples having 10 times the number of different orders found in other samples from the same type. Something similar was found for the samples from each species, meaning that there was high heterogeneity in samples used in this study (rarefaction curves for each species and sample type’ Supplementary Figure 2) Recommended revision: Rarefaction curve with reads after QC or OTU level per sample. A/We ran the rarefaction curve at OUT level, by sample, This is now on Supplementary Figure 3. Other comments: Line 9: Remove ‘is considered’, remove sensentence from partlly (as you go on to say the same thing in the next sentence). DONE Line 334: change ‘place where each individual was captured’ to ‘sampling location of each individual’. CHANGED Line 349: Ion torrent method – were samples pooled to equimolar concentrations? Perhaps add more briefbut relevant details from the stated protocols. CHANGED Line 519: What R version? INCLUDED Line 572: Keep sentence with how many OTUs found (is this 22,803?) and then how many taxonomically asigned remove the first part and put into methods as described above. INCLUDED; See above Figures: R/Figure 1: I think Figure 1 and Figure 2b can go in supplements as one figure. Recommended new figure 1a and b: A) Number of shared OTUs per sample type. I think this will be interesting as it tells us about the 84% of the community not tax assigned. Then Figure 2b) Number of shared orders per sample type. A/ we decided to keep our Figrues 1 and 2, but we included how many OTUs were assigned and in which frequency as Supplementary Figure 2 R/Figure 5 should go to supplements as it is not needed. And the shark species cover parts of the plot the reader will want to see. See recommendation above for rarefaction curve. A/This was changed, explained in the text above R/Supplementary Figure 3: Labels on plot hard to read consider removing. Image resolution quality may need to be improved for publication R/ Improved Comments for the Author R/ Both in the Abstract and Introduction authors speak about the behaviour of sharks during copulation, and the risk of infections. However, there is no discussion at all about the implications of the results obtained in this situation. A/ This suggestion was included in the discussion, lines 428-429. We also talk about the implication on lines 429-436. L21 and so on: If you decided to keep only the results on Orders, do not include the Genera. R/We were clearer on why we used orders. L23-24: There is an error in the redaction of the sentences: “Bacillales, However…” There is no sense. R/Clarified L24-28: Please rewrite those results since it is not clear what you mean. R/Improved L107: 90 % and 4 ºC, and be consistent all along the manuscript. R/Changed L196: Remove “and” after 28. R/Removed L238: due to a… R/changed L231: Add: “or fish in general” R/Included L410: Remove “and” R/Removed Fig. 8: were due to a… R/Improved "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>However, the role of skin mucus in protecting fish against pathogens is not well understood. During copulation in sharks, the male bites the female generating wounds, which are then highly likely to become infected by opportunistic bacteria from the water or from the male shark's mouth. Describing the microbial component of epithelial mucus may allow future understanding of this first line of defense in sharks. In this study, we analyzed mucus and skin samples obtained from 19 individuals of two shark species and a stingray: the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus). Total DNA was extracted from all samples, and the bacterial 16S rRNA gene (region V3-V4) was amplified and sequenced on the Ion Torrent Platform (amplicon sequencing). Bacterial diversity (order) was higher in skin and mucus than in water. Order composition was more similar between the two shark species.</ns0:p><ns0:p>Alpha-diversities (Shannon and Simpson) for OTUs (clusters of sequencesdefinedby a 97% identity threshold for the16S rRNA gene) were high and there were non-significant differences between elasmobranch species or types of samples. We found orders of potentially pathogenic bacteria in water samples collected from the area where the animals were found, such as Pasteurellales (i.e. genus Pasteurella spp. and Haemophilus spp.) and Oceanospirillales (i.e. genus Halomonas spp.) but these were not found in the skin or mucus samples from any species. Some bacterial orders, such as Flavobacteriales, Vibrionales (i.e. genus Pseudoalteromonas), Lactobacillales and Bacillales were found only in mucus and skin samples. However, in a co-occurrence analyses, no significant relationship was found among these orders (strength less than 0.6, p-value &gt; 0.01) but significant relationships were found among the order Trembayales, previously described as endosymbionts of insects, Fusobacteriales, previously described in the human gut, and some previously described marine environmental Bacteria and Archaea, including Elusimicrobiales, Thermoproteales, Deinococcales and Desulfarculales. This is, to our</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The first barrier of protection against microorganisms in fish is the mucosal immune system <ns0:ref type='bibr' target='#b26'>(Cone, 2009)</ns0:ref>. This system protects fish physically, chemically, and biologically from threats or pathogens found in their habitat <ns0:ref type='bibr' target='#b74'>(Subramanian, MacKinnon &amp; Ross, 2007;</ns0:ref><ns0:ref type='bibr'>Subramanian, Ross &amp; Mackinnon, 2008;</ns0:ref><ns0:ref type='bibr' target='#b65'>Raj et al., 2011)</ns0:ref>. The mucosal immune system is subdivided into three subgroups that correspond to the locations where the mucus is secreted: the gut, the gills and the skin <ns0:ref type='bibr' target='#b67'>(Salinas, Zhang &amp; Sunyer, 2011)</ns0:ref>. Some studies suggest that this mucus is constantly renewed, reducing the pathogenic load found on the surface of the fish <ns0:ref type='bibr' target='#b53'>(Nagashima et al., 2003)</ns0:ref>. The mucus is secreted in higher quantities as a response to threat <ns0:ref type='bibr' target='#b51'>(Mittal &amp; Datta Munshi, 1974;</ns0:ref><ns0:ref type='bibr' target='#b33'>Gostin, Neagu &amp; Vulpe, 2011;</ns0:ref><ns0:ref type='bibr' target='#b64'>Rai et al., 2012)</ns0:ref>, and the viscose substance consists of molecules that may help in healing and protecting the skin <ns0:ref type='bibr' target='#b18'>(Cameron &amp; Endean, 1973;</ns0:ref><ns0:ref type='bibr' target='#b3'>Al-Hassan et al., 1985)</ns0:ref>, including the secretion of antimicrobial and regenerative substances <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. The epithelial mucus is sometimes considered an ideal surface for bacterial adhesion. In fact, the accumulation of microorganisms appears to take place during the lifetime of the individual <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, leading to the establishment of the microbiota in fish skin. However, it is also recognized that the mucus has a concentration of molecules that prevent the adhesion of pathogenic bacteria (Crouse-Eisnor, <ns0:ref type='bibr' target='#b28'>Cone &amp; Odense, 1985)</ns0:ref>. As such, the role or the relationship between the mucus and environmental bacteria is not clear <ns0:ref type='bibr' target='#b47'>(Luer, 2012)</ns0:ref>. It has been suggested that bacteria found in this layer may play three possible roles <ns0:ref type='bibr' target='#b68'>(Salminen et al., 2010)</ns0:ref>: a) bacteria may stimulate mucus and antimicrobial compound production, b) bacteria may activate and help modulate the immune response in the fish, and c) the interaction between different types of bacteria may actively exclude or compete with potentially pathogenic bacteria. The mucus layer in sharks and rays has been poorly studied. However, it is known that mucus from stingray skin appear to accelerate the healing processes of wounds, and that bacteria found in the mucus present antibacterial activity against human pathogens <ns0:ref type='bibr' target='#b48'>(Luer et al., 2014)</ns0:ref>. Also, it has been found recently that the structure, geometry and arrangement of dermal denticles of the shark skin play an important role in allowing bacterial attachment and development of biofilms <ns0:ref type='bibr' target='#b23'>(Chien et al. 2020)</ns0:ref>. Reproductive behavior in this group is characterized by aggressiveness during courtship and copulation <ns0:ref type='bibr' target='#b59'>(Pratt &amp; Carrier, 2001;</ns0:ref><ns0:ref type='bibr' target='#b21'>Carrier, Pratt &amp; Martin, 2015)</ns0:ref>. In sharks, the male bites the female on her dorsal or pectoral fins generating wounds in those areas <ns0:ref type='bibr' target='#b59'>(Pratt &amp; Carrier, 2001)</ns0:ref>. Polyandry, a mating system in which one female mates with multiple males, is very common in some species <ns0:ref type='bibr' target='#b69'>(Saville et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b19'>Carrier et al., 2003)</ns0:ref>. This behavior drives competition between males and avoidance in females <ns0:ref type='bibr' target='#b41'>(Klimley, 1980;</ns0:ref><ns0:ref type='bibr' target='#b32'>Gordon, 1993;</ns0:ref><ns0:ref type='bibr' target='#b59'>Pratt &amp; Carrier, 2001)</ns0:ref>. There are also morphological characteristics related to this trait. Sexual dimorphism occurs in shark species in which the male&#180;s teeth are shaped so they can easily grab the female in order to remain close to her while mating. Females have thicker dermal denticles (tooth-like structures that provide hydrodynamics and protection) than males as protection against these bites <ns0:ref type='bibr' target='#b20'>(Carrier, Musick &amp; Heithaus, 2012)</ns0:ref>. In the case of rays, the females prick the male with their caudal spine <ns0:ref type='bibr' target='#b59'>(Pratt &amp; Carrier, 2001)</ns0:ref>. It has been shown in some stingray species that when many males are involved in mating, a few may die in the process <ns0:ref type='bibr' target='#b31'>(Gilad et al., 2008)</ns0:ref>. In spite of these apparently aggressive behaviors, copulation is necessary and the wounds provoked are highly likely to become infected <ns0:ref type='bibr' target='#b29'>(Daly-Engel et al., 2010)</ns0:ref> due to opportunistic bacteria in the water and in the oral cavity of males. Because of the high concentration of pathogenic microorganisms found in the aquatic environment <ns0:ref type='bibr' target='#b49'>(Magnadottir, 2010)</ns0:ref>, it is important to determine the microbiota component of the epithelial mucus, the skin, and to understand whether the bacteria found in these are similar or different from those found in the water surrounding the animals. This will help to understand the role of mucus in the protection against pathogens. In this study, we characterized the bacterial diversity in the epithelial mucus in three elasmobranch species, the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus) <ns0:ref type='bibr' target='#b46'>(Last et al., 2016)</ns0:ref>. We also hypothesize about the possible role of some of the bacteria found in the mucus and in the skin.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sample collection</ns0:head><ns0:p>Mucus and skin tissue samples were collected from 19 apparently healthy individuals (no visible wounds, normal swimming activity); 14 of them from animals captured in Bimini, Bahamas (25&#61616;43&#61602;59 N, 79&#61616;14&#61602;60 W): four corresponded to juvenile nurse sharks (Ginglymostoma cirratum), six to juvenile lemon sharks (Negaprion brevirostris), and four to adult southern stingrays (Hypanus americanus). Samples from an additional five adult nurse sharks were collected at Oceanario from Islas del Rosario (CEINER), in the Colombian Caribbean (10&#61616;10&#61602;30 N, 75&#61616;45&#61602;00 W). For each individual, we obtained a sample of skin tissue and mucus, following sampling protocols approved by the Animal Care Committee of Universidad de los Andes (CICUAL) (Bogota, Colombia). The skin tissue sample was cut, using a sterile blade for each specimen, from the posterior part of the dorsal fin (1 cm 3 or less) and the mucus from the skin surface, using a sterile 1.5 ml microcentrifuge tube to scrape the skin surface, ideally filling at least half of the tube. Animals were manipulated for approximately 5 minutes and immediately released. A water sample was also collected in sterile 15 ml tube from the sampling location of each individual. Thus, three samples were associated with each individual, for a total of 57 samples. The individuals were captured and raised slightly above the surface of the water, so that the samples could be taken outside the water, while the animal could continue breathing. Skin samples were preserved in ethanol 90%. All samples were maintained at 4 &#186;C for less than one week, until processing. DNA Extraction and PCR amplification DNA was extracted from the entire sample collected for all samples. The Tissue and Cells DNA Isolation Kit (MoBio Laboratories, Inc.) was used, following the manufacturer instructions. Water samples were filtered through a 0.8 &#61549;m cellulose nitrate filter before DNA extraction. The primers 515f and 806r were used in order to amplify the region V4 from the bacterial and archaea 16S rRNA gene using the primers 515F (5&#180;-GTGCCAGCMGCCGCGGTAA-3&#180;) and 806R (5&#180;GGACTAHVGGGTWTCTAAT-3&#180;) <ns0:ref type='bibr' target='#b17'>(Caporaso et al., 2010)</ns0:ref>. PCR amplification conditions were as follows: an initial denaturation at 94 &#176;C for 3 minutes, followed by 35 cycles of denaturing at 94 &#176;C for 45 seconds, annealing for 45 seconds at 50 &#176;C and extension for 45 seconds at 72 &#176;C, followed by a final extension of 20 minutes at 72 &#176;C. Successful amplification was confirmed on 1 % agarose gel.</ns0:p></ns0:div> <ns0:div><ns0:head>Ion torrent library preparation, quantification and sequencing</ns0:head><ns0:p>From the 57 samples, 32 were used to construct libraries (Supplementary Table <ns0:ref type='table'>1</ns0:ref>). Samples were chosen depending on their final DNA concentration, once the PCR products were cleaned using magnetic beads and run on a 1.5% agarose gel. Only the samples that had a clear strong band were used for library construction. Two libraries, each with 16 barcodes, were prepared using the protocol Ion Xpress&#8482; Plus gDNA Fragment Library Preparation (Life Technologies). Libraries were quantified with the Qubit kit. Templates were prepared following the Ion PGM&#8482; Template OT2 200 Kit (Life Technologies) protocols. Libraries were prepared for sequencing using the protocol Ion PGM&#8482; Sequencing 200 Kit v2 (Life Technologies). Libraries were pooled to equimolar concentration and loaded on two Ion 316 chips and sequenced in the Ion Torrent PGM (Life Technologies). 16S datasets used in this manuscript with accompanying metadata has been submitted to Dryad as DOI https://doi.org/105061/dryad.b5mkkwh8j Bioinformatic and statistical analyses Sequences were separated by barcodes directly by the Ion Torrent PGM and saved by the ion reporter in different files; sequence quality was analyzed using FastQC <ns0:ref type='bibr' target='#b5'>(Andrews, 2014)</ns0:ref>. The file format was changed from Fastq to Fasta. Demultiplexing was conducted by comparing the mapping file of the chip with the files containing the sequences. For the core diversity analysis, Qiime2 <ns0:ref type='bibr'>(Bolyen et al. 2019)</ns0:ref> was used via command line using the moving pictures tutorial as reference. The files were imported as 'MultiplexedSingleEndBarcodeInSequence' and demultiplexed using 'cutadapt', eliminating sequences shorter than 50 bp. The sequences went through DADA2 <ns0:ref type='bibr' target='#b16'>(Callahan et al. 2016)</ns0:ref> for quality control to delete sequences with lower qscore than 20 and then the remaining sequences were aligned de novo with align-to-tree-mafftfastree. In parallel, the sequences were clustered into OTUs used to perform non phylogenetic analysis. The rooted tree obtained with fasttree2 <ns0:ref type='bibr' target='#b61'>(Price et al. 2010)</ns0:ref> was used to perform an alpha rarefaction with a 1000 sequence depth. For taxonomic assignment, analyses were performed on the Galaxy online platform <ns0:ref type='bibr' target='#b1'>(Afgan et al. 2016)</ns0:ref> following one amplicon data workflow on Mothur v.1.28.0 <ns0:ref type='bibr' target='#b70'>(Schloss et al., 2009)</ns0:ref>. This workflow started by merging all read files into group files. Group files were identified as samples from each of the three elasmobranch species and also as type of sample (skin, mucus or water). The next step of the workflow identified unique sequences and generated a file with these sequences and a second file in which the number of each unique representative sequence was kept. Following this, reads were filtered based on quality and length. Parameters to remove low quality sequences (quality control) was for those with less than 20 Phred score and shorter than 50 bp. (minimum length) followed by a step to remove poorly aligned sequences and chimeric sequences. Finally, reads were clustered based on their degree of similarity, with a minimum of 97% identity threshold and aligned to the Silva V4 reference database <ns0:ref type='bibr' target='#b62'>(Quast et al., 2013)</ns0:ref>, followed by a classification step into taxonomic categories (order, family, genus and species when possible). Rstudio version 1.1.463 (R Development Core Team, 2010) was used <ns0:ref type='bibr' target='#b82'>(Wickham, 2009)</ns0:ref> for alpha (&#61537;) diversity analyses (Simpson and Shannon) (package Vegan) <ns0:ref type='bibr' target='#b55'>(Oksanen et al. 2015)</ns0:ref> which were conducted for OTUs, using the number of OTUs per sample, comparing among species (N. brevirostris, G. cirratum juveniles and adults and H. americanus) and among sample types (tissue, mucus and water). A Shapiro-Wilk normality test was conducted to evaluate normality among samples belonging to each elasmobranch species (Supplementary Table <ns0:ref type='table'>1</ns0:ref>), including the additional category of adults and juvenile for nurse sharks, or to each category of sample type before performing any statistical tests. Since results fell outside the normality assumption, a Kruskal-Wallis test was used to evaluate whether &#61537; diversity was significantly different among elasmobranch species or among sample type. To estimate beta (&#61538;) diversity (Bray-Curtis dissimilarity index and a Principal Component Analysis (PCA) the taxonomic category 'order' was used. Venn diagrams (package DVenn) were used to visualize shared orders among elasmobranch species and among sample types. In order to find co-occurrence between different bacterial and/or Archaea orders a correlation matrix was created in R using the Spearman&#180;s co-efficient as in <ns0:ref type='bibr' target='#b39'>Ju et al (2013)</ns0:ref>. Correlations had to be stronger than 0.6 with a p-value &lt; 0.01 to be considered to have a significant co-occurrence with other orders. All orders, including those with less than 0.2% presence were included in the co-ocurrence analysis. A chord plot was created to visualize the relations between the different orders.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The 32 samples used to build the libraries included a mucus or tissue sample for each of the individuals sampled and only four of the 19 samples from water (Supplementary Table <ns0:ref type='table'>1</ns0:ref>). The other samples, including 15 water samples, had low DNA concentrations that could not be used for NGS sequencing analysis, characterized by weak or no bands amplified. A total of 219,162 reads were obtained from the Ion Torrent PGM of which 55,642 were used for subsequent analyses following demultiplexing. After read quality control and chimera removal, 21,530 reads were used in the following steps for Qiime2 and in the Mothur workflow. Of these, 17,685 were grouped as unique OTUs in Qiime2 (most of them represented each by only one read, Supplementary Figure <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>) (82% total reads). In Mothur, 3,639 (16.9 % total reads) were assigned taxonomically against the SilvaV4 database while 19,164 were left unassigned (84% total reads); sequences assigned taxonomically belonged to 18 mucus, 10 skin and 4 water samples. A total of 25 phyla, 81 orders, 76 families and 33 genera were assigned (Figure <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>), but analyses were restricted to OTUs and to the taxonomic category 'order', since this was the category with higher levels of taxonomic assignments. Most reads were identified as belonging to the kingdom Bacteria (Supplementary Table <ns0:ref type='table'>2</ns0:ref>). Occurrence of reads belonging to the kingdom Archaea was low (&lt; 2%) and these were only found in one mucus sample from one nurse shark. Among the Archaea, the orders identified were Micrarchaeles, Cenarchaeales, Halobacteriales, and Methanobacteriales. Thirty-seven orders were shared between samples from the three elasmobranch species and the water samples, and 17 were solely found in elasmobranch samples. Twenty-seven orders were found only in the water samples (Figure <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>). Fifty-four were shared among all elasmobranch species, 28 were shared between the nurse shark and the lemon shark, and 25 were shared between the two shark species and the southern stingray (Figure <ns0:ref type='figure' target='#fig_4'>2a</ns0:ref>). Fortyfive orders were shared between all sample types (water, mucus and skin), 47 were shared between mucus and skin, and less than 20 were shared between tissue or mucus and water samples (Figure <ns0:ref type='figure' target='#fig_4'>2b</ns0:ref>). Also, among elasmobranch species and types of samples, similar orders were found in every sample and with a similar distribution (Figure <ns0:ref type='figure'>3a and 3b</ns0:ref>). The highest abundance was of the order Actinomycetales and the family Nocardiaceae (i.e.genus Rhodococcus), with a slightly greater abundance of reads obtained from the lemon shark and less abundance for reads obtained from the southern stingray. Mucus and skin samples had a higher number of reads than water samples (Supplementary Figure <ns0:ref type='figure' target='#fig_1'>2</ns0:ref>). Phylogenetic diversity was used to build a rarefaction curve, following a phylogenetic aligned tree method, as it allowed a better visualization of data since most rarefaction curves were too similar to be distinguished. However, this methodology allowed clearer observation of the high heterogeneity found in samples used in this study, with some samples having much a higher number of total reads than others. Also, it showed that most if not all the samples did not reach an asymptote as showed in Supplementary Figure <ns0:ref type='figure'>3</ns0:ref>. For OTUs, Alpha-diversity was similar among species and among types of samples (Table <ns0:ref type='table'>1a and 1b</ns0:ref>). Alpha-diversity was non significantly different among species or among type of samples (Figure <ns0:ref type='figure' target='#fig_8'>4a, 4b, 4c and 4d</ns0:ref>). Using the taxonomic category 'order', the Bray-Curtis dissimilarity index, used as a &#61538; diversity estimate, revealed greater dissimilarity (0.45) between the microbiome communities found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the skin and mucus of the lemon shark and nurse shark (Figure <ns0:ref type='figure' target='#fig_9'>5</ns0:ref>). When each sample was used to calculate the Bray-Curtis dissimilarity index, patterns of bacterial community dissimilarity were less clear, but it appears that mucus and skin samples from sharks and the southern stingray were less dissimilar from each other than when compared with the water samples (Figure <ns0:ref type='figure' target='#fig_10'>6</ns0:ref>). The percentage for each order identified from the total reads (sequences) obtained for each sample and analyzed is shown in Supplementary Table <ns0:ref type='table'>2</ns0:ref> and Supplementary Figure <ns0:ref type='figure' target='#fig_1'>2</ns0:ref>. Few sequences were assigned to the species or genus levels. Most of them were assigned to higher taxonomic levels (order). However, among the genus and species identified, several reported bacterial fish pathogens, symbionts and commensals were found in the mucus, tissue, and water samples (Supplementary Table <ns0:ref type='table'>2 and Supplementary Table 4</ns0:ref>). It is interesting to note that some fish pathogens were only found in the water and not in the mucus/tissue samples, such as the order Pastereullales (i. e. Pasteurella spp., Haemophilus spp) and Oceanospirillales (i.e. Halomonas spp.) The PCA showed higher similarity between the bacterial orders found in the skin and mucus of the two shark species in comparison with those in the southern stingray. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2) (Figure <ns0:ref type='figure'>7</ns0:ref>). In the PCA separating adults and juvenile nurse sharks, no clear differentiation patterns between microbiome community composition were detected at this time (Supplementary Figure <ns0:ref type='figure' target='#fig_6'>4</ns0:ref>). The co-occurrence analysis plot showed 104 out of all 202 recognized orders (including orders with less than 0.2% presence) (Supplementary Figure <ns0:ref type='figure' target='#fig_9'>5</ns0:ref>). Most of the correlations were between candidate orders, however orders such as Chlorobiales, Deinococcales Trembayales, Thermoproteales, Desulfarculales and Furobacteriales showed strong co-occurrence. Orders such as Actinomycetales and Bacteroidales, highly influential in the principal coordinate analysis, where not found in the co-occurrence analyses plot.</ns0:p><ns0:p>PeerJ reviewing PDF | (2018:07:29887:4:0:NEW 16 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed Discussion This study provides initial but useful baseline information on microbiome communities in elasmobranch species from which changes in microbiome communities over time and under changing conditions can be evaluated. Nevertheless, depending on the characteristics and populations of these animals, the composition and role of the whole microbiome may vary. From a conservation perspective, knowledge of the microbiome composition and function may be an important approach for understanding how these organisms may be affected in the long term by environmental change; for example, climate change or ocean acidification <ns0:ref type='bibr' target='#b8'>(Bahrndorff et al., 2016)</ns0:ref>. In general, there were few taxonomically identified sequences compared to the total (only 16.9 % of the total reads) and as compared to OTUs grouped (82% of the total reads). This may be the result of the shorter length of the sequences, the kits used in sequencing (to make libraries of short sequences), and differences in the DNA concentration at the start of the amplification and library preparation processes <ns0:ref type='bibr' target='#b72'>(Solonenko et al., 2013)</ns0:ref>. Also, it has been suggested that the primers used in this study may amplify DNA from the host species (eukaryotic DNA), which would then reduce the total number of microbial reads that would have been included in our analysis <ns0:ref type='bibr' target='#b58'>(Parada et al., 2016)</ns0:ref>. However, our results are relevant to understand the microbiome communities in elasmobranch fish and they suggest that skin tissue and mucus microbiomes of the three elasmobranch species were similar in composition. Also, although some orders were shared with the water samples, more of them were shared between the two shark species and to a lesser extent with the southern stingray. Alpha-diversity at OTU level was similar among samples from the three species and among types of samples. However, there was high variation in the Alphadiversity among samples within each species or within each sample type, which was confirmed by the rarefaction curve ran for all samples included in the study. This could be related with different number of reads obtained per sample, since alpha diversity indices can be sensitive to differences in sample sizes <ns0:ref type='bibr' target='#b9'>(Barrantes &amp; Sandoval, 2009)</ns0:ref>. This could have been caused by the storage conditions of some samples or due to the loss of DNA from some samples during the different steps of library preparation. Also, selective PCR amplification could generate higher amplification of some bacteria and not others. The richness of species was higher in mucus samples and in lemon shark samples. Composition of mucus samples and skin samples from sharks tended to be more similar to each other than to the southern stingray or the water samples. In this study, the bacterial diversity in the mucus and tissue included a wide range of orders, that have been described as pathogens, non-pathogens, and some that have scarcely been studied in relation to potential or confirmed hosts. Most orders identified belonged to the kingdom Bacteria, with a very small proportion of Archaea. However, some of the Archaea identified in a mucus sample belonging to a nurse shark included Cenarchaeales, which have been found to be symbionts of one marine sponge that lives at very low temperatures <ns0:ref type='bibr' target='#b60'>(Preston et al., 1996)</ns0:ref>. Interestingly, a high proportion of Actinomycetales (i.e. genus Rhodococcus) were found in mucus and tissue samples and influenced the community composition of all our samples, as showed in the PCA. Although Actinomycetales can be found in environmental samples from soil and water, strains have been isolated from marine environments and produce antimicrobial compounds against pathogenic bacterial and fungus, particularly against some pathogenic strains of E. coli and Pseudomonas sp. <ns0:ref type='bibr' target='#b83'>(Yellamanda et al., 2016)</ns0:ref>. The phylum Actinobacteria, to which the order Actinomycetales belongs, has also been found in the skin microbiota of bony fish (Osteichthyes) <ns0:ref type='bibr' target='#b45'>(Larsen et al., 2013)</ns0:ref>. Although we focused our analysis on microbiome community diversity and composition of the orders identified, we also investigated their characteristics and those of the genera within each order because, although a smaller number of reads were identified to the genus level, some interesting data was obtained. Within the bacterial order and genera found only in water samples, three have been described as pathogens for fish, including the order Pasteurellales (genus Pasteurella spp. and Haemophilus spp.) and of the order Oceanospirillales (genus Halomonas spp.) <ns0:ref type='bibr' target='#b15'>(Bullock, 1961;</ns0:ref><ns0:ref type='bibr' target='#b38'>Hawke et al., 1987;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. There was also a species only found in water samples, Acinetobacter johnsonii (order Pseudomonadales), which has been described as a fish pathogen <ns0:ref type='bibr' target='#b42'>(Kozi&#324;ska et al., 2014)</ns0:ref>. Other sequenced bacteria present in the results of water samples, such as Moraxella sp., are opportunistic bacteria and have been found in other animals, for example in mammals <ns0:ref type='bibr' target='#b81'>(Whitman, 2015)</ns0:ref>. Some orders found only in the elasmobranch samples may also play a role as pathogens. The order Alteromonadales (i.e. genera Alteromonas, Shewanella) <ns0:ref type='bibr' target='#b12'>(Boone &amp; Bryant, 1980)</ns0:ref>, Actinomycetales (i.e. genera Mycobacterium and Nocardia), Bacillales (i.e. Staphylococcus) and Flavobacteriales (i.e. Chryseobacterium) have been reported as pathogens for various fish species <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. The order Syntrophobacterales (i.e. genus Syntrophobacter) was also present in mucus and skin samples and considered a possible pathogen for fish, due to the fact that bacteria that belong to this group, degrade propionate, a corticoid used in healing skin <ns0:ref type='bibr' target='#b71'>(Schulze et al., 2006)</ns0:ref>. However, many other Flavobacteriales (i.e. Flavobacterium), Vibrionales (i.e. Pseudoalteromonas), Lactobacillales (i.e. Lactobacillus) and Bacillales (i.e. Bacillus), also found only in elasmobranch samples, are considered symbionts of marine fish <ns0:ref type='bibr' target='#b4'>(Anand et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b48'>Luer et al., 2014)</ns0:ref>. Some species of Flavobacterium have been studied as commensal to fish, and have shown antimicrobial activity against fish pathogens from the genus Vibrio <ns0:ref type='bibr' target='#b44'>(Lal &amp; Tabacchioni, 2009)</ns0:ref>. Bacillus polymyxa, found in mucus and skin samples in this study, has been isolated from fish guts and some strains of this species synthesize antibiotics <ns0:ref type='bibr' target='#b56'>(Olmos, 2014)</ns0:ref>. Similarly, Bacillus subtilis has been suggested as a probiotic involved in the optimization of fish feeding <ns0:ref type='bibr' target='#b50'>(Merrifield &amp; Rodiles, 2015)</ns0:ref>. Finally, various orders sequenced from mucus and skin samples are considered normal biota of fish gills or skin (i.e., Xanthomonadales, Caulobacteriales) <ns0:ref type='bibr' target='#b77'>(Sugita et al., 1996)</ns0:ref>. However, it is important to remember that pathogenicity may be related to particular strains <ns0:ref type='bibr' target='#b30'>(Fitzgerald &amp; Musser, 2001</ns0:ref>) so caution is needed in the interpretation of these results. For example, three orders genera found in mucus and tissue samples Lactobacillales (i.e. Streptococcus and Enterococcus), Pseudomonadales (i.e. Pseudomonas) and Vibrionales (i.e. Vibrio) are sometimes reported as pathogens and sometimes reported as symbionts. For example, S. parauberis produces streptococcosis in some fish <ns0:ref type='bibr' target='#b6'>(Austin, 2005;</ns0:ref><ns0:ref type='bibr' target='#b54'>Nho et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but other Streptococcus spp. inhibit the growth of pathogenic bacteria <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Similarly, Pseudomonas putrefaciens acts as a pathogen for fish <ns0:ref type='bibr' target='#b0'>(Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but P. fluorescens inhibits growth of pathogens <ns0:ref type='bibr'>(Subramanian, Ross &amp; MacKinnon, 2008)</ns0:ref> and has been isolated from healthy salmon eggs and mucus <ns0:ref type='bibr' target='#b25'>(Cipriano &amp; Dove, 2011;</ns0:ref><ns0:ref type='bibr' target='#b2'>Akinyemi et al., 2016)</ns0:ref>. Finally, Vibrio have been reported several times as an important pathogen for marine life because of its great capacity for survival and of acclimation in its host, as it hydrolyzes urea and uses it as a source of carbon and nitrogen <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Many species have been described as infectious for Negaprion brevirostris, especially when they are physically injured <ns0:ref type='bibr' target='#b34'>(Grimes et al., 1984a;</ns0:ref><ns0:ref type='bibr' target='#b35'>Grimes, Gruber &amp; May, 1985)</ns0:ref>; others are associated to the mortality of sharks in captivity <ns0:ref type='bibr' target='#b36'>(Grimes et al., 1984b)</ns0:ref>, and others to infections caused by hooks <ns0:ref type='bibr' target='#b13'>(Borucinska et al., 2002)</ns0:ref>. There are some species that, depending on the strain, are pathogenic or not, such as V. alginolyticus and V. parahemoliticus <ns0:ref type='bibr' target='#b7'>(Austin &amp; Austin, 2007;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>. Other species, such as Vibrio alginolyticus and V. fluviales, are considered pathogenic for fish in general <ns0:ref type='bibr' target='#b85'>(Zorrilla et al., 2003)</ns0:ref>; Vibrio fortis has been reported as a sea horse pathogen <ns0:ref type='bibr' target='#b79'>(Wang et al., 2016)</ns0:ref>; Vibrio shilonii has been found to cause coral bleaching <ns0:ref type='bibr' target='#b43'>(Kushmaro et al., 2001)</ns0:ref>. There are various bacteria identified in the mucus samples that are considered in other studies as symbionts or pathogens for other animals or humans. For example, some species of the order Bacteroidales (i.e. Bacteroides) have been described as human pathogens in periodontal disease and Prevotella copri, found in mucus and skin samples have been identified as pathogens in intestinal inflammation. Additionally, bacteria from the order Clostridiales (i.e. Helcoccocus) have also been described as pathogens for humans <ns0:ref type='bibr' target='#b24'>(Chow &amp; Clarridge, 2014)</ns0:ref>. Also, many species within the order Chlamydiales are reported as pathogens for birds and mammals <ns0:ref type='bibr' target='#b81'>(Whitman, 2015)</ns0:ref>. As examples of symbiosis of species of bacteria (found in samples for this study) with humans or other animals, it is worth mentioning Lactobacillus zeae (order Lactobacillales), which has been found to serve as protective biota for nematodes <ns0:ref type='bibr' target='#b84'>(Zhou et al., 2014)</ns0:ref>; Butyrivibrio and Selenomonas (both from the order Clostridiales) are found in the gastrointestinal tract of ruminants; other members of the order Clostridiales, including Faecalibacterium prausnitzii, Peptoniphilus, Ruminococcus, Megamonas <ns0:ref type='bibr' target='#b24'>(Chow &amp; Clarridge, 2014)</ns0:ref> and Butyricimonas (from the order Bacteroidales) <ns0:ref type='bibr' target='#b80'>(Wexler, 2007)</ns0:ref> are normal important bacteria in the human gut microbiota. Other orders sequenced from mucus samples were Flavobacteriales such as Sulcia muelleri <ns0:ref type='bibr' target='#b52'>(Moran, Tran &amp; Gerardo, 2005)</ns0:ref>, Enterobacteriales such as Baumannia cicadellinicola <ns0:ref type='bibr' target='#b27'>(Cottret et al., 2010)</ns0:ref> and Trembayales such as Carsonella ruddii <ns0:ref type='bibr' target='#b78'>(Thao et al., 2000)</ns0:ref>, which have been described in symbiotic association with insects. A very interesting case is the order Burkholderiales (i.e. Janthinobacterium lividum), which has been found in the skin of some amphibians and appears to prevent infection by Batrachochytrium dendrobatidis <ns0:ref type='bibr' target='#b14'>(Brucker et al., 2008)</ns0:ref>. These are startling examples that may be related to the findings of this study; however, more in-depth research should be conducted to identify the pathogenicity or symbiosis properties specifically in elasmobranch or fish. Results from the co-occurrence analysis presented some interesting results but not clear patterns related to the PCA results or to other previously presented analyses. Strong co-occurences were found among orders such as Elusimicrobiales, Halanaenobiales, Synachococcales, Solibacterales which are defined as marine environmental bacteria, including some desulfurating bacteria, such as Desulfarculales, but also with bacterial order characterized by their presence in extreme habitats, such as Thermobaculales and Thermoproteales. This could suggest that either these are random co-occurrences among environmental bacteria that may be contaminants to the mucus and skin samples or that desulfuration may be an important metabolic path used by bacteria in these microbiome communities. Further research on this idea may be warranted. Interestingly, Fusobacteriales, a bacterial order which has been previously found in the human gut <ns0:ref type='bibr' target='#b73'>(Suau et al., 2001)</ns0:ref>, as well as Trembayales, an order of bacteria found to be endosymbionts of insects <ns0:ref type='bibr' target='#b78'>(Thao et al., 2000)</ns0:ref>, were also found in the co-occurrence analyses, suggesting a possibly relevant role in the skin and mucus microbiome communities of elasmobranch. According to this study, the role of the mucus and the bacteria associated to it may depend on numerous variables, including the virulence and pathogenicity of each microorganism <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Opportunistic bacteria can acquire virulence determinants with environmental changes by different means, for example, by a) increasing their numbers by exploiting the higher production of mucus (glycoproteins) induced by presence of toxic substances in the water <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, by b) shifting from a non-infectious state to an infectious one through an activation caused by a physical or chemical change in the environment <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, or by c) Reaching the dermal layer to infect the host taking advantage of a degree of reduction of the defensive mucus layer, caused by the presence of abrasive substances in the surroundings of the fish <ns0:ref type='bibr' target='#b10'>(Benhamed et al., 2014)</ns0:ref>. These three opportunities for the bacteria to infect the hosts not only benefit these microorganisms but they also affect the host by reducing their physiological condition <ns0:ref type='bibr' target='#b6'>(Austin, 2005)</ns0:ref>, and may explain the finding of the reported bacterial pathogens on the skin of healthy animals. The orders considered fish pathogens found in the water samples but absent in the elasmobranch samples, allows this research to present an interesting assumption. We suggest that there may be specific antimicrobial activity in the skin environment, or partial control against infections that exists in low concentration in the mucus, but this might be also a result of the low number of samples and replicates analyzed <ns0:ref type='bibr' target='#b66'>(Rakers et al., 2010)</ns0:ref>. However, it is very likely that difficulties in sampling -for example, handling the sharks and stingrays-, prevented us from collecting a larger skin or mucus sample and that this in itself could be biasing our results. The simultaneous presence of pathogens and possible symbionts varied between samples; however, the role of each order should be verified for each of the host species considered in this analysis. According to these results, we suggest that the role of the epithelial microbiota may be considered as a first line of defense against infectious organisms but it could also be a potential threat for the injured host. This may be particularly relevant as a protective mechanism for sharks and rays that get hurt during copulation and that could otherwise die due to infected wounds. This could also depend on the whole combination of bacteria and their interaction between them in each host, as well as with the host cell and physiology, known as the 'holobiont' <ns0:ref type='bibr' target='#b22'>(Carthey et al., 2020)</ns0:ref>. As mentioned earlier, each fish may accumulate a specific community of microorganisms in its life span depending on the environments it inhabits during its development and growth <ns0:ref type='bibr' target='#b37'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. This particular accumulation and interaction between the microbiota and the host (holobiont) may also affect aspects such as survival and reproduction of the host, and may become relevant for conservation of these shark species in the near future <ns0:ref type='bibr' target='#b22'>(Carthey et al., 2020)</ns0:ref>. This study represents the first contribution to describing shark and ray skin and mucus microbiomes. The next steps to further understand the role of bacterial communities in skin and mucus of elasmobranchs require functional metagenomics and metabolomics analyses to unveil the role of these bacteria. Conclusions Figure <ns0:ref type='figure' target='#fig_9'>5</ns0:ref>. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (at order level) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure <ns0:ref type='figure' target='#fig_10'>6</ns0:ref>. Bray-Curtis dissimilarity index calculated at order level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure <ns0:ref type='figure'>7</ns0:ref>. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure <ns0:ref type='figure' target='#fig_3'>1</ns0:ref>. Bacterial order composition found in each sample successfully amplified in this Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 7</ns0:note><ns0:p>Principal component analysis (PCA) Figure <ns0:ref type='figure'>7</ns0:ref>. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2).</ns0:p><ns0:p>PeerJ reviewing PDF | (2018:07:29887:4:0:NEW 16 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type.Figure 3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.Figure5. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (at order level) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure6. Bray-Curtis dissimilarity index calculated at order level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure7. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure1. Bacterial order composition found in each sample successfully amplified in this study. SupplementaryFigure 2. Number of OTUs grouped and their frequency. Supplementary Figure 3. Faith's phylogenetic diversity index. Growth rate of the Faiths pd in place of standard rarefaction curve, showing fast increase of diversity with sequencing depth per sample (N#).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type.Figure 3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.Figure5. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (at order level) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure6. Bray-Curtis dissimilarity index calculated at order level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure7. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure1. Bacterial order composition found in each sample successfully amplified in this study. SupplementaryFigure 2. Number of OTUs grouped and their frequency. Supplementary Figure 3. Faith's phylogenetic diversity index. Growth rate of the Faiths pd in place of standard rarefaction curve, showing fast increase of diversity with sequencing depth per sample (N#).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Figure legends Figure 1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle).Figure 2. Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type.Figure 3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.Figure5. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbiome communities (at order level) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure6. Bray-Curtis dissimilarity index calculated at order level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure7. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure1. Bacterial order composition found in each sample successfully amplified in this study. SupplementaryFigure 2. Number of OTUs grouped and their frequency. Supplementary Figure 3. Faith's phylogenetic diversity index. Growth rate of the Faiths pd in place of standard rarefaction curve, showing fast increase of diversity with sequencing depth per sample (N#).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 2 .Figure 3 Figure 3 .</ns0:head><ns0:label>233</ns0:label><ns0:figDesc>Figure 2. Orders shared</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. Alpha diversity of OTUs</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 5 Bray-</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 6 Bray-</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2018:07:29887:4:0:NEW 16 Jul 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2018:07:29887:4:0:NEW 16 Jul 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Reply to reviewers Line 17: Define OTUs when you first mention in the text. R/Included Line 24 + 25: Give the P value R/included Line 155: Is that the right reference for Qiime? R/This was corrected following your suggestion and the one from the Academic Editor Line 177: Reference J Oksanen - ‎2019 for Vegan package – Vegan without all caps. R/Included and corrected Line 212: change to occurrence R/Corrected Line 340: change , to full stop R/Corrected Line 350: Within text change “Alpha-diversity for OTUs” to Alpha-diversity at OTU-level” – same for others such as order level. R/corrected Line 453: Remove startling, perhaps start the sentence from the word “More” R/shortened Line 472: Do you show that in this study? Or you mean the reference you are citing? R/We clarified, it was referring to that reference Line 410:I would perhaps move around this paragraphs – you talk about pathogens 410-456, then have a paragraph on co-occurrence then pathogens again 472-506. So perhaps move the co-occurrence to fit in above when discussing the make up of the communities. It could be shortened to add further up. R/We followed your suggestions to move the co-occurrence paragraph up. Line 844: Is it meant to be (N#). In the figure legend? R/Removed and corrected Line 819: for OTUs is mentioned twice R/Corrected Supplementary figure 3 – it’s unclear what the samples are as the reader won’t know your sample IDs. You will need to add a description to the legend. Or you can overlay a text box in powerpoint and re-save the image. R/we included the number of the samples, the species and the type of sample, following the color dot in the figure. Reviewer 3 (Anonymous) Very well written, everything is correct in this new version. I have just a suggestion. L280: Change the comma to a full stop. R/Corrected "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Skin mucus in fish is the first barrier between the organism and the environment but the role of skin mucus in protecting fish against pathogens is not well understood. During copulation in sharks, the male bites the female generating wounds, which are then highly likely to become infected by opportunistic bacteria from the water or from the male shark's mouth. Describing the microbial component of epithelial mucus may allow future understanding of this first line of defense in sharks. In this study, we analyzed mucus and skin samples obtained from 19 individuals of two shark species and a stingray: the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus). Total DNA was extracted from all samples, and the bacterial 16S rRNA gene (region V3-V4) was amplified and sequenced on the Ion Torrent Platform. Bacterial diversity (order) was higher in skin and mucus than in water.</ns0:p><ns0:p>Order composition was more similar between the two shark species. Alpha-diversities (Shannon and Simpson) for OTUs (clusters of sequences defined by a 97% identity threshold for the16S rRNA gene) were high and there were non-significant differences between elasmobranch species or types of samples. We found orders of potentially pathogenic bacteria in water samples collected from the area where the animals were found, such as Pasteurellales (i.e. genus Pasteurella spp. and Haemophilus spp.) and Oceanospirillales (i.e. genus Halomonas spp.) but these were not found in the skin or mucus samples from any species. Some bacterial orders, such as Flavobacteriales, Vibrionales (i.e. genus Pseudoalteromonas), Lactobacillales and Bacillales were found only in mucus and skin samples. However, in a co-occurrence analyses, no significant relationship was found among these orders (strength less than 0.6, p-value &gt; 0.01) but significant relationships were found among the order Trembayales, Fusobacteriales, and some previously described marine environmental Bacteria and Archaea, including Elusimicrobiales, Thermoproteales, Deinococcales and Desulfarculales. This is the first</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The first barrier of protection against microorganisms in fish is the mucosal immune system <ns0:ref type='bibr' target='#b28'>(Cone, 2009)</ns0:ref>. This system protects fish physically, chemically, and biologically from threats or pathogens found in their habitat <ns0:ref type='bibr' target='#b81'>(Subramanian, MacKinnon &amp; Ross, 2007;</ns0:ref><ns0:ref type='bibr'>Subramanian, Ross &amp; Mackinnon, 2008;</ns0:ref><ns0:ref type='bibr' target='#b69'>Raj et al., 2011)</ns0:ref>. The mucosal immune system is subdivided into three subgroups that correspond to the locations where the mucus is secreted: the gut, the gills and the skin <ns0:ref type='bibr' target='#b73'>(Salinas, Zhang &amp; Sunyer, 2011)</ns0:ref>. Some studies suggest that this mucus is constantly renewed, reducing the pathogenic load found on the surface of the fish <ns0:ref type='bibr' target='#b57'>(Nagashima et al., 2003)</ns0:ref>. The mucus is secreted in higher quantities as a response to threat <ns0:ref type='bibr' target='#b55'>(Mittal &amp; Datta Munshi, 1974;</ns0:ref><ns0:ref type='bibr' target='#b36'>Gostin, Neagu &amp; Vulpe, 2011;</ns0:ref><ns0:ref type='bibr' target='#b68'>Rai et al., 2012)</ns0:ref>, and this viscous substance consists of molecules that may help in healing and protecting the skin <ns0:ref type='bibr' target='#b20'>(Cameron &amp; Endean, 1973;</ns0:ref><ns0:ref type='bibr' target='#b3'>Al-Hassan et al., 1985)</ns0:ref>, including the secretion of antimicrobial and regenerative compounds <ns0:ref type='bibr' target='#b40'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. The epithelial mucus is sometimes considered an ideal surface for bacterial adhesion. In fact, the accumulation of microorganisms appears to take place during the lifetime of the individual <ns0:ref type='bibr' target='#b40'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, leading to the establishment of the microbiota in fish skin. However, it is also recognized that the mucus has a concentration of molecules that prevent the adhesion of pathogenic bacteria (Crouse-Eisnor, <ns0:ref type='bibr' target='#b30'>Cone &amp; Odense, 1985)</ns0:ref>. As such, the role or the relationship between the mucus and environmental bacteria is not clear <ns0:ref type='bibr' target='#b51'>(Luer, 2012)</ns0:ref>. It has been suggested that bacteria found in this layer may play three possible roles <ns0:ref type='bibr' target='#b74'>(Salminen et al., 2010)</ns0:ref>: a) bacteria may stimulate mucus and antimicrobial compound production, b) bacteria may activate and help modulate the immune response in the fish, and c) the interaction between different types of bacteria may actively exclude or compete with potentially pathogenic bacteria. The mucus layer in sharks and rays has been poorly studied. However, it is known that mucus from stingray skin appear to accelerate the healing processes of wounds, and that bacteria found in the mucus present antibacterial activity against human pathogens <ns0:ref type='bibr' target='#b52'>(Luer et al., 2014)</ns0:ref>. Also, it has been found recently that the structure, geometry and arrangement of dermal denticles of the shark skin play an important role in allowing bacterial attachment and development of biofilms <ns0:ref type='bibr' target='#b25'>(Chien et al., 2020)</ns0:ref>. Reproductive behavior in this group is characterized by aggressiveness during courtship and copulation <ns0:ref type='bibr' target='#b62'>(Pratt &amp; Carrier, 2001;</ns0:ref><ns0:ref type='bibr' target='#b23'>Carrier, Pratt &amp; Martin, 2015)</ns0:ref>. In sharks, the male bites the female on her dorsal or pectoral fins generating wounds in those areas <ns0:ref type='bibr' target='#b62'>(Pratt &amp; Carrier, 2001)</ns0:ref>. Polyandry, a mating system in which one female mates with multiple males, is very common in some species <ns0:ref type='bibr' target='#b75'>(Saville et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b21'>Carrier et al., 2003)</ns0:ref>. This behavior drives competition between males and avoidance in females <ns0:ref type='bibr' target='#b44'>(Klimley, 1980;</ns0:ref><ns0:ref type='bibr' target='#b35'>Gordon, 1993;</ns0:ref><ns0:ref type='bibr' target='#b62'>Pratt &amp; Carrier, 2001)</ns0:ref>. There are also morphological characteristics related to this trait. Sexual dimorphism occurs in shark species in which the male&#180;s teeth are shaped so they can easily grab the female in order to remain close to her while mating. Females have thicker dermal denticles (tooth-like structures that provide hydrodynamics and protection) than males as protection against these bites <ns0:ref type='bibr' target='#b22'>(Carrier, Musick &amp; Heithaus, 2012)</ns0:ref>. In the case of rays, the females prick the male with their caudal spine <ns0:ref type='bibr' target='#b62'>(Pratt &amp; Carrier, 2001)</ns0:ref>. It has been shown in some stingray species that when many males are involved in mating, a few may die in the process <ns0:ref type='bibr' target='#b34'>(Gilad et al., 2008)</ns0:ref>. In spite of these apparently aggressive behaviors, copulation is necessary and the wounds provoked are highly likely to become infected <ns0:ref type='bibr' target='#b31'>(Daly-Engel et al., 2010)</ns0:ref> due to opportunistic bacteria in the water and in the oral cavity of males. Because of the high concentration of pathogenic microorganisms found in the aquatic environment <ns0:ref type='bibr' target='#b53'>(Magnadottir, 2010)</ns0:ref>, it is important to determine the microbiota component of the epithelial mucus, the skin, and to understand whether the bacteria found in these are similar or different from those found in the water surrounding the animals. This will help to understand the role of mucus in the protection against pathogens. In this study, we characterized the bacterial diversity in the epithelial mucus in three elasmobranch species, the nurse shark (Ginglymostoma cirratum), the lemon shark (Negaprion brevirostris) and the southern stingray (Hypanus americanus) <ns0:ref type='bibr' target='#b50'>(Last et al., 2016)</ns0:ref>. We also hypothesize about the possible role of some of the bacteria found in the mucus and in the skin.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Sample collection</ns0:head><ns0:p>Mucus and skin tissue samples were collected from 19 apparently healthy individuals (no visible wounds, normal swimming activity); 14 of them from animals captured in Bimini, Bahamas (25&#61616;43&#61602;59 N, 79&#61616;14&#61602;60 W): four corresponded to juvenile nurse sharks (Ginglymostoma cirratum), six to juvenile lemon sharks (Negaprion brevirostris), and four to adult southern stingrays (Hypanus americanus). Samples from an additional five adult nurse sharks were collected at Oceanario from Islas del Rosario (CEINER), in the Colombian Caribbean (10&#61616;10&#61602;30 N, 75&#61616;45&#61602;00 W). For each individual, we obtained a sample of skin tissue and mucus, following sampling protocols approved by the Animal Care Committee of Universidad de los Andes (CICUAL) (Bogota, Colombia). The skin tissue sample was cut, using a sterile blade for each specimen, from the posterior part of the dorsal fin (1 cm 3 or less) and the mucus from the skin surface, using a sterile 1.5 ml microcentrifuge tube to scrape the skin surface, ideally filling at least half of the tube. Animals were manipulated for approximately 5 minutes and immediately released. A water sample was also collected in sterile 15 ml tube from the sampling location of each individual. Thus, three samples were associated with each individual, for a total of 57 samples. The individuals were captured and raised slightly above the surface of the water, so that the samples could be taken outside the water, while the animal could continue breathing. Skin samples were preserved in ethanol 90%. All samples were maintained at 4 &#186;C for less than one week, until processing. DNA Extraction and PCR amplification DNA was extracted from the entire sample collected for all samples. The Tissue and Cells DNA Isolation Kit (MoBio Laboratories, Inc.) was used, following the manufacturer instructions. Water samples were filtered through a 0.8 &#61549;m cellulose nitrate filter before DNA extraction. The primers 515f and 806r were used in order to amplify the region V4 from the bacterial and archaea 16S rRNA gene using the primers 515F (5&#180;-GTGCCAGCMGCCGCGGTAA-3&#180;) and 806R (5&#180;GGACTAHVGGGTWTCTAAT-3&#180;) <ns0:ref type='bibr'>(Caporaso et al., 2010)</ns0:ref>. PCR amplification conditions were as follows: an initial denaturation at 94 &#176;C for 3 minutes, followed by 35 cycles of denaturing at 94 &#176;C for 45 seconds, annealing for 45 seconds at 50 &#176;C and extension for 45 seconds at 72 &#176;C, followed by a final extension of 20 minutes at 72 &#176;C. A negative PCR control was always included to reduce the chance of contaminant amplification. Successful amplification was confirmed on 1 % agarose gel.</ns0:p></ns0:div> <ns0:div><ns0:head>Ion torrent library preparation, quantification and sequencing</ns0:head><ns0:p>From the 57 samples, 32 were used to construct libraries (Supplementary Table <ns0:ref type='table'>1</ns0:ref>). Samples were chosen depending on their final DNA concentration, once the PCR products were cleaned using magnetic beads and run on a 1.5% agarose gel. Only the samples that had a clear strong band were used for library construction. Two libraries, each with 16 barcodes, were prepared using the protocol Ion Xpress&#8482; Plus gDNA Fragment Library Preparation (Life Technologies). Libraries were quantified with the Qubit kit. Templates were prepared following the Ion PGM&#8482; Template OT2 200 Kit (Life Technologies) protocols. Libraries were prepared for sequencing using the protocol Ion PGM&#8482; Sequencing 200 Kit v2 (Life Technologies). Libraries were pooled to equimolar concentration and loaded on two Ion 316 chips and sequenced in the Ion Torrent PGM (Life Technologies). 16S rRNA datasets used in this manuscript with accompanying metadata has been submitted to Dryad as https://datadryad.org/stash/dataset/doi:10.5061/dryad.b5mkkwh8j Bioinformatic and statistical analyses Sequences were separated by barcodes directly by the Ion Torrent PGM and saved by the ion reporter in different files; sequence quality was analyzed using FastQC <ns0:ref type='bibr' target='#b5'>(Andrews, 2014)</ns0:ref>. The file format was changed from Fastq to Fasta. Demultiplexing was conducted by comparing the mapping file of the chip with the files containing the sequences. For the core diversity analysis, Qiime2 <ns0:ref type='bibr'>(Bolyen et al. 2019)</ns0:ref> was used via command line using the moving pictures tutorial as reference. The files were imported as 'MultiplexedSingleEndBarcodeInSequence' and demultiplexed using 'cutadapt', eliminating sequences shorter than 50 bp. The sequences went through DADA2 <ns0:ref type='bibr' target='#b17'>(Callahan et al. 2016)</ns0:ref> for quality control to delete sequences with lower qscore than 20 and then the remaining sequences were aligned de novo with align-to-tree-mafftfastree. In parallel, the sequences were clustered into OTUs used to perform non phylogenetic analysis. The rooted tree obtained with fasttree2 <ns0:ref type='bibr' target='#b65'>(Price et al. 2010)</ns0:ref> was used to perform an alpha rarefaction with a 1000 sequence depth. For taxonomic assignment, analyses were performed on the Galaxy online platform <ns0:ref type='bibr' target='#b1'>(Afgan et al. 2016)</ns0:ref> following one amplicon data workflow on Mothur v.1.28.0 <ns0:ref type='bibr' target='#b76'>(Schloss et al., 2009)</ns0:ref>. This workflow started by merging all read files into group files. Group files were identified as samples from each of the three elasmobranch species and also as type of sample (skin, mucus or water). The next step of the workflow identified unique sequences and generated a file with these sequences and a second file in which the number of each unique representative sequence was kept. Following this, reads were filtered based on quality and length. Parameters to remove low quality sequences (quality control) was for those with less than 20 Phred score and shorter than 50 bp. (minimum length) followed by a step to remove poorly aligned sequences and chimeric sequences. Finally, reads were clustered based on their degree of similarity, with a minimum of 97% identity threshold and aligned to the Silva V4 reference database <ns0:ref type='bibr' target='#b66'>(Quast et al., 2013)</ns0:ref>, followed by a classification step into taxonomic categories (order, family, genus and species when possible). Rstudio version 1.1.463 (R Development Core Team, 2010) was used <ns0:ref type='bibr' target='#b90'>(Wickham, 2009)</ns0:ref> for alpha (&#61537;) diversity analyses (Simpson and Shannon) (package Vegan) <ns0:ref type='bibr' target='#b59'>(Oksanen et al. 2015)</ns0:ref> which were conducted for OTUs, using the number of OTUs per sample, comparing among species (N. brevirostris, G. cirratum juveniles and adults and H. americanus) and among sample types (tissue, mucus and water). In this analysis, OTUs with less than 0.2% presence were not included. A Shapiro-Wilk normality test was conducted to evaluate normality among samples belonging to PeerJ reviewing <ns0:ref type='table'>PDF | (2018:07:29887:5:1:NEW 22 Sep 2020)</ns0:ref> Manuscript to be reviewed each elasmobranch species (Supplementary Table <ns0:ref type='table'>1</ns0:ref>), including the additional category of adults and juvenile for nurse sharks, or to each category of sample type before performing any statistical tests. Since results fell outside the normality assumption, a Kruskal-Wallis test was used to evaluate whether &#61537; diversity was significantly different among elasmobranch species or among sample type. To estimate beta (&#61538;) diversity (Bray-Curtis dissimilarity index and a Principal Component Analysis (PCA) the taxonomic category 'order' was used. Venn diagrams (package DVenn) were used to visualize shared orders among elasmobranch species and among sample types.</ns0:p><ns0:p>In order to find co-occurrence between different bacterial and/or Archaea orders a correlation matrix was created in R using the Spearman&#180;s co-efficient as in <ns0:ref type='bibr' target='#b42'>Ju et al (2013)</ns0:ref>. Correlations had to be stronger than 0.6 with a p-value &lt; 0.01 to be considered to have a significant co-occurrence with other orders. All orders, including those with less than 0.2% presence were included in the co-occurrence analysis. A chord plot was created to visualize the relations between the different orders.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>The 32 samples used to build the libraries included a mucus or tissue sample for each of the individuals sampled and only four of the 19 samples from water (Supplementary Table <ns0:ref type='table'>1</ns0:ref>). The other samples, including 15 water samples, had low DNA concentrations that could not be used for NGS sequencing analysis, characterized by weak or no bands amplified. A total of 219,162 reads were obtained from the Ion Torrent PGM of which 55,642 were used for subsequent analyses following demultiplexing. After read quality control and chimera removal, 21,530 reads were used in the following steps for Qiime2 and in the Mothur workflow. Of these, 17,685 were grouped as unique OTUs in Qiime2 (most of them represented each by only one read, Supplementary Figure <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>) (82% total reads). In Mothur, 3,639 (16.9 % total reads) were assigned taxonomically against the SilvaV4 database while 19,164 were left unassigned (84% total reads); sequences assigned taxonomically belonged to 18 mucus, 10 skin and 4 water samples. A total of 25 phyla, 81 orders, 76 families and 33 genera were assigned (Figure <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>), but analyses were restricted to OTUs and to the taxonomic category 'order', since this was the category with higher levels of taxonomic assignments. Most reads were identified as belonging to the Bacteria Domain (Supplementary Table <ns0:ref type='table'>2</ns0:ref>). Occurrence of reads belonging to the kingdom Archaea was low (&lt; 2%) and these were only found in one mucus sample from one nurse shark. Among the Archaea Domain, the orders identified were Micrarchaeles, Cenarchaeales, Halobacteriales, and Methanobacteriales. Thirty-seven orders were shared between samples from the three elasmobranch species and the water samples, and 17 were solely found in elasmobranch samples. Twenty-seven orders were found only in the water samples (Figure <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>). Fifty-four were shared among all elasmobranch species, 28 were shared between the nurse shark and the lemon shark, and 25 were shared between the two shark species and the southern stingray (Figure <ns0:ref type='figure' target='#fig_4'>2a</ns0:ref>). Fortyfive orders were shared between all sample types (water, mucus and skin), 47 were shared between mucus and skin, and less than 20 were shared between tissue or mucus and water samples (Figure <ns0:ref type='figure' target='#fig_4'>2b</ns0:ref>). Also, among elasmobranch species and types of samples, similar orders were found in every sample and with a similar distribution (Figure <ns0:ref type='figure'>3a and 3b</ns0:ref>). The highest abundance was of the order Actinomycetales and the family Nocardiaceae (i.e.genus Rhodococcus), with a slightly greater abundance of reads obtained from the lemon shark and less abundance for reads obtained from the southern stingray. Mucus and skin samples had a higher number of reads than water samples (Supplementary Figure <ns0:ref type='figure' target='#fig_4'>2</ns0:ref>). Phylogenetic diversity was used to build a rarefaction curve, following a phylogenetic aligned tree method, as it allowed a better visualization of data since most rarefaction curves were too similar to be distinguished. However, this methodology allowed clearer observation of the high heterogeneity found in samples used in this study, with some samples having much a higher number of total reads than others. Also, it showed that most if not all the samples did not reach an asymptote as showed in Supplementary Figure <ns0:ref type='figure'>3</ns0:ref>. For OTUs, Alpha-diversity was similar among species and among types of samples (Table <ns0:ref type='table'>1a and 1b</ns0:ref>). Alpha-diversity was non significantly different among species or among type of samples (Figure <ns0:ref type='figure' target='#fig_9'>4a, 4b, 4c and 4d</ns0:ref>). Using the taxonomic category 'order', the Bray-Curtis dissimilarity index, used as a &#61538; diversity estimate, revealed greater dissimilarity (0.45) between the microbial communities found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the skin and mucus of the lemon shark and nurse shark (Figure <ns0:ref type='figure' target='#fig_10'>5</ns0:ref>). When each sample was used to calculate the Bray-Curtis dissimilarity index, patterns of bacterial community dissimilarity were less clear, but it appears that mucus and skin samples from sharks and the southern stingray were less dissimilar from each other than when compared with the water samples (Figure <ns0:ref type='figure' target='#fig_11'>6</ns0:ref>). The percentage for each order identified from the total reads (sequences) obtained for each sample and analyzed is shown in Supplementary Table <ns0:ref type='table'>2</ns0:ref> and Supplementary Figure <ns0:ref type='figure' target='#fig_4'>2</ns0:ref>. Few sequences were assigned to the species or genus levels. Most of them were assigned to higher taxonomic levels (order). However, among the genus and species identified, several reported bacterial fish pathogens, symbionts and commensals were found in the mucus, tissue, and water samples (Supplementary Table <ns0:ref type='table'>2 and Supplementary Table 4</ns0:ref>). It is interesting to note that some fish pathogens were only found in the water and not in the mucus/tissue samples, such as the order Pastereullales (i. e. Pasteurella spp., Haemophilus spp) and Oceanospirillales (i.e. Halomonas spp.) The PCA showed higher similarity between the bacterial orders found in the skin and mucus of the two shark species in comparison with those in the southern stingray. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2) (Figure <ns0:ref type='figure'>7</ns0:ref>). In the PCA separating each sample, including adults and juvenile nurse sharks, no clear differentiation patterns among microbial community compositions were detected (Supplementary Figure <ns0:ref type='figure' target='#fig_5'>4</ns0:ref>). The co-occurrence analysis plot showed 104 out of all 202 recognized orders (including orders with less than 0.2% presence) (Supplementary Figure <ns0:ref type='figure' target='#fig_10'>5</ns0:ref>). Most of the correlations were between candidate orders, however orders such as Chlorobiales, Deinococcales Trembayales, Thermoproteales, Desulfarculales and Fusobacteriales showed strong co-occurrence. Orders such as Actinomycetales and Bacteroidales, highly influential in the principal coordinate analysis, where not found in the co-occurrence analyses plot. Manuscript to be reviewed Discussion This study provides initial but useful baseline information on microbial communities in elasmobranch species from which changes in microbial communities over time and under changing conditions can be evaluated. Nevertheless, depending on the characteristics and populations of these animals, the composition and role of the whole community may vary. From a conservation perspective, knowledge of the microbial composition and function may be an important approach for understanding how these organisms may be affected in the long term by environmental change; for example, climate change or ocean acidification <ns0:ref type='bibr' target='#b8'>(Bahrndorff et al., 2016)</ns0:ref>. In general, there were few taxonomically identified sequences compared to the total (only 16.9 % of the total reads) and as compared to OTUs grouped (82% of the total reads). This may be the result of the shorter length of the sequences, the kits used in sequencing (to make libraries of short sequences), and differences in the DNA concentration at the start of the amplification and library preparation processes <ns0:ref type='bibr'>(Solonenko et al., 2013)</ns0:ref>. Also, it has been suggested that the primers used in this study may amplify DNA from the host species (eukaryotic DNA), which would then reduce the total number of microbial reads that would have been included in our analysis <ns0:ref type='bibr' target='#b61'>(Parada et al., 2016)</ns0:ref>. However, our results are relevant to understand the microbial communities in elasmobranch fish and they suggest that skin tissue and mucus communities of the three elasmobranch species were similar in composition. Also, although some orders were shared with the water samples, more of them were shared between the two shark species and to a lesser extent with the southern stingray. Alpha-diversity at OTU level was similar among samples from the three species and among types of samples. However, there was high variation in the Alphadiversity among samples within each species or within each sample type, which was confirmed by the rarefaction curve ran for all samples included in the study. This could be related with different number of reads obtained per sample, since alpha diversity indices can be sensitive to differences in sample sizes <ns0:ref type='bibr' target='#b9'>(Barrantes &amp; Sandoval, 2009)</ns0:ref>. This could have been caused by the storage conditions of some samples or due to the loss of DNA from some samples during the different steps of library preparation. Also, selective PCR amplification could generate higher amplification of some bacteria and not others. The richness of species was higher in mucus samples and in lemon shark samples. Composition of mucus samples and skin samples from sharks tended to be more similar to each other than to the southern stingray or the water samples. In this study, the bacterial diversity in the mucus and tissue included a wide range of orders, that have been described as pathogens, non-pathogens, and some that have scarcely been studied in relation to potential or confirmed hosts. Most orders identified belonged to the Bacteria Domain, with a very small proportion of Archaea. However, some of the Archaea identified in a mucus sample belonging to a nurse shark included Cenarchaeales, which have been found to be symbionts of one marine sponge that lives at very low temperatures <ns0:ref type='bibr' target='#b63'>(Preston et al., 1996)</ns0:ref>. Interestingly, a high proportion of Actinomycetales (i.e. genus Rhodococcus) were found in mucus and tissue samples and influenced the community composition of all our samples, as showed in the PCA. Manuscript to be reviewed Although Actinomycetales can be found in environmental samples from soil and water, and have been found in marine water and sediments, some strains have been isolated from marine environments and produce antimicrobial compounds against pathogenic bacterial and fungus <ns0:ref type='bibr' target='#b11'>(Betancur et al., 2017)</ns0:ref>, particularly against some pathogenic strains of E. coli and Pseudomonas sp. <ns0:ref type='bibr'>(Yellamanda et al., 2016)</ns0:ref>. The phylum Actinobacteria, to which the order Actinomycetales belongs, has also been found in the skin microbiota of bony fish (Osteichthyes) <ns0:ref type='bibr' target='#b49'>(Larsen et al., 2013)</ns0:ref>. The finding of some Actinomycetales also in the water samples may represent contamination, although as mentioned before, they are an abundant order in marine environments. Also, a negative control was always included in the PCR amplifications and came out clean in all cases. Also, by not including OTUs or orders with less than 0.2% representation in the total sample, we tried to control for possible contaminants in the samples, maybe due to manipulation in the field or in the laboratory setting. Although we focused our analysis on microbial community diversity and composition of the orders identified, we also investigated their characteristics and those of the genera within each order because, although a smaller number of reads were identified to the genus level, some interesting data was obtained. Within the bacterial order and genera found only in water samples, three have been described as pathogens for fish, including the order Pasteurellales (genus Pasteurella spp. and Haemophilus spp.) and of the order Oceanospirillales (genus Halomonas spp.) <ns0:ref type='bibr' target='#b16'>(Bullock, 1961;</ns0:ref><ns0:ref type='bibr' target='#b41'>Hawke et al., 1987;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. There was also a species only found in water samples, Acinetobacter johnsonii (order Pseudomonadales), which has been described as a fish pathogen <ns0:ref type='bibr' target='#b45'>(Kozi&#324;ska et al., 2014)</ns0:ref>. Other sequenced bacteria present in the results of water samples, such as Moraxella sp., are opportunistic bacteria and have been found in other animals, for example in mammals <ns0:ref type='bibr' target='#b89'>(Whitman, 2015)</ns0:ref>. Some orders found only in the elasmobranch samples may also play a role as pathogens. The order Alteromonadales (i.e. genera Alteromonas, Shewanella) <ns0:ref type='bibr' target='#b13'>(Boone &amp; Bryant, 1980)</ns0:ref>, Actinomycetales (i.e. genera Mycobacterium and Nocardia), Bacillales (i.e. Staphylococcus) and Flavobacteriales (i.e. Chryseobacterium) have been reported as pathogens for various fish species <ns0:ref type='bibr' target='#b40'>(Hansen &amp; Olafsen, 1999;</ns0:ref><ns0:ref type='bibr' target='#b6'>Austin, 2005)</ns0:ref>. The order Syntrophobacterales (i.e. genus Syntrophobacter) was also present in mucus and skin samples and considered a possible pathogen for fish, due to the fact that bacteria that belong to this group, degrade propionate, a corticoid used in healing skin <ns0:ref type='bibr' target='#b77'>(Schulze et al., 2006)</ns0:ref>. However, many other Flavobacteriales (i.e. Flavobacterium), Vibrionales (i.e. Pseudoalteromonas), Lactobacillales (i.e. Lactobacillus) and Bacillales (i.e. Bacillus), also found only in elasmobranch samples, are considered symbionts of marine fish <ns0:ref type='bibr' target='#b4'>(Anand et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b52'>Luer et al., 2014)</ns0:ref>. Some species of Flavobacterium have been studied as commensal to fish, and have shown antimicrobial activity against fish pathogens from the genus Vibrio <ns0:ref type='bibr' target='#b48'>(Lal &amp; Tabacchioni, 2009)</ns0:ref>. Bacillus polymyxa, found in mucus and skin samples in this study, has been isolated from fish guts and some strains of this species synthesize antibiotics <ns0:ref type='bibr' target='#b60'>(Olmos, 2014)</ns0:ref>. Similarly, Bacillus subtilis has been suggested as a probiotic involved in the optimization of fish feeding <ns0:ref type='bibr' target='#b54'>(Merrifield &amp; Rodiles, 2015)</ns0:ref>. Finally, various orders sequenced from mucus and skin samples are considered normal biota of fish gills or skin (i.e., Xanthomonadales, Caulobacteriales) <ns0:ref type='bibr' target='#b84'>(Sugita et al., 1996)</ns0:ref>. However, it is important to remember that pathogenicity may be related to particular strains <ns0:ref type='bibr' target='#b33'>(Fitzgerald &amp; Musser, 2001</ns0:ref>) so caution is needed in the interpretation of these results. For example, three orders genera found in mucus and tissue samples Lactobacillales (i.e. Manuscript to be reviewed reported as pathogens and sometimes reported as symbionts. For example, S. parauberis produces streptococcosis in some fish <ns0:ref type='bibr' target='#b6'>(Austin, 2005;</ns0:ref><ns0:ref type='bibr' target='#b58'>Nho et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but other Streptococcus spp. inhibit the growth of pathogenic bacteria <ns0:ref type='bibr' target='#b40'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Similarly, Pseudomonas putrefaciens acts as a pathogen for fish <ns0:ref type='bibr' target='#b0'>(Abrahamian &amp; Goldstein, 2011)</ns0:ref>, but P. fluorescens inhibits growth of pathogens <ns0:ref type='bibr'>(Subramanian, Ross &amp; MacKinnon, 2008)</ns0:ref> and has been isolated from healthy salmon eggs and mucus <ns0:ref type='bibr' target='#b27'>(Cipriano &amp; Dove, 2011;</ns0:ref><ns0:ref type='bibr' target='#b2'>Akinyemi et al., 2016)</ns0:ref>. Finally, Vibrio have been reported several times as an important pathogen for marine life because of its great capacity for survival and of acclimation in its host, as it hydrolyzes urea and uses it as a source of carbon and nitrogen <ns0:ref type='bibr' target='#b40'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Many species have been described as infectious for Negaprion brevirostris, especially when they are physically injured <ns0:ref type='bibr' target='#b37'>(Grimes et al., 1984a;</ns0:ref><ns0:ref type='bibr' target='#b38'>Grimes, Gruber &amp; May, 1985)</ns0:ref>; others are associated to the mortality of sharks in captivity <ns0:ref type='bibr' target='#b39'>(Grimes et al., 1984b)</ns0:ref>, and others to infections caused by hooks <ns0:ref type='bibr' target='#b14'>(Borucinska et al., 2002)</ns0:ref>. There are some species that, depending on the strain, are pathogenic or not, such as V. alginolyticus and V. parahemoliticus <ns0:ref type='bibr' target='#b7'>(Austin &amp; Austin, 2007;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abrahamian &amp; Goldstein, 2011)</ns0:ref>. Other species, such as Vibrio alginolyticus and V. fluviales, are considered pathogenic for fish in general <ns0:ref type='bibr' target='#b94'>(Zorrilla et al., 2003)</ns0:ref>; Vibrio fortis has been reported as a sea horse pathogen <ns0:ref type='bibr'>(Wang et al., 2016)</ns0:ref>; Vibrio shilonii has been found to cause coral bleaching <ns0:ref type='bibr' target='#b46'>(Kushmaro et al., 2001)</ns0:ref>. There are various bacteria identified in the mucus samples that are considered in other studies as symbionts or pathogens for other animals or humans. For example, some species of the order Bacteroidales (i.e. Bacteroides) have been described as human pathogens in periodontal disease and Prevotella copri, found in mucus and skin samples have been identified as pathogens in intestinal inflammation. Additionally, bacteria from the order Clostridiales (i.e. Helcoccocus) have also been described as pathogens for humans <ns0:ref type='bibr' target='#b26'>(Chow &amp; Clarridge, 2014)</ns0:ref>. Also, many species within the order Chlamydiales are reported as pathogens for birds and mammals <ns0:ref type='bibr' target='#b89'>(Whitman, 2015)</ns0:ref>. As examples of symbiosis of species of bacteria (found in samples for this study) with humans or other animals, it is worth mentioning Lactobacillus zeae (order Lactobacillales), which has been found to serve as protective biota for nematodes <ns0:ref type='bibr' target='#b93'>(Zhou et al., 2014)</ns0:ref>; Butyrivibrio and Selenomonas (both from the order Clostridiales) are found in the gastrointestinal tract of ruminants; other members of the order Clostridiales, including Faecalibacterium prausnitzii, Peptoniphilus, Ruminococcus, Megamonas <ns0:ref type='bibr' target='#b26'>(Chow &amp; Clarridge, 2014)</ns0:ref> and Butyricimonas (from the order Bacteroidales) <ns0:ref type='bibr' target='#b88'>(Wexler, 2007)</ns0:ref> are normal important bacteria in the human gut microbiota. Other orders sequenced from mucus samples were Flavobacteriales such as Sulcia muelleri <ns0:ref type='bibr' target='#b56'>(Moran, Tran &amp; Gerardo, 2005)</ns0:ref>, Enterobacteriales such as Baumannia cicadellinicola <ns0:ref type='bibr' target='#b29'>(Cottret et al., 2010)</ns0:ref> and Trembayales such as Carsonella ruddii <ns0:ref type='bibr' target='#b85'>(Thao et al., 2000)</ns0:ref>, which have been described in symbiotic association with insects. A very interesting case is the order Burkholderiales (i.e. Janthinobacterium lividum), which has been found in the skin of some amphibians and appears to prevent infection by Batrachochytrium dendrobatidis <ns0:ref type='bibr' target='#b15'>(Brucker et al., 2008)</ns0:ref>. These are startling examples that may be related to the findings of this study; however, more in-depth research should be conducted to identify the pathogenicity or symbiosis properties specifically in elasmobranch or fish. Results from the co-occurrence analysis presented some interesting results but not clear patterns related to the PCA results or to other previously presented analyses. Strong co-occurences were found among orders such as Elusimicrobiales, Halanaerobiales, Synachococcales, Solibacterales which are defined as marine environmental bacteria (some of these orders can be classified as cyanobacteria), including some desulfurating bacteria, such as Desulfarculales, but also with bacterial order characterized by their presence in extreme habitats, such as Thermobaculales and Thermoproteales. This could suggest that either these are random co-occurrences among environmental bacteria that may be contaminants to the mucus and skin samples or that desulfuration may be an important metabolic path used by bacteria in these microbial communities as has been shown in the gut microbial communities of some marine fish <ns0:ref type='bibr' target='#b32'>(Egerton et al., 2018)</ns0:ref>. Further research on this idea may be warranted. Interestingly, Fusobacteriales, a bacterial order which has been previously found in the human gut <ns0:ref type='bibr' target='#b80'>(Suau et al., 2001)</ns0:ref> as well as in the gills of coral reef fish <ns0:ref type='bibr' target='#b72'>(Reverter et al., 2017)</ns0:ref>, as well as Trembayales, an order of bacteria found to be endosymbionts of insects <ns0:ref type='bibr' target='#b85'>(Thao et al., 2000)</ns0:ref>, were also found in the co-occurrence analyses, suggesting a possible role in the skin and mucus microbial communities of elasmobranch. According to this study, the role of the mucus and the bacteria associated to it may depend on numerous variables, including the virulence and pathogenicity of each microorganism <ns0:ref type='bibr' target='#b40'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. Opportunistic bacteria can acquire virulence determinants with environmental changes by different means, for example, by a) increasing their numbers by exploiting the higher production of mucus (glycoproteins) induced by presence of toxic substances in the water <ns0:ref type='bibr' target='#b40'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, by b) shifting from a non-infectious state to an infectious one through an activation caused by a physical or chemical change in the environment <ns0:ref type='bibr' target='#b40'>(Hansen &amp; Olafsen, 1999)</ns0:ref>, or by c) Reaching the dermal layer to infect the host taking advantage of a degree of reduction of the defensive mucus layer, caused by the presence of abrasive substances in the surroundings of the fish <ns0:ref type='bibr' target='#b10'>(Benhamed et al., 2014)</ns0:ref>. These three opportunities for the bacteria to infect the hosts not only benefit these microorganisms but they also affect the host by reducing their physiological condition <ns0:ref type='bibr' target='#b6'>(Austin, 2005)</ns0:ref>, and may explain the finding of the reported bacterial pathogens on the skin of healthy animals. The orders considered fish pathogens found in the water samples but absent in the elasmobranch samples, allows this research to present an interesting assumption. We suggest that there may be specific antimicrobial activity in the skin environment, or partial control against infections that exists in low concentration in the mucus, but this might be also a result of the low number of samples and replicates analyzed <ns0:ref type='bibr'>(Rakers et al., 2010)</ns0:ref>. However, it is very likely that difficulties in sampling -for example, handling the sharks and stingrays-, prevented us from collecting a larger skin or mucus sample and that this in itself could be biasing our results. The simultaneous presence of pathogens and possible symbionts varied between samples; however, the role of each order should be verified for each of the host species considered in this analysis. According to these results, we suggest that the role of the epithelial microbiota may be considered as a first line of defense against infectious organisms but it could also be a potential threat for the injured host. This may be particularly relevant as a protective mechanism for sharks and rays that get hurt during copulation and that could otherwise die due to infected wounds. This could also depend on the whole combination of bacteria and their interaction between them in each host, as well as with the host cell and physiology, known as the 'holobiont' <ns0:ref type='bibr' target='#b24'>(Carthey et al., 2020)</ns0:ref>. As mentioned earlier, each fish may accumulate a specific community of microorganisms in its life span depending on the environments it inhabits during its development and growth <ns0:ref type='bibr' target='#b40'>(Hansen &amp; Olafsen, 1999)</ns0:ref>. This particular accumulation and interaction between the microbiota and the host (holobiont) may also affect aspects such as survival and reproduction of the host, and may become relevant for conservation of these shark species in the near future <ns0:ref type='bibr' target='#b24'>(Carthey et al., 2020)</ns0:ref>. This study represents the first contribution to describing shark and ray skin and mucus microbial communities. The next steps to further understand the role of bacterial communities in skin and mucus of elasmobranchs require functional metagenomics and metabolomics analyses to unveil the role of these bacteria. Conclusions This study presents the first description of skin and mucus microbiota from two shark species and a stingray. Orders were highly diverse and similar between species and types of samples and a higher number of orders were found in skin and mucus when compared to water samples. The order Actinomycetales was found in a very high percentage (&gt;50%) of skin and mucus samples and could represent bacteria that may have antimicrobial activity, however the co-occurrence analysis showed strong relationships among order previously found in the human and fish gut, as endosymbionts of insects and among orders involved in metabolic paths related to desulfuration. This is baseline information that could help in future monitoring of microbiota change in elasmobranch species that may be caused by climate change and ocean acidification.</ns0:p></ns0:div> <ns0:div><ns0:head>Conflict of interest</ns0:head><ns0:p>We declare potential conflict of interest with Dr. M. Suzuki. For that reason, we ask for him not to be asked as a reviewer or editor for this manuscript. Author contribution Susana Caballero: project and experiment design, manuscript writing and data analysis Ana Maria Galeano: project and experiment development and data analysis Juan Diego Lozano: Data analysis Martha Vives: Project and experiment design, manuscript writing Funding Financial support for this project was provided by Proyecto de Ciencias B&#225;sicas, Vicerrectoria de Investigaciones, Universidad de los Andes. Acknowledgements We would like to give a special thanks to all those involved in samples collection, particularly to the Bimini Shark Laboratory, to D. Carde&#241;osa, and to R. Vieira and his team at Oceanario Islas del Rosario (Ceiner). We thank E. Salguero and A. P. Jimenez for their help with sequencing. Figure <ns0:ref type='figure' target='#fig_10'>5</ns0:ref>. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbial communities (at order level) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure <ns0:ref type='figure' target='#fig_11'>6</ns0:ref>. Bray-Curtis dissimilarity index calculated at order level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure <ns0:ref type='figure'>7</ns0:ref>. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>. Bacterial order composition found in each sample successfully amplified Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 7</ns0:note><ns0:p>Principal component analysis (PCA) Figure <ns0:ref type='figure'>7</ns0:ref>. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2).</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2018:07:29887:5:1:NEW 22 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2018:07:29887:5:1:NEW 22 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Streptococcus and Enterococcus), Pseudomonadales (i.e. Pseudomonas) and Vibrionales (i.e. Vibrio) are sometimes PeerJ reviewing PDF | (2018:07:29887:5:1:NEW 22 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>Figure legendsFigure1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle). Figure2. Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type. Figure3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.Figure5. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbial communities (at order level) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure6. Bray-Curtis dissimilarity index calculated at order level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure7. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure1. Bacterial order composition found in each sample successfully amplified in this study. Supplementary Figure2. Number of OTUs grouped and their frequency. Supplementary Figure3. Faith's phylogenetic diversity index. Growth rate of the Faiths pd in place of standard rarefaction curve, showing fast increase of diversity with sequencing depth per sample (</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure legendsFigure1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle). Figure2. Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type. Figure3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.Figure5. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbial communities (at order level) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure6. Bray-Curtis dissimilarity index calculated at order level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure7. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure1. Bacterial order composition found in each sample successfully amplified in this study. Supplementary Figure2. Number of OTUs grouped and their frequency. Supplementary Figure3. Faith's phylogenetic diversity index. Growth rate of the Faiths pd in place of standard rarefaction curve, showing fast increase of diversity with sequencing depth per sample (</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure legendsFigure1. Summary of taxonomic assignments. Venn diagram showing the number of orders shared among elasmobranch samples (mucus and tissue), and water samples. Also, orders unique to either elasmobranch samples (brown circle) or water samples (blue circle). Figure2. Orders (a) shared between and among elasmobranch species and those unique to each species. Orders (b) shared between and among sample types and those unique to each sample type. Figure3. Bacterial order (a) composition found for each elasmobranch species (Hypanus americana, Ginglymostoma cirratum and Negaprion brevirostris). Bacterial order (b) composition found for each sample type.Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.Figure5. Bray-Curtis dissimilarity index tree showing greater dissimilarity (0.45) between the microbial communities (at order level) found in the tissue and mucus of the southern stingray and those found in the shark species, the lemon shark, and nurse shark, and less dissimilarity (0.30) between the communities found in the tissue and mucus of the lemon shark and nurse shark. Figure6. Bray-Curtis dissimilarity index calculated at order level for different types of sample for different elasmobranch species showing mucus and tissue samples from sharks and the southern stingray being less dissimilar from each other than when compared with the water samples. Figure7. Principal component analysis (PCA) showed higher similarity between the bacterial communities found in the tissue and mucus of the two shark species in comparison with those in the southern stingray at both order and family levels. Similarities were due to a similar number and distribution of reads identified as belonging to the order Actinomycetales and to the family Nocardiaceae (dimension 1) and to reads belonging to the order Bacteroidales (dimension 2). Supplementary Figure1. Bacterial order composition found in each sample successfully amplified in this study. Supplementary Figure2. Number of OTUs grouped and their frequency. Supplementary Figure3. Faith's phylogenetic diversity index. Growth rate of the Faiths pd in place of standard rarefaction curve, showing fast increase of diversity with sequencing depth per sample (</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. Alpha diversity of OTUs</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. Box-plots showing Alpha-diversity was non significantly different among species for OTUs (a)Shannon and (b) Simpson or among sample type for OTUs (c) Shannon and (d) Simpson.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 5 Bray-</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 6 Bray-</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2018:07:29887:5:1:NEW 22 Sep 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2018:07:29887:5:1:NEW 22 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

" 1. Errors: there are some nomenclature errors, so please check all the taxa names. R/this was corrected 2. Water sample diversity. It is extremely unusual, and you might need to explain it. If Actinomycetales is dominated by one or a few OTUs in all samples (an if the dominance is more important with samples with less DNA it could be a contaminant see : DOI: 10.1128/mSystems.00290-19 and /doi.org/10.1186/s40168-018-0605-2. Also, it is very strange that those samples are all over in Figure 6. One really would expect them to be closer together. R/ high variance from only 4 water samples working and having enough data to analyze if this was indeed result of contamination or not. However, contamination in the samples or PCRs is unlikely, since we always included a negative control in the PCR, meaning a tube with all the same reagents but no DNA and this control always came clean in our PCR gels. Also, if there was some kind of contamination, there is a possibility that the contaminant bacterial reads were in general in low number and probably by not including in our analyses OUT or orders with less than 0.2% presence in the samples. However, Actinomycetales in itself are an important part of aquatic and marine bacterial communities so it is hard to decide that their appearance, at least for some groups of this order, is indeed contamination. 3. Statistics: I cannot understand why you merged replicates in Figure 5 and in your PCA without those it is difficult to evaluate any of your conclusions R/The editor did not see our supplementary figure 4 4. Discussion: You are extrapolating physiology and lifestyle at an order level (I.e. you are assuming that sulfur reduction is a characteristic of orders where it is not the case. You need to tone down the discussion. There are now many publications in microbiota of fish mucus. Maybe you should instead compare yours to results in bony fish rather than making these risky conclusions. R/ we have already gone through 5 previous revisions and the reviewers approved on these sections. We are also supporting our hypotheses with references. I have a list of modifications I would like you to make: Title. Specify: Description of the microbiota in epidermal mucus and skin of the nurse shark (Ginglymostoma cirratum), the lemon shark Negaprion brevirostris) and the southern stingray (Hypanus americanus). R/the title was changed line 2 add doi number R/corrected line 23. Pseudoalteromonas is not in Vibrionales. I believe this is an error in the references used for taxonomy (i know that is a fact for the green genes database that is also based on SILVA). Also, with you description is very difficult to evaluate which version of the arb database and which classifier you used. Please add that information in the methods R/we explained that the version of the Silva database was the one available from Mothur (this was already in the methods section) and we also had already included the right reference for the database. And these are valid orders line 47 viscous R/added line 49 compounds instead of substances R/Corrected line 199 archaeal R/Corrected line 138. add rRNA gene to 16S, Also, the link does not work, so I could not see the data R/The link was copied with a mistake. This was corrected and can now be accessed. rRNA added line 182. Does this include all samples including water? R/yes it does line 206. Bacteria and Archaea are Domains not Kingdoms. R/corrected line 231. Merge with previous paragraph R/corrected line 236. Microbial, not microbiome. remove the term microbiome from the Manuscript R/corrected line 239 Figure 5 and 7 PCA. I don't understand why you merged the replicate individuals for each species. Can you explain? I would like to see a tree showing each of the replicates, and a mention in the text with the merged distances in the text We presented each sample by itself on a PCA in Supplementary figure 4 and this figure shows that there is no evident grouping particular to adults and juveniles from the same species. line 242. I do not see this in the figure, and I find hard to explain why the water samples are not more similar to each other and somehow more separated from the mucus samples. As someone who work with bacterioplankton for the last 30 years I also find very difficult to understand how Actinomycetales can make such a large proportion of reads in seawater, since I never seen this be the case in any of the datasets I ever worked with. This needs to be checked or at least discussed R/ this was further discussed and we found references supporting the fact that this order has been found widely in environments, including marine waters and they may play important roles in protecting corals from pathogenic bacteria. Also, water samples may be different from each other since only 4 out of our 15 original water samples amplified and were sequenced and therefore variance may be very high among these 4 samples. line 254. see comment in 239. There's gotta be a reasoning for 'merging' the replicates R/see reply to 239 line 259, delete 'at this time' R/This was deleted line 264. Furobacteriales is not a prokaryotic order R/name of order was corrected line 290 can you refer to the results you use to make this conclusion? R/we are referring to our results line 302. Figure 6 seems to contradict this statement. line 378-393. You are extrapolating results based on orders to very different animals. I ask you to remove this entire paragraph R/We are suggesting a hypothesis and explaining that similar results were found microbial communities from other animal, therefore we decided to keep this. line 397 I do not believe there is a bacterial order called Synachococcales neither Halanaenobiales, R/The names of the orders were corrected line 398. I do not see the term desufurating used widely. Plese use 'sulfate reducing' R/ we kept desulfurating since this was foun in references line 399. Orders R/corrected line 402. As far as I know Sulfate reduction is not a major characteristic of all these orders, so attributing it to the cooccurrence of these is over speculation. moreover Synechococcales is an oxygenic phototroph. I ask you to remove this from the discussion. R/ we included references to support our suggestion. line 406. The fact that two species co-occur does not say much about their occurrence. The presence of fusobacteria confirms previous results e.g. https://doi.org/10.1007/s00248-020-01484-y https://doi.org/10.1093/femsec/fix051 R/This reference was included to support our results line 409. This study did not study the role of mucus or its bacteria. You could use. 'Here we show the presence of bacterial orders that could be involves on pathogenicity' R/this was corrected as suggested line 457 orders R/corrected line 458. Unless you can justify it with references remove the section related to desulfuration. R/references were included to support this hypothesis Figure 5. It is a Chord diagram R/this spelling mistake was corrected "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Formosan subterranean termites, Coptotermes formosanus Shiraki , usually transport clay materials into tree hollows and bait stations. Our previous research showed that C. formosanus preferred to aggregate in the locations containing field-collected clay samples, but it was not clear whether this preference was influenced by clay types and/or moisture.</ns0:p><ns0:p>In the present study, we conducted multiple-choice tests under low-moisture (25% moisture) or moderate-moisture (50% moisture) conditions to evaluate the aggregation and wood-feeding preferences of C. formosanus responding to hollow wooden cylinders (simulation of tree hollows) or baiting containers (simulation of bait stations) filled with different clay materials ( bentonite , kaolin, chlorite, illite, or attapulgite), soil, or unfilled.</ns0:p><ns0:p>Under low-moisture conditions, the majority of termites were found in the wooden cylinders or baiting containers filled with bentonite. Under moderate-moisture conditions, however, termites preferred to aggregate in wooden cylinders filled with chlorite or attapulgite; the percentages of termites that stayed in baiting containers filled with chlorite, attapulgite or soil were similar, which were significantly higher than those that filled with kaolin, illite, or unfilled. We then conducted no-choice tests to study the effect of clay materials on termites. Under low-moisture conditions, clay filled in the baiting containers significantly increased survivorship and body water percentage (an indicator of termite vigor) of termites, whereas no similar effect was detected under moderatemoisture conditions. This study demonstrated that both clay type and moisture affect termites' preference.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head n='1.'>Introduction</ns0:head><ns0:p>The Formosan subterranean termite, Coptotermes formosanus Shiraki (Blattodea: Rhinotermitidae), is an economically significant pest distributed in many warm temperate/subtropical regions of the world, including the United States of America, China, and Japan <ns0:ref type='bibr' target='#b41'>(Su, 2003;</ns0:ref><ns0:ref type='bibr' target='#b1'>Austin et al., 2006;</ns0:ref><ns0:ref type='bibr'>Scheffrahn et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b9'>Chouvenc et al., 2016)</ns0:ref>. <ns0:ref type='bibr' target='#b43'>Suszkiw (2000)</ns0:ref> estimated that the annual repair and control cost of this pest was ~ 1 billion dollars in the United States. C. formosanus damages not only wooden structures, but also live plants <ns0:ref type='bibr' target='#b26'>(Lai et al., 1983;</ns0:ref><ns0:ref type='bibr' target='#b13'>Evans et al., 2019)</ns0:ref>. <ns0:ref type='bibr' target='#b26'>Lai et al. (1983)</ns0:ref> reported that C. formosanus usually consumed the xylem, tree vascular tissue that transports water with dissolved minerals from the roots to stems and leaves and provides physical support as well. Although these trees may appear healthy and normal (the living part of the tree remained undamaged), they could be easily broken by winds <ns0:ref type='bibr' target='#b26'>(Lai et al. 1983)</ns0:ref>. C. formosanus can also damage trunks and roots, which may result in wilt and sometimes death of the plant <ns0:ref type='bibr' target='#b26'>(Lai et al., 1983)</ns0:ref>. The impacts of C. formosanus on forests had been largely ignored in the past but have received some attention in recent years. For example, <ns0:ref type='bibr' target='#b13'>Evans et al. (2019)</ns0:ref> reported that 38% experimental patches of forests around Charleston (South Carolina, USA) and 42% patches around New Orleans (Louisiana, USA) were infested by C. formosanus, which caused significantly more and larger tree hollows compared with patches without termite infestation. Interestingly, C. formosanus usually transport large amounts of clay and soil into tree holes and other hollow spaces within/around food (e.g., gaps between bait stations and matrices) during foraging (Figure <ns0:ref type='figure'>1</ns0:ref>). <ns0:ref type='bibr' target='#b21'>Henderson (2008)</ns0:ref> reported that clay was more preferred than soil for PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed C. formosanus to fill the void space of tree holes, and a large amount of clay (~1 m 3 ) can be found in such voids. <ns0:ref type='bibr' target='#b45'>Wang et al. (2015)</ns0:ref> found that C. formosanus preferred to aggregate in chambers with field-collected clay. Also, termites preferentially used clay to cover the smooth surface of containers and construct shelter tubes <ns0:ref type='bibr' target='#b46'>(Wang &amp; Henderson, 2014;</ns0:ref><ns0:ref type='bibr' target='#b45'>Wang et al., 2015)</ns0:ref>. <ns0:ref type='bibr' target='#b51'>Xiong et al. (2018a)</ns0:ref> reported that significantly more C. formosanus and Reticulitermes guangzhouensis Ping aggregated and fed in baiting containers filled with bentonite, a clay mineral, than unfilled containers. In each of these studies, preference of termites to a single source of clay material was investigated and confirmed, but two questions remained unanswered:</ns0:p><ns0:p>(1) Do clay types and moisture conditions influence the aggregation and feeding preference by termites? And (2) Do clay materials benefit C. formosanus by improving their survival, vigor, and wood feeding?</ns0:p><ns0:p>Based on the structure and mineralogy, clay can be divided into several mineral groups including the montmorillonite/smectite group, kaolin group, chlorite group, illite group, and palygorskite group. In this study, five common clay materials were selected from these groups to investigate their effects on the survival and behavior of C. formosanus (Table <ns0:ref type='table'>1</ns0:ref>). Multiple-choice tests were conducted to study the aggregation and wood-feeding preference of C. formosanus among different clay materials that were either filled in the hollow wooden cylinders (simulation of tree hollows) or baiting containers (simulation of baiting stations). Also, no-choice tests were conducted to investigate whether each clay material affects the survival, wood-feeding behavior, and vigor (indicated by body water percentage) of termites. All choice and no-choice tests were conducted under low-moisture (25% moisture) conditions that were relatively dry for termites, or Manuscript to be reviewed moderate-moisture (50% moisture) conditions that were suitable for termites. Here we did not conduct experiments under high-moisture conditions because termites cannot make tunnels in substrates with extremely high moisture content <ns0:ref type='bibr' target='#b15'>(Gautam and Henderson, 2011a)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.'>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>Termite Collection and Maintenance</ns0:head><ns0:p>Underground baiting stations that included 6 pine-wood sticks (without termiticide; 4.5 &#215; 3.0 &#215; 16.0 cm) surrounded by plastic collars (height: 19.5 cm; diameter of upper side: 15.0 cm; diameter of bottom side: 13.5 cm) were buried in different locations of the arboretum of South China Agricultural University (SCAU, Guangzhou, China). C. formosanus infestation in each bait station was checked monthly, and the station with large numbers of termites were brought to the laboratory <ns0:ref type='bibr' target='#b51'>(Xiong et al., 2018a)</ns0:ref>. Three colony groups of C. formosanus were collected in November 2018 (for experiments 1 and 2), and two colony groups were collected in May 2019 (for experiment 3). Colonies were over 1 km apart (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). Collected baiting stations were maintained in the lab in 60 L plastic storage boxes for &lt; 1 month (23-27&#176;C under darkness).</ns0:p><ns0:p>Before the experiment, wood sticks were taken out and gently knocked to extract termites, and the caste distribution of each colony group were determined by counting 100 termites for 5 times (Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Soil and Clay</ns0:head><ns0:p>Top soil (depth &lt; 5cm) was collected from a location (23&#176;09&#8242;26&#8243;N, 113&#176;21&#8242;08&#8243;E) in the Architecture, SCAU), and identified as sandy loam soil (12% clay, 21% silt, and 67% sand). The dried soil was ground with a wooden mortar and pestle, and then sifted through a 2-mm sieve to remove coarse particles and plant roots. Five clay materials, bentonite (Fresh &amp; Natural TM , Bentonite Performance Minerals LLC, Houston, USA), kaolin (Jufeng &#174; , Shanxi Jufeng Kaolin Co., Ltd, Jinzhong, China), chlorite (Hetalc &#174; , Haicheng Hetalc Powder Technology Co., Ltd, Haicheng, China), illite (Junhong &#174; , Huiyuan Junhong New Material Co., Ltd, Datong, China), and attapulgite (Dingbang &#174; , Dingbang Mineral Products Technology Co., Ltd, Changzhou, China), were purchased. Sample of clay materials or soil were sent to the Laboratory of Environmental Chemistry (College of Natural Resources and Environment, SCAU) to measure chemical properties (i.e., pH, contents of organic matter, total nitrogen, and exchangeable cation, and cation exchange capacity, as shown in Table <ns0:ref type='table'>1</ns0:ref>). Clay and soil were sterilized at 80&#176;C for 3 days, and then completely dried at 50&#176;C for &gt;2 weeks. The formula provided by <ns0:ref type='bibr' target='#b6'>Chen and Shelton (2017)</ns0:ref> was used to determine the moisture content of soil and clay: moisture content (%) = [weight of distilled water added / (weight of saturated soil or clay -weight of dried soil or clay)] &#215; 100%. To prepare soil and clay with 25%-or 50%-moisture, the required amount of deionized water and dried soil or clay were placed in the zip-lock bags and thoroughly mixed (Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Experiment 1: Preference of Clay Materials Filled in Wooden Cylinders</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Multiple-choice tests were conducted to study whether C. formosanus prefer to aggregate and feed in hollow wooden cylinders which were filled with certain clay material or soil, or unfilled. Each test (under either low-or moderate-moisture conditions) was repeated 12 times (each of the three colony groups was repeated 4 times). The bioassay arenas were plastic containers (volume = 1250 mL, height = 6 cm, diameter of upper side = 19.2 cm, diameter of bottom side = 16 cm). To set the bioassays under low-moisture conditions, 25%-moisture soil (substrate) was added into the container to the depth of 0.5 cm. Hollow wooden cylinders (Schima superba Gardn. et Champ., height = 28 mm, internal diameter = 26 mm, external diameter = 30 mm, thickness of the bottom side = 3 mm, diameter of hole on the bottom side = 16 mm; Fig. <ns0:ref type='figure'>2A</ns0:ref>) were oven-dried at 80&#176;C for 5 days and weighed. Seven wooden cylinders were filled with 25%-moisture clay materials (bentonite, kaolin, chlorite, illite, or attapulgite) or soil, or unfilled (Fig. <ns0:ref type='figure'>2A</ns0:ref>). These wooden cylinders were placed on the substrate in the arena with randomly assigned orders, and the adjacent cylinders were equally distanced. Substrate (25%moisture soil) was then added in the container until the base of cylinders was partially buried in the depth of 1 cm (Fig. <ns0:ref type='figure'>2B</ns0:ref>). Similar procedures were carried out to set the bioassays under moderate-moisture conditions, but clay and soil with 50% moisture were used.</ns0:p><ns0:p>Four hundred termites (percentages of workers and soldiers were determined by the caste distribution of each colony group as shown in Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>) were counted and released into the center of each arena. The containers were sealed with plastic wrap to keep the internal moisture conditions and maintained in a 25&#176;C environmental chamber under total darkness. At the end of the experiment (day 21), we counted the number of live termites stayed within each wooden PeerJ reviewing <ns0:ref type='table' target='#tab_1'>PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:ref> Manuscript to be reviewed cylinder or substrate (none of the termites stayed on the outer wall of the wooden cylinders or on the surface of the substrate). The wooden cylinders were carefully washed using distilled water to remove any particles, and placed in an oven (80&#176;C) for 5 days and weighed. The dry weight change of wooden cylinders before and after the experiment was measured to calculate wood consumption.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>Experiment 2: Preference of Clay Materials Filled in Baiting Containers</ns0:head><ns0:p>The protocols of multiple-choice tests provided by <ns0:ref type='bibr' target='#b48'>Xie et al. (2019a)</ns0:ref> were modified to investigate whether C. formosanus prefer to aggregate and feed in the baiting containers filled with each clay material or soil, or unfilled. Each choice-test (under either low-or moderatemoisture conditions) was repeated 12 times (each of the three colony groups was repeated 4 times). The bioassay arena was a 1250 mL plastic container as mentioned earlier. The baiting container was plastic box (height = 33 mm; diameter of upper side = 41 mm, diameter of bottom side = 31 mm) with 10 holes (5 mm in diameter, staggered distributed in two rows) drilled on the wall (Fig. <ns0:ref type='figure'>3A</ns0:ref>). A pine wood block (20 &#215; 20 &#215; 20 mm) was completely dried in an 80&#176;C oven for 5 days and weighed, and then placed into the box (Fig. <ns0:ref type='figure'>3A</ns0:ref>). Under low-moisture conditions, the void space of seven baiting containers was either filled with 25%-moisture clay (bentonite, kaolin, chlorite, illite, or attapulgite) or soil (Fig. <ns0:ref type='figure'>3B</ns0:ref>), or unfilled. These baiting containers were placed in the bioassay arenas with randomly assigned orders. Each baiting container was equally distanced with the adjacent ones. Substrate (25%-moisture soil) was then added until the baiting containers were buried (Fig. <ns0:ref type='figure'>3C</ns0:ref>). We carried out similar procedures to set the choice test under <ns0:ref type='table' target='#tab_1'>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:ref> Manuscript to be reviewed moderate-moisture conditions, but clay and soil at the 50%-moisture level were used.</ns0:p><ns0:p>Four hundred termites were released into the center of each arena. The bioassay arenas were sealed with plastic wraps and placed in the environmental chamber (25&#176;C and under total darkness). At the end of the experiment (day 21), the number of live termites stayed within each baiting container or substrate was counted. The wood consumption was measured as mentioned earlier. The formula provided by <ns0:ref type='bibr' target='#b48'>Xie et al. (2019a)</ns0:ref> was used to calculate the moisture content of wood blocks: wood moisture (%) = [(wet weight of wood block after the experiment &#8722; dry weight of wood block after the experiment) / dry weight of wood block after the experiment] &#215; 100%.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>Experiment 3: Effect of Clay Materials on Survival, Vigor, and Wood Consumption of</ns0:head></ns0:div> <ns0:div><ns0:head>Termites</ns0:head><ns0:p>The protocols of no-choice tests provided by <ns0:ref type='bibr' target='#b48'>Xie et al. (2019a)</ns0:ref> were modified to investigate the survival, body water percentage (an indicator of termite vigor), and wood consumption of termites, as well as wood moisture when the baiting containers (as mentioned in experiment 2) were filled with each clay material (bentonite, kaolin, chlorite, illite, or attapulgite) or soil, or unfilled. The tests were conducted under either low-moisture (25% moisture) or moderatemoisture (50% moisture) conditions. In total, the tests contained 14 treatments, and each treatment was repeated 10 times (each of the two colony groups was repeated 5 times).</ns0:p><ns0:p>To set the bioassays under low-moisture conditions, a baiting container (either filled with 25%-moisture bentonite, kaolin, chlorite, illite, attapulgite, soil or unfilled) was placed in the Manuscript to be reviewed center of a plastic box (volume = 300 mL, height = 62 mm; diameter of upper side = 86 mm, diameter of bottom side = 66 mm). Substrate (25%-moisture soil) was then added into the plastic box until the bating container was buried. The same procedure was conducted to set the bioassays under moderate-moisture conditions, but 50%-moisture soil or clay materials were used.</ns0:p><ns0:p>One hundred termites were counted and released into the center of each box. The bioassays were sealed with plastic wraps and placed in a completely dark environment chamber at 25&#8451;. The survivorship of termites was recorded at the end of the experiment (day 21). Body water percentage of termites were measured as previously described in <ns0:ref type='bibr' target='#b48'>Xie et al. (2019a)</ns0:ref>. Specifically, 10 workers were randomly selected, and their fresh weight was measured using a 0.1 mg electronic balance. These termites were then placed in an oven (50&#8451;) for 3 days, and their dry weights were measured using the same electronic balance. The formula provided by <ns0:ref type='bibr' target='#b48'>Xie et al. (2019a)</ns0:ref> was used to calculate the body water percentage of termites: body water percentage (%) = [(fresh weight of termites -dry weight of termites) / fresh weight of termites] &#215; 100%. The wood consumption and wood moisture were also measured and calculated as mentioned above.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>Data Analysis</ns0:head><ns0:p>For each multiple-choice test in the experiments 1 and 2, the percentage of termites that aggregated in each wooden cylinders or baiting containers (filled with bentonite, kaolin, chlorite, illite, attapulgite, soil, or unfilled), or stayed within the substrate was calculated. Because of the sum constraint of the percentage data, we applied log-ratio transformation mentioned by Kucera Manuscript to be reviewed and Malmgren (1998) to make the raw percentages data independent. Two-way analysis of variance (ANOVA, SAS 9.4, SAS Institute, Cary, NC) was used to analyze the transformed data with termite colony as the random factor and aggregation site as the fixed factor. In addition, we compared wood consumption and wood moisture using the two-way ANOVA with termite colony as a random factor and filling types (filled with different clay materials or soil or remained unfilled) as a fixed factor. For no-choice tests in the experiments 3, we compared the survivorship, body water percentage, and wood consumption of termites, as well as wood moisture, using a two-way ANOVA with termite colony as the random factor and treatment as the fixed factor. Tukey's Honest Significant Difference (HSD) test was used after each ANOVA for post-hoc comparisons. In all tests, the significance levels were determined at &#945; = 0.05.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.'>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>Experiment 1: Preference of Clay Materials Filled in Wooden Cylinders</ns0:head><ns0:p>Under low-moisture conditions, low survivorship (&lt;30%) of termites were found in the colony group 1. As a result, only data obtained from the colony groups 2 and 3 (survivorship &#8805; 70%) were analyzed. Similar percentages of termites aggregated in the substrate and wooden cylinders filled with bentonite, both were significantly higher than that in other locations (Fig. <ns0:ref type='figure'>4A</ns0:ref>). No significant difference in wood consumption was detected when compared among wooden cylinders filled with each clay material or soil, or unfilled (Fig. <ns0:ref type='figure'>4B</ns0:ref>).</ns0:p><ns0:p>Under moderate-moisture conditions, data obtained from the three termite colonies were analyzed. Similar percentages of termites were found in the wooden cylinders filled with PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed attapulgite and chlorite, and both were significantly higher than that of wooden cylinders filled with kaolin, illite, or soil, or unfilled (Fig. <ns0:ref type='figure'>5A</ns0:ref>). However, wood consumption was similar when compared among filling types (Fig. <ns0:ref type='figure'>5B</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>Experiment 2: Preference of Clay Materials Filled in Baiting Containers</ns0:head><ns0:p>Under low-moisture conditions, low survivorship (&lt;30%) of termites were found in the colony group 1, and therefore only data obtained from colony groups 2 and 3 (survivorship &#8805; 70%) were analyzed. Most termites were found in the baiting containers filled with bentonite, whereas only a few termites were found in other locations (Fig. <ns0:ref type='figure'>6A</ns0:ref>). The wood consumption in the baiting containers filled with bentonite was also significantly higher than the other ones (Fig. <ns0:ref type='figure'>6B</ns0:ref>). The wood moisture was similar when compared among different filling types (Fig. <ns0:ref type='figure'>6C</ns0:ref>).</ns0:p><ns0:p>Under moderate-moisture conditions, data obtained from the three termite colonies were analyzed. Similar percentages of termites were found in the baiting containers filled with attapulgite, chlorite, or soil, which were significantly higher than that of containers filled with kaolin or illite, or unfilled (Fig. <ns0:ref type='figure'>7A</ns0:ref>). The wood consumption was not significantly different among filling types (Fig. <ns0:ref type='figure'>7B</ns0:ref>), but wood moisture in baiting containers filled with bentonite was significantly higher than other ones (Fig. <ns0:ref type='figure'>7C</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>Experiment 3: Effect of Clay Materials on Survival, Vigor, and Wood Consumption of</ns0:head></ns0:div> <ns0:div><ns0:head>Termites</ns0:head><ns0:p>Under low-moisture conditions, treatments with clay materials had significantly higher PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed termite survivorship compared to the treatment with unfilled baiting containers (Fig. <ns0:ref type='figure'>8A</ns0:ref>). Also, clay significantly increased body water percentage of termites compared to the treatment with soil-filled baiting containers under low-moisture conditions (Fig. <ns0:ref type='figure'>8B</ns0:ref>). No significant difference in survivorship and body water percentage of termites were detected among treatments under moderate-moisture conditions (Figs. <ns0:ref type='figure'>8A and 8B</ns0:ref>). Termites consumed least wood when baiting containers were filled with kaolin under low-moisture conditions, whereas the highest wood consumption was found when baiting containers were unfilled under moderate-moisture conditions (Fig. <ns0:ref type='figure'>8C</ns0:ref>). The wood moisture was significantly higher when the baiting containers were filled with bentonite, attapulgite, or chlorite (under moderate-moisture conditions) compared with the remained treatments (Fig. <ns0:ref type='figure'>8D</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head n='4.'>Discussion</ns0:head><ns0:p>Many previous studies focused on clay preference and utilization by the higher fungusgrowing termites in the family Termitidae. The biological functions of these termites as soil engineers have been reviewed by <ns0:ref type='bibr' target='#b2'>Bignell (2006)</ns0:ref>, <ns0:ref type='bibr' target='#b35'>Pardeshi and Prusty (2010</ns0:ref><ns0:ref type='bibr' target='#b24'>), and Jouquet et al. (2011</ns0:ref><ns0:ref type='bibr'>, 2016)</ns0:ref>. <ns0:ref type='bibr' target='#b24'>Jouquet et al. (2011)</ns0:ref> pointed out that higher termites transport large amounts of clay from various depths in underground sites to the soil surface. After they use clay to construct the aboveground biostructures such as sheetings and mounds, the subsequent erosion processes would modify the physical and chemical properties of surface soil, which may exert a significant impact on the ecosystems <ns0:ref type='bibr' target='#b24'>(Jouquet et al., 2011;</ns0:ref><ns0:ref type='bibr'>2016)</ns0:ref>. For example, Harit et al. <ns0:ref type='bibr' target='#b38'>(2015)</ns0:ref> reported that the fungus-growing termite Hypotermes obscuriceps (Wasmann) constructed extensive Manuscript to be reviewed sheetings on their food (leaves and branches), and when sheetings were degraded by rain a lot of inorganic ions (e.g., K + , F &#8722; , and Cl &#8722; ) were released and therefore impacted soil properties. <ns0:ref type='bibr' target='#b39'>Sileshi et al. (2010)</ns0:ref> reported that mounds constructed by termites (e.g., species in the genus Ancistrotermes, Macrotermes, Odontotermes, Cubitermes, and Trinervitermes) were enriched in clay and nutrition, thus creating 'islands of fertility' and enhancing the growth of plants, which shaped the spotted vegetation patterns in savannas across Africa. <ns0:ref type='bibr' target='#b3'>Bonachela et al. (2015)</ns0:ref> reported that such spotted vegetation patterns created by termites made the landscapes more robust to aridity and more stabilized to global climate changes. Likewise, <ns0:ref type='bibr' target='#b12'>Evans et al. (2011)</ns0:ref> reported that in the arid climate zones where earthworms are absent, termites provide alternative ecological services to improve water infiltration and soil nitrogen, and therefore contributed to the sustainability of dryland agriculture.</ns0:p><ns0:p>Compared to higher termites, much less attention has been paid to the potential interactions among clay, lower subterranean termites, and ecosystems. <ns0:ref type='bibr' target='#b20'>Harit et al. (2017)</ns0:ref> reviewed 29 articles about soil sheeting (always enriched in clay) produced by termites, and only 2 of them focused on the sheeting behaviors of lower subterranean termites, Psammotermes allocerus Silvestri <ns0:ref type='bibr' target='#b44'>(Vlieghe et al., 2015)</ns0:ref> and Coptotermes acinaciformis (Froggatt) <ns0:ref type='bibr' target='#b33'>(Oberst et al. 2016</ns0:ref><ns0:ref type='bibr' target='#b34'>(Oberst et al. , 2019))</ns0:ref>. <ns0:ref type='bibr' target='#b44'>Vlieghe et al. (2015)</ns0:ref> observed a high level of soil or sand sheeting on grasses during the early formation stages of Namibian fairy circles constructed by P. allocerus. In contrast, the lowest number of termites and sheet grasses can be detected in the mature circles, which indicates that termites abandon their ephemeral polycalic nests within the mature circle <ns0:ref type='bibr' target='#b44'>(Vlieghe et al., 2015)</ns0:ref>. Manuscript to be reviewed different purposes according to the situational context. When the wood was unloaded, C. acinaciformis wrapped the dry wood with a layer of clay to increase its moisture levels.</ns0:p><ns0:p>However, when the wood was loaded, C. acinaciformis kept the wood dry to improve its compressive strength and rigidity; meanwhile, they substituted some of the wood for clay walls to improve the bearing capacity. Some previous studies showed that C. formosanus also transported clay to fill the void volumes within tree holes or bait stations <ns0:ref type='bibr'>(Henderson, 2018)</ns0:ref>.</ns0:p><ns0:p>Such behaviors may result from tunnel excavation and subsequent transport processes <ns0:ref type='bibr' target='#b28'>(Li et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b27'>Lee et al., 2020)</ns0:ref>. Some evidence also showed that these behaviors may be important for the foraging of lower subterranean termites because they preferred to aggregate and feed on food which was artificially covered/filled with clay <ns0:ref type='bibr' target='#b46'>(Wang &amp; Henderson, 2014;</ns0:ref><ns0:ref type='bibr' target='#b45'>Wang et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b51'>Xiong et al., 2018a)</ns0:ref>.</ns0:p><ns0:p>Previous studies showed that moisture conditions of substrates are important for the survival of subterranean termites <ns0:ref type='bibr' target='#b40'>(Sponsler &amp; Appel, 1990;</ns0:ref><ns0:ref type='bibr' target='#b10'>Cornelius &amp; Osbrink, 2010;</ns0:ref><ns0:ref type='bibr'>Gautam &amp; Henderson, 2015)</ns0:ref>. For example, <ns0:ref type='bibr' target='#b10'>Cornelius and Osbrink (2010)</ns0:ref> reported that C. formosanus contacted with dry soil had high mortality caused by desiccation. <ns0:ref type='bibr' target='#b18'>Gautam and Henderson (2015)</ns0:ref> reported that C. formosanus individuals showed three stages of desiccation -curling of antennae (stage I), on back but can right themselves and walk (stage II), and unable to get off back (stage III) -soon after exposed to open-air conditions, and most termites were destined to die once they reached stage III. Also, <ns0:ref type='bibr' target='#b18'>Gautam and Henderson (2015)</ns0:ref> reported a colony-level variation in the rate of water loss, since termites from one colony dried out faster than that from other colonies.</ns0:p><ns0:p>Similarly, one of the three termite colonies used in our choice tests had a high mortality rate PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed under low-moisture conditions, probably due to the low drought-tolerance of this colony.</ns0:p><ns0:p>Interestingly, <ns0:ref type='bibr' target='#b18'>Gautam and Henderson (2015)</ns0:ref> showed that termites in the groups (n = 50) had a slower desiccation rate than the individual ones, and suggested that the large densities of field colonies of C. formosanus may contribute to maintaining high humidity levels and reducing water loss. One potential limitation of our studies is that we used only 400 termites in each replicate of the choice tests, and this relatively low density of termites may have an effect on the moisture-maintaining capacity and behaviors of termites, especially under low-moisture conditions. Future experiments with larger groups of termites would be helpful.</ns0:p><ns0:p>Our no-choice tests showed that all types of clay materials significantly increased body water percentage, an important indicator of termite vigor <ns0:ref type='bibr' target='#b0'>(Arquette et al., 2006)</ns0:ref>, compared with soil under low-moisture conditions (Fig. <ns0:ref type='figure'>8B</ns0:ref>). This probably occurred because clay can retain more water than soil (as shown in Table <ns0:ref type='table'>1</ns0:ref>), and created a more favorable microenvironment in the baiting containers. To avoid desiccation, C. formosanus has a strong tendency to aggregate in locations with proper humidity/moisture levels <ns0:ref type='bibr' target='#b32'>(Nakayama et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b15'>Gautam &amp; Henderson, 2011a</ns0:ref><ns0:ref type='bibr' target='#b16'>, 2011b</ns0:ref><ns0:ref type='bibr' target='#b17'>, 2011c)</ns0:ref>. However, they do not prefer substrate and wood with extremely high moisture content <ns0:ref type='bibr' target='#b32'>(Nakayama et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b15'>Gautam &amp; Henderson 2011a)</ns0:ref>. Our choice tests showed that the majority of termites stayed in the wooden cylinders or baiting containers filled with bentonite under low-moisture conditions (Figs. <ns0:ref type='figure'>4 and 6</ns0:ref>). Such preference was moisturedependent, because no significant termite aggregation was detected responding to the 50%moisture bentonite. It is probable that termites can acquire enough water under moderatemoisture conditions. Therefore, it is not necessary to stay within bentonite to maintain moisture. Manuscript to be reviewed Also, bentonite can absorb a large amount of water at the 50%-saturation level (Table <ns0:ref type='table'>1</ns0:ref>), and caused much higher wood moisture compared with other clay materials or soil (Figs. <ns0:ref type='figure'>7C and 8D</ns0:ref>), which may inhibit the feeding activities of C. formosanus. Likewise, <ns0:ref type='bibr' target='#b5'>Carey et al. (2019)</ns0:ref> reported that the mound-building termites, Macrotermes michaelseni (Sj&#246;stedt), performed different clay-relocation behaviors depending on the humidity levels, as they transport less soil and creates structures with smaller volumetric envelopes in the laboratory with low ambient humidity compared with high-humidity conditions.</ns0:p><ns0:p>The present study focused on the clay preference by termites under different moisture conditions. There may be other factors affecting termite behaviors in response to clay materials.</ns0:p><ns0:p>For example, previous research showed that the lower subterranean termites Reticulitermes flavipes (Kollar) can detect certain ions in soil <ns0:ref type='bibr' target='#b4'>(Botch &amp; Judd, 2011)</ns0:ref>, and directly acquire micronutrients such as calcium, magnesium, iron, and manganese from the soil <ns0:ref type='bibr' target='#b22'>(Janzow &amp; Judd, 2015)</ns0:ref>. Our choice tests showed that termites tended to aggregate in wooden cylinders and baiting containers filled with attapulgite and chlorite under moderate-moisture conditions. These clay materials have high contents of exchangeable cations of calcium and magnesium (Table <ns0:ref type='table'>1</ns0:ref>), which may result in the termite aggregation. In addition, previous studies showed that soil microbes such as Metarrhizium anisopliae (Metschn.) Sorok and Trichoderma fungi significantly influenced the aggregation and tunneling preferences of subterranean termites <ns0:ref type='bibr' target='#b52'>(Xiong et al., 2018b;</ns0:ref><ns0:ref type='bibr' target='#b42'>2019;</ns0:ref><ns0:ref type='bibr' target='#b47'>Wen et al., 2020)</ns0:ref>. In our study, different microbes may colonize wooden cylinders or baiting containers containing each clay material and soil, and affect termites' choice. Also, clay may have more biological functions for termites besides creating a PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed moist environment and preventing termites from desiccation. For example, many social insects cover/fill food sources with various materials (e.g., soil particles) to block competitors and predators (e.g., <ns0:ref type='bibr' target='#b29'>Maciel et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b31'>Mendon&#231;a et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b36'>Qin et al., 2019)</ns0:ref>. <ns0:ref type='bibr' target='#b8'>Chouvenc et al. (2015)</ns0:ref> reported that when C. formosanus encountered its predator, the big-headed ant, Pheidole megacephala (Fabr.), termites immediately deposited particles and sealed the access point of ants to 'create a physical separation with little to no casualties'. Clay materials in the void spaces may also protect termites from being exposed to the open-air environment and attacked by ants and other predators. One limitation of our study is that we only tested five clay materials, and many other clay or silt minerals may also affect aggregation and foraging behaviors of C. formosanus. It would be valuable to conduct choice and no-choice tests with more clay and silt materials in the future.</ns0:p><ns0:p>Baiting is one of the main methods to suppress and eliminate populations of subterranean termites <ns0:ref type='bibr' target='#b14'>(Evans &amp; Iqbal, 2015;</ns0:ref><ns0:ref type='bibr' target='#b42'>Su, 2019)</ns0:ref>, but termites showed a low tendency to attack bait with low moisture levels <ns0:ref type='bibr' target='#b11'>(Cornelius &amp; Osbrink, 2011)</ns0:ref>. Our previous studies tried to create a microhabitat more suitable for termites by adding super absorbent polymers into bait stations.</ns0:p><ns0:p>Although these water-retaining materials increased bait consumption, they did not cause significant aggregation by termites, probably because super absorbent polymers are gel-like and therefore termites cannot make tunnels to access the bait matrices <ns0:ref type='bibr' target='#b48'>(Xie et al., 2019a</ns0:ref><ns0:ref type='bibr' target='#b49'>(Xie et al., , 2019b))</ns0:ref>. The present study showed that bentonite filled in the baiting containers not only caused aggregation of termites but also increased wood consumption under low-moisture conditions (Fig. <ns0:ref type='figure'>6A</ns0:ref>). This result indicated that placing bentonite in bait stations may increase termite infestation and bait Manuscript to be reviewed consumption in drought locations. However, it is worth noting that moisture levels in reality may vary locally and fluctuate over time. Also, multiple environmental factors may influence termites' choice in the field. It is important to conduct field studies to confirm whether bentonite can potentially be used as termite attractants under natural conditions.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>In this study, we discovered that termites preferred to aggregate in wooden cylinders or baiting containers filled with bentonite compare with other clay materials (kaolin, chlorite, illite, and attapulgite) under low-moisture conditions. Also, termite consumed significantly more wood in the baiting containers filled with bentonite. Under moderate-moisture conditions, however, chlorite and attapulgite were most preferred by termites. In addition, no-choice tests showed that baiting containers filled with clay materials increased termite survivorship and body water percentage (an indicator of termite vigor) under low-moisture conditions. This study showed that both clay types and moisture are important for the survival and foraging activities of termites, and can influence their aggregation and wood-feeding preferences.</ns0:p><ns0:p>a CEC indicates cation exchange capacity.</ns0:p><ns0:p>b Water saturation level.</ns0:p><ns0:p>c Amount of deionized water (g) can be absorbed by 1 g dry powder of clay to reach the 100%, 50%, or 25% water saturation level. Manuscript to be reviewed Basic information of the three colony groups of Coptotermes formosanus used in the choice and no-choice tests.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed a The percentages of workers and soldiers in each colony group were determined by counting 100 termites for 5 times. The mean percentages are shown here and used to set the experiment.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:p><ns0:note type='other'>Figure 1</ns0:note><ns0:p>Coptotermes formosanus usually transports clay or soil into tree holes (A) and bait stations (B).</ns0:p><ns0:p>The first picture was taken by Wenquan Qin, and the second one was taken by Zhengya Jin.</ns0:p><ns0:note type='other'>Figure 2</ns0:note><ns0:p>Procedures to set experiment 1.</ns0:p><ns0:p>Hollow space of wooden cylinders was either filled with the clay material (chlorite, attapulgite, bentonite, kaolin, or illite) or soil, or remained unfilled (A). Substrate (soil) was added into the container to the depth of 0.5 cm, and seven wooden cylinders were placed on the substrate with randomly assigned orders. Additional substrate was then added until the base of cylinders was partially buried in the depth of 1 cm (B). Pictures were taken by Zhengya Jin.</ns0:p><ns0:note type='other'>Figure 8</ns0:note><ns0:p>Results (mean &#177; SE) of experiment 3 showing the survivorship (A), body water percentage (B), and wood consumption (C) of termites, and wood moisture (D) in each treatment.</ns0:p><ns0:p>Significant differences are indicated by different letters (P &lt; 0.05).</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020) Manuscript to be reviewed arboretum of SCAU where C. formosanus activities have been detected. A sample of soil was sent to the Laboratory of Forestry and Soil Ecology (College of Forestry and Landscape</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc><ns0:ref type='bibr' target='#b34'>Oberst et al. (2019)</ns0:ref> reported that C. acinaciformis performed clay-sheeting behaviors for PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='34,42.52,70.87,366.25,672.95' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='39,42.52,224.62,525.00,408.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='40,42.52,224.62,525.00,408.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='46,42.52,70.87,371.55,672.95' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:06:49998:1:1:NEW 24 Sep 2020)</ns0:note> </ns0:body> "

"Dear Editor, We sincerely thank you and three reviewers for valuable comments on our manuscript. We carefully went through these comments and revised the manuscript accordingly. We are resubmitting the revised manuscript. Following is the response to the comments. Editor: The manuscript is clearly written and, in my opinion, authors may address the reviewers’ requests without the need for running other experiments First of all, since no field-trials have been carried out, more caution should be put in drawing conclusions. Response: We agree with the editor that more caution should be put in drawing conclusions since no field-trials have been carried out. We revised the discussion as follows: “The present study showed that bentonite filled in the baiting containers not only caused aggregation of termites but also increased wood consumption under low-moisture conditions (Fig. 6A). This result indicated that placing bentonite in bait stations may increase termite infestation and bait consumption in drought locations. However, it is worth noting that moisture levels in reality may vary locally and fluctuate over time. Also, multiple environmental factors may influence termites’ choice in the field. It is important to conduct field studies to confirm whether bentonite can potentially be used as termite attractants under natural conditions.” Authors should also better discuss the context of their experiments and provide a comprehensive discussion of other factors that have potentially influenced termites’ choice. Response: We sincerely thank the editor for the valuable comments. We mentioned more factors that may affect termites’ choice in the revised manuscript: “The present study focused on the clay preference by termites under different moisture conditions. There may be other factors affecting termite behaviors in response to clay materials. For example, previous research showed that the lower subterranean termites Reticulitermes flavipes (Kollar) can detect certain ions in soil (Botch & Judd, 2011), and directly acquire micronutrients such as calcium, magnesium, iron, and manganese from the soil (Janzow & Judd, 2015). Our choice tests showed that termites tended to aggregate in wooden cylinders and baiting containers filled with attapulgite and chlorite under moderate-moisture conditions. These clay materials have high contents of exchangeable cations of calcium and magnesium (Table 1), which may result in the termite aggregation. In addition, previous studies showed that soil microbes such as Metarrhizium anisopliae (Metschn.) Sorok and Trichoderma fungi significantly influenced the aggregation and tunneling preferences of subterranean termites (Xiong et al., 2018b; 2019; Wen et al., 2020). In our study, different microbes may colonize wooden cylinders or baiting containers containing each clay material and soil, and affect termites’ choice. Also, clay may have more biological functions for termites besides creating a moist environment and preventing termites from desiccation. For example, many social insects cover/fill food sources with various materials (e.g., soil particles) to block competitors and predators (e.g., Maciel et al., 2015; Mendonça et al., 2019; Qin et al., 2019). Chouvenc et al. (2015) reported that when C. formosanus encountered its predator, the big-headed ant, Pheidole megacephala (Fabr.), termites immediately deposited particles and sealed the access point of ants to “create a physical separation with little to no casualties”. Clay materials in the void spaces may also protect termites from being exposed to the open-air environment and attacked by ants and other predators. One limitation of our study is that we only tested five clay materials, and many other clay or silt minerals may also affect aggregation and foraging behaviors of C. formosanus. It would be valuable to conduct choice and no-choice tests with more clay and silt materials in the future.” It should be also important to specify the physico-chemical properties and size of soil/clay used in the study (I think that specifics may be easily available from manufacturers), and why authors decided to choose such materials (or decided not to consider others, e.g. silt materials). Response: We sincerely thank the editor for the valuable comments. We revised Table 1 and added more information about the physical and chemical properties of clay used in our studies. We also mentioned why we choose the five clay materials in our tests. “Based on the structure and mineralogy, clay can be divided into several mineral groups including the montmorillonite/smectite group, kaolin group, chlorite group, illite group, and palygorskite group. In this study, five common clay materials were selected from these groups to investigate their effects on the survival and behavior of C. formosanus (Table 1).” Please, also consider other relevant literature that may improve the discussion. Response: We sincerely thank the editor for the valuable comments. We cited more literature to improve the discussion. Reviewer 1: Basic reporting All of the main points are met. No comments. Experimental design No comments. All the points are sufficiently met. Validity of the findings No comments. Comments for the Author I found the manuscript to be clearly written, and the science overall relatively sound. I really could not find any critical issues. The one item that could be detailed better in the writing relates to use of the terms 'dry' and 'wet' to describe the moisture levels compared in experiments. 25% moisture is not necessarily 'low' moisture, but is more intermediate, and in some ecosystem or soil types it can be the highest level encountered (e.g., sand). Better ways to refer to 'dry' and 'wet' throughout the manuscript would be low and high since dry and wet is less descriptive. In general I felt the experimental designs and setups were sound, and the interpretations relatively straightforward. The conclusions are appropriate based on the results. Previous reports are both acknowledged and appropriately discussed relative to the current results. I feel some minor revisions around how moisture levels are described should be sufficient to get the final paper ready for publication. Response: We sincerely thank the reviewer for the valuable comments. Here we used two moisture contents (25%- or 50%-moisture) of clay/soil in our choice and non-choice tests. Based on previous studies, the substrate (soil) with 25%-moisture content was very dry and usefully cause the desiccation and death of C. formosanus, while the substrate with 50%-moisture content was proper for the survival and foraging activities of termites. As a result, we used “low-moisture” and “moderate-moisture” to describe the moisture levels in the revised manuscript. Reviewer 2: Basic reporting This is fine. The English is good and there are no serious flaws with the structure or readability of the paper. I have identified below where some change of emphasis in the methods would be helpful Experimental design This is clear but complicated. I hope that the illustrations can go close to the methods, as a diagram is always useful for clarity. Response: We sincerely thank the reviewer for the valuable comments. We revised Figures 2 and 3 to better illustrate the methods. Validity of the findings The findings are interesting and add something useful to our knowledge of how termites move soil around. It is important, however, that a reader does not take away the impression that all lower termites move soil around. Only those that forage outside the nest do it. This means that the families Kalotermitidae, Archotermopsidae, and Stolotermitidae do not produce soil sheeting or shelter tubes. Response: We sincerely thank the reviewer for the valuable comments. We agree that not all lower termites transport soil. We replaced “lower termites” with “lower subterranean termites” in the revised manuscript. Comments for the Author A little more could be made about the choice of the minerals. At the moment, the introduction does not tell us anything about the clay minerals or their water-holding capacities. A few lines explaining why each clay mineral was chosen would help make the paper clearer. Response: We sincerely thank the reviewer for the valuable comments. We mentioned why we choose the five clay materials in the revised manuscript. “Based on the structure and mineralogy, clay can be divided into several mineral groups including the montmorillonite/smectite group, kaolin group, chlorite group, illite group, and palygorskite group. In this study, five common clay materials were selected from these groups to investigate their effects on the survival and behavior of C. formosanus (Table 1).” Reviewer 3: Basic reporting The use of English language is appropriate. Still, the manuscript could benefit from some more proofreading and logical consistency Eg. - check for missed articles 'the Unites States [of America], China,...', with 'a wooden mortar and pestle' Response: We changed “Unites States” to “the United States of America”, and changed “wooden mortar and pestle” to “a wooden mortar and pestle”. - use 'tree vascular tissue' instead of 'plant' Response: We changed “plant vascular tissue” to “tree vascular tissue” - 'was ground' Response: We changed “was grounded” to “was ground”. - '(none of the termites stayed on the outer wall of the wooden cylinders or on the surface of the substrate)' Response: We rewrote the sentence as suggested by the reviewer. - I think you should consider citing 'Oberst et al, Termites manipulate moisture content of wood to maximise feeding, Biology Letters, 15(7). 20190365. https://doi.org/10.1098/rsbl.2019.0365'; since they considered similarly to you the influence of moisture levels on foraging of lower termites (Coptotermes acinaciformis). Also, when it comes to the discussion, this paper should be discussed and the lower and upper bounds of moisture levels relevant to termites (Gautam and Henderson need to be also more discussed in this context). Response: We sincerely thank the reviewer for the valuable comments. This paper is very interesting and we cited this paper in the revised manuscript. “Oberst et al. (2019) reported that C. acinaciformis performed clay-sheeting behaviors for different purposes according to the situational context. When the wood was unloaded, C. acinaciformis wrapped the dry wood with a layer of clay to increase its moisture levels. However, when the wood was loaded, C. acinaciformis kept the wood dry to improve its compressive strength and rigidity; meanwhile, they substituted some of the wood for clay walls to improve the bearing capacity.” T. A. Evans, T. Z. Dawes, P. R. Ward, N. Lo, Ants and termites increase crop yield in a dry climate, Nature Communications 2 (2011) 1–7 provide a valuable reference for ants and termites increasing soil quality especially in more arid climate zones. Response: We sincerely thank the reviewer for the valuable comments. This paper is very interesting and we cited this paper in the revised manuscript. “Likewise, Evans et al. (2011) reported that in the arid climate zones where earthworms are absent, termites provide alternative ecological services to improve water infiltration and soil nitrogen, and therefore contributed to the sustainability of dryland agriculture.” Experimental design I think the experiment is interesting since it focuses on clay properties, but some critical considerations were not taken, and the data /information provided is not fully discussed. Central in the experiment is the choice of clay materials and the number of termites chosen as well as the consequences resulting from that. Especially the novelty of the paper – which lies in using different clay materials is insufficiently presented and the analysis is not going deep enough. The number of termites and their behaviour and ecological and behavioural consequences due to the artificial situation constructed is not discussed in the extend required. Response: We sincerely thank the reviewer for the valuable comments. We revised Table 1 and added more information about the physical and chemical properties of clay used in our studies. We also mentioned why we choose the five clay materials in our tests. “Based on the structure and mineralogy, clay can be divided into several mineral groups including the montmorillonite/smectite group, kaolin group, chlorite group, illite group, and palygorskite group. In this study, five common clay materials were selected from these groups to investigate their effects on the survival and behavior of C. formosanus (Table 1).” We also discussed the number of termites used in our choice tests: “Interestingly, Gautam and Henderson (2015) showed that termites in the groups (n = 50) had a slower desiccation rate than the individual ones, and suggested that the large densities of field colonies of C. formosanus may contribute to maintaining high humidity levels and reducing water loss. One potential limitation of our studies is that we used only 400 termites in each replicate of the choice tests, and this relatively low density of termites may have an effect on the moisture-maintaining capacity and behaviors of termites, especially under low-moisture conditions. Future experiments with larger groups of termites would be helpful.” - Table 1 should be extended in that it is less of interest which company produces those clays, but rather what the different properties are, eg particle size, mineralisation, chemical composition and ionisation. Water retention has been reported, but then the table as well as all figures should be sorted according to the property investigated based on the hypothesis of the authors (eg water absorption) Response: We sincerely thank the reviewer for the valuable comments. We revised Table 1 and added more information about chemical properties of clay used in our studies. - Also, the number of termites seem very small in order to generate a more natural condition – certainly 400 termites are very stressed and limiting the moisture results in changed behaviour. Also, the number of termites has an effect on the moisture in turn and this changes the behaviour – hence, separating single factors is difficult if not impossible. The authors should have shown the same effect for a larger number of termites (why is colony 1 not considered in experiment A? A clear sign of stress in termites). Response: We sincerely thank the reviewer for the valuable comments. One of the three tested colonies had a high mortality rate under low-moisture conditions, which may indicate a colony effect on drought tolerance of termites. We agree with the reviewer that the number of termites may have an effect on the moisture, and therefore may change termite behavior. As suggested by the reviewer, it would be better to conduct laboratory studies with more termites. We discussed these in the revised manuscript. “Also, Gautam and Henderson (2015) reported a colony-level variation in the rate of water loss, since termites from one colony dried out faster than that from other colonies. Similarly, one of the three termite colonies used in our choice tests had a high mortality rate under low-moisture conditions, probably due to the low drought-tolerance of this colony. Interestingly, Gautam and Henderson (2015) showed that termites in the groups (n = 50) had a slower desiccation rate than the individual ones, and suggested that the large densities of field colonies of C. formosanus may contribute to maintaining high humidity levels and reducing water loss. One potential limitation of our studies is that we used only 400 termites in each replicate of the choice tests, and this relatively low density of termites may have an effect on the moisture-maintaining capacity and behaviors of termites, especially under low-moisture conditions. Future experiments with larger groups of termites would be helpful.” - Please describe more in detail how you ensured the quality of the termites collected (I assume due to baiting only mature workers and soldiers were taken) and discuss why colony 1 in experiment A was not considered. I find the ratio very low 1 to 4 % soldiers only? This indicates to me that the baiting station was not property contacted yet (in lower termites of Cop. formosanus it is usually 5-10 % - and rather on the higher end towards 10% see eg The proportion of soldiers in termite colonies: a list and a bibliography (Isoptera) [1977]. Haverty, M.I Response: We sincerely thank the reviewer for the valuable comments. We added more information about termite collection in the revised manuscript. “Underground baiting stations that included 6 pine-wood sticks (without termiticide; 4.5 × 3.0 × 16.0 cm) surrounded by plastic collars (height: 19.5 cm; diameter of upper side: 15.0 cm; diameter of bottom side: 13.5 cm) were buried in different locations of the arboretum of South China Agricultural University (SCAU, Guangzhou, China). C. formosanus infestation in each bait station was checked monthly, and the stations with large numbers of termites were brought to the laboratory (Xiong et al., 2018).” Colonies 1 had a high mortality rate when the moisture was low, probably because this colony was sensitive to the drought conditions, and we did not analyze data obtained from this colony under low-moisture conditions. Haverty (1977) reported that the soldier/worker ratio of entire colonies of C. formosanus was ranging from 5%-10%. The soldier/worker ratios can be affected by many factors such as group sizes (Haverty 1979), seasons (Delaplane et al. 1991), temperature (Waller and LaFage 1988), etc. In our study, the soldier/worker ratios of the foraging groups of C. formosanus collected from the bait stations were ranging from 1%-6%. References: Delaplane KS, Saxton AM, LaFage JP. 1991. Foraging phenology of the Formosan subterranean termite (Isoptera: Rhinotermitidae) in Louisiana. American Midland Naturalist 125: 222-230. Haverty MI. 1977. The proportion of soldiers in termite colonies: A listand a bibliography (Isoptera). Sociobiology 2: 199 -216. Haverty MI. 1979. Soldier production and maintenance of soldier proportions in laboratory experimental groups of Coptotermes formosanus Shiraki. Insectes Sociaux 26: 69-84. Waller DA, LaFage JP. 1988. Environmental influence on soldier differentiation in Coptotermes formosanus Shiraki (Rhinotermitidae). Insectes Sociaux 35: 144-152. Validity of the findings I do not doubt that the results are valid, but the findings need to be very critically discussed considering the situation / context of the experiments. More validation is required with regards to the clays used and more hypothesis should be developed based on other properties than moisture only. The authors should consider running a small field trial and monitoring their results and conditions using data loggers very carefully. Also an experiment with more termites and a larger arena could be used as alternative as I believe that in practice too many factors might influence the results so that the choice of termites in terms of clays cannot be observed. However, if in the field this preference can be observed it is a very strong indication for the correctness of the authors’ hypothesis. Response: We agree with the reviewer that more caution should be put in drawing conclusions since no field-trials have been carried out. We revised the discussion as follows: “The present study showed that bentonite filled in the baiting containers not only caused aggregation of termites but also increased wood consumption under low-moisture conditions (Fig. 6A). This result indicated that placing bentonite in bait stations may increase termite infestation and bait consumption in drought locations. However, it is worth noting that moisture levels in reality may vary locally and fluctuate over time. Also, multiple environmental factors may influence termites’ choice in the field. It is important to conduct field studies to confirm whether bentonite can potentially be used as termite attractants under natural conditions.” - The authors discuss attapulgite and chlorite but why not bentonite? Certainly, the choice of termites is depending on the humidity levels and certain configurations have been found to be advantageous for termites (it is not ‘the more moisture, the better’ – see Gautam and Henderson (2010) or also Oberst et al (2019)). Response: We sincerely thank the reviewer for the valuable comments. We discussed more about bentonite in the revised manuscript. “Our no-choice tests showed that all types of clay materials significantly increased body water percentage, an important indicator of termite vigor (Arquette et al., 2006), compared with soil under low-moisture conditions (Fig. 8B). This probably occurred because clay can retain more water than soil (as shown in Table 1), and created a more favorable microenvironment in the baiting containers. To avoid desiccation, C. formosanus has a strong tendency to aggregate in locations with proper humidity/moisture levels (Nakayama et al., 2005; Gautam & Henderson, 2011a, 2011b, 2011c). However, they do not prefer substrate and wood with extremely high moisture content (Nakayama et al., 2005; Gautam & Henderson 2011a). Our choice tests also showed that the majority of termites stayed in the wooden cylinders or baiting containers filled with bentonite under low-moisture conditions (Figs. 4 and 6). Such preference was moisture-dependent, because no significant termite aggregation was detected responding to the 50%-moisture bentonite. It is probable that termites can acquire enough water under moderate-moisture conditions. Therefore, it is not necessary to stay within bentonite to maintain moisture. Also, bentonite can absorb a large amount of water at the 50%-saturation level (Table 1), and caused much higher wood moisture compared with other clay materials or soil (Figs. 7C and 8D), which may inhibit the feeding activities of C. formosanus.” - The conclusions drawn that bentonite can be used when its drier and attapulgite and chlorite if moist, is flawed, since moisture and humidity levels in reality fluctuate a fair bit and vary locally as well. I question therefore the practicality of the author’s hypothesis. The authors mention in the discussion specifically attapulgite and chlorite? Why not other clay materials? Why not soils? Apart from the logical fallacies, conclusions drawn from this part seem a bit out of the blue and their connection to previous parts appears arbitrary. Response: We agree with the reviewer that it is not proper to draw the conclusions that bentonite can be used in drought locations and attapulgite and chlorite can be used in wet areas. We revised this conclusion in the manuscript. We also discussed more about bentonite and other clay or silt materials in the revised manuscript. “One limitation of our study is that we only tested five clay materials, and many other clay or silt minerals may also affect aggregation and foraging behaviors of C. formosanus. It would be valuable to conduct choice and no-choice tests with more clay and silt materials in the future.” - Also, the wood consumption has not been properly discussed. The results from that part are missing in the result section and should be brought into context with Gautam and Henderson and Oberst et al. which studied in length the wood consumption under different moisture levels and in different situational context. Response: We sincerely thank the reviewer for the valuable comments. We discussed wood consumption in the revised manuscript. “Baiting is one of the main methods to suppress and eliminate populations of subterranean termites (Evans & Iqbal, 2015; Su, 2019), but termites showed a low tendency to attack bait with low moisture levels (Cornelius & Osbrink, 2011). Our previous studies tried to create a microhabitat more suitable for termites by adding super absorbent polymers into bait stations. Although these water-retaining materials increased bait consumption, they did not cause significant aggregation by termites, probably because super absorbent polymers are gel-like and therefore termites cannot make tunnels to access the bait matrices (Xie et al., 2019a, 2019b). The present study showed that bentonite filled in the baiting containers not only caused aggregation of termites but also increased wood consumption under low-moisture conditions (Figure 6A). This result indicated that placing bentonite in bait stations may increase termite infestation and bait consumption in drought locations. However, it is worth noting that moisture levels in reality may vary locally and fluctuate over time. Also, multiple environmental factors may influence termites’ choice in the field. It is important to conduct field studies to confirm whether bentonite can potentially be used as termite attractants under natural conditions.” - I am missing a more comprehensive discussion of other potential factors influencing termite preference in the given situation with regards to other clay properties. The authors started discussing this a bit when they mention fertility of vegetation patches in the desert, but this was not satisfactorily elaborated on. Response: We sincerely thank the reviewer for the valuable comments. We discussed more factors that may affect clay preferences by termites in the revised manuscript. “The present study focused on the clay preference by termites under different moisture conditions. There may be other factors affecting termite behaviors in response to clay materials. For example, previous research showed that the lower subterranean termites Reticulitermes flavipes (Kollar) can detect certain ions in soil (Botch & Judd, 2011), and directly acquire micronutrients such as calcium, magnesium, iron, and manganese from the soil (Janzow & Judd, 2015). Our choice tests showed that termites tended to aggregate in wooden cylinders and baiting containers filled with attapulgite and chlorite under moderate-moisture conditions. These clay materials have high contents of exchangeable cations of calcium and magnesium (Table 1), which may result in the termite aggregation. In addition, previous studies showed that soil microbes such as Metarrhizium anisopliae (Metschn.) Sorok and Trichoderma fungi significantly influenced the aggregation and tunneling preferences of subterranean termites (Xiong et al., 2018b; 2019; Wen et al., 2020). In our study, different microbes may colonize wooden cylinders or baiting containers containing each clay material and soil, and affect termites’ choice. Also, clay may have more biological functions for termites besides creating a moist environment and preventing termites from desiccation. For example, many social insects cover/fill food sources with various materials (e.g., soil particles) to block competitors and predators (e.g., Maciel et al., 2015; Mendonça et al., 2019; Qin et al., 2019). Chouvenc et al. (2015) reported that when C. formosanus encountered its predator, the big-headed ant, Pheidole megacephala (Fabr.), termites immediately deposited particles and sealed the access point of ants to “create a physical separation with little to no casualties”. Clay materials in the void spaces may also protect termites from being exposed to the open-air environment and attacked by ants and other predators.” - Also “N. E. Carey, D. S. Calovi, P. Bardunias, J. S. Turner, R. Nagpal, J. Werfel, Differential construction response to humidity by related species of mound-building termites, Journal of Experimental Biology 222 (2019). doi:10.1242/jeb.212274. “ should be considered and discussed. Response: We sincerely thank the reviewer for the valuable comments. This paper is very interesting and we cited this paper in the revised manuscript. “Likewise, Carey et al. (2019) reported that the mound-building termites, Macrotermes michaelseni (Sjöstedt), performed different clay-relocation behaviors depending on the humidity levels, as they transport less soil and creates structures with smaller volumetric envelopes in the laboratory with low ambient humidity compared with high-humidity conditions.” - It should be very clear in the introduction, what is known about the influence of different clay materials; clays are also categorised according to their particle size which has not at all been discussed. The authors need to thoroughly justify their choice of clay materials. Why did they not look at also silt materials? Silt materials are often reported to be preferred over clay materials, since the shrinkage of silt is less than that of clay. Could this be related to the different purpose of using soil, clay, silt etc; of the different context (building material versus sheeting material, construction for the inner nest versus material used as outer shell etc) – this needs to be discussed, needs a foundation in the methods and then but properly introduced as well as well. Response: We sincerely thank the reviewer for the valuable comments. We mentioned why we choose five clay materials in our tests. “Based on the structure and mineralogy, clay can be divided into several mineral groups including the montmorillonite/smectite group, kaolin group, chlorite group, illite group, and palygorskite group. In this study, five common clay materials were selected from these groups to investigate their effects on the survival and behavior of C. formosanus (Table 1).” Also, we discussed the limitation of our study as follows: “One limitation of our study is that we only tested five clay materials, and many other clay or silt minerals may also affect aggregation and foraging behaviors of C. formosanus. It would be valuable to conduct choice and no-choice tests with more clay and silt materials in the future.” Comments for the Author I believe that some of the figures are not necessary, eg 2B or 3B seem redundant (not much value in seeing the extra layer of soil in C, or better, no value in seeing the setup without the soil). Some figures may be combined; overall the paper could be more focussed; maybe more in the form of a letter or short paper to initiate discussions about the influence of different soil types and their properties on termite foraging decisions considering different situational context. Response: We sincerely thank the reviewer for the valuable comments. We deleted Figures 2B and 3B as suggested by the reviewer. Also, we tried our best to improve the discussion. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background: In this study, we investigated the effect of the mechanical loading history on the expression of receptor activator of nuclear factor kappa B ligand (RANKL) and osteoprotegerin (OPG) in MLO-Y4 osteocyte-like cells.</ns0:p><ns0:p>Methods: Three hours after MLO-Y4 osteocytes were seeded, a continuous compressive force (CCF) of 31 dynes/cm 2 with or without additional CCF (32 dynes/cm 2 ) was loaded onto the osteocytes. After 36 h, the additional CCF (loading history) was removed for a recovery period of 10 h. The expression of RANKL, OPG, RANKL/OPG ratio, cell numbers, viability, and morphology were time-dependently examined at 0, 3, 6, and 10 h. Then, the same additional CCF was applied again for 1 h to all osteocytes with or without the gap junction inhibitor to examine the expression of RANKL, OPG, the RANKL/OPG ratio, and other genes that essential to characterize the phenotype of MLO-Y4 cells. Fluorescence recovery after photobleaching (FRAP) technique was also applied to test the differences of gap-junctional intercellular communications (GJIC) among MLO-Y4 cells.</ns0:p></ns0:div> <ns0:div><ns0:head>Results:</ns0:head><ns0:p>The expression of RANKL and OPG by MLO-Y4 osteocytes without a loading history was dramatically decreased and increased, respectively, in response to the 1-h loading of additional weight. However, the expression of RANKL, OPG, and the RANKL/OPG ratio were maintained at the same level as in the control group in the MLO-Y4 osteocytes with a loading history but without gap junction inhibitor treatment. Treatment of loading history significantly changed the capacity of GJIC and protein expression of connexin 43 (Cx43) but not the mRNA expression of Cx43. No significant difference was observed in the cell number or viability between the MLO-Y4 osteocyte-like cells with and without a loading history or among different time checkpoints during the recovery period. The cell morphology showed significant changes and was correlated with the expression of OPG, Gja1, and Dmp1 during the recovery period.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion:</ns0:head><ns0:p>Our findings indicated that the compressive force-induced changes in the RANKL/OPG expression could be habituated within at least 11 h by 36-h CCF exposure. GJIC and cell morphology may play roles in response to loading history in MLO-Y4 osteocyte-like cells.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Osteocytes are the most abundant (90%-95% of total bone cells in the adult skeleton) and longlived cell type in bone, which are major regulators of bone mechanosensation and mechanotransduction <ns0:ref type='bibr'>(Wang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b21'>Qin et al., 2020)</ns0:ref>. It has been proposed that the bone cell network stores its mechanical loading history, allowing it to adjust its sensitivity to additional mechanical loading or strain <ns0:ref type='bibr'>(Turner et al., 2002)</ns0:ref>.</ns0:p><ns0:p>The loading history reshapes the morphology of trabecular bone and the extracellular matrix surrounding osteocytes, as is described in the well-known Wolff's law <ns0:ref type='bibr' target='#b3'>(Kerschnitzki et al., 2013)</ns0:ref>, which is also known as bone adaptation. The morphology of the extracellular matrix surrounding osteocytes can influence the extracellular fluid-flow shear stress, thereby enhancing the influence of the loading history on the bone <ns0:ref type='bibr'>(Kamioka et al., 2012)</ns0:ref>. Consequently, the osteocyte networks are acclimated to daily mechanical stimuli in which high-magnitude strain occurs rarely, and low-magnitude signals occur much more often to accommodate a daily mechanical loading environment (Fritton, J. <ns0:ref type='bibr'>McLeod &amp; Rubin, 2000)</ns0:ref>. Previous observations showed that extending the loading duration has a diminishing effect on further bone adaptation, and accommodating to a mechanical loading environment in bone cells makes them less responsive to routine or customary loading signals <ns0:ref type='bibr'>(Turner &amp; Pavalko, 1998;</ns0:ref><ns0:ref type='bibr' target='#b24'>Robling, 2012)</ns0:ref>.</ns0:p><ns0:p>Xenopus cardiomyocytes and epidermal cell progenitors can be designed by an evolutionary algorithm in silico and engineered to move in desired patterns, such as drawing a circle or writing English letters <ns0:ref type='bibr' target='#b4'>(Kriegman et al., 2020)</ns0:ref>. However, the lacuna-canalicular system and bone cell network are more complicated than these artificial organisms. Therefore, the bone cell network is considered to be encoded with a unique system for maintaining the history of mechanical stimuli received (Fritton, J. <ns0:ref type='bibr'>McLeod &amp; Rubin, 2000;</ns0:ref><ns0:ref type='bibr'>Turner et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b13'>Moorer &amp;</ns0:ref> PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed <ns0:ref type='bibr' target='#b13'>Stains, 2017)</ns0:ref>. Accumulated evidence has also suggested an additional important role of osteocytes in mobilizing minerals from the surrounding bone matrix via perilacunar/canalicular remodeling <ns0:ref type='bibr' target='#b22'>(Qing et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b8'>Lotinun et al., 2019)</ns0:ref>. Therefore, osteocytes may be the principal regulator for the functional bone adaptation <ns0:ref type='bibr' target='#b29'>(Skedros, Hunt &amp; Bloebaum, 2004;</ns0:ref><ns0:ref type='bibr'>Hazenberg, Lee &amp; Taylor, 2006)</ns0:ref>. Under culture conditions, osteocytes may retain information about their skeletal site of origin. For example, calvarial bone cells are much less sensitive to mechanical stimuli than ulnar bone cells <ns0:ref type='bibr' target='#b23'>(Rawlinson et al., 2009)</ns0:ref>. Repetitive mechanical loads rapidly desensitize bone cells <ns0:ref type='bibr'>(Turner, 1998)</ns0:ref>, indicating that bone tissue can be habituated, reducing its response to repetitive mechanical stimuli. Habituation is a term that describes the decrement in responsiveness to a repetitive stimulus in neuronal systems <ns0:ref type='bibr' target='#b11'>(McDiarmid, Yu &amp; Rankin, 2019)</ns0:ref>.</ns0:p><ns0:p>Osteocytes play a crucial role in bone remodeling by controlling osteoblasts and osteoclasts via the expression of receptor activator of nuclear factor kappa B ligand (RANKL) and its decoy receptor, osteoprotegerin (OPG) <ns0:ref type='bibr' target='#b14'>(Nakashima et al., 2011;</ns0:ref><ns0:ref type='bibr'>Xiong et al., 2011)</ns0:ref>. Recent studies have shown that the main source of RANKL is osteocytes <ns0:ref type='bibr'>(Xiong et al., 2015)</ns0:ref>. Correct osteoclastogenesis relies on a correct RANKL/OPG ratio <ns0:ref type='bibr'>(Capulli, Paone &amp; Rucci, 2014)</ns0:ref>, and osteocytes express both factors at levels comparable with or exceeding those of osteoblasts <ns0:ref type='bibr' target='#b14'>(Bonewald, 2011)</ns0:ref>.</ns0:p><ns0:p>Based on these findings, we hypothesized that osteocytes might be able to encode their loading history, with this encoded loading history regulating their gene expression even under in vitro culture. It has been stated that, in general, the disuse load was under 200 microstrains, the physiological load was between 200 and 2500 microstrains, and the overuse loading range was 2500-5000 microstrains when applying mechanical loads on the skeleton <ns0:ref type='bibr'>(Duncan &amp; Turner, 1995;</ns0:ref><ns0:ref type='bibr' /> PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Verbruggen, <ns0:ref type='bibr'>Vaughan &amp; McNamara, 2012)</ns0:ref>. While, the osteocytes receive more mechanical force since the findings suggested that osteocytes have mechanical signal amplification systems <ns0:ref type='bibr'>(Takano-Yamamoto, 2014)</ns0:ref>. The application of 2000 microstrains macroscopically to a piece of bone resulted in a much greater microscopic strain surrounding the osteocyte lacunae of over 30000 microstrains <ns0:ref type='bibr' target='#b15'>(Nicolella et al., 2006)</ns0:ref>. A past study used finite element modeling analysis which reported that global compressive loads of 150 microstrains (disuse), 1000 microstrains (physiological), 3000 microstrains (overuse), and 5000 microstrains (pathological overload) resulted in the maximum principal strains of 633, 4272, 12820, and 21528 microstrains respectively <ns0:ref type='bibr'>(Wang, Dong &amp; Xian, 2018)</ns0:ref>. A previous study already measured the Young's modulus of MLO-Y4 osteocyte-like cells as 1.98 &#177; 0.25 kPa and changed very slightly at a variant indentation range (500nm-1000nm) by using atomic force microscopy <ns0:ref type='bibr'>(Wu et al., 2017)</ns0:ref>.</ns0:p><ns0:p>Therefore, we applied approximate 3.1 Pa (resulted in 3.1 Pa/1.98 kPa &#8776; 1566 microstrains) and 6.3 Pa (resulted in 6.3 Pa/1.98 kPa &#8776; 3182 microstrains) compressive force to MLO-Y4 osteocytelike cells to simulate the bending loads-caused compressive stress in vivo within the pathological load range.</ns0:p><ns0:p>In the present study, MLO-Y4 osteocyte-like cells were proliferated under a continuous compressive force (&#8776; 3.1 Pa or 31 dynes/cm 2 ) throughout the entire experiment after seeding the cells 3 h. A long-duration (36 h) additional continuous compressive force (CCF) at 3.2 Pa was applied as the treatment of loading history, followed by re-applying the same additional CCF (&#8776; 3.2 Pa or 32 dynes/cm 2 ) for a short duration (1 h), to assess the effect of loading history on the expression of interesting genes as well as the cell number, viability, morphology, and cell-to-cell communications of MLO-Y4 osteocyte-like cells.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Cell culture and reagents</ns0:head><ns0:p>The MLO-Y4 cell line was purchased from Kerafast (Boston, MA, USA). MLO-Y4 cells (at 39 passages), an osteocyte-like cell line derived from the long bone of a transgenic female mouse containing the osteocalcin promoter driving SV40 T-antigen <ns0:ref type='bibr' target='#b2'>(Kato et al., 1997)</ns0:ref>, were seeded onto the type I collagen-coated 24-well plates and cultured in alpha-modified Eagle's minimal essential medium (&#945;-MEM; Thermo Fisher Scientific, Waltham, MA, USA) containing 5.0% heatinactivated fetal bovine serum (HIFBS; HyClone Laboratories, Logan, UT, USA), 5.0% fetal calf serum (FCS; HyClone), 100 U/ml penicillin, and 100 mg/ml streptomycin (Thermo Fisher Scientific) at 37 &#176;C with 5% CO 2 . MLO-Y4 cells express a high level of connexin 43 (Cx43), early osteocyte markers, such as podoplanin (Pdpn, also know at E11), Osteocalcin (OCN), and low levels of some mature osteocyte markers, such as sclerostin (Sost) and dentin matrix protein 1 (Dmp1) <ns0:ref type='bibr'>(Yang et al., 2009;</ns0:ref><ns0:ref type='bibr'>Dallas, Prideaux &amp; Bonewald, 2013;</ns0:ref><ns0:ref type='bibr' target='#b27'>Sato et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The gap junction inhibitor 18&#945;-glycyrrhetinic acid (18&#945;-GA) and dimethyl sulfoxide (DMSO) were purchased from Sigma-Aldrich (St. Louis, MO, USA). The following antibodies were used: Rabbit anti-Cx43 polyclonal antibody (Cell Signaling, #3512), Rabbit anti-phospho-Cx43 (Ser368; pCx43) polyclonal antibody (Cell Signaling, #3511), Goat anti-Sost polyclonal antibody (R&amp;D system, AF1589), Mouse anti-&#946;-actin monoclonal antibody (Sigma-Aldrich, A5441), HRP-linked Goat anti-Rabbit IgG (Cell Signaling, #7074S), HRP-linked Rabbit anti-Goat IgG polyclonal antibody (R&amp;D system, HAF017), HRP-linked Goat anti-Mouse IgG polyclonal antibody (Millipore, AP124P), Alexa Fluor &#174; 594 phalloidin (ThermoFisher, A12381), and Alexa</ns0:p><ns0:p>Fluor &#174; 488 linked Goat anti-Rabbit polyclonal antibody (ThermoFisher, A11008) used for Western blotting or immunofluorescence staining with MLO-Y4 osteocyte-like cells.</ns0:p></ns0:div> <ns0:div><ns0:head>Habituation experiment with CCF</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The entire experiment design is shown in Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>. MLO-Y4 cells were seeded onto the type I collagen-coated 24-well plate, 60-mm culture dish, or 35-mm glass-bottom (glass diameter: 14 mm) plastic dish at 2.63&#215;10 4 cells/cm 2 . Three hours after seeding the MLO-Y4 cells, a round micro-cover glass (Fig. <ns0:ref type='figure' target='#fig_5'>1A</ns0:ref>; MATSUNAMI, Japan; area, 78.54 mm 2 ; height, 0.21 mm; diameter,10 mm; volume, 16.49 mm 3 ; weight, 0.041 g) or an assembly of two pieces of the normal cover glass (Fig. <ns0:ref type='figure' target='#fig_5'>1A</ns0:ref>; MATSUNAMI, Japan; area, 960 mm 2 ; height, 0.14 mm; volume, 202.16 mm 3 ; weight, 0.505 g) was placed onto the MLO-Y4 cells as the background CCF of 31 dynes/cm 2 . As additional CCF, a modified 200-&#181;l pipette tip (Fig. <ns0:ref type='figure' target='#fig_5'>1A</ns0:ref>; density, 0.92 g/cm 3 ; height, 16 mm; volume, 28.26 mm 3 ; weight, 0.211 g) was placed onto the micro-cover glass. The modified 200-&#181;l pipette tip itself generated 32 dynes/cm 2 CCF when it was immersed into the well of the 24-well plate with 2.1 ml culture media. Therefore, as shown in Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>, the MLO-Y4 cells in the loading history group were grown under a total of 63 dynes/cm 2 CCF, while the cells in the control group were grown under only the background CCF (31 dynes/cm 2 ).</ns0:p><ns0:p>After maintaining the MLO-Y4 cells under additional CCF for 36 h, the additional CCF was removed for 10 h (recovery period) before the same additional CCF was applied again for another hour. One hour before applying the additional CCF again for an extra hour, 3.0 &#181;M 18&#945;-GA or 0.1% DMSO was added and kept in the medium until the end of this experiment (Fig. <ns0:ref type='figure' target='#fig_5'>1B</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Calcein-acetoxymethyl ester (Calcein-AM) and Hoechst 33342 staining</ns0:head><ns0:p>During the 10-h recovery period, the cell number and viability were examined at 0, 3, 6, and 10 h using Calcein-AM and Hoechst 33342 staining. The micro-cover glasses were removed 15 minutes prior to each time checkpoint, and the cells were loaded with 1.25 &#181;M Calcein-AM and 1 &#181;g/ml Hoechst 33342 in the culture media for 15 minutes. Fluorescent and phase-contrast images of the area that had been under the micro-cover glass were then taken with a KEYENCE BZ-9000</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed fluorescence microscope (KEYENCE, Osaka, Japan) using a 20x phase-contrast lens.</ns0:p></ns0:div> <ns0:div><ns0:head>Cell numbers, viability, and morphological measurements</ns0:head><ns0:p>After routine background correction using the ImageJ/Fiji software program <ns0:ref type='bibr' target='#b28'>(Schindelin et al., 2012)</ns0:ref>, the background was neutralized using the 'subtract background' <ns0:ref type='bibr' target='#b30'>(Sternberg, 1983)</ns0:ref> feature of the ImageJ/Fiji tool. Finally, the number of cells with positive staining for Calcein-AM and</ns0:p><ns0:p>Hoechst 33342 and the cell morphological results were analyzed using the 'Analyze Particles' function after auto-thresholding with the default method in the ImageJ/Fiji tool. Cell numbers were defined as the number of cell nuclei with positive staining on Hoechst 33342. The viable cell number was defined as the number of cells with positive staining on both Calcein-AM or Hoechst 33342.</ns0:p><ns0:p>For the cell morphology, the aspect ratio, circularity, and solidity were measured. The aspect ratio was defined as the ratio of the major axis to the minor axis of the best-fitted ellipse.</ns0:p><ns0:p>Circularity was defined as the 4&#960; &#215; cell area / perimeter 2 . Solidity was defined as the ratio of the cell area to the convex area.</ns0:p><ns0:p>Reverse transcription and quantitative real-time polymerase chain reaction (qRT-PCR) Total RNA was extracted using ISOGEN (Nippon Gene, Tokyo, Japan) and was used to synthesize complementary DNA (cDNA) with a ReverTra Ace qRT-PCR Kit (FSQ-201; Toyobo Co., Ltd., Osaka, Japan) in the total RNA concentration of 100 ng/&#181;l. The resulting cDNA products were diluted 5 times using pure water, and 1 &#181;l of 5 times diluted-cDNA product was used as a template to quantify the relative content of messenger RNA (mRNA) by a qRT-PCR using SYBR &#174; Green Real-time PCR Master Mix <ns0:ref type='bibr'>Toyobo Co.,</ns0:ref><ns0:ref type='bibr'>Ltd.,</ns0:ref><ns0:ref type='bibr'>Osaka,</ns0:ref><ns0:ref type='bibr'>Japan)</ns0:ref>. The relative levels of the PCR products were determined using a LightCycler System (Roche Diagnostics, Mannheim,</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed org/10.17632/2yfd2w8jfp.1#file-c35071d0-dec9-47c0-84dc-351288a8356c). Differences in gene expression levels following treatment were calculated using the 2 &#8722;&#916;&#916;Ct method after normalization within each sample of interesting gene expression levels against the expression levels of the reference genes (Gapdh).</ns0:p></ns0:div> <ns0:div><ns0:head>Fluorescence recovery after photobleaching (FRAP) assay and immunofluorescence staining</ns0:head><ns0:p>The MLO-Y4 osteocyte-like cells cultured in the glass-bottom dish were loaded with 1.25 &#181;M Calcein-AM 1 h prior to the time point (45 h in Fig 1B <ns0:ref type='figure'>)</ns0:ref> of re-applying CCF. The culture medium was refreshed two hours after loading with Calcein-AM, then the FRAP assay was performed alternately among the normal group (without cover glass and pipette tip), control group (cultured with glass only), loading history group (cultured with glass and pipette tip after loading history treatment), and CCF group (cultured with glass and pipette without loading history treatment) within 90 minutes. FLUOVIEW FV500 confocal laser scanning microscopy (CLS) system (Olympus, Tokyo, Japan) equipped for differential interference contrast (DIC) microscopy. The CLS microscopy system was coupled to an inverted microscope (IX-71; Olympus) with a &#215;60 (N.A. = 1.4) oilimmersion objective lens. The scanning rate was 1.66 s/scan for a 16-bit image, 512 &#215; 512 pixels in size. An MLO-Y4 cell surrounded by other cells under the cover glass (if applied), which was confirmed by the DIC view, was chosen for photobleaching. The boundary was enclosed and outlined with a rectangular region-of-interest tool. A predefined three-step FRAP procedure was automatically executed at a scan speed of 1.66 s/scan on the largest cross section of the target cell.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>In the first step, a prebleached image of the whole field was taken using a low laser intensity (AOTF = 10%, zoom = &#215;1). The laser intensity was then increased&#215;100 (AOTF=100%, zoom=&#215;40), and the target cell was photobleached 1 time for about 2-3 s (depending on the area of the target cell). Finally, the laser intensity and zoom were immediately reset to the prebleach levels (AOTF = 10%, zoom= &#215;1), and time-lapse images were acquired with an interval of 15 s.</ns0:p><ns0:p>The average intensity at each imaging time point was measured for three regions of interest:</ns0:p><ns0:p>the bleached target cell ( ), all other cells in the image field ( ) as control, and the non-fluorescent</ns0:p><ns0:formula xml:id='formula_0'>&#119868; &#119905; &#119879; &#119905;</ns0:formula><ns0:p>region outside of all of the cells for background subtraction (BG) using the 'Time Series Analyzer' tool of ImageJ software (https://imagej.nih.gov/ij/plugins/time-series.html). The fluorescence intensity of the target osteocyte (F) was normalized as follows <ns0:ref type='bibr' target='#b17'>(Phair, Gorski &amp; Misteli, 2003)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_1'>&#119865; &#119905; = (&#119879; prebleach -BG)(&#119868; &#119905; -BG) (&#119879; &#119905; -BG)(&#119868; prebleach -BG)<ns0:label>(1)</ns0:label></ns0:formula><ns0:p>The replacement of fluorescence within a bleached cell ( ) was calculated using the &#119877; &#119905; following equation <ns0:ref type='bibr'>(Ishihara et al., 2008;</ns0:ref><ns0:ref type='bibr'>Wang et al., 2016)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_2'>&#119877; &#119905; = [(&#119865; &#119905; -&#119865; 0 )/(&#119865; &#119894; -&#119865; 0 )] &#215; 100 (%) (2)</ns0:formula><ns0:p>The percent replacement was defined as the fraction of molecules that were replaced during the time-course of the experiment. is the normalized fluorescence intensity at the time (t) after &#119865; &#119905; photobleaching by Eq. 1. is the normalized fluorescence immediately after photobleaching.</ns0:p><ns0:formula xml:id='formula_3'>&#119865; 0 &#119865; &#119894;</ns0:formula><ns0:p>is the initial fluorescence intensity before photobleaching. Recovery curves could be analyzed for passive transport of fluorescent dyes through MLO-Y4 osteocyte-like dendritic processes connected by gap junctions. Its kinetics follow the equation <ns0:ref type='bibr'>(Wade, Trosko &amp; Schindler, 1986)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_4'>&#119877; &#119901; -&#119877; &#119905; &#119877; &#119901; -&#119877; 0 = &#119890; -&#119896;&#119905; (3)</ns0:formula><ns0:p>where , , and , are replacement of fluorescence in the bleached target cell at plateau &#119877; &#119901; &#119877; 0 &#119877; &#119905; (equilibrium), zero time, and time (t) after bleaching, respectively. The Eq. 3 could be rearranged as , which is also called one-phase exponential association</ns0:p><ns0:formula xml:id='formula_5'>&#119877; &#119905; = &#119877; 0 + (&#119877; &#119901; -&#119877; 0 ) &#215; (1 -&#119890; -&#119896;&#119905; )</ns0:formula><ns0:p>equation. The parameter of k and were estimated by a curve fit in Graphpad Prism software &#119877; &#119901; (GraphPad Software, Inc., San Diego, CA, USA).</ns0:p><ns0:p>If we ignore the replacement of fluorescence during the photobleaching period, we could take the as the mobile fraction ( ). The rate coefficient k is positively related to the permeability</ns0:p><ns0:formula xml:id='formula_6'>&#119877; &#119901; f m coefficient of calcein.</ns0:formula><ns0:p>To verify the protein expression of Cx43 and gap-junctional connections between MLO-Y4 cells, an immunofluorescence staining was performed. MLO-Y4 osteocyte-like cells on a glass-bottom dish were fixed with 4% paraformaldehyde in phosphate-buffered saline (PBS) for 10 min, then permeabilized by incubation in 0.5% Triton X-100 in PBS for 10 min. The cells were blocked with Blocking One Histo (Nacalai tesque, Osaka, Japan) for 8 min at RT. After blocking, the cells were incubated with Rabbit anti-Cx43 polyclonal antibody (overnight at 4 &#176;C), Alexa</ns0:p><ns0:p>Fluor &#174; 488 linked Goat anti-Rabbit polyclonal antibody (1 h at RT), Alexa Fluor &#174; 594 phalloidin</ns0:p><ns0:p>(1 h at RT), and Hoechst 33342 (10 min at RT) in PBST containing 1% bovine serum albumin (BSA; Sigma-Aldrich, St. Louis, MO, USA). The cells were rinsed three times with PBST after each above-mentioned step.</ns0:p></ns0:div> <ns0:div><ns0:head>Western blot analyses</ns0:head><ns0:p>After the above-mentioned habituation experiment with CCF, the cells were washed with cold PBS and lysed with a lysate buffer (1 mM Dithiothreitol, 1mM Phenylmethylsulfonyl</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>MLO-Y4 cells maintained high viability under both 31 and 63 dynes/cm 2 for at least 36 h</ns0:head><ns0:p>As Figure <ns0:ref type='figure'>2A</ns0:ref> and B show, the MLO-Y4 cells survived under both 31 and 63 dynes/cm 2 CCF for at least 36 h. No significant differences in the cell number (239 cells/mm 2 on average in Fig. <ns0:ref type='figure'>3A</ns0:ref>)</ns0:p><ns0:p>or viability (93.67% on average in Fig. <ns0:ref type='figure'>3B</ns0:ref>) under the micro-cover glass were observed between the MLO-Y4 osteocytes with and without a loading history or among different time checkpoints during the recovery period.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The morphology changed during the recovery period Figure <ns0:ref type='figure'>2C</ns0:ref> shows an example of the morphological measurements. At the end of this 10 h recoverperiod, the aspect ratio was significantly increased only in the MLO-Y4 osteocytes without a loading history (median aspect ratio of 1.7 vs. 2.0 with FDR value less than 0.001 in Fig. <ns0:ref type='figure'>4A</ns0:ref>). The circularity of MLO-Y4 osteocytes with a loading history was lower than that of the cells without a loading history immediately after removing the additional weight but ultimately returned to the same level after the 10-h recovery period (Fig. <ns0:ref type='figure'>4B</ns0:ref>). The solidity (cell area / convex area) of the MLO-Y4 osteocytes with a loading history was lower than that of the cells without a loading history after the 10-h recovery period but the same level as when immediately removing the additional weight (Fig. <ns0:ref type='figure'>4C</ns0:ref>). Similarly to the solidity, the cell area did not show any significant differences between the MLO-Y4 cells under 63 dynes/cm 2 and 31 dynes/cm 2 CCF for 36 h, although the cell area was significantly different after the 10-h recovery period (Fig. <ns0:ref type='figure'>4D</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>The expression of most of the expression of our interesting genes recovered to the control level after removal of the mechanical stimuli</ns0:head><ns0:p>The mRNA expression of RANKL, OPG, Gja1, and Pdpn was decreased, and the RANKL/OPG ratio, Sost, Dmp1, and OCN higher in the MLO-Y4 osteocyte-like cells under 63 dynes/cm 2 than in those under 31 dynes/cm 2 (Fig. <ns0:ref type='figure' target='#fig_7'>5</ns0:ref>). After changing the CCF from 63 dynes/cm 2 back to 31 dynes/cm 2 for 3 h, the mRNA expression of RANKL, Gja1, Dmp1, Pdpn, and OCN recovered back to the same level as in the MLO-Y4 osteocyte-like cells under 31 dynes/cm 2 (Figs. <ns0:ref type='figure' target='#fig_7'>5A, D, F, G, and H</ns0:ref>), but the mRNA expression of OPG increased, so the RANKL/OPG ratio consequently decreased (Fig. <ns0:ref type='figure' target='#fig_7'>5C</ns0:ref>). Ultimately, the expression of RANKL and OPG and the RANKL/OPG ratio returned to the same level as in the control group after changing the CCF from 63 dynes/cm 2 back</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed to 31 dynes/cm 2 for 10 h (Figs. <ns0:ref type='figure' target='#fig_7'>5A-C</ns0:ref>). However, the mRNA expression of Sost still higher in the cells previously under 63 dynes/cm 2 than in those only under 31 dynes/cm 2 even after changing the CCF from 63 dynes/cm 2 back to 31 dynes/cm 2 for 10 h (Fig. <ns0:ref type='figure' target='#fig_7'>5E</ns0:ref>). Notably, the mRNA expression of Dmp1 was suddenly increased in the cells previously under 63 dynes/cm 2 (with loading history) at the end of this 10-h recovery period (Fig. <ns0:ref type='figure' target='#fig_7'>5F</ns0:ref>).</ns0:p><ns0:p>The expression profiles of OPG, Gja1, and Dmp1 were significantly correlated with the cell morphological changes during the recovery period</ns0:p><ns0:p>The mRNA expression profile of OPG, Gja1, and Dmp1 was significantly correlated with the morphological changes in circularity, solidity, or area during the 10-h recovery period (Figs. <ns0:ref type='figure' target='#fig_7'>5I-L</ns0:ref>). Interestingly, more significant changes of all of the solidity (Fig. <ns0:ref type='figure'>4C</ns0:ref>), area (Fig. <ns0:ref type='figure'>4D</ns0:ref>), and the mRNA expression profile of Dmp1 (Fig. <ns0:ref type='figure' target='#fig_7'>5F</ns0:ref>) were observed at the end of the 10-h recovery period.</ns0:p><ns0:p>Please note that the Pearson's Correlation Coefficient was calculated using the mean value of both morphological changes and mRNA expression fold change, but the linear regression test was performed using the individual mRNA expression fold change against the mean value of morphological changes.</ns0:p></ns0:div> <ns0:div><ns0:head>The loading history reduced the responsiveness when the same CCF was applied again but could be influenced by gap junctional inhibitor</ns0:head><ns0:p>The mRNA expression of RANKL, OPG, and the RANKL/OPG ratio in the MLO-Y4 osteocytes without a loading history was dramatically changed (i vs. iii in Fig. <ns0:ref type='figure' target='#fig_8'>6A-C</ns0:ref>) in response to the new 1-h application of additional weight loading, but no significant changes were observed in the MLO-Y4 osteocyte-like cells with a loading history (i vs. ii in Fig. <ns0:ref type='figure' target='#fig_8'>6A-C</ns0:ref>). However, the expression of RANKL, OPG, and the RANKL/OPG ratio remained at the same level as in the control group in the MLO-Y4 osteocyte-like cells with a loading history (i vs. ii in Figs. <ns0:ref type='figure' target='#fig_8'>6A-C</ns0:ref>), but similar findings were not found in the MLO-Y4 osteocyte-like cells treated with gap junction inhibitor (v vs. viii in Figs. <ns0:ref type='figure' target='#fig_8'>6A-C</ns0:ref>). In other words, the mRNA expression of RANKL, OPG, and the RANKL/OPG ratio was habituated by a 36-h CCF and was disrupted by junction inhibitor. Notably, 18&#945;-GA treatment reduced the RANKL/OPG ratio by decreasing the RANKL expression (iv vs. v in Figs. <ns0:ref type='figure' target='#fig_8'>6A and B</ns0:ref>). However, in response to the new application of 1-h loading of additional weight in the MLO-Y4 osteocyte-like cells without a loading history (i vs. iii and v vs. vii in Figs. <ns0:ref type='figure' target='#fig_8'>6A-C</ns0:ref>), the mRNA expression of OPG showed a similar tendency to that in the MLO-Y4 osteocytes with 18&#945;-GA (comparing i vs. iii with v vs. vii in Figs. 6B), but the changes in the MLO-Y4 osteocytes with 18&#945;-GA were less significant than the MLO-Y4 osteocytes without a loading history (comparing i vs. iii with v vs. vii in Figs. 6B). Interestingly, the increased RANKL, the decreased OPG, and the increased RANKL/OPG ratio were observed in the 18&#945;-GAtreated MLO-Y4 osteocyte-like cells with a loading history in response to the re-application of 1h loading of additional weight (v vs. viii in Figs. <ns0:ref type='figure' target='#fig_8'>6A-C</ns0:ref>), a finding that was completely the opposite of that in MLO-Y4 osteocyte-like cells without both 18&#945;-GA treatment and loading history(comparing i vs. iii with v vs. viii in Figs. <ns0:ref type='figure' target='#fig_8'>6A-C</ns0:ref>).</ns0:p><ns0:p>Whereas, the rest of our interesting genes (Figs. <ns0:ref type='figure' target='#fig_8'>6D-H</ns0:ref>) did not show such obvious habituation phenomena or opposite trend between with and without 18&#945;-GA in response to the new 1-h application of additional weight loading as described above. However, the increase of mRNA expression of Sost and OCN in the MLO-Y4 osteocyte-like cells with a loading history is less than that in the MLO-Y4 osteocyte-like cells without a loading history (ii vs. iii in Figs. <ns0:ref type='figure' target='#fig_8'>6E and H</ns0:ref>). In other words, the mRNA expression of Sost and OCN showed sensitivity to the treatment of loading history (ii vs. iii in Figs. <ns0:ref type='figure' target='#fig_8'>6E and H</ns0:ref>).</ns0:p><ns0:p>18&#945;-GA blocks the gap-junctional intercellular communications (GJIC), which was shown in our previous studies <ns0:ref type='bibr'>(Kamioka et al., 2007;</ns0:ref><ns0:ref type='bibr'>Ishihara et al., 2008)</ns0:ref>. However, the mode of inhibitory action of GA is still not completely understood <ns0:ref type='bibr'>(Willebrords et al., 2017)</ns0:ref>. Direct interaction between 18&#945;-GA and gap junctions (GJs) is possible when the former is inserted into the plasma membrane, thereby binding to GJs and causing a conformational alteration <ns0:ref type='bibr'>(Willebrords et al., 2017)</ns0:ref>. Other possibilities include changes in the connexin phosphorylation status, which led to a reduction in connexin expression <ns0:ref type='bibr'>(Willebrords et al., 2017)</ns0:ref>. Our results (iv vs. v in Fig. <ns0:ref type='figure' target='#fig_8'>6D</ns0:ref>, P-value &lt;0.05 by unpaired t-test which did not show) also showed a reduction of Gja1, which were in good agreement with the previous results <ns0:ref type='bibr'>(Willebrords et al., 2017)</ns0:ref>, although this reduction did not show significance by Fisher's LSD due to the big pooled variance.</ns0:p></ns0:div> <ns0:div><ns0:head>Intercellular gap-junctional communications (GJIC) and Cx43 accumulation was reduced by loading history</ns0:head><ns0:p>The GJIC among the MLO-Y4 osteocyte-like cells was confirmed by the immunofluorescence staining of Cx43 and FRAP assay (Figs. <ns0:ref type='figure' target='#fig_10'>7A and B</ns0:ref> Manuscript to be reviewed suggested a significant influence of the loading history on the fluorescence recover curve. The MLO-Y4 osteocyte-like cells without loading history showed a sharper recover curve and higher coefficient k than that with loading history. In other words, the loading history disrupted the CCFcaused GJIC increase. High R 2 values shown in Figure <ns0:ref type='figure' target='#fig_10'>7F</ns0:ref> suggested a good fitness of the actual recover curve to the theoretically predicted curve (Fig. <ns0:ref type='figure' target='#fig_10'>7C</ns0:ref>). No significant differences were observed in the number of neighboring cells, which implied that the GJIC differences among groups in this study were not caused by the different number of neighboring cells.</ns0:p><ns0:p>The ratio of pCx43 to total Cx43 was unchanged among the different treatment of mechanical stimuli (Fig. <ns0:ref type='figure' target='#fig_11'>8A and D</ns0:ref>). Although the mRNA expression of Sost showed sensitivity to the treatment of loading history (ii vs. iii in Fig. <ns0:ref type='figure' target='#fig_8'>6E</ns0:ref>), the protein expression of Sost did not show significant differences between the MLO-Y4 osteocyte-like cells with and without loading history (ii vs. iii in Figs. <ns0:ref type='figure' target='#fig_11'>8A and E</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>In this study, the phenotype of MLO-Y4 cells was confirmed by checking the mRNA expression of Pdpn, Cx43, RANKL, OCN, Dmp1, Sost, and OPG, respectively, with the average C t values of <ns0:ref type='bibr'>18.13, 19.75, 22.22, 23.74, 28.93, 30.74, and 33.92</ns0:ref> <ns0:ref type='figure' target='#fig_11'>dfdc8c8cf309</ns0:ref>). The protein expression of Cx43 and Sost was confirmed by Western blot (Fig. <ns0:ref type='figure' target='#fig_11'>8A</ns0:ref>). The GJIC was confirmed by the FRAP assay and immunofluorescence staining of Cx43 (Fig. <ns0:ref type='figure' target='#fig_10'>7A and B</ns0:ref>). The dendritic cellular processes were also observed (Figs. <ns0:ref type='figure' target='#fig_10'>2, 7A, and B</ns0:ref>). Therefore, the MLO-Y4 cells used in this study were characterized as the osteocyte-like cells.</ns0:p><ns0:p>Our results showed that MLO-Y4 cells maintained high viability under both 31 and 63</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed dynes/cm 2 for at least 36 h (Fig. <ns0:ref type='figure'>3B</ns0:ref>); however, the proliferation may be inhibited. The grown area covering each well of the 24-well plate was 1.9 cm 2 , so the estimated cell number in total was 45,410 cells/well, based on our results shown in Figure <ns0:ref type='figure'>3A</ns0:ref> (239 cells/mm 2 ), which was even smaller than our seeding density (50,000 cells/well). The difference in the density between the MLO-Y4 cells grown under a cover glass and without a cover glass was very obvious at the edge of the cover glass (supplementary Fig. <ns0:ref type='figure'>2</ns0:ref>). This may be because placing the cover glass directly on the cell may have created a relatively sealed environment that reduced nutrition. This relatively sealed environment is similar to the environment of mineralized tissue. Moreover, this condition also reduced the proliferation of MLO-Y4 osteocytes that may impact the cell morphology and gene expression profile. A previous microarray study showed that the MLO-Y4 osteocytes had a different gene expression profile between conditions of low and high cell density <ns0:ref type='bibr'>(Yang et al., 2009)</ns0:ref>. Cell density may also influence cell morphology. A relatively sealed environment combined with the inhibition of proliferation ultimately created an ideal condition for us to observe the cell morphological changes during the 10-h recovery period after 36-h additional CCF exposure.</ns0:p><ns0:p>In the current study, we developed an in vitro platform mimicking the habituation phenomena observed in in vivo or ex vivo bone tissues that provide a more economic and convenient approach to investigating the possible mechanism of encoding the loading history in osteocytes. With this platform, all MLO-Y4 osteocytes were grown under background CCF, which is similar to the in vivo conditions, as all osteocytes in our bodies are growing under a complicated loading environment <ns0:ref type='bibr'>(Turner, 1998)</ns0:ref>. Unlike to hydrostatic pressure, compressive pressure generates the uniaxial deformation that is also an important mechanical type received by osteocytes in vivo by daily activities <ns0:ref type='bibr'>(Duncan &amp; Turner, 1995)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>In vitro cultured MLO-Y4 osteocytes were successfully habituated</ns0:head><ns0:p>The reduced responsiveness of the RANKL/OPG expression to the re-application of the same CCF was diminished in the MLO-Y4 osteocytes with a loading history, suggesting that the in vitro cultured MLO-Y4 osteocytes could be habituated by 36-h CCF application in a loading environment with background CCF (comparing i vs. iii with i vs. ii in Figs. <ns0:ref type='figure' target='#fig_8'>5A-C and 6A-C</ns0:ref>).</ns0:p><ns0:p>Loading history significantly suppressed the CCF-induced increase of mRNA expression of Sost and OCN (ii vs. iii in Figs. <ns0:ref type='figure' target='#fig_8'>6E and H</ns0:ref>). However, no significant differences in protein expression changes (iii vs. iv in Figs. <ns0:ref type='figure' target='#fig_11'>8A and E</ns0:ref>) in Sost between the MLO-Y4 osteocyte-like cells with and without loading history in response to the application of the additional loading weight for 1 h.</ns0:p><ns0:p>Treatment of loading history reversed the response of the protein expression of Cx43 and GJIC to the re-application of the same CCF for 1 h (comparing ii vs. iii with ii vs. iv in Figs. <ns0:ref type='figure' target='#fig_10'>7C-D</ns0:ref> and 8A-B). However, the treatment of loading history did not show any significant influences on the mRNA expression of Cx43 (ii vs. iii in Fig. <ns0:ref type='figure' target='#fig_8'>6D</ns0:ref>).</ns0:p><ns0:p>It is well documented that mechanical stimuli changed the protein secretion in many other types of cells <ns0:ref type='bibr' target='#b0'>(Apodaca, 2002)</ns0:ref>. Since the Sost is a secreted protein <ns0:ref type='bibr' target='#b20'>(Poole et al., 2005)</ns0:ref>, the discrepancy between the mRNA and protein expression of Sost may be due to the mechanical stimuli-induced changes in protein secretion. Indeed, our previous study found that mechanical unloading changed the concentration of extracellular Sost but not the intracellular Sost in the femur in vivo using a transmission electron microscopy <ns0:ref type='bibr' target='#b16'>(Osumi et al., 2020)</ns0:ref>. On the other hand, the discrepancy between the mRNA and protein expression of Cx43 may be due to the posttranslational modifications, since the mechanical stimulation changed the phosphorylation status of Cx43 <ns0:ref type='bibr'>(Genetos et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b21'>Qin et al., 2020)</ns0:ref> and Cx43 degradation is controlled by complex crosstalk between connexin phosphorylation and ubiquitination <ns0:ref type='bibr'>(Totland et al., 2020)</ns0:ref>. Ser368 of PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Cx43 is phosphorylated by protein kinase C (PKC), which decreases cell-to-cell communication <ns0:ref type='bibr' target='#b5'>(Lampe et al., 2000)</ns0:ref>. However, the pCx43/Cx43 ratio in the Figures <ns0:ref type='figure' target='#fig_11'>8A and D</ns0:ref> did not show significant differences among all groups, which indicated that the loading history-induced changes in GJIC and protein expression of Cx43 in this study was not due to the phosphorylation of Ser368 of Cx43 by PKC. Mitogen-activated protein kinase (MAPK)-mediated phosphorylation of Cx43 at serine residues 255, 262, 279, and 282 was related to the Cx43 degradation <ns0:ref type='bibr'>(Totland et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Lots of studies showed that the MAPK pathway could be rapidly activated by various cellular mechanical stimuli (Takano-Yamamoto, 2014). Therefore, it is worthy of further studies in the future which the role of the MAPK pathway in the loading history mediated gene expression revealed by this study. The above discussions indicated that loading history might also have an influence on the post-translational modifications on proteins, which is not fully supported by this study but worthy of further investigations.</ns0:p></ns0:div> <ns0:div><ns0:head>Blockade of junctions influenced the habituation effect</ns0:head><ns0:p>Gap junctions are hexametric channels formed by two docked hemichannels from adjacent cells that permit the direct intercellular transfer of small signaling molecules, such as inositol phosphates, cyclic nucleotides, and ATP. Connexins are the main components of gap junctions and hemichannels, and the most abundant connexin in bone cells is <ns0:ref type='bibr'>Cx43 (Ishihara et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b10'>Manuscript, Plotkin &amp; Bellido, 2013)</ns0:ref>, which is highly expressed in MLO-Y4 cells <ns0:ref type='bibr' target='#b2'>(Kato et al., 1997)</ns0:ref>. Cx43 is a key component of intracellular machinery responsible for signal transduction in bone in response to variant stimuli <ns0:ref type='bibr' target='#b10'>(Manuscript, Plotkin &amp; Bellido, 2013)</ns0:ref>. Our results showed that 18&#945;-GA treatment of MLO-Y4 osteocytes with a loading history rescued their sensitivity to RANKL and OPG expression in response to the re-application of CCF (comparing i vs. ii with v vs. viii in Figs. <ns0:ref type='figure' target='#fig_8'>6A-C</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed 18&#945;-GA-treated MLO-Y4 osteocytes with a loading history in the present study reflected a similar condition to the conditional deletion of Cx43 in mice, since osteocytes in vivo are always under a complicated loading environment. Therefore, the conditional deletion of Cx43 in mice is likely to block the gap junction in MLO-Y4 osteocytes with a certain loading history but not in those without any history of mechanical stimuli exposure. Therefore, our in vitro findings are consistent with those of previous reports in vivo.</ns0:p><ns0:p>A previous study showed a greater response to loading at the endocortical surface than the periosteal surface <ns0:ref type='bibr'>(Birkhold et al., 2016)</ns0:ref>. However, the finite elements analysis in this abovementioned study <ns0:ref type='bibr'>(Birkhold et al., 2016)</ns0:ref> showed that the endocortical surface was less strained than the periosteal surface. Our findings may provide a possible explanation for this observation that osteocytes under higher-magnitude loading may be more habituated than those under lowermagnitude loading, thereby showing less sensitivity to mechanical stimuli. In addition, we found that the expression of our interesting genes in MLO-Y4 osteocytes under 31 dynes/cm 2 CCF was more sensitive to additional CCF than MLO-Y4 osteocytes that had previously been exposed to 63 dynes/cm 2 CCF (Figs. <ns0:ref type='figure' target='#fig_11'>6 and 8</ns0:ref>).</ns0:p><ns0:p>A number of previous studies have reported an enhanced response to mechanical stimulation in mice with conditional deletion of Cx43 from either osteoblasts or osteocytes <ns0:ref type='bibr'>(Zhang et al., 2011</ns0:ref><ns0:ref type='bibr'>), osteochondroprogenitors (Grimston et al., 2012)</ns0:ref>, and osteocytes only <ns0:ref type='bibr'>(Bivi et al., 2013)</ns0:ref>. These reports supported our present finding that 18&#945;-GA treatment increased the sensitivity to CCF in the MLO-Y4 osteocytes with a loading history (Fig. <ns0:ref type='figure' target='#fig_8'>6</ns0:ref>). Deletion of Cx43 in mature osteoblasts and osteocytes <ns0:ref type='bibr' target='#b19'>(Plotkin et al., 2008)</ns0:ref> or in osteocytes only <ns0:ref type='bibr'>(Bivi et al., 2012)</ns0:ref> does not decrease the bone mass. Quite the contrary, it increases the periosteal bone formation in the pattern of a bone subjected to modeling during growth <ns0:ref type='bibr'>(Bivi et al., 2012)</ns0:ref>, which is in agreement with our</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed results that blockade of the gap junction by 18&#945;-GA decreased the RANKL/OPG ratio. Given the above, our findings suggest that gap junctional intercellular communications may be involved in the habituation of osteocytes.</ns0:p><ns0:p>The mRNA expression of OPG, Gja1, and Dmp1 showed significant correlation to cell morphological changes during the recovery period Intriguingly, the expression profile of OPG, Gja1, and Dmp1 showed a significant correlation with the morphological changes in the MLO-Y4 osteocytes with a loading history (Figs. <ns0:ref type='figure' target='#fig_7'>5I-L</ns0:ref>).</ns0:p><ns0:p>Gja1/Cx43 has been reported to control cell morphology and migration in other types of cells <ns0:ref type='bibr'>(Xu et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b7'>Liu et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b9'>Machtaler et al., 2014)</ns0:ref>. However, the authors do not find the previous studies reported the correlations between cell morphological changes and the mRNA expression of OPG or Dmp1. Notably, both the solidity and cell area of the MLO-Y4 osteocytes with a loading history were significantly different from in those without a loading history after the 10-h recovery period, even it was at the same level at the beginning of the recovery period (Fig. <ns0:ref type='figure'>4C and D</ns0:ref>). Similarly, more significant changes of all of the mRNA expression profile of Dmp1 (Fig. <ns0:ref type='figure' target='#fig_7'>5F</ns0:ref>) were observed at the end of the 10-h recovery period, which is significantly correlated to the solidity and cell area (Figs. <ns0:ref type='figure' target='#fig_7'>5K and L</ns0:ref>). According to the definition of the solidity in the ImageJ/Fiji software program <ns0:ref type='bibr' target='#b28'>(Schindelin et al., 2012)</ns0:ref>, a lower solidity may suggest more cellular dendritic processes in MLO-Y4 osteocytes since the expended slim dendritic processes would greatly increase the convex area but contribute slightly to the entire cell area (Fig. <ns0:ref type='figure'>2C</ns0:ref>). It was also demonstrated that fluid shear stress changed the cell morphology of osteoblast-like IDG-SW3 cells <ns0:ref type='bibr'>(Xu et al., 2018)</ns0:ref>, and 48 h of clinorotation changed the &#945;-tubulin distribution in <ns0:ref type='bibr'>MLO-Y4 cells (Xu et al., 2012)</ns0:ref>. Indeed, our results showed that the cell morphology was not only immediately changed after the mechanical PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed stimuli exposure but also gradually changed over 10 h after a long period of CCF loading (Fig. <ns0:ref type='figure'>4</ns0:ref>).</ns0:p><ns0:p>A previous study from our group showed that mechanical loading induced morphological changes in osteocytes in vivo <ns0:ref type='bibr'>(Sugawara et al., 2013)</ns0:ref>. Recent studies showed that the cell morphological changes determine the direction of human mesenchymal stem cell (hMSC) differentiation through activating or inhibiting differential biological signals <ns0:ref type='bibr'>(Fan et al., 2019)</ns0:ref>. For example, hMSCs with a spread shape will differentiate to osteoblasts, those with a round shape will differentiate to adipocytes, etc. Actin, one of the three major components of the cytoskeleton, regulates the cell shape by controlling the dynamic equilibrium between the monomeric and filamentous states, which also presents in the nucleus for transcriptional regulation <ns0:ref type='bibr' target='#b12'>(Misu, Takebayashi &amp; Miyamoto, 2017)</ns0:ref>. There are numerous studies showing that morphological differences in osteocytes always correlate to some changes in gene expression or metabolomics <ns0:ref type='bibr'>(Bacabac et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b25'>Sasaki et al., 2012;</ns0:ref><ns0:ref type='bibr'>Xu et al., 2012)</ns0:ref>; however, the underlying mechanism remains unclear and should be examined in future studies. Given the discussion above, our findings suggest that CCF-induced cell morphological changes may be involved in the habituation of osteocytes.</ns0:p></ns0:div> <ns0:div><ns0:head>Limitations</ns0:head><ns0:p>The approach reported in this study is economic and convenient; however, the limitations of this approach are also remarkable. First, the CCF was not delivered to every cell since the area of the cover glass is smaller than the area of cell culture dish or well (supplementary Figs. <ns0:ref type='figure' target='#fig_5'>1 and 2</ns0:ref>). Second, the tolerance in the size of the cover glass may cause a variance in the CCF strength.</ns0:p><ns0:p>These above-mentioned limitations may generate a considerable variance, which can be noticed from all our results. For example, since the linear regression test was performed using the individual mRNA expression fold change against the mean value of morphological changes, the </ns0:p></ns0:div> <ns0:div><ns0:head>Summary</ns0:head><ns0:p>Our findings showed that the mRNA expression of RANKL, OPG, Sost, and OCN in MLO-Y4 osteocyte-like cells with treatment of loading history showed the decrement in responsiveness to a re-application of the same CCF as the loading history (Fig. <ns0:ref type='figure' target='#fig_8'>6</ns0:ref>). This habituation phenomenon could be disrupted by a GJIC inhibitor, which suggested the MLO-Y4 osteocyte-like cells network is important for this habituation in vitro (Fig. <ns0:ref type='figure' target='#fig_8'>6</ns0:ref>). This behavior of in vitro cultured MLO-Y4 osteocyte-like cells network is pretty similar to that of mathematical modeling of small world networks <ns0:ref type='bibr'>(Strogatz, 2001)</ns0:ref> that was used to explain how rest-inserted loading arises more bone formation than continuous cyclic loading <ns0:ref type='bibr'>(Gross et al., 2004)</ns0:ref>. A small world network exhibit power law behavior, in which small magnitude events occur often, whereas large magnitude events occur infrequently <ns0:ref type='bibr' target='#b6'>(Latora &amp; Marchiori, 2001;</ns0:ref><ns0:ref type='bibr'>Strogatz, 2001;</ns0:ref><ns0:ref type='bibr'>Gross et al., 2004)</ns0:ref>. A small world network also exhibits threshold behavior <ns0:ref type='bibr' target='#b6'>(Latora &amp; Marchiori, 2001;</ns0:ref><ns0:ref type='bibr'>Strogatz, 2001;</ns0:ref><ns0:ref type='bibr'>Gross et al., 2004)</ns0:ref>. The decreased GJIC by the treatment of loading history (Fig. <ns0:ref type='figure' target='#fig_10'>7</ns0:ref>) blocked the connections between the MLO-Y4 osteocyte-like cells then consequently decreased the efficient of the small world network since the decreased connection range (k) and probability (p) in this small world mathematic model <ns0:ref type='bibr' target='#b6'>(Latora &amp; Marchiori, 2001)</ns0:ref>. Therefore, the raised threshold of the small word network by efficient changes may be a possible mechanism to explain the habituation behavior of in vitro cultured MLO-Y4 osteocyte-like cells observed in this study. However, this hypothesis needs to be further confirmed by more supportive evidence in the future. Since the osteocytes network is important for bone adaptation <ns0:ref type='bibr' target='#b24'>(Robling, 2012)</ns0:ref>, findings about the behavior of in vitro Manuscript to be reviewed The influences of loading history and 18&#945;-GA on compressive force-induced changes of mRNA expression of interesting genes in MLO-Y4 osteocyte-like cells. Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Germany). The values of the threshold cycle (C t ) were determined automatically by LightCycler 96 software (version 1.1; Roche Diagnostics, Mannheim, Germany) with the default setting. The sequences of the primers used in this study can be downloaded from Mendeley Data (http://dx.doi.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Fluoride, 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>&#956;g/mL leupeptin, 2 &#956;g/mL aprotinin, 5mM EGTA) and sonicated on ice using a supersonic machine. The protein concentration was determined using the Pierce&#8482; BCA Protein Assay Kit (Thermo Scientific, Waltham, MA, USA) and adjusted to a concentration of 1.1 mg/ml with the lysate buffer. Fifteen micrograms of each sample and Precision TM Plus Protein Dual Xtra Standards markers (Bio-Rad, Berkeley, CA, USA) were separated by 7.5% or Any kD TM Criterion TM TGX&#8482; Precast Gel (Bio-Rad, Berkeley, CA, USA) according to the predicted molecular weight (MW) of our interesting proteins. The separated proteins were then transferred to PVDF membranes (Millipore, Billerica, MA, USA). The membranes were blocked in a solution consisting of 5% nonfat skim milk in PBS containing 0.1% Tween-20 (PBST) for 1 h, and then incubated 1 h at room temperature (RT) in Can Get Signal Immunoreaction Enhancer solution (NKB-101; Toyobo Co., Ltd., Osaka, Japan) containing specific antibodies. The membranes were washed 3 times (10 min each time) in PBST, then incubated for 1 h at RT with the corresponding secondary antibodies. After washing 3 times, as described above, the proteins were detected by a chemiluminescence system (ChemiDoc&#8482; XRS+; Bio-Rad, Berkeley, CA, USA) with 20X LumiGLO &#174; Reagent and 20X Peroxide (Cell Signaling, Danvers, MA, USA). The densitometric analysis of bands was performed using the ImageLab software (version 6.0.1; Bio-Rad, Berkeley, CA, USA). The MW of our interesting proteins was estimated by a standard curve of the logarithm of the MW versus relative migration distance that was generated using the Precision TM Plus Protein Dual Xtra Standards.Statistical analysesAll experiments in this study were performed in biological triplicated or quadruplicated wells or dishes with different batches. The cell that was cultured in 24-well plate within the first batch were used for morphological measurements and RNA extraction (see the assignment of treatment in PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)Manuscript to be reviewed supplementary Fig.1). The cells cultured in 60 mm plastic dishes in the second batch were used for protein extraction. The cells cultured in glass-bottom plastic dishes in the last batch were used for FRAP experiments and immunofluorescence staining. The normality of all results was tested by the Shapiro-Wilk test. A one-way analysis of variance (ANOVA) followed by a multiple comparisons test with Fisher's least significant difference (LSD) test or with false discovery rate (FDR) control was performed for the results with a normal distribution, while the Kruskal-Wallis test followed by a multiple comparisons test with FDR control was performed for the results with a non-normal distribution. The correlation of the expression of interesting genes with the cell morphology (aspect ratio, circularity, and solidity) was examined by Pearson's correlation coefficient and linear regression, but only significant correlations were plotted out in this study. A two-way ANOVA followed by a multiple comparisons test with FDR control was applied to test the differences of intracellular fluorescence intensity of calcein among different treatments at each time checkpoint during the FRAP experiments.All of the statistical analyses were performed using the GraphPad Prism software program, version 8.0.0 for Windows (GraphPad Software, Inc., San Diego, CA, USA).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>). Comparing with normal cultured MLO-Y4 cells (i in Figs.7C-G and 8), the MLO-Y4 cells cultured under glass (ii in Figs.7C-G and 8) with (iii in Figs.7C-G and 8) or without (iv in Figs.7C-G and 8) loading history showed decreased mobile fraction (i.e., lower recover percentage) in Figures7C and Dwith decreased protein expression of Cx43 (Figs.8A and B). Remarkably, the changes in the capacity of GJIC and protein expression of Cx43 were opposite between the MLO-Y4 osteocyte-like cells with and without treatment of loading history (comparing ii vs. iii with ii vs. iv in Figs.7C, D, 8A, and B) in response to the application of 1-h loading of additional weight. Indeed, the significant interaction effect was observed between mechanical stimuli (i.e., normal cultured, cultured under cover glass with or without loading history) and time after photobleaching in Figure7C, whichPeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020) Manuscript to be reviewed discrepancy between P-values for Pearson's correlation coefficient and non-zero slope in Figure 5J suggested a high intraclass variance, which was also suggested by the long error bars in Figures 5A-H and 6.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)Manuscript to be reviewed cultured MLO-Y4 osteocyte-like cells network in response to loading history from this study may have contributions to the further understanding in the molecular mechanism of the bone adaptation and finally may contribute to reduce the risk of bone fracture by mediation of bone adaptation.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 2 Figure 4</ns0:head><ns0:label>24</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>The mRNA expression of (A) RANKL, (B) OPG, (C) RANKL/OPG, (D) Gja1, (E) Sost, (F) Dmp1, (G) PDNP, and (H) OCN of MLO-Y4 osteocyte-like cells in response to the new applied or re-applied continuous compressive force (1h) with or without 18&#945;-GA treatment (2h). The values of each replicate are presented as the dots. The results are shown as mean &#177; standard deviation. ANOVA, analysis of variance; Fisher's least Significant Difference (LSD) test was performed following the ANOVA test. *, P &lt;0.05; **, P &lt;0.01; ***, P &lt;0.001; ****, P &lt;0.0001. PeerJ reviewing PDF | (2020:05:48517:1:0:NEW 14 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 7</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='44,42.52,357.37,525.00,371.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='51,42.52,70.87,525.00,371.25' type='bitmap' /></ns0:figure> </ns0:body> "

"Editor’s Decision All reviewers have identified major issues with the described research. Reviewers 1 and 3 in particular identified specific points that have to be addressed with revisions of the text and/or additional experimental work. For example, there is concern about the phenotype of the cell line. It has to be demonstrated that the cells used in the study are able to differentiate and function properly. Especially, it has to be established that these cellular properties are maintained at the late passages used for evaluation. Based on the reviewers' comments, I encourage you to revise your manuscripts and respond to each of the individual points raised in the reviews. Response to Editor: We thank the editor and reviewers for their thoughtful questions and have detailed our responses below. To address the major concerns of the reviewers, the phenotype of MLO-Y4 cells was confirmed by check of the gene expressions and cell-to-cell communications since the MLO-Y4 cells are high expressed connexin 43. Since additional experiments were performed, the manuscript was extensively revised. Therefore, we have made several general changes, including re-organizing the figures and making corresponding changes to the manuscript, making our significant figures consistent, correcting several typographical errors, and adding new parts for description and discussion of the new additional experimental findings. In this revision, we uploaded all of our original data to the Mendeley Data, including raw images for cell morphological measurements, fluorescence recover after photobleaching (FRAP) assay, and Western blot analyses. The results from qRT-PCR were reported according to the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines and made corresponding changes in the manuscript and descriptions in uploaded raw Ct values in Mendeley Data. The reserved DOI (10.17632/2yfd2w8jfp.1) of our uploaded dataset are not yet activated. Therefore, all links in the current manuscript that referred to subfolder or single file of our uploaded dataset are also not activated yet. Please visit the link below to access all original raw data: https://data.mendeley.com/datasets/2yfd2w8jfp/draft?a=d62b3e56-7d7b-4629-b752-e57e32990d99 We apologize for such inconvenience to access our raw data. Since the first author are struggling with the dissertation defense and examinations for his graduation from PhD degree under the outbreak of COVID 19, there is no enough time for the English copyediting service of current manuscript. We apologize for any English grammar errors in this manuscript and rebuttal letter. We thank reviewers for giving us in-depth, thoughtful, constructive comments. We believe that addressing those comments has greatly improved our manuscript. Reviewer 1 Basic reporting 1 This reviewer suggests authors to cite the references appropriately. Please add missing references. Add appropriate reference for lines 219, 227-228, 230 and 258. Response: Original line 219 was moved into the results section by suggestion from reviewer 3 and changed as follows: “18α-GA blocks the gap-junctional intercellular communications (GJIC), which was shown in our previous studies (Kamioka et al., 2007; Ishihara et al., 2008).” Kamioka H, Kameo Y, Imai Y, Bakker AD, Bacabac RG, Yamada N, Takaoka A, Yamashiro T, Adachi T, Klein-Nulend J. 2012. Microscale fluid flow analysis in a human osteocyte canaliculus using a realistic high-resolution image-based three-dimensional model. Integrative Biology 4:1198–1206. Ishihara Y, Kamioka H, Honjo T, Ueda H, Takano-Yamamoto T, Yamashiro T. 2008. Hormonal, pH, and calcium regulation of connexin 43-mediated dye transfer in osteocytes in chick calvaria. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research 23:350–60. Original lines 226-231 were deleted since it over-interpreted the results. Original line 258 was changed as follow: “According to the definition of the solidity in the ImageJ/Fiji software program (Schindelin et al., 2012), a lower solidity may suggest more cellular dendritic processes in MLO-Y4 osteocytes since the expended slim dendritic processes would greatly increase the convex area but contribute slightly to the entire cell area (Fig. 2C).” 2 General comment for all figures: please provide more experimental details and expand the figure legends and describe x and y axis. Response: The figure legends were expanded in the revised manuscript. The ticks on x axis was labeled and referred more clearly in the body text of the current manuscript. Experimental design 1 Line 143. Authors included a general statement that all experiments were performed in triplicates. However throughout the results, it is not clear whether the experiment were performed independently three times and under identical conditions. Please describe in detail about the experimental conditions, set-up format and number of independent experiments for figure 3-6. Response: The experiments were performed with biological triplicated wells or dishes in the same batch to create an identical conditions for each type of experiments (i.e. one batch of cells for RNA extraction, one batch of cells for protein extraction, and one batch of cells for FRAP experiments and immunofluorescence stanning). We indicated the numbers of biological replicates and each of the individual result by plotting points in all bar figures We have provided more details in the section of “Statistical analyses” with new supplementary figure 1. The changes are as follows: “All experiments in this study were performed in biological triplicated or quadruplicated wells or dishes with different batches. The cell that was cultured in 24-well plate within the first batch were used for morphological measurements and RNA extraction (see the assignment of treatment in supplementary Fig. 1). The cells cultured in 60 mm plastic dishes in the second batch were used for protein extraction. The cells cultured in glass-bottom plastic dishes in the last batch were used for FRAP experiments and immunofluorescence staining.” Validity of the findings 1 Line 155. Please describe what was the criteria for selecting 31 and 63 CCF for studying osteocytes. Additionally, what is the physiological relevance for such CCF compression forces for osteocytes. Also, please discuss the overall implication of this study in context to both normal physiology and diseased conditions. Response: We have added the following discussion into the revised manuscript: “It has been stated that, in general, the disuse load was under 200 microstrains, the physiological load was between 200 and 2500 microstrains, and the overuse loading range was 2500-5000 microstrains when applying mechanical loads on the skeleton (Duncan & Turner, 1995; Verbruggen, Vaughan & McNamara, 2012). While, the osteocytes receive more mechanical force since the findings suggested that osteocytes have mechanical signal amplification systems (Takano-Yamamoto, 2014). The application of 2000 microstrains macroscopically to a piece of bone resulted in a much greater microscopic strain surrounding the osteocyte lacunae of over 30000 microstrains (Nicolella et al., 2006). A past study used finite element modeling analysis which reported that global compressive loads of 150 microstrains (disuse), 1000 microstrains (physiological), 3000 microstrains (overuse), and 5000 microstrains (pathological overload) resulted in the maximum principal strains of 633, 4272, 12820, and 21528 microstrains respectively (Wang, Dong & Xian, 2018). A previous study already measured the Young’s modulus of MLO-Y4 osteocyte-like cells as 1.98 ± 0.25 kPa and changed very slightly at a variant indentation range (500nm–1000nm) by using atomic force microscopy (Wu et al., 2017). Therefore, we applied approximate 3.1 Pa (resulted in 3.1 Pa/1.98 kPa ≈ 1566 microstrains) and 6.3 Pa (resulted in 6.3 Pa/1.98 kPa ≈ 3182 microstrains) compressive force to MLO-Y4 osteocyte-like cells to simulate the bending loads-caused compressive stress in vivo within the pathological load range.” 2 Line 234. Authors did not reported such analysis in the manuscript. Please explain. Response: We are sorry for the unclear English. Such analysis are refer to the above mentioned previous study. We changed the sentence as “A previous study showed a greater response to loading at the endocortical surface than the periosteal surface (Birkhold et al., 2016). However, the finite elements analysis in this above-mentioned study (Birkhold et al., 2016) showed that…”. 3 Figure 2. There is a discrepancy for reported time points between cells exposed to 31 CCF (36, 39, 42 and 46h) and 63 CCF (36 h). Currently, results described with Figure 2A-B are misleading and not very clear. Response: The right labels in figure 2B was changed as “63 dyne/cm2 (36h)”, “63 dyne/cm2 (36h) + 31 dyne/cm2 (3h)”, “63 dyne/cm2 (36h) + 31 dyne/cm2 (6h)”, and “63 dyne/cm2 (36h) + 31 dyne/cm2 (10h)”, which is corresponding to the left labels “31 dyne/cm2 (36h)”, “31 dyne/cm2 (39h)”, “31 dyne/cm2 (42h)”, and “31 dyne/cm2 (46h)” respectively. More explanations were added in the legend of figure 2B as “The right samples experienced an additional 32 dynes/cm2 loading before this 10 h recover-period as the treatment of loading history comparing to the left samples.” Comments for the author 1 Figure 1. It would be beneficial for the readers if authors can provide the overview of the experimental design in figure legends. Response: A brief description for the experiment design was provided in the figure legends as “In the present study, MLO-Y4 osteocyte-like cells were proliferated under a continuous compressive force (≈ 3.1 Pa or 31 dynes/cm2) throughout the entire experiment after seeding the cells 3 h. A long-duration (36 h) additional continuous compressive force (CCF) at 3.2 Pa was applied as the treatment of loading history, followed by re-applying the same additional CCF (≈ 3.2 Pa or 32 dynes/cm2) for a short duration (1 h), to assess the effect of loading history on the expression of interesting genes as well as the cell number, viability, morphology, and cell-to-cell communications of MLO-Y4 osteocyte-like cells.” 2 Figure 1. scale bar is not visible. Response: We re-took the photo and put a ruler beside the object in the new Figure 1A. 3 Figure 2A scale bar is missing Response: Scale bars were added in the revised version. 4 Figure 2B scale bar is not visible Response: Scale bars were added in the revised version. 5 Figure 2A-B. Overall, the resolution of figures is very poor. Response: We now uploaded the figures with higher resolution (600 dpi). Reviewer 2 Basic reporting no comments Experimental design no comments Validity of the findings no comments Comments for the author 1 Introduction section, first paragraph, first sentence does not make sense, rewrite it. Response: Agreed. We have rewritten it as “Osteocytes are the most abundant (90%–95% of total bone cells in the adult skeleton) and long-lived cell type in bone, which are major regulators of bone mechanosensation and mechanotransduction (Wang et al., 2019; Qin et al., 2020).” 2 Application of CCF force magnitude and duration was determined based on which in vivo situation in human such as regular exercise, walking, running……and how was that determined? Response: We have added the following introduction into the revised manuscript: “It has been stated that, in general, the disuse load was under 200 microstrains, the physiological load was between 200 and 2500 microstrains, and the overuse loading range was 2500-5000 microstrains when applying mechanical loads on the skeleton (Duncan & Turner, 1995; Verbruggen, Vaughan & McNamara, 2012). While, the osteocytes receive more mechanical force since the findings suggested that osteocytes have mechanical signal amplification systems (Takano-Yamamoto, 2014). The application of 2000 microstrains macroscopically to a piece of bone resulted in a much greater microscopic strain surrounding the osteocyte lacunae of over 30000 microstrains (Nicolella et al., 2006). A past study used finite element modeling analysis which reported that global compressive loads of 150 microstrains (disuse), 1000 microstrains (physiological), 3000 microstrains (overuse), and 5000 microstrains (pathological overload) resulted in the maximum principal strains of 633, 4272, 12820, and 21528 microstrains respectively (Wang, Dong & Xian, 2018). A previous study already measured the Young’s modulus of MLO-Y4 osteocyte-like cells as 1.98 ± 0.25 kPa and changed very slightly at a variant indentation range (500nm–1000nm) by using atomic force microscopy (Wu et al., 2017). Therefore, we applied approximate 3.1 Pa (resulted in 3.1 Pa/1.98 kPa ≈ 1566 microstrains) and 6.3 Pa (resulted in 6.3 Pa/1.98 kPa ≈ 3182 microstrains) compressive force to MLO-Y4 osteocyte-like cells to simulate the bending loads-caused compressive stress in vivo within the pathological load range.” 3 What is the translational value of the findings of this study (in vivo or in preclinical studies)? Response: We added the discussion of the significance of this study at the end as “Since the osteocytes network is important for bone adaptation (Robling, 2012), findings about the behavior of in vitro cultured MLO-Y4 osteocyte-like cells network in response to loading history from this study may have contributions to the further understanding in the molecular mechanism of the bone adaptation and finally may contribute to reduce the risk of bone fracture by mediation of bone adaptation.” Reviewer: Rene Buchet Basic reporting 1 The phenotypes of cell line were insufficiently characterized. It was unclear if the cells were adequately differentiated and functional, especial that they were assayed at 39 passages. Response: MLO-Y4 cells express a high level of connexin 43 (Cx43), early osteocyte markers, such as podoplanin (Pdpn, also know at E11), Osteocalcin (OCN), and low levels of some mature osteocyte markers, such as sclerostin (Sost) and dentin matrix protein 1 (Dmp1) (Yang et al., 2009; Dallas, Prideaux & Bonewald, 2013; Sato et al., 2017). In this revision, we confirmed the phenotype of MLO-Y4 cells by checking the mRNA expression of Pdpn, Cx43, RANKL, OCN, Dmp1, Sost, and OPG, respectively, with the average Ct values of 18.13, 19.75, 22.22, 23.74, 28.93, 30.74, and 33.92 comparing to the average Ct = 14.03 of Gapdh using the same sample. The protein expression of Cx43 and Sost was confirmed by Western blot (Fig. 8A) and the GJIC was confirmed by the fluorescence recover after photobleaching (FRAP) assay and immunofluorescence staining of Cx43 (Fig. 7A and B) using the MLO-Y4 cells at the same passage number of 39. As shown below, a remarkable feature of MLO-Y4 cells is their obvious dendritic processes, which can be seen in the prebleaching confocal microscope images for FRAP assay (Fig. 7B). As suggested by Reviewer 1, the Figure 2 was re-uploaded with higher resolution, which now can see the dendritic processes more clearly. Supplementary prebleaching figure under the confocal microscope using the MLO-Y4 cells at the passage number of 39 in our uploaded dataset (https://data.mendeley.com/datasets/2yfd2w8jfp/draft?a=d62b3e56-7d7b-4629-b752-e57e32990d99). The dendritic cellular processes are obvious. 2 Several statements were insufficiently supported by references or explanations see the minor comments. 1) Introduction, p7, lines 55-56: Add references to support “Therefore, the bone cell network is considered to be encoded with a unique system for maintaining the history of mechanical stimuli received.” Response: The below references was added after this sentence. Turner CH, Robling AG, Duncan RL, Burr DB. 2002. Do Bone Cells Behave Like a Neuronal Network? Calcified Tissue International 70:435–442. DOI: 10.1007/s00223-001-1024-z. Moorer MC, Stains JP. 2017. Connexin43 and the Intercellular Signaling Network Regulating Skeletal Remodeling. Current Osteoporosis Reports 15:24–31. DOI: 10.1007/s11914-017-0345-4. 2) Introduction, p7 lines 64-65: Add references to support “Therefore, bone cells may store and modify long-term mechanical memory through structural changes in the lacuna-canalicular system.” Response: We added relevant references and changed this sentence as “Therefore, osteocytes may be the principal regulator for the functional bone adaptation (Skedros, Hunt & Bloebaum, 2004; Hazenberg, Lee & Taylor, 2006).” 3) Introduction, p8 lines 70-71: Add references to support “Habituation is a term that describes the decrement in responsiveness to a repetitive stimulus in neuronal systems.” Response: The below reference was added after this statement. McDiarmid TA, Yu AJ, Rankin CH. 2019. Habituation Is More Than Learning to Ignore: Multiple Mechanisms Serve to Facilitate Shifts in Behavioral Strategy. BioEssays 41:1900077. DOI: 10.1002/bies.201900077. 4) Introduction, p8 lines 75-76: Add references to support “The relative amount and distribution of RANKL and OPG proteins is thought to determine the destination of osteoclasts.” Response: Lines 75-76 were changed as follows: “Correct osteoclastogenesis relies on a correct RANKL/OPG ratio (Capulli, Paone & Rucci, 2014), and osteocytes express both factors at levels comparable with or exceeding those of osteoblasts (Bonewald, 2011).” Capulli M, Paone R, Rucci N. 2014. Osteoblast and osteocyte: Games without frontiers. Archives of Biochemistry and Biophysics 561:3–12. Bonewald LF. 2011. The amazing osteocyte. Journal of Bone and Mineral Research 26:229–238. DOI: 10.1002/jbmr.320. 5) Introduction, p8 lines 79-80: Delete or add references in “However, very few studies have investigated the habituation of osteocytes to mechanical loading using an in vitro culture system.” Response: We deleted this statement. 6) Blockade of junctions partially rescued the habituation effect, line 219, p15: Move into the result section to explain the rationale of 18α-GA treatment “18α-GA could block the gap junctions” Response: We moved this sentence into the result section with elucidation of its function as follows: “18α-GA blocks the gap-junctional intercellular communications (GJIC), which was shown in our previous studies (Kamioka et al., 2007; Ishihara et al., 2008). However, the mode of inhibitory action of GA is still not completely understood (Willebrords et al., 2017). Direct interaction between 18α-GA and gap junctions (GJs) is possible when the former is inserted into the plasma membrane, thereby binding to GJs and causing a conformational alteration (Willebrords et al., 2017). Other possibilities include changes in the connexin phosphorylation status, which led to a reduction in connexin expression (Willebrords et al., 2017). Our results (iv vs. v in Fig. 6D, P-value <0.05 by unpaired t-test which did not show) also showed a reduction of Gja1, which were in good agreement with the previous results (Willebrords et al., 2017), although this reduction did not show significance by Fisher’s LSD due to the big pooled variance.” Experimental design 1 Cell culture and reagents, p9 lines 87-94: There were no information how phenotypes of MLO-Y4 cell line was checked and if they acted as osteocytes, especially that they were selected at 39 passages in “The MLO-Y4 cells line was purchased from Kerafast (Boston, MA, USA). MLO-Y4 cells (at 39 passages), an osteocyte-like cell line derived from long bone of a transgenic female mouse containing the osteocalcin promoter driving SV40 T-antigen (Kato et al., 1997), were seeded onto type I collagen-coated 24-well plates and cultured in alpha-modified Eagle's minimal essential medium (α-MEM; Thermo Fisher Scientific, Waltham, MA, USA) containing 5.0% heat-inactivated fetal bovine serum (HIFBS; HyClone Laboratories, Logan, UT, USA), 5.0% fetal calf serum (FCS; HyClone), 100 U/ml penicillin, and 100 mg/ml streptomycin (Thermo Fisher Scientific) at 37 °C with 5% CO2.” Response: We added a brief introduction of MLO-Y4 cells in the materials and methods section as: “MLO-Y4 cells express a high level of connexin 43 (Cx43), early osteocyte markers, such as podoplanin (Pdpn, also know at E11), Osteocalcin (OCN), and low levels of some mature osteocyte markers, such as sclerostin (Sost) and dentin matrix protein 1 (Dmp1) (Yang et al., 2009; Dallas, Prideaux & Bonewald, 2013; Sato et al., 2017).” We have then did additional experimental work to confirm the expression of above-mentioned genes, and added a summary at the beginning of the discussion part as “In this study, the phenotype of MLO-Y4 cells was confirmed by checking the mRNA expression of Pdpn, Cx43, RANKL, OCN, Dmp1, Sost, and OPG, respectively, with the average Ct values of 18.13, 19.75, 22.22, 23.74, 28.93, 30.74, and 33.92 comparing to the average Ct = 14.03 of Gapdh (raw Ct values could be downloaded from Mendeley Data: http://dx.doi.org/10.17632/2yfd2w8jfp.1#file-22aa2376-6feb-4709-b37e-dfdc8c8cf309). The protein expression of Cx43 and Sost was confirmed by Western blot (Fig. 8A). The GJIC was confirmed by the FRAP assay and immunofluorescence staining of Cx43 (Fig. 7A and B). The dendritic cellular processes were also observed (Figs. 2, 7A, and B). Therefore, the MLO-Y4 cells used in this study were characterized as the osteocyte-like cells.” Validity of the findings 1 The statistical analysis was not adequately supported by independent experiments to validate the findings. 1) Statistical analyses, line 143, p 11: It was unclear if there were independent measurements to obtain reliable statistics. Triplicates obtained from the same sample are insufficient to obtain reliable statistics in “All experiments in this study were performed in triplicate.” Response: The experiments were performed with biological triplicated wells or dishes in the same batch to create an identical conditions for each type of experiments (i.e. one batch of cells for RNA extraction, one batch of cells for protein extraction, and one batch of cells for FRAP experiments and immunofluorescence staining). We indicated the numbers of biological replicates and each of the individual result by plotting points in all bar figures We have provided more details in the section of “Statistical analyses” with new supplementary figure 1. The changes are as follows: “All experiments in this study were performed in biological triplicated or quadruplicated wells or dishes with different batches. The cell that was cultured in 24-well plate within the first batch were used for morphological measurements and RNA extraction (see the assignment of treatment in supplementary Fig. 1). The cells cultured in 60 mm plastic dishes in the second batch were used for protein extraction. The cells cultured in glass-bottom plastic dishes in the last batch were used for FRAP experiments and immunofluorescence staining.” Since the triplicates were obtained from different sample, the relative big intraclass variance may come from the biological differences and operational differences for the different samples. We therefore added a limitation section to discuss such relative big variances in this study as follows: “The approach reported in this study is economic and convenient; however, the limitations of this approach are also remarkable. First, the CCF was not delivered to every cell since the area of the cover glass is smaller than the area of cell culture dish or well (supplementary Figs. 1 and 2). Second, the tolerance in the size of the cover glass may cause a variance in the CCF strength. These above-mentioned limitations may generate a considerable variance, which can be noticed from all our results. For example, since the linear regression test was performed using the individual mRNA expression fold change against the mean value of morphological changes, the discrepancy between P-values for Pearson’s correlation coefficient and non-zero slope in Figure 5J suggested a high intraclass variance, which was also suggested by the long error bars in Figures 5A-H and 6.” 2 There were a lack of experiments to support hypothesis as indicated: 1) In vitro cultured MLO-Y4 osteocytes were successfully habituated, line 210-211, p15: Delete since there were no findings associated with plasma membrane disruption or perform experiments to support “The habituation phenomena that we observed in the present study may be related to plasma membrane disruption (PMD) and PMD repair under conditions of heavy mechanical loading.” Response: Agreed. We have deleted the original lines 210-217. 2) Blockade of junctions partially rescued the habituation effect, line 219, p15: Move into the result section to explain the rationale of 18α-GA treatment “18α-GA could block the gap junctions” Response: We changed the original title “Blockade of junctions partially rescued the habituation effect” into “Blockade of junctions influenced the habituation effect”, since the 18α-GA treatment reversed the OPG expression in response to re-applied compressive force, which is not literally “rescued”. 3) Blockade of junctions partially rescued the habituation effect, line 219 p15 and lines 228-230 p16: Additional findings are needed to support adequately “Connexins are main components of gap junctions and hemichannels, and the most abundant connexin in bone is connexin43 (Cx43), which is also expressed by osteocytes (Ishihara et al., 2008).” And “Therefore, the conditional deletion of Cx43 in mice is likely to block the gap junction in MLO-Y4 osteocytes with a certain loading history but not in those without any history of mechanical stimuli exposure” Response: Original lines 226-231 were deleted later one since it over-interpreted the results. We added a supportive reference for the first as: “Connexins are the main components of gap junctions and hemichannels, and the most abundant connexin in bone cells is Cx43 (Ishihara et al., 2008; Manuscript, Plotkin & Bellido, 2013), which is highly expressed in MLO-Y4 cells (Kato et al., 1997).” Manuscript A, Plotkin LI, Bellido T. 2013. Beyond gap junctions: Connexin43 and bone cell signaling. Bone 52:157–166. Ishihara Y, Kamioka H, Honjo T, Ueda H, Takano-Yamamoto T, Yamashiro T. 2008. Hormonal, pH, and calcium regulation of connexin 43-mediated dye transfer in osteocytes in chick calvaria. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research 23:350–60. Kato Y, Windle JJ, Koop BA, Mundy GR, Bonewald LF. 1997. Establishment of an Osteocyte-like Cell Line, MLO-Y4. Journal of Bone and Mineral Research 12:2014–2023. 4) The expression OPG showed significant correlation to cell morphological changes during recovery period, lines 273-275, p18: Additional experiments are needed to support “Therefore, it is reasonable to hypothesize that mechanical stimuli-induced morphological changes may influence the gene expression profile in osteocytes for a considerably long time.” Response: We have deleted this statement since it over-interpreted our results and out of the main purpose of work. Comments for the author Minor comments : 1 Abstract, p1: Specify OPG in ” The RANKL/OPG expression, cell numbers, viability, and morphology were time-dependently examined at 0, 3, 6, and 10 h.” Response: This sentence was changed as “The expression of RANKL, OPG, RANKL/OPG ratio, cell numbers, viability, and morphology were time-dependently examined at 0, 3, 6, and 10 h.” 2 The morphology changed during the recovery period lines 161-162, p12: Specify aspect ratio in “Figure 2C shows an example of the morphological measurements. After changing the CCF from 63 dynes/cm2 back to 31 dynes/cm2 for 10 h (recovery period), the aspect ratio was significantly increased only in the MLO-Y4 osteocytes without a loading history (Fig. 4A).” Response: This sentence was changed as: “Figure 2C shows an example of the morphological measurements. At the end of this 10 h recover-period, the aspect ratio was significantly increased only in the MLO-Y4 osteocytes without a loading history (median aspect ratio of 1.7 vs. 2.0 with FDR value less than 0.001 in Fig. 4A).” 3 Conclusion, lines 309-314, p20: Delete conclusion since it was repeated in the discussions “In conclusion, in order to investigate the influence of the loading history on the RANKL/OPG expression and morphology of MLO-Y4 osteocytes, we established a useful in vitro model using osteocyte-like MLO-Y4 cells. In this study, the in vitro cultured MLO-Y4 osteocytes showed habituation of RANKL/OPG expression in their response to long-duration (36 h) CCF. Gap junctional intercellular communication and cell morphology may play a role in this habituation phenomena in MLO-Y4 osteocytes.” Response: We rewrote the conclusion part, added a discussion of a possible underlying mechanism, and emphasized the significance of this study, as shown follows: “Our findings showed that the mRNA expression of RANKL, OPG, Sost, and OCN in MLO-Y4 osteocyte-like cells with treatment of loading history showed the decrement in responsiveness to a re-application of the same CCF as the loading history (Fig. 6). This habituation phenomenon could be disrupted by a GJIC inhibitor, which suggested the MLO-Y4 osteocyte-like cells network is important for this habituation in vitro (Fig. 6). This behavior of in vitro cultured MLO-Y4 osteocyte-like cells network is pretty similar to that of mathematical modeling of small world networks (Strogatz, 2001) that was used to explain how rest-inserted loading arises more bone formation than continuous cyclic loading (Gross et al., 2004). A small world network exhibit power law behavior, in which small magnitude events occur often, whereas large magnitude events occur infrequently (Latora & Marchiori, 2001; Strogatz, 2001; Gross et al., 2004). A small world network also exhibits threshold behavior (Latora & Marchiori, 2001; Strogatz, 2001; Gross et al., 2004). The decreased GJIC by the treatment of loading history (Fig. 7) blocked the connections between the MLO-Y4 osteocyte-like cells then consequently decreased the efficient of the small world network since the decreased connection range (k) and probability (p) in this small world mathematic model (Latora & Marchiori, 2001). Therefore, the raised threshold of the small word network by efficient changes may be a possible mechanism to explain the habituation behavior of in vitro cultured MLO-Y4 osteocyte-like cells observed in this study. However, this hypothesis needs to be further confirmed by more supportive evidence in the future. Since the osteocytes network is important for bone adaptation (Robling, 2012), findings about the behavior of in vitro cultured MLO-Y4 osteocyte-like cells network in response to loading history from this study may have contributions to the further understanding in the molecular mechanism of the bone adaptation and finally may contribute to reduce the risk of bone fracture by mediation of bone adaptation.” "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>APLN, APELA and their common receptor APLNR (composing the apelinergic axis) have been described in various species with extensive body distribution and multiple physiological functions. Recent studies have witnessed emerging intracellular cascades triggered by APLN and APELA which play crucial roles in female reproductive organs, including hypothalamus-pituitary-gonadal axis, ovary, oviduct, uterus and placenta.</ns0:p><ns0:p>However, a comprehensive summary of APLN and APELA roles in physiology and pathology of female reproductive system has not been reported to date. In this review, we aim to concentrate on the general characteristics of APLN and APELA, as well as their specific physiological roles in female reproductive system. Meanwhile, the pathological contexts of apelinergic axis dysregulation in the obstetrics and gynecology are also summarized here, suggesting its potential prospect as a diagnostic biomarker and/or therapeutic intervention in the polycystic ovary syndrome, ovarian cancer, preeclampsia and gestational diabetes mellitus.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Main article text 1. Introduction</ns0:head><ns0:p>Apelin receptor (APLNR, also known as APJ, APJR, AGTRL1 and HG11) was firstly identified as a class A G protein-coupled receptor in 1993. It consists of 380 amino acids, which has a sequence sharing 31% homology with that of the angiotensin type 1 receptor <ns0:ref type='bibr' target='#b47'>(O'Dowd et al., 1993)</ns0:ref>. Nevertheless, APLNR cannot actually bind to angiotensin II and remains as an 'orphan receptor' until its endogenous ligand apelin (APLN, also named APEL and XNPEP2) was later extracted from bovine stomach <ns0:ref type='bibr' target='#b75'>(Tatemoto et al., 1998)</ns0:ref>. APLN is generally existed in functional isoforms which are cleaved and modified from the C-terminus of a 77-amino acid pre-propeptide encoded by APLN gene, with different affinities for APLNR and prevalent distribution <ns0:ref type='bibr' target='#b15'>(Chapman, Dupr&#233; and Rainey, 2014)</ns0:ref>. Both APLN and its receptor APLNR levels are universally high at multiple organs like brain, retina, heart, stomach, liver, kidney and blood vessels in many species <ns0:ref type='bibr' target='#b32'>(Kawamata et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b89'>Zeng et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b31'>Kasai et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b60'>Qian et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b33'>Krist et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b38'>Lv et al., 2017)</ns0:ref>. Recent years, apelin receptor early endogenous ligand (APELA, also named ELABELA, Toddler and Ende) was identified as a new endogenous ligand for APLNR in both Chng and Pauli's labs independently <ns0:ref type='bibr' target='#b16'>(Chng et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b53'>Pauli et al., 2014)</ns0:ref>. Similar to APLN, this 54-amino acid polypeptide is also processed into several isoforms. APELA is highly enriched in the early stage of embryo and confirmed to play a vital role in embryogenesis and angiogenesis <ns0:ref type='bibr' target='#b46'>(Norris et al., 2017)</ns0:ref>. APLNR and its two ligands compose the apelinergic axis, which is well delineated in systemic physiological processes like cardiogenesis, angiogenesis, fluid homeostasis, vasodilation and energy metabolism. More recently, several studies have been investigating the possible intervention of apelinergic axis in female reproductive system based on its precise regulation of steroidogenesis, angiogenesis and vasodilation, before moving onto the dysregulation of this system which hypothetically causes fertility disorders and pregnancy complications like polycystic ovary syndrome (PCOS), ovarian cancer, gestational diabetes mellitus (GDM) and preeclampsia (PE) (summarized in Table <ns0:ref type='table'>1</ns0:ref>). This review summarizes and evaluates the current role of apelinergic system in female reproductive system at both physiological and pathological profiles (Fig <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>), as well as providing the direction for future research.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.'>Survey methodology</ns0:head><ns0:p>Jiangxi Provincial Key Laboratory of Reproductive Physiology and Pathology, Medical Experimental Teaching Center of Nanchang University.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.'>APLN and APELA, endogenous ligands of APLNR</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>Characteristics of APLN</ns0:head><ns0:p>Human APLN gene is located on chromosome Xq25-26.1 which encodes a pre-propeptide of 77 amino acids. After cleavage of the 22-amino acid secretory sequence at N terminus by endopeptidases, the propeptide is subsequently processed into three active fragments at several dibasic residues (Arg-Lys and Arg-Arg), including APLN-36, APLN-17 and APLN-13. APLN-13 undergoes post-transcriptional cyclization at the N-terminal glutamine, generating pyroglutamate-APLN-13 (Pyr1-APLN-13) <ns0:ref type='bibr' target='#b75'>(Tatemoto et al., 1998)</ns0:ref>. The potency and efficacy of APLN differ from different isoforms. For instance, APLN-36, APLN-13 and Pyr1-APLN-13 are preponderantly contributed in human cardiovascular regulation <ns0:ref type='bibr' target='#b39'>(Maguire et al., 2009)</ns0:ref>, whereas APLN-17 plays crucial role in APLNR internalization <ns0:ref type='bibr' target='#b43'>(El Messari et al., 2004)</ns0:ref>. To date, APLN is abundantly distributed in female reproductive system such as ovary, oviduct, uterus and placenta. Emphatically, APLN is identified as one type of adipokines secreted by white adipose tissue, which plays a role with other adipokines in regulating the secretion of gonadotropin releasing hormone (GnRH), gonadotropins and steroids through hypothalamo-pituitary-gonadal (HPG) axis <ns0:ref type='bibr' target='#b5'>(Bertrand, Valet &amp; Castan-Laurell, 2015;</ns0:ref><ns0:ref type='bibr' target='#b85'>Yang et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>APLN dependent signaling pathway</ns0:head><ns0:p>APLN/APLNR activates different types of G protein and further stimulates three important signaling pathways, which are phosphorylation of phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), reduction of cyclic adenosine monophosphate (cAMP) and activation of phospholipase C-&#946; (PLC-&#946;), respectively (Fig <ns0:ref type='figure' target='#fig_2'>2 A</ns0:ref>) <ns0:ref type='bibr' target='#b15'>(Chapman, Dupr&#233; &amp; Rainey, 2014)</ns0:ref>. There are two types of pertussis toxin-sensitive G&#945; protein (G&#945;i/o, G&#945;q/11) at the downstream of APLNR, mediating different signaling transduction <ns0:ref type='bibr' target='#b41'>(Masri et al., 2002)</ns0:ref>. G&#945;i/o activates PI3K/Akt dependent manner which is crucial for cell survival and nitric oxide (NO) induced vasodilation <ns0:ref type='bibr' target='#b36'>(Liu et al., 2010)</ns0:ref>. Akt phosphorylates Bcl-2-associated death promoter (Bad, a BH3-only protein) and shifts it to an inert form, which inhibits the binding of Bad and Bcl-2. Bcl-2 plays an anti-apoptotic role by disturbing the aggregation of Bak and Bax (BH123 proteins) in the mitochondrial outer membrane, and thereby attenuating the release of cytochrome c and activation of caspase-3 <ns0:ref type='bibr' target='#b37'>(Liu et al., 2019)</ns0:ref>. Moreover, endothelial nitric oxide synthase (eNOS) can also be activated by Akt through phosphorylation, triggering the release of NO for vasodilation (Fig <ns0:ref type='figure' target='#fig_2'>2 A</ns0:ref>) <ns0:ref type='bibr' target='#b86'>(Yang et al., 2014)</ns0:ref>. Additionally, G&#945;i/o inhibits adenylate cyclase (AC), following with the reduction of 3', 5&#8242;-cAMP and protein kinase A (PKA), which could potentially regulate the glucose homeostasis (Fig <ns0:ref type='figure' target='#fig_2'>2 A</ns0:ref>) <ns0:ref type='bibr' target='#b41'>(Masri et al., 2002)</ns0:ref>. G&#945;q/11 activates PLC-&#946; hydrolyze phosphatidylinositol 4, 5-bisphosphate into second messengers diacylglycerol and inositol trisphosphate, which increases the release of calcium (Ca 2+ ) from intracellular store and activates protein kinase C (PKC) <ns0:ref type='bibr' target='#b12'>(Carp&#233;n&#233; et al., 2007)</ns0:ref>. Amplified intracellular Ca 2+ not only mediates positive inotropic effect in cardiac smooth muscle, but also stimulates NO release in periphery via activating eNOS by calmodulin <ns0:ref type='bibr' target='#b20'>(Dai, Ramirez-Correa and Gao, 2006)</ns0:ref>. PKC in turn activates Ras/MAPK system, which plays a crucial role in cell proliferation <ns0:ref type='bibr' target='#b72'>(Szokodi et al., 2002)</ns0:ref>. Furthermore, MAPK halts the expression of pro-oxidant enzymes and subsequently attenuates the release of reactive oxygen species (ROS), which suppresses lipid metabolism and inflammatory reaction ( <ns0:ref type='bibr'>(Yue et al., 2014)</ns0:ref> and chromosome 1 in Danio rerio <ns0:ref type='bibr' target='#b79'>(Ulitsky et al., 2011)</ns0:ref>, was originally annotated to be transcribed exclusively into a non-coding RNA in zebrafish embryo <ns0:ref type='bibr' target='#b16'>(Chng et al., 2013)</ns0:ref>, while recently it was confirmed to encode a 54-amino acid precursor which further undergoes proteolysis and generates four mature isoforms: APELA-32, APELA-22, APELA-21 and APELA-11. The shortest isoform is conserved across vertebra species <ns0:ref type='bibr' target='#b28'>(Huang et al., 2017)</ns0:ref>. Compared with APLN, APELA as the second discovered endogenous ligand of APLNR is also ubiquitously detected in placenta, heart, kidney, prostate and mammalian plasma but not as widely as APLN <ns0:ref type='bibr' target='#b81'>(Wang et al., 2015)</ns0:ref>. In addition, studies have reported that APELA is highly expressed in human embryonic stem cells (hESCs) where the APLNR is absent, indicating the existence of an alternative APLNR-independent transduction <ns0:ref type='bibr'>(Ho et al., 2015)</ns0:ref>. A recent report has suggested that an orphan G protein-coupled receptor 25 (GPR25), associated with blood pressure regulation and autoimmune disease, could be activated by both APLN and APELA in non-vertebrates, which is similar as APLN in decreasing the intracellular cAMP level. However, the accurate role of this putative receptor in vertebrates remains to be determined <ns0:ref type='bibr' target='#b90'>(Zhang et al., 2018)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.4'>APELA dependent signaling pathway</ns0:head><ns0:p>Similar to APLN, APELA binds to APLNR, subsequently activating G&#945;i/o and G&#945;q/11 mediated signaling cascades, including PI3K/Akt, PKC and PKC-independent Ras/MAPK pathways (Fig <ns0:ref type='figure' target='#fig_2'>2 A</ns0:ref>) <ns0:ref type='bibr' target='#b56'>(Perj&#233;s et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b90'>Zhang et al., 2018)</ns0:ref>. Nevertheless, it also plays non-redundant role for its specific properties during embryo development. In mouse ESCs, Apela acts as a long non-coding RNA that binds to heterogeneous nuclear ribonucleoprotein L (hnRNPL) at the 3' UTR, which negatively regulates the interaction between p53 and hnRNPL, and promotes p53-mediated DNA damage induced apoptosis (Fig <ns0:ref type='figure' target='#fig_2'>2 B</ns0:ref>) <ns0:ref type='bibr' target='#b54'>(Li et al., 2015)</ns0:ref>. In hESCs, APELA acts as a paracrine secreted hormone that binds to an alternative unknown receptor (non-APLNR) and activates PI3K/AKT signaling for cell survival and self-renewal. This process resembles other fibroblast growth factor like exogenous insulin and endogenous insulin-like growth factors (IGFs) in PI3Kmediated cell proliferation. However, APELA-pulsed hESCs is non-redundant as it also implicates in mesendodermal linage commitment through an PI3K-independent manner <ns0:ref type='bibr'>(Ho et al., 2015)</ns0:ref>. During zebrafish gastrulation, a proper level of APELA acting as a mitogen, indirectly mediates the internalization of ventrolateral mesendodermal cells. This process is presumably achieved via activating NODAL/TGF&#946; signaling pathway (Fig <ns0:ref type='figure' target='#fig_2'>2 C</ns0:ref>), whereas its specific mechanism remains unknown <ns0:ref type='bibr' target='#b53'>(Pauli et al., 2014)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='4.'>Roles of APLN and APELA in HPG axis</ns0:head><ns0:p>Endocrine function of female reproduction initiates from hypothalamic GnRH neurons, which mainly receipt projections from arcuate, paraventricular, supraoptic and medial preoptic nuclei of hypothalamus. These neurons secrete GnRH in a pulsatile manner that favours the secretion of lutenizing hormone (LH) and follicle stimulating hormone (FSH) from gonadotroph cells in the anterior pituitary <ns0:ref type='bibr' target='#b29'>(Jin and Yang, 2014)</ns0:ref>. APLN and its receptor are intensively detected in the same nucleic group of the hypothalamus <ns0:ref type='bibr' target='#b57'>(Pope et al., 2012)</ns0:ref>, indicating an essential behavior of them in reproductive regulation. It was reported in both intracerebroventricular and intraperitoneal infusion that APLN-13 suppressed the secretion of FSH and LH in frontal hypophysis in rats, but it cannot cause a disturbance at the GnRH level <ns0:ref type='bibr' target='#b73'>(Taheri et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b78'>Tekin et al., 2017)</ns0:ref>. The structural and functional similarities between APLN and GnRH <ns0:ref type='bibr' target='#b17'>(Cho et al., 2007)</ns0:ref> was reasonably suspected that APLN could be a competitive inhibitor in the adenohypophysis for GnRH receptors. In addition, the central action of APELA in hypothalamus was also demonstrated that it exerted as an anorexigenic hormone via binding to APLNR and activating arginine vasopressin and corticotropin releasing hormone neurons in the paraventricular nuclei <ns0:ref type='bibr' target='#b65'>(Santoso et al., 2015)</ns0:ref>. Whether it has an effect on reproductive-dependent hormone or not remains to be illuminated.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.'>Roles of APLN and APELA in uterine appendages</ns0:head></ns0:div> <ns0:div><ns0:head n='5.1'>Distribution and role of APLN in the ovarian follicle</ns0:head><ns0:p>Under the normal physiological states, APLN has been identified as a steroidogenic regulator in ovaries of various species including bovine, mouse, rat, porcine, sheep and human <ns0:ref type='bibr' target='#b62'>(Roche et al., 2016</ns0:ref><ns0:ref type='bibr' target='#b63'>(Roche et al., , 2017;;</ns0:ref><ns0:ref type='bibr' target='#b70'>Shuang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b61'>Rak et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b42'>Mercati et al., 2019)</ns0:ref>. In cultured bovine follicles, it was firstly reported that APLN mRNA was not found in granulosa cells (GCs), whereas APLNR mRNA was detected and significantly stimulated by estradiol and progesterone in GCs of estrogen-inactive follicles. In interstitial theca cells, both APLN and its receptor mRNA were obviously expressed <ns0:ref type='bibr' target='#b68'>(Shimizu et al., 2009)</ns0:ref>. Two years later, another group cultured bovine ovarian follicles at the similar condition, and found that estradiol over 5 ng/ml (evaluation for follicular maturation) stimulated the expression of APLN and APLNR in theca cells. However, it had no significant effect on the expression of APLN and APLNR in GCs <ns0:ref type='bibr' target='#b67'>(Schilffarth et al., 2009)</ns0:ref>. Recent research confirmed that the expression level of APLN and APLNR were up-regulated in both GCs and oocytes, but remained constant in theca cells <ns0:ref type='bibr' target='#b67'>(Schilffarth et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b68'>Shimizu et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b63'>Roche et al., 2017)</ns0:ref>. In vitro, APLN from GCs of inactive follicles, in response to IGF1 but not to FSH, markedly increased the progesterone production <ns0:ref type='bibr' target='#b63'>(Roche et al., 2017)</ns0:ref>. In porcine follicles, elevated APLN and APLNR were detected following the follicular growth. In turn, APLN significantly increased the secretion of basal steroid hormone (progesterone and estradiol) through the activation of steroidogenic enzyme (3&#946;HSD and CYP19A1) via AMPK&#593; stimulation, whereas it also decreased the IGF1-and FSHinduced steroid secretion <ns0:ref type='bibr' target='#b61'>(Rak et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.2'>Role of APLN in corpus luteum (CL)</ns0:head><ns0:p>As a potent angiogenic factor, apelinergic axis also plays a role in the transient luteal stage after ovulation. It has been mentioned that this system exclusively exists in the bovine smooth muscle of intraluteal arterioles, with ligands elevated from early to late CL and followed by a significant decrease at regressed CL, while receptors increased from early to mid CL and remained constant till regressed CL <ns0:ref type='bibr' target='#b69'>(Shirasuna et al., 2008)</ns0:ref>. Paradoxically, another study showed that APLNR also decreased significantly after mid CL <ns0:ref type='bibr' target='#b67'>(Schilffarth et al., 2009)</ns0:ref>. Luteolytic factor prostaglandin F2&#945; stimulates APLN and APLNR mRNA expression particularly at the periphery of mid CL <ns0:ref type='bibr' target='#b69'>(Shirasuna et al., 2008)</ns0:ref>. In ewes, both APLN and APLNR proteins were observed in large luteal cells, and the highest level of APLN mRNA was detected in the luteal phase of the ovarian cycle compared to ewes in the anestrous one <ns0:ref type='bibr' target='#b42'>(Mercati et al., 2019)</ns0:ref>. In porcine cultured CL, APLN stimulates 3&#946;HSD activity, which converts inert 5-ene-3&#946;HSD to the active 4-ene-3-oxo steroid, therefore it has a pivotal role in progesterone biosynthesis, suggesting an auto/paracrine pattern of the APLN/APLNR system in the ovary <ns0:ref type='bibr' target='#b64'>(R&#243;&#380;ycka et al., 2018)</ns0:ref>. In human, this system is found in the whole ovary through different developmental stages, including luteinized human GCs, theca, oocytes and corona cumulus complex. In cultured luteinized human GCs and follicular fluid, IGF1 exclusively stimulates APLNR expression whereas LH and FSH cannot show the same effect. Conversely, recombinant human APLN-13 and -17 stimulates the secretion of both basal and IGF-induced progesterone and estradiol in a dose-dependent manner, and this process is significantly accelerated in response to IGF1 <ns0:ref type='bibr' target='#b62'>(Roche et al., 2016)</ns0:ref>. This hormone regulation is in agreement to those discovered in bovine that demonstrated APLN could stimulate steroidogenesis and it is speculatively implemented via 3&#946;HSD activation and Akt and MAPK3/1 signaling <ns0:ref type='bibr' target='#b62'>(Roche et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.3'>Regulation of APLN in PCOS</ns0:head><ns0:p>PCOS is a common gynecological endocrinopathy characterized by over-expressed LH triggered hyperandrogenism, chronic oligo/anovulation and polycystic ovaries morphology, with clinical manifestations described as 'hirsutism, acne, irregular menstruation and subfertility' <ns0:ref type='bibr' target='#b76'>(Teede, Deeks and Moran, 2010;</ns0:ref><ns0:ref type='bibr' target='#b77'>Teede et al., 2018)</ns0:ref>. Despite of the positive correlation between PCOS and complications such as visceral obesity, insulin resistance and type 2 diabetes <ns0:ref type='bibr' target='#b21'>(Farrell and Antoni, 2010)</ns0:ref>, the definite aetiology of PCOS at the molecular level still need to be elucidated. It is known that adipokines are bridges to link the energy metabolism and reproductive system, thus they are probably implicated in this process. Hypothetically, APLN controls several aspects of ovarian function in PCOS, underpinned by its role in steroid hormone regulation and insulin resistance. Firstly, the concentration of APLN and its receptors were detected to be significantly increased in PCOS patients with a positive correlation between follicle count and APLN levels <ns0:ref type='bibr' target='#b6'>(Bongrani et al., 2019)</ns0:ref>. This process could be explained by a steroid hormone disturbance effect of APLN in HPG axis. Moreover, as mentioned above, the secretion of APLN in atretic follicles is notably increased in response to IGF1 and insulin, and subsequently stimulates steroidogenesis in GCs <ns0:ref type='bibr' target='#b7'>(Boucher et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b62'>Roche et al., 2016)</ns0:ref>. It indicates a possible implication of insulin in APLN synthesis via activating PI3K/Akt and MAPK3/1 signaling pathways <ns0:ref type='bibr' target='#b7'>(Boucher et al., 2005)</ns0:ref>. Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and Body Mass Index (BMI) as hall markers of PCOS have been confirmed to be associated with adipocytokines, even if there is still an inconsistency among different researches. In normal cases, studies have revealed either positive or negative correlations of APLN with HOMA-IR and BMI <ns0:ref type='bibr' target='#b13'>(Cekmez et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b48'>Olszanecka-Glinianowicz et al., 2015)</ns0:ref>. In PCOS cases, several groups have shown an enhanced level of serum APLN positively correlated with HOMA-IR and BMI <ns0:ref type='bibr' target='#b71'>(Sun et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b62'>Roche et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b6'>Bongrani et al., 2019)</ns0:ref>, while one research reported a decreased serum APLN level which was positively associated with HOMA-IR and BMI <ns0:ref type='bibr' target='#b1'>(Altinkaya et al., 2014)</ns0:ref>. These discrepant findings among published literature may be attributed to the differences in research design, different stages of PCOS, sample size, genetic characteristics of patients and APLN evaluation methodology.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.4'>Roles of APLN and APELA in ovarian cancer</ns0:head><ns0:p>Previous studies demonstrated that the level of APLN expression was significantly increased in ovarian cancer cells. In MCF-7 cells, the APLN-APLNR system was involved in regulating the proliferation and metastasis via phosphorylating ERK1/2 pathway <ns0:ref type='bibr' target='#b54'>(Peng et al., 2015)</ns0:ref>. Secretion and expression of APLN as a mitogenic factor was also detected in OVCAR3 cell line which regulates the proliferation progress in a dose-dependent manner <ns0:ref type='bibr' target='#b26'>(Hoffmann, Fiedor and Ptak, 2017)</ns0:ref>. In SKOV3 cell line, over-expressed APLN and its receptor reduced the sensitivity of antiangiogenic therapeutic regimen <ns0:ref type='bibr' target='#b40'>(Masoumi et al., 2020)</ns0:ref>. Recently, an elevated APELA level was documented in various histotypes of ovarian cancers, especially in ovarian clear cell carcinoma (OCCC) <ns0:ref type='bibr' target='#b87'>(Yi et al., 2017)</ns0:ref>. It is speculated that APELA was involved in multiple pathways in tumorigenesis. For instances, it accelerates cell mitosis and migration through activating ERK and PI3K/AKT cascades <ns0:ref type='bibr'>(Ho et al., 2015)</ns0:ref>. In addition, it was also reported that APELA might negatively regulate p53 in OCCC cell lines, causing non-apoptotic cell growth through an APLNR-independent pathway <ns0:ref type='bibr' target='#b87'>(Yi et al., 2017)</ns0:ref>. However, another study showed that increased APLNR expression was significantly correlated with decreased median overall survival by 14.7 months in patients with high-grade serous ovarian cancer, and APLNR expression was both necessary and sufficient to increase prometastatic phenotypes of ovarian cancer cells including the proliferation, cell adhesion, migration and invasion in vitro <ns0:ref type='bibr' target='#b45'>(Neelakantan et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.5'>Distribution of APLN and APLNR in the oviduct</ns0:head><ns0:p>The expression of apelinergic system in the ovary has been widely discussed. However, currently only one study mentioned its expression in the sheep oviduct. This study showed that APLN was detected in the epithelial cell coat of ampullary ciliated cells, which facilitated the transport of oocytes and spermatozoa through the oviductal tract. APLNR was expressed exclusively in the ampullary secretory cells, suggesting the fertilization and implantation roles of this system during the luteal stage <ns0:ref type='bibr' target='#b42'>(Mercati et al., 2019)</ns0:ref>. In ewe oviduct, the mRNA level of both APLN and APLNR were detected higher in estrus when compared with those in anestrus. As the function of oviduct is to provide place for embryogenesis and transport of early embryo, the disruption of normal oviduct function may cause infertility, which is considering as a serious concern recently, and attracting more expected studies <ns0:ref type='bibr' target='#b42'>(Mercati et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='6.'>Role of APLN in uterus</ns0:head></ns0:div> <ns0:div><ns0:head n='6.1'>Distribution and function of APLN and APLNR in uterus</ns0:head><ns0:p>Recently, it has been witnessed that APLN and its receptor also display potential behaviors in uterus among species such as rat, mouse, ewe and human. The expression of APLNR mRNA in uterus was firstly detected through a nonspecific rat tissue RT-PCR screen <ns0:ref type='bibr' target='#b27'>(Hosoya et al., 2000)</ns0:ref>, then its ligand APLN was described to be elevated during the secretory phase in the glandular cells of endometrial layer whereas it remained at a low level in the stromal cells <ns0:ref type='bibr' target='#b32'>(Kawamata et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b50'>Ozkan et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b42'>Mercati et al., 2019)</ns0:ref>. It is evidently deduced that the apelinergic system is stimulated by elevated steroid hormones during the uterine secretory phase also known as the luteal phase of ovarian cycle. APLN subsequently plays a spatio-temporal role in spiral arterioles maturation and interstitial edema in endometrium where angiogenesis is taking place. An in vitro study showed that APLN played an vasodilation role in suppressing both spontaneous and oxytocin-induced contraction in human myometrial fibers <ns0:ref type='bibr' target='#b22'>(Hehir and Morrison, 2012)</ns0:ref>. However, serum APLN was also reported to exert a positive inotropic effect in rat myometrial layer via PKC-mediated intracellular Ca 2+ amplication <ns0:ref type='bibr' target='#b30'>(Kacar et al., 2018)</ns0:ref>. These opposite results may be explained by the intracellular balance between vascular dilation and smooth muscle contraction mechanisms of apelinergic system, as well as the impacts of species diversity and reagent concentrations.</ns0:p></ns0:div> <ns0:div><ns0:head n='6.2'>Role of APLN in endometriosis</ns0:head><ns0:p>Endometriosis is defined as an estrogen-dependent invasion of endometrial tissue from uterus to uterine adnexa <ns0:ref type='bibr' target='#b9'>(Bulun et al., 2019)</ns0:ref>. It is a very common cause for chronic pain in the pelvis and could even lead to infertility in moderate and significant patients <ns0:ref type='bibr' target='#b14'>(Chaljub, Medlock and Services, 2018)</ns0:ref>. Current explanations of endometriosis pathogenesis are endometrial implantation, coelomic metaplasia and induction theories which are all in agreement with the impacts of steroid hormone dysregulation and inflammatory response. Similar expression patterns of APLN was seen in both eutopic and ectopic endometrium during the menstrual cycle indicated that the ectopic endometrial lesion could share some characteristics with eutopic cellular processes in endometrium regeneration <ns0:ref type='bibr' target='#b42'>(Mercati et al., 2019)</ns0:ref>. Additionally, the angiogenesis and vasodilation effects of APLN could potentially be one of the causes in triggering the symptoms of endometriosis, whereas more studies are expected to confirm this point.</ns0:p></ns0:div> <ns0:div><ns0:head n='7.'>Roles of APLN and APELA during pregnancy</ns0:head><ns0:p>7.1 Role of APLN and APELA in embryonic development APLNR was reported to be expressed in the angioblast of frog embryo, which would contribute to the formation of aortic arch vessels and posterior cardinal veins. APLN was detected either within or adjacent to the endothelial cells expressed by APLNR, functioning as an angiogenic agent for nascent blood vessels, especially the intersegmental vessels formation. It also showed the chemotactic ability of APLN to induce the migration of endothelial cells <ns0:ref type='bibr' target='#b19'>(Cox et al., 2006)</ns0:ref>. Moreover, APLN was proved possessing an anti-apoptotic role in osteoblastic cell line of humans and mice <ns0:ref type='bibr' target='#b74'>(Tang et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b82'>Xie et al., 2007)</ns0:ref>. It releases Bcl-2 molecule from Bad via activating PI3K/Akt pathway, which subsequently attenuates the activation of downstream apoptotic factors, such as cytochrome c and caspase-3, resulting in the inhibition of osteoblastic cell apoptosis. Additionally, APELA has also been revealed to hold a key role in cardiogenesis, angiogenesis and bone formation during the embryonic development. In APELA knockout mice, the hearts are developed poorly or not developed at all, suggesting the essential role in heart morphogenesis <ns0:ref type='bibr' target='#b16'>(Chng et al., 2013)</ns0:ref>. It triggers the endothelial precursor (angioblasts) to migrate towards midline and coalesce underneath the notochord, and form the first axial vessels <ns0:ref type='bibr' target='#b53'>(Pauli et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b22'>Helker et al., 2015)</ns0:ref>. Consistently, APELA-APLNR axis is involved in early placental development and angiogenesis <ns0:ref type='bibr'>(Ho et al., 2015</ns0:ref><ns0:ref type='bibr' target='#b23'>(Ho et al., , 2017))</ns0:ref>. In mouse placenta, APELA is robustly expressed in syncytiotrophoblasts from early-to-mid gestation, which favors the sprout of new formed blood vessels <ns0:ref type='bibr' target='#b23'>(Ho et al., 2017)</ns0:ref>. It is also associated with skeletal formation through inhibiting the expression of Sox32, which can bind to Pou5f3 and Nanog molecules as a transcription factor in dorsal endoderm during gastrulation, and inhibit the formation of Pou5f3-Nanog complex. APELA-APLNR pathway can reduce Sox32 expression and allow Pou5f3-Nanog complexes formation, subsequently activating bone morphogenetic protein signaling for sclerotome fate determination <ns0:ref type='bibr' target='#b55'>(Perez-Camps et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='7.2'>Distribution and function of APLN and APELA in the placenta</ns0:head><ns0:p>Apelinergic system has been hypothesized as a key factor in placental angiogenesis. APLN was strongly expressed in the cytoplasm of human cytotrophoblasts during the first two trimester of pregnancy, and then decreased at the third trimester. Subtle signals were also detected in the syncytiotrophoblasts during the first trimester, but it disappeared completely in the third trimester <ns0:ref type='bibr' target='#b18'>(Cobellis et al., 2007)</ns0:ref>. The expression of APLNR in the placenta was later than that of APLN. In the first trimester, it was relatively low and exclusively in the cytotrophoblasts. However, in the third trimester, APLNR was expressed intensely not only in cytotrophoblasts but also in syncytiotrophoblasts, smooth muscle cells and endothelial cells inside of the placental villi <ns0:ref type='bibr' target='#b18'>(Cobellis et al., 2007)</ns0:ref>. This change suggests a potential chemoarractant and vasculogenic role of APLN in the invasion process of interstitial and endovascular extravillous trophoblasts. In mouse, APELA was detected initially in the trophoblasts and then increased robustly after the allantoic fusion. At the mid-gestation, it was expressed restrictedly in syncytiotrophoblasts, where APLNR was wildly existed in adjacent endothelial cells, indicating a paracrine function of this system to favor the placental angiogenic sprouting <ns0:ref type='bibr' target='#b23'>(Ho et al., 2017)</ns0:ref>. However, in human placenta, APELA was expressed in both cytotrophoblasts and syncytiotrophoblasts synchronously during the whole pregnancy <ns0:ref type='bibr' target='#b23'>(Ho et al., 2017)</ns0:ref> and its speculated role remains to be illuminated.</ns0:p></ns0:div> <ns0:div><ns0:head n='7.3'>Regulation of APELA and APLN in PE</ns0:head><ns0:p>The basic pathological changes of hypertensive disorders in pregnancy are currently recognized as insufficient spiral arteries recasting and inflammation mediated endothelial damage triggered by the intricate network of signaling cascades. APELA as mentioned above plays a crucial role in placental angiogenesis via activating PI3K/AKT/mTOR pathway <ns0:ref type='bibr' target='#b23'>(Ho et al., 2017)</ns0:ref>, and whether its reduction could lead to PE is now being widely studied. It was firstly discovered that APELA knockout pregnant mice exhibited a hypertensive symptom accompanied with proteinuria and glomerular endotheliosis, which were manifested as preeclampsia-like symptoms <ns0:ref type='bibr' target='#b23'>(Ho et al., 2017)</ns0:ref>. Scientists therefore started investigating the change of APELA in PE patients and wanted to know whether the APELA could act as a biomarker <ns0:ref type='bibr' target='#b91'>(Zhou et al., 2019)</ns0:ref>. In the late-onset PE (LOPE), two studies measured a significant increased concentration of APELA in the placenta and serum <ns0:ref type='bibr' target='#b51'>(Panaitescu et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b52'>Para et al., 2020)</ns0:ref>, while one study measured significant decrease <ns0:ref type='bibr' target='#b91'>(Zhou et al., 2019)</ns0:ref>. And for early-onset PE (EOPE), only one study observed decrease in both APELA mRNA and protein <ns0:ref type='bibr' target='#b37'>(Wang et al., 2019)</ns0:ref>, while other studies report no significant change of APELA level on either protein or mRNA <ns0:ref type='bibr'>(Pritchard et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b80'>Villie et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b91'>Zhou et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b51'>Panaitescu et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b52'>Para et al., 2020)</ns0:ref>. Furthermore, it was found that hypoxia significantly decreased the expression of LIN28B, LIN28A and APELA, and the downregulation of LIN28B and APELA may play a role in PE by reducing trophoblast invasion and syncytialization <ns0:ref type='bibr' target='#b11'>(Canfield et al., 2019)</ns0:ref>. There are also contradictions about the expression level of APLN in PE patients. Initially, a clinical study found an increased APLN protein level in the placental samples of PE patients, indicating a speculated correlation between APLN and PE <ns0:ref type='bibr' target='#b18'>(Cobellis et al., 2007)</ns0:ref>. This study was further proved by an experiment which showed intravenous injection of APLN in male mice could lead to the downregulation of blood pressure, suggesting that APLN might act as a vasodilator in PE <ns0:ref type='bibr'>(Lee et al., 2000)</ns0:ref>. However, case studies also found either decreased <ns0:ref type='bibr' target='#b28'>(Inuzuka et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b84'>Yamaleyeva et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b66'>Sattar Taha, Zahraei &amp; Al-Hakeim, 2020)</ns0:ref> or no significantly changed <ns0:ref type='bibr' target='#b44'>(Van Mieghem et al., 2016)</ns0:ref> APLN level in PE patients compared with normotensive pregnancies. Not only its ligands, the expression of APLNR is also rather conflicting. It has long been thought that APLNR level increases when the patient suffer from PE <ns0:ref type='bibr' target='#b18'>(Cobellis et al., 2007)</ns0:ref>, but two other studies suggest APLNR level remains unchanged when PE occurs <ns0:ref type='bibr' target='#b84'>(Yamaleyeva et al., 2015;</ns0:ref><ns0:ref type='bibr'>Pritchard et al., 2018)</ns0:ref>. However, one recent study found a significant decrease both in APLNR mRNA expression and in situ expression between PE patients and normal control, and this significance can be found when controls compared to both EOPE and LOPE groups <ns0:ref type='bibr' target='#b91'>(Zhou et al., 2019)</ns0:ref>. Altogether, the different expression of apelinergic system could be explained by confounding factors like BMI and mean maternal age mismatches between the cases and controls. Moreover, the balance between vasorelaxant and myocardial contractile effects of apelinergic system, as well as the crosslink of apelinergic axis with intricate inflammatory and endothelial factors in PE should also be taken into consideration. Further investigations should focus on the specific molecular mechanisms of APLN and APELA in the hypertensive disorders of pregnancy.</ns0:p></ns0:div> <ns0:div><ns0:head n='7.4'>Regulation of APLN and APELA in GDM</ns0:head><ns0:p>APLN as one of the adipose tissue-derived hormones has been identified to play a role in blood glucose metabolism <ns0:ref type='bibr'>(Antushevich and W&#243;jcik, 2018)</ns0:ref>. It has been described that insulin may upregulate the expression of APLN through PKC and PI3K signaling pathways in both murine and human adipocytes <ns0:ref type='bibr' target='#b7'>(Boucher et al., 2005)</ns0:ref>. Raised apelin levels were found in both insulinresistant mice and type 2 diabetes mellitus patients <ns0:ref type='bibr' target='#b83'>(Xu, Tsao and Yue, 2011)</ns0:ref>, which supported the speculation that insulin can stimulate APLN secretion. Nevertheless, the correlation of APLN levels with GDM has not yet reached an agreement in clinical researches. Three studies reported a decrease of serum APLN level in GDM patients <ns0:ref type='bibr' target='#b4'>(Aydin, 2010;</ns0:ref><ns0:ref type='bibr' target='#b8'>Boyadzhieva et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b0'>Akinci et al., 2014)</ns0:ref> while another two groups revealed an increase <ns0:ref type='bibr'>(Aslan et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b10'>Caglayan et al., 2016)</ns0:ref>. In contrast, there were also no significant association reports between normal control and GDM patients <ns0:ref type='bibr' target='#b78'>(Telejko et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b49'>Oncul et al., 2013)</ns0:ref>. Thus, the correlation of APLN with the pathophysiology of GDM remains to be elucidated. In addition, factors like BMI, HOMA-IR and birth weight have been shown not correlated with serum APLN level according to these studies <ns0:ref type='bibr'>(Aslan et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b49'>Oncul et al., 2013)</ns0:ref>, but these confounding factors varied a lot among different groups during pregnancy, which was probably one of the cases in the controversy. APELA had a positive correlation with fasting plasma glucose levels in healthy pregnant women during the second trimester, while decreased APELA circulating level was observed in GDM patients at the same time. In the third trimester, circulating APELA level decreased significantly in both GDM and healthy groups. This study suggested that APELA could be a physiological demand in glucose metabolism, and further contributions should focus on dynamic levels monitoring and mechanism analysis <ns0:ref type='bibr'>(Guo et al., 2020)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='8.'>Conclusion</ns0:head><ns0:p>This review presents a landscape of the novel APLN/APELA-APLNR system in the female reproductive field (Table <ns0:ref type='table'>1 and Fig 1)</ns0:ref>. Intricate signaling pathways and crosslinks of APLN and APELA imply their multifunctional roles in different organs like ovary, uterus and placenta, during specific developmental stages. APLN as an adipokine appears to have specific effects in steriodogenesis and metabolic regulation in GCs and CL of the ovary. Insulin and IGF1-induced APLN secretion possibly plays a role in glucose regulation in GDM patients. In addition, APLN may sustain a balance between the vasodilative and myocontractile effects in the uterus which could be correlated with hypertensive disorders during the pregnancy. Similarly, APELA as a novel ligand of APLNR also has a potential role in PE, based on the angiogenic effect of spiral arterioles. APELA is essential for fetal and placental development through stimulating the invasion of extravillous trophoblasts. This process is potentially achieved through a chemoattractant mechanism in placental angiogenic sprouting. Moreover, there is a hyperplasia effect of APELA which could be one of the causes in ovarian tumorigenesis. All the data suggest that there should be additional studies to further investigate the precise roles of this axis in female reproductive system especially at the pathological profile. In the future, it will be important to clarify the crosslink and interaction between APLN and other adipokines in sex hormone regulation and energy metabolism. Specific expression and biological effects of APELA in ovary and uterus are also needed in prospect. It may also be crucial to identify the balance of smooth muscle contraction and vasodilation in apelinergic system at a molecular hierarchy. Collectively, the apelinergic axis is still a novel project for further investigation in both physiological and pathological aspects, and probably brings better therapeutic or prophylactic intervention towards female reproductive disorders.</ns0:p></ns0:div> <ns0:div><ns0:head n='9.'>Acknowledgments</ns0:head><ns0:p>None.</ns0:p></ns0:div> <ns0:div><ns0:head n='10.'>Additional information and Declarations</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:05:48913:1:0:CHECK 15 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure legends</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Fig 2 A) (Than et al., 2014). 3.3 Characteristics of APELA Apela gene, located on chromosome 4 of Homo sapiens (Fagerberg et al., 2014) (chromosome 8 in Mus musculus</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Expression and function of APLN and APELA in reproduction system. (A) In physiological conditions, APLN (in blue textbox) and APELA (in green textbox) play diverse roles at the different parts of the ovary, uterus and placenta. (B) In pathological conditions, aberrant expression of APLN (in orange textbox) and APELA (in purple textbox) lead to female reproductive disorders such as polycystic ovary syndrome (PCOS), ovarian cancer, preeclampsia (PE), gestational diabetes mellitus (GDM) and endometriosis. * indicating potential apelinergic stimulating factors. ? indicating still unclear or controversy about the functions or contributions of apelinergic molecules in these diseases. &#8593;and&#8595;in the textbox means increase and decrease respectively, both indicate statistically significant changes. &#8594; means resulting.Figure 2: Intracellular signaling pathways and physiological functions of APLN and APELA. (A) Both APLN (in blue) and APELA (in orange) can classically activate G&#945;i/o and G&#945;q/11 mediated intracellular transduction via binding to their common receptor APLNR. (B) APELA also stimulates PI3K-independent NODAL/TGF&#946; signal through alternative receptors in hESCs. (C) Non-coding APELA binds to hnRNPL and promotes p53-mediated cell apoptosis. AC, adenylate cyclase; eNOS, endothelial nitric oxide synthase; IncRNA, long non-coding RNA; hnRNPL, heterogeneous nuclear ribonucleoprotein L.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 1: Expression and function of APLN and APELA in reproduction system. (A) In physiological conditions, APLN (in blue textbox) and APELA (in green textbox) play diverse roles at the different parts of the ovary, uterus and placenta. (B) In pathological conditions, aberrant expression of APLN (in orange textbox) and APELA (in purple textbox) lead to female reproductive disorders such as polycystic ovary syndrome (PCOS), ovarian cancer, preeclampsia (PE), gestational diabetes mellitus (GDM) and endometriosis. * indicating potential apelinergic stimulating factors. ? indicating still unclear or controversy about the functions or contributions of apelinergic molecules in these diseases. &#8593;and&#8595;in the textbox means increase and decrease respectively, both indicate statistically significant changes. &#8594; means resulting.Figure 2: Intracellular signaling pathways and physiological functions of APLN and APELA. (A) Both APLN (in blue) and APELA (in orange) can classically activate G&#945;i/o and G&#945;q/11 mediated intracellular transduction via binding to their common receptor APLNR. (B) APELA also stimulates PI3K-independent NODAL/TGF&#946; signal through alternative receptors in hESCs. (C) Non-coding APELA binds to hnRNPL and promotes p53-mediated cell apoptosis. AC, adenylate cyclase; eNOS, endothelial nitric oxide synthase; IncRNA, long non-coding RNA; hnRNPL, heterogeneous nuclear ribonucleoprotein L.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='28,42.52,331.87,525.00,263.25' type='bitmap' /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48913:1:0:CHECK 15 Aug 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48913:1:0:CHECK 15 Aug 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot' n='3'>For each study, the authors, year, disease type, species, samples, molecule, sample size (No. of cases and controls), analyzed 4 expression and significance were listed. There would be a significance when p&lt;0.05, and p values were listed in the table (if given). 5 The table was ordered by diseases, molecules and year of publication. PCOS, polycystic ovary syndrome; OvCa, ovarian cancer; 6 PE, preeclampsia; GDM, gestational diabetes mellitus; NA, not available.PeerJ reviewing PDF | (2020:05:48913:1:0:CHECK 15 Aug 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

" Department of Physiology Basic Medical College Nanchang University Nanchang Jiangxi 330006 Haibin Kuang 86-791-83827148 [email protected] Yanling 86-791-86895863 [email protected] August 10th, 2020 Dear Editors: We thank the reviewers for their generous comments on the manuscripts, and have carefully reviewed the comments and revised the manuscript as per reviewers’ suggestions. Our point to point responses are appended in the part of “Response to Reviewers”. In particular we have checked our reference list and polished our English grammar multiple times. We also added the content of APLN system expression in oviduct. We believe that the manuscript is now suitable for publication in PeerJ. Sincerely, Dr Haibin Kuang Professor of Physiology Response to Reviewers: Reviewer 1 (Anonymous) Dear Authors, This review deals with a very interesting and current topic. As the reviewer’s knowledge, to date there are not papers that describe apelin system on all organs and structures of female genital system as it is showed in this review. The manuscript is clearly written and English style is fluent. A number of articles have been taken into account by Authors. Each section is accurately described and well detailed. However, a paragraph describing apelin on oviduct should be added. I have made some corrections in order to improve the clarity of the text and enrich information where necessary. Response: We are very pleased with the positive comments of reviewer; and also appreciate your constructive suggestions and critiques. The paragraph describing apelin on oviduct was already added in the revised manuscript. The changes made in the text: 5.5 Distribution of APLN and APLNR in the oviduct The ovarian expression of apelinergic system has been widely discussed. However, currently only one study mentioned its expression in the sheep oviduct. This study showed that APLN was detected in the epithelial cell coat of ampullary ciliated cells, which facilitated the transport of oocytes and spermatozoa through the oviductal tract. APLNR was expressed exclusively in the ampullary secretory cells, suggesting the fertilization and implantation roles of this system during the luteal stage (Mercati et al., 2019). In ewe oviduct, the mRNA level of both APLN and APLNR were detected higher in estrus when compared with those in anestrus. As the function of oviduct is to provide place for embryogenesis and transport of early embryo, the disruption of normal oviduct function may cause infertility, which is considering as a serious concern recently, and attracting more expected studies (Mercati et al., 2019). Line 91: “HG11” should be mentioned among receptor known names. Line 96: delete “(1996)”. The year is already write in the citation. Line 172. Delete a parenthesis: “(Ulitsky et al., 2011))” Line 322: replace “adema” with “edema”. Line 432: replace “marine” with “murine”. Response: Thank the reviewer very much for your patience and careful review. We have made those changes according to your advice in the revised manuscript. Line 134: please, check the reference “Chun et al., 2010” and verify that it is correct in this position. Information described in the previous sentences (From line 129 to line 134: Human APLN gene is located on …. …. generating pyroglutamate-APLN-13 (Pyr1-APLN-13) cannot be found in Chun et al., 2010. Response: Thank the reviewer very much for your patience and careful review. We have checked this reference, and changed it to “Tatemoto et al., 1998” in the revised manuscript. Line 138. Since the review takes into account the entire female reproductive system and not just the ovaries, oviducts should also be added in the following sentence: 'To date, APLN is widely distributed in the female reproductive system such as the ovary, uterus and placenta'. Please, consider Mercati F, Scocco P, Maranesi M, et al. Apelin system detection in the reproductive apparatus of ewes grazing on semi-natural pasture. Theriogenology. Response: We are very appreciated for the reviewer’s constructive suggestion and the very specialized article recommended. The paragraph describing apelin on oviduct was already added in the revised manuscript. The changes made in the text: 5.5 Distribution of APLN and APLNR in the oviduct The ovarian expression of apelinergic system has been widely discussed. However, currently only one study mentioned its expression in the sheep oviduct. This study showed that APLN was detected in the epithelial cell coat of ampullary ciliated cells, which facilitated the transport of oocytes and spermatozoa through the oviductal tract. APLNR was expressed exclusively in the ampullary secretory cells, suggesting the fertilization and implantation roles of this system during the luteal stage (Mercati et al., 2019). In ewe oviduct, the mRNA level of both APLN and APLNR were detected higher in estrus when compared with those in anestrus. As the function of oviduct is to provide place for embryogenesis and transport of early embryo, the disruption of normal oviduct function may cause infertility, which is considering as a serious concern recently, and attracting more expected studies (Mercati et al., 2019). Line 142. It would be better to insert at least another citation describing not only apelin system in energy metabolism but also its role in GnRH, gonadotropins and steroids through hypothalamo-pituitary-gonadal axis; for example, Yang N, Li T, Cheng J, Tuo Q, Shen J. Role of apelin/APJ system in hypothalamic-pituitary axis. Clin Chim Acta. 2019;499:149-153. doi:10.1016/j.cca.2019.09.011. Response: Thank the reviewer for your suggestion and we have added this article to our revised manuscript. Change made in the text: Emphatically, APLN is identified as one type of adipokines secreted by white adipose tissue, which plays a role with other adipokines in regulating the secretion of gonadotropin releasing hormone (GnRH), gonadotropins and steroids through hypothalamo-pituitary-gonadal (HPG) axis (Bertrand, Valet & Castan-Laurell, 2015; Yang et al., 2019). Figure 2. In reviewer’ opinion Apela is (in yellow) and not (in orange). Response: Thank the reviewer very much for your patience and careful review. It is actually confusing by being yellow itself but also having an orange edge around it. To avoid the unnecessary confusion, we have changed it to completely orange in our revised Figure 2. Line 195. Figure 2 C should be mentioned after figure 2 B that is at line 203. Response: Thank the reviewer very much for your patience and careful review. We agree and have made corresponding changes in both revised manuscript and the revised Figure 2. Line 228. Please, check the reference “Kwak et al., 2019”. Information regarding “APLN as a steroidogenic regulator in ovaries” are not included in this article. Response: Thank the reviewer very much for your patience and careful review. We agreed and deleted this reference in the revised manuscript. In chapter 5 'Roles of APLN and APELA in the ovary', sheep must also be mentioned among the species in which apelin and apelin receptor were detected at the follicle and corpus luteum level, as described in “Mercati F, Scocco P, Maranesi M, et al. Apelin system detection in the reproductive apparatus of ewes grazing on semi-natural pasture. Theriogenology. 2019;139:156-166. doi:10.1016/j.theriogenology.2019.08.012' Response: Thank the reviewer very much for your constructive suggestion. We have added the expression of APLN and APLNR in the sheep according to the article recommended. Change made in the text: In ewes, both APLN and APLNR proteins were observed in large luteal cells, and the highest level of APLN mRNA was detected in the luteal phase of the ovarian cycle compared to ewes in the anestrous one (Mercati et al., 2019). Since this review is intended to describe the apelin system in the female reproductive apparatus, all information existing in the scientific literature must be considered. Apelin and apelin receptor have been described in the ewe oviduct with a higher level of apelin during the luteal phase than in the anestrous phase of the ovarian cycle. A role of the apelin system in the regulation of gamete transport and nutrition / support along the oviduct has been hypothesized. I suggest that you consider the data on the oviduct described in this publication: “Mercati F, Scocco P, Maranesi M, et al. Apelin system detection in the reproductive apparatus of ewes grazing on semi-natural pasture. Theriogenology. 2019;139:156-166. doi:10.1016/j.theriogenology.2019.08.012 Response: We are very appreciated for the reviewer’s constructive suggestion and the very specialized article recommended. The paragraph describing apelin on oviduct is added, The changes made in the text: 5.5 Distribution of APLN and APLNR in the oviduct The ovarian expression of apelinergic system has been widely discussed. However, currently only one study mentioned its expression in the sheep oviduct. This study showed that APLN was detected in the epithelial cell coat of ampullary ciliated cells, which facilitated the transport of oocytes and spermatozoa through the oviductal tract. APLNR was expressed exclusively in the ampullary secretory cells, suggesting the fertilization and implantation roles of this system during the luteal stage (Mercati et al., 2019). In ewe oviduct, the mRNA level of both APLN and APLNR were detected higher in estrus when compared with those in anestrus. As the function of oviduct is to provide place for embryogenesis and transport of early embryo, the disruption of normal oviduct function may cause infertility, which is considering as a serious concern recently, and attracting more expected studies (Mercati et al., 2019). Table 1. In the title of the table, it would be better to write the full name of disease type than their abbreviation. Response: We agree. The changes have been made in the revised Table 1. Such as the revised title for table 1: Table 1: Summary of studies about the expressional changes of APLN and APELA in the polycystic ovary syndrome (PCOS), Ovarian cancer (OvCa), preeclampsia (PE) and gestational diabetes mellitus (GDM). Figure 1. In the caption, please, explain the significance of the arrows contained in textboxes. Response: Thank the reviewer for your careful review and reminder. The significance of the arrows in the textboxes has been added in the revised figure legend of Figure 1. Such as the revised legend for figure 1: ↑and↓ in the textbox means increase and decrease respectively, both indicate statistically significant changes. → means resulting. Please, check English language. Response: Thank the reviewer for your kind suggestion. We have checked it multiple times and have tried our best. Reviewer 2 (Anonymous) Apelin and Apela are two endogenous ligands of APLNR, and composing the apelinergic axis with APLNR. The apelinergic pathway has been generating increasing interest in the past few years for its potential as a therapeutic target in heart failure, pulmonary arterial hypertension, atherosclerosis, but also type 2 diabetes, and preeclampsia. This review summarizes and evaluates the current role of apelinergic system in female reproductive system at both physiological and pathological conditions. suggesting its potential prospect as a diagnostic biomarker and/or therapeutic intervention in the polycystic ovary syndrome, ovarian cancer, preeclampsia and gestational diabetes mellitus. This work is of significance to Gynaecology and Obstetrics. Response: We are very pleased with the positive comments of reviewer; and also appreciate your constructive suggestions and critiques. 1、Recent published paper in J Matern Fetal Neonatal Med (PMID: 32008387) should be cited in this review. Response: Thank the reviewer very much for your suggestion and educational article recommended. We have cited this article in our revised manuscript. For example: In the late-onset PE (LOPE), two studies measured a significant increased concentration of APELA in the placenta and serum (Panaitescu et al., 2020; Para et al., 2020), while one study measured significant decrease (Zhou et al., 2019). And for early-onset PE (EOPE), only one study observed decrease in both APELA mRNA and protein (Wang et al., 2019), while other studies report no significant change of APELA level on either protein or mRNA (Pritchard et al., 2018; Villie et al., 2019; Zhou et al., 2019; Panaitescu et al., 2020; Para et al., 2020) 2、The description of APLNR in PE should be added. Response: We really appreciate it for your constructive suggestion and we admit the APLNR in PE is also important. Such as the paragraph added: Not only its ligands, is the expression of APLNR also rather conflicting. It has long been thought that APLNR level increases when the patient suffer from PE (Cobellis et al., 2007), but two other studies suggest APLNR level remains unchanged when PE occurs (Yamaleyeva et al., 2015; Pritchard et al., 2018). However, one recent study found a significant decrease both in APLNR mRNA expression and in situ expression between PE patients and normal control, and this significance can be found when controls compared to both EOPE and LOPE groups (Zhou et al., 2019). 3、The expression level of APLA in patients with late-onset PE is controversial (Ho et al., 2017 ,Wang et al., 2019; Zhou et al., 2019, Canfield et al., 2019) , while that of ELA in patients with early-onset PE is consistent (Pritchard et al., 2018; Villie et al., 2019; Zhou et al., 2019; Panaitescu et al., 2020), Therefore, table1 should distinguish early-onset PE from late-onset PE. Response: Thank the reviewer very much for your constructive suggestion. We agree and have adjusted Table 1 according to your advice. However, as Ho et al., 2017 and Canfield et al., 2019 are not case studies, and therefore are excluded from our table. We are appreciated for your understanding. 4、Please, add corresponding reference(s) the following sentences in 3.2: ……reduction of cyclic adenosine monophosphate (cAMP) and activation of phospholipase C-β (PLC-β), respectively (Fig 2 A). Gαi/o activates PI3K/Akt dependent manner which is crucial for cell survival and nitric oxide (NO) induced vasodilation. Response: Thank the reviewer very much for your patience and careful review. We have added the corresponding references to the sentences in the revised manuscript. Reference added: ……reduction of cyclic adenosine monophosphate (cAMP) and activation of phospholipase C-β (PLC-β), respectively (Fig 2 A) (Chapman, Dupré & Rainey, 2014). Gαi/o activates PI3K/Akt dependent manner which is crucial for cell survival and nitric oxide (NO) induced vasodilation (Liu et al., 2010) "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>APLN, APELA and their common receptor APLNR (composing the apelinergic axis) have been described in various species with extensive body distribution and multiple physiological functions. Recent studies have witnessed emerging intracellular cascades triggered by APLN and APELA which play crucial roles in female reproductive organs, including hypothalamus-pituitary-gonadal axis, ovary, oviduct, uterus and placenta.</ns0:p><ns0:p>However, a comprehensive summary of APLN and APELA roles in physiology and pathology of female reproductive system has not been reported to date. In this review, we aim to concentrate on the general characteristics of APLN and APELA, as well as their specific physiological roles in female reproductive system. Meanwhile, the pathological contexts of apelinergic axis dysregulation in the obstetrics and gynecology are also summarized here, suggesting its potential prospect as a diagnostic biomarker and/or therapeutic intervention in the polycystic ovary syndrome, ovarian cancer, preeclampsia and gestational diabetes mellitus.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Main article text 1. Introduction</ns0:head><ns0:p>Apelin receptor (APLNR, also known as APJ, APJR, AGTRL1 and HG11) was firstly identified as a class A G protein-coupled receptor in 1993. It consists of 380 amino acids, which has a sequence sharing 31% homology with that of the angiotensin type 1 receptor <ns0:ref type='bibr'>(O'Dowd et al., 1993)</ns0:ref>. Nevertheless, APLNR cannot actually bind to angiotensin II and remains as an 'orphan receptor' until its endogenous ligand apelin (APLN, also named APEL and XNPEP2) was later extracted from bovine stomach <ns0:ref type='bibr' target='#b67'>(Tatemoto et al., 1998)</ns0:ref>. APLN is generally existed in functional isoforms which are cleaved and modified from the C-terminus of a 77-amino acid pre-propeptide encoded by APLN gene, with different affinities for APLNR and prevalent distribution <ns0:ref type='bibr' target='#b14'>(Chapman, Dupr&#233; &amp; Rainey, 2014)</ns0:ref>. Both APLN and its receptor APLNR levels are universally high at multiple organs like brain, retina, heart, stomach, liver, kidney and blood vessels in many species <ns0:ref type='bibr' target='#b34'>(Kawamata et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b86'>Zeng et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b33'>Kasai et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b52'>Qian et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b36'>Krist et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b41'>Lv et al., 2017)</ns0:ref>. Recent years, apelin receptor early endogenous ligand (APELA, also named ELABELA, Toddler and Ende) was identified as a new endogenous ligand for APLNR in both Chng and Pauli's labs independently <ns0:ref type='bibr' target='#b15'>(Chng et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b45'>Pauli et al., 2014)</ns0:ref>. Similar to APLN, this 54-amino acid polypeptide is also processed into several isoforms. APELA is highly enriched in the early stage of embryo and confirmed to play a vital role in embryogenesis and angiogenesis <ns0:ref type='bibr'>(Norris et al., 2017)</ns0:ref>. APLNR and its two ligands compose the apelinergic axis, which is well delineated in systemic physiological processes like cardiogenesis, angiogenesis, fluid homeostasis, vasodilation and energy metabolism. More recently, several studies have been investigating the possible intervention of apelinergic axis in female reproductive system based on its precise regulation of steroidogenesis, angiogenesis and vasodilation, before moving onto the dysregulation of this system which hypothetically causes fertility disorders and pregnancy complications like polycystic ovary syndrome (PCOS), ovarian cancer, gestational diabetes mellitus (GDM) and preeclampsia (PE) (summarized in Table <ns0:ref type='table'>1</ns0:ref>). This review summarizes and evaluates the current role of apelinergic system in female reproductive system at both physiological and pathological profiles (Fig <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>), as well as providing the direction for future research.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.'>Survey methodology</ns0:head><ns0:p>Jiangxi Provincial Key Laboratory of Reproductive Physiology and Pathology, Medical Experimental Teaching Center of Nanchang University.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.'>APLN and APELA, endogenous ligands of APLNR</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>Characteristics of APLN</ns0:head><ns0:p>Human APLN gene is located on chromosome Xq25-26.1 which encodes a pre-propeptide of 77 amino acids. After cleavage of the 22-amino acid secretory sequence at N terminus by endopeptidases, the propeptide is subsequently processed into three active fragments at several dibasic residues (Arg-Lys and Arg-Arg), including APLN-36, APLN-17 and APLN-13. APLN-13 undergoes post-transcriptional cyclization at the N-terminal glutamine, generating pyroglutamate-APLN-13 (Pyr1-APLN-13) <ns0:ref type='bibr' target='#b67'>(Tatemoto et al., 1998)</ns0:ref>. The potency and efficacy of APLN differ from different isoforms. For instance, APLN-36, APLN-13 and Pyr1-APLN-13 are preponderantly contributed in human cardiovascular regulation <ns0:ref type='bibr' target='#b42'>(Maguire et al., 2009)</ns0:ref>, whereas APLN-17 plays crucial role in APLNR internalization <ns0:ref type='bibr'>(El Messari et al., 2004)</ns0:ref>. To date, APLN is abundantly distributed in female reproductive system such as ovary, oviduct, uterus and placenta. Emphatically, APLN is identified as one type of adipokines secreted by white adipose tissue, which plays a role with other adipokines in regulating the secretion of gonadotropin releasing hormone (GnRH), gonadotropins and steroids through hypothalamo-pituitary-gonadal (HPG) axis <ns0:ref type='bibr' target='#b5'>(Bertrand, Valet &amp; Castan-Laurell, 2015;</ns0:ref><ns0:ref type='bibr' target='#b82'>Yang et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>APLN dependent signaling pathway</ns0:head><ns0:p>APLN/APLNR activates different types of G protein and further stimulates three important signaling pathways, which are phosphorylation of phosphoinositide 3-kinase/protein kinase B (PI3K/Akt), reduction of cyclic adenosine monophosphate (cAMP) and activation of phospholipase C-&#946; (PLC-&#946;), respectively (Fig <ns0:ref type='figure' target='#fig_4'>2 A</ns0:ref>) <ns0:ref type='bibr' target='#b14'>(Chapman, Dupr&#233; &amp; Rainey, 2014)</ns0:ref>. There are two types of pertussis toxin-sensitive G&#945; protein (G&#945;i/o, G&#945;q/11) at the downstream of APLNR, mediating different signaling transduction <ns0:ref type='bibr' target='#b44'>(Masri et al., 2002)</ns0:ref>. G&#945;i/o activates PI3K/Akt dependent manner which is crucial for cell survival and nitric oxide (NO) induced vasodilation <ns0:ref type='bibr' target='#b39'>(Liu et al., 2010)</ns0:ref>. Akt phosphorylates Bcl-2-associated death promoter (Bad, a BH3-only protein) and shifts it to an inert form, which inhibits the binding of Bad and Bcl-2. Bcl-2 plays an anti-apoptotic role by disturbing the aggregation of Bak and Bax (BH123 proteins) in the mitochondrial outer membrane, and thereby attenuating the release of cytochrome c and activation of caspase-3 <ns0:ref type='bibr' target='#b40'>(Liu et al., 2019)</ns0:ref>. Moreover, endothelial nitric oxide synthase (eNOS) can also be activated by Akt through phosphorylation, triggering the release of NO for vasodilation (Fig <ns0:ref type='figure' target='#fig_4'>2 A</ns0:ref>) <ns0:ref type='bibr' target='#b83'>(Yang et al., 2014)</ns0:ref>. Additionally, G&#945;i/o inhibits adenylate cyclase (AC), following with the reduction of 3', 5&#8242;-cAMP and protein kinase A (PKA), which could potentially regulate the glucose homeostasis (Fig <ns0:ref type='figure' target='#fig_4'>2 A</ns0:ref>) <ns0:ref type='bibr' target='#b44'>(Masri et al., 2002)</ns0:ref>. G&#945;q/11 activates PLC-&#946; hydrolyze phosphatidylinositol 4, 5-bisphosphate into second messengers diacylglycerol and inositol trisphosphate, which increases the release of calcium (Ca 2+ ) from intracellular store and activates protein kinase C (PKC) <ns0:ref type='bibr'>(Carp&#233;n&#233; et al., 2007)</ns0:ref>. Amplified intracellular Ca 2+ not only mediates positive inotropic effect in cardiac smooth muscle, but also stimulates NO release in periphery via activating eNOS by calmodulin <ns0:ref type='bibr' target='#b19'>(Dai, Ramirez-Correa &amp; Gao, 2006)</ns0:ref>. PKC in turn activates Ras/MAPK system, which plays a crucial role in cell proliferation <ns0:ref type='bibr' target='#b64'>(Szokodi et al., 2002)</ns0:ref>. Furthermore, MAPK halts the expression of pro-oxidant enzymes and subsequently attenuates the release of reactive oxygen species (ROS), which suppresses lipid metabolism and inflammatory reaction (Fig <ns0:ref type='figure' target='#fig_4'>2 A</ns0:ref>) <ns0:ref type='bibr' target='#b72'>(Than et al., 2014)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>Characteristics of APELA</ns0:head><ns0:p>Apela gene, located on chromosome 4 of Homo sapiens <ns0:ref type='bibr' target='#b20'>(Fagerberg et al., 2014)</ns0:ref> (chromosome 8 in Mus musculus <ns0:ref type='bibr'>(Yue et al., 2014)</ns0:ref> and chromosome 1 in Danio rerio <ns0:ref type='bibr' target='#b73'>(Ulitsky et al., 2011)</ns0:ref>, was originally annotated to be transcribed exclusively into a non-coding RNA in zebrafish embryo <ns0:ref type='bibr' target='#b15'>(Chng et al., 2013)</ns0:ref>, while recently it was confirmed to encode a 54-amino acid precursor which further undergoes proteolysis and generates four mature isoforms: APELA-32, APELA-22, APELA-21 and APELA-11. The shortest isoform is conserved across vertebra species <ns0:ref type='bibr' target='#b29'>(Huang et al., 2017)</ns0:ref>. Compared with APLN, APELA as the second discovered endogenous ligand of APLNR is also ubiquitously detected in placenta, heart, kidney, prostate and mammalian plasma but not as widely as APLN <ns0:ref type='bibr' target='#b75'>(Wang et al., 2015)</ns0:ref>. In addition, studies have reported that APELA is highly expressed in human embryonic stem cells (hESCs) where the APLNR is absent, indicating the existence of an alternative APLNR-independent transduction <ns0:ref type='bibr' target='#b26'>(Ho et al., 2015)</ns0:ref>. A recent report has suggested that an orphan G protein-coupled receptor 25 (GPR25), associated with blood pressure regulation and autoimmune disease, could be activated by both APLN and APELA in non-vertebrates, which is similar as APLN in decreasing the intracellular cAMP level. However, the accurate role of this putative receptor in vertebrate remains to be determined <ns0:ref type='bibr' target='#b87'>(Zhang et al., 2018)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.4'>APELA dependent signaling pathway</ns0:head><ns0:p>Similar to APLN, APELA binds to APLNR, subsequently activating G&#945;i/o and G&#945;q/11 mediated signaling cascades, including PI3K/Akt, PKC and PKC-independent Ras/MAPK pathways (Fig <ns0:ref type='figure' target='#fig_4'>2 A</ns0:ref>) <ns0:ref type='bibr' target='#b49'>(Perj&#233;s et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b87'>Zhang et al., 2018)</ns0:ref>. Nevertheless, it also plays non-redundant role for its specific properties during embryo development. In mouse ESCs, Apela acts as a long non-coding RNA that binds to heterogeneous nuclear ribonucleoprotein L (hnRNPL) at the 3' UTR, which negatively regulates the interaction between p53 and hnRNPL, and promotes p53-mediated DNA damage induced apoptosis (Fig <ns0:ref type='figure' target='#fig_4'>2 B</ns0:ref>) <ns0:ref type='bibr' target='#b38'>(Li et al., 2015)</ns0:ref>. In hESCs, APELA acts as a paracrine secreted hormone that binds to an alternative unknown receptor (non-APLNR) and activates PI3K/AKT signaling for cell survival and self-renewal. This process resembles other fibroblast growth factor like exogenous insulin and endogenous insulin-like growth factors (IGFs) in PI3Kmediated cell proliferation. However, APELA-pulsed hESCs is non-redundant as it also implicates in mesendodermal linage commitment through a PI3K-independent manner <ns0:ref type='bibr' target='#b26'>(Ho et al., 2015)</ns0:ref>. During zebrafish gastrulation, a proper level of APELA acting as a mitogen, indirectly mediates the internalization of ventrolateral mesendodermal cells. This process is presumably achieved via activating NODAL/TGF&#946; signaling pathway (Fig <ns0:ref type='figure' target='#fig_4'>2 C</ns0:ref>), whereas its specific mechanism remains unknown <ns0:ref type='bibr' target='#b45'>(Pauli et al., 2014)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='4.'>Roles of APLN and APELA in HPG axis</ns0:head><ns0:p>Endocrine function of female reproduction initiates from hypothalamic GnRH neurons, which mainly receipt projections from arcuate, paraventricular, supraoptic and medial preoptic nuclei of hypothalamus. These neurons secrete GnRH in a pulsatile manner that favours the secretion of lutenizing hormone (LH) and follicle stimulating hormone (FSH) from gonadotroph cells in the anterior pituitary <ns0:ref type='bibr' target='#b31'>(Jin &amp; Yang, 2014)</ns0:ref>. APLN and its receptor are intensively detected in the same nucleic group of the hypothalamus <ns0:ref type='bibr' target='#b50'>(Pope et al., 2012)</ns0:ref>, indicating an essential behavior of them in reproductive regulation. It was reported in both intracerebroventricular and intraperitoneal infusion that APLN-13 suppressed the secretion of FSH and LH in frontal hypophysis in rats, but it cannot cause a disturbance at the GnRH level <ns0:ref type='bibr' target='#b65'>(Taheri et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b70'>Tekin et al., 2017)</ns0:ref>. The structural and functional similarities between APLN and GnRH <ns0:ref type='bibr' target='#b16'>(Cho et al., 2007)</ns0:ref> were reasonably suspected that APLN could be a competitive inhibitor in the adenohypophysis for GnRH receptors. In addition, the central action of APELA in hypothalamus was also demonstrated that it exerted as an anorexigenic hormone via binding to APLNR and activating arginine vasopressin and corticotropin releasing hormone neurons in the paraventricular nuclei <ns0:ref type='bibr' target='#b57'>(Santoso et al., 2015)</ns0:ref>. Whether it has an effect on reproductive-dependent hormone or not remains to be illuminated.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.'>Roles of APLN and APELA in uterine appendages</ns0:head></ns0:div> <ns0:div><ns0:head n='5.1'>Distribution and role of APLN in the ovarian follicle</ns0:head><ns0:p>Under the normal physiological states, APLN has been identified as a steroidogenic regulator in ovaries of various species including bovine, mouse, rat, porcine, sheep and human <ns0:ref type='bibr' target='#b54'>(Roche et al., 2016</ns0:ref><ns0:ref type='bibr' target='#b55'>(Roche et al., , 2017;;</ns0:ref><ns0:ref type='bibr' target='#b62'>Shuang et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b53'>Rak et al., 2017;</ns0:ref><ns0:ref type='bibr'>Mercati et al., 2019)</ns0:ref>. In cultured bovine follicles, it was firstly reported that APLN mRNA was not found in granulosa cells (GCs), whereas APLNR mRNA was detected and significantly stimulated by estradiol and progesterone in GCs of estrogen-inactive follicles. In interstitial theca cells, both APLN and its receptor mRNA were obviously expressed <ns0:ref type='bibr' target='#b60'>(Shimizu et al., 2009)</ns0:ref>. Two years later, another group cultured bovine ovarian follicles at the similar condition, and found that estradiol over 5 ng/ml (evaluation for follicular maturation) stimulated the expression of APLN and APLNR in theca cells. However, it had no significant effect on the expression of APLN and APLNR in GCs <ns0:ref type='bibr' target='#b59'>(Schilffarth et al., 2009)</ns0:ref>. Recent research confirmed that the expression level of APLN and APLNR were up-regulated in both GCs and oocytes, but remained constant in theca cells <ns0:ref type='bibr' target='#b59'>(Schilffarth et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b60'>Shimizu et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b55'>Roche et al., 2017)</ns0:ref>. In vitro, APLN from GCs of inactive follicles, in response to IGF1 but not to FSH, markedly increased the progesterone production <ns0:ref type='bibr' target='#b55'>(Roche et al., 2017)</ns0:ref>. In porcine follicles, elevated APLN and APLNR were detected following the follicular growth. In turn, APLN significantly increased the secretion of basal steroid hormone (progesterone and estradiol) through the activation of steroidogenic enzyme (3&#946;HSD and CYP19A1) via AMPK&#593; stimulation, whereas it also decreased the IGF1-and FSHinduced steroid secretion <ns0:ref type='bibr' target='#b53'>(Rak et al., 2017)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.2'>Role of APLN in corpus luteum (CL)</ns0:head><ns0:p>As a potent angiogenic factor, apelinergic axis also plays a role in the transient luteal stage after ovulation. It has been mentioned that this system exclusively exists in the bovine smooth muscle of intraluteal arterioles, with ligands elevated from early to late CL and followed by a significant decrease at regressed CL, while receptors increased from early to mid CL and remained constant till regressed CL <ns0:ref type='bibr' target='#b61'>(Shirasuna et al., 2008)</ns0:ref>. Paradoxically, another study showed that APLNR also decreased significantly after mid CL <ns0:ref type='bibr' target='#b59'>(Schilffarth et al., 2009)</ns0:ref>. Luteolytic factor prostaglandin F2&#945; stimulates APLN and APLNR mRNA expression particularly at the periphery of mid CL <ns0:ref type='bibr' target='#b61'>(Shirasuna et al., 2008)</ns0:ref>. In ewes, both APLN and APLNR proteins were observed in large luteal cells, and the highest level of APLN mRNA was detected in the luteal phase of the ovarian cycle compared to ewes in the anestrous one <ns0:ref type='bibr'>(Mercati et al., 2019)</ns0:ref>. In porcine cultured CL, APLN stimulates 3&#946;HSD activity, which converts inert 5-ene-3&#946;HSD to the active 4-ene-3-oxo steroid, therefore it has a pivotal role in progesterone biosynthesis, suggesting an auto/paracrine pattern of the APLN/APLNR system in the ovary <ns0:ref type='bibr' target='#b56'>(R&#243;&#380;ycka et al., 2018)</ns0:ref>. In human, this system is found in the whole ovary through different developmental stages, including luteinized human GCs, theca, oocytes and corona cumulus complex. In cultured luteinized human GCs and follicular fluid, IGF1 exclusively stimulates APLNR expression whereas LH and FSH cannot show the same effect. Conversely, recombinant human APLN-13 and -17 stimulates the secretion of both basal and IGF-induced progesterone and estradiol in a dose-dependent manner, and this process is significantly accelerated in response to IGF1 <ns0:ref type='bibr' target='#b54'>(Roche et al., 2016)</ns0:ref>. This hormone regulation is in agreement to those discovered in bovine that demonstrated APLN could stimulate steroidogenesis and it is speculatively implemented via 3&#946;HSD activation and Akt and MAPK3/1 signaling <ns0:ref type='bibr' target='#b54'>(Roche et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.3'>Regulation of APLN in PCOS</ns0:head><ns0:p>PCOS is a common gynecological endocrinopathy characterized by over-expressed LH triggered hyperandrogenism, chronic oligo/anovulation and polycystic ovaries morphology, with clinical manifestations described as 'hirsutism, acne, irregular menstruation and subfertility' <ns0:ref type='bibr' target='#b68'>(Teede, Deeks &amp; Moran, 2010;</ns0:ref><ns0:ref type='bibr' target='#b69'>Teede et al., 2018)</ns0:ref>. Despite of the positive correlation between PCOS and complications such as visceral obesity, insulin resistance and type 2 diabetes <ns0:ref type='bibr' target='#b21'>(Farrell &amp; Antoni, 2010)</ns0:ref>, the definite aetiology of PCOS at the molecular level still need to be elucidated. It is known that adipokines are bridges to link the energy metabolism and reproductive system, thus they are probably implicated in this process. Hypothetically, APLN controls several aspects of ovarian function in PCOS, underpinned by its role in steroid hormone regulation and insulin resistance. Firstly, the concentration of APLN and its receptors were detected to be significantly increased in PCOS patients with a positive correlation between follicle count and APLN levels <ns0:ref type='bibr' target='#b6'>(Bongrani et al., 2019)</ns0:ref>. This process could be explained by a steroid hormone disturbance effect of APLN in HPG axis. Moreover, as mentioned above, the secretion of APLN in atretic follicles is notably increased in response to IGF1 and insulin, and subsequently stimulates steroidogenesis in GCs <ns0:ref type='bibr' target='#b7'>(Boucher et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b54'>Roche et al., 2016)</ns0:ref>. It indicates a possible implication of insulin in APLN synthesis via activating PI3K/Akt and MAPK3/1 signaling pathways <ns0:ref type='bibr' target='#b7'>(Boucher et al., 2005)</ns0:ref>. Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) and Body Mass Index (BMI) as hall markers of PCOS have been confirmed to be associated with adipocytokines, even if there is still an inconsistency among different researches. In normal cases, studies have revealed either positive or negative correlations of APLN with HOMA-IR and BMI <ns0:ref type='bibr' target='#b13'>(Cekmez et al., 2011;</ns0:ref><ns0:ref type='bibr'>Olszanecka-Glinianowicz et al., 2015)</ns0:ref>. In PCOS cases, several groups have shown an enhanced level of serum APLN positively correlated with HOMA-IR and BMI <ns0:ref type='bibr' target='#b63'>(Sun et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b54'>Roche et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b6'>Bongrani et al., 2019)</ns0:ref>, while one research reported a decreased serum APLN level which was positively associated with HOMA-IR and BMI <ns0:ref type='bibr' target='#b1'>(Altinkaya et al., 2014)</ns0:ref>. These discrepant findings among published literature may be attributed to the differences in research design, different stages of PCOS, sample size, genetic characteristics of patients and APLN evaluation methodology.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.4'>Roles of APLN and APELA in ovarian cancer</ns0:head><ns0:p>Previous studies demonstrated that the level of APLN expression was significantly increased in ovarian cancer cells. In MCF-7 cells, the APLN-APLNR system was involved in regulating the proliferation and metastasis via phosphorylating ERK1/2 pathway <ns0:ref type='bibr' target='#b47'>(Peng et al., 2015)</ns0:ref>. Secretion and expression of APLN as a mitogenic factor was also detected in OVCAR3 cell line which regulates the proliferation progress in a dose-dependent manner <ns0:ref type='bibr' target='#b27'>(Hoffmann, Fiedor &amp; Ptak, 2017)</ns0:ref>. In SKOV3 cell line, over-expressed APLN and its receptor reduced the sensitivity of antiangiogenic therapeutic regimen <ns0:ref type='bibr' target='#b43'>(Masoumi et al., 2020)</ns0:ref>. Recently, an elevated APELA level was documented in various histotypes of ovarian cancers, especially in ovarian clear cell carcinoma (OCCC) <ns0:ref type='bibr' target='#b84'>(Yi et al., 2017)</ns0:ref>. It is speculated that APELA was involved in multiple pathways in tumorigenesis. For instances, it accelerates cell mitosis and migration through activating ERK and PI3K/AKT cascades <ns0:ref type='bibr' target='#b26'>(Ho et al., 2015)</ns0:ref>. In addition, it was also reported that APELA might negatively regulate p53 in OCCC cell lines, causing non-apoptotic cell growth through an APLNR-independent pathway <ns0:ref type='bibr' target='#b84'>(Yi et al., 2017)</ns0:ref>. However, another study showed that increased APLNR expression was significantly correlated with decreased median overall survival by 14.7 months in patients with high-grade serous ovarian cancer, and APLNR expression was both necessary and sufficient to increase prometastatic phenotypes of ovarian cancer cells including the proliferation, cell adhesion, migration and invasion in vitro <ns0:ref type='bibr'>(Neelakantan et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='5.5'>Distribution of APLN and APLNR in the oviduct</ns0:head><ns0:p>The expression of apelinergic system in the ovary has been widely discussed. However, currently only one study mentioned its expression in the sheep oviduct. This study showed that APLN was detected in the epithelial cell coat of ampullary ciliated cells, which facilitated the transport of oocytes and spermatozoa through the oviductal tract. APLNR was expressed exclusively in the ampullary secretory cells, suggesting the fertilization and implantation roles of this system during the luteal stage <ns0:ref type='bibr'>(Mercati et al., 2019)</ns0:ref>. In ewe oviduct, the mRNA level of both APLN and APLNR were detected higher in estrus when compared with those in anestrus. As the function of oviduct is to provide place for embryogenesis and transport of early embryo, the disruption of normal oviduct function may cause infertility, which is considering as a serious concern recently, and attracting more expected studies <ns0:ref type='bibr'>(Mercati et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='6.'>Role of APLN in uterus</ns0:head></ns0:div> <ns0:div><ns0:head n='6.1'>Distribution and function of APLN and APLNR in uterus</ns0:head><ns0:p>Recently, it has been witnessed that APLN and its receptor also display potential behaviors in uterus among species such as rat, mouse, ewe and human. The expression of APLNR mRNA in uterus was firstly detected through a nonspecific rat tissue RT-PCR screen <ns0:ref type='bibr' target='#b28'>(Hosoya et al., 2000)</ns0:ref>, then its ligand APLN was described to be elevated during the secretory phase in the glandular cells of endometrial layer whereas it remained at a low level in the stromal cells <ns0:ref type='bibr' target='#b34'>(Kawamata et al., 2001;</ns0:ref><ns0:ref type='bibr'>Ozkan et al., 2013;</ns0:ref><ns0:ref type='bibr'>Mercati et al., 2019)</ns0:ref>. It is evidently deduced that the apelinergic system is stimulated by elevated steroid hormones during the uterine secretory phase also known as the luteal phase of ovarian cycle. APLN subsequently plays a spatio-temporal role in spiral arterioles maturation and interstitial edema in endometrium where angiogenesis is taking place. An in vitro study showed that APLN played a vasodilation role in suppressing both spontaneous and oxytocin-induced contraction in human myometrial fibers <ns0:ref type='bibr' target='#b23'>(Hehir &amp; Morrison, 2012)</ns0:ref>. However, serum APLN was also reported to exert a positive inotropic effect in rat myometrial layer via PKC-mediated intracellular Ca 2+ amplication <ns0:ref type='bibr' target='#b32'>(Kacar et al., 2018)</ns0:ref>. These opposite results may be explained by the intracellular balance between vascular dilation and smooth muscle contraction mechanisms of apelinergic system, as well as the impacts of species diversity and reagent concentrations.</ns0:p></ns0:div> <ns0:div><ns0:head n='6.2'>Role of APLN in endometriosis</ns0:head><ns0:p>Endometriosis is defined as an estrogen-dependent invasion of endometrial tissue from uterus to uterine adnexa <ns0:ref type='bibr' target='#b9'>(Bulun et al., 2019)</ns0:ref>. It is a very common cause for chronic pain in the pelvis and could even lead to infertility in moderate and significant patients <ns0:ref type='bibr'>(Chaljub, Medlock &amp; Services, 2018)</ns0:ref>. Current explanations of endometriosis pathogenesis are endometrial implantation, coelomic metaplasia and induction theories which are all in agreement with the impacts of steroid hormone dysregulation and inflammatory response. Similar expression pattern of APLN was seen in both eutopic and ectopic endometrium during the menstrual cycle indicated that the ectopic endometrial lesion could share some characteristics with eutopic cellular processes in endometrium regeneration <ns0:ref type='bibr'>(Mercati et al., 2019)</ns0:ref>. Additionally, the angiogenesis and vasodilation effects of APLN could potentially be one of the causes in triggering the symptoms of endometriosis, whereas more studies are expected to confirm this point.</ns0:p></ns0:div> <ns0:div><ns0:head n='7.'>Roles of APLN and APELA during pregnancy</ns0:head><ns0:p>7.1 Role of APLN and APELA in embryonic development APLNR was reported to be expressed in the angioblast of frog embryo, which would contribute to the formation of aortic arch vessels and posterior cardinal veins. APLN was detected either within or adjacent to the endothelial cells expressed by APLNR, functioning as an angiogenic agent for nascent blood vessels, especially the intersegmental vessels formation. It also showed the chemotactic ability of APLN to induce the migration of endothelial cells <ns0:ref type='bibr' target='#b18'>(Cox et al., 2006)</ns0:ref>. Moreover, APLN was proved possessing an anti-apoptotic role in osteoblastic cell line of humans and mice <ns0:ref type='bibr' target='#b66'>(Tang et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b79'>Xie et al., 2007)</ns0:ref>. It releases Bcl-2 molecule from Bad via activating PI3K/Akt pathway, which subsequently attenuates the activation of downstream apoptotic factors, such as cytochrome c and caspase-3, resulting in the inhibition of osteoblastic cell apoptosis. Additionally, APELA has also been revealed to hold a key role in cardiogenesis, angiogenesis and bone formation during the embryonic development. In APELA knockout mice, the hearts are developed poorly or not developed at all, suggesting the essential role in heart morphogenesis <ns0:ref type='bibr' target='#b15'>(Chng et al., 2013)</ns0:ref>. It triggers the endothelial precursor (angioblasts) to migrate towards midline and coalesce underneath the notochord, and form the first axial vessels <ns0:ref type='bibr' target='#b45'>(Pauli et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b24'>Helker et al., 2015)</ns0:ref>. Consistently, APELA-APLNR axis is involved in early placental development and angiogenesis <ns0:ref type='bibr' target='#b26'>(Ho et al., 2015</ns0:ref><ns0:ref type='bibr' target='#b25'>(Ho et al., , 2017))</ns0:ref>. In mouse placenta, APELA is robustly expressed in syncytiotrophoblasts from early-to-mid gestation, which favors the sprout of new formed blood vessels <ns0:ref type='bibr' target='#b25'>(Ho et al., 2017)</ns0:ref>. It is also associated with skeletal formation through inhibiting the expression of Sox32, which can bind to Pou5f3 and Nanog molecules as a transcription factor in dorsal endoderm during gastrulation, and inhibit the formation of Pou5f3-Nanog complex. APELA-APLNR pathway can reduce Sox32 expression and allow Pou5f3-Nanog complexes formation, subsequently activating bone morphogenetic protein signaling for sclerotome fate determination <ns0:ref type='bibr' target='#b48'>(Perez-Camps et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='7.2'>Distribution and function of APLN and APELA in the placenta</ns0:head><ns0:p>Apelinergic system has been hypothesized as a key factor in placental angiogenesis. APLN was strongly expressed in the cytoplasm of human cytotrophoblasts during the first two trimester of pregnancy, and then decreased at the third trimester. Subtle signals were also detected in the syncytiotrophoblasts during the first trimester, but it disappeared completely in the third trimester <ns0:ref type='bibr' target='#b17'>(Cobellis et al., 2007)</ns0:ref>. The expression of APLNR in the placenta was later than that of APLN. In the first trimester, it was relatively low and exclusively in the cytotrophoblasts. However, in the third trimester, APLNR was expressed intensely not only in cytotrophoblasts but also in syncytiotrophoblasts, smooth muscle cells and endothelial cells inside of the placental villi <ns0:ref type='bibr' target='#b17'>(Cobellis et al., 2007)</ns0:ref>. This change suggests a potential chemoarractant and vasculogenic role of APLN in the invasion process of interstitial and endovascular extravillous trophoblasts. In mouse, APELA was detected initially in the trophoblasts and then increased robustly after the allantoic fusion. At the mid-gestation, it was expressed restrictedly in syncytiotrophoblasts, where APLNR was wildly existed in adjacent endothelial cells, indicating a paracrine function of this system to favor the placental angiogenic sprouting <ns0:ref type='bibr' target='#b25'>(Ho et al., 2017)</ns0:ref>. However, in human placenta, APELA was expressed in both cytotrophoblasts and syncytiotrophoblasts synchronously during the whole pregnancy <ns0:ref type='bibr' target='#b25'>(Ho et al., 2017)</ns0:ref> and its speculated role remains to be illuminated.</ns0:p></ns0:div> <ns0:div><ns0:head n='7.3'>Regulation of APELA and APLN in PE</ns0:head><ns0:p>The basic pathological changes of hypertensive disorders in pregnancy are currently recognized as insufficient spiral arteries recasting and inflammation mediated endothelial damage triggered by the intricate network of signaling cascades. APELA as mentioned above plays a crucial role in placental angiogenesis via activating PI3K/AKT/mTOR pathway <ns0:ref type='bibr' target='#b25'>(Ho et al., 2017)</ns0:ref>, and whether its reduction could lead to PE is now being widely studied. It was firstly discovered that APELA knockout pregnant mice exhibited a hypertensive symptom accompanied with proteinuria and glomerular endotheliosis, which were manifested as preeclampsia-like symptoms <ns0:ref type='bibr' target='#b25'>(Ho et al., 2017)</ns0:ref>. Scientists therefore started investigating the change of APELA in PE patients and wanted to know whether the APELA could act as a biomarker <ns0:ref type='bibr' target='#b88'>(Zhou et al., 2019)</ns0:ref>. In the late-onset PE (LOPE), two studies measured a significant increased concentration of APELA in the placenta and serum <ns0:ref type='bibr'>(Panaitescu et al., 2020;</ns0:ref><ns0:ref type='bibr'>Para et al., 2020)</ns0:ref>, while one study measured significant decrease <ns0:ref type='bibr' target='#b88'>(Zhou et al., 2019)</ns0:ref>. And for early-onset PE (EOPE), only one study observed decrease in both APELA mRNA and protein <ns0:ref type='bibr' target='#b76'>(Wang et al., 2019)</ns0:ref>, while other studies report no significant change of APELA level on either protein or mRNA <ns0:ref type='bibr' target='#b51'>(Pritchard et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b74'>Villie et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b88'>Zhou et al., 2019;</ns0:ref><ns0:ref type='bibr'>Panaitescu et al., 2020;</ns0:ref><ns0:ref type='bibr'>Para et al., 2020)</ns0:ref>. Furthermore, it was found that hypoxia significantly decreased the expression of LIN28B, LIN28A and APELA, and the downregulation of LIN28B and APELA may play a role in PE by reducing trophoblast invasion and syncytialization <ns0:ref type='bibr' target='#b10'>(Canfield et al., 2019)</ns0:ref>. There are also contradictions about the expression level of APLN in PE patients. Initially, a clinical study found an increased APLN protein level in the placental samples of PE patients, indicating a speculated correlation between APLN and PE <ns0:ref type='bibr' target='#b17'>(Cobellis et al., 2007)</ns0:ref>. This study was further proved by an experiment which showed intravenous injection of APLN in male mice could lead to the downregulation of blood pressure, suggesting that APLN might act as a vasodilator in PE <ns0:ref type='bibr' target='#b37'>(Lee et al., 2000)</ns0:ref>. However, case studies also found either decreased <ns0:ref type='bibr' target='#b30'>(Inuzuka et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b81'>Yamaleyeva et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b58'>Sattar Taha, Zahraei &amp; Al-Hakeim, 2020)</ns0:ref> or no significantly changed <ns0:ref type='bibr'>(Van Mieghem et al., 2016)</ns0:ref> APLN level in PE patients compared with normotensive pregnancies. Not only its ligands, the expression of APLNR is also rather conflicting. It has long been thought that APLNR level increases when the patient suffer from PE <ns0:ref type='bibr' target='#b17'>(Cobellis et al., 2007)</ns0:ref>, but two other studies suggest APLNR level remains unchanged when PE occurs <ns0:ref type='bibr' target='#b81'>(Yamaleyeva et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b51'>Pritchard et al., 2018)</ns0:ref>. However, one recent study found a significant decrease both in APLNR mRNA expression and in situ expression between PE patients and normal control, and this significance can be found when controls compared to both EOPE and LOPE groups <ns0:ref type='bibr' target='#b88'>(Zhou et al., 2019)</ns0:ref>. Altogether, the different expression of apelinergic system could be explained by confounding factors like BMI and mean maternal age mismatches between the cases and controls. Moreover, the balance between vasorelaxant and myocardial contractile effects of apelinergic system, as well as the crosslink of apelinergic axis with intricate inflammatory and endothelial factors in PE should also be taken into consideration. Further investigations should focus on the specific molecular mechanisms of APLN and APELA in the hypertensive disorders of pregnancy.</ns0:p></ns0:div> <ns0:div><ns0:head n='7.4'>Regulation of APLN and APELA in GDM</ns0:head><ns0:p>APLN as one of the adipose tissue-derived hormones has been identified to play a role in blood glucose metabolism <ns0:ref type='bibr' target='#b2'>(Antushevich &amp; W&#243;jcik, 2018)</ns0:ref>. It has been described that insulin may upregulate the expression of APLN through PKC and PI3K signaling pathways in both murine and human adipocytes <ns0:ref type='bibr' target='#b7'>(Boucher et al., 2005)</ns0:ref>. Raised apelin levels were found in both insulinresistant mice and type 2 diabetes mellitus patients <ns0:ref type='bibr' target='#b80'>(Xu, Tsao &amp; Yue, 2011)</ns0:ref>, which supported the speculation that insulin can stimulate APLN secretion. Nevertheless, the correlation of APLN levels with GDM has not yet reached an agreement in clinical researches. Three studies reported a decrease of serum APLN level in GDM patients <ns0:ref type='bibr' target='#b4'>(Aydin, 2010;</ns0:ref><ns0:ref type='bibr' target='#b8'>Boyadzhieva et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b0'>Akinci et al., 2014)</ns0:ref> while two other groups revealed an increase <ns0:ref type='bibr' target='#b3'>(Aslan et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b35'>Caglayan et al., 2016)</ns0:ref>. In contrast, there were also no significant association reports between normal control and GDM patients <ns0:ref type='bibr' target='#b71'>(Telejko et al., 2010;</ns0:ref><ns0:ref type='bibr'>Oncul et al., 2013)</ns0:ref>. Thus, the correlation of APLN with the pathophysiology of GDM remains to be elucidated. In addition, factors like BMI, HOMA-IR and birth weight have been shown not correlated with serum APLN level according to these studies <ns0:ref type='bibr' target='#b3'>(Aslan et al., 2012;</ns0:ref><ns0:ref type='bibr'>Oncul et al., 2013)</ns0:ref>, but these confounding factors varied a lot among different groups during pregnancy, which was probably one of the cases in the controversy.</ns0:p><ns0:p>APELA had a positive correlation with fasting plasma glucose levels in healthy pregnant women during the second trimester, while decreased APELA circulating level was observed in GDM patients at the same time. In the third trimester, circulating APELA level decreased significantly in both GDM and healthy groups. This study suggested that APELA could be a physiological demand in glucose metabolism, and further contributions should focus on dynamic levels monitoring and mechanism analysis <ns0:ref type='bibr' target='#b22'>(Guo et al., 2020)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='8.'>Conclusion</ns0:head><ns0:p>This review presents a landscape of the novel APLN/APELA-APLNR system in the female reproductive field (Table <ns0:ref type='table'>1 and Fig 1)</ns0:ref>. Intricate signaling pathways and crosslinks of APLN and APELA imply their multifunctional roles in different organs like ovary, uterus and placenta, during specific developmental stages. APLN as an adipokine appears to have specific effects in steriodogenesis and metabolic regulation in GCs and CL of the ovary. Insulin and IGF1-induced APLN secretion possibly plays a role in glucose regulation in GDM patients. In addition, APLN may sustain a balance between the vasodilative and myocontractile effects in the uterus which could be correlated with hypertensive disorders during the pregnancy. Similarly, APELA as a novel ligand of APLNR also has a potential role in PE, based on the angiogenic effect of spiral arterioles. APELA is essential for fetal and placental development through stimulating the invasion of extravillous trophoblasts. This process is potentially achieved through a chemoattractant mechanism in placental angiogenic sprouting. Moreover, there is a hyperplasia effect of APELA which could be one of the causes in ovarian tumorigenesis. All the data suggest that there should be additional studies to further investigate the precise roles of this axis in female reproductive system especially at the pathological profile. In the future, it will be important to clarify the crosslink and interaction between APLN and other adipokines in sex hormone regulation and energy metabolism. Specific expression and biological effects of APELA in ovary and uterus are also needed in prospect. It may also be crucial to identify the balance of smooth muscle contraction and vasodilation in apelinergic system at a molecular hierarchy. Collectively, the apelinergic axis is still a novel project for further investigation in both physiological and pathological aspects, and probably brings better therapeutic or prophylactic intervention towards female reproductive disorders.</ns0:p></ns0:div> <ns0:div><ns0:head n='9.'>Acknowledgments</ns0:head><ns0:p>None. </ns0:p></ns0:div> <ns0:div><ns0:head n='10.'>Additional information and Declarations</ns0:head></ns0:div> <ns0:div><ns0:head>List of Abbreviations</ns0:head><ns0:note type='other'>Figure legends</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Biophysical Research Communications 290:539-545. DOI: 10.1006/bbrc.2001.6230. Mercati F, Scocco P, Maranesi M, Acuti G, Petrucci L, Cocci P, Renzi A, De Felice E, Dall'Aglio C. 2019. Apelin system detection in the reproductive apparatus of ewes grazing on semi-natural pasture. Theriogenology 139:156-166. DOI: 10.1016/j.theriogenology.2019.08.012. El Messari S, Iturrioz X, Fassot C, De Mota N, Roesch D, Llorens-Cortes C. 2004. Functional dissociation of apelin receptor signaling and endocytosis: Implications for the effects of apelin on arterial blood pressure. Journal of Neurochemistry 90:1290-1301. DOI: 10.1111/j.1471-4159.2004.02591.x. Van Mieghem T, Doherty A, Baczyk D, Drewlo S, Baud D, Carvalho J, Kingdom J. 2016. Apelin in Normal Pregnancy and Pregnancies Complicated by Placental Insufficiency. Reproductive Sciences 23:1037-1043. DOI: 10.1177/1933719116630422. Neelakantan D, Dogra S, Devapatla B, Jaiprasart P, Mukashyaka MC, Janknecht R, Dwivedi SKD, Bhattacharya R, Husain S, Ding K, Woo S. 2019. Multifunctional APJ pathway promotes ovarian cancer progression and metastasis. Molecular cancer research 17:1378-1390. DOI: 10.1158/1541-7786.MCR-18-0989. Norris ML, Pauli A, Gagnon JA, Lord ND, Rogers KW, Mosimann C, Zon LI, Schier AF. 2017. Toddler signaling regulates mesodermal cell migration downstream of nodal signaling. eLife 6:1-18. DOI: 10.7554/eLife.22626. O'Dowd BF, Heiber M, Chan A, Heng HHQ, Tsui LC, Kennedy JL, Shi X, Petronis A, George SR, Nguyen T. 1993. A human gene that shows identity with the gene encoding the angiotensin receptor is located on chromosome 11. Gene 136:355-360. DOI: 10.1016/0378-1119(93)90495-O. Olszanecka-Glinianowicz M, Madej P, Owczarek A, Chudek J, Ska&#322;ba P. 2015. Circulating anti-M&#252;llerian hormone levels in relation to nutritional status and selected adipokines levels in polycystic ovary syndrome. Clinical Endocrinology 83:98-104. DOI: 10.1111/cen.12687. Oncul M, Tuten A, Erman H, Gelisgen R, Benian A, Uzun H. 2013. Maternal and cord blood apelin, resistin and visfatin levels in gestational diabetes mellitus. Minerva Medica 104:527. DOI: 10.1186/1471-2296-14-145. Ozkan ZS, Cilgin H, Simsek M, Cobanoglu B, Ilhan N. 2013. Investigation of apelin expression in endometriosis. Journal of Reproduction and Infertility 14:50-55. Panaitescu B, Romero R, Gomez-Lopez N, Pacora P, Erez O, Vadillo-Ortega F, Yeo L, Hassan SS, Hsu CD. 2020. ELABELA plasma concentrations are increased in women with lateonset preeclampsia. Journal of Maternal-Fetal and Neonatal Medicine 33:5-15. DOI: 10.1080/14767058.2018.1484089. Para R, Romero R, Gomez-Lopez N, Tarca AL, Panaitescu B, Done B, Hsu R, Pacora P, Hsu CD. 2020. Maternal circulating concentrations of soluble Fas and Elabela in early-and lateonset preeclampsia. Journal of Maternal-Fetal and Neonatal Medicine 0:1-14. DOI: 10.1080/14767058.2020.1716720.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: Expression and function of APLN and APELA in reproduction system. (A) In physiological conditions, APLN (in blue textbox) and APELA (in green textbox) play diverse roles at the different parts of the ovary, uterus and placenta. (B) In pathological conditions, aberrant expression of APLN (in orange textbox) and APELA (in purple textbox) lead to female reproductive disorders such as polycystic ovary syndrome (PCOS), ovarian cancer, preeclampsia (PE), gestational diabetes mellitus (GDM) and endometriosis. * indicating potential apelinergic stimulating factors. ? indicating still unclear or controversy about the functions or contributions of apelinergic molecules in these diseases. &#8593;and&#8595;in the textbox means increase and decrease respectively, both indicate statistically significant changes. &#8594; means resulting.Figure 2: Intracellular signaling pathways and physiological functions of APLN and APELA. (A) Both APLN (in blue) and APELA (in orange) can classically activate G&#945;i/o and G&#945;q/11 mediated intracellular transduction via binding to their common receptor APLNR. (B) Noncoding APELA binds to hnRNPL and promotes p53-mediated cell apoptosis. (C) APELA also stimulates PI3K-independent NODAL/TGF&#946; signal through alternative receptors in hESCs. AC, adenylate cyclase; eNOS, endothelial nitric oxide synthase; IncRNA, long non-coding RNA; hnRNPL, heterogeneous nuclear ribonucleoprotein L.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 1: Expression and function of APLN and APELA in reproduction system. (A) In physiological conditions, APLN (in blue textbox) and APELA (in green textbox) play diverse roles at the different parts of the ovary, uterus and placenta. (B) In pathological conditions, aberrant expression of APLN (in orange textbox) and APELA (in purple textbox) lead to female reproductive disorders such as polycystic ovary syndrome (PCOS), ovarian cancer, preeclampsia (PE), gestational diabetes mellitus (GDM) and endometriosis. * indicating potential apelinergic stimulating factors. ? indicating still unclear or controversy about the functions or contributions of apelinergic molecules in these diseases. &#8593;and&#8595;in the textbox means increase and decrease respectively, both indicate statistically significant changes. &#8594; means resulting.Figure 2: Intracellular signaling pathways and physiological functions of APLN and APELA. (A) Both APLN (in blue) and APELA (in orange) can classically activate G&#945;i/o and G&#945;q/11 mediated intracellular transduction via binding to their common receptor APLNR. (B) Noncoding APELA binds to hnRNPL and promotes p53-mediated cell apoptosis. (C) APELA also stimulates PI3K-independent NODAL/TGF&#946; signal through alternative receptors in hESCs. AC, adenylate cyclase; eNOS, endothelial nitric oxide synthase; IncRNA, long non-coding RNA; hnRNPL, heterogeneous nuclear ribonucleoprotein L.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48913:2:0:NEW 20 Sep 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48913:2:0:NEW 20 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

" Department of Physiology Basic Medical College Nanchang University Nanchang Jiangxi 330006 Haibin Kuang (Tel: 86-791-83827148) [email protected] Yanling (Tel: 86-791-86895863) [email protected] September 19th, 2020 Dear Editors: We thank the reviewers for their generous comments on the manuscript, and have carefully reviewed the comments and revised the manuscript as per reviewers’ suggestions. Our point to point responses are appended in the part of “Response to Reviewers”. In particular we have checked our reference list and polished our English grammar multiple times. Additionally, we have one referenced article without DOI number, which titles ’Investigation of apelin expression in endometriosis’. We believe that the manuscript is now suitable for publication in PeerJ. Sincerely, Dr Haibin Kuang Professor of Physiology Response to Reviewers: Reviewer 1 Basic reporting English revision is suggested Response: Thank you for your kind suggestion. We have proofread carefully the manuscript by ourselves, and asked native English scientist in the field to extensively proofread the whole manuscript. Comments for the author The manuscript entitled “Emerging roles of APLN and APELA in physiology and pathology of female reproductive system” was edited as suggested and a point by point response to my comments were provide. However, I have a few other considerations to address. Response: We are very pleased with the positive comments of the reviewer; and also appreciate your constructive suggestions and critiques. Figure 2: The figure and the text were changed as suggested but the caption were not changed. Please, reverse B and C description. Response: Thank the reviewer very much for your kind reminder. In the revised manuscript, we have made the change according to your advice. Line 101: Change “and” with “&” in this reference and other references in the text. Response: Thank the reviewer very much for your patient and careful review. We have made those changes according to your advice in the revised manuscript. Examples: …with different affinities for APLNR and prevalent distribution (Chapman, Dupré & Rainey, 2014) …gonadotropins and steroids through hypothalamo-pituitary-gonadal (HPG) axis (Bertrand, Valet & Castan-Laurell, 2015; Yang et al., 2019). Line 234-235: Since Kwak reference was delete, also “mouse” should be deleted by the sentence. Otherwise add another reference regarding mouse species. Response: Thank the reviewer for your suggestion and we have deleted “mouse” in the revised manuscript. Line 488: Please, change “another two groups” with “two other groups”. Response: We are very appreciated for the reviewer’s suggestion on English language. We have changed “another two groups” into “two other groups” in the revised manuscript. Line 501: “Guo et al., 2020” is missing in the references chapter. Line 637: Please, do not delete “92(6):431-440.” I suggest to revise citations in the text and in the chapter of References where several references were cancelled even if they are cited in the text. For example: Fagerberg et al., 2014; Lee et al., 2000 ; Than et al., 2014; Wang et al., 2019; Response: Thank the reviewer very much for your patience and careful review. We readded the reference for “Guo et al., 2020” “Fagerberg et al., 2014” “Lee et al., 2000” “Than et al., 2014” and “Wang et al., 2019”, and also “92(6):431-440.” in the reference chapter. Reviewer 2 Comments for the author The author answered all my questions and I agreed to accept. however, there is one point that should be corrected by the authors. In table 1, Zhou et al. also measured ELA concentrations in EOPE (n=15) and LOPE (n=22) using plasma samples, and the sample size used was larger than that of placental tissue. Therefore, the results are more convincing and should be reflected in Table 1. Response: We are very pleased with the positive comments of reviewer; and also appreciate your constructive suggestions and critiques. We added two additional lines in our table 1 to represent Zhou’s work on plasma as you suggested. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. In December 2019, an ongoing outbreak of pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/ 2019-nCoV) infection was initially reported in Wuhan, Hubei Province, China. Early in 2020, the World Health Organization (WHO) announced a new name for the 2019-nCoV-caused disease: coronavirus disease 2019 (COVID-19) and declared COVID-19 to be a Public Health Emergency of International Concern (PHEIC). Cellular co-infection is a critical determinant of both viral fitness and infection outcomes and plays a crucial role in shaping the host immune response to infections.</ns0:p><ns0:p>Methods. In this study, 68 public next-generation sequencing data from SARS-CoV-2 infected patients were retrieved from the NCBI Sequence Read Archive database using SRA-Toolkit. Data screening was performed using an alignment-free method based on k-mer mapping and extension, fastv. Taxonomic classification was performed using Kraken 2 on all reads containing one or more virus sequences other than SARS-CoV-2.</ns0:p><ns0:p>Results. SARS-CoV-2 was identified in all except three patients. Influenza type A (H7N9) virus, human immunodeficiency virus, rhabdovirus, human metapneumovirus, coronavirus NL63, parvovirus, simian virus 40, and hepatitis virus genomes sequences were detected in SARS-CoV-2 infected patients.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>In December 2019, the first cases of coronavirus disease 2019 were possibly due to a zoonotic transmission in China. It was tied to a large seafood market that also traded in live wild animals <ns0:ref type='bibr' target='#b19'>(Tay et al. 2020)</ns0:ref>. The causative virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is capable of human-to-human transmission and rapidly spread to other regions of China, and then to other countries (World Health Organization 2020). It is now a global pandemic and is a considerable concern for public health. So far, more than 16,101,367 confirmed cases were diagnosed in nearly 213 countries and territories around the world and two international conveyances, causing globally over 645,000 deaths <ns0:ref type='bibr' target='#b24'>(Worldometer 2020, July 25)</ns0:ref>.</ns0:p><ns0:p>Coronaviruses are known to cause severe diseases in humans and animals. Of these, four human coronaviruses (229E, NL63, OC43, and HKU1) typically only infect the upper respiratory tract and cause relatively minor symptoms <ns0:ref type='bibr' target='#b7'>(Fehr &amp; Perlman 2015)</ns0:ref>. However, there are three coronaviruses (severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and SARS-CoV-2) that can replicate in the lower respiratory tract and cause pneumonia which can be fatal. With 79% genome sequence similarity, SARS-CoV is the closest relative to SARS-CoV-2 among human coronaviruses <ns0:ref type='bibr'>(Gorbalenya et al. 2020)</ns0:ref>. However, of all known coronavirus sequences, SARS-CoV-2 is most similar to bat coronavirus RaTG13, with a similarity of 98% <ns0:ref type='bibr' target='#b26'>(Zhou et al. 2020)</ns0:ref>. SARS-CoV-2 pathophysiology closely parallels that of SARS-CoV infection, with active inflammatory responses strongly implicated in the resulting airway damage <ns0:ref type='bibr' target='#b21'>(Wong et al. 2004</ns0:ref>).</ns0:p><ns0:p>Hence the extent of the disease in patients is attributed not only to the viral infection but also to the host's response <ns0:ref type='bibr' target='#b19'>(Tay et al. 2020)</ns0:ref>.</ns0:p><ns0:p>Underlying co-infections in primary infectious disease are an important variable that needs to be considered but is often undetected. Remarkable developments in next-generation sequencing PeerJ reviewing PDF | (2020:06:50170:1:1:NEW 28 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed have recently made metagenomics, an unbiased shotgun method of analysis, a widely used tool in just about every field of biology, including diagnosis of infectious diseases <ns0:ref type='bibr' target='#b10'>(Kuroda et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b13'>Lecuit &amp; Eloit 2014)</ns0:ref>. Metagenomics is powerful because it can diagnose unsuspected microbial agents <ns0:ref type='bibr' target='#b20'>(Wilson et al. 2014)</ns0:ref>. It directly analyzes samples in their entirety, eliminating the need for prior knowledge to obtain comprehensive information. In this capacity, metagenomics exceeds traditional diagnostic limitations. With the viral genomes in hand, we can now explore the possibility of using metagenomic and metatranscriptomic next-generation sequencing (mNGS) directly as a screening method of other viruses in a sample.</ns0:p><ns0:p>A simple approach would be to first map sequencing reads from the sample to the reference viral genome. However, the accuracy of such an alignment-based method is relatively low compared to an alignment-free approach. In the alignment-based method, genome sequences from closely related viruses can lead to false-positive results <ns0:ref type='bibr' target='#b3'>(Chen et al. 2020b)</ns0:ref>. Moreover, the virus-specific reads obtained may not be adequate for unambiguous detection (degraded RNA, incompletely target-enriched sequence library by multiple-PCR <ns0:ref type='bibr' target='#b15'>(Lundberg et al. 2013)</ns0:ref> or hybrid capture <ns0:ref type='bibr' target='#b6'>(Duncavage et al. 2011</ns0:ref>)) which can lead to false-negative results.</ns0:p><ns0:p>Fastv is an alignment-free, ultra-fast tool for detecting the microbial sequences in sequence data <ns0:ref type='bibr' target='#b3'>(Chen et al. 2020b)</ns0:ref>. It can identify target microorganisms using unique k-mers. It detects SARS and other coronaviruses from sequencing data and efficiently distinguishing SARS from MERS.</ns0:p><ns0:p>In this study, identification experiments were conducted on public next-generation sequencing data from SARS-CoV-2 infected patients using fastv, along with the pre-computed unique k-mer resources <ns0:ref type='bibr' target='#b3'>(Chen et al. 2020b)</ns0:ref>. Taxonomic classification was performed using Kraken 2 on all reads containing more than one virus sequences <ns0:ref type='bibr' target='#b22'>(Wood et al. 2019)</ns0:ref>. The findings of the present </ns0:p></ns0:div> <ns0:div><ns0:head>Material and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Computing hardware</ns0:head><ns0:p>Amazon Elastic Compute Cloud (EC2) instance (i.e., virtual server in the AWS cloud) was used.</ns0:p><ns0:p>SRA-tools package (version 2.9.1), Kraken 2, and fastv (version 0.9.0) were installed within the Linux 2 EC2 instance.</ns0:p></ns0:div> <ns0:div><ns0:head>SRA database mining</ns0:head><ns0:p>Next-generation sequencing technologies have enabled large-scale genomic surveillance of SARS-CoV-2 as thousands of isolates are being sequenced around the world and deposited in public data repositories. The sequence data were downloaded as .sra files using the prefetch tool, then extracted to. fastq files using the NCBI fastq-dump tool.</ns0:p><ns0:p>Data sets for analysis were chosen through a keyword search of the SRA descriptions for 'COVID19' and downloaded between 27 January 2020 and 16 May 2020. Sequence data from negative COVID-19 patients, experimental studies and controlled access were excluded.</ns0:p><ns0:p>(Table <ns0:ref type='table'>S1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Table S1: SRA sequences used in this study with the detection result for SARS-</ns0:head></ns0:div> <ns0:div><ns0:head>CoV-2 k-mer</ns0:head><ns0:p>Sequence data pre-processing and screening using fastv Fastv, along with the pre-computed unique k-mer resources, was used as previously described <ns0:ref type='bibr' target='#b3'>(Chen et al. 2020b)</ns0:ref>. Initially, fastv performed adapter trimming, quality pruning, base correction, <ns0:ref type='table'>PeerJ reviewing PDF | (2020:06:50170:1:1:NEW 28 Jul 2020)</ns0:ref> Manuscript to be reviewed and other pre-processing to ensure the accuracy of k-mer analysis on fastq input files. The fastv tool identifies a target virus from sequencing data and detects any microbial sequences for which a unique k-mer data is provided. A unique SARS-CoV-2 k-mer set and the SARS-CoV-2 reference genome were used as input files (downloaded from https://github.com/OpenGene/fastv/tree/master/data) with the k-mer collection for viral genomes (downloaded from http://opengene.org/viral.kc.fasta.gz). The k-mer scanning results were visualized in a figure on a single HTML page by fastv.</ns0:p></ns0:div> <ns0:div><ns0:head>Sequence data analysis using Kraken 2</ns0:head><ns0:p>We validated the result of fastv with Kraken 2, a k-mer-based program (https://github.com/DerrickWood/kraken2) <ns0:ref type='bibr' target='#b22'>(Wood et al. 2019)</ns0:ref>. Kraken constructs an index of all k-mers found in the reference genomes and assigns each k-mer to the least common ancestor (LCA) of all species that have that k-mer. Then Kraken matches the k-mers contained in the reads to this index and eventually assigns the reads to the taxon with the most fitting k-mers by following the path from the root of the tree <ns0:ref type='bibr' target='#b22'>(Wood et al. 2019)</ns0:ref>. Through lowering memory use by 85%, Kraken 2 improves upon Kraken 1, enabling higher numbers of genomic reference data to be used while retaining high accuracy and fivefold speed. A standard database containing RefSeq complete bacterial, archaeal, and viral genomes, along with the human genome and a collection of known vectors (UniVec_Core) was downloaded. Then the database was built using 32 threads on an AWS EC2 h1.8xlarge storage optimized instance with 16 dual-core hyperthreaded 2.30 GHz CPUs and 132 gigabytes (GB) of RAM.</ns0:p></ns0:div> <ns0:div><ns0:head>Data visualization</ns0:head><ns0:p>The results of Kraken 2 analysis were visualized with Krona tool (https://github.com/marbl/Krona/wiki) <ns0:ref type='bibr' target='#b16'>(Ondov et al. 2011)</ns0:ref>, which displays hierarchical data (like taxonomic assignation) in multi-layered pie charts. We converted the Kraken 2 output in HTML PeerJ reviewing PDF | (2020:06:50170:1:1:NEW 28 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed format using the program ktImportTaxonomy, which parses the information relative to the query ID and the taxonomy ID.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>SARS-CoV-2 Identification</ns0:head><ns0:p>Identification experiments were performed on public Illumina HiSeq/ MiSeq libraries from the NCBI SRA database (Bioproject PRJNA605983) sequenced from bronchoalveolar lavage fluid from five patients (WIV02, WIV04, WIV05, WIV06 and WIV07) with pneumonia at the early COVID-19 outbreak in Wuhan, China. Nine libraries were downloaded as .sra files using the prefetch tool; then the fastq files were extracted using the NCBI fastq-dump tool. Prior to the kmer analysis, sequencing adapters and low-quality bases were removed by fastv.</ns0:p><ns0:p>After scanning the fastq data, fastv reported the k-mer coverage for each microbial genome with valid hits. SARS-CoV-2 was detected in all patients by fastv (Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>). where twelve SARS-CoV-2 hits were included in the genome list and ordered by k-mer coverage (99.4972% to 99.2308%). Mismatches were highlighted in red. SARS-CoV-2 was detected in all of the other 68-sequence date except three samples (Bioproject PRJNA631042) were negative for SARS-CoV-2. These samples belong to one study where the research group used different sequencing technologies on the same sample to find a cost-effective and highly scalable method for SARS-CoV-2 sequencing. Because sequence technologies vary in reading depth and coverage thresholds, fastv was unable to detect SARS-CoV-2 in sequenced samples with lower coverage metrics.</ns0:p></ns0:div> <ns0:div><ns0:head>Non-SARS-CoV-2 genome sequences were detected in COVID-19 infected patients</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:06:50170:1:1:NEW 28 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed Fastv also identified influenza type A (A/Shanghai/02/2013(H7N9) and rhabdovirus in the sequence data from WIV04, WIV06, and WIV07 patients with accession numbers SRR11092062, SRR11092060 and SRR11092059, respectively.</ns0:p><ns0:p>Influenza type A segment 4 hemagglutinin (HA) gene was detected with coverage (94.80%, 94.28% and 100%) and mean depth (3.80, 3.78 and 879.41) in WIV04, WIV06 and WIV07 patients respectively. Influenza A virus polymerase gene, nuclear export protein (NEP), nonstructural protein 1 (NS1) genes, matrix protein 1 and 2 gene segments were also identified with an average 17.25% coverage.</ns0:p><ns0:p>The complete genome of rhabdovirus was detected with coverage (47.55%, 46.53% and 53.22%) and mean depth (2.11, 2.11 and 4.04) in WIV04, WIV06 and WIV07 patients respectively.</ns0:p><ns0:p>In addition, human immunodeficiency virus, hepatitis virus and simian virus 40 were found in WIV07 patient sequence data with coverage below 21%. The low coverage and non-human specific pathogen hits have been overlooked.</ns0:p><ns0:p>Human coronavirus NL63 complete genomes (coverage=29.13% and mean depth=0.81) and human metapneumovirus (coverage=11.41% and mean depth=5.29) were detected in SRR11772648 (Bioproject PRJNA631042).</ns0:p><ns0:p>Parvovirus NIH-CQV genes coding for a putative replication-associated protein (rep), and putative capsid protein (cap) (coverage=14.62% and mean depth=0.41) were detected in SRR10971381 (Bioproject PRJNA603194).</ns0:p></ns0:div> <ns0:div><ns0:head>Kraken Taxonomic classification</ns0:head><ns0:p>Taxonomic classification was performed using Kraken 2 on all reads containing more than one virus sequences. The genetic data for constructing the databases were retrieved from the NCBI RefSeq library. A very diverse group of the viral, bacterial and archaeal population was observed in the samples. A taxonomic classification that was obtained from WIV04, WIV06, and PeerJ reviewing PDF | (2020:06:50170:1:1:NEW 28 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed WIV07 patients revealed a dominance of Bacteria (7%, 5%, and 59%, respectively), followed by Viruses (0.3%, 0.3%, and 0.3%, respectively) while Archaea was lower than 0.02% in all the patients. The most abundant bacterial phylum was Proteobacteria in (32%) WIV04 and (41%) WIV06 patients while Firmicutes phylum was most abundant (64%) in WIV07 patient. Influenza type A (8%), rather than, SARS-CoV-2 (2%) was found to be dominant in the WIV07 patient (Figure <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). Among viral communities, SARS-CoV-2, rhabdovirus and influenza type A dominated the sequence data from WIV06 patient (Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>) and WIV04 patient (Figure <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>).</ns0:p><ns0:p>A rank code, indicating(U)nclassified, (d)omain, (k)ingdom, (p)hylum, (c)lass, (o)rder, (f)amily, (g)enus, or (s)pecies was used. from kraken 2 analysis of samples collected from SRR11092059 patients were visualized using krona tool. Among viral communities, influenza type A (8%), SARS-CoV-2 (2%) and rhabdovirus (0.6%) dominated the sequence data from WIV07 patient. from kraken 2 analysis of samples collected from SRR11092060 patients were visualized using krona tool. Among viral communities, SARS-CoV-2 (1%), rhabdovirus (0.6%) and influenza type A (0.4%) dominated the sequence data from WIV06 patient. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The value of identifying underlying co-infection(s) is gaining greater appreciation <ns0:ref type='bibr' target='#b9'>(Griffiths et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b14'>Li &amp; Zhou 2013)</ns0:ref>, but it remains challenging to get such information. The source of clinical samples and the sequencing technology can be inferior in co-infection detection <ns0:ref type='bibr' target='#b1'>(Birdsell et al. 2018b)</ns0:ref>.</ns0:p><ns0:p>A better understanding of the prevalence of co-infection is urgently required, partly because coinfecting pathogens can interact with each other directly or indirectly via the host 's resources or immune system <ns0:ref type='bibr' target='#b5'>(Cox 2001;</ns0:ref><ns0:ref type='bibr' target='#b9'>Griffiths et al. 2011)</ns0:ref>. These interactions within co-infected hosts can alter the transmission, clinical progression and control of multiple infectious diseases as compared to single pathogen species infection <ns0:ref type='bibr' target='#b4'>(Chiodini 2001;</ns0:ref><ns0:ref type='bibr' target='#b9'>Griffiths et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b17'>Palacios et al. 2009)</ns0:ref>. Recent studies indicate that the adverse effects of co-infection are more common than those with no-effects or positive impacts on human health <ns0:ref type='bibr' target='#b18'>(Pullan &amp; Brooker 2008)</ns0:ref>.</ns0:p><ns0:p>The underdiagnosis of co-infections is attributed to a lack of clinical suspicion, common symptoms, and the fact that conventional methods have little capacity to detect co-infections in the absence of a priori knowledge.</ns0:p><ns0:p>Co-infection can potentially affect the performance of laboratory testing for coronavirus disease 2019. A previous study <ns0:ref type='bibr' target='#b11'>(Lai et al. 2020)</ns0:ref> showed that reverse transcription polymerase chain reaction (rRT -PCR) could not detect SARS-CoV-2 in two patients co-infected with influenza A virus. Given these considerations, COVID-19 might be underdiagnosed, especially during the influenza season, since typical clinical symptoms of COVID-19, including fever, cough, and dyspnea, resemble those of influenza <ns0:ref type='bibr' target='#b2'>(Chen et al. 2020a;</ns0:ref><ns0:ref type='bibr' target='#b25'>Wu et al. 2020)</ns0:ref>.</ns0:p><ns0:p>Therefore, exploring new diagnostic approaches is essential to advance understanding of coinfection contribution to disease manifestations and treatment responses <ns0:ref type='bibr' target='#b0'>(Birdsell et al. 2018a)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50170:1:1:NEW 28 Jul 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>Remarkable developments in next-generation sequencing have recently made metagenomics, an unbiased shotgun method of analysis, a widely used tool in just about every field of biology, including diagnosis of infectious diseases <ns0:ref type='bibr' target='#b10'>(Kuroda et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b13'>Lecuit &amp; Eloit 2014)</ns0:ref>. In this study, using fastv and Kraken 2, genome sequences of various viruses, including the SARS-CoV-2 virus, were detected. Influenza A virus was detected in three COVID-19 infected patients in China. Kraken 2 is fast and requires less memory than Kraken 1. However, the standard database construction requires approximately 100 gigabytes (GB) of disk space and randomaccess memory (RAM) of more than 30 GB. For that purpose, an AWS EC2 h1.8xlarge storage optimized instance with 16 dual-core hyperthreaded 2.30 GHz CPUs and 132 GB of RAM was used.</ns0:p><ns0:p>Understanding the nature and consequences of co-infection is essential for accurate estimates of infectious disease burden. In particular, more systematic data on infectious diseases would also help measure the extent of the impact of co-infection on human health. Increased knowledge of the risk factors, the conditions in which co-infecting pathogens interact and the mechanisms behind these interactions, particularly in experimental studies, will also help develop and evaluate infectious disease management programs. To date, most disease prevention programs typically follow a vertical intervention strategy to treat each pathogen individually. If co-infecting pathogens consistently interact to worsen human health, more advanced control strategies will need to be established.</ns0:p><ns0:p>The consequence of reported co-infections in COVID-19 patients is still unclear. Future studies are urgently needed not only to genetically characterize these viruses and conduct screening studies for different viruses in larger sample sets but also to research the impact of co-infection on the host immune system of COVID-19 patients, and their role in disease progression.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50170:1:1:NEW 28 Jul 2020)Manuscript to be reviewed study have confirmed the actual existence of genome sequences of other viruses in SARS-CoV-2 infected patients.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: SARS-CoV-2 detection by fastv. SARS-CoV-2 was detected in WIV07 patient,</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2: The Krona pie chart of the viral taxonomy of the WIV07 patient. Viruses identified</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3: The Krona pie chart of the viral taxonomy of the WIV06 patient. Viruses identified</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4: The Krona pie chart of the viral taxonomy of the WIV04 patient. Viruses identifiedfrom kraken 2 analysis of samples collected from SRR11092062 patients were visualized using krona tool. Among viral communities, SARS-CoV-2 (1%), rhabdovirus (0.8%) and influenza type A (0.4%) dominated the sequence data from WIV04 patient.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='17,42.52,255.37,525.00,418.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='18,42.52,255.37,525.00,408.00' type='bitmap' /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:06:50170:1:1:NEW 28 Jul 2020)</ns0:note> </ns0:body> "

"Dear Prof. Dr.Theerapong Krajaejun, Thank you for your suggestions on my manuscript, and thorough comments. I appreciate the insightful and constructive comments of the reviewers and detailed how I addressed each. Mohamed Abouelkhair, DVM, MS, Ph.D., DACVM  Diplomate of American College of Veterinary Microbiologist  Post-Doctoral Research Associate Comparative and Experimental medicine [email protected] University of TN Veterinary Medical Center 2407 River Drive Room A-239 Knoxville, TN 37996 Phone: 865-919-8581 ORCID: https://orcid.org/0000-0003-0109-6000 Researchgate: https://www.researchgate.net/profile/Mohamed_Abouelkhair2 Reviewer 1 Basic reporting In this study, the author examined infection of COVID-19 and other viruses in publicly available 68 SRA data using Fastv program, which is published in bioRxiv:2020.2005.2012.092163. 10.1101/2020.05.12.092163. Author identified infection of COVID-19 in 65 SRA data. In addition, several viruses were identified. Experimental design In fact, this manuscript should be rejected due to several reasons. The first is that there is no novelty of this study. Similar study is already done by Chen et al. who developed Fastv program. The difference is just the number of SRA data for virus identification. Although the author increased the number of SRA data for virus identification, I cannot find any valuable results. Title should be also changed. Most SRA data were derived from transcriptome data not metagenome data. Maybe co-infection might be common in COVID-19 infected samples. I cannot find any results which support the identification of other viruses in the examined SRA data. I appreciate your time reading my manuscript and your valuable comments. I've edited the method section with more details on how each program works. Also, I have provided a Github link for each tool so that anyone who needs to know more. I have revised the tile, results and discussion sections to explain the importance of my paper findings. Chen et al. developed a computational toolset for rapid identification of microorganisms, in general, from sequencing data, and he generously made it available for anyone. In my manuscript, since I am looking for co-infection, I used his tool to screen the data for viral genomes sequences. Taxonomic classification was performed using Kraken 2 on all reads containing one or more virus sequences other than SARS-CoV-2 to confirm the result of fastv analysis. It is a self-funded study (no fund from any source). The standard Kraken 2 database construction requires approximately 100 gigabytes (GB) of disk space and random-access memory (RAM) of more than 30 GB. For that purpose, an AWS EC2 h1.8xlarge storage optimized instance with 16 dual-core hyperthreaded 2.30 GHz CPUs and 132 GB of RAM was used, which cost more than $2 per hour. I used fastv first on all sequence data and then used Kraken 2 for only screening reads containing one or more virus sequences other than SARS-CoV-2. The findings of my manuscript have confirmed the actual existence of genome sequences of other viruses in SARS-CoV-2 infected patients and provide strong evidence of co-infections. Co-infection can potentially affect the performance of laboratory testing for coronavirus disease 2019. A previous study (Lai et al. 2020) showed that reverse transcription polymerase chain reaction (rRT -PCR) could not detect SARS-CoV-2 in two patients co-infected with influenza A virus. Given these considerations, COVID-19 might be underdiagnosed, especially during the influenza season, since typical clinical symptoms of COVID-19, including fever, cough, and dyspnea, resemble those of influenza (Chen et al. 2020a; Wu et al. 2020). Validity of the findings There is no result associated with validation of the findings in this study. Comments for the author The manuscript is really poorly written. There are lots of errors in English. Many sentences and paragraphs were poorly written. The materials and methods were not sufficiently written. I only see the detailed information of Macbook pro which was used for data analysis. The results were really badly written. Without proper results, how the author can write the discussion part? Revised by English language institute at the University of Tennessee, USA. I deleted the macbook pro information. There were lots of errors. These are some examples. In abstract L32: sixty-eight public next-generation sequencing libraries -> sixty-eight public next-generation sequencing data Revised as suggested L34: Screen the raw reads for viral genome sequences, including SARS-COV-2, using an alignment-free method based on K-mer mapping and extension. -> The sentence is not complete. Revised L65 (Viruses 2020) -> The reference is not correct. Revised, I replaced it with a correct one L66 98 percent -> 98% Revised as suggested L104 A reference for Fastv is required. Revised, reference was added. L109 libraries -> data Revised as suggested Materials and methods L114-118 The hardware for data analysis may be not necessary. Revised L120-126 Authors selected SRA data from six projects. Which thresholds were used to select SRA data? Revised and I mentioned why I have selected that data in the revised manuscript. L126 Table. 1 -> Table 1 Revised L 128-138 It is necessary how authors conducted data analysis using Fastv program in detail. Revised L142 We conducted -> I conducted (there is only one author in this manuscript) Revised as suggested The Table 1 is not informative. Author should describe sample information for individual SRA data. L149-150 No information associated with PRJNA631042 is available. Revised Results and discussion are terribly written. Author should write results in detail. Tables and figures were poorly prepared. Revised Reviewer 2 Basic reporting This paper reported identification of possible viral co-infections in samples from SARS-CoV-2 infected patients. This article is well written and easy to follow. However, Figures and Tables need a major improvement. In general, the results section was quite vague where random outputs from Fastv software are shown. Experimental design The author simply used Fastv to analyse 68 publicly available SARS-CoV-2 samples from SRA database. Fastv outputs for all analysed samples are not provided. The author should make the Fastv output for all samples publicly available. Validity of the findings Whilst the authors discovered possible co-infections in a number of samples, the significance of these identification as well as their relevance for the accurate estimates of infectious disease burden was not explored. The authors should either attempt to describe how these co-infections could be driving disease progression or outcome, or outline that the consequence of these co-infections are still unclear. Thank you so much for your valuable comments and encouraging words. This is an excellent comment. The consequence of reported co-infections in COVID-19 patients is still unclear. It would be interesting to explore that in future funded studies. Co-infection can potentially affect the performance of laboratory testing for coronavirus disease 2019. A previous study (Lai et al. 2020) showed that reverse transcription polymerase chain reaction (rRT -PCR) could not detect SARS-CoV-2 in two patients co-infected with influenza A virus. Given these considerations, COVID-19 might be underdiagnosed, especially during the influenza season, since typical clinical symptoms of COVID-19, including fever, cough, and dyspnea, resemble those of influenza (Chen et al. 2020a; Wu et al. 2020).  Comments for the author Table 1 should be placed in supplementary. Can also add more information about each sample such as read length, total sequences, total bases, etc. Revised as suggested Figure 1's resolution is too low. Impossible to read. Revised, I changed the format of all figures to pdf, which should increase the resolution. I have high-resolution figures in .tiff format, but unfortunately, this format is not supported by peerJ. Remove 'Figure.a:' from Figure 1 text. Revised as suggested Which sample does Figure 1 represent? Sample from WIV07 patient (accession number SRR11092059), I revised that in the manuscript Line 158: Figure.2, a: should be Figure 1 Revised as suggested Line 161: Figure.2, b: there is no description of this Figure in the manuscript. Revised, now I have Figure 2 A, B and C. Line 166-168: The author should provide sampleIDs for those possible co-infected samples. Revised Line 168: Figure 3. Why use Krona to visualise these 3 samples? Are they the only samples that contain possible co-infection? Samples with co-infections are SRR11772648, SRR10971381, SRR11092062, SRR11092060 and SRR11092059. I validated the fastv result by kraken 2, then visualized the results with Krona tool (https://github.com/marbl/Krona/wiki), which displays hierarchical data (like taxonomic assignation) in multi-layered pie charts. I converted the Kraken 2 output in HTML format using the program ktImportTaxonomy, which parses the information relative to the query ID and the taxonomy ID. For all co-infected samples, what are their coverage and depth? Can they be false positive? Revised as suggested, information on coverage and mean depth were added for each sample. Fastv is an alignment-free, ultra-fast tool for detecting the microbial sequences in sequence data. It can identify target microorganisms using unique k-mers. It detects SARS and other coronaviruses from sequencing data and efficiently distinguishing SARS from MERS. Moreover, the results obtained from Kraken 2 analysis confirmed the existence of other co-infecting viruses. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>In December 2019, an ongoing outbreak of pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2/ 2019-nCoV) infection was initially reported in Wuhan, Hubei Province, China. Early in 2020, the World Health Organization (WHO) announced a new name for the 2019-nCoV-caused disease: coronavirus disease 2019 (COVID-19) and declared COVID-19 to be a Public Health Emergency of International Concern (PHEIC). Cellular co-infection is a critical determinant of viral fitness and infection outcomes and plays a crucial role in shaping the host immune response to infections.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head><ns0:p>In this study, 68 public next-generation sequencing data from SARS-CoV-2 infected patients were retrieved from the NCBI Sequence Read Archive database using SRA-Toolkit. Data screening was performed using an alignment-free method based on k-mer mapping and extension, fastv. Taxonomic classification was performed using Kraken 2 on all reads containing one or more virus sequences other than SARS-CoV-2.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>SARS-CoV-2 was identified in all except three patients. Influenza type A (H7N9) virus, human immunodeficiency virus, rhabdovirus, human metapneumovirus, Human adenovirus, Human herpesvirus 1, coronavirus NL63, parvovirus, simian virus 40, and hepatitis virus genomes sequences were detected in SARS-CoV-2 infected patients. Besides, a very diverse group of bacterial populations were observed in the samples.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>In December 2019, the first cases of coronavirus disease 2019 were possibly due to a zoonotic transmission in China. It was tied to a large seafood market that also traded in live wild animals <ns0:ref type='bibr' target='#b28'>(Tay et al. 2020)</ns0:ref>. The causative virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is capable of human-to-human transmission and rapidly spread to other regions of China and other countries (World Health Organization 2020). It is now a global pandemic and is a considerable concern for public health. So far, more than 16,101,367 confirmed cases were diagnosed in nearly 213 countries and territories around the world and two international conveyances, causing globally over 645,000 deaths <ns0:ref type='bibr' target='#b33'>(Worldometer 2020, July 25)</ns0:ref>.</ns0:p><ns0:p>Coronaviruses are known to cause severe diseases in humans and animals. Of these, four human coronaviruses (229E, NL63, OC43, and HKU1) typically only infect the upper respiratory tract and cause relatively minor symptoms <ns0:ref type='bibr' target='#b9'>(Fehr &amp; Perlman 2015)</ns0:ref>. However, there are three coronaviruses (severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and SARS-CoV-2) that can replicate in the lower respiratory tract and cause pneumonia, which can be fatal. With 79% genome sequence similarity, SARS-CoV is the closest relative to SARS-CoV-2 among human coronaviruses <ns0:ref type='bibr'>(Gorbalenya et al. 2020)</ns0:ref>. However, of all known coronavirus sequences, SARS-CoV-2 is most similar to bat coronavirus RaTG13, with a similarity of 98% <ns0:ref type='bibr' target='#b35'>(Zhou et al. 2020)</ns0:ref>. SARS-CoV-2 pathophysiology closely parallels that of SARS-CoV infection, with active inflammatory responses strongly implicated in the resulting airway damage <ns0:ref type='bibr' target='#b30'>(Wong et al. 2004</ns0:ref>).</ns0:p><ns0:p>Hence the extent of the disease in patients is attributed not only to the viral infection but also to the host's response <ns0:ref type='bibr' target='#b28'>(Tay et al. 2020)</ns0:ref>.</ns0:p><ns0:p>Underlying co-infections in primary infectious disease are an important variable that needs to be considered but is often undetected. Remarkable developments in next-generation sequencing have recently made metagenomics, an unbiased shotgun method of analysis, a widely used tool in just about every field of biology, including diagnosis of infectious diseases <ns0:ref type='bibr' target='#b15'>(Kuroda et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b17'>Lecuit &amp; Eloit 2014)</ns0:ref>. Metagenomics is powerful because it can diagnose unsuspected microbial agents <ns0:ref type='bibr' target='#b29'>(Wilson et al. 2014)</ns0:ref>. It directly analyzes samples in their entirety, eliminating the need for prior knowledge to obtain comprehensive information. In this capacity, metagenomics exceeds traditional diagnostic limitations. With the microbial genomes in hand, we can now explore the possibility of using metagenomic and metatranscriptomic nextgeneration sequencing (mNGS) directly as a screening method of other microbes in a sample <ns0:ref type='bibr' target='#b26'>(Plyusnin et al. 2020)</ns0:ref>.</ns0:p><ns0:p>A simple approach would be to first map sequencing reads from the sample to the reference microbial genome. However, the accuracy of such an alignment-based method is relatively low compared to an alignment-free approach. In the alignment-based method, genome sequences from closely related viruses can lead to false-positive results <ns0:ref type='bibr' target='#b5'>(Chen et al. 2020b)</ns0:ref>. Moreover, the virus-specific reads obtained may not be adequate for unambiguous detection (degraded RNA, incompletely target-enriched sequence library by multiple-PCR <ns0:ref type='bibr' target='#b21'>(Lundberg et al. 2013)</ns0:ref> or hybrid capture <ns0:ref type='bibr' target='#b8'>(Duncavage et al. 2011)</ns0:ref>, which can lead to false-negative results.</ns0:p><ns0:p>Fastv is an alignment-free, ultra-fast tool for detecting the microbial sequences in sequence data <ns0:ref type='bibr' target='#b5'>(Chen et al. 2020b)</ns0:ref>. It can identify target microorganisms using unique k-mers. It detects SARS and other coronaviruses from sequencing data and efficiently distinguishing SARS from MERS.</ns0:p><ns0:p>In this study, public next-generation sequencing data from SARS-CoV-2 infected patients were analyzed by fastv using the pre-computed unique k-mer resources <ns0:ref type='bibr' target='#b5'>(Chen et al. 2020b)</ns0:ref>.</ns0:p><ns0:p>Taxonomic classification was performed using Kraken 2 on all reads containing more than one microbial sequence <ns0:ref type='bibr' target='#b31'>(Wood et al. 2019)</ns0:ref>. The present study's findings have confirmed the actual existence of genome sequences of other microbes in SARS-CoV-2 infected patients.</ns0:p></ns0:div> <ns0:div><ns0:head>Material and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Computing hardware</ns0:head><ns0:p>Amazon Elastic Compute Cloud (EC2) instance (i.e., virtual server in the AWS cloud) was used.</ns0:p><ns0:p>SRA-tools package version 2.9.1 (https://github.com/ncbi/sra-tools), Kraken 2 (https://github.com/DerrickWood/kraken2) <ns0:ref type='bibr' target='#b31'>(Wood et al. 2019)</ns0:ref>, and fastv version 0.9.0 (https://github.com/OpenGene/fastv) <ns0:ref type='bibr' target='#b5'>(Chen et al. 2020b)</ns0:ref> were installed within the Linux 2 EC2 instance.</ns0:p></ns0:div> <ns0:div><ns0:head>SRA database mining</ns0:head><ns0:p>Next-generation sequencing technologies have enabled large-scale genomic surveillance of SARS-CoV-2 as thousands of isolates are being sequenced worldwide and deposited in public data repositories. The sequence data were downloaded as .sra files using the prefetch tool (https://github.com/ncbi/sra-tools/tree/master/tools/prefetch), then extracted to. fastq files using the NCBI fastq-dump tool (https://github.com/ncbi/sra-tools/tree/master/tools/fastq-dump).</ns0:p><ns0:p>Data sets for analysis were chosen through a keyword search of the SRA descriptions for 'COVID19' and downloaded between 27 January 2020 and 16 May 2020. Sequence data from negative COVID-19 patients, experimental studies, and controlled access were excluded.</ns0:p><ns0:p>(Table <ns0:ref type='table'>S1</ns0:ref>).</ns0:p><ns0:p>Table <ns0:ref type='table'>S1</ns0:ref>: SRA sequences used in this study with the detection result for SARS-</ns0:p></ns0:div> <ns0:div><ns0:head>CoV-2 k-mer</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:06:50170:2:0:NEW 13 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Sequence data pre-processing and screening using fastv Fastv, along with the pre-computed unique k-mer resources, was used as previously described <ns0:ref type='bibr' target='#b5'>(Chen et al. 2020b)</ns0:ref>. Initially, fastv performed adapter trimming, quality pruning, base correction, and other pre-processing to ensure the accuracy of k-mer analysis on fastq input files. The fastv tool identifies a target virus from sequencing data and detects any microbial sequences for which a unique k-mer data is provided. A unique SARS-CoV-2 k-mer set and the SARS-CoV-2 reference genome were used as input files (downloaded from https://github.com/OpenGene/fastv/tree/master/data) with the k-mer collections for viral and microbial genomes (downloaded from http://opengene.org/microbial.kc.fasta.gz). The k-mer scanning results were visualized in a figure on a single HTML page by fastv.</ns0:p></ns0:div> <ns0:div><ns0:head>Sequence data analysis using Kraken 2</ns0:head><ns0:p>The results of fastv were validated with Kraken 2. Kraken 2 is the latest version of Kraken, a taxonomic classification system that uses exact k-mer matches to achieve high accuracy and rapid classification (https://github.com/DerrickWood/kraken2) <ns0:ref type='bibr' target='#b31'>(Wood et al. 2019)</ns0:ref>. Kraken constructs an index of all k-mers found in the reference genomes and assigns each k-mer to the least common ancestor (LCA) of all species that have that k-mer. Then Kraken matches the kmers contained in the reads to this index and eventually assigns the reads to the taxon with the most fitting k-mers by following the path from the root of the tree <ns0:ref type='bibr' target='#b31'>(Wood et al. 2019)</ns0:ref>. Through lowering memory use by 85%, Kraken 2 improves upon Kraken 1, enabling higher numbers of genomic reference data to be used while retaining high accuracy and fivefold speed. A standard database containing RefSeq complete bacterial, archaeal, and viral genomes, along with the human genome and a collection of known vectors (UniVec_Core), was downloaded (https://ccb.jhu.edu/software/kraken2/downloads.shtml). The database was then constructed using 32 threads with the default parameters on an AWS EC2 h1.8xlarge storage optimized instance with 16 dual-core hyperthreaded 2.30 GHz CPUs and 132 gigabytes (GB) of RAM. <ns0:ref type='table'>PDF | (2020:06:50170:2:0:NEW 13 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head></ns0:div> <ns0:div><ns0:head>Data visualization</ns0:head><ns0:p>The results of Kraken 2 analysis were visualized with Pavian (https://github.com/fbreitwieser/pavian) <ns0:ref type='bibr' target='#b3'>(Breitwieser &amp; Salzberg 2016)</ns0:ref> and Krona tool (https://github.com/marbl/Krona/wiki) <ns0:ref type='bibr' target='#b24'>(Ondov et al. 2011)</ns0:ref>, which displays hierarchical data (like taxonomic assignation) in multi-layered pie charts. The Kraken 2 outputs were converted in HTML format using the program ktImportTaxonomy (https://github.com/marbl/Krona/tree/master/KronaTools/scripts), which parses the information relative to the query ID and the taxonomy ID.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>SARS-CoV-2 Identification</ns0:head><ns0:p>Sequence data analysis was performed on public Illumina HiSeq/ MiSeq libraries from the NCBI SRA database (Bioproject PRJNA605983) sequenced from bronchoalveolar lavage fluid from five patients (WIV02, WIV04, WIV05, WIV06, and WIV07) with pneumonia at the early COVID-19 outbreak in Wuhan, China. Nine libraries were downloaded as .sra files using the prefetch tool; then, the fastq files were extracted using the NCBI fastq-dump tool. Prior to the k-mer analysis, sequencing adapters and low-quality bases were removed by fastv.</ns0:p><ns0:p>After scanning the fastq data, fastv reported the k-mer coverage for each microbial genome with valid hits (Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). where twelve SARS-CoV-2 hits were included in the genome list and ordered by k-mer coverage (99.4972% to 99.2308%). The number of hits (on the y-axis) of each k-mer key (on the x-axis) were plotted. Mismatches were highlighted in red. SARS-CoV-2 was detected in all of the 68-sequence data except SRR11772662, SRR11772663, and SRR11772664 samples were negative for SARS-CoV-2. These samples belong to one study (Bioproject PRJNA631042), where the research group used different sequencing technologies on the same sample to find a cost-effective and highly scalable method for SARS-CoV-2 sequencing. Because sequence technologies vary in reading depth and coverage thresholds, fastv could not detect SARS-CoV-2 in sequenced samples with lower coverage metrics.</ns0:p></ns0:div> <ns0:div><ns0:head>Non-SARS-CoV-2 genome sequences were detected in COVID-19 infected patients</ns0:head><ns0:p>Fastv also identified influenza type A (A/Shanghai/02/2013(H7N9) and rhabdovirus genomic sequences in the data from WIV02 (SRR11092058 and SRR11092063 data), WIV04 (SRR11092057 and SRR11092062 data), WIV05 (SRR11092061 data), WIV06 (SRR11092056 and SRR11092060 data), and WIV07 (SRR11092059 and SRR11092064 data) patients.</ns0:p><ns0:p>Influenza type A segment 4 hemagglutinin (HA) gene was detected with high coverage (100%, 100%, 98.57%, 95.71%, and 100%) and mean depth <ns0:ref type='bibr'>(5.58, 16.52, 4.8, 2.95, and 881.37</ns0:ref>) in WIV02, WIV04, WIV05, WIV06, and WIV07 patients, respectively. Genes coding for Influenza A virus polymerase, non-structural proteins, matrix proteins 1 and 2 were also identified in the previously mentioned patients but with lower coverages. The genome sequence of rhabdovirus was detected with coverage <ns0:ref type='bibr'>(57.36, 72.73, 57.58, 67.75, and 53</ns0:ref>.46%) and mean depth (4.82, 8.13, 4.84, 5.08, and 4.06) in WIV02, WIV04, WIV05, WIV06, and WIV07 patients, respectively.</ns0:p><ns0:p>The genome sequence of the Nipah virus was detected in WIV05, WIV06, and WIV07 patients.</ns0:p><ns0:p>Infection with the Nipah virus in humans causes a number of clinical manifestations that range from asymptomatic (subclinical) infection to acute respiratory infection and fatal encephalitis. Manuscript to be reviewed below 21%. The low coverage and non-human specific pathogen hits have been overlooked (Table <ns0:ref type='table'>S2</ns0:ref>).</ns0:p><ns0:p>Human coronavirus 229E genome sequence was detected (coverage=14% and mean depth=1.55) in SRR11772654 (Bioproject PRJNA631042). Human adenovirus 5 sequences were detected in SRR11772660, SRR11772663, SRR11772666, SRR11772672, SRR11772675 and SRR11772680 data. In addition, human adenovirus 1 sequences were detected in SRR11772663 and SRR11772666 data. Parvovirus NIH-CQV genes coding for a putative replication-associated protein (rep), and putative capsid protein (cap) (coverage=14.51% and mean depth=0.41) were detected in SRR10971381 (Bioproject PRJNA603194) (Table <ns0:ref type='table'>S2</ns0:ref>).</ns0:p><ns0:p>A very diverse group of bacterial populations were observed in the COVID-19 infected patients.</ns0:p><ns0:p>Enterobacter hormaechei was identified in WIV02, WIV04, WIV05, WIV06, and WIV07 patients.</ns0:p><ns0:p>Enterobacter hormaechei is an important emerging pathogen and can cause nosocomial infections, and often have resistance to multiple clinically relevant antibiotics <ns0:ref type='bibr' target='#b23'>(Monahan et al. 2019)</ns0:ref>. Acinetobacter baumannii sequence was detected in WIV05 and WIV07 patients. A. baumannii is one of the most successful pathogens associated with hospital-acquired infections worldwide <ns0:ref type='bibr' target='#b18'>(Lee et al. 2017)</ns0:ref>. Enterococcus faecalis sequence was identified in WIV04, WIV05, and WIV07 patients (Table <ns0:ref type='table'>S2</ns0:ref>).</ns0:p><ns0:p>Coliphage phi-X174 was identified in most sequence data, which might be introduced by the Illumina PhiX control library <ns0:ref type='bibr' target='#b22'>(Meyer &amp; Kircher 2010)</ns0:ref>. Stenotrophomonas phage phiSMA7, Enterobacteria phage phi80, DE3, Fels-2 and M13, Proteus virus, and Delftia phage RG-2014 were identified in the sequence data (Table <ns0:ref type='table'>S2</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Kraken Taxonomic classification</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:06:50170:2:0:NEW 13 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Taxonomic classification was performed using Kraken 2 on all reads containing more than one virus sequences. The genetic data for constructing the databases were retrieved from the NCBI RefSeq library. A very diverse group of viral, bacterial, and archaeal populations was observed in the samples. A taxonomic classification that was obtained from WIV04, WIV06, and WIV07 patients revealed a dominance of Bacteria (7%, 5%, and 59%, respectively), followed by Viruses (0.3%, 0.3%, and 0.3%, respectively) while Archaea was lower than 0.02% in all the patients. Among viral communities, influenza type A (8%), rather than SARS-CoV-2 (2%), was found to be dominant in the WIV07 patient, which is consistent with fastv result (Figure <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). SARS-CoV-2, rhabdovirus, and influenza type A dominated the sequence data from WIV06 patient (Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>) and WIV04 patient (Figure <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>).</ns0:p><ns0:p>A rank code, indicating unclassified (U), domain (D), kingdom (K), phylum (P), class (C), order (O), family (F), genus (G), or species (S) was used. from Kraken 2 analysis of samples collected from SRR11092059 patients were visualized using the krona tool. Among viral communities, influenza type A (8%), SARS-CoV-2 (2%), and rhabdovirus (0.6%) dominated the sequence data from WIV07 patient. from Kraken 2 analysis of samples collected from SRR11092062 patients were visualized using the krona tool. Among viral communities, SARS-CoV-2 (1%), rhabdovirus (0.8%), and influenza type A (0.4%) dominated the sequence data from WIV04 patient.</ns0:p><ns0:p>Acinetobacter baumannii and Enterobacter species genomic sequences were detected in SRR11092059 (Figure <ns0:ref type='figure' target='#fig_13'>5</ns0:ref>), SRR11092060 (Figure <ns0:ref type='figure' target='#fig_6'>6</ns0:ref>), SRR11092061, SRR11092062 (Figure <ns0:ref type='figure' target='#fig_7'>7</ns0:ref>), and SRR11092063 sequence data. By using Kraken2, a tool for read taxonomy, many bacterial species were identified that most of them present in the normal flora and rarely cause problems. However, compared to the fastv result, the Pasteurella multocida sequence was detected in SRR11092062 (Figure <ns0:ref type='figure' target='#fig_7'>7</ns0:ref>) and SRR11092063 sequence date. The genome sequence of Staphylococcus aureus was detected in SRR11092059 data (Figure <ns0:ref type='figure' target='#fig_13'>5</ns0:ref>). </ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The importance of detecting co-infections is becoming more recognized <ns0:ref type='bibr' target='#b12'>(Griffiths et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b20'>Li &amp; Zhou 2013)</ns0:ref>, but it remains challenging to get such information. The source of clinical samples and the sequencing technology can be inferior in co-infection detection <ns0:ref type='bibr' target='#b2'>(Birdsell et al. 2018b)</ns0:ref>.</ns0:p><ns0:p>A better understanding of co-infection's prevalence is required, partly because co-infecting pathogens can interact with each other directly or indirectly via the host's resources or immune system <ns0:ref type='bibr' target='#b7'>(Cox 2001;</ns0:ref><ns0:ref type='bibr' target='#b12'>Griffiths et al. 2011)</ns0:ref>. These interactions within co-infected hosts can alter the transmission, clinical progression, and control of multiple infectious diseases as compared to single pathogen species infection <ns0:ref type='bibr' target='#b6'>(Chiodini 2001;</ns0:ref><ns0:ref type='bibr' target='#b12'>Griffiths et al. 2011;</ns0:ref><ns0:ref type='bibr' target='#b25'>Palacios et al. 2009)</ns0:ref>.</ns0:p><ns0:p>Recent studies indicate that co-infection's adverse effects are more common than those with no-effects or positive impacts on human health <ns0:ref type='bibr' target='#b27'>(Pullan &amp; Brooker 2008)</ns0:ref>.</ns0:p><ns0:p>The underdiagnosis of co-infections is attributed to a lack of clinical suspicion, common symptoms, and the fact that conventional methods have little capacity to detect co-infections in the absence of a priori knowledge.</ns0:p><ns0:p>Co-infection can potentially affect the performance of laboratory testing for coronavirus disease 2019. A previous study <ns0:ref type='bibr' target='#b16'>(Lai et al. 2020)</ns0:ref> showed that reverse transcription polymerase chain reaction (RT -PCR) could not detect SARS-CoV-2 in two patients co-infected with influenza A PeerJ reviewing PDF | (2020:06:50170:2:0:NEW 13 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed virus. Some researchers have suggested that inadequate viral specimens, the use of improperly validated assay, timing and methods of collecting specimens, the presence of mutations at the primer binding site, and co-infection with other viruses might be responsible <ns0:ref type='bibr' target='#b0'>(Arevalo-Rodriguez et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b13'>Kucirka et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b16'>Lai et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b19'>Li et al. 2020)</ns0:ref>. Based on a limited number of observational studies, it was found that the false-negative rate for SARS-CoV-2 RT-PCR was 20% <ns0:ref type='bibr' target='#b16'>(Lai et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b19'>Li et al. 2020)</ns0:ref>.</ns0:p><ns0:p>Given these considerations, COVID-19 might be underdiagnosed, especially during the influenza season, since typical clinical symptoms of COVID-19, including fever, cough, and dyspnea, resemble those of influenza <ns0:ref type='bibr' target='#b4'>(Chen et al. 2020a;</ns0:ref><ns0:ref type='bibr' target='#b34'>Wu et al. 2020)</ns0:ref>.</ns0:p><ns0:p>Therefore, exploring new diagnostic approaches is essential to advance understanding of coinfection contribution to disease manifestations and treatment responses <ns0:ref type='bibr' target='#b1'>(Birdsell et al. 2018a)</ns0:ref>.</ns0:p><ns0:p>Remarkable developments in next-generation sequencing have recently made metagenomics, an unbiased shotgun method of analysis, a widely used tool in just about every field of biology, including diagnosis of infectious diseases <ns0:ref type='bibr' target='#b15'>(Kuroda et al. 2012;</ns0:ref><ns0:ref type='bibr' target='#b17'>Lecuit &amp; Eloit 2014)</ns0:ref>.</ns0:p><ns0:p>In this study, using k-mer based tools (fastv and Kraken 2), genome sequences of various microorganisms, including the SARS-CoV-2 virus, were detected. The accuracy of such an alignment-free method is relatively high compared to an alignment-based approach. Fastv is an alignment-free, ultra-fast tool for detecting the microbial sequences in sequence data using unique k-mers <ns0:ref type='bibr' target='#b5'>(Chen et al. 2020b</ns0:ref>). To validate the results obtained from fastv analysis, Kraken 2 was used. Kraken 2 is the latest version of Kraken, a taxonomic classification system that uses exact k-mer matches to achieve high accuracy and rapid classification <ns0:ref type='bibr' target='#b31'>(Wood et al. 2019)</ns0:ref>.</ns0:p><ns0:p>Kraken 2 is fast and requires less memory than Kraken 1. However, the standard database construction requires approximately 100 gigabytes (GB) of disk space and random-access memory (RAM) of more than 30 GB. For that purpose, an AWS EC2 h1.8xlarge storage Manuscript to be reviewed optimized instance with 16 dual-core hyperthreaded 2.30 GHz CPUs and 132 GB of RAM was used.</ns0:p><ns0:p>Multidrug-resistant bacteria associated with hospital-acquired infections worldwide, such as E. hormaechei , S. aureus, P. multocida, and A. baumannii, were detected in COVID-19 infected patients <ns0:ref type='bibr' target='#b18'>(Lee et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b23'>Monahan et al. 2019)</ns0:ref>. Most of the infections caused by the previously mentioned bacteria occur in critically ill and or immunocompromised patients in the intensive care unit (ICU) setting <ns0:ref type='bibr' target='#b10'>(Fournier et al. 2006</ns0:ref>).</ns0:p><ns0:p>Understanding the nature and consequences of co-infection is essential for accurate estimates of infectious disease burden. In particular, more systematic data on infectious diseases would also help measure the extent of co-infection on human health. Increased knowledge of the risk factors, the conditions in which co-infecting pathogens interact, and the mechanisms behind these interactions, particularly in experimental studies, will also help develop and evaluate infectious disease management programs.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In this study, screening of 68 public next-generation sequencing data from SARS-CoV-2 infected patients was performed using fastv and Kraken 2. Multiple viruses, including the SARS-CoV-2 virus, genome sequences were detected. Further large-sample studies are warranted to investigate the prevalence of COVID-19 co-infection, the impact of co-infection on the host immune system of COVID-19 patients, and their role in disease progression. The Krona pie chart of the viral taxonomy of the WIV07 patient.</ns0:p><ns0:p>Viruses identified from kraken 2 analysis of samples collected from SRR11092059 patients were visualized using krona tool. Among viral communities, influenza type A (8%), SARS-CoV-2 (2%) and rhabdovirus (0.6%) dominated the sequence data from WIV07 patient.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50170:2:0:NEW 13 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 3</ns0:note><ns0:p>The Krona pie chart of the viral taxonomy of the WIV06 patient.</ns0:p><ns0:p>Viruses identified from kraken 2 analysis of samples collected from SRR11092060 patients were visualized using krona tool. Among viral communities, SARS-CoV-2 (1%), rhabdovirus (0.6%) and influenza type A (0.4%) dominated the sequence data from WIV06 patient. Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 4</ns0:note><ns0:p>The Krona pie chart of the viral taxonomy of the WIV04 patient.</ns0:p><ns0:p>Viruses identified from kraken 2 analysis of samples collected from SRR11092062 patients were visualized using krona tool. Among viral communities, SARS-CoV-2 (1%), rhabdovirus (0.8%) and influenza type A (0.4%) dominated the sequence data from WIV04 patient. Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1: SARS-CoV-2 detection by fastv. SARS-CoV-2 was detected in WIV07 patient,</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>In addition, human immunodeficiency virus, human herpesvirus 1, human T-lymphotropic virus 1, hepatitis virus, and simian virus 40 were found in WIV07 patient sequence data with coverage PeerJ reviewing PDF | (2020:06:50170:2:0:NEW 13 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 :</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2: The Krona pie chart of the viral taxonomy of the WIV07 patient. Viruses identified</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3: The Krona pie chart of the viral taxonomy of the WIV06 patient. Viruses identifiedfrom Kraken 2 analysis of samples collected from SRR11092060 patients were visualized using the krona tool. Among viral communities, SARS-CoV-2 (1%), rhabdovirus (0.6%), and influenza type A (0.4%) dominated the sequence data from WIV06 patient.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4: The Krona pie chart of the viral taxonomy of the WIV04 patient. Viruses identified</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure5:</ns0:head><ns0:label /><ns0:figDesc>Figure5: Bacteria Identified in SRR11092059. Sankey diagrams of Kraken 2 report results obtained from SRR11092059. The width of the flow is proportional to the number of reads. The number above each node is the number of k-mer hits. A rank code, indicating domain (D), phylum (P), family (F), genus (G), or species (S) was used.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 6 :</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6: Bacteria Identified in SRR11092060. Sankey diagrams of Kraken 2 report results obtained from SRR11092060. The width of the flow is proportional to the number of reads. The number above each node is the number of k-mer hits. A rank code, indicating domain (D), phylum (P), family (F), genus (G), or species (S) was used.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 7 :</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7: Bacteria Identified in SRR11092062. Sankey diagrams of Kraken 2 report results obtained from SRR11092062. The width of the flow is proportional to the number of reads. The number above each node is the number of k-mer hits. A rank code, indicating domain (D), phylum (P), family (F), genus (G), or species (S) was used.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 8 :</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8: Sankey diagrams of Kraken 2 report results obtained from SRR10971381. The width of the flow is proportional to the number of reads. The number above each node is the number of k-mer hits. A rank code, indicating domain (D), kingdom (K), phylum (P), family (F), genus (G), or species (S) was used.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50170:2:0:NEW 13 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 1 SARS</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50170:2:0:NEW 13 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 5 Bacteria</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Figure 6 Bacteria</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure 7 Bacteria</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head>Figure 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8</ns0:figDesc></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:06:50170:2:0:NEW 13 Sep 2020)</ns0:note> </ns0:body> "

"Dear Prof. Dr.Theerapong Krajaejun, Thank you for your suggestions on my manuscript, and thorough comments. I appreciate the insightful and constructive comments of the reviewers and detailed how I addressed each. Mohamed Abouelkhair, DVM, MS, Ph.D., DACVM  Diplomate of American College of Veterinary Microbiologist  Post-Doctoral Research Associate Comparative and Experimental medicine [email protected] University of TN Veterinary Medical Center 2407 River Drive Room A-239 Knoxville, TN 37996 Phone: 865-919-8581 ORCID: https://orcid.org/0000-0003-0109-6000 Researchgate: https://www.researchgate.net/profile/Mohamed_Abouelkhair2 Reviewer 1 Basic reporting In this study, the author examined infection of COVID-19 and other viruses in publicly available 68 SRA data using Fastv program and Kranken 2. Experimental design As compared to the previous version of the manuscript, the revised manuscript is very much improved. However, author did not provide many results derived from the data analysis such as bacterial taxonomy, bacteria phages, and non-SARS-CoV-2. Validity of the findings Author used two different programs for the virus identification. Comparative analysis might be useful. Comments for the author Authors used two different programs for the virus identification. Comparative analysis might be useful. L95 identification experiments -> Not clear to understand. Please revise it. It was revised. L96 using fastv, along with -> by fastv using the pre-computed ~ It was revised as suggested Supplementary data Fastv results such as peerj-50170-SRR10971381.html file should be summarized. Please do not show the raw results as it is. It was revised as suggested. A file summarizing the fastv results of the co-infected samples was prepared. The table is so large that it is in the manuscript, so I provided it as a supplementary table (Table S2). L133 We validated -> I validated (There is only one author in this manuscript. Check it thoroughly in the manuscript.) It was revised as suggested throughout the manuscript. L183 Author stated that coverages ranged from 47.55% to 53.22% indicating that the obtained sequences for the rhabdovirus is not complete genome. Please revise it. It was revised as suggested L208 Please revise the sentence as follows. A rank code, indicating unclassified (U), domain (D), kingdom (K), It was revised as suggested A rank code, indicating unclassified (U), domain (D), kingdom (K), phylum (P), class (C), order (O), family (F), genus (G), or species (S) was used. In the results, I would like to suggest generating phylogenetic trees using obtained viral sequences. fastv tool does not output the classified/identified sequence. The tool, by default, selected only twelve SARS-CoV-2 genomes from the GISAID database. Coverage sorting identifies the most closely related genome out of those 12 genomes to the query. To address your comment, I used the pavian tool to plot Sankey diagrams depicting the microbial communities' multi-domain profiles, where the flow's width is proportional to the number of reads. L228 Please revise the sentence. It is not easy to understand. The value of identifying underlying co-infection(s) is gaining greater appreciation Revised L232 urgently required -> delete urgently Deleted as suggested L253-260 It might be deleted. Deleted as suggested In discussion, it is necessary to discuss about identified bacteria. Discussed as suggested Authors used two different programs for the virus identification. Please compared the difference between two different methods in the results and discussion. It was revised as suggested Figure 2-4 Author identified many reads associated with bacteria phages. Please write results and discussion about the identified bacterial phage. It was revised as suggested. By using Kraken2, a tool for read taxonomy, many bacterial species were identified that most of them present in the normal flora and rarely cause problems. I focused on the most important pathogens, and the low coverage and non-human specific pathogen hits have been overlooked. I cannot find any tables or figures addressing the identified non-SARS-CoV-2. Please include them. In addition, author should provide a table or a figure showing identified bacteria by Kranken2. It was revised as suggested; four additional figures and one supplementary table are provided. Reviewer 2 Basic reporting The author has addressed some of the concerns I previously raised. However, more information is still needed at various places in the manuscript. Experimental design Download links and references for all the tools and databases used in this study need be added to the manuscript. All parameters also to be shown. This is to ensure reproducibility. Validity of the findings All analysis outputs have to be provided to show the validity of the findings described in this manuscript Comments for the author LINE 241: 'SRA-tools package (version 2.9.1), Kraken 2, and fastv (version 0.9.0)' - Please add download links and references for these tools. It was revised as suggested Amazon Elastic Compute Cloud (EC2) instance (i.e., virtual server in the AWS cloud) was used. SRA-tools package version 2.9.1 (https://github.com/ncbi/sra-tools), Kraken 2 (https://github.com/DerrickWood/kraken2) (Wood et al. 2019), and fastv version 0.9.0 (https://github.com/OpenGene/fastv) (Chen et al. 2020b) were installed within the Linux 2 EC2 instance. LINE 247-248: 'The sequence data were downloaded as .sra files using the prefetch tool, then extracted to. fastq files using the NCBI fastq-dump tool. ' - Please add download links and references for these tools. It was revised as suggested The sequence data were downloaded as .sra files using the prefetch tool (https://github.com/ncbi/sra-tools/tree/master/tools/prefetch), then extracted to. fastq files using the NCBI fastq-dump tool (https://github.com/ncbi/sra-tools/tree/master/tools/fastq-dump).  LINE: 285 'a k-mer-based program ' - Please elaborate. A k-mer-based program for? It was revised as suggested LINE 292-294 'A standard database containing RefSeq complete bacterial, archaeal, and viral genomes, along with the human genome and a collection of known vectors (UniVec_Core) was downloaded.' - Please add download links for these datasets. It was revised as suggested LINE 294: 'Then the database was built using' - Please provide database building parameters (e.g. default parameters?) It was revised as suggested LINE 311-312: 'We converted the Kraken 2 output in HTML format using the program ktImportTaxonomy' - Please add the download link for this tool. It was revised as suggested LINE 326-328: 'Figure 1: SARS-CoV-2 detection by fastv. SARS-CoV-2 was detected in WIV07 patient, where twelve SARS-CoV-2 hits were included in the genome list and ordered by k-mer coverage (99.4972% to 99.2308%). Mismatches were highlighted in red. ' - Provide more description. What are x and y axes representing? It was revised as suggested LINE 330: 'SARS-CoV-2 was detected in all of the other 68-sequence date' - date -> data - all of the other 59 sequence data It was revised as suggested LINE 330-331: 'SARS-CoV-2 was detected in all of the other 68-sequence date except three samples (Bioproject PRJNA631042) were negative for SARS-CoV-2. ' - Which sample/run ID were negative? It was revised as suggested LINE 430-432: 'Influenza type A (8%), rather than, SARS-CoV-2 (2%) was found to be dominant in the WIV07 patient (Figure 2).' - Is this consistent with Fastv result? Yes, it is. SECTION 'Kraken Taxonomic classification' - Provide results for all samples It was revised as suggested. I have included the Kraken 2 results of all of the co-infected samples. Pavian tool was used to visualize the viral and bacterial species identified. Some samples were visualized with the krona tool to show better all of the viruses identified. LINE 472-474 'A previous study (Lai et al. 2020) showed that reverse transcription polymerase chain reaction (rRT -PCR) could not detect SARS-CoV-2 in two patients co-infected with influenza A virus.' - Why cannot detect? - How often does this happen? It was revised as suggested Some researchers have suggested that inadequate viral specimens, the use of improperly validated assay, timing and methods of collecting specimens, the presence of mutations at the primer binding site, and co-infection with other viruses might be responsible (Arevalo-Rodriguez et al. 2020; Kucirka et al. 2020; Lai et al. 2020; Li et al. 2020). Based on a limited number of observational studies, it was found that the false-negative rate for SARS-CoV-2 RT-PCR was 20% (Lai et al. 2020; Li et al. 2020). Sample SRR11772648 that is provided as supplementary data is not found in Table S1. This sample was deleted from the manuscript because it does not meet the sampling criteria mentioned in this study since it was collected from NEG-1 patients in this study. Only 5 Fastv outputs are provided as supplementary data. The author should make all 68 Fastv outputs available. Since the reviewer 1 recommended not to show the raw reads as it is. I prepared a summary file instead. From the 5 Fastv outputs that are provided as supplementary data, each output appears to be generated using slightly different Fastv parameters. The author should be consistent with how Fastv is applied to all of the 68 datasets. This is to ensure that all of the results are comparable and without biases. Here are the commands that were used to generate the 5 outputs provided. ./fastv -i SRR10971381.fastq -c viral.kc.fasta.gz ./fastv -i SRR11092059.fastq -c viral.kc.fasta.gz -g SARS-CoV-2.genomes.fa -k SARS-CoV-2.kmer.fa ./fastv -i SRR11092062.fastq -c Downloads/microbial.kc.fasta.gz ./fastv -i SRR11092062.fastq -c viral.kc.fasta.gz ./fastv -i ncbi/public/sra/SRR11772648.fastq -c Downloads/microbial.kc.fasta.gz -w 10 I rerun the fastv tool on all samples using microbial k-mer collections, including viral and bacterial k-mers, and I have updated the results. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Insects not only play a significant role in the ecological process of nature but since prehistoric times have also formed a part of the human diet. With a still growing population and skewed demographic structures across most societies of the world, their role as nutrient-rich food has been increasingly advocated by researchers and policymakers globally. In this study, we intended to examine the edible insect diversity and entomophagy attitudes of ethnic people in Manas National Park, a UNESCO Natural World Heritage Site, located in South Asia. The study involved a field investigation through which the pattern of entomophagy and the attitude towards insect-eating was studied. Following this, we examined the edible insect diversity and abundance at different sampling points.</ns0:p><ns0:p>A total of 22 species of edible insects belonging to fifteen families and nine orders were recorded from different habitat types. Out of these 22 species, Orthopterans showed a maximum number of 8 species followed by Hymenoptera (4), Hemiptera (3), Lepidoptera</ns0:p><ns0:p>(2), Blattodea (2) and 1 species each from Coleoptera, Odonata, and Mantodea. Dominance, diversity, and equitability indices were computed along with the relative abundance of the insects concerning four habitat types. Biochemical analyses of the recorded insect species was done to record their nutrient composition to establish their role as crucial nutrient inputs. The economic significance of entomophagy was also observed during the field investigation. To manage insects in the interest of food security, more attention should be given to an environmentally sustainable collection and rearing method, emphasizing their economic, nutritional, and ecological advantages.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Insects are the most diverse and abundant forms of life and constitute a primary component of the total faunal biodiversity on Earth. They play vital roles in an ecosystem that includes soil turning and aeration, dung burial, pest control, pollination, and wildlife nutrition <ns0:ref type='bibr' target='#b1'>(Bernard &amp; Womeni, 2017)</ns0:ref>. Besides providing ecological services, insects are also an important source of protein, fat, carbohydrate, and other nutrients. As per the current scientific literature, there are 1.4 million species of insects worldwide which are an intrinsic part of the Earth's ecosystem <ns0:ref type='bibr' target='#b30'>(Kulshrestha &amp; Jain, 2016)</ns0:ref>. As such, they influence not only with their immense species richness but also with their species variety and their role in energy flow. An interesting dimension to their existence pertains to the fact that they have formed a part of human diets since prehistoric times. Evidence points to at least 113 countries where insects form a part of human diets in one way or the other. This practice of consuming insects as part of the human diet is referred to as entomophagy. Insect-eating or entomophagy is not a traditional or common practice in most countries, except some in South-and South-East Asia, Latin America, and Africa <ns0:ref type='bibr' target='#b52'>(Rumpold &amp; Schluter, 2013)</ns0:ref>, where more than 2,000 insect species are consumed <ns0:ref type='bibr' target='#b27'>(Jongema, 2015)</ns0:ref>. Given the shortfalls of the 'green revolution' and high risk of food insecurity in developing and underdeveloped nations, the use of insects as a potential source of food for the burgeoning human population had been advocated by <ns0:ref type='bibr' target='#b36'>Meyer-Rochow (1975)</ns0:ref>, a suggestion that has been gaining interest among researchers, entrepreneurs and policy makers worldwide ever since. Insect farming is popular in most Asian nations for food, feed, and other purposes <ns0:ref type='bibr' target='#b64'>(Zhang et al., 2008)</ns0:ref>. Weaver ants (Occophylla smaragdina), whose chemical composition and value as a human food item has been assessed by <ns0:ref type='bibr'>Chakravorty et al. (2016)</ns0:ref>, are widespread in the Asia-Pacific region and are found from China south into northern Australia and as far west as India. Though edible insects have commercial value in other countries yet, economic and marketing data on edible insects in Asia and the Pacific is scarce <ns0:ref type='bibr' target='#b28'>(Johnson, 2010)</ns0:ref>. In Thailand, over 150 species from eight insect orders are eaten by its people. Approximately 50 insect species are eaten in the north and about 14 species are eaten by people in southern Thailand <ns0:ref type='bibr' target='#b50'>(Rattanapan, 2000)</ns0:ref>. The insect-eating habits in various regions may depend on the indigenous populations' cultural practices, religion, or geographical area. But insects used as emergency food during natural calamities or other national contingencies as well as for their organoleptic characteristics also <ns0:ref type='bibr' target='#b19'>(Dumont, 1987)</ns0:ref>. In central India too, the people of Pithra village of Simdega district (Jharkhand) collect the red ants (Solenopsis invicta) and their pupae which are found on the trees for consumption <ns0:ref type='bibr'>(Srivastava et al., 2009)</ns0:ref>.</ns0:p><ns0:p>The North-Eastern part of India has diverse ethnic groups that have a unique culture of food intake with insect-eating mostly prevalent amongst rural tribal people of the region which have a long-cultured history. In Arunachal Pradesh, 39 coleopteran insect species are used as indigenous food by approximately 50 ethnic tribes of Arunachal Pradesh <ns0:ref type='bibr' target='#b9'>(Chakravorty et al., 2013)</ns0:ref>. The ethnic Nishi tribe of Arunachal Pradesh consumed more than 50 edible insect species belonging to 45 genera, 38 families, and 11 orders as a part of their diet <ns0:ref type='bibr' target='#b8'>(Chakravorty, 2009)</ns0:ref>. Further, a total of 81 species are eaten in Arunachal Pradesh by two ethnic tribes namely Galo and Nyishi <ns0:ref type='bibr' target='#b10'>(Chakravorty et al., 2011)</ns0:ref>. Odonata were consumed the most followed by Orthoptera, Hemiptera, Hymenoptera, and Coleoptera.</ns0:p><ns0:p>Scientific reports indicate insects to be significant sources of proteins and vitamins and possess viability of providing daily requirements of these nutrients in most developing countries <ns0:ref type='bibr' target='#b6'>(Bukkens, 1997;</ns0:ref><ns0:ref type='bibr' target='#b20'>Elemo et al., 2011)</ns0:ref>. For instance, edible aquatic beetles play an important role in the nutrition and economy of the rural population in Asian, Latin American and African nations <ns0:ref type='bibr' target='#b55'>(Shantibala et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b34'>Macadam &amp; Stockan, 2017)</ns0:ref>. It should be noted that the diversity and abundance of insects in different habitat types have an observed correlation with the entomophagy attitude of a particular region. Therefore, research indicates the importance of exploiting insect diversity effectively through insect farming to avoid global problems associated with dependency on a limited number of insect species as experienced with some food animals and crops <ns0:ref type='bibr' target='#b29'>(Khoury et al., 2014)</ns0:ref>.</ns0:p><ns0:p>In this research article, we have made an effort to study the edible insect diversity of a UNESCO Natural World Heritage Site, located in the Indo-Burmese biodiversity hotspot. Regional entomophagy was studied through a field investigation. Information on the nutrient composition (macro-and micronutrients) of the edible insect species was used to explore the possibility of promoting them as food/feed or as a base for nutritive products. In short, the aims of this study have been to determine the degree to which the ethnic people use insects in their diet and which species they consume. Recording seasonal abundance and availability of edible species as well as evaluating the role that entomophagy could possibly play as a measure of food security in the region, were further aspects of this study.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Study Area</ns0:head><ns0:p>The Manas National Park (MNP), located at 26.6594&#176; N, 91.0011&#176; E, was declared a UNESCO Natural World Heritage Site (WHS) in 1985 (Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>). Renowned for its array of rich, rare, and endangered wildlife not found anywhere else in the world, the faunal diversity of MNP includes the Pygmy Hog, Golden Langur, Hispid Hare, Assam roofed turtle and so on. Located at the Himalayan foothills of India, MNP is shares land territory with Bhutan where it is known as the Royal Manas National Park. The park is composed majorly of grassland and a forest biome. It is covered by the Brahmaputra Valley semi-evergreen forest vegetation along with the Himalayan subtropical broadleaf forests and the Assam Valley semi-evergreen alluvial grassland vegetation. This renders MNP a region of rich and abundant biodiversity. Major trees include the Bombax ceibar, Gmelina arborea, Bauhini purpurea, Syzygium cumin, Aphanamixis polystachya, Oroxylum indcum, etc. The climate is sub-tropical with a warm and humid summer, followed by a cool and dry winter. Temperature ranges from 10 0 C to 32 0 C. The park has more than 58 fringe villages directly or indirectly dependent upon it, distributed across three ranges: Bansibari, Bhuiyaparaa and Panbari. The village Agrang lies at MNP's core while most are located in its buffer zone. Spread over the State of Assam's Barpeta and Bongaigaon districts, the tribal population in its fringe areas predominantly include Bodos and Rabhas among which the practice of insect eating and rearing are widespread <ns0:ref type='bibr' target='#b47'>(Rabha, 2016;</ns0:ref><ns0:ref type='bibr' target='#b15'>Das &amp; Hazarika, 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Insect sampling</ns0:head><ns0:p>Insects were collected using entomological nets, beating tray, water traps, or through digging and handpicking. The local people of the study area helped in the collection process. Insects were usually collected during the early hours of the day (0500-0900 hours). The flying insects were collected via entomological nets at a time when they were active (midmorning/late afternoon). Sweep net was used for collecting grasshoppers and other insects which naturally hid in low grass-or herb-dominated vegetation or in small shrubs. Netting was normally carried out during daytime as it required good vision, thus causing some limitation to its wider applicability as we could not collect nocturnal taxa. In order to catch nocturnal species, we used light traps. Nocturnal arthropods like species of moths and beetles are easily attracted towards artificial light sources. Light traps have therefore been widely used in nocturnal insect sampling for a long time. A high-power CFL bulb was arranged behind a white cloth for trapping nocturnal insects. Generally, a bowl filled with water was placed under the light sources in the evening, after rainfall, to attract termites. The light attracted the reproductive termites which came out for nuptial flights and were trapped in the water or collected by hand from the water to prevent them from escaping. Light trapping was used widely in case of agricultural habitat type and open field habitat type. Beating trays were used to collect insects such as Lepidoptera and Hymenoptera. Shrubs and small trees were sampled through commonly used beating tray sample method. Moreover, the red weaver ants were harvested by plucking the nest from the tree and dropping them in a bucket of water before being sorted out for consumption. The soil dwelling edible insects were collected by digging with the help of spades. Further, insects were hand-picked according to a method described by <ns0:ref type='bibr' target='#b42'>Musundire et al. (2014)</ns0:ref>. Large insects such as grasshoppers and beetles were collected by hand which were caught early in the morning or in evening when they were less mobile due to their low body temperature. The mole cricket and field crickets were dug out of holes. We used the hand-netting technique to collect the aquatic insects along with other local traditional equipment like Jakoi, Saloni, etc. Long handled aquatic net was used to collect insects that live on the water surface. Many adult insects living on the surface were predators, so they were removed from the net using forceps directly into a collection container. The kick-net method which is a process where insects are collected by dislodging insects from the substrate (habitat) was also used. The organisms that were dislodged by the disturbance were collected on the net.</ns0:p><ns0:p>For preservation of specimens, both dry and wet preservation methods were followed. For dry preservation, the specimens were preserved using pins in insect cabinet box and were mainly sun-dried. Soft-bodied insects were preserved using 70% ethyl alcohol. Besides, some hardbodied edible insects were preserved using 2-3% formaldehyde. Some edible insect specimens were also preserved using standard methods <ns0:ref type='bibr' target='#b23'>(Ghosh &amp; Sengupta, 1982)</ns0:ref>. Identification was done later by comparison with other specimens. Some were identified in the Zoological Survey of India, Shillong, India. Sampling was done from 20 chosen sites located in and around MNP. The sampling was done during the period 2018 (June)-2019 (June). The permission for conducting the field study was obtained from Office of the Principal Chief Conservator of Forests (Wildlife) and Chief Wildlife Warden, Government of Assam, India vide No. WL/FG31/ResearchStudyPermission/19th Meeting/2019. The remaining methodology of the study is outlined in Figure <ns0:ref type='figure'>2</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Edible insect density, diversity and abundance</ns0:head><ns0:p>Studying the diversity required us to divide each sampling point into four different habitat types, namely, open field habitat (OFH), forest/backyard forest habitat (FBH), swampy area habitat (SAH), and agricultural field habitat (AFH). The entire sampling area amounted to approximately 842 km 2 . Insects were recorded within quadrates (2m x 2m dimension) established in the habitat type and monitored for four seasons, namely, pre-monsoon (March, April and May), monsoon (June. July, August and September), retreating monsoon (October and November), and winter (December, January and February) <ns0:ref type='bibr'>(Borthakur, 1986</ns0:ref>). An approximate representation is given in Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>. The Shannon-Wiener index (H') for diversity, Simpson index (D) for dominance, and Margalef index for species richness in the four selected habitat types were also computed. Order-wise relative abundance and species-wise abundance in the different habitats were also computed. The descriptions and mathematical expressions are outlined below. The indices were estimated using PAST (v.3.26) <ns0:ref type='bibr' target='#b25'>(Hammer et al., 2019)</ns0:ref> and SPSS (v.23). Shannon-Weiner index (H') determines the diversity of insect species in a particular habitat type. The higher the H' value, the greater is the diversity. Expression (i) gives the formula. H' = -&#8721; p i ln p i &#8230;&#8230; (i) Where p i = proportion of individuals found in i th species Simpson's index (D) defines the probability of drawing any two individuals at random from a very large community of the same species. If D increases, we can say that diversity has decreased. This index, defined by expression (ii), accounts for both aspects of diversity, i.e., richness and evenness.</ns0:p><ns0:formula xml:id='formula_0'>D = &#8721; &#8230;&#8230; (ii) ( &#8721;&#119899; &#119894; [&#119899; &#119894; -1] &#119873; [&#119873; -1] )</ns0:formula><ns0:p>Where, n i = individuals in i th species, N = total number of individuals Margalef's index (R) gives a precise idea about a species' richness. It attempts to compensate for the effects of sampling by taking a ratio of species richness by the total number of individuals in a sample, given in expression (iii).</ns0:p></ns0:div> <ns0:div><ns0:head>R = (S-1) / lnN</ns0:head><ns0:p>Where, S = total species in a community, N = total number of individuals in that community.</ns0:p></ns0:div> <ns0:div><ns0:head>Entomophagy study</ns0:head><ns0:p>Understanding the entomophagy attitudes and distribution among the tribal population near MNP required conducting a survey. Methods included interactions with the villagers through questionnaires, field surveys, and a market survey. The villages were selected randomly and were surveyed once per season for the whole year. Questions were asked to a mixed group of ethnic people which included individuals from all sections of the society. The market survey helped record the economic importance of these insects for the local economy. Questions pertained to the number of insects sold per week/month, their market prices, and how popular were the insects in ethnic cuisine. Overall, the questionnaire survey included 2672 respondents from 30 villages. Written consent was obtained from the respondents during the field interviews.</ns0:p></ns0:div> <ns0:div><ns0:head>Biochemical analysis</ns0:head><ns0:p>Studying the importance of edible insects in food security required us to conduct their biochemical analysis. The analysis was for macronutrients and micronutrients in the laboratory of the Institute of Advanced Study in Science &amp; Technology (IASST), Guwahati.</ns0:p><ns0:p>The protein content of the edible insects was estimated following the method of Lowry et al., (1951) using bovine serum albumin as a standard protein. In a series of test tubes, 0.10 -1.0 ml of the standard BSA (bovine serum albumin) was taken and made up to 1 ml by adding distilled water. Next, 1.5 ml of protein reagent was added to the above solution and allowed to stand for 10 minutes at room temperature. Then, 0.5 ml of 10% diluted Folin-Ciocalteau reagent was added and incubated for 20 min in room temperature at dark to develop colour. The blue colour developed was read at 660 nm using spectrophotometer against a blank solution prepared by replacing BSA with water. A standard curve was prepared by putting the BSA concentrations in x-ordinate against the ODs in the y-ordinate. For tissue (insect) sample, 0.1 ml of insect tissue homogenate was added with distilled water to make 1 ml total volume. After that 1.5 ml protein reagent, 0.5 ml Folio reagent was added and incubated for 20 minutes. The colour developed was observed at 660 nm. The values of absorbance were noted and the content of tissue protein was calculated from the standard graph of BSA. Estimation of carbohydrate was done by following the anthrone method <ns0:ref type='bibr' target='#b53'>(Sadasivam and Manickam, 2008)</ns0:ref>. In a series of cleaned test tubes 0.10, 0.50, 1.00, 2.50, 3.00, 4.00, 5.00, 7.50; 10.00 mg /ml of standard glucose solutions were taken. Next, 5 ml anthrone solution was added to the above solution. Similarly, for insects, 1 ml samples supernatant was taken in a clean test tube. Next, 5 ml anthrone solution was added and then incubated for 15 min at 90&#176;C. After the incubation was over, the colour developed was read at 625 nm in a spectrophotometer against a blank solution, containing all the chemicals except the sample. The absorbance values were noted and the concentrations of carbohydrate present in the insects were calculated from the standard graph of glucose.</ns0:p><ns0:p>The total lipid was estimated using chloroform methanol method described by <ns0:ref type='bibr' target='#b21'>Folch et al. (1957)</ns0:ref>. To a known weight of dried, powdered sample taken in a test tube, 5 ml of chloroform-50 methanol (2:1) mixture was added and incubated overnight at room temperature after closing the mouth of the test tube with aluminium foil. After incubation, the mixture was filtered using What-man No.1 filter paper. The filtrate was collected in a pre-weighed 10 ml beaker which was kept on a hot plate. The beaker with the residue at the bottom was weighed after the chloroform methanol gets evaporated and the weight of the empty beaker was subtracted from this to know the weight of the lipid present in the sample. The result was been expressed as mg of lipids per 100 mg of dry tissue material similar to protein and carbohydrate.</ns0:p><ns0:p>The mineral elements were determined by atomic absorption spectroscopy (AAS). All the value of the micronutrients of the sample was recorded in ppm (parts per million) and calculated. The resultant values in AAS were converted into mg/100 g sample using expression (iv). &#181;g/gm of sample = (AAS reading x volume taken)/wt. of sample &#8230;. (iv) (1 ppm = 0.001 mg/g)</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref> shows the order-wise number of edible insects found in the study area. In MNP, the order Orthopteran recorded the maximum number with 8 species, followed by Hymenoptera with 4 species. The order Hemiptera was found to have 3 species and Lepidoptera with 2 species. The order Coleoptera, Isoptera, Blattodea, Mantodea, and Odonata accounted for 1 from each species and family. A total of 9,213 edible insects were recorded from AFH, 1455 in FBH, 3435 in OFH and 6497 individuals in SAH, during the field observation. No common abundant species was found in a single habitat. Most of the insects were found in two or three habitats during the study period.</ns0:p><ns0:p>Table <ns0:ref type='table'>2</ns0:ref> showcases the types of edible insects consumed by the ethnic people. In this table, the local and common name, the scientific name with their taxonomy, and their seasonal availability, edible parts, and mode of consumption are tabulated. Seasonal availability was maximum during June to September, gradually reducing towards the winter season. Species of the order Orthoptera were most abundant in May to September, whereas, Coleopterans were usually available from April to September. Insects belonging to the Hemiptera and Hymenoptera were found to be restricted to the period lasting from April to October, whereas, Mantodea were available from June to October. Some edible insects like Hydrophilus olivaceus, Lethocerus indicus, Periplaneta americana and Gryllotalpa africana were found to be available throughout the year, but in the winter, they were less abundant than during the pre-monsoon and monsoon season.</ns0:p><ns0:p>Simpson index (D) for dominance, Shannon-Wiener index (H') for diversity, and Margalef index for evenness/equitability were calculated in the four selected habitats (Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>). Further, species abundance was found to be the highest in Chondracris rosea with 18.64, followed by Gryllotalpa africana with 8.50 in AFH. In FBH, the highest species abundance was found in Heiroglyphus banian with 8.91, followed by Polistis olivaceus with 5.20. In OFH, Gryllus bimaculatus was the highest abundant species with 5.1, followed by Lethocerus indicus with 3.17. Table <ns0:ref type='table' target='#tab_3'>4</ns0:ref> shows the relative abundance of the edible species in selected habitats.</ns0:p><ns0:p>Chondracris rosea has the highest relative abundance (11.50%) followed by Choroedocus robustus (8.92%), the least relative abundant insect species includes Laccotrephes ruber (0.42%).</ns0:p><ns0:p>As regards the relative abundance of edible insect species, order Orthoptera has the highest relative abundance (56.30%) followed by Coleoptera (8.02%) and order Odonata has the least relative abundance (0.66%) (Table <ns0:ref type='table' target='#tab_3'>4</ns0:ref>). Seasonal variation in abundance of edible insects (Figure <ns0:ref type='figure'>4</ns0:ref>) shows Mantis religiosa (466) to be the most abundant species (344) found in monsoon season followed by Periplaneta americana (798), and the least abundant species is Mecopoda elongate <ns0:ref type='bibr' target='#b14'>(13)</ns0:ref>. In pre-monsoon, Anthera assama (443) has the highest presence and Acheta domestica (3) has the lowest. Choroedocus robustus has availability of 420 individuals during retreating monsoon compared to 10 individuals of Gryllus bimuculatus. Finally. In winter, Vespa affinis has the highest availability (112) compared to 12 individuals of Heiroglyphus banian. Highest insect species was observed during monsoon season (4808) followed by pre-monsoon (2785), retreating monsoon (2106), and winter (774).</ns0:p><ns0:p>Further, the proportion of ethnic communities practicing entomophagy in MNP has been graphically represented in Figure <ns0:ref type='figure' target='#fig_4'>5</ns0:ref>. We categorised the age-groups of consumers, who considered the insect-eating habit favourable, into four groups, namely, less than 60 years, between 40-60 years, between 20-40 years and greater than 20 years (Figure <ns0:ref type='figure'>6</ns0:ref>). Consumers in the 20-40 group responded highly favourably while those in less than 20 years group responded less favourably owing to different variations of entomophobia. There are various reasons for eating insects which were found among the different ethnic groups during the questionnaire survey (Figure <ns0:ref type='figure'>7</ns0:ref>). The different modes of insect consumption have been presented in Figure <ns0:ref type='figure' target='#fig_6'>8</ns0:ref>. Finally, Table <ns0:ref type='table' target='#tab_4'>5</ns0:ref> showcases the nutritional composition of all insect species recorded in the study.</ns0:p><ns0:p>The highest total nutritional composition can be seen in termites (Microtermes obesi). Water beetle (Diplonychus rusticus) contains the maximum protein. Lower quantities of protein can be seen in rock bee (Apis dorsata), field crickets (Gryllus bimaculatus), and termites. Almost all the insect species are high in Omega-3 and Omega-6 content, with a good amount of essential amino acid and lipid content. Magnesium and carbohydrate contents are minimal while calcium is moderately present. The species-wise nutrient composition in colour-codes is represented in Figure <ns0:ref type='figure'>9</ns0:ref> (content-specific) and Figure <ns0:ref type='figure' target='#fig_1'>10</ns0:ref> (species-specific).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head>Edible insect diversity and abundance</ns0:head><ns0:p>As part of this study, we find that species of the order Orthoptera are popular among the ethnic people for consumption purposes. The edible species majorly include both short and long-horned grasshoppers (Eupreponotus inflatus, Choroedocus robustus, Chondracris rosea, Mecopoda elongate and Heiroglyphus banian), field crickets (Gryllus bimculatus), house crickets (Acheta domestica) and mole crickets (Gryllotalpa Africana). Other species include potter wasp (Vespa affinis) and paper wasp (Polistis olivaceus), Indian honey bee (Apis indica) and rock bee (Apis dorsata), giant water bug (Lethocerus indicus) and so on. The ethnic (tribal) communities consuming these insects included mainly of the Adivashis, followed by the Bodo, Rabha, and Sarania communities. A section of the non-tribal population also consumed insects as part of their diets. Species diversity, richness, and evenness gives an idea about the variety and diversity of species in the study sites. The most commonly used dominance and diversity indices in ecology are the Simpson index and the Shannon-Wiener index. Simpson index is used to assess the dominance but fails to provide an idea about species richness. Shannon-Wiener index is expected to determine both diversity characteristics (evenness and richness) but does not provide any information on rare species which, however, are very important in studies of biodiversity.</ns0:p><ns0:p>Results show that the species dominance is highest in FBH (0.3871), followed by SAH (0.2423), OFH (0.1467), and AFH (0.1148). On the other hand, species diversity, as per H', was highest in AFH (2.822), OFH (2.392), FBH (2.153) and SAH (1.329). This establishes the fact that as insect diversity decreases, their dominance should increase. In MNP, this can be noticed for the forest habitat. Further, this result is corroborated by the Margalef index which is found to be highest for AFH (2.936), OFH (2.294), FBH (1.836), and SAH (0.653).</ns0:p><ns0:p>Notably, forest habitats are the prime source of edible insects for local people. This adverse finding in the case of FBH may be attributed to various reasons. Decreasing forest cover, changes in vegetation type, adverse climatic conditions, or indiscriminate collection and consumption of edible insect. These directly affect the insect diversity and rejuvenation of insect species. In the case of MNP, high temperatures, inadequate rainfall, and vegetation cover may also have influenced the population density of these edible insects. Notably, the overall climate of Assam has warmed by over 0.5 0 C for the past decade which is expected to rise up to 2.2 0 C by 2050.</ns0:p><ns0:p>It should be noted that Shannon-Weiner and Simpson diversities increase as richness increases for a given pattern of evenness, and increase as evenness increases for a given richness, but they do not always follow the same trend. Simpson diversity is less susceptible to richness and sensitive to evenness than Shannon index which, in turn, is more receptive to evenness. At the other extreme, the Berger-Parker index, depends entirely on evenness-it is simply the inverse of the proportion of individuals in the community that belongs to the single most common species, while the other indices (Margalef) are dependent on the number of species. Apart from the diversity and distribution patterns for insect taxa, interactions between insect groupings and plant groups are another important topic requiring urgent research attention. This is because plants provide key habitat parameters for many insect species ranging from shelter to breeding sites. This has not been covered under this study and could be pointed out as its limitation.</ns0:p><ns0:p>Our analysis of seasonal diversity of edible insect species shows that the diversity of the edible insects was greater during monsoon and pre-monsoon </ns0:p></ns0:div> <ns0:div><ns0:head>Entomophagy, food security, and its economic implications</ns0:head><ns0:p>The field investigation revealed that most of the respondents found insects to be tasty and delicious (59%), while a section found them to be an inexpensive source of food (17.1%). Traditional medicinal food is also one of the reasons why edible insects are collected (Meyer-Rochow, 2017). This indicates the substantial preference of insects in the food habits of people and underscores their importance in the allocation of household costs and sustaining food security. This can be corroborated with the findings of <ns0:ref type='bibr' target='#b41'>Mozhui et al. (2017)</ns0:ref> for Nagaland, where the ethnic people considered insects as a regular food source, rather than an emergency food item. The local people favoured eating insects mostly by frying, roasting, or smoked. This emphasises the wide variety of ways through which insects may be consumed. However, a low percentage of respondents claimed them to be easily available food as collecting them is rather difficult compared to conventional livestock. This calls for the development of an insect farming industry as well. Besides, the nutritional significance of edible insects has been well established by current scientific literature. This is further corroborated by the results of this study. Also, it is observed that nutrients vary widely across insect species wherein some are rich in protein and lipids while others are rich in mineral content. <ns0:ref type='bibr' target='#b11'>Chen et al. (2009)</ns0:ref> note that edible insects are rich in protein and fat, but sometimes may lack carbohydrate content. However, insects like bees, honeypot ants, etc., are very rich in carbohydrates. Our study verifies this fact as we can see from Figure <ns0:ref type='figure'>7</ns0:ref> that the insects are rich in protein but have minimal carbohydrates. Notably, they have high omega-3, omega-6, and essential amino-acid content. Besides, <ns0:ref type='bibr' target='#b12'>Collavo et al. (2005)</ns0:ref> note that the presence of high essential amino acids is a major reason for insects having high-quality protein. This is validated by our study where most of the recorded insects show high protein and amino acid characteristics. These insects also have good calcium content and a moderate presence of magnesium.</ns0:p><ns0:p>The biochemical analysis suggests that the edible insects should potentially be able to supplement the diet obtained from livestock. This is necessitated by the fact that the majority of the population near MNP belong to low-or lower-middle-income category people. Their demography is skewed towards ethnic backgrounds and hence, the economy is highly underdeveloped. Rearing livestock and maintaining animal husbandry practices, require a substantial amount of money. The piggery sector is robust in this area. Practicing this requires large amounts of land and also involves substantial capital. However, the nutritional benefits gained from it are not enough to compensate for the effort. Also, insects generally meet the WHO recommendation for amino acid content with nymphs being their most abundant source (Tang et al., 2019). Coleoptera has a higher amount of protein than most livestock. More importantly, edible insects bear many non-health related benefits related to environmental and financial costs than livestock.</ns0:p><ns0:p>On the other hand, it is important to note that many edible insects have higher energy, sodium, and saturated fat content than typical livestock <ns0:ref type='bibr' target='#b45'>(Payne et al., 2016;</ns0:ref><ns0:ref type='bibr'>Tang et al., 2019)</ns0:ref>. This diminishes their worth as alternative nutrient sources to fight nutrition-related diseases. This is because the saturated fat content of edible insects is not recommended for people with heart disease risk, obesity, or metabolism issues. Further, some beetle or butterfly species produce dangerous toxins that are harmful to human health. Such species must be identified before being consumed as food <ns0:ref type='bibr' target='#b3'>(Blum, 1994)</ns0:ref>. However, insects have very high micronutrient content which can be extracted or consumed at a third of the cost than other food products.</ns0:p><ns0:p>MNP is also a highly flood-ravaged area with untimely floods occurring during the sowing period. Floods in 2019 affected over a million people of Assam with a majority from the Baksa District (where MNP is located) and the adjacent district of Barpeta. This frequently uproots livelihood of the local people rendering them vulnerable to high food insecurity. It should be noted that these ethnic people otherwise have decent livestock and animal husbandry resources.</ns0:p><ns0:p>With floods, they tend to lose livestock in a large-scale manner. At this juncture, edible insects can play a significant role in maintaining the nutritional content of their diet intact.</ns0:p><ns0:p>Among the edible insects in the study area, aquatic insects (water beetles) are quite favourable groups among the consumers due to their taste. Besides food and feed of humans and other animals, the predatory species of Coleoptera such as ladybird beetles are considered important biological control agents of aphids and scale insects (Arya &amp; Verma, 2020). In our study, it was observed that water beetles are rich in protein content and have a considerable amount of lipid and carbohydrate. There is also a positive correlation between protein and lipid content. This establishes the fact that when the protein content in any insect increases then the lipid content in it also increases. Also, it can be inferred that the insects are rich in protein and carbohydrate contents together. Hydrophilus olivaceus (water scavenger) have a high quantity of protein, a good quantity of lipid and a considerable amount of carbohydrate compared to Phyllophaga spp. (June beetle), another commonly consumed Coleoptera. The protein content of adult H. parallela was approximately 24%, which is higher than the 16% protein content of silkworm <ns0:ref type='bibr' target='#b31'>(Longvah et al., 2011)</ns0:ref>. On a dry weight (DW) basis, H. parallela contained 70.57 g of protein/100 g, which is comparable to the protein content of beef and pork (40-75 g of protein/100 g DW; <ns0:ref type='bibr' target='#b6'>Bukkens, 1997)</ns0:ref>.</ns0:p><ns0:p>Animal protein is superior to plant; therefore, the best protein supplements should include some animal protein. Thus, insects may provide for good quality protein ingredients to produce a high standard protein supplement for the food industry <ns0:ref type='bibr' target='#b59'>(Ssepuuya et al., 2017)</ns0:ref>. It was also found that the lipid content of larvae (37.87%) was higher than the soybean (14.60%). From the energy point of view, lipids are important because one gram of lipid provides more than 9 kcal of energy when oxidized in the body. Lipids are structural components of all tissues and indispensable in cell membranes structure and cell organelles <ns0:ref type='bibr' target='#b18'>(Drin, 2014)</ns0:ref>. The fat content of pupae and larvae of edible Coleoptera is higher than that of the adult insect. These results coupled with the significant role played by edible insects in the local food habits make it undeniable that the desirability of food security in their context is valid as they can be considered as viable sources of macro-and micro-nutrients for human beings.</ns0:p><ns0:p>Edible insects such as beetles have been a rich source of proteins and also other nutrients for a long time and have been preferred over traditional livestock by several communities all over the world <ns0:ref type='bibr' target='#b32'>(Losey et al., 2006)</ns0:ref>. For instance, indigenous communities of Mexico are involved in buying and selling edible insects, which are also processed and sold in urban markets. Insects have low-fat content and as such, there has been a high worldwide demand for edible insects. Additionally, aquatic insects are commonly exported from South Asian nations to the United States which are prepared and served in high-end eateries. The estimated size of this market was approximately USD 40 million in 2015. Moreover, in the Lao PDR, insects can be found in markets as ready-to-eat snacks or fried with lime leaves (van Huis, 2003). Concerning agriculture, beetles have been found to contribute more than a billion dollars in environmental and economic benefits globally. This comes from the fact that they recycle cattle manure, thereby, improving pasture growth, yielding high agricultural benefits, and thus, augmenting the livelihood of agriculturalists. In the context of MNP, a gap in the literature has been observed wherein comprehensive studies on beetles' economic benefits haven't been witnessed.</ns0:p><ns0:p>Rearing insects have high environmental benefits with respect to food and feed. They also have tremendous scope in terms of organic farming while helping to reduce environmental contamination, as they emit lesser greenhouse gases and ammonia, compared to other livestock <ns0:ref type='bibr' target='#b13'>(Dangles &amp; Casas, 2019)</ns0:ref>. Given the inclination of Bodos and other tribes in eating insects and rearing them to an extent, economic policies must target rearing practices of insects, rather than solely focussing on animal husbandry. Therefore, several strategies could be employed that can help in efficiently and sustainably making use of such natural biodiversity in augmenting the societal income and its food security, following learnings of other countries like South Korea (Meyer-Rochow et al., 2019).</ns0:p><ns0:p>Our study shows that edible insects are of considerable nutritional value and expanding their acceptability as human food can be expected to improve the nutritional status of people and possible reduction of their costs. With wide insect diversity, the nutritional status of people also gets widened while costs get reduced <ns0:ref type='bibr' target='#b16'>(Dickie et al., 2019)</ns0:ref>. For instance, mealworms consist of six fatty acids and unsaturated omega-3 components that are equivalent to those found in fish, and also higher than those found in pigs and cattle <ns0:ref type='bibr' target='#b48'>(Raheem et al., 2019)</ns0:ref>. Since nutrition has been one of the core components in the evolution of economic policies as well as family welfare, it is necessary that the insect eating habits of ethnic people in the study area must be widely augmented while focussing on the preservation of its insect diversity.</ns0:p><ns0:p>Certain insects like silkworms, honey bees, and as of late bumble bees and wasps have been traditionally domesticated ones since they have high economic value. As such, insect farming is much needed in the study area. This concept is widely prevalent in Korea, Thailand, Vietnam, and Laos PDR. Vertical farming is another technique that can immensely strengthen local economics and help in the exploitation of new protein sources <ns0:ref type='bibr' target='#b57'>(Specht et al., 2019)</ns0:ref>. Family-run enterprises are mostly involved in this business along with other firms that have commercialised insects as not only food but also sources of protein and other health supplements.</ns0:p><ns0:p>Insect diversity can be critical for livelihood development since, in some developing countries, the poorest members of a society are engaged in gathering and rearing of mini-livestock <ns0:ref type='bibr' target='#b35'>(Mason et al., 2018)</ns0:ref>. Industrial-scale interventions can also augment their livelihoods that have now been observed in the case of silkworms of Assam. Given the relatively process of rearing, accessibility, and transportation of insects, the people of Study area can immensely benefit if steps to set up an Insect Marketing Hub, assisted by an Insect Development Authority is set up. The hub should be created following a hub-and-spoke model that would not only pertain to processing and distribution matters but also training and R&amp;D issues.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In this study, we made an effort to record the edible insect diversity and abundance, characteristics, and attitudes of the ethnic communities involved in entomophagy that are residing in the fringes of the Manas National Park, a Natural World Heritage Site. A total of 22 species of edible insects belonging to fifteen families and nine orders were recorded from different habitat types. Out of these 22 species, we recorded a maximum number of 8 Orthopteran species followed by Hymenoptera (4), Hemiptera (3), Lepidoptera (2), Blattodea (2) and 1 species each from Coleoptera, Odonata, and Mantodea. Diversity indices such as Shannon-Wiener, Simpson dominance, and Margalef indices were computed. Results of the study show that edible insect diversity has significantly decreased in the forest habitat. For a region highly dominated by entomophagy, such decreasing diversity raises a red flag. The field investigation showed that edible insects are highly sought after by local people. We identified the entomophagy practicing population mainly belonging to the Adivashi, Bodo, Rabha, and Sarania communities. They consume insects via different modes of preparation, such as fried, smoked, raw, etc. Moreover, people preferring entomophagy mainly belong to the youth (20-40 year) population. Therefore, our results conclude that MNP is a place vibrant with a high diversity, and abundance of edible insects. Further, it was found that these insects are good sources of protein, lipid, essential amino acids, omega-3, and omega-6 content, besides calcium, magnesium, and carbohydrate content. This validates edible insects as a future alternative source for an adequately nutrient-rich diet, proving to be majorly desirable in the context of food security. Preservation of such diversity necessitates the adoption of efficient and unique conservation techniques along with appropriate policymaking which can go a long way in augmenting greater insect diversity and also the food security of people in South Asia. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 2</ns0:note><ns0:note type='other'>Figure 4</ns0:note><ns0:p>Seasonal availability of insects.</ns0:p><ns0:p>Blue section indicates pre-monsoon availability of insect; red section indcates monsoon; yellow indicates retreating monsoon and green section indicates availability in winter. Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 6</ns0:note><ns0:p>Age group of consumers favouring entomophagy.</ns0:p><ns0:note type='other'>Figure 7</ns0:note><ns0:p>Different reasons for practicing entomophagy. Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 9</ns0:note><ns0:p>Combined nutrient composition (content specific). Manuscript to be reviewed Nutrient composition of edible insects.</ns0:p><ns0:p>Each data point displays the nutrient composition of different edible insects with respect to the nutrient-types detailed in the table.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:49115:1:1:NEW 19 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Further, a large number of respondents in the 20-40 years and 40-60 years age bracket favoured eating insects due to the various reasons as in Figure 6. Entomophagy, as such, is highly popular among the youth population. This corroborates the observation of Vaccaro et al. (2019) but does not agree with the study by Ghosh et al. (2020), carried out in Ethiopia.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 Study</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Methodology.PeerJ reviewing PDF | (2020:05:49115:1:1:NEW 19 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3 Representation</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 5 Entomophagy</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>The coloured sections of the pie display the different reasons why insect-eating (entomophagy) is practiced by the local people.PeerJ reviewing PDF | (2020:05:49115:1:1:NEW 19 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 8 Different</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,229.87,525.00,324.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='27,42.52,178.87,525.00,305.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='32,42.52,229.87,525.00,231.75' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head /><ns0:label /><ns0:figDesc>season, moderate in the retreating monsoon season, and lowest in the winter season. As per the survey report, it was found that the abundance of insects found today is much lower than what it was earlier. A decreasing pattern is corroborated by Doley &amp; Kalita (2011), Narzary &amp; Sarmah (2015), Das et al. (2012), with slight changes. This establishes that seasonal availability of edible insects is declining with time while remaining constant at some points. This calls for urgent ecosystem restoration to sustain the distribution pattern and abundance of edible insects. Anthropogenic disturbances and deforestation are seen rampant in the fringes of MNP. Ground-level evidence glaringly shows that villagers are converting forest lands into agricultural fields. This is an outcome of the burgeoning population of Assam where the human population density is 398 persons per km2 </ns0:figDesc><ns0:table><ns0:row><ns0:cell>highest</ns0:cell></ns0:row><ns0:row><ns0:cell>constituting about 33.33%, followed by Hymenoptera with 20%, Coleoptera with 16.66%,</ns0:cell></ns0:row><ns0:row><ns0:cell>Hemiptera with 10%, Lepidoptera with 6.66%, Isoptera with 3.33%, Odonata with 3.33%,</ns0:cell></ns0:row><ns0:row><ns0:cell>Blattodea with 3.33% and Mantodea also with 3.33%. The maximum types of species consumed</ns0:cell></ns0:row><ns0:row><ns0:cell>in the study area is from order Orthoptera which comprise 8 species of which 7 are short-horned</ns0:cell></ns0:row><ns0:row><ns0:cell>and long-horned grasshoppers. This is corroborated by Ronghang &amp; Ahmed (2010) and Das &amp;</ns0:cell></ns0:row><ns0:row><ns0:cell>Hazarika (2019).</ns0:cell></ns0:row></ns0:table><ns0:note>which is way above the global density of 14.7 persons per km2 . Such anthropogenic pressure<ns0:ref type='bibr' target='#b40'>(Morris, 2010</ns0:ref>) is bound to destroy species composition, community structure, and insect diversity (Bolvin et al., 2016). In the regional context, a study of the diversity of insects consumed by the people in Dhemaji District of Assam revealed that a total of 14 species of insects were used as food<ns0:ref type='bibr' target='#b17'>(Doley &amp; Kalita, 2011)</ns0:ref>. 40 species of edible insects were recorded in Karbi Anglong District of Assam<ns0:ref type='bibr' target='#b51'>(Ronghang &amp; Ahmed, 2010)</ns0:ref>, further corroborated by<ns0:ref type='bibr' target='#b26'>Hanse &amp; Teron (2012)</ns0:ref>. Another study involving the ethnic community of the Bodos, recorded 25 species of local insects, belonging to eight orders and fourteen families which are consumed as food(Narzary &amp; Sarmah, 2015). In this study, out of 22 edible species, the consumption of Orthopteran species was the</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Order-wise number of edible insects.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>A; Carbohydrate content</ns0:cell></ns0:row><ns0:row><ns0:cell>B; Magnesium content</ns0:cell></ns0:row><ns0:row><ns0:cell>C; Essential amino acid content</ns0:cell></ns0:row><ns0:row><ns0:cell>D; Lipid content</ns0:cell></ns0:row><ns0:row><ns0:cell>E; Omega-3 content</ns0:cell></ns0:row><ns0:row><ns0:cell>F; Omega-6 content</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Diversity indices (habitat type) of edible insects recovered from four selected habitats.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>AFH</ns0:cell><ns0:cell>FBH</ns0:cell><ns0:cell>SAH</ns0:cell><ns0:cell>OFH</ns0:cell></ns0:row><ns0:row><ns0:cell>Species Richness</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>23</ns0:cell></ns0:row><ns0:row><ns0:cell>Total individuals</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>encountered</ns0:cell><ns0:cell>9213</ns0:cell><ns0:cell>1455</ns0:cell><ns0:cell>3435</ns0:cell><ns0:cell>6497</ns0:cell></ns0:row><ns0:row><ns0:cell>Simpson</ns0:cell><ns0:cell>0.1148</ns0:cell><ns0:cell>0.3871</ns0:cell><ns0:cell>0.2423</ns0:cell><ns0:cell>0.1467</ns0:cell></ns0:row><ns0:row><ns0:cell>Shannon-Wiener</ns0:cell><ns0:cell>2.822</ns0:cell><ns0:cell>2.153</ns0:cell><ns0:cell>1.329</ns0:cell><ns0:cell>2.392</ns0:cell></ns0:row><ns0:row><ns0:cell>Margalef</ns0:cell><ns0:cell>2.936</ns0:cell><ns0:cell>1.836</ns0:cell><ns0:cell>0.653</ns0:cell><ns0:cell>2.294</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 4 :</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Abundance of edible insect in three different terrestrial habitats.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Order</ns0:cell><ns0:cell>Species</ns0:cell><ns0:cell>AFH</ns0:cell><ns0:cell>Quadrate</ns0:cell><ns0:cell cols='3'>Abundance FBH Quadrate</ns0:cell><ns0:cell cols='2'>Abundance OFH</ns0:cell><ns0:cell>Quadrate</ns0:cell><ns0:cell>Abundance</ns0:cell><ns0:cell>Relative</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Occurrence</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Occurrence</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Occurrence</ns0:cell><ns0:cell /><ns0:cell>abundance</ns0:cell></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>Eupreponotus</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>5.82</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>inflatus</ns0:cell><ns0:cell>44</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>1.63</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0.00</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0.00</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>Mecopoda</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>7.45</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>elongate</ns0:cell><ns0:cell>212</ns0:cell><ns0:cell>128</ns0:cell><ns0:cell>1.66</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>1.33</ns0:cell><ns0:cell>384</ns0:cell><ns0:cell>152</ns0:cell><ns0:cell>2.53</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>Choroedocus</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>8.92</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>robustus</ns0:cell><ns0:cell>67</ns0:cell><ns0:cell>39</ns0:cell><ns0:cell>1.72</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>2.22</ns0:cell><ns0:cell>41</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>3.73</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>Heiroglyphus</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>8.75</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>banian</ns0:cell><ns0:cell>31</ns0:cell><ns0:cell>21</ns0:cell><ns0:cell>1.48</ns0:cell><ns0:cell>78</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell>6.00</ns0:cell><ns0:cell>72</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>3.00</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>Gryllus</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>4.22</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>bimculatus</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>1.33</ns0:cell><ns0:cell>44</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>4.00</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>1.25</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>Acheta domestica</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>1.38</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>1.67</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0.00</ns0:cell><ns0:cell>7.96</ns0:cell></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>Gryllotalpa</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>8.83</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>africana</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>1.41</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>1.50</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>2.00</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>Chondracris</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>4.35</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>rosea</ns0:cell><ns0:cell>58</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>2.52</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>2.00</ns0:cell><ns0:cell>25</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>4.17</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Hymenoptera</ns0:cell><ns0:cell>Vespa affinis</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0.00</ns0:cell><ns0:cell>110</ns0:cell><ns0:cell>76</ns0:cell><ns0:cell>1.45</ns0:cell><ns0:cell>28</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>3.50</ns0:cell><ns0:cell>0.94</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Hymenoptera Polistis olivaceus</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>6.50</ns0:cell><ns0:cell>87</ns0:cell><ns0:cell>49</ns0:cell><ns0:cell>1.78</ns0:cell><ns0:cell>35</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell>2.69</ns0:cell><ns0:cell>0.92</ns0:cell></ns0:row><ns0:row><ns0:cell>Hymenoptera</ns0:cell><ns0:cell>Apis indica</ns0:cell><ns0:cell>43</ns0:cell><ns0:cell>36</ns0:cell><ns0:cell>1.19</ns0:cell><ns0:cell>189</ns0:cell><ns0:cell>49</ns0:cell><ns0:cell>3.86</ns0:cell><ns0:cell>44</ns0:cell><ns0:cell>42</ns0:cell><ns0:cell>1.05</ns0:cell><ns0:cell>3.89</ns0:cell></ns0:row><ns0:row><ns0:cell>Hymenoptera</ns0:cell><ns0:cell>Apis dorsata</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>4.00</ns0:cell><ns0:cell>178</ns0:cell><ns0:cell>72</ns0:cell><ns0:cell>2.47</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>3.00</ns0:cell><ns0:cell>2.27</ns0:cell></ns0:row><ns0:row><ns0:cell>Hemiptera</ns0:cell><ns0:cell>Lethocerus</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.71</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>indicus</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>2.00</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>1.00</ns0:cell><ns0:cell>88</ns0:cell><ns0:cell>46</ns0:cell><ns0:cell>1.91</ns0:cell><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49115:1:1:NEW 19 Jul 2020) Manuscript to be reviewed PeerJ reviewing PDF | (2020:05:49115:1:1:NEW 19 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>1 Table 5 :</ns0:head><ns0:label>15</ns0:label><ns0:figDesc>Nutrient composition of edible insects.Common NameProtein Lipid Carbohydrate Calcium Magnesium Essential amino acid Omega-3 Omega-6</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>Rhinoceros Beetle</ns0:cell><ns0:cell>0.25431 0.02228 0.03567</ns0:cell><ns0:cell>0.04617 0.05547</ns0:cell><ns0:cell>0.21402</ns0:cell><ns0:cell>0.18132 0.185</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Indian honey bee</ns0:cell><ns0:cell>0.19842 0.06833 0.076</ns0:cell><ns0:cell>0.09222 0.0958</ns0:cell><ns0:cell>0.13621</ns0:cell><ns0:cell>0.17431 0.16283</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Giant Water Bugs Dragonfly (large)</ns0:cell><ns0:cell>0.23412 0.133 0.059 0.14536 0.0163 0.04535</ns0:cell><ns0:cell>0.15689 0.0788 0.04019 0.06515</ns0:cell><ns0:cell>0.15609 0.1143</ns0:cell><ns0:cell>0.27334 0.18904 0.2213 0.22311</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Termites Crickets</ns0:cell><ns0:cell>0.13859 0.18633 0.06525 0.13209 0.06833 0.0212</ns0:cell><ns0:cell>0.21022 0.08505 0.09222 0.041</ns0:cell><ns0:cell>0.10323 0.19631</ns0:cell><ns0:cell>0.2653 0.2721 0.21041 0.22577</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Mole Crickets Praying Mantis</ns0:cell><ns0:cell>0.17823 0.065 0.078 0.15672 0.035 0.06541</ns0:cell><ns0:cell>0.08889 0.0978 0.05889 0.08521</ns0:cell><ns0:cell>0.23102 0.18231</ns0:cell><ns0:cell>0.24101 0.24781 0.06812 0.16102</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>House Crickets Rock bee</ns0:cell><ns0:cell>0.20587 0.069 0.043 0.10602 0.06833 0.09102</ns0:cell><ns0:cell>0.09289 0.0628 0.09222 0.11082</ns0:cell><ns0:cell>0.02204 0.10274</ns0:cell><ns0:cell>0.2301 0.2369 0.10632 0.21032</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell cols='2'>Grasshopper (large) 0.16254 0.07201 0.03502</ns0:cell><ns0:cell>0.0959 0.05482</ns0:cell><ns0:cell>0.1283</ns0:cell><ns0:cell>0.15321 0.16001</ns0:cell></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='2'>Grasshopper (brown) 0.23143 0.069 0.049</ns0:cell><ns0:cell>0.09289 0.0688</ns0:cell><ns0:cell>0.05902</ns0:cell><ns0:cell>0.09302 0.1982</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='2'>Grasshopper (small) 0.19721 0.07033 0.04205</ns0:cell><ns0:cell>0.09422 0.06185</ns0:cell><ns0:cell>0.08465</ns0:cell><ns0:cell>0.12941 0.13621</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Wasp (larvae)</ns0:cell><ns0:cell>0.15232 0.06833 0.091</ns0:cell><ns0:cell>0.09222 0.1108</ns0:cell><ns0:cell>0.1963</ns0:cell><ns0:cell>0.1123 0.2193</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Water scavenger</ns0:cell><ns0:cell>0.27503 0.062 0.038</ns0:cell><ns0:cell>0.08589 0.0578</ns0:cell><ns0:cell>0.06501</ns0:cell><ns0:cell>0.15603 0.18812</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Eri (Pupae)</ns0:cell><ns0:cell>0.19651 0.073 0.01803</ns0:cell><ns0:cell>0.09689 0.03783</ns0:cell><ns0:cell>0.25432</ns0:cell><ns0:cell>0.21631 0.18111</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Water beetle</ns0:cell><ns0:cell>0.21231 0.072 0.035</ns0:cell><ns0:cell>0.09589 0.0548</ns0:cell><ns0:cell>0.15302</ns0:cell><ns0:cell>0.21897 0.2281</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='2'>Eri (4th instar larvae) 0.14243 0.0461 0.03217</ns0:cell><ns0:cell>0.06999 0.05197</ns0:cell><ns0:cell>0.08321</ns0:cell><ns0:cell>0.09812 0.07492</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Cockroach</ns0:cell><ns0:cell>0.1374 0.19204 0.0021</ns0:cell><ns0:cell>0.21593 0.0219</ns0:cell><ns0:cell>0.09832</ns0:cell><ns0:cell>0.03102 0.11312</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:49115:1:1:NEW 19 Jul 2020) Manuscript to be reviewed PeerJ reviewing PDF | (2020:05:49115:1:1:NEW 19 Jul 2020)</ns0:note></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49115:1:1:NEW 19 Jul 2020)</ns0:note> </ns0:body> "

"Reviewer 1 Study area: Figure 1 is not mentioned. It should be mentioned. The recommendation has been adhered to. Line 175: Table/diagram of the market price of some insects could be inserted (if possible) We apologise to say this is not be possible as of now. Lines 182-184: These could be removed. We feel that incorporating the name of the laboratory would enhance the authenticity of the paper. Hence, we have decided to retain these. Lines 185-186: The name of chemical compounds should be given. We have removed that section completely. The methodology otherwise is good. Figure 2 could be improved (if felt necessary). We have improved the figure as recommended. In the discussion part, the following studies could be cited: Arya, M. K., & Verma, A. (2020). An Insight Into the Butterflies (Lepidoptera, Papilionoidea) Associated With Protected Area Network of Uttarakhand, Western Himalaya. In Current State and Future Impacts of Climate Change on Biodiversity (pp. 154-178). IGI Global. Guadalquiver, D. M., Nuñeza, O. M., & Dupo, A. L. (2019). Species Diversity of Lepidoptera in Mimbilisan Protected Landscape, Misamis Oriental, Philippines. Entomology and Applied Science Letters, 6(3), 33-47. Dewan, S., Chettri, I. K., Sharma, K., & Acharya, B. K. (2019). Kitam Bird Sanctuary, the only low elevation protected area of Sikkim: A conservation hotspot for butterflies in the Eastern Himalaya. Journal of Asia-Pacific Entomology, 22(2), 575-583.\ Hagstrum, D. W., & Phillips, T. W. (2017). Evolution of stored-product entomology: protecting the world food supply. Annual review of entomology, 62, 379-397. We have cited these studies as recommended by the reviewer: Arya, M. K., & Verma, A. (2020). An insight into the butterflies (Lepidoptera, Papilionoidea) associated with protected area network of Uttarakhand, Western Himalaya. In Current state and future impacts of climate change on biodiversity (pp. 154-178). IGI Global. Reviewer 2 Title: to mention “…a Natural World Heritage Site of Southern Asia” is far too vague. Where in southern Asia? Southern Asia covers a huge area. Even later in the description of the study area, no information about where this “natural World Heritage Site” is located is given. Is it in Assam? Part of it in Bhutan? If so, that should be added. In Fig. 1 there should be a map between that overview map of India and that detailed view of the heritage site. The reader MUST have a map of the part of Assam (if the heritage site is in Assam) that shows the area. Also, maps must have a scale (x km). The mentioning of desirability of food security in a Natural World Heritage Site is somewhat odd: food security is desirable only in the World Heritage site? Elsewhere it is not desirable? We have changed the title as per the recommendations of Reviewer 3. The information on the study area has also been refined as suggested to include Bhutan. The recommended map has been added along with scale details. Further, we have changed the title to avoid the mentioned issue about ‘desirability’. Abstract: Line 24: write “Insects not only play a significant role in the ecological processes of Nature, but since pre-historic times they have also formed a part of the human diet. With a still growing…” Line 36: Isoptera have for several years now not been treated as a separate order of insects any more, but are included in the order of Blattodea. Line 38: write “Biochemical analyses” (plural of analysis is analyses!). Further, what does “these” refer to in ‘these insects’ (no specific insets have been mentioned). Line39/40: delete the lines “Further, the economic significance…. It was observed that” and start “To manage insects…advantages.” These changes have been done. Introduction: Line 49: the reference Yi etal. 2012 is misleading as Yi et al have not researched insect nutrients. There is no need for a reference at all with regard to the statement made on line 49. Yi et al. 2012 has been removed and other changes have been done. L. 54: Likewise, Van Huis 2013 has never studied the diets of prehistoric humans and the reference this reference is simply wrong and either has to be removed or replaced by an appropriate reference. This has been modified. Lines 60-62: the authors had better write: “Given the shortfalls of the ‘green revolution’and high risk of food insecurity in developing and underdeveloped nations, the use of insects as a potential source of food for the burgeoning human population had been advocated by Meyer-Rochow (1975), a suggestion that has been gaining interest among researchers, entrepreneurs and policy makers worldwide ever since.” This has been done accordingly. Line 63: replace “in most Asian…” with “ in some Asian…” Line 64: write “Weaver ants (Oecophylla smaragdina), whose chemical composition and value as a human food item has been assessed by Chakravorty et al. (2016), are widespread …” L67: Delete “Besides” and start “In Thailand over…” L70, 71, 72: Style! What do the words “their cultural…”, “But they…”, “They are…”refer to? L73/74: provide scientific name for the ‘red ants’ and clarify “…their eggs”. Almost certainly NOT eggs (the eggs are miniscule, more likely their pupae!) L76/78: Condense and make one sentence. Drop Borgohain et al. 2014 ,as it is the wrong reference. L79/80: the reference to “various ethnic tribes” is too vague. There are approx. 50 ethnic groups in Arunachal! Better use Chakravorty et al. 2013 ! L83: write “Odonata were consumed…” L86: start the paragraph with “Scientific reports…” L101: Write “In short, the aims of this study have been to determine the degree to which the ethnic people use insects in their diet and which species they consume. Recording seasonal abundance and availability of edible species as well as evaluating the role that entomophagy could possibly play as a measure of food security in the region, were further aspects of this study.” The above suggestions have been incorporated accordingly. Materials and Methods Describe clearly where the national park is located. Add a proper map (with scale) L124: “these tribes…”? Which? Has Rabha 2016 and have Das & Hazarika 2019 studied all of them? They (who?) really rear insects??? Which species (there are several lakh of insect species in India? This has been changed accordingly. Sampling: more details are required. Describe the equipment used for sampling. How often were traps emptied? Who was involved in the sampling? Figure 2 does not give ANY information on traps, the frequency that collecting took place, people involved, whether collecting occurred during the day or nighttime hours, if light traps were used (and if not why not), what kinds of traps for aquatic insects were used? The suggestions have been incorporated. The sampling process has been discussed in details. L140-146: approximately what were the total areas in sq km that the 4 different habitat types covered? This was added as per suggestion. L172: “…once per season….and twice during the whole survey duration” is not clear. Explain what seasons you distinguish in that area (perhaps spring, summer, autumn, winter? Or maybe monsoon and pre-monsoon; rainy and dry season?), but which months are involved. The project was a one-year project: = 4 seasons? But “twice visited per season”? Not clear “during the survey duration”, but ”once”? This has been revised and corrected. The details have been included under Materials and Methods. L180-195: This is one of the least satisfactory parts of the manuscript. You used fresh or dried insets? How were they dried? Values given are per wet weight or dry weight. You write that for this study “we chose insect species of the order Coleoptera” but Table 5 lists species belonging to all kinds of insect orders! Changes have been incorporated in the Biochemical Analysis section to address these discrepancies. You need to provide proper references for standard methods, e.g. Bragdon’s method, etc. It sounds as if for protein analysis the Lowry method was used. But there is a chance for overestimation as some flavonoids, polyphenols also contribute in the development of the colour. The Micro-Kjeldahl process is superior and more reliable to estimate N and then protein. The methods used in the study have been discussed in detail following the recommendation. Results (FIGURS AND TABLES): The Tables 1 -4 are very good and detailed. Congratulation, well done! For Table 4 you need to explain in a legend: Occurrence, FBH ,OFH, Abundance and Relative Abundance. This has been explained in a footnote. Figures 1, 2, and 3 need to be improved! Fig. 3 looks nice, but you have to give the scientific names of the insects you depict in the figure! Figure 1 has been improved. Figure 3 is just a depiction of the habitat types. Hence, we did not see the need to mention the insect names. Fig. 4 is OK. Fig. 5 is terrible: What is the y-axis (number of peopåle interviewed, percentage of population?) What is the x-axis (distance in km?). How can the surface of the data be ‘curved’ if you have separate data points . Explain. Figure 5 has been changed and improved. Fig. 6: shows men or women? Figures 7 and 8: good. Figures 9 – 17: inadequate. What is the unit for the data? Based on dry or wet weight? You need to give the scientific names of the insects studied. Based on what quantities (numbers of insects, weight used for analysis; how many replicates?) Figure 6 show both males and females. For other figures, we have incorporated necessary changes in the Discussion section. L210: “The order Hemiptera….” “The order Coleoptera…) L212: “A total of 9,213 edible insects… L213: …the field observation.” L220: “Species of the order…” L226: “…the year, but in the winter they were less abundant than during the premonsoon and monsoon season.” Which months is winter? Changes for the above lines have been done. L231: This paper should be cited: Journal of Asia-Pacific Entomology 17 (2014) 407–415 Nutritional composition of Chondracris rosea and Brachytrupes orientalis:“Two common insects used as food by tribes of Arunachal Pradesh, India”Jharna Chakravorty, Sampat Ghosh, Chuleui Jung, V.B. Meyer-Rochow. Unfortunately, this paper could not be cited as it was referred to as a plagiarized paper by the Editor-in-Chief of Journal of Asia-Pacific Entomology. Discussion L271- 330: This ecological section is useful and interesting and should be retained, even though it is not directly (but certainly indirectly) related to edible insects of the region. L277: scientific names of insects should be italicized. L296: “This adverse finding…” L330-334: “For instance,….their lives” should be deleted L340: “…of the Bodos…” L346: write “…is from the order Orthoptera, which comprise 8 species of which 7 are short-horned …”Or you can write “…, Orthoptera, which contain 8 species…” L348-353: Delete “Notably, Assam…and so on.” L358: “…are collected (cf., Meyer-Rochow 2017). This indicates…” L362: “…rather than an…” L369: Vaccaro et al. (2019): reference is incomplete! Add: “…observation of Vaccaro et al. (2019), but does not agree with the study by Ghosh et al. (2020), carried out in Ethiopia. (Journal of Insects as Food and Feed 2020, 6 (1), 59-64). L376: wrong general statement: not ALL insets contain minimal amounts of carbohydrates. No, some like bees, honeypot ants etc are VERY rich in carbohydrates! L377: How can you cite a 2012 paper and then write that the results were “further verified” by a 2006 paper!!! The citations on nutrients L377, L379, should be replaced by newer and more reliable ones. All aforementioned recommendations have been incorporated. L384: write “…insects should potentially be able to supplement the diet of livestock.” L391/2: Payne et al 2016 noted that there is NO SIGNIFICANT DIFFERENCE (!) in the nutritional qualities between insects and conventional protein food sources like pork, beef and poultry! Get this right, please. L396: benefits: like what? L405408: Delete “For instance….areas.” L420: “…ladybird beetles..,” L425: yes, here you mention it “rich in protein and carbohydrates” but earlier on Line 376 you wrote carbohydrates were minimal! L434: Delete “be” L436: which larvae? And who found that (reference please) L 440: “…higher than that of the adult…” All the aforementioned changes have been done. L445 – 458: Delete the whole paragraph. We cannot delete the paragraph as it is an important part of our paper. L469: Write “Our study shows that edible insects are of considerable nutritional value and expanding their acceptability as human food can be expected to improve the nutritional status of people and possible reduce their costs. L472: you mean ‘six’, but you need a reference to back up that statement! L478:”Certain insects…” ? Which? Silkworms, honey bees, and as of late bumble bees and wasps. Is Akerele et al 2018 a correct reference? L480: how can you leave out Korea with hundreds of years of insect cultures! L482: Specht et al. 2019: the title is missing in the references! L486: the statement “ Insect diversity…. 2018).” Is it relevant for Assam and the Heritage Site? L488: “These activities…” (WHICH?) “…improving their diets… (WHOSE?) and their livelihoods (WHOSE?) In the 4 lines 486-489 you use the word “also” three times All these changes have been done in the manuscript. Conclusion L513: why ‘may be concluded’? You are doubting your own results? L516: whose ‘status’? L518: why ‘also’. Delete ‘immense’. We have NO IDEA if the economic advantages will be or “are immense”. We have tried our best to incorporate these changes in the paper. Reviewer 3 TITLE PAGE: The title of the paper needs to be carefully revised because it is not very clear and does represent the context of the paper. The title too wordy. A possible title could be “Composition and nutritional profile of edible insects in the Manas National Park, India: Implications for food security in the region”. The title has been modified to “Composition and nutritional profile of edible insects in a Natural World Heritage Site of India: Implications for food security in the region” This paper also lacks a running heading, which is one of the key instructions to authors. The running title has been added: Edible Insects and Food Security INTRODUCTION This section does not situate the exact importance of this study and it is full of grammatical errors. Most of the paragraphs will need to be revised and rephrase accordingly. Most of the sentences are very confusing but the objective of the work is well explained. We have tried to revamp this section as per the comments. Professional help was obtained in order to do this. DISCUSSION The discussion has a very poor scientific presentation format. However, I think the discussion section needs to be rewritten after proper presentation of results. Authors should avoid presenting results in this section. The authors should seek the assistance of an English speaker to address the numerous errors found in this section. Very poor conclusion drawn from the work. We have tried to make some changes as recommended. However, we cannot agree with the reviewer that the conclusion was drawn poorly. We believe the conclusion is fair and justifiable given our sphere of work. Further, the previous reviewers have corroborated the importance of the work as well. REFERENCES The references have failed to follow the format of the journal. We have done the references in APA format as according to PeerJ’s policy “PeerJ prefers you spend your time doing science, not formatting references! Submit your references in whatever style you like. Just make sure they're full, clear, and consistent and we'll standardize at production.” FIGURE Most of the graphs are poor done and the some if the axes are overcrowded. Figures have been presented with no labels. Figure 9 is not reported in the Result section. However, I think these figures should be presented in a tabular format. Figure 10, is not necessary because it is a summary of all the figure 9s. Again, the different elements (minerals) were not measured using the same approach as such the units of measurements are different. Therefore, they can be lump together as shown in figure 10. I think figure 10 should be deleted. Necessary changes have been done as suggested. We have provided the figure 9s as a composite figure. For better clarity, we have decided against removing Figure 10. TABLE The abbreviations in Table 3, should be written in full as a footnote below the table. The headings of the tables should not be centralized. The suggested footnote has been added in Table 3. With regard to the format of headings, we hand over the discretion to the PEERJ Academic Editor. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Insects not only play a significant role in the ecological process of nature but since prehistoric times have also formed a part of the human diet. With a still growing population and skewed demographic structures across most societies of the world, their role as nutrient-rich food has been increasingly advocated by researchers and policymakers globally. In this study, we examine the edible insect diversity and entomophagy attitudes of ethnic people in Manas National Park, a UNESCO Natural World Heritage Site, located in Assam (India). The study involved a field investigation through which the pattern of entomophagy and the attitude towards insect-eating was studied. Following this, we examined the edible insect diversity and abundance at different sampling points. A total of 22 species of edible insects belonging to fifteen families and eight orders were recorded from different habitat types. Out of these 22 species, Orthopterans showed a maximum number of 8 species followed by Hymenoptera (4), Hemiptera (3), Lepidoptera (2), Blattodea (2) and 1 species each from Coleoptera, Odonata, and Mantodea. Dominance, diversity, and equitability indices were computed along with the relative abundance of the insects concerning four habitat types. The economic significance of entomophagy was also observed during the field investigation. To manage insects in the interest of food security, more attention should be given to sustainable collecting and rearing methods emphasizing their economic, nutritional, and ecological advantages.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Insects are the most diverse and abundant forms of life and constitute a primary component of the total faunal biodiversity on Earth. They play vital roles in an ecosystem that includes soil turning and aeration, dung burial, pest control, pollination, and wildlife nutrition <ns0:ref type='bibr' target='#b0'>(Bernard &amp; Womeni, 2017)</ns0:ref>. Besides providing ecological services, insects are also an important source of protein, fat, carbohydrate, and other nutrients. As per the current scientific literature, there are 1.4 million species of insects worldwide which are an intrinsic part of the Earth's ecosystem <ns0:ref type='bibr' target='#b29'>(Kulshrestha &amp; Jain, 2016)</ns0:ref>. As such, they arouse interest not only with their immense species richness but also with their species variety and their role in energy flow. A dimension of their existence not to be overlooked pertains to the fact that they have formed a part of human diets since prehistoric times. Evidence points to at least 113 countries where insects form or formed a part of human diets in one way or the other. This practice of consuming insects as part of the human diet is referred to as entomophagy. Insect-eating or entomophagy is nowadays no longer a traditional or common practice in most countries, except for some in South-and South-East Asia, Latin America, and Africa <ns0:ref type='bibr' target='#b50'>(Rumpold &amp; Schluter, 2013)</ns0:ref>, where more than 2,000 insect species are consumed <ns0:ref type='bibr' target='#b26'>(Jongema, 2015)</ns0:ref>. Given the shortfalls of the 'green revolution' and high risk of food insecurity in developing and underdeveloped nations, the use of insects as a potential source of food for the burgeoning human population had been advocated by Meyer-Rochow (1975), a suggestion that has been gaining interest among researchers, entrepreneurs and policy makers worldwide ever since. Insect farming is popular in many Asian nations for food, feed, and other purposes <ns0:ref type='bibr' target='#b62'>(Zhang et al., 2008)</ns0:ref>. Weaver ants (Occophylla smaragdina), whose chemical composition and value as a human food item has been assessed by <ns0:ref type='bibr'>Chakravorty et al. (2016)</ns0:ref>, are widespread in the Asia-Pacific region and are found from China's south to northern Australia and as far west as India. Although edible insects are not yet of much commercial value, some economic and marketing data on edible insects in Asia and the Pacific are available scarce <ns0:ref type='bibr' target='#b27'>(Johnson, 2010)</ns0:ref>. In Thailand, over 150 species from eight insect orders are eaten. Approximately 50 insect species are eaten in the north and about 14 species are eaten by people in southern Thailand <ns0:ref type='bibr' target='#b49'>(Rattanapan, 2000)</ns0:ref>. The insect-eating habits in various regions depend on the indigenous populations' cultural practices, religion and the place they call home. But insects used as emergency food during natural calamities or other national contingencies as well as for their organoleptic characteristics also <ns0:ref type='bibr' target='#b18'>(Dumont, 1987)</ns0:ref>.</ns0:p><ns0:p>The North-Eastern part of India has diverse ethnic groups that have a unique culture of food intake with insect-eating mostly prevalent amongst rural tribal people of the region which have a long-cultured history. In Arunachal Pradesh, 39 coleopteran insect species are used as indigenous food by approximately 50 ethnic tribes <ns0:ref type='bibr' target='#b8'>(Chakravorty et al., 2013)</ns0:ref>. The ethnic Nishi tribe of Arunachal Pradesh consumed more than 50 edible insect species belonging to 45 genera, 38 families, and 11 orders as a part of their diet <ns0:ref type='bibr' target='#b6'>(Chakravorty, 2009)</ns0:ref>. Further, a total of 81 species are eaten in Arunachal Pradesh by the Galo and Nyishi tribes <ns0:ref type='bibr' target='#b9'>(Chakravorty et al., 2011)</ns0:ref>.</ns0:p><ns0:p>Odonata were consumed the most followed by Orthoptera, Hemiptera, Hymenoptera, and Coleoptera.</ns0:p><ns0:p>Scientific reports indicate insects to be significant sources of not only proteins and vitamins, but also lipids, minerals, fibre and carbohydrates. Insects possess a viability of providing daily requirements of these nutrients in most developing countries <ns0:ref type='bibr' target='#b5'>(Bukkens, 1997;</ns0:ref><ns0:ref type='bibr' target='#b19'>Elemo et al., 2011)</ns0:ref>. For instance, edible aquatic beetles play an important role in the nutrition and economy of the rural population in Asian, Latin American and African nations <ns0:ref type='bibr' target='#b52'>(Shantibala et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b32'>Macadam &amp; Stockan, 2017)</ns0:ref>. It should be noted that the diversity and abundance of insects in different habitat types have an observed correlation with the entomophagy attitude of a particular region. Therefore, research indicates the importance of exploiting insect diversity effectively through insect farming to avoid global problems associated with dependency on a limited number of insect species as experienced with some food animals and crops <ns0:ref type='bibr' target='#b28'>(Khoury et al., 2014)</ns0:ref>.</ns0:p><ns0:p>In this research article, we have made an effort to study the edible insect diversity of a UNESCO Natural World Heritage Site, located in the Indo-Burmese biodiversity hotspot. Regional entomophagy was studied through a field investigation. We made an effort to determine the degree to which the ethnic people use insects in their diet and which species they consume. Recording seasonal abundance and availability of edible species as well as evaluating the role that entomophagy could possibly play as a measure of food security in the region, were further aspects of this study.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Study Area</ns0:head><ns0:p>The Manas National Park (MNP), located at 26.6594&#176; N, 91.0011&#176; E, was declared a UNESCO Natural World Heritage Site (WHS) in 1985 (Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>). Renowned for its array of rich, rare, and endangered wildlife not found anywhere else in the world, the faunal diversity of MNP includes the Pygmy Hog, Golden Langur, Hispid Hare, Assam roofed turtle and so on. Located at the Himalayan foothills of India, MNP is shares land territory with Bhutan where it is known as the Royal Manas National Park. The park is composed majorly of grassland and a forest biome. It is covered by the Brahmaputra Valley semi-evergreen forest vegetation along with the Himalayan subtropical broadleaf forests and the Assam Valley semi-evergreen alluvial grassland vegetation. This renders MNP a region of rich and abundant biodiversity. Major trees include the Bombax ceibar, Gmelina arborea, Bauhini purpurea, Syzygium cumin, Aphanamixis polystachya, Oroxylum indcum, etc. The climate is sub-tropical with a warm and humid summer, followed by a cool and dry winter. Temperatures range from 10 0 C to 32 0 C. The park has more than 58 fringe villages directly or indirectly dependent upon it, distributed across three ranges: Bansibari, Bhuiyaparaa and Panbari. The village Agrang lies at MNP's core while most are located in its buffer zone. Spread over the State of Assam's Barpeta and Bongaigaon districts, the tribal population in its fringe areas predominantly include Bodos and Rabhas among which the practice of insect eating and rearing are widespread <ns0:ref type='bibr' target='#b46'>(Rabha, 2016;</ns0:ref><ns0:ref type='bibr' target='#b14'>Das &amp; Hazarika, 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Insect sampling</ns0:head><ns0:p>Insects were collected using entomological nets, beating tray, water traps, or through digging and handpicking. The local people of the study area helped in the collection process. Insects were usually collected during the early hours of the day (0500-0900 hours). The flying insects were collected via entomological nets at a time when they were active (midmorning/late afternoon). Sweep nets were used for collecting grasshoppers and other insects which hid in low grass-or herb-dominated vegetation and in small shrubs. Netting was normally carried out during early hours of the day as it required good vision, thus causing some limitation to its wider applicability as we could not collect nocturnal taxa. In order to catch nocturnal species, we used light traps. Nocturnal arthropods like species of moths and beetles are easily attracted towards artificial light sources. Light traps have therefore been widely used in nocturnal insect sampling. A high-power CFL bulb was arranged behind a white cloth for trapping nocturnal insects. Generally, a bowl filled with water was placed under the light sources in the evening, after rainfall, to attract termites. The light attracted the reproductive termites which came out for nuptial flights and were trapped in the water or collected by hand from the water to prevent them from escaping. Light trapping was used widely in case of agricultural habitat type and open field habitat type. Beating trays were used to collect insects such as Lepidoptera and Hymenoptera. Shrubs and small trees were sampled through commonly used beating tray sample method. Moreover, the red weaver ants were harvested by plucking the nest from the tree and dropping them in a bucket of water before being sorted out for consumption. The soil dwelling edible insects were collected by digging with the help of spades. Further, insects were hand-picked according to a method described by <ns0:ref type='bibr' target='#b41'>Musundire et al. (2014)</ns0:ref>. Besides, sweep netting, large insects such as grasshoppers and beetles were also collected by hand which were caught early in the morning or in evening when they were less mobile due to their low body temperature. The mole cricket and field crickets were dug out of holes. We used the hand-netting technique to collect the aquatic insects along with other local traditional equipment like Jakoi, Chaloni, etc. The Jakoi is a species of wicker work shovel that is either dragged along the bottom or placed on the water bed to catch the aquatic insects which take refuge in it when the weed is trampled. It is prepared with bamboo slips, which are locally known as 'dai'. 'Jati' bamboo is specially used for making this particular implement. Chaloni is a bamboo strainer used to separate insects from collected water. Long handled aquatic net was used to collect insects that live on the water surface. Many adult insects living on the surface were predators, so they were removed from the net using forceps directly into a collection container. The kick-net method which is a process where insects are collected by dislodging insects from the substrate (habitat) was also used. The organisms that were dislodged by the disturbance were collected on the net. For preservation of specimens, both dry and wet preservation methods were followed. For dry preservation, the specimens were preserved using pins in insect cabinet box and were mainly sun-dried. Soft-bodied insects were preserved using 70% ethyl alcohol. Besides, some hardbodied edible insects were preserved using 2-3% formaldehyde <ns0:ref type='bibr' target='#b21'>(Ghosh &amp; Sengupta, 1982)</ns0:ref>. Identification was done later by comparison with other specimens. Some were identified in the Zoological Survey of India, Shillong, Meghalaya (India). Sampling was done from 20 chosen sites located in and around MNP. The sampling was done during the period 2018 (June)-2019 (June). The permission for conducting the field study was obtained from Office of the Principal Chief Conservator of Forests (Wildlife) and Chief Wildlife Warden, Government of Assam, India vide No. WL/FG31/ResearchStudyPermission/19th Meeting/2019. The remaining methodology of the study is outlined in Figure <ns0:ref type='figure'>2</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Edible insect density, diversity and abundance</ns0:head><ns0:p>Studying the diversity required us to divide each sampling point into four different habitat types, namely, open field habitat (OFH), forest/backyard forest habitat (FBH), swampy area habitat (SAH), and agricultural field habitat (AFH). The entire sampling area amounted to approximately 842 km 2 . Insects were recorded within quadrates (2m x 2m dimension) established in the habitat type and monitored for four seasons, namely, pre-monsoon (March, April and May), monsoon (June. July, August and September), retreating monsoon (October and November), and winter (December, January and February) <ns0:ref type='bibr' target='#b1'>(Borthakur, 1986)</ns0:ref>. The Shannon-Wiener index (H') for diversity, Simpson index (D) for dominance, and Margalef index for species richness in the four selected habitat types were computed. Order-wise relative abundance and species-wise abundance in the different habitats were also computed. The descriptions and mathematical expressions are outlined below. The indices were estimated using PAST (v.3.26) <ns0:ref type='bibr' target='#b24'>(Hammer et al., 2019)</ns0:ref> and SPSS (v.23). Shannon-Weiner index (H') determines the diversity of insect species in a particular habitat type. The higher the H' value, the greater is the diversity. Expression (i) gives the formula. H' = -&#8721; p i ln p i &#8230;&#8230; (i) Where p i = proportion of individuals found in i th species Simpson's index (D) defines the probability of drawing any two individuals at random from a very large community of the same species. If D increases, we can say that diversity has decreased. This index, defined by expression (ii), accounts for both aspects of diversity, i.e., richness and evenness.</ns0:p><ns0:formula xml:id='formula_0'>D = &#8721; &#8230;&#8230; (ii) ( &#8721;&#119899; &#119894; [&#119899; &#119894; -1] &#119873; [&#119873; -1] )</ns0:formula><ns0:p>Where, n i = individuals in i th species, N = total number of individuals Margalef's index (R) gives a precise idea about a species' richness. It attempts to compensate for the effects of sampling by taking a ratio of species richness by the total number of individuals in a sample, given in expression (iii).</ns0:p></ns0:div> <ns0:div><ns0:head>R = (S-1) / lnN</ns0:head><ns0:p>Where, S = total species in a community, N = total number of individuals in that community.</ns0:p></ns0:div> <ns0:div><ns0:head>Entomophagy study</ns0:head><ns0:p>Understanding the entomophagy attitudes and distribution among the tribal population near MNP required conducting a survey. Methods included interactions with the villagers through questionnaires, field surveys, and a market survey. The villages were selected randomly and were surveyed once per season for the whole year. Questions were asked to a mixed group of ethnic people which included individuals from all sections of the society. The market survey helped record the economic importance of these insects for the local economy. Questions pertained to the number of insects sold per week/month, their market prices, and how popular were the insects in ethnic cuisine. Overall, the questionnaire survey included 2672 respondents from 30 villages of which 981 were from the Adivashi tribe, 695 were Bodos, 436 were Saranias, 422 were Rabhas and 138 were non-tribal individuals. Written consent was obtained from the respondents during the field interviews.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Table <ns0:ref type='table'>1</ns0:ref> shows the order-wise number of edible insects found in the study area. In MNP, the order Orthopteran recorded the maximum number with 8 species, followed by Hymenoptera with 4 species. The order Hemiptera was found to have 3 species followed by Lepidoptera and Blattodea with 2 species each. The order Coleoptera, Mantodea, and Odonata accounted for 1 from each species and family. A total of 9,213 edible insects were recorded from AFH, 1455 in FBH, 3435 in OFH and 6497 individuals in SAH, during the field observation. No common abundant species was found in a single habitat. Most of the insects were found in two or three habitats during the study period.</ns0:p><ns0:p>Table <ns0:ref type='table'>2</ns0:ref> showcases the types of edible insects consumed by the ethnic people. In this table, the local and common name, the scientific name with their taxonomy, and their seasonal availability, edible parts, and mode of consumption are tabulated. Seasonal availability was maximum during June to September, gradually reducing towards the winter season. Species of the order Orthoptera were most abundant in May to September, whereas, Coleopterans were usually available from April to September. Insects belonging to the Hemiptera and Hymenoptera were found to be restricted to the period lasting from April to October, whereas, Mantodea were available from June to October. Some edible insects like Lethocerus indicus, Periplaneta americana and Gryllotalpa africana were found to be available throughout the year, but in the winter, they were less abundant than during the pre-monsoon and monsoon season.</ns0:p><ns0:p>Simpson index (D) for dominance, Shannon-Wiener index (H') for diversity, and Margalef index for evenness/equitability were calculated in the four selected habitats (Table <ns0:ref type='table' target='#tab_1'>3</ns0:ref>). Further, species abundance was found to be the highest in Chondracris rosea with 18.64, followed by Gryllotalpa africana with 8.50 in AFH. In FBH, the highest species abundance was found in Hieroglyphus banian with 8.91, followed by Polistis olivaceus with 5.20. In OFH, Gryllus bimaculatus was the highest abundant species with 5.1, followed by Lethocerus indicus with 3.17. Table <ns0:ref type='table'>4</ns0:ref> shows the relative abundance of the edible species in selected habitats.</ns0:p><ns0:p>Chondracris rosea has the highest relative abundance (11.50%) followed by Choroedocus robustus (8.92%), the least relative abundant insect species includes Laccotrephes ruber (0.42%).</ns0:p><ns0:p>Seasonal variation in abundance of edible insects (Figure <ns0:ref type='figure'>3</ns0:ref>) shows Periplaneta americana to be the most abundant species with 798 individuals found in monsoon season followed by Mantis religiosa with 466 individuals, and the least abundant species is Mecopoda elongata with 13 individuals. In pre-monsoon, Antheraea assama with 443 individuals has the highest presence and Acheta domesticus with 3 individuals has the lowest. Choroedocus robustus has availability of 420 individuals during retreating monsoon compared to 10 individuals of Gryllus bimuculatus. Finally. In winter, Vespa affinis has the highest availability with 125 individuals, followed by Periplaneta americana with 112 individuals. The least number of individuals (12) was observed in case of Hieroglyphus banian. In general, highest number of insect species was observed during monsoon season with a total of 4808 individuals followed by pre-monsoon with 2758 individuals, retreating monsoon with 2106 individuals, and winter with 774 individuals.</ns0:p><ns0:p>Further, the proportion of ethnic communities practicing entomophagy in MNP has been graphically represented in Figure <ns0:ref type='figure'>4</ns0:ref>. As mentioned before, the 2672 respondents to our survey included 981 individuals from the Adivashi tribe, 695 from the Bodo tribe, 436 from the Sarania tribe, 422 from the Rabha tribe and a total of 138 individuals were non-tribal. We also categorised the respondents of our survey who considered the insect-eating habit favourable, into four age-groups, namely, less than 60 years, between 40-60 years, between 20-40 years and greater than 20 years (Figure <ns0:ref type='figure'>5</ns0:ref>). Consumers in the 20-40 group responded highly favourably while those in less than 20 years group responded less favourably owing to different variations of entomophobia. There are various reasons for eating insects which were found among the different ethnic groups during the questionnaire survey (Figure <ns0:ref type='figure'>6</ns0:ref>). The different modes of insect consumption have been presented in Figure <ns0:ref type='figure'>7</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head>Edible insect diversity and abundance</ns0:head><ns0:p>As part of this study, we find that species of the order Orthoptera are popular among the ethnic people for consumption purposes. The edible species majorly include both short and long-horned grasshoppers (Eupreponotus inflatus, Choroedocus robustus, Chondracris rosea, Mecopoda elongata and Hieroglyphus banian), field crickets (Gryllus bimculatus), house crickets (Acheta domesticus) and mole crickets (Gryllotalpa Africana). Other species include potter wasp (Vespa affinis) and paper wasp (Polistis olivaceus), Indian honey bee (Apis indica) and rock bee (Apis dorsata), giant water bug (Lethocerus indicus) and some others. The ethnic (tribal) communities consuming these insects included mainly those of the Adivashis, followed by the Bodo, Rabha, and Sarania. A section of the non-tribal population also consumed insects as part of their diets. Species diversity, richness, and evenness gives an idea about the variety and diversity of species in the study sites. The most commonly used dominance and diversity indices in ecology are the Simpson index and the Shannon-Wiener index. Simpson index is used to assess the dominance but fails to provide an idea about species richness. Shannon-Wiener index is expected to determine both diversity characteristics (evenness and richness) but does not provide any information on rare species which, however, are very important in studies of biodiversity.</ns0:p><ns0:p>Results show that the species dominance is highest in FBH (0.3871), followed by SAH (0.2423), OFH (0.1467), and AFH (0.1148). On the other hand, species diversity, as per H', was highest in AFH (2.822), OFH (2.392), FBH (2.153) and SAH (1.329). This establishes the fact that as insect diversity decreases, their dominance should increase. In MNP, this can be noticed for the forest habitat. Further, this result is corroborated by the Margalef index which is found to be highest for AFH (2.936), OFH (2.294), FBH (1.836), and SAH (0.653).</ns0:p><ns0:p>Notably, forest habitats are the prime source of edible insects for local people. This adverse finding in the case of FBH may be attributed to various reasons. Decreasing forest cover, changes in vegetation type, adverse climatic conditions, or indiscriminate collection and consumption of edible insect. These directly affect the insect diversity and rejuvenation of insect species. In the case of MNP, high temperatures, inadequate rainfall, and vegetation cover may also have influenced the population density of these edible insects. Notably, the overall climate of Assam has warmed by over 0.5 0 C for the past decade which is expected to rise up to 2.2 0 C by 2050.</ns0:p><ns0:p>It should be noted that Shannon-Weiner and Simpson diversities increase as richness increases for a given pattern of evenness, and increase as evenness increases for a given richness, but they do not always follow the same trend. Simpson diversity is less susceptible to richness and sensitive to evenness than Shannon index which, in turn, is more receptive to evenness. At the other extreme, the Berger-Parker index, depends entirely on evenness-it is simply the inverse of the proportion of individuals in the community that belongs to the single most common species, while the other indices (Margalef) are dependent on the number of species. Apart from the diversity and distribution patterns for insect taxa, interactions between insect groupings and plant groups are another important topic requiring urgent research attention. This is because plants provide key habitat parameters for many insect species ranging from shelter to breeding sites. This has not been covered under this study and could be pointed out as its limitation.</ns0:p><ns0:p>Our analysis of seasonal diversity of edible insect species shows that the diversity of the edible insects was greater during monsoon and pre-monsoon season, moderate in the retreating monsoon season, and lowest in the winter season. As per the survey report, it was found that the abundance of insects found today is </ns0:p></ns0:div> <ns0:div><ns0:head>Entomophagy, food security, and its economic implications</ns0:head><ns0:p>The field investigation revealed that most of the respondents found insects to be tasty and delicious (59%), while a section found them to be an inexpensive source of food (17.1%).</ns0:p><ns0:p>Traditional medicinal food is also one of the reasons why edible insects are collected (Meyer-Rochow, 2017). This indicates the substantial preference of insects in the food habits of people and underscores their importance in the allocation of household costs and sustaining food security. This can be corroborated with the findings of <ns0:ref type='bibr' target='#b39'>Mozhui et al. (2017)</ns0:ref> for Nagaland, where the ethnic people considered insects as a regular food source, rather than an emergency food item. The local people favoured eating insects mostly by frying, roasting, or smoked. This emphasises the wide variety of ways through which insects may be consumed. However, a low percentage of respondents claimed them to be easily available food as collecting them is rather difficult compared to conventional livestock. This calls for the development of an insect farming industry as well. Further, a large number of respondents in the 20-40 years and 40-60 years age bracket favoured eating insects due to the various reasons as in Figure <ns0:ref type='figure'>5</ns0:ref>. Entomophagy, as such, is highly popular among the youth population. This corroborates the observation of Vaccaro et al. (2019) but in Ethiopia young people are less inclined to eat or even taste insects <ns0:ref type='bibr' target='#b22'>(Ghosh et al. 2020)</ns0:ref>.</ns0:p><ns0:p>Besides, the nutritional significance of edible insects has been well established by current scientific literature. It is observed that nutrients vary widely across insect species wherein some are rich in protein and lipids while others are rich in mineral content. <ns0:ref type='bibr' target='#b10'>Chen et al. (2009)</ns0:ref> note that edible insects are rich in protein and fat, but sometimes may lack carbohydrate content. However, insects like bees, honeypot ants, etc., are very rich in carbohydrates. Besides, <ns0:ref type='bibr' target='#b11'>Collavo et al. (2005)</ns0:ref> note that the presence of high essential amino acids is a major reason for insects having high-quality protein. Majority of the population near MNP belong to low-or lowermiddle-income category people. Their demography is skewed towards ethnic backgrounds and hence, the economy is highly underdeveloped. Rearing livestock and maintaining animal husbandry practices, require a substantial amount of money. The piggery sector is robust in this area. Practicing this requires large amounts of land and also involves substantial capital. However, the nutritional benefits gained from it are not enough to compensate for the effort. Also, insects generally meet the WHO recommendation for amino acid content with nymphs being their most abundant source (Tang et al., 2019). Coleoptera has a higher amount of protein than most livestock. More importantly, edible insects bear many non-health related benefits related to environmental and financial costs than livestock.</ns0:p><ns0:p>On the other hand, it is important to note that many edible insects have higher energy, sodium, and saturated fat content than typical livestock <ns0:ref type='bibr' target='#b44'>(Payne et al., 2016;</ns0:ref><ns0:ref type='bibr'>Tang et al., 2019)</ns0:ref>. This diminishes their worth as alternative nutrient sources to fight nutrition-related diseases. This is because the saturated fat content of edible insects is not recommended for people with heart disease risk, obesity, or metabolism issues. Further, some beetle or butterfly species produce dangerous toxins that are harmful to human health. Such species must be identified before being consumed as food <ns0:ref type='bibr' target='#b2'>(Blum, 1994)</ns0:ref>. However, insects have very high micronutrient content which can be extracted or consumed at a third of the cost than other food products.</ns0:p><ns0:p>MNP is a highly flood-ravaged area with untimely floods occurring during the sowing period. Floods in 2019 affected over a million people of Assam with a majority from the Baksa District (where MNP is located) and the adjacent district of Barpeta. This frequently uproots livelihood of the local people rendering them vulnerable to high food insecurity. It should be noted that these ethnic people otherwise have decent livestock and animal husbandry resources. With floods, they tend to lose livestock in a large-scale manner. At this juncture, edible insects can play a significant role in maintaining the nutritional content of their diet intact.</ns0:p><ns0:p>Animal protein is superior to plant; therefore, the best protein supplements should include some animal protein. Thus, insects may provide for good quality protein ingredients to produce a high standard protein supplement for the food industry <ns0:ref type='bibr' target='#b57'>(Ssepuuya et al., 2017)</ns0:ref>. It was also found that the lipid content of common insect larvae (37.87%) are higher than the soybean (14.60%). From the energy point of view, lipids are important because one gram of lipid provides more than 9 kcal of energy when oxidized in the body. Lipids are structural components of all tissues and indispensable in cell membranes structure and cell organelles <ns0:ref type='bibr' target='#b17'>(Drin, 2014)</ns0:ref>. The fat content of pupae and larvae of edible Coleoptera is higher than that of the adult insect. These results coupled with the significant role played by edible insects in the local food habits make it undeniable that the desirability of food security in their context is valid as they can be considered as viable sources of macro-and micro-nutrients for human beings.</ns0:p><ns0:p>Edible insects such as beetles have been a rich source of proteins and also other nutrients for a long time and have been preferred over traditional livestock by several communities all over the world <ns0:ref type='bibr' target='#b30'>(Losey et al., 2006)</ns0:ref>. For instance, indigenous communities of Mexico are involved in buying and selling edible insects, which are also processed and sold in urban markets. Insects have low-fat content and as such, there has been a high worldwide demand for edible insects. Additionally, aquatic insects are commonly exported from South Asian nations to the United States which are prepared and served in high-end eateries. The estimated size of this market was approximately USD 40 million in 2015. Moreover, in the Lao PDR, insects can be found in markets as ready-to-eat snacks or fried with lime leaves (van Huis, 2003). Concerning agriculture, beetles have been found to contribute more than a billion dollars in environmental and economic benefits globally. This comes from the fact that they recycle cattle manure, thereby, improving pasture growth, yielding high agricultural benefits, and thus, augmenting the livelihood of agriculturalists. In the context of MNP, a gap in the literature has been observed wherein comprehensive studies on beetles' economic benefits haven't been witnessed.</ns0:p><ns0:p>Rearing insects can results in environmental benefits with respect to food and feed. Insects can impact organic farming while helping to reduce environmental contamination, as they emit fewer greenhouse gases and ammonia, compared with conventional livestock <ns0:ref type='bibr' target='#b12'>(Dangles &amp; Casas, 2019)</ns0:ref>. Given the inclination of Bodos and other tribes in eating insects and rearing them to an extent, economic policies must target rearing practices of insects, rather than solely focussing on animal husbandry. Therefore, several strategies could be employed that can help in efficiently and sustainably making use of such natural biodiversity in augmenting the societal income and its food security, following learnings of other countries like South Korea (Meyer-Rochow et al., 2019).</ns0:p><ns0:p>Our study confirms that edible insects are of considerable nutritional value and expanding their acceptability as human food can be expected to improve the nutritional status of people and possibly reduce the insects' costs. With a wider insect diversity, the nutritional status of people should improve while costs get reduced <ns0:ref type='bibr' target='#b15'>(Dickie et al., 2019)</ns0:ref>. For instance, mealworms consist of six fatty acids and unsaturated omega-3 components that are equivalent to those found in commonly consumed fishes, and also higher than those found in pigs and cattle <ns0:ref type='bibr' target='#b47'>(Raheem et al., 2019)</ns0:ref>. Since nutrition has been one of the core components in the evolution of economic policies as well as family welfare, it is necessary that the insect eating habits of ethnic people in the study area must be widely augmented while focussing on the preservation of its insect diversity.</ns0:p><ns0:p>Certain insects like silkworms, honey bees, and as of late bumble bees and wasps have been traditionally domesticated since they are of high economic value. As such, insect farming is much needed in the study area. This concept is widely prevalent in Korea, Thailand, Vietnam, and Laos PDR. Vertical farming is another technique that can strengthen local economics and help exploiting new protein sources <ns0:ref type='bibr' target='#b54'>(Specht et al., 2019)</ns0:ref>. Family-run enterprises are mostly involved in this business along with other firms that have commercialised insects as not only food but also sources of protein and other health supplements.</ns0:p><ns0:p>Insect diversity can be critical for livelihood development since, in some developing countries, the poorest members of a society are engaged in gathering and rearing of mini-livestock <ns0:ref type='bibr' target='#b33'>(Mason et al., 2018)</ns0:ref>. Industrial-scale interventions can also augment their livelihoods that have now been observed in the case of silkworms of Assam. Given the relatively process of rearing, accessibility, and transportation of insects, the people of the study area can immensely benefit if steps to set up an Insect Marketing Hub, assisted by an Insect Development Authority is set up. The hub should be created following a hub-and-spoke model that would not only pertain to processing and distribution matters but also training and R&amp;D issues.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In this study, we recorded edible insect diversity and abundance, characteristics, and attitudes of the ethnic communities involved in entomophagy that are residing in the fringes of the Manas National Park, a Natural World Heritage Site. A total of 22 species of edible insects belonging to fifteen families and eight orders were recorded from different habitat types. Out of these 22 species, we recorded a maximum number of 8 Orthopteran species followed by Hymenoptera (4), Hemiptera (3), Lepidoptera (2), Blattodea (2) and 1 species each from Coleoptera, Odonata, and Mantodea. Diversity indices such as Shannon-Wiener, Simpson dominance, and Margalef indices were computed. Results of the study show that edible insect diversity has significantly decreased in the forest habitat. For a region highly dominated by entomophagy, such decreasing diversity raises a red flag. The field investigation showed that edible insects are highly sought after by local people. We identified the entomophagy practicing population mainly belonging to the Adivashi, Bodo, Rabha, and Sarania communities. They consume insects via different modes of preparation, such as fried, smoked, raw, etc. Moreover, people preferring entomophagy mainly belong to the youth (20-40 year) population. Therefore, our results conclude that MNP is a place vibrant with a high diversity, and abundance of edible insects. Further, it was found that these insects are good sources of protein, lipid, essential amino acids, omega-3, and omega-6 content, besides calcium, magnesium, and carbohydrate content. This validates edible insects as a future alternative source for an adequately nutrient-rich diet, proving to be majorly desirable in the context of food security. Preservation of such diversity necessitates the adoption of efficient and unique conservation techniques along with appropriate policymaking which can go a long way in augmenting greater insect diversity and also the food security of people in South Asia. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>much lower than what it was earlier. A decreasing pattern is corroborated by Doley &amp; Kalita (2011), Narzary &amp; Sarmah (2015), Das et al. (2012), with slight changes. This establishes that seasonal availability of edible insects is declining with time while remaining constant at some points. This calls for urgent ecosystem restoration to sustain the distribution pattern and abundance of edible insects. Anthropogenic disturbances and deforestation are seen rampant in the fringes of MNP. Ground-level evidence glaringly shows that villagers are converting forest lands into agricultural fields. This is an outcome of the burgeoning population of Assam where the human population density is 398 persons per km2 which is way above the global density of 14.7 persons per km2 . Such anthropogenic pressure<ns0:ref type='bibr' target='#b38'>(Morris, 2010</ns0:ref>) is bound to destroy species composition, community structure, and insect diversity (Bolvin et al., 2016). In the regional context, a study of the diversity of insects consumed by the people in Dhemaji District of Assam revealed that a total of 14 species of insects were used as food<ns0:ref type='bibr' target='#b16'>(Doley &amp; Kalita, 2011)</ns0:ref>.<ns0:ref type='bibr' target='#b44'>40</ns0:ref> species of edible insects were recorded in Karbi Anglong District of Assam (Ronghang &amp; Ahmed, 2010), further corroborated by Hanse &amp; Teron (2012). Another study involving the ethnic community of the Bodos, recorded 25 species of local insects, belonging to eight orders and fourteen families which are consumed as food (Narzary &amp; Sarmah, 2015).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 Study</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='21,42.52,178.87,525.00,352.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='22,42.52,204.37,525.00,324.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='23,42.52,229.87,525.00,325.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='24,42.52,204.37,525.00,306.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,229.87,525.00,222.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='26,42.52,229.87,525.00,292.50' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>1 Table 1 :</ns0:head><ns0:label>11</ns0:label><ns0:figDesc>Order-wise number of edible insects.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Order</ns0:cell><ns0:cell>Number of species</ns0:cell></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>8</ns0:cell></ns0:row><ns0:row><ns0:cell>Hymenoptera</ns0:cell><ns0:cell>4</ns0:cell></ns0:row><ns0:row><ns0:cell>Hemiptera</ns0:cell><ns0:cell>3</ns0:cell></ns0:row><ns0:row><ns0:cell>Lepidoptera</ns0:cell><ns0:cell>2</ns0:cell></ns0:row><ns0:row><ns0:cell>Blattodea</ns0:cell><ns0:cell>2</ns0:cell></ns0:row><ns0:row><ns0:cell>Coleoptera</ns0:cell><ns0:cell>1</ns0:cell></ns0:row><ns0:row><ns0:cell>Odonata</ns0:cell><ns0:cell>1</ns0:cell></ns0:row><ns0:row><ns0:cell>Mantodea</ns0:cell><ns0:cell>1</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>22</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Diversity indices (habitat type) of edible insects recovered from four selected habitats.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>AFH</ns0:cell><ns0:cell>FBH</ns0:cell><ns0:cell>SAH</ns0:cell><ns0:cell>OFH</ns0:cell></ns0:row><ns0:row><ns0:cell>Species Richness</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>23</ns0:cell></ns0:row><ns0:row><ns0:cell>Total individuals</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>encountered</ns0:cell><ns0:cell>9213</ns0:cell><ns0:cell>1455</ns0:cell><ns0:cell>3435</ns0:cell><ns0:cell>6497</ns0:cell></ns0:row><ns0:row><ns0:cell>Simpson</ns0:cell><ns0:cell>0.1148</ns0:cell><ns0:cell>0.3871</ns0:cell><ns0:cell>0.2423</ns0:cell><ns0:cell>0.1467</ns0:cell></ns0:row><ns0:row><ns0:cell>Shannon-Wiener</ns0:cell><ns0:cell>2.822</ns0:cell><ns0:cell>2.153</ns0:cell><ns0:cell>1.329</ns0:cell><ns0:cell>2.392</ns0:cell></ns0:row><ns0:row><ns0:cell>Margalef</ns0:cell><ns0:cell>2.936</ns0:cell><ns0:cell>1.836</ns0:cell><ns0:cell>0.653</ns0:cell><ns0:cell>2.294</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49115:2:0:NEW 10 Aug 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49115:2:0:NEW 10 Aug 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Editor comments (Joseph Gillespie) Dear Dr. Hazarika and colleagues: Your manuscript seems to contain several inaccuracies, ambiguities and false statements. Also, there are many spelling mistakes and other grammatical issues. Please enlist the help of an English expert. We have modified this as recommended. Of more concern, please address the problems raised by reviewer 2 with your chemical analyses! Some figures and Tables appear to contain many errors and must be fixed (or removed). It might be that your manuscript will be in more publishable form if you restrict the work to the ecological findings and conclusions regarding insect uses as food. Please consider this. However, please carefully revise your work and cull inconsistencies (e.g., you report one species of edible Coleoptera in the Abstract and most of the text, but then discuss two species later). The biochemical analysis part has been removed and the study has been restricted to only ecological findings, as recommended by the Editor. We have tried our best to rectify errors in the manuscript and hope that this will be publishable for you. Reviewer 1 Basic reporting All recommended changes have been appropriately done. Experimental design The experimental design has been improved. I accept the changes and do not recommend any further changes. Validity of the findings I accept the revisions done. Comments for the Author I accept the revisions made and recommend the paper for publication. We are indeed grateful for these comments and feel encouraged. Reviewer 2 Abstract L29: delete ‘intend to’ L30: already criticized the first time, write “…located in Assam (India).” L34: not nine orders, but eight ! The next sentence actually lists them. L39: “…were carried out to record….their possible role as nutrient inputs.” L41: delete ‘an’ and write “…sustainable collecting and rearing methods, emphasizing…” These have been corrected accordingly. Introduction L52: “As such, they arouse interest not only…” L53: “ A dimension of their existence not to be overlooked pertains to…” L55: “…insects form or formed a part of…” L57: “…is nowadays no longer a traditional or common …, except for some…” L64: many Asian nations… L67 “…found from China’s South to northern Australia…” L70: delete ‘by its people’. “Approximately 50 insect species are consumed in the north and about 14 species in the southern part of Thailand…” L72: delete ‘may’ L73: “…religion and place they call home.” L75-77: Delete, because that sentence is totally out of place with no connection to previous or following sentences. L82: delete ‘of Arunachal Pradesh’ L85: write “…by the Galo and Nyishi tribes.” LL89: NOTE: only proteins and vitamins? Not also lipids and minerals and perhaps fibre and carbohydrates? We have duly applied these changes. Material & Methods L124: Temperatures range from… L137: Sweep nets were used for collecting grasshoppers… L138: naturally hide in low grass NOTE: why ‘naturally’? Can they also hide unnaturally? L139¨netting was normally carried out during daytime, BUT see Line 135, where it says during the early hours 0500-0900 ! L154: NOTE: you write grasshoppers and beetles were collected by hand, but on Line 137 it says grasshoppers were collected by sweep netting ! L158-159: explain or use references to explain the terms ‘Jakoi’ and ‘Saloni’. NOTE: what kinds of waterbodies were collections made from and when and how often did that take place? E.g., rivers, swamps, brooks, ponds? L169: are alcohol and formaldehyde not “standard methods”? L171: write “…Shillong, Meghalaya (India). L185: is it ‘Borthakur’ or ‘Barthakur’ as in the references? L188: delete ‘also’ NOTE: these ecological indices are useful. I like them. L216: 2672 respondents from 30 villages, BUT what would interest the reader is the number of respondents per tribe studied! These has been modified/changed as recommended. Biochemical analyses (use the plural ‘analyses’ not singular ’analysis’. NOTE: this goes for ALL the analyses: how many replicates were carried out! From which part of the insect body was the tissue taken: muscle tissue, fatbody, gonads, brain??? L223: do you really mean just ‘estimated’ or do you mean ‘determined’? NOTE: where is the detailed description on how you obtained data on the various amino acids and their amounts? L236: “…was done according to the …” L245: NOTE: for lipid analyses how were omega-3 and omega-6 fatty acid amounts obtained? L254: How the specimens were prepared for mineral analyses is not explained properly. The section pertaining to biochemical analysis has been removed from the manuscript. Results L265: the order Isoptera no longer exists; termites are now with Blattodea! Correct also Table 2 and 4. L271: Table 2, table 4, figure 4 and also the text of the ms contains spelling errors. Please correct: Mecopoda elongata, Hieroglyphus banian, Acheta domesticus, Antheraea assama, Oryctes rhinoceros ! L278: the beetle Hydrophilus olivaceus, mentioned here, occurs in no table or figure! This was an inadvertent error. We apologise for this. Instead, it says in several places that only one species of beetle (Oryctes rhinoceros) was considered edible (and probably only the grubs and not the adult, but that seems to go unmentioned). L287: Hieroglyphus banian L296: “…the order Orthoptera…” L295: “…followed by Coleoptera (8.02% while the Odonata has the least relative abundance” NOTE: this cannot be right as you have only one species of beetle. Explain. FIGURE 4 is inadequate: what about the x-axis? There needs to be a scale or some numbers. Furthermore you write Mantis religiosa is most abundant in the monsoon season, but Fig 4 suggests that it is Periplaneta! In winter Vespa affinis has the highest ‘availability’ (really? Isn’t Periplaneta equally abundant?) Figure 6: meaningless unless you explain which tribe this refers to and what the little numbers in the columns mean. For ALL the figures and tables you have to have a brief text, a ‘figure legend ’to explain what the figure or Table contains. We have applied these recommendations. The results, nicely summarized in Fig. 7: but for which tribal group is this applicable? NOTE: In figures 9 and 10 you are using ‘common names’ like house cricket, crickets, eri and even ‘water beetle’ (!), which did not appear at all until then, not even in Table 2. Please check ALL of your figures and Tables. BE CONSISTENT ! Do NOT use ‘common names’ in some tables and scientific names in others, but stick to the scientific names in all tables and figures ! Figures 9 and 10 are wholly inadequate. You can’t use common names here (like grasshoppers, small, brown, large, etc) when in Table 2 and Fig 4 you use scientific terms! In 9 A – E the sequence of the insects is the same, but in F it is different: why? You need an explanatory legend to say that the values entered are based on analyses of 100 mg. Even so, the data are more than dubious: magnesium content is as high as carbohydrate (see lengths of the bars!): it can’t be! Another example: for mole cricket lipid you state 0.055, BUT omega-6 content is 0.24781: impossible! (I earlier mentioned that you did not provide information on how you measured omega-3 and omega-6 fatty acids! You do not mention on how many replicates the data are based! You are listing figures with up to 5 decimals behind the comma, which is ridiculous: you are dealing with mg !!! Using with 5 digits behind the comma you are in nanogram range! I feel you ought to ditch (= delete all the data in Fig 9 as they are unreliable, which cannot be good for you and your institute’s reputation. Likewise Figure 10 (incidentally, suddenly there is a water beetle again in addition to the rhinoceros beetle!): the data are all wrong unless fully explained in a figure legend how you constructed this figure. According to the figure, which lacks units and numbers, calcium and magnesium content (taken together) is higher than lipid !? That whole figure should also be ditched as it is unreliable. By the way, do you say anywhere in the text which amino acids you refer to as ‘essential’ and how you determined amino acids qualitatively and quantitatively? The section on biochemical analysis has been entirely removed. Discussion First paragraph, spelling: Mecopoda elongata, Hieroglyphus banian, Acheta domesticus, Gryllotalpa africana. “and so on” does not sound very elegant; perhaps you could write “and some others”. L333-334: “…insects are mainly those of the Adivashis… Sarania. A section…” L414: “…does not agree…” is misleading. You need to write “…(2019), but in Ethiopia young people are less inclined to eat or even taste insects (Ghosh et al. 2020).” These recommendations have been applied. L420-421: you write “…are very rich in carbohydrates. Our study verifies this fact as we can see from Figure 7 that the insects are rich in protein, but have minimal carbohydrates.” You just wrote in the first half of the sentence “rich in carbohydrates’ and now it’s “minimal carbohydrates’. That is another one of those contradictions in your ms. Besides, you refer to Fig. 7, but Fig. 7 shows “Reasons for practicing entomophagy”! L427: you write about a “moderate presence of magnesium”, but on Line 319 you write magnesium content is minimal! L449: you need a reference here to back up your statement! L451: why “also”? In fact, there are many places you use “also” and frequently it is not clear why ‘also’. For example ‘also’ on Line 477 and many others. 459-473: that is a terrible paragraph, muddled, inconsistent and about beetles that are either totally inedible (like ladybirds) or are not mentioned in this ms, because you made the earlier statement (n the abstract as well) that there was only one edible coleoptera species, namely Oryctes rhinoceros. I cannot even start correcting this paragraph. Unless completely rewritten, the paragraph should be dropped. L478: lipid content of larvae… Which larvae? L481: you do not examine fat content of pupae and larvae of edible Coleoptera of your one species of beetle. If you want to use a reference to show differences in fat (and other contents) between larvae, pupae and adults use this reference: Ghosh et al.2016 “Nutritional value and chemical composition of larvae, pupae, and adults of worker honey bee, Apis mellifera ligustica as a sustainable food source” Journal of Asia-Pacific Entomology 19 (2016) 487–495. The biochemical analysis part has been deleted entirely. L502/3: Write “Rearing insects can result in environmental benefits.... Insects can impact organic farming and help to reduce…emit fewer greenhouse gases….compared with conventional livestock…” L512: Our study confirms… L514”…possibly reduce the insects’ costs. ….With a wider insect diversity, ….of people should improve while…. L516: ‘fish’? Which fish? There are more than 40,000 species of fish with very variable fatty acid contents. L523: “…domesticated since they are of high…” L525: delete ‘immensely’ L526 ?...help exploiting new… L530-537: cite Gahukar, R.T. Edible insects collected from forests for family livelihood and wellness of rural communities - a review. Global Food Security 2020, Doi.org 10.1016/j.gfs.2020.100348. These changes have been applied. Conclusions L541: Write “In this study we recorded edible insect diversity…” L544: not nine, but eight orders of insects. These recommendations have been adhered to. References: I did not check the references for accuracy and leave that to the authors. This section has been cross checked for error. Figures and Tables Already commented on in detail (see above text): all need to be modified and some should be dropped. Figure 1: ok Figures 2 and 3 are unnecessary. Fig. 4 needs to be improved (see earlier comments above); Gigs 5-8 should be improved (see earlier comments above) Figure 3 has been removed. Figure 4-8 has been modified according to the comments. Figures 9 and 10 contain inaccurate data and should be deleted. These figures have been deleted. Table 1: ok Table 2: needs to be corrected; Table 3: ok; Table 4: scient. Names to be corrected; The tables have been corrected. Names have been rectified. Table 5: completely false data (e.g. termite and cockroach calcium data are almost twice that of protein! Wasp larvae twice as much magnesium as lipid! All of these data are completely wrong. Delete this terrible table as quickly as possible!!! This table has been deleted. We apologise for this. The data was computed by a junior research assistant. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Insects not only play a significant role in the ecological process of nature but since prehistoric times have also formed a part of the human diet. With a still growing population and skewed demographic structures across most societies of the world, their role as nutrient-rich food has been increasingly advocated by researchers and policymakers globally. In this study, we examine the edible insect diversity and entomophagy attitudes of ethnic people in Manas National Park, a UNESCO Natural World Heritage Site, located in Assam (India). The study involved a field investigation through which the pattern of entomophagy and the attitude towards insect-eating was studied. Following this, we examined the edible insect diversity and abundance at different sampling points. A total of 22 species of edible insects belonging to fifteen families and eight orders were recorded from different habitat types. Out of these 22 species, Orthopterans showed a maximum number of 8 species followed by Hymenoptera (4), Hemiptera (3), Lepidoptera (2), Blattodea (2) and 1 species each from Coleoptera, Odonata, and Mantodea. Dominance, diversity, and equitability indices were computed along with the relative abundance of the insects concerning four habitat types. Aspects of the economic significance of entomophagy were also observed during the field investigation. To manage insects in the interest of food security, more attention should be given to sustainable collecting and rearing methods emphasizing their economic, nutritional, and ecological advantages.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Insects are the most diverse and abundant forms of life and constitute a primary component of the total faunal biodiversity on Earth. They play vital roles in an ecosystem that includes soil turning and aeration, dung burial, pest control, pollination, and wildlife nutrition <ns0:ref type='bibr' target='#b0'>(Bernard &amp; Womeni, 2017)</ns0:ref>. Besides providing ecological services, insects are also an important source of protein, fat, carbohydrate, and other nutrients. As per the current scientific literature, there are 1.4 million species of insects worldwide which are an intrinsic part of the Earth's ecosystem. As such, they arouse interest not only with their immense species richness but also with their species variety and their role in energy flow. A dimension of their existence not to be overlooked pertains to the fact that they have formed a part of human diets since prehistoric times. Evidence points to at least 113 countries where insects form or formed a part of human diets in one way or the other. This practice of consuming insects as part of the human diet is referred to as entomophagy <ns0:ref type='bibr' target='#b16'>(Evans et al., 2015)</ns0:ref>. Insect-eating or entomophagy is nowadays no longer a traditional or common practice in most countries, except for some in South-and South-East Asia, Latin America, and Africa <ns0:ref type='bibr' target='#b41'>(Rumpold &amp; Schluter, 2013)</ns0:ref>, where more than 2,000 insect species are consumed <ns0:ref type='bibr' target='#b21'>(Jongema, 2015)</ns0:ref>. Given the shortfalls of the 'green revolution' and high risk of food insecurity in developing and underdeveloped nations, the use of insects as a potential source of food for the burgeoning human population had been advocated by Meyer-Rochow (1975), a suggestion that has been gaining interest among researchers, entrepreneurs and policy makers worldwide ever since. Insect farming is popular in many Asian nations for food, feed, and other purposes <ns0:ref type='bibr' target='#b46'>(Zhang et al., 2008)</ns0:ref>. Weaver ants (Occophylla smaragdina), whose chemical composition and value as a human food item is well known are widespread in the Asia-Pacific region and are found from China's south to northern Australia and as far west as India. Although edible insects are not yet of much commercial value, some economic and marketing data on edible insects in Asia and the Pacific are available scarce <ns0:ref type='bibr' target='#b22'>(Johnson, 2010)</ns0:ref>. Approximately 50 insect species are eaten in Thailand's north and about 14 species are eaten by people in southern Thailand <ns0:ref type='bibr' target='#b40'>(Rattanapan, 2000)</ns0:ref>.The insect-eating habits in various regions depend on the indigenous populations' cultural practices, religion and the place they call home. But insects used as emergency food during natural calamities or other national contingencies as well as for their organoleptic characteristics can also be important <ns0:ref type='bibr' target='#b14'>(Dumont, 1987)</ns0:ref>.</ns0:p><ns0:p>The North-Eastern part of India has diverse ethnic groups that have a unique culture of food intake with insect-eating mostly prevalent amongst rural tribal people of the region which have a long-cultured history. A total of 81 species are eaten in Arunachal Pradesh by the Galo and Nyishi tribes <ns0:ref type='bibr' target='#b4'>(Chakravorty et al., 2011)</ns0:ref>. Odonata were consumed the most followed by Orthoptera, Hemiptera, Hymenoptera, and Coleoptera.</ns0:p><ns0:p>Scientific reports indicate insects to be significant sources of not only proteins and vitamins, but also lipids, minerals, fibre and carbohydrates. Insects possess a viability of providing daily requirements of these nutrients in most developing countries <ns0:ref type='bibr' target='#b3'>(Bukkens, 1997;</ns0:ref><ns0:ref type='bibr' target='#b15'>Elemo et al., 2011)</ns0:ref>. For instance, edible aquatic beetles play an important role in the nutrition and economy of the rural population in Asian, Latin American and African nations <ns0:ref type='bibr' target='#b25'>(Macadam &amp; Stockan, 2017)</ns0:ref> and are popular in Manipur <ns0:ref type='bibr' target='#b43'>(Shantibala et al., 2014)</ns0:ref>. It should be noted that the diversity and abundance of insects in different habitat types have an observed correlation with the entomophagy attitude of a particular region. Therefore, research indicates the importance of exploiting insect diversity effectively through insect farming to avoid global problems associated with dependency on a limited number of insect species as experienced with some food animals and crops.</ns0:p><ns0:p>In this research article, we have made an effort to study the edible insect diversity of a UNESCO Natural World Heritage Site, located in the Indo-Burmese biodiversity hotspot. Regional entomophagy was studied through a field investigation. We made an effort to determine the degree to which the ethnic people use insects in their diet and which species they consume. Recording seasonal abundance and availability of edible species as well as evaluating the role that entomophagy could possibly play as a measure of food security in the region, were further aspects of this study.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Study Area</ns0:head><ns0:p>The Manas National Park (MNP), located at 26.6594&#176; N, 91.0011&#176; E, was declared a UNESCO Natural World Heritage Site (WHS) in 1985 (Figure <ns0:ref type='figure'>1</ns0:ref>). Renowned for its array of rich, rare, and endangered wildlife not found anywhere else in the world, the faunal diversity of MNP includes the Pygmy Hog, Golden Langur, Hispid Hare, Assam roofed turtle and so on. Located at the Himalayan foothills of India, MNP is shares land territory with Bhutan where it is known as the Royal Manas National Park. The park is composed majorly of grassland and a forest biome. It is covered by the Brahmaputra Valley semi-evergreen forest vegetation along with the Himalayan subtropical broadleaf forests and the Assam Valley semi-evergreen alluvial grassland vegetation. This renders MNP a region of rich and abundant biodiversity. Major trees include the Bombax ceibar, Gmelina arborea, Bauhini purpurea, Syzygium cumin, Aphanamixis polystachya, Oroxylum indcum, etc. The climate is sub-tropical with a warm and humid summer, followed by a cool and dry winter. Temperatures range from 10 0 C to 32 0 C. The park has more than 58 fringe villages directly or indirectly dependent upon it, distributed across three ranges: Bansibari, Bhuiyaparaa and Panbari. The village Agrang lies at MNP's core while most are located in its buffer zone. Spread over the State of Assam's Barpeta and Bongaigaon districts, the tribal population in its fringe areas predominantly include Bodos and Rabhas among which the practice of insect eating and rearing are widespread.</ns0:p></ns0:div> <ns0:div><ns0:head>Insect sampling</ns0:head><ns0:p>Insects were collected using entomological nets, beating tray, water traps, or through digging and handpicking. The local people of the study area helped in the collection process. Insects were usually collected during the early hours of the day (0500-0900 hours). The flying insects were collected via entomological nets at a time when they were active (midmorning/late afternoon). Sweep nets were used for collecting grasshoppers and other insects which hid in low grass-or herb-dominated vegetation and in small shrubs. Netting was normally carried out during early hours of the day as we could not collect nocturnal taxa in this way. In order to catch nocturnal species, we used light traps. Nocturnal arthropods like species of moths and beetles are easily attracted towards artificial light sources. Light traps have therefore been widely used in nocturnal insect sampling. A high-power CFL bulb was arranged in front of a white cloth for trapping nocturnal insects. Generally, a bowl filled with water was placed under the light sources in the evening, after rainfall, to attract termites. The light attracted the reproductive termites which came out for nuptial flights and were trapped in the water or collected by hand from the water to prevent them from escaping. Light trapping was used widely in case of agricultural habitat type and open field habitat type. Beating trays were used to collect insects such as Lepidoptera and Hymenoptera. Shrubs and small trees were sampled through commonly used beating tray sample method. Moreover, the red weaver ants were harvested by plucking the nest from the tree and dropping it in a bucket of water before being sorted out for consumption. The soil dwelling edible insects were collected by digging with the help of spades. Besides sweep netting, large insects such as grasshoppers and beetles were also collected by hand which were caught early in the morning or in the evening when they were less mobile due to their low body temperature. Mole and field crickets were dug out of holes. We used the hand-netting technique to collect the aquatic insects along with other local traditional equipment like Jakoi, Chaloni, etc. The Jakoi is a species of wicker work shovel that is either dragged along the bottom or placed on the water bed to catch the aquatic insects which take refuge in it when the weed is trampled. It is prepared with bamboo slips, which are locally known as 'dai'. 'Jati' bamboo is specially used for making this particular implement. Chaloni is a bamboo strainer used to separate insects from collected water. Long handled aquatic net was used to collect insects that live on the water surface. Many adult insects living on the surface were predators, so they were removed from the net using forceps directly into a collection container. The kick-net method which is a process where insects are collected by dislodging them from the substrate (habitat) was also used. The organisms that were dislodged by the disturbance were collected on the net. For preservation of specimens, both dry and wet preservation methods were followed. For dry preservation, the specimens were preserved using pins in insect cabinet box and were mainly sun-dried. Soft-bodied insects were preserved using 70% ethyl alcohol. Besides, some hardbodied edible insects were preserved using 2-3% formaldehyde <ns0:ref type='bibr' target='#b17'>(Ghosh &amp; Sengupta, 1982)</ns0:ref>. Identification was done later by comparison with other specimens. Some were identified in the Zoological Survey of India, Shillong, Meghalaya (India).</ns0:p><ns0:p>Sampling was done from 20 chosen sites located around MNP during the period 2018 (June)-2019 (June). The permission for conducting the field study was obtained from Office of the Principal Chief Conservator of Forests (Wildlife) and Chief Wildlife Warden, Government of Assam, India vide No. WL/FG31/ResearchStudyPermission/19th Meeting/2019. The remaining methodology of the study is outlined in Figure <ns0:ref type='figure'>2</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Edible insect density, diversity and abundance</ns0:head><ns0:p>Studying the diversity required us to divide each sampling point into four different habitat types, namely, open field habitat (OFH), forest/backyard forest habitat (FBH), swampy area habitat (SAH), and agricultural field habitat (AFH). The entire sampling area amounted to approximately 842 km 2 . Insects were recorded within quadrates (2m x 2m dimension) established in the habitat type and monitored for four seasons, namely, pre-monsoon (March, April and May), monsoon (June. July, August and September), retreating monsoon (October and November), and winter (December, January and February) <ns0:ref type='bibr' target='#b1'>(Borthakur, 1986)</ns0:ref>. The Shannon-Wiener index (H') for diversity, Simpson index (D) for dominance, and Margalef index for species richness in the four selected habitat types were computed. Order-wise relative abundance and species-wise abundance in the different habitats were also computed. The descriptions and mathematical expressions are outlined below. The indices were estimated using PAST (v.3.26) <ns0:ref type='bibr' target='#b19'>(Hammer et al., 2019)</ns0:ref> and SPSS (v.23). Shannon-Weiner index (H') determines the diversity of insect species in a particular habitat type. The higher the H' value, the greater is the diversity. Expression (i) gives the formula. H' = -&#8721; p i ln p i &#8230;&#8230; (i) Where p i = proportion of individuals found in i th species Simpson's index (D) defines the probability of drawing any two individuals at random from a very large community of the same species. If D increases, we can say that diversity has decreased. This index, defined by expression (ii), accounts for both aspects of diversity, i.e., richness and evenness.</ns0:p><ns0:formula xml:id='formula_0'>D = &#8721; &#8230;&#8230; (ii) ( &#8721;&#119899; &#119894; [&#119899; &#119894; -1] &#119873; [&#119873; -1] )</ns0:formula><ns0:p>Where, n i = individuals in i th species, N = total number of individuals Margalef's index (R) gives a precise idea about a species' richness. It attempts to compensate for the effects of sampling by taking a ratio of species richness by the total number of individuals in a sample, given in expression (iii). R = (S-1) / lnN Where, S = total species in a community, N = total number of individuals in that community.</ns0:p></ns0:div> <ns0:div><ns0:head>Entomophagy study</ns0:head><ns0:p>Understanding the entomophagy attitudes and distribution among the tribal population near MNP required conducting a survey. Methods included interactions with the villagers through questionnaires, field surveys, and a market survey. The villages were selected randomly and were surveyed once per season for the whole year. Questions were asked to a mixed group of ethnic people which included individuals from all sections of the society. The market survey helped record the economic importance of these insects for the local economy. Questions pertained to the number of insects sold per week/month, their market prices, and how popular were the insects in ethnic cuisine. Overall, the questionnaire survey included 2672 respondents from 30 villages of which 981 were from the Adivashi tribe, 695 were Bodos, 436 were Saranias, 422 were Rabhas and 138 were non-tribal individuals. Written consent was obtained from the respondents during the field interviews.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Table <ns0:ref type='table'>1</ns0:ref> shows the order-wise number of edible insects found in the study area. In MNP, the order Orthopteran recorded the maximum number with 8 species, followed by Hymenoptera with 4 species. The order Hemiptera was found to have 3 species followed by Lepidoptera and Blattodea with 2 species each. The order Coleoptera, Mantodea, and Odonata accounted for 1 from each species and family. A total of 9,213 edible insects were recorded from AFH, 1455 in FBH, 3435 in OFH and 6497 individuals in SAH, during the field observation. No common abundant species was found in a single habitat. Most of the insects were found in two or three habitats during the study period.</ns0:p><ns0:p>Table <ns0:ref type='table'>2</ns0:ref> showcases the types of edible insects consumed by the ethnic people. In this table, the local and common name (in Bodo), the scientific name with their taxonomy, and their seasonal availability, edible parts, and mode of consumption are tabulated. Common names in Bodo have been displayed in Table <ns0:ref type='table'>2</ns0:ref> as they were more popular among the local people. Seasonal availability was maximum during June to September, gradually reducing towards the winter season. Species of the order Orthoptera were most abundant in May to September, whereas, Coleopterans were usually available from April to September. Insects belonging to the Hemiptera and Hymenoptera were found to be restricted to the period lasting from April to October, whereas, Mantodea were available from June to October. Some edible insects like Lethocerus indicus, Periplaneta americana and Gryllotalpa africana were found to be available throughout the year, but in the winter, they were less abundant than during the pre-monsoon and monsoon season.</ns0:p><ns0:p>Simpson index (D) for dominance, Shannon-Wiener index (H') for diversity, and Margalef index for evenness/equitability were calculated in the four selected habitats (Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>). Further, species abundance was found to be the highest in Chondracris rosea with 18.64, followed by Gryllotalpa africana with 8.50 in AFH. In FBH, the highest species abundance was found in Hieroglyphus banian with 8.91, followed by Polistis olivaceus with 5.20. In OFH, Gryllus bimaculatus was the highest abundant species with 5.1, followed by Lethocerus indicus with 3.17. Table <ns0:ref type='table'>4</ns0:ref> shows the relative abundance of the edible species in selected habitats.</ns0:p><ns0:p>Chondracris rosea has the highest relative abundance (11.50%) followed by Choroedocus robustus (8.92%), the least relative abundant insect species includes Laccotrephes ruber (0.42%).</ns0:p><ns0:p>Seasonal variation in abundance of edible insects (Figure <ns0:ref type='figure'>3</ns0:ref> Further, the proportion of ethnic communities practicing entomophagy in MNP has been graphically represented in Figure <ns0:ref type='figure'>4</ns0:ref>. As mentioned before, the 2672 respondents to our survey included 981 individuals from the Adivashi tribe, 695 from the Bodo tribe, 436 from the Sarania tribe, 422 from the Rabha tribe and a total of 138 individuals were non-tribal. We also categorised the respondents of our survey who considered the insect-eating habit favourable, into four age-groups, namely, less than 60 years, between 40-60 years, between 20-40 years and greater than 20 years (Figure <ns0:ref type='figure'>5</ns0:ref>). Consumers in the 20-40 group responded highly favourably while those in less than 20 years group responded less favourably owing to different variations of entomophobia. There are various reasons for eating insects which were found among the different ethnic groups during the questionnaire survey (Figure <ns0:ref type='figure'>6</ns0:ref>). The different modes of insect consumption have been presented in Figure <ns0:ref type='figure'>7</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head>Edible insect diversity and abundance</ns0:head><ns0:p>As part of this study, we find that species of the order Orthoptera are popular among the ethnic people for consumption purposes. The edible species majorly include both short and long-horned grasshoppers (Eupreponotus inflatus, Choroedocus robustus, Chondracris rosea, Mecopoda elongata and Hieroglyphus banian), field crickets (Gryllus bimculatus), house crickets (Acheta domesticus) and mole crickets (Gryllotalpa Africana). Other species include potter wasp (Vespa affinis) and paper wasp (Polistis olivaceus), Indian honey bee (Apis indica) and rock bee (Apis dorsata), giant water bug (Lethocerus indicus) and some others. The ethnic (tribal) communities consuming these insects were mainly those of the Adivashis, followed by the Bodo, Rabha, and Sarania. A section of the non-tribal population also consumed insects as part of their diets.</ns0:p><ns0:p>Species diversity, richness, and evenness gives an idea about the variety and diversity of species in the study sites. The most commonly used dominance and diversity indices in ecology are the Simpson index and the Shannon-Wiener index. Simpson index is used to assess the dominance but fails to provide an idea about species richness. Shannon-Wiener index is expected to determine both diversity characteristics (evenness and richness) but does not provide any information on rare species which, however, are very important in studies of biodiversity. Our results show that the species dominance is highest in FBH (0.3871), followed by SAH (0.2423), OFH (0.1467), and AFH (0.1148). On the other hand, species diversity, as per H', was highest in AFH (2.822), OFH (2.392), FBH (2.153) and SAH (1.329). This establishes the fact that as insect diversity decreases, their dominance should increase. In MNP, this can be noticed for the forest habitat. Further, this result is corroborated by the Margalef index which is found to be highest for AFH (2.936), OFH (2.294), FBH (1.836), and SAH (0.653).</ns0:p><ns0:p>Notably, forest habitats are the prime source of edible insects for local people. This adverse finding in the case of FBH may be attributed to various reasons. Decreasing forest cover, changes in vegetation type, adverse climatic conditions, or indiscriminate collection and consumption of edible insect. These directly affect the insect diversity and rejuvenation of insect species. In the case of MNP, high temperatures, inadequate rainfall, and vegetation cover may also have influenced the population density of these edible insects. Notably, the overall climate of Assam has warmed by over 0.5 0 C for the past decade which is expected to rise up to 2.2 0 C by 2050.</ns0:p><ns0:p>It should be noted that Shannon-Weiner and Simpson diversities increase as richness increases for a given pattern of evenness, and increase as evenness increases for a given richness, but they do not always follow the same trend. Simpson diversity is less susceptible to richness and sensitive to evenness than Shannon index which, in turn, is more receptive to evenness. At the other extreme, the Berger-Parker index, depends entirely on evenness-it is simply the inverse of the proportion of individuals in the community that belongs to the single most common species, while the other indices (Margalef) are dependent on the number of species. Apart from the diversity and distribution patterns for insect taxa, interactions between insect groupings and plant groups are another important topic requiring urgent research attention. This is because plants provide key habitat parameters for many insect species ranging from shelter to breeding sites. This has not been covered under this study and could be pointed out as its limitation.</ns0:p><ns0:p>Our analysis of seasonal diversity of edible insect species shows that the diversity of the edible insects was greater during monsoon and pre-monsoon Further, anthropogenic disturbances and deforestation are seen rampant in the fringes of MNP. Ground-level evidence glaringly shows that villagers are converting forest lands into agricultural fields. This is an outcome of the burgeoning population of Assam where the human population density is 398 persons per km 2 which is way above the global density of 14.7 persons per km 2 . Such anthropogenic pressure <ns0:ref type='bibr' target='#b33'>(Morris, 2010</ns0:ref>) is bound to destroy species composition, community structure, and insect diversity. This calls for urgent ecosystem restoration to sustain the distribution pattern and abundance of edible insects.</ns0:p><ns0:p>In the regional context, a study of the diversity of insects consumed by the people in Dhemaji District of Assam revealed that a majority of 14 species of insects were used as food <ns0:ref type='bibr' target='#b12'>(Doley &amp; Kalita, 2011)</ns0:ref>. 40 species of edible insects were recorded in Karbi Anglong District of Assam corroborated by <ns0:ref type='bibr' target='#b20'>Hanse &amp; Teron (2012)</ns0:ref>. Another study involving the ethnic community of the Bodos, recorded 25 species of local insects, belonging to eight orders and fourteen families which are consumed as food <ns0:ref type='bibr' target='#b36'>(Narzary &amp; Sarmah, 2015)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Entomophagy, food security, and its economic implications</ns0:head><ns0:p>The field investigation revealed that most of the respondents found insects to be tasty and delicious (59%), while a section found them to be an inexpensive source of food (17.1%).</ns0:p><ns0:p>Traditional medicinal food is also one of the reasons why edible insects are collected (Meyer-Rochow, 2017). This indicates the substantial preference of insects in the food habits of people and underscores their importance in the allocation of household costs and sustaining food security. This can be corroborated with the findings of <ns0:ref type='bibr' target='#b34'>Mozhui et al. (2017)</ns0:ref> for Nagaland, where the ethnic people considered insects as a regular food source, rather than an emergency food item. The local people favoured eating insects mostly by frying, roasting, or smoked. This emphasises the wide variety of ways through which insects may be consumed. However, a low percentage of respondents claimed them to be easily available food as collecting them is rather difficult compared to conventional livestock. This calls for the development of an insect farming industry as well. Further, a large number of respondents in the 20-40 years and 40-60 years age bracket favoured eating insects due to the various reasons as in Figure <ns0:ref type='figure'>5</ns0:ref>. Entomophagy, as such, is highly popular among the youth population. However, in Ethiopia young people are less inclined to eat or even taste insects <ns0:ref type='bibr' target='#b18'>(Ghosh et al. 2020</ns0:ref>).</ns0:p><ns0:p>Besides, the nutritional significance of edible insects has been well established by current scientific literature. It is observed that nutrients vary widely across insect species wherein some are rich in protein and lipids while others are rich in mineral content. <ns0:ref type='bibr' target='#b6'>Chen et al. (2009)</ns0:ref> note that edible insects are rich in protein and fat, but sometimes may lack carbohydrate content. However, insects like bees, honeypot ants, etc., are very rich in carbohydrates. Besides, <ns0:ref type='bibr' target='#b7'>Collavo et al. (2005)</ns0:ref> note that the presence of high essential amino acids is a major reason for insects having high-quality protein. Majority of the population near MNP belong to low-or lowermiddle-income category people. Their demography is skewed towards ethnic backgrounds and hence, the economy is highly underdeveloped. Rearing livestock and maintaining animal husbandry practices, require a substantial amount of money. The piggery sector is robust in this area. Practicing this requires large amounts of land and also involves substantial capital. However, the nutritional benefits gained from it are not enough to compensate for the effort. Also, insects generally meet the WHO recommendation for amino acid content with nymphs being their most abundant source. Coleoptera has a higher amount of protein than most livestock. More importantly, edible insects bear many non-health related benefits related to environmental and financial costs than livestock.</ns0:p><ns0:p>On the other hand, it is important to note that many edible insects require higher energy in culture and contain higher sodium and saturated fat content <ns0:ref type='bibr' target='#b37'>(Payne et al., 2016)</ns0:ref>. This diminishes their worth as alternative nutrient sources to fight nutrition-related diseases. This is because the saturated fat content of edible insects is not recommended for people with heart disease risk, obesity, or metabolism issues. Further, some beetle or butterfly species produce dangerous toxins that are harmful to human health. Such species must be identified before being consumed as food <ns0:ref type='bibr' target='#b2'>(Blum, 1994)</ns0:ref>. However, insects have very high micronutrient content which can be extracted or consumed at a third of the cost than other food products.</ns0:p><ns0:p>MNP is a highly flood-ravaged area with untimely floods occurring during the sowing period. Floods in 2019 affected over a million people of Assam with a majority from the Baksa District (where MNP is located) and the adjacent district of Barpeta. This frequently uproots the livelihood of the local people rendering them vulnerable to high food insecurity. It should be noted that these ethnic people otherwise have decent livestock and animal husbandry resources. With floods, they tend to lose livestock in a large-scale manner. At this juncture, edible insects can play a significant role in maintaining the nutritional content of their diet intact.</ns0:p><ns0:p>Animal protein is superior to plant; therefore, the best protein supplements should include some animal protein. Thus, insects may provide for good quality protein ingredients to produce a high standard protein supplement for the food industry <ns0:ref type='bibr' target='#b45'>(Ssepuuya et al., 2017)</ns0:ref>. It was also found that the lipid content of common insect larvae (37.87%) are higher than the soybean (14.60%). From the energy point of view, lipids are important because one gram of lipid provides more than 9 kcal of energy when oxidized in the body. Lipids are structural components of all tissues and indispensable in cell membranes structure and cell organelles <ns0:ref type='bibr' target='#b13'>(Drin, 2014)</ns0:ref>. The fat content of pupae and larvae of edible Coleoptera is higher than that of the adult insect. These results coupled with the significant role played by edible insects in the local food habits make it undeniable that the desirability of food security in their context is valid as they can be considered as viable sources of macro-and micro-nutrients for human beings.</ns0:p><ns0:p>Edible insects such as beetles have been a rich source of proteins and also other nutrients for a long time and have been preferred over traditional livestock by several communities all over the world <ns0:ref type='bibr' target='#b24'>(Losey et al., 2006)</ns0:ref>. For instance, indigenous communities of Mexico are involved in buying and selling edible insects, which are also processed and sold in urban markets. Insects have low-fat content and as such, there has been a high worldwide demand for edible insects. Additionally, aquatic insects are commonly exported from South Asian nations to the United States which are prepared and served in high-end eateries. The estimated size of this market was approximately USD 40 million in 2015. Moreover, in the Lao PDR, insects can be found in markets as ready-to-eat snacks or fried with lime leaves (Meyer-Rochow et al., 2008). Concerning agriculture, beetles have been found to contribute more than a billion dollars in environmental and economic benefits globally. This comes from the fact that they recycle cattle manure, thereby, improving pasture growth, yielding high agricultural benefits, and thus, augmenting the livelihood of agriculturalists. In the context of MNP, a gap in the literature has been observed wherein comprehensive studies on beetles' economic benefits haven't been witnessed.</ns0:p><ns0:p>Rearing insects can result in environmental benefits with respect to food and feed. Insects can impact organic farming while helping to reduce environmental contamination, as they emit fewer greenhouse gases and ammonia, compared with conventional livestock <ns0:ref type='bibr' target='#b8'>(Dangles &amp; Casas, 2019)</ns0:ref>.</ns0:p><ns0:p>Given the inclination of Bodos and other tribes in eating insects and rearing them to an extent, economic policies must target rearing practices of insects, rather than solely focussing on animal husbandry. Therefore, several strategies could be employed that can help in efficiently and sustainably making use of such natural biodiversity in augmenting the societal income and its food security, following learnings of other countries like South Korea (Meyer-Rochow et al., 2019).</ns0:p><ns0:p>Our study confirms that edible insects are of considerable nutritional value and expanding their acceptability as human food can be expected to improve the nutritional status of people and possibly reduce the insects' costs. With a wider insect diversity, the nutritional status of people should improve while costs get reduced <ns0:ref type='bibr' target='#b10'>(Dickie et al., 2019)</ns0:ref>. For instance, mealworms consist of six fatty acids and unsaturated omega-3 components that are equivalent to those found in commonly consumed fishes, and also higher than those found in pigs and cattle <ns0:ref type='bibr' target='#b38'>(Raheem et al., 2019)</ns0:ref>. Since nutrition has been one of the core components in the evolution of economic policies as well as family welfare, it is necessary that the insect eating habits of ethnic people in the study area must be widely augmented while focussing on the preservation of its insect diversity.</ns0:p><ns0:p>Certain insects like silkworms, honey bees, and as of late bumble bees and wasps have been traditionally domesticated since they are of high economic value. As such, insect farming is much needed in the study area. This concept is widely prevalent in Korea, Thailand, Vietnam, and Laos PDR. Vertical farming is another technique that can strengthen local economics and help exploiting new protein sources <ns0:ref type='bibr' target='#b44'>(Specht et al., 2019)</ns0:ref>. Family-run enterprises are mostly involved in this business along with other firms that have commercialised insects as not only food but also sources of protein and other health supplements.</ns0:p><ns0:p>Insect diversity can be critical for livelihood development since, in some developing countries, the poorest members of a society are engaged in gathering and rearing of mini-livestock <ns0:ref type='bibr' target='#b26'>(Mason et al., 2018)</ns0:ref>. Industrial-scale interventions can also augment their livelihoods that have now been observed in the case of silkworms of Assam. Given the relatively process of rearing, accessibility, and transportation of insects, the people of the study area can immensely benefit if steps to set up an Insect Marketing Hub, assisted by an Insect Development Authority is set up. The hub should be created following a hub-and-spoke model that would not only pertain to processing and distribution matters but also training and R&amp;D issues.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In this study, we recorded edible insect diversity and abundance, characteristics, and attitudes of the ethnic communities involved in entomophagy that are residing in the fringes of the Manas National Park, a Natural World Heritage Site. A total of 22 species of edible insects belonging to fifteen families and eight orders were recorded from different habitat types. Out of these 22 species, we recorded a maximum number of 8 Orthopteran species followed by Hymenoptera (4), Hemiptera (3), Lepidoptera (2), Blattodea (2) and 1 species each from Coleoptera, Odonata, and Mantodea. Diversity indices such as Shannon-Wiener, Simpson dominance, and Margalef indices were computed. Results of the study show that edible insect diversity has significantly decreased in the forest habitat. For a region highly dominated by entomophagy, such decreasing diversity raises a red flag. The field investigation showed that edible insects are highly sought after by local people. We identified the entomophagy practicing population mainly belonging to the Adivashi, Bodo, Rabha, and Sarania communities. They consume insects via different modes of preparation, such as fried, smoked, raw, etc. Moreover, people preferring entomophagy mainly belong to the youth (20-40 year) population. Therefore, our results conclude that MNP is a place vibrant with a high diversity, and abundance of edible insects. Further, it was found that these insects are good sources of protein, lipid, essential amino acids, omega-3, and omega-6 content, besides calcium, magnesium, and carbohydrate content. This validates edible insects as a future alternative source for an adequately nutrient-rich diet, proving to be majorly desirable in the context of food security. Preservation of such diversity necessitates the adoption of efficient and unique conservation techniques along with appropriate policymaking which can go a long way in augmenting greater insect diversity and also the food security of people in South Asia. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>) shows Periplaneta americana to be the most abundant species with 798 individuals found in monsoon season followed by Mantis religiosa with 466 individuals, and the least abundant species is Mecopoda elongata with 13 individuals. In pre-monsoon, Antheraea assama with 443 individuals has the highest presence and Acheta domesticus with 3 individuals has the lowest. Choroedocus robustus has availability of 420 individuals during retreating monsoon compared to 10 individuals of Gryllus bimuculatus. Finally. In winter, Vespa affinis has the highest availability with 125 individuals, followed by Periplaneta americana with 112 individuals. The least number of individuals (12) was observed in case of Hieroglyphus banian. In general, highest number of insect species was observed during monsoon season with a total of 4808 individuals followed by pre-monsoon with 2758 individuals, retreating monsoon with 2106 individuals, and winter with 774 individuals.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>(a) Map of India (&#169; Google) (b) Map indicating location of Manas National Park (&#169; Google) (c) Map depicting sampling sites (&#169; ESRI)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='20,42.52,178.87,525.00,352.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='21,42.52,204.37,525.00,324.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='22,42.52,229.87,525.00,325.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='23,42.52,204.37,525.00,306.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='24,42.52,229.87,525.00,222.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,229.87,525.00,292.50' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head /><ns0:label /><ns0:figDesc>season, moderate in the retreating monsoon season, and lowest in the winter season. As per the survey report, it was found that the</ns0:figDesc><ns0:table /><ns0:note>abundance of insects found today is much lower than what it was earlier. The decreasing pattern is corroborated by Doley &amp; Kalita (2011), Narzary &amp; Sarmah (2015), Das et al. (2012), with slight changes. This establishes that seasonal availability of edible insects is declining with time.</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>1 Table 1 :</ns0:head><ns0:label>11</ns0:label><ns0:figDesc>Order-wise number of edible insects.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Order</ns0:cell><ns0:cell>Number of species</ns0:cell></ns0:row><ns0:row><ns0:cell>Orthoptera</ns0:cell><ns0:cell>8</ns0:cell></ns0:row><ns0:row><ns0:cell>Hymenoptera</ns0:cell><ns0:cell>4</ns0:cell></ns0:row><ns0:row><ns0:cell>Hemiptera</ns0:cell><ns0:cell>3</ns0:cell></ns0:row><ns0:row><ns0:cell>Lepidoptera</ns0:cell><ns0:cell>2</ns0:cell></ns0:row><ns0:row><ns0:cell>Blattodea</ns0:cell><ns0:cell>2</ns0:cell></ns0:row><ns0:row><ns0:cell>Coleoptera</ns0:cell><ns0:cell>1</ns0:cell></ns0:row><ns0:row><ns0:cell>Odonata</ns0:cell><ns0:cell>1</ns0:cell></ns0:row><ns0:row><ns0:cell>Mantodea</ns0:cell><ns0:cell>1</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>22</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Diversity indices (habitat type) of edible insects recovered from four selected habitats.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>AFH</ns0:cell><ns0:cell>FBH</ns0:cell><ns0:cell>SAH</ns0:cell><ns0:cell>OFH</ns0:cell></ns0:row><ns0:row><ns0:cell>Species Richness</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>23</ns0:cell></ns0:row><ns0:row><ns0:cell>Total individuals</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>encountered</ns0:cell><ns0:cell>9213</ns0:cell><ns0:cell>1455</ns0:cell><ns0:cell>3435</ns0:cell><ns0:cell>6497</ns0:cell></ns0:row><ns0:row><ns0:cell>Simpson</ns0:cell><ns0:cell>0.1148</ns0:cell><ns0:cell>0.3871</ns0:cell><ns0:cell>0.2423</ns0:cell><ns0:cell>0.1467</ns0:cell></ns0:row><ns0:row><ns0:cell>Shannon-Wiener</ns0:cell><ns0:cell>2.822</ns0:cell><ns0:cell>2.153</ns0:cell><ns0:cell>1.329</ns0:cell><ns0:cell>2.392</ns0:cell></ns0:row><ns0:row><ns0:cell>Margalef</ns0:cell><ns0:cell>2.936</ns0:cell><ns0:cell>1.836</ns0:cell><ns0:cell>0.653</ns0:cell><ns0:cell>2.294</ns0:cell></ns0:row></ns0:table></ns0:figure> </ns0:body> "

"Reviewer 2 Review Report Title: Composition and nutritional profile of edible insects in a Natural World Heritage Site of India: Implications for food security in the region By: Arup Kumar Hazarika et al. The revised version of the manuscript is much improved, but some inaccuracies remain and need to be corrected. Also the title had better read: “Diversity of edible insects in a Natural World Heritage Site of India: entomophagy attitudes and implications for food security in the region” Having composition and nutritional profile in the title is misleading and sends the wrong message. The title has been revised and modified as suggested. L38: write “Aspects of the economic significance of entomophagy were also observed during the field investigation.” L55: insert after “…is referred to as entomophagy” the reference: Evans J, Alemu MH, Flore R, Frost MB, Halloran A, Jensen AB, Maciel-Vergara G, Meyer-Rochow VB, Münke-Svendsen C, Olsen SB, Payne C, Roos N, Rozin P, Tans HSG, Van Huis A, Vantomme P, Eilenberg J. ‘Entomophagy’: an evolving terminology in need of review. J Insects Food Feed. 2015;1(4):293–305. Add this to the references list. L68/69: the reference to Johnson 2010 is incomplete in the reference list. Page numbers are missing and the name of the book’s editors are Durst, P.B.; Johnson, D.V.; Leslie, R.N. and Shono, K. (eds.). The publisher is issing: FAP Publ., the place is missing: Bangkok. L69: delete “In Thailand…eaten.” And write “Approximately 50 insect species are eaten in Thailand’s north and about 14 species are eaten by people in southern Thailand (Rattanapan, 2000).” L 73: “…characteristics can also be important (Dumont, 1987). L78-80: delete “In Arunachal….. Further” and write “A total of 81 species are eaten in Arunachal Pradesh by the Galo and Nyishi tribes (Chakravorty et al. 2011).” NOTE: this is not the reference you currently have in the list. L90/91: write “…African nations (Macadam & Stockan, 2017) and are popular in Manipur (India) (Shantibala et al., 2014).” L134: you write “…as it required good vision” Good vision by whom? Best drop that part of the sentence and continue “….as we could not collect nocturnal taxa in this way.” L138/139: it makes no sense to have a light source behind a white cloth and then place a bucket under the light source! The bucket should be IN FRONT of the white cloth ! L146: replace ‘them’ with “it” L150: “..or in the evening…” L151: “Mole and field crickets were dug out…” L162: replace ‘insects’ with “them” L170: write: “…around MNP during the period 2018 (June)- 2019 (June). And delete “The sampling was done” at the end of Line 170. L213/215; 265; Table2 (local name): Not clear why in the column titled “Local name” the Bodo language was chosen. The majority of the respondents were Adivashi not Bodo. Explain please. L285: “…insects were mainly…” L93 “Our results show….” L306 “…has warmed by over 0.5C…” (you need a reference here for that statement!) L32: The decreasing pattern…” L 326/7: not clear “…with time while remaining constant at some point.” That seem contradictory! L327: “This calls for urgent….” (What do you mean by “This”???) L330-334: good point ! L 367: “The majority of…” L378: write “….edible insects require higher energy in culture and contain higher sodium and saturated fat content…” L389: “This frequently uproots the livelihood…” L415: wrong citation Van Huis 2003 does not mention with even one word the situation in Laos. You want this reference: Meyer-Rochow VB, Nonaka K, Boulidam S 2018 “More Feared than Revered: Insects and their impact on human societies (with some specific data on the importance of entomophagy in a Laotian setting)” Entomologie Heute 20, 3-25. L489: please delete this part of the sentence “and Prof V.B. Meyer-Rochow, Department of Ecology & Genetcs, University of Oulu, Finland” References: Delete Chakravorty 2009 and delete reference 8, but replace reference 8 with: Chakravorty J, Ghosh, S. & Meyer-Rochow, V.B. 2011. Practices of entomophagy and entomotherapy by members of the Nyishi and Galo tribes, two ethnic groups of the state of Arunachal Pradesh (North-East India). Journal of Ethnobiology and Ethnomedicine 2011, 7:5 L644: delete reference 54. The references that should be removed (or cited in the text) are References 4, 6, 8, 13, 19, 27, 29, 38, 39, 41, 44, 47, 49, 53, 54, 55, 56. An undergraduate tesis (ref 53) is not something that's citable, unless it is available on the web (in that case give webpage) These have all been revised and modified as recommended. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background: Invasive ductal carcinoma (IDC) is a common pathological type of breast cancer that is characterized by high malignancy and rapid progression. Upregulation of glycolysis is a hallmark of tumor growth, and correlates with the progression of breast cancer. We aimed to establish a model to predict the prognosis of patients with breast IDC based on differentially expressed glycolysis-related genes (DEGRGs) .</ns0:p><ns0:p>Methods: Transcriptome data and clinical data of patients with breast IDC were from The Cancer Genome Atlas (TCGA). Glycolysis-related gene sets and pathways were from the Molecular Signatures Database (MSigDB). DEGRGs were identified by comparison of tumor tissues and adjacent normal tissues. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to screen for DEGRGs with prognostic value. A risk-scoring model based on DEGRGs related to prognosis was constructed. Receiver operating characteristic (ROC) analysis and calculation of the area under the curve (AUC) were used to evaluate the performance of the model. The model was verified in different clinical subgroups using an external dataset (GSE131769). A nomogram that included clinical indicators and risk scores was established. Gene function enrichment analysis was performed, and a protein-protein interaction network was developed.</ns0:p></ns0:div> <ns0:div><ns0:head>Results:</ns0:head><ns0:p>We analyzed data from 772 tumors and 88 adjacent normal tissues from the TCGA database and identified 286 glycolysis-related genes from the MSigDB. There were 185 DEGRGs. Univariate Cox regression and LASSO regression indicated that 13 of these genes were related to prognosis. A riskscoring model based on these 13 DEGRGs allowed classification of patients as high-risk or low-risk according to median score. The duration of overall survival (OS) was longer in the low-risk group (P&lt;0.001), and the AUC was 0.755 for 3-year OS and 0.726 for 5-year OS. The results were similar when using the GEO data set for external validation (AUC for 3-year OS: 0.731, AUC for 5-year OS: 0.728). Subgroup analysis showed there were significant differences in OS among high-risk and low-risk patients in different subgroups (T1-2, T3-4, N0, N1-3, M0, TNBC, non-TNBC; all P&lt;0.01). The C-index was 0.824, and the AUC was 0.842 for 3-year OS and 0.808 for 5-year OS from the nomogram. Functional enrichment analysis demonstrated the DEGRGs were mainly involved in regulating biological functions.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>hallmark of tumor growth, and correlates with the progression of breast cancer. We aimed to establish a model to predict the prognosis of patients with breast IDC based on differentially expressed glycolysis-related genes (DEGRGs).</ns0:p><ns0:p>Methods: Transcriptome data and clinical data of patients with breast IDC were from The Cancer Genome Atlas (TCGA). Glycolysis-related gene sets and pathways were from the Molecular Signatures Database (MSigDB). DEGRGs were identified by comparison of tumor tissues and adjacent normal tissues. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to screen for DEGRGs with prognostic value.</ns0:p><ns0:p>A risk-scoring model based on DEGRGs related to prognosis was constructed. Receiver operating characteristic (ROC) analysis and calculation of the area under the curve (AUC) were used to evaluate the performance of the model. The model was verified in different clinical subgroups using an external dataset (GSE131769). A nomogram that included clinical indicators and risk scores was established. Gene function enrichment analysis was performed, and a protein-protein interaction network was developed.</ns0:p></ns0:div> <ns0:div><ns0:head>Results:</ns0:head><ns0:p>We analyzed data from 772 tumors and 88 adjacent normal tissues from the TCGA database and identified 286 glycolysis-related genes from the MSigDB. There were 185 DEGRGs. Univariate Cox regression and LASSO regression indicated that 13 of these genes were related to prognosis. A risk-scoring model based on these 13 DEGRGs allowed classification of patients as high-risk or low-risk according to median score. The duration of overall survival (OS) was longer in the low-risk group (P&lt;0.001), and the AUC was 0.755 for 3year OS and 0.726 for 5-year OS. The results were similar when using the GEO data set for</ns0:p></ns0:div> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Breast invasive ductal carcinoma (IDC) is the most common malignant tumor in females worldwide <ns0:ref type='bibr' target='#b0'>(Harbeck et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b1'>Hanker et al., 2020)</ns0:ref>. In 2018, there were more than 266,000 cases of breast IDC among females in the United States, and this cancer accounted for 30% of malignant tumors in females, far more than lung cancer (13%) <ns0:ref type='bibr' target='#b2'>(Bray et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b3'>Ahmad, 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>The prognosis of women with breast IDC is related to the activation or silencing of various</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:07:50871:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed biological functions in tumor tissues and signaling pathways. There are prognostic models based on tumor immunity and autophagy, but no models have exclusively focused on IDC <ns0:ref type='bibr'>(Li et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b6'>Zhang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b7'>Hu et al., 2020)</ns0:ref> and few models examined genes that function in basic metabolism.</ns0:p><ns0:p>Glycolysis is a series of reactions that catabolize most carbohydrates. 'Metabolic reprogramming' is the hallmark of tumors, and glycolysis is the main source of energy for tumor cells, even when there is insufficient oxygen <ns0:ref type='bibr' target='#b8'>(Wu et al., 2020a)</ns0:ref>. Moreover, activation of glycolysis-related genes occurs in almost all tumor cells. For example, <ns0:ref type='bibr'>Dai et al.</ns0:ref> found that glycolysis promoted the progression of pancreatic cancer and induced gemcitabine chemotherapy resistance <ns0:ref type='bibr' target='#b9'>(Dai et al., 2020)</ns0:ref>. Long noncoding RNAs (lncRNAs) that interact with Long Intergenic Noncoding RNA for IGF2BP2 Stability (LINRIS) activate aerobic glycolysis in tumor cells, and can affect the development and prognosis of rectal cancer <ns0:ref type='bibr'>(Wang et al., 2019)</ns0:ref>.</ns0:p><ns0:p>Research on the function of glycolysis-related genes in breast tumors showed that hexokinase (HK2) had high expression in breast IDC cells, and that HK2 silencing inhibited IDC <ns0:ref type='bibr' target='#b12'>(Patra et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b13'>Cao et al., 2020)</ns0:ref>. Other research showed that overexpression of 6-Phosphofructo 2-kinase/fructose 2, 6-bisphosphatase 3 (PFKFB3) promoted the progression of breast IDC, and had negative associations with progression-free survival (PFS), distant metastasis-free survival (DMFS), and overall survival (OS) in patients with breast IDC <ns0:ref type='bibr' target='#b14'>(O'Neal et al., 2016;</ns0:ref><ns0:ref type='bibr'>Peng et al., 2018)</ns0:ref>. Thus, glycolysis-related genes have a potentially significant impact on the progression of breast tumors and on the survival and prognosis of patients with breast tumors.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50871:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed Our aim was to develop a prognostic model of breast IDC based on glycolysis-related genes and determine the potential functions of glycolysis-related genes in the progression of breast IDC.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and methods</ns0:head></ns0:div> <ns0:div><ns0:head>Data resources and preprocessing</ns0:head><ns0:p>The transcriptome data and corresponding clinical data of breast invasive ductal carcinoma were downloaded from the TCGA database (https://www.cancer.gov/) <ns0:ref type='bibr' target='#b16'>(Tomczak et al., 2015)</ns0:ref>.</ns0:p><ns0:p>The data set of glycolysis-related genes was obtained from the MSigDB database (http://www.hmdb.ca). Using | log 2 FC |&gt; 0.5 and false discovery rate (FDR) &lt;0.05 as the cut-off value, the data was normalized with the 'edgeR' package from R, and then the differential analysis was performed to obtain the differential expression of glycolysis-related genes (DEGRGs) between the tumor tissue and normal tissue.</ns0:p></ns0:div> <ns0:div><ns0:head>Construction of risk-scoring model</ns0:head><ns0:p>Based on the above DGRG, univariate Cox regression and LASSO regression were used to screen out prognostic-related glycolysis genes. The risk score was evaluated by the coefficient of each prognostic-related glycolysis gene. The risk scoring formula was constructed as , where i is the number of genes used to build the model, coefi is the</ns0:p><ns0:formula xml:id='formula_0'>Risk scores = &#8721; &#119894; 1 (coefi * expri)</ns0:formula><ns0:p>coefficients of the genes in the model, and expriis the expression of genes in the model. Taking the median risk score as the cut-off point, patients were divided into high-risk and low-risk groups. The survival outcome of the two groups was observed by Kaplan-Meier survival analysis.</ns0:p><ns0:p>Receiver operating characteristic (ROC) curve was applied to calculate the area under the curve (AUC) to evaluate the predictive ability of the risk-scoring model. Independent GEO (https://www.ncbi.nlm.nih.gov/geo/) data sets are used to verify the above results <ns0:ref type='bibr' target='#b17'>(Barrett et al., 2013)</ns0:ref>. Univariate Cox regression and multivariate Cox regression were used to identified the independent prognostic factors among risk scores, age, tumor TNM stage, and whether triple negative breast cancer (TNBC) or not. Through clinical survival analysis, the predictive ability of the risk-scoring model in different clinical subgroups was clarified.</ns0:p></ns0:div> <ns0:div><ns0:head>External validation of the risk scoring model</ns0:head><ns0:p>The TCGA results were validated using the GEO (https://www.ncbi.nlm.nih.gov/geo/) dataset (GSE131769). For this validation, the outcomes of the two groups were compared using Kaplan-Meier survival analysis. ROC curves were used to calculate AUCs and evaluate the predictive performance of the risk-scoring model.</ns0:p></ns0:div> <ns0:div><ns0:head>Construction of the nomogram</ns0:head><ns0:p>A nomogram was constructed based on the results of the multivariate Cox regression, with clinical information such as age, TMN stage, TNBC status, and DEGRG risk scores, to predict 3year and 5-year OS. The predictive ability of the nomogram was evaluated by calculating the Cindex and the calibration chart, clinical decision curve analysis, and an ROC curve.</ns0:p></ns0:div> <ns0:div><ns0:head>Function enrichment analysis</ns0:head><ns0:p>We analyzed the genes that were differentially expressed in the high-risk and low-risk groups using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) to identify pathway enrichment <ns0:ref type='bibr' target='#b18'>(Kanehisa et al., 2019)</ns0:ref>. This analysis allowed identification of the PeerJ reviewing <ns0:ref type='table'>PDF | (2020:07:50871:1:1:NEW 2 Oct 2020)</ns0:ref> Manuscript to be reviewed functions of the differentially expressed genes. We then examined whether the differentially expressed genes were involved in the development of breast cancer.</ns0:p></ns0:div> <ns0:div><ns0:head>Construction of interactive network diagram</ns0:head><ns0:p>To determine the relationship of the DEGRG model with prognosis, a network between genes was developed. The prognosis-related genes were imported into Search Tool for the Retrieval of Interacting Genes Proteins (STRING) to construct an interaction network <ns0:ref type='bibr' target='#b19'>(Szklarczyk et al., 2019)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>DEGRGs in breast IDC</ns0:head><ns0:p>We obtained gene expression data and clinical data of females with IDC of the breast (772 tumor tissues, 88 adjacent normal tissues) from the TCGA database and the glycolysis gene set (286 genes) from the GSEA website. Based on standard cut-off values for fold-change in gene expression (|log 2 (FC)| &gt; 0.5) and false discovery rate (FDR &lt; 0.05), the IDC tissues had 185 DEGRGs, with 67 down-regulated genes and 118 up-regulated genes (Figure <ns0:ref type='figure' target='#fig_0'>1A, B</ns0:ref>, Supplementary material Table1).</ns0:p></ns0:div> <ns0:div><ns0:head>Relationship of DEGRGs with prognosis and risk-scoring model</ns0:head><ns0:p>We then identified patients with follow-up times greater than 30 days, and performed univariate Cox regression and LASSO regression to screen for DEGRGs that were related to prognosis (Figure <ns0:ref type='figure' target='#fig_2'>2A, B, C</ns0:ref>). This analysis indicated that 13 DEGRGs were closely related to prognosis.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50871:1:1:NEW 2 Oct 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>We constructed a risk-scoring model based on multivariate Cox regression and divided patients into high-risk and low-risk groups based on median risk score. Kaplan-Meier survival analysis showed that patients with high-risk had significantly reduced duration of OS (P = 9.795 &#215; 10 &#8722;8 , Figure <ns0:ref type='figure'>3A</ns0:ref>). ROC analysis indicated the AUC was 0.755 for 3-year OS and 0.726 for 5year OS (Figure <ns0:ref type='figure'>3B</ns0:ref>). The risk curve and scatterplot (Figure <ns0:ref type='figure'>3C, D</ns0:ref>) show the risk scores and survival status of all patients, and indicate that the risk coefficient and mortality rate were greater in the high-risk group. We plotted a 'heat map' to visualize the expression of the 13 DEGRGs in the high-risk and low-risk groups (Figure <ns0:ref type='figure'>3E</ns0:ref>). Taken together, these results confirm that 13 DEGRGs were significant prognostic indicators for patients with IDC of the breast.</ns0:p><ns0:p>We performed univariate and multivariate Cox regression to evaluate the effect of risk score, age, triple-negative breast cancer (TNBC), and TNM stage on patient prognosis (Figures <ns0:ref type='figure'>4A, B</ns0:ref>).</ns0:p><ns0:p>The results confirmed that the risk score was an independent prognostic factor for patients with IDC of the breast (adjusted hazard ratio: 2.71, 95% confidence interval: 1.87-3.94).</ns0:p><ns0:p>We also performed survival analysis of different subgroups based on TNM status (Figure <ns0:ref type='figure' target='#fig_3'>5</ns0:ref>). This analysis indicated that the risk-scoring model had good predictive value in the T1-2 subgroup, T3-4 subgroup, N0 subgroup, N1-3 subgroup, M0 subgroup, TNBC subgroup, and non-TNBC subgroup (all P &lt; 0.001), but not in the M1 subgroup (P = 0.857).</ns0:p></ns0:div> <ns0:div><ns0:head>External validation of the risk scoring model</ns0:head><ns0:p>We verified the model using the GEO dataset (GSE131769). Kaplan-Meier survival curves showed that patients with high-risk had a significantly shorter duration of OS (P = 3.245 &#215; 10 &#8722;3 , Figure <ns0:ref type='figure' target='#fig_4'>6A</ns0:ref>). ROC analysis indicated that the AUC was 0.731 for 3-year OS and was 0.728 for 5year OS (Figure <ns0:ref type='figure' target='#fig_4'>6B</ns0:ref>). These results confirm the validity of our risk scoring model.</ns0:p></ns0:div> <ns0:div><ns0:head>Construction of the prediction model</ns0:head><ns0:p>Based on the results of the multivariate Cox regression, we developed a nomogram based on age, TMN stage, risk score, and TNBC status to predict 3-year and 5-year OS (Figure <ns0:ref type='figure' target='#fig_5'>7A</ns0:ref>).</ns0:p><ns0:p>We then used the C-index, clinical decision curve, calibration chart, and ROC curve to evaluate the predictive performance of the nomogram (Figure <ns0:ref type='figure' target='#fig_5'>7B-F</ns0:ref>). The results indicated that the prognostic model had good prediction accuracy, with a C-index of 0.824, an AUC for 3-year OS of 0.842, and an AUC for 5-year OS of 0.808. These results verified the predictive ability of the nomogram.</ns0:p></ns0:div> <ns0:div><ns0:head>Gene function enrichment analysis</ns0:head><ns0:p>To explore the potential mechanisms of prognosis-related DEGRGs in breast invasive ductal carcinoma, we performed KEGG enrichment analysis and GO enrichment analysis.</ns0:p><ns0:p>KEGG pathway enrichment analysis showed that the gene set was enriched in the cell cycle, DNA replication, glycolysis and gluconeogenesis, RNA degradation, arachidonic acid metabolism, cytokine-cytokine receptor interactions, cytosolic DNA sensing, and ribosome function (Figure <ns0:ref type='figure'>8A-H</ns0:ref>). GO enrichment analysis showed that the gene set was enriched in the cell cycle G1-S phase transition, DNA geometric changes, the meiotic cell cycle process, regulation of cellular response to heat, cytokine-mediated signaling pathways, regulation of homotypic cell-cell adhesion, regulation of production of molecular mediators of immune responses, and T cell differentiation (Figure <ns0:ref type='figure'>8I-P</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50871:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Construction of an interactive network diagram</ns0:head><ns0:p>We constructed a network diagram to visualize the interactions between hub genes and different miRNAs to better understand the potential functions of the different DEGRGs on prognosis. The results from STRING showed there were 6 interacting hub genes: P4HA2, P4HA1, PGK1, G6PD, HK3, and PMM2 (Figure <ns0:ref type='figure'>9</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Breast IDC is the most common pathological type of breast tumor, and morbidity and mortality from this cancer continue to increase <ns0:ref type='bibr' target='#b0'>(Harbeck et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b21'>Badve &amp; Gokmen-Polar, 2019)</ns0:ref>. There is evidence that changes in glycolysis-related genes have multiple effects on the prognosis of these patients <ns0:ref type='bibr'>(Li et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b23'>Chen et al., 2019)</ns0:ref>. In particular, tumor cells reprogram the glycolysis pathway to accommodate the increased energy required for malignant transformations, including invasion and metastasis <ns0:ref type='bibr' target='#b24'>(Shen et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b25'>Abbaszadeh et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Given the importance of glycolysis on tumor prognosis, numerous research groups have developed models based on glycolysis-related genes in their studies of different cancers <ns0:ref type='bibr' target='#b6'>(Zhang et al., 2019;</ns0:ref><ns0:ref type='bibr'>Wang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b27'>Karasinska et al., 2020)</ns0:ref>. However, no previous study developed a prognostic model for patients with breast IDC based on glycolysis-related genes.</ns0:p><ns0:p>In this research, we identified 13 DEGRGs that were related to prognosis in patients with breast IDC, and then established a risk-scoring model. The results showed that the OS of patients in the high-risk group was significantly shorter than that of patients in the low-risk group. We also examined the impact of patient age, TMN stage, TNBC status, and risk score to construct a nomogram that predicts the 3-year and 5-year OS of these patients. Our application of various evaluation methods indicated that the nomogram had good performance in the prediction of OS.</ns0:p><ns0:p>Our ROC analysis showed that the AUC was 0.842 for 3-year OS and 0.808 for 5-year OS, higher than the AUC values reported in previous models <ns0:ref type='bibr' target='#b28'>(Lin et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b29'>Xie et al., 2019)</ns0:ref>, thus indicating that our model had better predictive ability.</ns0:p><ns0:p>Among the 13 DEGRGs we used to construct the risk model, increased levels of P4H2A, NUP155, ALDH3B1, SDC1, G6PD, COPB2, B3GNT3, PMM2, and PGK1 were associated with poor prognosis and increased levels of HK3, AGRN, P4HA1, and ISG20 were associated with favorable prognosis (Supplementary material Table2). Previous research reported increased levels of P4HA2 and P4HA1 (the two isomers of collagen prolyl 4-hydroxylase) in several types of human cancers and that both enzymes promoted glycolysis in tumor cells <ns0:ref type='bibr' target='#b30'>(Li et al., 2019)</ns0:ref>.</ns0:p><ns0:p>PGK1 is the first key enzyme to produce ATP in the glycolytic pathway, PGK1 is not only a metabolic enzyme but also a protein kinase, which mediates the tumor growth, migration and invasion through phosphorylation some important substrates <ns0:ref type='bibr' target='#b31'>(Fu &amp; Yu, 2020)</ns0:ref>. There is also evidence that SDC1 can promote the migration of breast cancer cells across the blood-brain barrier by regulating the expression of cytokines, thus promoting brain metastasis <ns0:ref type='bibr' target='#b32'>(Sayyad et al., 2019)</ns0:ref>. <ns0:ref type='bibr'>Mele et al.</ns0:ref> found that the overexpression of G6PD can induce lapatinib resistance in breast cancer and also found a significant correlation between high expression of G6PD and tumor recurrence <ns0:ref type='bibr' target='#b33'>(Mele et al., 2019)</ns0:ref>. Sauter et al. found that the level of HK3 in the nipple aspirate of patients with breast cancer was significantly lower than that of healthy women, and PeerJ reviewing PDF | (2020:07:50871:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed considered an elevated HK3 level as a possible sign of early breast cancer <ns0:ref type='bibr' target='#b35'>(Mannello &amp; Gazzanelli, 2001</ns0:ref>). Thus, these previous studies are consistent with our finding that glycolysisrelated genes were closely related to the occurrence and development of breast cancer and the prognosis of patients.</ns0:p><ns0:p>To further characterize the potential roles of the 13 DEGRGs in our risk model, we performed GO and KEGG enrichment analysis. The results showed that the gene set was enriched in cell cycle, DNA replication, glycolysis gluconeogenesis, RNA degradation, arachidonic acid metabolism, cytokine cytokine receptor interaction, cytosolic DNA sensing pathway and ribosome. Previous studies showed that under hypoxic conditions, metabolic reprogramming of breast tumor stem cells helped to maintain their growth and proliferation <ns0:ref type='bibr'>(Peng et al., 2018)</ns0:ref>. Breast cancer occurs in patients with impaired immune function, in which cytokines function as growth signals for tumor cells. Many studies showed that interactions between the immune system and cancer cells, which are mediated by cytokines and chemokines, affect the initiation and progression of breast cancer and the response to treatment <ns0:ref type='bibr' target='#b39'>(Lim et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b37'>King et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b38'>Fabre et al., 2018)</ns0:ref>. DNA replication is a fundamental biological process, and replication disorders can lead to genomic instability, an important feature of breast cancer.</ns0:p><ns0:p>Many experimental and clinical studies have identified disorders of DNA replication during the development and progression of breast cancer <ns0:ref type='bibr' target='#b40'>(Kitao et al., 2018)</ns0:ref>. Aerobic glycolysis pathway includes hexokinase, phosphofructokinase (PFK), and other genes <ns0:ref type='bibr' target='#b41'>(Wu et al., 2020b)</ns0:ref>. These previous findings therefore support our conclusion that the 13 glycolysis-related genes identified here play an important role in the progression of breast tumors. (A) In the T1-T2 subgroup, the OS of the high-risk group was lower than that of the low-risk group (P&lt;0.001). (B) In the T3-T4 subgroup, the OS of the high-risk group was lower than that of the low-risk group (P=0.006). (C) In the N0 subgroup, the OS of the high-risk group was lower than that of the low-risk group (P&lt;0.001). (D) In the N0-N3 subgroup, the OS of the high-risk group was lower than that of the low-risk group (P=0.006). (E) In the M0 subgroup, the OS of the high-risk group was lower than that of the low-risk group (P&lt;0.001). (F) In the M1 subgroup, there was no significant difference in OS between patients in the high-risk group and the low-risk group, because the number of cases in the M1 subgroup is relatively small (P=0.857). (G) In the TNBC subgroup, the OS of the high-risk group was lower than that of the low-risk group (P&lt;0.001). (H) In the NTNBC subgroup, the OS of the high-risk group was lower than that of the low-risk group (P=0.007). The above results suggested that the DGRG risk-scoring model had a good predictive ability. , Figure <ns0:ref type='figure' target='#fig_4'>6A</ns0:ref>). The ROC curve was drawn to calculate the AUC of the 3-year OS and 5-year OS as 0.731 and 0.728, respectively (Figure <ns0:ref type='figure' target='#fig_4'>6B</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50871:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed (A-H) KEGG pathway analysis showed that these genes were involved in cell cycle, DNA replication, glycolysis gluconeogenesis, RNA degradation , arachidonic acid metabolism, cytokine cytokine receptor interaction, cytosolic DNA sensing pathway and ribosome. (I-P) GO enrichment analysis showed that the genes were enriched in the cell cycle G1-S phase transition, DNA geometric change, meiotic cell cycle process, regulation of cellular response to heat, cytokine mediated signaling pathway, regulation of homotypic cell cell adhesion, regulation of production of molecular mediator of immune response, T cell differentiation.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>(A) The volcano gram showed that compared with normal tissues, 67 GRGs were downregulated and 118 GRGs were up-regulated in breast invasive ductal carcinoma. (P&lt;0.05) (B) The heat map showed the expression of 185 DGRGs in both tumor tissues and normal tissues.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 Screening</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 7</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>Figure 8</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='23,42.52,358.49,525.00,324.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='24,42.52,280.87,525.00,195.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='26,42.52,70.87,525.00,269.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='31,42.52,229.87,525.00,328.50' type='bitmap' /></ns0:figure> </ns0:body> "

"Responses to the comments of the reviewers We extend many thanks for your kind suggestions and help. The replies to your comments are as follows: Reviewer 1 (Anonymous): Minor points: 1.They should include the references for all the software and data they used in this this study. RE: We agree with the reviewer. We added relevant references to the revised manuscript (page 6 line 20，page 7 line 17, page 8 line14 and line 22). Thank you very much! 2.Can they change the color of Fig. 1B to make it look brighter? The background is a little dark right now. RE: We agree with the reviewer. We modified Fig. 1B in the revised manuscript. Thank you very much! 3.The analysis of STRING showed that there were interactions among 6 genes (P4HA2, P4HA1, PGK1, G6PD, HK3, PMM2) in DGRG. They should have some introduction of these 6 genes, so that readers can understand it better. RE: We agree with the reviewer. We added a description of these 6 genes in the “Discussion” of the revised manuscript (page 13 lines 8-11and lines 14-16). Thank you very much! 4.In Fig. 10, did they include all the tumor tissue or just the IDC tumor tissue? RE: Reviewer #2 requested the deletion of Fig. 10 because analysis of miRNA was not necessary. After repeated discussions, our research group considered Fig.10 was not closely related to the main content of the paper, so we decided to delete it. Thank you very much! 5.They could consider combine Fig. 9 and Fig.10 together. RE: Reviewer #2 requested deletion of Fig. 10 (see above). 6.They found 185 DGRGs between tumors and normal tissues. If they can include a table as supplementary data to show these 185 DGRGs and the p values, it will be better. RE: We agree with the reviewer. We added supplementary materials to the revised manuscript (page 9 line 10-11). Thank you very much! Reviewer 2 (Anonymous): Major comments: 1. GO and KEGG enrichment analysis are good to reveal the underline function of the GRGs. However, the functions and networks the authors found are not directly related to the biology of breast cancer. I suggest the author could perform further KEGG analysis or GSEA analysis to find whether the GRG signature has close relationship with cancer gene sets, like immunity, proliferation, DNA damage and so on. RE: We agree with the reviewer. We used GSEA analysis to identify GRGs that were closely related to the cancer gene set, and added relevant descriptions in the revised manuscript (page 8 lines 12-17 and page 11, lines 11-18). Thank you very much! 2.Analysis of the miRNA is not necessary. I suggest the author could delete this part. RE: We agree that the analysis of miRNAs was not central to the topic of this article. However, our analysis of miRNAs provided some insights for prognostic studies, so we decided to keep this part of the “Results”. Thank you very much for your comments! Minor points: 1.The abbreviation of differentially expressed glycolysis-related genes is DGRGs in the manuscripts. It is better to use (DEGRGs). RE: We agree with the reviewer. We made corresponding modifications in the revised manuscript. Thank you very much! 2.It is a bioinformatic analysis, and the potential functional mechanisms were not studied. It is better for the author to address the limitation in the “Discussion” section. RE: We agree with the reviewer. We added a statement about the limitations of the paper in the “Discussion” (page 15 line 1-4). Thank you very much! "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The vast tree-like dendritic structure of neurons allows them to receive and integrate input from many neurons. A wide variety of neuronal morphologies exist, however, their role in dendritic integration, and how it shapes the response of the neuron, is not yet fully understood. Here, we study the evolution and interactions of dendritic spikes in excitable neurons with complex real branch structures. We focus on dozens of digitally reconstructed illustrative neurons from the online repository NeuroMorpho.org, which contains over 130,000 neurons. Yet, our methods can be promptly extended to any other neuron. This approach allows us to estimate and map specific and heterogeneous patterns of activity observed across extensive dendritic trees with thousands of compartments. We propose a classification of neurons based on the location of the soma (centrality) and the number of branches connected to the soma. These are key topological factors in determining the neuron's energy consumption, firing rate, and the dynamic range, which quantifies the range in synaptic input rate that can be reliably encoded by the neuron's firing rate. Moreover, we find that bifurcations, the structural building blocks of complex dendrites, play a major role in increasing the dynamic range of neurons. Our results provide a better understanding of the effects of neuronal morphology in the diversity of neuronal dynamics and function.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The vast tree-like dendritic structure of neurons allows them to receive and integrate input from many neurons. A wide variety of neuronal morphologies exist, however, their role in dendritic integration, and how it shapes the response of the neuron, is not yet fully understood. Here, we study the evolution and interactions of dendritic spikes in excitable neurons with complex real branch structures. We focus on dozens of digitally reconstructed illustrative neurons from the online repository NeuroMorpho.org, which contains over 130,000 neurons. Yet, our methods can be promptly extended to any other neuron. This approach allows us to estimate and map specific and heterogeneous patterns of activity observed across extensive dendritic trees with thousands of compartments. We propose a classification of neurons based on the location of the soma (centrality) and the number of branches connected to the soma. These are key topological factors in determining the neuron's energy consumption, firing rate, and the dynamic range, which quantifies the range in synaptic input rate that can be reliably encoded by the neuron's firing rate. Moreover, we find that bifurcations, the structural building blocks of complex dendrites, play a major role in increasing the dynamic range of neurons. Our results provide a better understanding of the effects of neuronal morphology in the diversity of neuronal dynamics and function.</ns0:p></ns0:div> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Neurons are specialized excitable cells that are characterized by distinctive and often complex structures. Although the dendritic complexity is evident in various neuron types, it is often disregarded in computational models, and its role in dendritic integration in the presence of naturalistic stimuli is largely unknown. Moreover, the topology of dendritic trees may reflect fundamental elements for dendritic computation.</ns0:p><ns0:p>Each neuron in the brain is unique, and they can be classified into a myriad of neuron types and subtypes <ns0:ref type='bibr' target='#b0'>(1)</ns0:ref>. Classification schemes often explore common properties of neurons, such as the neuron's morphology or neurotransmitter type (which can be excitatory or inhibitory), the anatomical region they belong to and their role in the circuit, or other dynamical and functional properties of neurons. With the ever-growing NeuroMorpho.org (2-4) public online repository, there are nearly 130,000 digital reconstructions of neuronal morphology available. These data can be used for anatomically realistic models <ns0:ref type='bibr' target='#b4'>(5)</ns0:ref><ns0:ref type='bibr' target='#b5'>(6)</ns0:ref><ns0:ref type='bibr' target='#b6'>(7)</ns0:ref> and morphometric analyses <ns0:ref type='bibr' target='#b7'>(8)</ns0:ref>. They can be invaluable for neuronal classification, which is typically based on morphology, electrophysiology, molecular, or functional properties <ns0:ref type='bibr' target='#b8'>(9)</ns0:ref><ns0:ref type='bibr' target='#b9'>(10)</ns0:ref><ns0:ref type='bibr' target='#b10'>(11)</ns0:ref>. By obeying fundamental consistence rules such as enforcing neurons to have a tree topology (characterized by the absence of loops), digital reconstructions provide an unprecedented wealth of data with exquisite spatial resolution, which can be used to gain further insights on this complex problem of classifying and distinguishing different types of neurons.</ns0:p><ns0:p>In stark contrast to what some simple and influential point-neuron models suggest, such as the leaky integrate-and-fire model <ns0:ref type='bibr' target='#b11'>(12)</ns0:ref> and the Hodgkin-Huxley model <ns0:ref type='bibr' target='#b12'>(13)</ns0:ref>, neurons can have large and intricate morphological structure that processes and integrates complex spatial patterns of input coming from thousands of synapses. Additionally, dendrites are not only passive media that filter electric input by leaking part of the current and propagate the rest. Instead, in addition to these passive properties, dendrites are also capable of producing supralinear amplification called dendritic spikes that occur owing to the voltage-gated dynamics of ion channels <ns0:ref type='bibr' target='#b13'>(14)</ns0:ref><ns0:ref type='bibr' target='#b14'>(15)</ns0:ref><ns0:ref type='bibr' target='#b15'>(16)</ns0:ref>. These nonlinear properties can boost the signal and generate interactions between neighboring compartments that are crucial to facilitate the transmission of information along extensive dendritic trees. Hence, spikes caused by neuronal integration of input from various synaptic sources depend on these non-linear (non-additive) dynamics taking place at dendrites with complex topology. Much work has been done to investigate how topology determines the capability of single neurons to detect intensity of stimulus <ns0:ref type='bibr' target='#b16'>(17)</ns0:ref>, to reliably detect dendritic spikes <ns0:ref type='bibr' target='#b17'>(18)</ns0:ref>, to discriminate input patterns <ns0:ref type='bibr' target='#b18'>(19)</ns0:ref>, and to perform other forms of dendritic computation <ns0:ref type='bibr' target='#b19'>(20)</ns0:ref><ns0:ref type='bibr' target='#b20'>(21)</ns0:ref><ns0:ref type='bibr' target='#b21'>(22)</ns0:ref>. There has also been some attempts to study this problem analytically <ns0:ref type='bibr' target='#b23'>(23,</ns0:ref><ns0:ref type='bibr' target='#b24'>24)</ns0:ref>. However, given the complexity of the task, they are usually limited to regular or oversimplified dendritic structure <ns0:ref type='bibr' target='#b23'>(23)</ns0:ref>.</ns0:p><ns0:p>Simple models play a major role at revealing fundamental dynamic mechanisms in neuroscience <ns0:ref type='bibr' target='#b25'>(25)</ns0:ref>. Here we describe the spatial structure of neurons and focus on main dynamics taking place at dendrites <ns0:ref type='bibr' target='#b26'>(26)</ns0:ref>. Conventional multi-compartment models often have less than 100 compartments (e.g. <ns0:ref type='bibr' target='#b27'>(27)</ns0:ref><ns0:ref type='bibr' target='#b28'>(28)</ns0:ref><ns0:ref type='bibr' target='#b29'>(29)</ns0:ref>) and overlook the large number of synapses (about 10,000 in a human neuron) that lead to complex nonlinear interactions. Some approaches feature a detailed description of a specific neuron. However, a major limitation of this realistic approach is the large number of parameters in the model <ns0:ref type='bibr' target='#b21'>(22,</ns0:ref><ns0:ref type='bibr' target='#b30'>(30)</ns0:ref><ns0:ref type='bibr' target='#b31'>(31)</ns0:ref><ns0:ref type='bibr' target='#b32'>(32)</ns0:ref><ns0:ref type='bibr' target='#b33'>(33)</ns0:ref><ns0:ref type='bibr' target='#b34'>(34)</ns0:ref><ns0:ref type='bibr' target='#b35'>(35)</ns0:ref>. Many of these parameters represent unknown variables, which is typical from such high-dimensional problems that include the description of dynamics of a variety of (often spatially dependent) ion channels along the dendritic tree.</ns0:p><ns0:p>Utilizing simplified neuronal dynamics, we mapped the heterogeneous response of dendritic compartments, independently subjected to stochastic excitatory input, in digitally reconstructed neurons. The structure of these neurons are trees that can be considered as complex networks, and consist of up to 10,000 compartments. We focused on the input-output response curve of these neurons as the intensity of incoming stimuli varies over several orders of magnitude. These response curves can be used to quantify features of the neuronal dynamics <ns0:ref type='bibr' target='#b24'>(24,</ns0:ref><ns0:ref type='bibr' target='#b36'>36)</ns0:ref>. Fundamental principles of neuronal functions may be determined by these dynamic features. Knowing the neuronal functions may be helpful as a way to classify and compare neurons and neuron types <ns0:ref type='bibr' target='#b37'>(37)</ns0:ref> within and across species <ns0:ref type='bibr' target='#b38'>(38)</ns0:ref>.</ns0:p><ns0:p>By applying this theoretical framework, our main aim is to investigate the implications of complex and realistic dendritic structure on dendritic integration and neuronal activity. We characterize the effects of topological properties of the neurons on the dynamic range of the response functions, which quantifies the ability of neurons to discriminate the intensity of incoming input, and show the contribution of bifurcations to heterogeneous activity. We identify distinctive dynamical behaviors of different types of neurons, induced by the dendritic topology, that reflect dynamical properties of the rate of activity of the soma with respect to the dendritic tree. Finally, we show how these findings can be explored to provide a novel functional classification of neurons, which is complementary to existing ones.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head><ns0:p>To estimate the spatial contribution of dendrites to the neuronal activity of digitally reconstructed neurons, a number of simplified assumptions was considered. The dynamics of each node was simulated using a simple model that represents the dynamics of excitable media. The dynamics of 26 different neurons from 6 different species (see details on Table <ns0:ref type='table'>1</ns0:ref>), was characterized. Because details on the spatial distribution of all those neurons are not available, homogeneous dynamics was assumed, and the main goal was to better understand the contribution of the dendritic topology and their bifurcations on the dynamics of neurons. Given the large number of compartments and bifurcations that make up the dendritic arbor, any attempts of analytically modelling the propagation and interaction of potentially hundreds of spikes simultaneously are rendered nearly impractical and hence we focused on numerical experiments. Further, we expect these interactions to be highly non-linear owing to the heterogeneity of the neuronal topology. We overcome this complexity in spike dynamics by adapting a discrete computational model from previous studies <ns0:ref type='bibr' target='#b16'>(17,</ns0:ref><ns0:ref type='bibr' target='#b24'>24,</ns0:ref><ns0:ref type='bibr' target='#b39'>39)</ns0:ref>. Our model preserves the main features of excitable systems, and by implementing real dendritic structures, we focus on the resultant spatial properties of neurons with active dendrites.</ns0:p></ns0:div> <ns0:div><ns0:head>Digital reconstructions</ns0:head><ns0:p>NeuroMorpho is a free online database of tens of thousands of three-dimensional neuron reconstructions. Each neuron has up to thousands of individual compartments, and the dataset is available in a standardized format, allowing the development of frameworks that can implement any neuron. In contrast to previous studies <ns0:ref type='bibr' target='#b16'>(17,</ns0:ref><ns0:ref type='bibr' target='#b24'>24,</ns0:ref><ns0:ref type='bibr' target='#b39'>39)</ns0:ref>, we take the entire spatial information provided by NeuroMorpho and treat the compartments as fundamental units of the neuron that are governed by identical dynamical rules (see next section). We focused on a variety of neurons with high-quality reconstructions, based on visual inspection and diameter regularity. The sampling was such that a large portion of a two-dimensional space comprising the number of branches connected to the soma and the relative centrality of the soma was covered, which were main topological features of neurons. More specifically, the list of neurons used in this paper is given in Table <ns0:ref type='table'>1</ns0:ref> (see below for a definition of the centrality). The NeuroMorpho version was 7.6.</ns0:p></ns0:div> <ns0:div><ns0:head>Compartment dynamics</ns0:head><ns0:p>We adapt a synchronous susceptible -infected (active) -refractory -susceptive model (SIRS) used in previous studies <ns0:ref type='bibr' target='#b16'>(17)</ns0:ref>. The model is a probabilistic cyclic cellular automata with discrete time and compartments. A compartment switches states as a result of interactions from its neighboring compartments, or stochastic processes. A compartment that is in the susceptible state (state 0) will remain there until activated either externally via synapses (see below), or by a propagation of activity from an active neighbor. A signal propagates to a susceptible neighboring compartment with a constant probability P. The probability of a failure to propagate (1-P) represents the net effect of two different contributions: the passive dumping of signal amplitude that propagates along dendrites, and the incoming inhibition. Both contributions can be responsible to prevent the threshold required to generate a dendritic spike to be reached, and thus represent a failure in propagation of activity. Once active (state 1), a compartment will switch to the refractory period (state 2) for a specific time, after which it will return to state 0. Here, we fix the refractory period to 8 time steps. Because of these dynamic rules, activity may spread to all susceptible neighboring compartment and travel in various directions (see Video S1). Moreover, two opposing signals will not add but annihilate each other <ns0:ref type='bibr' target='#b40'>(40)</ns0:ref>. The model also recreates backpropagation, in which an action potential will travel back up the dendritic arbor once the soma has been activated <ns0:ref type='bibr' target='#b41'>(41)</ns0:ref>. For simplicity, here we assume that the probability of forward and backward propagation is the same, as previous work incorporating different probabilities of propagation, depending on the direction, found that they affect the shape of the response function but have little influence on other measures such as the dynamic range <ns0:ref type='bibr' target='#b16'>(17,</ns0:ref><ns0:ref type='bibr' target='#b24'>24,</ns0:ref><ns0:ref type='bibr' target='#b39'>39)</ns0:ref>, which will be explored here. The soma itself also follows the same rules, however, it remains distinctive because it may be connected to many branches (Table <ns0:ref type='table'>1</ns0:ref>). Previous works using regular dendrites have explored the effects of spatial-dependent dynamics <ns0:ref type='bibr' target='#b39'>(39)</ns0:ref> and synaptic input <ns0:ref type='bibr' target='#b16'>(17,</ns0:ref><ns0:ref type='bibr' target='#b24'>24)</ns0:ref>. Here, for simplicity, we assumed that the dynamics of all compartments is identical because detailed information regarding how heterogeneous activity takes place in various neuron types from different species and brain regions is absent.</ns0:p><ns0:p>In reality, many external factors are responsible for determining whether and when a compartment should fire. For example, a compartment could have thousands of synaptic connections, some inhibitory, some excitatory. In the end, however, the result will be either On (activate the compartment) or Off (remain in the susceptible state). We model this result using a probabilistic approach, where the probability of an excitatory synaptic signal is r = 1 -exp(-h&#8226;&#948;t), where h is the excitation rate, and &#948;t is the time step of 1ms. Here we will focus on a range of h that spans several orders of magnitude (from 10 -4 to 10 4 Hz), and P that varies from 0.5 to 1 (as values of P smaller than 0.5 exhibit a very strong attenuation, which is not plausible and give rise to little spatial contribution). The model is a discrete map, and the probability of a susceptible site to be excited in the next time step depends on the activity of its &#119894; &#119896; &#119894; neighbors, and can be written as:</ns0:p><ns0:formula xml:id='formula_0'>&#119875; &#119894; ( &#119905; + &#120575;&#119905; ) = 1 -( 1 -&#119903; )&#8719; &#119896; &#119894; &#119895; = 1 ( 1 -&#119875; ) &#120575;(&#119909; &#119895; , 1) ,</ns0:formula><ns0:p>where is the Kronecker delta, and is the state of the neighbor compartment . We simulate &#120575;(&#119886;, &#119887;) &#119909; &#119895; &#119895; each neuron for 10 6 time steps (1000 seconds) for combinations of h and P, running every simulation five times. Over each simulation, we count the total number of times the soma fires (F S ) and the total number of times a dendritic compartment fires (F D ). The simulations were performed in MATLAB (MathWorks Inc.) using a custom code (see Code availability).</ns0:p></ns0:div> <ns0:div><ns0:head>Firing rate</ns0:head><ns0:p>The characteristic sigmoidal response function of a neuron is recovered by plotting the firing rate at some compartment against the excitation rate h for some value of P. It shows how the neuron responds to various levels of input activity. An important feature of the response curve is the dynamic range, which represents the range of input rates that the neuron can effectively discern. By convention <ns0:ref type='bibr' target='#b36'>(36,</ns0:ref><ns0:ref type='bibr' target='#b42'>42)</ns0:ref>, it is defined as:</ns0:p><ns0:formula xml:id='formula_1'>&#916; = 10 &#215; log 10 ( &#8462; 90 &#8462; 10 ) ,</ns0:formula><ns0:p>where h 10 and h 90 correspond to the excitation rates that produce a firing rate that is 10% and 90% of the maximum firing rate.</ns0:p></ns0:div> <ns0:div><ns0:head>Relative energy consumption</ns0:head><ns0:p>Another metric of determining performance is the relative energy consumption, which we define here as</ns0:p><ns0:formula xml:id='formula_2'>&#119864; = &#119865; &#119863; /&#119865; &#119878; &#119873; -1 ,</ns0:formula><ns0:p>where N is the total number of compartments, and F D and F S are the number of dendritic and somatic spikes, respectively. The energy indicates how active the whole dendritic tree is compared to the soma, that is, how many times, on average, dendritic compartments activate for each somatic spike.</ns0:p></ns0:div> <ns0:div><ns0:head>Dynamics of benchmark neurites</ns0:head><ns0:p>To better understand the relationship between neuronal morphology and dynamics, we constructed and simulated a set of artificial neurites, which consist only of two branches. The primary branch is taken to be of fixed length N, whereas the secondary branch changes both in length L and the position Q at which it bifurcates from the primary branch, where Q is the index of the parent compartment of the primary branch. These toy neurons can be used to isolate the behavior we see in the full neurons.</ns0:p></ns0:div> <ns0:div><ns0:head>Centrality</ns0:head><ns0:p>A way of quantifying the soma's position in the neuron is by estimating how far away it is from the furthest endpoint. Let T be the number of dendritic endpoints (branch terminals) of the neuron, and D ij be the distance (number of compartments) along the neuron from the i-th compartment to the j-th terminal compartment. Since no loops exist, this distance is always unique. Then we define the centrality of the ith compartment as</ns0:p><ns0:formula xml:id='formula_3'>&#119862; &#119894; = max &#119895; = 1, &#8230;, &#119879; {&#119863; &#119894;&#119895; }.</ns0:formula><ns0:p>Once the set of all compartmental centralities C = { C 1 , &#8230;, C N } has been calculated (excluding axonal compartments), the relative centrality of the soma is given by</ns0:p><ns0:formula xml:id='formula_4'>&#119862; &#119903;&#119890;&#119897; = 1 - &#119862; &#119904;&#119900;&#119898;&#119886; -min { &#119862; } max { &#119862; } -min { &#119862; } ,</ns0:formula><ns0:p>where C rel = 0 implies that the soma is the least central compartment of the neuron, while C rel = 1 implies that the soma is the most central compartment.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>We investigate how morphology affects the dynamics of neurons. To focus on the topological properties of neurons with many compartments (100-10000), we utilized a simple dynamic model: a canonical cyclic cellular automata model <ns0:ref type='bibr' target='#b16'>(17,</ns0:ref><ns0:ref type='bibr' target='#b36'>36,</ns0:ref><ns0:ref type='bibr' target='#b43'>43)</ns0:ref>. We first introduce, illustrate, and characterize the relationship between neuronal structure and dynamics in a pyramidal mouse neuron <ns0:ref type='bibr' target='#b44'>(44)</ns0:ref>. Then, we compare the resulting dynamical properties of multiple neurons from different species with a variety of neuronal cell types and structures (see Methods). Each compartment is considered to have synapses that can receive external input, and become active at a rate h, which is varied over several orders of magnitude. The activity propagates to quiescent (susceptible) neighbors with a probability P. By keeping track of the somatic and compartmental firing events, we quantify some fundamental dynamical properties of the neuron, such as the firing rate, relative energy consumption, and dynamic range. The emerging dynamics of the model is depicted in Fig. <ns0:ref type='figure' target='#fig_8'>1</ns0:ref> (see also Video S1).</ns0:p></ns0:div> <ns0:div><ns0:head>Spatial maps of the activation rate</ns0:head><ns0:p>One strength of our computational model is the ability to simulate the complex dynamics of very large neurons with many compartments and including their specific digitally reconstructed morphology. To highlight the heterogeneity across dendritic branches, these results can be visualized spatially in the form of heat maps. The average rate of activation across time (T = 10 6 ms) of each compartment (N = 1580) is illustrated in Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref> for different values of P, the probability of propagation of activity (see Fig. <ns0:ref type='figure' target='#fig_8'>S1</ns0:ref> for other neurons). It is clear that the topology of the neuron affects the firing rate. Crucially, the soma (indicated by the arrow, left panel) becomes active at a higher rate than other compartments. Please note the different colormaps for the different panels. Because the model assumes homogeneity across compartments (P and h), this amplification of firing rate at the soma occurs solely due to the topology. The soma has seven branches connected to it. These branches increase the likelihood of activations to reach the soma in comparison to other compartments because they can come from any active neighbor. Moreover, the lower h and P are, the greater is the relative amplification of the firing rate at the soma (see Fig. <ns0:ref type='figure' target='#fig_3'>S2</ns0:ref> for other neurons and values of h). These results also lead to the prediction that the activation rate can vary substantially across dendritic sites. For neuron A (Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>), the firing rate increases near the soma, but the firing rate is usually larger in sites close to a large number of bifurcations (see Figs. <ns0:ref type='figure' target='#fig_8'>S1 and S2</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Energy consumption for neuronal spikes</ns0:head><ns0:p>Active dendrites are capable of generating dendritic spikes, which allows for enhancement of activity and non-linear interactions. However, these dynamical benefits require additional energy. Here we estimated the relative energy consumption of the soma with respect to the number of activations the whole neuron experiences (see Methods for details). In our model, two processes are responsible for increasing the relative energy consumption of the neuron: (i) the external driving h, and (ii) the propagation and bifurcation of a dendritic spike as it passes a dendritic junction, initiating an additional spike that consumes energy. On the other hand, there are three mechanisms that reduce the relative energy consumption of the neuron: (i) energy dissipates stochastically due to the attenuation rate (1-P), (ii) signals can propagate in nonlinear waves that can be annihilated, and (iii) a signal travelling away from the soma will necessarily die when reaching an endpoint of a branch.</ns0:p><ns0:p>It is important for a neuron to balance its energy usage while performing its functions. In Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>, we plot the relative energy consumption over the parameter space. The blue regions highlight areas of most efficient operation, as somatic spikes require fewer dendritic spikes to take place. In this case, it corresponds to a weak external driving rate (h &lt; 0.01 Hz) and a rate of transmission that allows for failure of dendritic spike propagation (P &lt; 0.95).</ns0:p><ns0:p>The behavior of our measure of energy consumption in the limits of the parameter space, as seen in Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>, can be explained. Firstly, as P approaches 1, every signal will be able to visit all compartments of the neuron once, or interact with another signal which will be able to visit the remaining compartments. In that case, the average firing rate of the compartments is identical and does not depend on topology. Hence, every dendritic compartment has to fire once for the soma to fire once (deterministic behavior). Secondly, in line with other studies <ns0:ref type='bibr' target='#b45'>(45)</ns0:ref>, the energy consumption of spikes increases with h. Moreover, as h approaches &#8734;, every compartment will fire independently at the highest possible rate, &#119865; max = 1 duration of active state + duration of refractory state .</ns0:p><ns0:p>Again, the average firing rate of the compartments is identical, hence we expect a relative energy consumption of 1. Only at these simple limiting cases is the dynamical behavior independent of morphology.</ns0:p></ns0:div> <ns0:div><ns0:head>Spatially resolved response function and dynamic range</ns0:head><ns0:p>One informative and influential way to quantify how dendritic trees process incoming signals is given by input-output response functions. It is defined by the mean output activation rate (across a long time interval, here T = 10 6 ms) as a function of the rate of activations induced by external driving h (neuronal input). This means that the firing rate can be computed for each compartment. Response functions have their minimal in the absence of external input and their maximal for very strong external driving. As illustrated for different recording sites, response functions exhibit a sigmoidal shape (Fig. <ns0:ref type='figure' target='#fig_5'>4</ns0:ref>). These results show for this neuron a larger firing rate at the soma compared to other regions, especially at low external driving, which is consistent with the amplification of the firing rate observed at the soma (Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>). At high values of h, the saturation of the response curves occurs in a similar manner regardless of the recording site. Moreover, for P &#8776; 1, this spatial heterogeneity vanishes.</ns0:p><ns0:p>An important feature of response functions that can be quantified corresponds to the dynamic range &#916; <ns0:ref type='bibr' target='#b16'>(17,</ns0:ref><ns0:ref type='bibr' target='#b36'>36)</ns0:ref>. It depends on the values of external driving at which the neuron responds at 10% of its maximal firing rate (h 10 ), and at 90% (h 90 ). The dynamic range quantifies the range between h 10 and h 90 (see Methods for details). It assumes that, based on the firing rate, the neuron is unable to reliably distinguish activation rates too close to saturation, h &lt; h 10 and h &gt; h 90 . Figure <ns0:ref type='figure' target='#fig_5'>4</ns0:ref> also illustrates the definition of the dynamic range for the response function measured at the soma and at a basal dendrite.</ns0:p><ns0:p>The dynamic range is a measure of the sensitivity to changes in the input rate. A large dynamic range indicates that a neuron can discern signals produced by a large range of input rates. For example, ganglion cells from the retina require a large dynamic range to be able to reliably respond to changes in lighting conditions that vary over several orders of magnitude <ns0:ref type='bibr' target='#b46'>(46)</ns0:ref>.</ns0:p><ns0:p>Our model allows us to identify the spatial gradients observed in the dynamic range (Fig. <ns0:ref type='figure' target='#fig_6'>5</ns0:ref>). Despite changes in the transmission probability P, the soma tends to exhibit high values of dynamic range. However, if P is close enough to 1, the amplification of signals become detrimental, and the dynamic range at the soma can be lower than other regions. In this latter case, it is also relevant to notice that the differences in dynamic range across the neuron are overall very small (&lt; 1dB). This happens because h 10 remains essentially unchanged whilst the saturation of the response function (h 90 ) occurs slightly earlier at the soma (see right panel of <ns0:ref type='bibr'>Fig 4)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Teasing apart the effects of a single branch on the dynamic range</ns0:head><ns0:p>To characterize the effects of neuronal topology, we explored the dynamic range of each compartment in the neuron as a function of its distance from the soma (Fig. <ns0:ref type='figure' target='#fig_7'>6</ns0:ref>). This new perspective reveals a general relationship that is mostly governed by P. For P &lt; 0.99, the dynamic range mostly decreases with the distance from the soma, and bifurcations generate a local boost in dynamic range, while a drop occurs at branch endpoints. For larger values of P, the dynamic range peaks at the main branch to the distal dendrites (yellow).</ns0:p><ns0:p>To better understand the relationship between dendritic topology and neuronal dynamics, we systematically studied how a single branch modifies the dynamic range. To pinpoint the effects of a single bifurcation on the dynamic range, we created a set of very simple neurons containing a single bifurcation with a small branch (Fig. <ns0:ref type='figure' target='#fig_7'>6</ns0:ref>). Starting with a primary branch (black) of constant length, we append a secondary branch (red) of length L to the primary branch at position Q, then run the simulations. Despite its simplified spatial structure, the minimal toy neuron faithfully reproduces many features in its dynamic range profile that we see from the full neuron reconstruction. For example, the effect of a single Manuscript to be reviewed bifurcation or branch endpoint on the local dynamic range is consistent. A more complete set of toy neurites and their dynamic range is provided in Fig. <ns0:ref type='figure' target='#fig_6'>S5</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>How does the dynamic range change across neurons?</ns0:head><ns0:p>Given the wide variety of neuronal morphologies, one might expect very different neurons to exhibit very different dynamics. In general, the dynamic range at the soma, the maximum dynamic range and the minimum dynamic range of the neuron increase with P (Fig. <ns0:ref type='figure'>7</ns0:ref>). At its highest, the dynamic range at the soma attains values of more than 35 dB for all neurons, and up to 43 dB. In addition, as shown before (Figs. <ns0:ref type='figure' target='#fig_6'>4 and 5</ns0:ref>), the measures of the dynamic range at the different sites become more homogeneous for very large values of P. The measure of the relative &#916; at the soma shows that the soma is most often close to the sites of maximum dynamic range. However, some neurons (R, T, Y and Z) exhibit the dynamic range at the soma somewhat smaller than the maximum dynamic range of the neuron. Moreover, the maximum heterogeneity of dynamic range across neurons varied substantially (from 7 to 13 dB). This spatial heterogeneity, even when the dynamics of the compartments is assumed to be identical, demonstrates that the topology of neurons plays a major role in shaping neuronal dynamics.</ns0:p></ns0:div> <ns0:div><ns0:head>Trends in energy consumption</ns0:head><ns0:p>The dynamic range tells us about the capability of neurons to encode stimuli that vary over orders of magnitude. However, this process has a cost, and the dynamic range does not reveal the neuronal efficiency in terms of energy consumption. Previously, we have introduced our measure of relative energy consumption, defined as the average number of times a dendritic compartment spikes for an action potential to be generated (Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>). If we compare the energy consumption across all neurons, three distinct types of behaviors emerge (Figs. 8-10), along with a transitioning behavior (Fig. <ns0:ref type='figure' target='#fig_8'>11</ns0:ref>). For the full set of energy consumption plots, refer to Fig. <ns0:ref type='figure' target='#fig_7'>S6</ns0:ref>.</ns0:p><ns0:p>Type 1 (Fig. <ns0:ref type='figure'>8</ns0:ref>) occurs for the majority of neurons, despite the stark differences in morphologies. For these neurons, the energy is minimized for approximately h &lt; 10 Hz and P &lt; 0.95. Although the maximum dynamic range at the soma of every neuron occurs near P = 1, it corresponds to a very high relative energy consumption. However, a slight decrease in P can almost minimize the energy consumption in these neurons, while keeping the dynamic range near its maximum. An optimally performing neuron would therefore slightly subject signal propagation to failure, saving energy without considerable loss in dynamic range.</ns0:p><ns0:p>Type 2 (Fig. <ns0:ref type='figure'>9</ns0:ref>) corresponds to a narrower region of minimal energy consumption (h &lt; 1 Hz and 0.85 &lt; P &lt; 0.95). Unlike Type 1, decreasing the transmission probability below 0.8 is detrimental to the efficient operation of these neurons.</ns0:p><ns0:p>Type 3 (Fig. <ns0:ref type='figure' target='#fig_8'>10</ns0:ref>) display high relative energy consumption, with a maximum in the region h &lt; 1 Hz and 0.8 &lt; P &lt; 0.9. Moreover, the maximum and minimum energy consumption is much higher than for neurons of other types, and it never reaches a value below 1. As such, Type 3 seems to be intrinsically energy inefficient.</ns0:p><ns0:p>The transition (Fig. <ns0:ref type='figure' target='#fig_8'>11</ns0:ref>) Type T exhibits a behavior that is between Types 1 and 2. Given the different behaviors, it is clear that the dendritic morphology affects the energy consumption of neurons. A crucial element in the computation of the energy consumption corresponds to the location of the soma, and the number of branches it has. Neurons of Type 1 have the soma located in a centralized position. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Centrality</ns0:head><ns0:p>To quantitatively describe the soma's relative position within the overall extent of the dendritic arbor, we devise a general measure of centrality (see Methods). When C = 1, the soma is considered the most central compartment in the neuron. When C = 0, it is considered the least central. If a compartment is not central, it does not necessarily imply that it lies near the border of the neuron; for example, as for neuron A, compartments in the two separated regions of high bifurcation densities would experience a low centrality despite being surrounded by many compartments. Only the branch connecting these two areas would be central. Heat maps of the compartmental centrality for all neurons are provided in Fig. <ns0:ref type='figure'>S7</ns0:ref>. The spatial mapping reveals that centrality is related to how symmetrically the rest of the neuron is distributed around a compartment.</ns0:p></ns0:div> <ns0:div><ns0:head>Categorization</ns0:head><ns0:p>Based on our estimation of energy consumption, the behavior of Type 2 can be distinguished from the behavior of Type 3 by the centrality (Fig. <ns0:ref type='figure' target='#fig_8'>12</ns0:ref>). Moreover, the behavior of Type 1 and the transition Type T can be explained by the number of branches connecting to the soma. This is an important property of neurons, as more branches naturally allow the soma to capture more information from the dendritic arbor. Then, if the soma is also located centrally, information can reach the soma more easily from any part of the neuron, and vice versa.</ns0:p><ns0:p>Taking into account how these main structural features affect neuronal dynamics, we propose a categorization of neurons based on the relative centrality of the soma, and number of somatic branches (Fig. <ns0:ref type='figure' target='#fig_8'>12</ns0:ref>). Neurons in the same category exhibit qualitatively similar energy consumption profiles, and thus determine how efficiently the neuron operates over the parameter space: Type 1 neurons are intrinsically energy efficient, while Type 3 is intrinsically inefficient. The transition between classes is smooth. For example, neurons with 3 or 4 somatic branches have a higher minimum energy consumption than those with more somatic branches (see Fig. <ns0:ref type='figure' target='#fig_7'>S6</ns0:ref>), however, they follow the same general behavior.</ns0:p><ns0:p>The general neuronal firing behavior of neurons can also be ascribed to their classification. For P = 1, the average response functions of neurons within types are very similar, as they do not depend much on the centrality and number of somatic branches. However, as P decreases, each class tends to behave independently (Fig. <ns0:ref type='figure' target='#fig_8'>13 a-c</ns0:ref>). For a given input rate, neurons in category 1 fire more often, followed by the neurons in the transition regime, neurons of category 2 and neurons of category 3. Furthermore, we find that a low probability of signal propagation has a detrimental effect on the somatic dynamic range of neurons with a low number of somatic branches (Fig. <ns0:ref type='figure' target='#fig_8'>13 d</ns0:ref>). Additionally, neurons with a large number of compartments or bifurcations can achieve a higher maximum dynamic range independently of other morphological features (Fig. <ns0:ref type='figure' target='#fig_8'>13</ns0:ref>. e, f). How close this site with maximum dynamic range is to the soma, however, does depend on the neuronal morphology.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Dendritic computation occurs as a result of multiple non-linear interactions taking place at dendrites <ns0:ref type='bibr' target='#b13'>(14,</ns0:ref><ns0:ref type='bibr' target='#b47'>47)</ns0:ref>. To provide insights into this phenomenon, we proposed a modelling approach that considers real neurons under naturalistic conditions, receiving independent synaptic-like input at thousands of compartments. These detailed neurons are spatially-extended excitable trees from NeuroMorpho, a database containing over 130,000 digitally reconstructed neurons <ns0:ref type='bibr' target='#b1'>(2)</ns0:ref><ns0:ref type='bibr' target='#b2'>(3)</ns0:ref><ns0:ref type='bibr' target='#b3'>(4)</ns0:ref><ns0:ref type='bibr' target='#b48'>(48)</ns0:ref><ns0:ref type='bibr' target='#b49'>(49)</ns0:ref><ns0:ref type='bibr' target='#b50'>(50)</ns0:ref><ns0:ref type='bibr' target='#b51'>(51)</ns0:ref><ns0:ref type='bibr' target='#b52'>(52)</ns0:ref>. Here we focus our results on a set 26 selected neurons, however, it is possible to extend these analyses to any neuron of the database using the code provided.</ns0:p><ns0:p>We demonstrated the presence of substantial spatial dependence in neuronal dynamics that can be attributed to morphological features. Specifically, we mapped the excitability (firing rate) and dynamic range of dendritic branches and the soma. We identified bifurcations as a major structural source that can be very effective in raising the dynamic range. Furthermore, we showed how the number of branches connected to the soma and its centrality influence the energy consumption of neurons, and can be explored to classify neuron types. Hence, we classified neurons into three different families based on centrality and number of branches connecting the soma, and a family that is within a transition zone. We found that a soma with only one branch is special, and a general behavior is expected when the soma has many branches. It is also possible to observe a transition that happens when the soma has two or three branches.</ns0:p></ns0:div> <ns0:div><ns0:head>Neuronal diversity</ns0:head><ns0:p>Diversity is a hallmark of neurons, and this is clearly demonstrated by the large variety of digitally reconstructed neurons found in the NeuroMorpho database, which currently has &gt;130,000 neurons, from &gt;640 cell types, and 60 species. Each of these neurons is unique. They have a tree topology, and their morphological features are crucial for classification. However, additional attempts have also been made to classify neurons based not only on their morphology but taking into account features of their electrophysiology, and their dynamics <ns0:ref type='bibr' target='#b0'>(1,</ns0:ref><ns0:ref type='bibr' target='#b8'>9,</ns0:ref><ns0:ref type='bibr' target='#b53'>53,</ns0:ref><ns0:ref type='bibr' target='#b54'>54)</ns0:ref>. These proposals attempt to improve neuronal classification with information about dynamics and function of neurons. Along this line, here we propose to incorporate a few key structural features that inform about neuronal dynamics and function. Our classification based on neuronal topology, together with other forms of neuronal classification that take into account species, anatomical region, morphological, and electrophysiological properties of neurons, may lead to more accurate functional classification schemes.</ns0:p><ns0:p>Utilizing a minimal dynamic model, we were able to simulate the dynamics of many neurons with thousands of compartments. This simple method is suitable to identify and highlight the most important structural features of neurons. Here we focused on a variety of neurons, representing several neuron types, from different species, and acquired at multiple laboratories. Given this diversity, we did not focus on harmonizing the length of compartments. However, NeuroMorpho is a very rich dataset that allows a parcellation that forces compartments to have the same length in order to improve comparisons among neurons. The study was also primarily focused on neurons with high-quality and fine-resolution reconstructions (with large number of compartments), but it was comprised of a large proportion of pyramidal neurons. By incorporating more neuron types, the diversity of the sampling can be increased, and this approach may be effective to further explore the relationship between dendritic topology and neuronal function.</ns0:p><ns0:p>Action potentials and dendritic spikes consume energy because of the active flux of ions that is required to charge the membrane capacitance. To allow active signaling, these ions have to be pumped and this process uses energy provided by ATP. The energy cost of action potentials can vary considerably across neurons <ns0:ref type='bibr' target='#b55'>(55)</ns0:ref>. Here we propose a different approach that focusses not on the cost of an action potential, but on the cost of a neuronal spike relative to the cost of the routing of electric activity through dendrites. We found that our estimation of relative energy consumption of neurons appears in stereotypical forms that can be linked to specific topological features. Hence, we propose that these features are relevant to characterize neuronal dynamics. According to our approach, it is clear that specific morphological fingerprints such as bitufted cells can be classified as belonging to a specific category (T). Furthermore, neurons with multiple branches are more effective at generating somatic spikes. These branches increase the convergence of input to the soma and reduce the overall density of dendritic spikes typically required to trigger a somatic spike. In contrast, neurons with a non-central soma connected to a single branch show the largest relative energy consumption, and they require more than one dendritic spike per compartment for each somatic spike. These distinct behaviors suggest specific computational function for neurons belonging to different families. Moreover, this simple approach reveals a clear role of dendritic topology, which might not be so evident in more complex neuron models that require a large number of parameters.</ns0:p></ns0:div> <ns0:div><ns0:head>Neuronal topology and dynamics</ns0:head><ns0:p>Other aspects of neuronal dynamics affected by dendritic topology include response function and dynamic range. It has been previously shown that the size of dendritic trees play a crucial role in determining the maximum dynamic range an active dendritic tree can attain <ns0:ref type='bibr' target='#b39'>(39)</ns0:ref>. However, this proposal was based only on a single topology (a regular and binary Cayley tree) with variable sizes (number of layers). This regular and artificial topology is relevant but the approach does not distinguish clearly the number of compartments from the number of bifurcations. Here, by utilizing real neurons from NeuroMorpho, we can assess the role of these two factors. We found that both the number of bifurcations (Pearson correlation, r = 0.72, p &lt; 10 -4 ) as well as the number of compartments (Pearson correlation, r = 0.65, p &lt; 10 -4 ) can be good predictors for the maximum dynamic range of neurons. However, it must be taken into account that the number of compartments is also correlated with the number of bifurcations. In this dataset, it is important to consider that the number of compartments is mostly determined by the resolution of the digital reconstruction. In contrast, the number of bifurcations reflects more fundamental properties of dendritic topology.</ns0:p><ns0:p>Typically, the larger is the number of bifurcations, the larger is the dynamic range. This trend is also consistent with our minimal modelling approach containing a single bifurcation. We found that a single bifurcation tends to increase the dynamic range by a few decibels. A real dendritic topology can have many bifurcations that contribute to increase the dynamic range of the neuron. Although their contribution is not additive, it is reasonable to find that the number of bifurcations is perhaps the most important element to increase the dynamic range. As large dendrites have many bifurcations, the resolution used to digitalize such a complex structure needs to be fine. As a result, the number of compartments often correlates with the number of bifurcations. Together, our results suggest that the number of bifurcations is likely among the most essential features of dendrites to shape the dynamic range.</ns0:p><ns0:p>Centrality is also fundamental for the dynamics because central branches exhibit larger firing rates. This feature tends to increase the dynamic range as it is very effective at amplifying weak inputs. However, this amplification can also be beneficial to the dynamic range when P approaches 1. In this case, when P is nearly deterministic, we found that the dynamic range of central compartments is usually higher than at non-central ones (see Fig. <ns0:ref type='figure'>S8</ns0:ref>). Going beyond single neurons, which have a tree topology with no loops, future work should test whether topological features (such as centrality and degree) of more general networks can also inform spatiotemporal patterns of activity in networks of larger scales of circuits, columns, and brain regions. Furthermore, the dynamics of networks depend on the diversity of neurons and properties of neuronal integration <ns0:ref type='bibr' target='#b42'>(42,</ns0:ref><ns0:ref type='bibr' target='#b43'>43,</ns0:ref><ns0:ref type='bibr' target='#b56'>56)</ns0:ref>. Hence, it remains to be determined how the different types of neurons proposed here influence the activity of networks.</ns0:p></ns0:div> <ns0:div><ns0:head>Neuronal models</ns0:head><ns0:p>Our model is suitable to explore the topological effects of tens of thousands of digitally reconstructed neurons with thousands of compartments in neuronal dynamics under complex input conditions. In order to focus on these crucial spatial aspects of neurons, here we considered explicitly simplified neuronal dynamics. We disregarded heterogeneity of ion channels along neurons and assumed homogeneity for simplicity. This allows us to highlight topological features of neurons and ascribe the heterogeneous types of dynamics exclusively to dendritic structure. We argue that our simple modelling approach retains the essential features to simulate the dynamics of excitable systems without the burden of an excessive number of details and parameters. However, this is clearly a simplification, and future work should address the role of more sophisticated biophysical models with additional free parameters that describe the membrane potential of dendritic branches as continuous variables (differential equations, instead of a map with discrete states (57)), and explicitly consider the contributions of excitatory and inhibitory synapses. Here, as a first step, inhibition is only implicitly considered in the net synaptic contribution since in a previous study using a similar dynamic model inhibition did not show much impact in the dynamic range of the network whilst requiring additional free parameters <ns0:ref type='bibr' target='#b43'>(43)</ns0:ref>. More detailed models might also incorporate heterogeneity of dynamics, taking into account impedance gradients, the dendritic diameter, type of dendrite, distance from soma, and so on <ns0:ref type='bibr' target='#b58'>(58)</ns0:ref>. Future studies including electrotonic analysis will require more parameters but will represent an important validation step of our findings and may lead to a better understanding of the relationship between dendritic topology and function. Moreover, our simplifying assumptions of homogeneous and constant input can also be extended in future works. As a first step, a more detailed description of the dynamics of the soma can be considered in which the model has two types of dynamics, one for the dendrites and one for the soma, and the role of two types of integration can be independently assessed. This distinction might be relevant because it is known that signal integration at the soma can be crucial for coincidence detection and the resulting network response <ns0:ref type='bibr' target='#b56'>(56)</ns0:ref>.</ns0:p><ns0:p>Changes in neuronal structure are reported in many neuropsychiatric disorders <ns0:ref type='bibr' target='#b59'>(59)</ns0:ref><ns0:ref type='bibr' target='#b60'>(60)</ns0:ref><ns0:ref type='bibr' target='#b61'>(61)</ns0:ref><ns0:ref type='bibr' target='#b62'>(62)</ns0:ref><ns0:ref type='bibr' target='#b63'>(63)</ns0:ref>. The minimal modelling approach proposed here can be used to characterize the changes in neuronal dynamics caused by these structural alterations <ns0:ref type='bibr' target='#b64'>(64)</ns0:ref>. Our simplified approach might also be relevant for simulating motifs and circuits of neurons with detailed dendritic structure under complex and realistic input conditions. Future work can focus on more complex and specific extensions of the model. For example, spatial-and time-dependent input may reveal other main features of neuronal dynamics with dendritic computation taking place in parallel at functional subunits in cortical circuits.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Our model provides insights into the role the dendritic structure plays in the behavior of a neuron, both local and on the larger scale. We used digital reconstructions of real neurons to address the effects of intricate and nonhomogeneous spatial features of neurons on their dynamics. Our results indicate that two main morphological features -the centrality of the soma, and the number of branches connected to the soma -can determine the type of behavior a neuron exhibits. Neurons whose soma lies on the border and in a non-central location are intrinsically energy inefficient, whereas neurons with many branches connected to the soma are intrinsically energy efficient. Furthermore, we have shown that bifurcations in the dendritic tree can enhance the dynamic range, and that the maximum dynamic range of neurons increase with the number of bifurcations and compartments. Our approach can be extended to more than 130,000 neurons available at the NeuroMorpho database.</ns0:p></ns0:div> <ns0:div><ns0:head>Code availability</ns0:head><ns0:p>Matlab code to reproduce the results, named 'Neurodynamics', is available at Systems Neuroscience Group: http://www.sng.org.au/Downloads.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:48151:1:1:NEW 17 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure 1</ns0:note><ns0:p>Series of snapshots showing how signals propagate along the neuron.</ns0:p><ns0:p>Visualization of digital reconstruction of neuron A (see Methods), where compartments are colored according to the following scheme: green for basal dendrites, purple for apical dendrites, blue for the soma (too small to be seen here), red for active (spiking) compartments, orange for refractory compartments. In each time step, spikes may propagate from active compartments to susceptible neighboring compartments with transmission probability P (here, P = 0.96). A susceptible compartment may also spike due to the synaptic input, which we model stochastically with a Poisson rate of h (here, h = 0.1 Hz).</ns0:p><ns0:p>Once active, a compartment transitions to the refractory period and is unable to spike for 8 Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 7</ns0:note><ns0:p>Comparison of dynamic ranges across neurons.</ns0:p><ns0:p>Each row of graphs corresponds to the row of neurons above (see Methods for a description of each neuron). Colors do not have physical meaning, and are used only to differentiate the neurons of each row. The soma is marked by the green arrow, while the red and blue arrows indicate the location of the compartment at which the dynamic range is highest and lowest when P = 0.92. The relative dynamic range was calculated using (&#916; soma -&#916; min ) / (&#916; max -&#916; min ).</ns0:p><ns0:p>See Table <ns0:ref type='table'>1</ns0:ref> for original references and description of neurons.</ns0:p><ns0:note type='other'>Figure 12</ns0:note><ns0:p>Categorization of neurons according to their relative energy consumption profile. Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 13</ns0:note><ns0:p>Comparison of firing behavior.</ns0:p><ns0:p>(a-c) Average somatic response functions of the neurons in each category (see Fig. <ns0:ref type='figure' target='#fig_8'>12</ns0:ref>) for different values of P. The shading represents the standard deviation of firing rate within each group for a given stimulus intensity. For large P, all groups converge to the same behavior.</ns0:p><ns0:p>For lower P, there is a distinct behavior between the average response functions of each </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:48151:1:1:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:48151:1:1:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>time steps. Panels A to F are different time points. The inset plot provides a closer look at the soma and surrounding compartments. B: At t = 73, the neuron fires as a result of the dendritic integration of synaptic input (somatic spike, see black arrow). C-D: Between t = 74 and t = 75, a signal fails to transmit (see blue arrow). D-E: Between t = 75 and t = 76, two spikes can be seen annihilating each other (see red arrow). The snapshots were taken from Video S1.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 2 Spatial</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 3 Variations</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 4 Response</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 5 Heat</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 6 Dynamic</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Type 1 (</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>blue) corresponds to Fig. 8, Type 2 (yellow) to Fig. 9, Type 3 (red) to Fig. 10, and Type T (transition, purple) to Fig. 11. The white dotted lines represent the approximate boundaries between different neuron types, and the colors indicate the different types. PeerJ reviewing PDF | (2020:04:48151:1:1:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>group. (d) Dynamic range at the soma of each neuron against the number of somatic branches for P = 0.5. The colors represent the groups. The black trend line and Pearson correlation (r = 0.91) confirm that the dynamic range is strongly correlated to the number of somatic branches for lower values of P. (e, f) At high values of P, the number of bifurcations and number of compartments are good indicators of the maximum dynamic range that a neuron can achieve (here P = 0.98). Please note the logarithmic scale. The black trend lines and Pearson correlation show that the maximum &#916; achieved is approximately linearly correlated with the neuron's size and complexity.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='30,42.52,229.87,525.00,192.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='31,42.52,229.87,525.00,192.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='32,42.52,229.87,525.00,192.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='33,42.52,229.87,525.00,192.00' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 (on next page)Table 1 .</ns0:head><ns0:label>11</ns0:label><ns0:figDesc>List of neuron reconstructions used in this study, taken from NeuroMorpho.Org (version 7.6).</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:48151:1:1:NEW 17 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>1 Table 1 : List of neuron reconstructions used in this study, taken from NeuroMorpho.Org (version 7.6).</ns0:head><ns0:label>11</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>layer</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Label P</ns0:cell><ns0:cell cols='2'>Cell type Pyramidal occipital; Region primary visual,</ns0:cell><ns0:cell>Species Monkey</ns0:cell><ns0:cell>Number of 9</ns0:cell><ns0:cell>Number of compartmen 751</ns0:cell><ns0:cell>Number of 28</ns0:cell><ns0:cell>Relative centrality 0.336</ns0:cell><ns0:cell>NeuroM orpho ID 62656 NMO_</ns0:cell><ns0:cell>ence Refer [76]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>layer 6</ns0:cell><ns0:cell /><ns0:cell>somatic</ns0:cell><ns0:cell>ts</ns0:cell><ns0:cell>bifurcati</ns0:cell><ns0:cell>of soma</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Q</ns0:cell><ns0:cell>Granule</ns0:cell><ns0:cell>hippocampus;</ns0:cell><ns0:cell>Rat</ns0:cell><ns0:cell>branches 2</ns0:cell><ns0:cell>431</ns0:cell><ns0:cell>ons 17</ns0:cell><ns0:cell>0.940</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[77]</ns0:cell></ns0:row><ns0:row><ns0:cell>A</ns0:cell><ns0:cell cols='2'>Pyramidal occipital; dentate gyrus</ns0:cell><ns0:cell>Mouse</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>1580</ns0:cell><ns0:cell>30</ns0:cell><ns0:cell>0.552</ns0:cell><ns0:cell>NMO_ 00462</ns0:cell><ns0:cell>[44]</ns0:cell></ns0:row><ns0:row><ns0:cell>R</ns0:cell><ns0:cell>Purkinje</ns0:cell><ns0:cell>posteromedial cerebellar</ns0:cell><ns0:cell>Mouse</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>5726</ns0:cell><ns0:cell>358</ns0:cell><ns0:cell>0.879</ns0:cell><ns0:cell>72082 NMO_</ns0:cell><ns0:cell>[78]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>visual, layer 5 cortex; vermis,</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>00864</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>B</ns0:cell><ns0:cell cols='2'>Pyramidal frontal; Purkinje layer</ns0:cell><ns0:cell>Human</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>640</ns0:cell><ns0:cell>49</ns0:cell><ns0:cell>0.676</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[65]</ns0:cell></ns0:row><ns0:row><ns0:cell>S</ns0:cell><ns0:cell cols='2'>primary motor Pyramidal hippocampus;</ns0:cell><ns0:cell>Rat</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>473</ns0:cell><ns0:cell>47</ns0:cell><ns0:cell>0.500</ns0:cell><ns0:cell>84457 NMO_</ns0:cell><ns0:cell>[79]</ns0:cell></ns0:row><ns0:row><ns0:cell>C</ns0:cell><ns0:cell cols='2'>Pyramidal anterior CA1;</ns0:cell><ns0:cell>Human</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>1441</ns0:cell><ns0:cell>213</ns0:cell><ns0:cell>0.756</ns0:cell><ns0:cell>NMO_ 06145</ns0:cell><ns0:cell>[66]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>cingulate; pyramidal</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>01058</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>layer 5 layer</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>D T</ns0:cell><ns0:cell cols='2'>Pyramidal temporal; Unknown frontal</ns0:cell><ns0:cell>Human Rat</ns0:cell><ns0:cell>6 2</ns0:cell><ns0:cell>9678 511</ns0:cell><ns0:cell>76 22</ns0:cell><ns0:cell>0.623 0.327</ns0:cell><ns0:cell>NMO_ NMO_</ns0:cell><ns0:cell>[67] [80]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Brodmann</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>68177 10137</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>area 21, layer</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>8</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>U</ns0:cell><ns0:cell>Induced</ns0:cell><ns0:cell>2-3 forebrain</ns0:cell><ns0:cell>Human</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>372</ns0:cell><ns0:cell>66</ns0:cell><ns0:cell>0.317</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[81]</ns0:cell></ns0:row><ns0:row><ns0:cell>E</ns0:cell><ns0:cell cols='2'>Pyramidal anterior Neurons</ns0:cell><ns0:cell>Human</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>1091</ns0:cell><ns0:cell>222</ns0:cell><ns0:cell>0.907</ns0:cell><ns0:cell>NMO_ 10325</ns0:cell><ns0:cell>[66]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>cingulate;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>01064 6</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>V</ns0:cell><ns0:cell>Purkinje</ns0:cell><ns0:cell>layer 5 cerebellum;</ns0:cell><ns0:cell>Mouse</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>667</ns0:cell><ns0:cell>142</ns0:cell><ns0:cell>0.886</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[82]</ns0:cell></ns0:row><ns0:row><ns0:cell>F</ns0:cell><ns0:cell>Ganglion</ns0:cell><ns0:cell>retina; inner vermis, lobule</ns0:cell><ns0:cell>Mouse</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>3936</ns0:cell><ns0:cell>50</ns0:cell><ns0:cell>0.827</ns0:cell><ns0:cell>NMO_ 80037</ns0:cell><ns0:cell>[68]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>plexiform layer III, apex</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>08168</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>G W</ns0:cell><ns0:cell cols='2'>Pyramidal parietal; Interneur optic lobe;</ns0:cell><ns0:cell>Human drosophila</ns0:cell><ns0:cell>6 1</ns0:cell><ns0:cell>413 4659</ns0:cell><ns0:cell>24 762</ns0:cell><ns0:cell>0.943 0.826</ns0:cell><ns0:cell>NMO_ NMO_</ns0:cell><ns0:cell>[69] [83]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>on</ns0:cell><ns0:cell>Brodmann lobula</ns0:cell><ns0:cell>melanogaster</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>03500 51008</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>area 39 complex;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>H</ns0:cell><ns0:cell>Ganglion</ns0:cell><ns0:cell>retina; lobula plate</ns0:cell><ns0:cell>Mouse</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>2876</ns0:cell><ns0:cell>51</ns0:cell><ns0:cell>0.956</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[70]</ns0:cell></ns0:row><ns0:row><ns0:cell>X</ns0:cell><ns0:cell cols='2'>ganglion layer Pyramidal medial</ns0:cell><ns0:cell>Rat</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>636</ns0:cell><ns0:cell>15</ns0:cell><ns0:cell>0.698</ns0:cell><ns0:cell>05321 NMO_</ns0:cell><ns0:cell>[84]</ns0:cell></ns0:row><ns0:row><ns0:cell>I</ns0:cell><ns0:cell cols='2'>Pyramidal frontal; prefrontal;</ns0:cell><ns0:cell>Wallaby</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>797</ns0:cell><ns0:cell>34</ns0:cell><ns0:cell>0.900</ns0:cell><ns0:cell>NMO_ 33937</ns0:cell><ns0:cell>[65]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>primary layer 2-3</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>84354</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Y</ns0:cell><ns0:cell>Purkinje</ns0:cell><ns0:cell>motor, deep cerebellar</ns0:cell><ns0:cell>Mouse</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>1568</ns0:cell><ns0:cell>129</ns0:cell><ns0:cell>0.382</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[85]</ns0:cell></ns0:row><ns0:row><ns0:cell>J</ns0:cell><ns0:cell>Sensory</ns0:cell><ns0:cell>peripheral cortex;</ns0:cell><ns0:cell>Drosophila</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>4844</ns0:cell><ns0:cell>350</ns0:cell><ns0:cell>0.794</ns0:cell><ns0:cell>NMO_ 54509</ns0:cell><ns0:cell>[71]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>neuron</ns0:cell><ns0:cell>nervous Purkinje layer</ns0:cell><ns0:cell>melanogaster</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>79779</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Z</ns0:cell><ns0:cell>Purkinje</ns0:cell><ns0:cell>system; cuticle cerebellum;</ns0:cell><ns0:cell>Mouse</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>993</ns0:cell><ns0:cell>107</ns0:cell><ns0:cell>0.196</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[86]</ns0:cell></ns0:row><ns0:row><ns0:cell>K</ns0:cell><ns0:cell cols='2'>Pyramidal hippocampus vermis,</ns0:cell><ns0:cell>Mouse</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>775</ns0:cell><ns0:cell>38</ns0:cell><ns0:cell>0.741</ns0:cell><ns0:cell>NMO_ 93863</ns0:cell><ns0:cell>[72]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>anterior,</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>71409</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>L</ns0:cell><ns0:cell cols='2'>Pyramidal medial lobule V</ns0:cell><ns0:cell>Rat</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>804</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>0.385</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[73]</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell>prefrontal;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>66093</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>layer 5</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>M</ns0:cell><ns0:cell cols='2'>Pyramidal subiculum;</ns0:cell><ns0:cell>Rat</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>856</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>0.325</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[74]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>stratum</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>34951</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>pyramidale</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>N</ns0:cell><ns0:cell cols='2'>Pyramidal subiculum;</ns0:cell><ns0:cell>Rat</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>708</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>0.352</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[74]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>stratum</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>34958</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>pyramidale</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>O</ns0:cell><ns0:cell cols='2'>Pyramidal hippocampus;</ns0:cell><ns0:cell>Mouse</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>848</ns0:cell><ns0:cell>38</ns0:cell><ns0:cell>0.357</ns0:cell><ns0:cell>NMO_</ns0:cell><ns0:cell>[75]</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>CA1;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>50703</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>pyramidal</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:48151:1:1:NEW 17 Sep 2020)Manuscript to be reviewed</ns0:note></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:04:48151:1:1:NEW 17 Sep 2020)</ns0:note> <ns0:note place='foot' n='3'>PeerJ reviewing PDF | (2020:04:48151:1:1:NEW 17 Sep 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:04:48151:1:1:NEW 17 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"10 August 2020 Dear Dr. Jafri Abdullah, Thank you for providing us with the opportunity to revise and resubmit our manuscript “Spatially resolved dendritic integration: Towards a functional classification of neurons” for consideration in PeerJ. In our revisions we have addressed all points raised by the reviewers, and our detailed responses are below. We hope that you will find the revised manuscript suitable for publication. We look forward to hearing from you. Sincerely yours, Leonardo Gollo, PhD (corresponding author) Head, Brain Networks & Modelling Group Senior Lecturer | ARC Future Fellow Turner Institute for Brain and Mental Health Monash University, Australia [email protected] Reviewer Responses We thank the reviewers for their interest in our manuscript and their constructive feedback. In what follows, we provide a point-by-point response (in black text) to each reviewer comment (in blue). Text edits in the revised manuscript are highlighted in italic. Reviewer 1 (Anonymous) Basic reporting 1. Line 40: 'Filters' should be 'filter', just grammatically. This typo has been corrected. 2. Line 39 -1: If by punctual you mean point-neuron models, these have no dendrites at all. Furthermore, the statement, 'dendrites are not passive media that filters electric input' makes it seem like there is no passive filtering at all, which there is. More generally, the study clearly focuses on active, nonlinear properties of dendrites, but the article would improve by acknowledging the existence of passive, linear properties, and especially by briefly explaining your reasoning for focusing on dendritic spikes. We have edited the Introduction and Methods to clarify that passive propagation properties are ubiquitous in dendrites. Of course, we do not want to omit this feature or claim it has no role. Instead, we also want to address the role of active properties that allows for long-distance propagation of signals along dendrites and multiple bifurcation points. In the Introduction, we have clarified the roles of passive as well as active properties of dendrites: In stark contrast to what some simple and influential point-neuron models suggest, such as the leaky integrate-and-fire model [12] and the Hodgkin-Huxley model [13], neurons can have large and intricate morphological structure that processes and integrates complex spatial patterns of input coming from thousands of synapses. Additionally, dendrites are not only passive media that filter electric input by leaking part of the current and propagate the rest. Instead, in addition to these passive properties, dendrites are also capable of producing supralinear amplification called dendritic spikes that occur owing to the voltage-gated dynamics of ion channels [14-16]. These nonlinear properties can boost the signal and generate interactions between neighboring compartments that are crucial to facilitate the transmission of information along extensive dendritic trees. Hence, spikes caused by neuronal integration of input from various synaptic sources depend on these non-linear (non-additive) dynamics taking place at dendrites with complex topology. Much work has been done to investigate how topology determines the capability of single neurons to detect intensity of stimulus [17], to reliably detect dendritic spikes [18], to discriminate input patterns [19], and to perform other forms of dendritic computation [20-22]. There has also been some attempts to study this problem analytically [23, 24]. However, given the complexity of the task, they are usually limited to regular or oversimplified dendritic structure [23]. In the Methods, we have clarified that the probabilistic transmission of activity accounts for the passive filtering, as well as the net effects of potential inhibitory synapses: A signal propagates to a susceptible neighboring compartment with a constant probability P. The probability of a failure to propagate (1-P) represents the net effect of two different contributions: the passive dumping of signal amplitude that propagates along dendrites, and the inhibitory incoming signals. Both contributions can be responsible to prevent the threshold required to generate a dendritic spike to be reached, and thus represent a failure in propagation of activity. 3. Table 1: Please include brain region for each cell - for instance, hippocampal vs cortical pyramidal cells As requested, we have updated the table to include the brain regions of neurons. 4. While I understand that the model has been previously published elsewhere, I believe this study would improve from a slightly more detailed description of it. Could you elaborate on the justification for the probability of spike propagation between compartments being < 1? Is there experimental evidence that in the absence of inhibitory inputs, dendritic spikes fail to propagate once initiated? In our probabilistic model, the failure to propagate that takes place with probability 1-P corresponds to the passive filtering that reduces the intensity of signals and also the contribution of inhibitory synapses at the specific site. The rationale is that there is also some reduction in the signal and if the activity doesn’t reach a threshold on the neighbour compartment, its subthreshold activity may die out with a certain probability, which is varied in the study, typically from 0 to 0.5. If the failure of propagation is larger than 0.5, only trivial dynamics can take place, and the spatial contribution of the dendritic tree to the neuronal spikes, that we want to estimate, quickly becomes negligible. Again, this point has been clarified in the Methods: A signal propagates to a susceptible neighboring compartment with a constant probability P. The probability of a failure to propagate (1-P) represents the net effect of two different contributions: the passive dumping of signal amplitude that propagates along dendrites, and incoming inhibition. Both contributions can be responsible to prevent the required threshold to generate a dendritic spike to be reached, and thus represent a failure in propagation of activity. Experimental design 1. The list of included cells is heavily biased towards pyramidal cells. Adding some more diversity to the cell types investigated would greatly increase quality of the study. We have thoroughly characterized the dynamics of dozens of neurons that have a large number of compartments and a represent a fine resolution for neuronal reconstruction that passed our quality control. Our results indicate that the different categories of the classification that we propose here have been sufficiently covered, and some of them have somewhat few exemplar neurons with high-quality reconstructions. We do agree that adding more neurons can increase the diversity of the sampling, but that goes beyond our aims. Furthermore, we have provided the code that allows any interested researcher to address their specific questions exploring any type of neuron available in the database (which includes more than 135K neurons). This has been clarified in the Discussion: The study was also primarily focused on neurons with high-quality and fine-resolution reconstructions (with large number of compartments), but it was comprised of a large proportion of pyramidal neurons. By incorporating more neuron types, the diversity of the sampling can be increased, and this approach may be effective to further explore the relationship between dendritic topology and neuronal function. 2. Do you perform any quality control on morphologies you're using (i.e. check for irregularities in diameter or other artifacts)? Some artifacts are present in morphologies available on NeuroMorpho, and sometimes morphologies from certain labs can be plagued with specific problems. Some of these probably have little impact on the results, but it would be helpful to know if the cells you chose pass any sort of initial testing. We have carefully selected the set of neurons in two waves. First we focused only on high-quality reconstructions with a large number of compartments that were more suitable to highlight the effects of the dendritic spatial structure. From this first set of results we realized that different categories of neurons existed but we had few neurons with only one or two branches connected to the soma. Hence, we added more neurons to populate the different categories and to be more certain about our classification. Irregularities in the diameter were not detected in any selected neuron. We have edited the Methods: We focused on a variety of neurons with high-quality reconstructions, based on visual inspection and diameter regularity. The sampling was such that a large portion of a two-dimensional space comprising the number of branches connected to the soma and the relative centrality of the soma was covered, which were main topological features of neurons. 3. It seems as though the dendritic spikes and backpropagating action potentials are treated equivalently here. If this is not the case, please clarify. If it is, however, I do not believe there is sufficient justification. Since spikes generated in the dendrites are mediated by NMDA or voltage-gated calcium channels, and backpropagating action potentials are mediated by sodium channels, this will impact the spiking dynamics, or in the context of this model the state transition probabilities. I would expect this would also distinguish their impact on energy consumption. The basic excitable mechanisms are modelled in the same way as we are not modelling the dynamics of ion channels but instead the resulting net effect. A simple way to incorporate this asymmetry is by adding one parameter (0<beta<1) that multiplies P when backpropagation takes place. This has been done before in a series of previous papers [17, 24, 39]. This additional parameter changes the shape of the response function but typically not the dynamic range, as the values of , and are essentially preserved. This has been clarified in the Methods: For simplicity, here we assume that the probability of forward and backward propagation is the same, as previous work incorporating different probabilities of propagation, depending on the direction, found that they affect the shape of the response function but have little influence on other measures such as the dynamic range [17, 24, 39], which will be explored here. 4. What seems to me a shortcoming of the model is that the probability of generating a spike in one compartment is not influenced by the synaptic activity (subthreshold post synaptic potentials) in adjacent compartments. Another is the uniformity of dynamics. Different types of spike are generated in different parts of the neuronal arbor. Furthermore, some review, even if cursory, of what has been seen experimentally regarding dendritic spikes in the cell types studied here. For instance, are dendritic spike as prevalent in pyramidal cells as in Purkinje cells? Previous studies have focused on heterogeneous spatial behaviour [39], which were motivated by the fact that the distribution of ion channels are not homogeneous along dendrites, nor are the distribution of synapses [17, 24]. However, these studies do not take into account many neurons with realistic and detailed dendritic trees with thousands of compartments. Because we did not have precise information on these parameters to constrain our model, we have explored only the homogeneous model. Furthermore, we are not aware of systematic studies characterizing the spatial distribution of ion channels and electrophysiological properties that include all the different types of neurons and species used in the manuscript. A more restricted subset of neurons, satisfying these specific properties, can be used in future studies to identify their role. In the Methods section we have clarified: Previous works using regular dendrites have explored the effects of spatial-dependent dynamics [39] and synaptic input [17, 24]. Here, for simplicity, we assumed that the dynamics of all compartments is identical because detailed information regarding how heterogeneous activity takes place in various neuron types from different species and brain regions is absent. Validity of the findings 1. How does categorization of cells based on energy consumption compare to their anatomical and physiological categories? This is a key follow up question from our study, and we believe neuronal morphology and its intrinsic topology play a major role to shape anatomical and physiological categorizations. A lot of work has focused on anatomical and physiological properties, and we acknowledge this as a main line of research in the field. However, this more standard approach also has major limitations caused by the extraordinary complexity of the problem, which requires meticulous information about a large number of non-linear interacting elements. They can comprise a very large number of parameters of a detailed model. Furthermore, the parameters for the different types of ion channels are often found to be spatially dependent, and precisely how this dependency takes place is not fully understood. Finally, the amount of electrophysiological data covering the entire dendritic tree in different neurons is still very limited. Hence, despite important, substantial work from many groups is required to elucidate this question. Our approach can be considered a workaround to this hard question, and focuses mostly on the topology, overlooking many details. Nonetheless, we believe these are relevant features that can be used to guide future research on the topic. We have also added to the Discussion: Our classification based on neuronal topology, together with other forms of neuronal classification that take into account species, anatomical region, morphological, and electrophysiological properties of neurons, may lead to more accurate functional classification schemes. Comments for the Author This study addresses some important, pressing questions in neuroscience: What is the relationship between morphology and dendritic spiking, and what are the energetic requirements? The authors employ interesting and novel methods to explore these questions. We thank the reviewer for the assessment and constructive feedback. I have two general comments that if addressed I believe will greatly improve the manuscript. First, while all models make simplifications, I think it would be worth further addressing what this model ignores and why it ignores it. We are addressing a long-lasting and challenging question, and to be able to advance in the specific question of the spatial contribution of the dendritic tree, we did simplify the problem. We captured the essential features of excitable media, and overlooked many parameters that are often unknown, different across neurons, and also spatially dependent within neurons. This simplification allowed us to characterize the dynamics of many neurons, and to propose a new approach for functional classification of neurons, taking advantage of the fact that many groups have previously worked in characterizing neuronal structure, and that an enormous amount of data has been collated and made available to anyone. Essentially, our steps are the first steps towards this multimodal functional classification of neurons, and future work is required to incorporate these overlooked features. We have clarified our assumptions and approach in the Methods: To estimate the spatial contribution of dendrites to the neuronal activity of digitally reconstructed neurons, a number of simplified assumptions was considered. The dynamics of each node was simulated using a simple model that represents the dynamics of excitable media. The dynamics of 26 different neurons from 6 different species (see details on Table 1), was characterized. Because details on the spatial distribution of all those neurons are not available, homogeneous dynamics was assumed, and the main goal was to better understand the contribution of the dendritic topology and their bifurcations on the dynamics of neurons. Given the large number of compartments and bifurcations that make up the dendritic arbor, any attempts of analytically modelling the propagation and interaction of potentially hundreds of spikes simultaneously are rendered nearly impractical and hence we focused on numerical experiments. Further, we expect these interactions to be highly non-linear owing to the heterogeneity of the neuronal topology. We overcome this complexity in spike dynamics by adapting a discrete computational model from previous studies [17, 24, 39]. Our model preserves the main features of excitable systems, and by implementing real dendritic structures, we focus on the resultant spatial properties of neurons with active dendrites. Second, I think it would be useful to try drawing more of a connection between your results and physiology (e.g. What particular cell types might belong to which energy consumption categories? Or how does the dynamic range of dendrites observed in this study compare to experimentally observed dendritic spike frequencies?) This is definitely a very thrilling avenue for future work. Unfortunately, in practical terms most of these electrophysiological experiments are challenging and limited information exists on the characterization of spatiotemporal activity of neurons, mostly due to the technical difficulties involved. The dynamic range, is a standard measure, but most data focusing on the dynamic range is measured at the soma. A proper measure of the dynamic range is also experimentally challenging because it requires long averages across time for a reliable measure, and the input level has to be varied over orders of magnitude, whilst the entire experimental setup remains intact. Hence, it is a challenge to keep the neuron alive and responding with recordings from multiple sites. As a result, the soma is the main focus in the literature and the dynamic range of dendritic sites and the spatial contribution of dendrites remain largely overlooked. We hope the computational endeavour proposed here will motivate future electrophysiological experiments aiming at covering this gap in knowledge. In the Discussion we have included: Our classification based on neuronal topology, together with other forms of neuronal classification that take into account species, anatomical region, morphological, and electrophysiological properties of neurons, may lead to more accurate functional classification schemes. Reviewer 2 (Hanbing Song) Basic reporting This manuscript is well written overall with sufficient background context and references provided. However, the following points might be improved for readers to better comprehend the major findings of this manuscript. We thank the reviewer for the careful reading of the manuscript and the constructive suggestions. 1. At the end of the Introduction, the authors stated that the analysis of the topological structure of dendritic trees would help the classification of neurons. Here the authors should clarify what it means to classify neurons, in terms of functionality, or types of excitatory/inhibitory synapses, or anatomical regions, or consumption of energy. We have rewritten the Introduction to clarify that we propose a new type of functional classification. We have also added to the Discussion that our proposal, focusing on specific dynamic properties of neurons, can be considered a starting point towards more accurate functional classification of neurons, taking into account all the different variables. In the Introduction we have added: By applying this theoretical framework, our main aim is to investigate the implications of complex and realistic dendritic structure on dendritic integration and neuronal activity. We characterize the effects of topological properties of the neurons on the dynamic range of the response functions, which quantifies the ability of neurons to discriminate the intensity of incoming input, and show the contribution of bifurcations to heterogeneous activity. We identify distinctive dynamical behaviors of different types of neurons, induced by the dendritic topology, that reflect dynamical properties of the rate of activity of the soma with respect to the dendritic tree. Finally, we show how these findings can be explored to provide a novel functional classification of neurons. In the Discussion we have added: They have a tree topology, and their morphological features are crucial for classification. However, additional attempts have also been made to classify neurons based not only on their morphology but taking into account features of their electrophysiology, and their dynamics [1, 9, 74, 75]. These proposals attempt to improve neuronal classification with information about dynamics and function of neurons. Along this line, here we propose to incorporate a few key structural features that inform about neuronal dynamics and function. Our classification based on neuronal topology, together with other forms of neuronal classification that take into account species, anatomical region, morphological, and electrophysiological properties of neurons, may lead to more accurate functional classification schemes. 2. In the method section, the authors did a great job describing the SIRS model but the readers will understand more easily and intuitively if the equations are provided explicitly. We have used a simple map with discrete time and discrete space to model the dendritic dynamics. We have introduced an explicit equation to describe the probabilistic activity that excites compartments. After excitation, the following transitions to the refractory and susceptible states are deterministic. We have added to the Methods: The model is a discrete map, and the probability of a susceptible site to be excited in the next time step depends on the activity of its neighbors, and can be written as: , where is the Kronecker delta, and is the state of the neighbor compartment . 3. In the method section, it seems that the authors did not specify which software/HPC was used to run these simulations. We used Matlab to simulate the dynamics with a custom code, which is available to download. We have added to the Methods: The simulations were performed in MATLAB (MathWorks Inc.) using a custom code (see Code availability). Experimental design 1. The authors selected 26 digital reconstructions from NeuroMorpho. However, it is unclear why these 26 neurons were picked. It will make the study more impactful if the authors show that the samples in this study are representative of most neuronal topological structures. We selected 26 neurons that have passed our quality control and have a high resolution, and hence many compartments (minimum 413, and maximum 9678). Our code is available so that any other neuron can be explored by any researcher. We have clarified our rationale in the Methods and Discussion. We have added to the Methods: We focused on a variety of neurons with high-quality reconstructions, based on visual inspection and diameter regularity. The sampling was such that a large portion of a two-dimensional space comprising the number of branches connected to the soma and the relative centrality of the soma was covered, which were main topological features of neurons. We have added to the Discussion: The study was also primarily focused on neurons with high-quality and fine-resolution reconstructions (with large number of compartments), but it was comprised of a large proportion of pyramidal neurons. By incorporating more neuron types, the diversity of the sampling can be increased, and this approach may be effective to further explore the relationship between dendritic topology and neuronal function. 2. The use of network metrics such as closeness centrality is very clever in evaluating the neuronal structure. However in this study based on SIRS model, only excitatory input is considered whereas in reality each neuron is embedded with a combination of inhibitory and excitatory inputs. The coexistence of inhibitory and excitatory inputs, theoretically, could make the spiking properties much more complicated. I am wondering if the authors could provide some insight on how the addition of inhibitory input would affect the classification. We assume that the external driving is the net input of all synapses located in each compartment. Hence inhibition is considered only implicitly in this description of the dynamics of dendrites. A more explicit separation between excitatory and inhibitory contribution can indeed make the dynamics more realistic but also more complicated. In a similar context of networks of SIRS nodes, inhibition was studied before, and it did not impact much the dynamics of the network [43]. For this reason, as a first step, here we focused only on the simplest case without an explicit description of inhibition. To clarify this point, we have edited the Discussion: We argue that our simple modelling approach retains the essential features to simulate the dynamics of excitable systems without the burden of an excessive number of details and parameters. However, this is clearly a simplification, and future work should address the role of more sophisticated biophysical models with additional free parameters that describe the membrane potential of dendritic branches as continuous variables (differential equations, instead of a map with discrete states [56]), and explicitly consider the contributions of excitatory and inhibitory synapses. Here, as a first step, inhibition is only implicitly considered in the net synaptic contribution since in a previous study using a similar dynamic model inhibition did not show much impact in the dynamic range of the network whilst requiring additional free parameters [43]. 3. SIRS model, in terms of computational cost, is relatively low. In this case, is it possible to test one neuron from each of the three categories by imposing a soma-to-soma connection within an Erdos-Renyl network given a fixed connection probability? On a network level, consumption of energy and closeness centrality would be more functionally relevant. Our measures of energy consumption and centrality can be extended to any network. In our case, the networks have a tree topology and represent a variety of real neurons with complex structure. We agree that these measures can be informative in more general contexts of other networks. A random network is likely not the best example, as it has no spatial structure and is fairly homogeneous across nodes, and often accurately described by mean-field approximations in theoretical models. Our measures were developed precisely to highlight the spatial differences between subparts of the network. In our case the networks are neurons, and the subparts of interest are mainly the soma and the dendrites. The extent to which our approach also hold for circuits and networks of spiking neurons is an exciting point. This suggestions has been incorporated to the Discussion: Going beyond single neurons, which have a tree topology with no loops, future work should test whether topological features (such as centrality and degree) of more general networks can also inform spatiotemporal patterns of activity in networks of larger scales of circuits, columns, and brain regions. Furthermore, the dynamics of networks depend on the diversity of neurons and properties of neuronal integration [42, 43, 56]. Hence, it remains to be determined how the different types of neurons proposed here influence the activity of networks. Validity of the findings Based on the various centrality and consumption of energy properties, the authors proposed a 3-category classification of neurons. However, if possible, a more thorough functional implication is appreciated to show if this classification is any indication with respect to its anatomical region. Based on our approach, we could not find evidence for the role of anatomical region to neuronal function. Most likely a much larger sampling is required to address this question. Many types of neurons can exist within a specific region, and they can be specialized on different functions. An example is the Purkinje cell and the granule cell of the Cerebellum. We expect future approaches to incorporate additional features (including topology of neurons) to characterize specific neuron types more accurately, within an anatomical region of a given species. This has been included in the Discussion: Our classification based on neuronal topology, together with other forms of neuronal classification that take into account species, anatomical region, morphological, and electrophysiological properties of neurons, may lead to more accurate functional classification schemes. Furthermore, to validate the symmetry of the dendritic modeling, the manuscript will be more impactful to include some electrotonic analysis. For example, dendritic structures from NeuroMorpho could be imported in NEURON or other simulators, where the inward/outward impedance could be easily computed. I understand that at this stage adding in dendritic diameters would add considerable complexity, but this type of validation is necessary to make any functional connection between dendritic topology and firing properties. We thank the reviewer for this suggestion, which was added as a next step to validate the classification proposed here. This constitutes a major effort because a number of parameters are unknown. Each compartment will need to be represented by several parameters, and finding suitable sets of parameters for all neurons, such that the net activity of the neuron is meaningful have their own challenges. We have added to the Discussion: Future studies including electrotonic analysis will require more parameters but will represent an important validation step of our findings and may lead to a better understanding of the relationship between dendritic topology and function. Comments for the Author The authors proposed a very novel and systematic way of analyzing neuronal dendritic topology by adopting concepts such as the consumption of energy and centrality metrics. In conclusion, the authors classified neurons into three categories based on their dynamic range and firing behavior. However, in the field of computational neuroscience, multiple simulators are on the market for biophysically realistic modeling of complicated dendritic structure, on both cellular and network levels. With the help of HPCs and parallel computing, multi-compartmental models of neuronal networks have been proposed. Under this circumstance, the insight drawn from a simplified model without dendritic spatial structure or diversified synapses is limited. Therefore several aspects could be improved to make this work more impactful and helpful to the modeling society. All models have limitations, and characterizing the spatial contribution of the dendrites is far from a trivial problem. Many simulators do exist, and the problem remains unsolved. A main challenge is due to the complexity of the problem, and on the number of parameters required to have a more general and realistic model that works for any neuron. To be able to extract basic spatiotemporal patterns of activity, here we simplify the problem using the dynamics of a general excitable system, After studying many neurons, we found that only a small number of neuron types is observed, and they can be characterized by only two essential features of the neuronal topology. Of course, this can be considered as a first step towards a much bigger problem. There is plenty of room to incorporate additional biophysical properties but the challenge to make them work across neuron types remains substantial. We appreciate the suggestions and, by addressing them, we have improved the manuscript. We have clarified the assumptions of the models at the beginning of the Methods. Furthermore, the code is available to attract other researchers to this fundamental problem. We have clarified our assumptions and approach in the Methods: To estimate the spatial contribution of dendrites to the neuronal activity of digitally reconstructed neurons, a number of simplified assumptions was considered. The dynamics of each node was simulated using a simple model that represents the dynamics of excitable media. The dynamics of 26 different neurons from 6 different species (see details on Table 1), was characterized. Because details on the spatial distribution of all those neurons are not available, homogeneous dynamics was assumed, and the main goal was to better understand the contribution of the dendritic topology and their bifurcations on the dynamics of neurons. Given the large number of compartments and bifurcations that make up the dendritic arbor, any attempts of analytically modelling the propagation and interaction of potentially hundreds of spikes simultaneously are rendered nearly impractical and hence we focused on numerical experiments. Further, we expect these interactions to be highly non-linear owing to the heterogeneity of the neuronal topology. We overcome this complexity in spike dynamics by adapting a discrete computational model from previous studies [17, 24, 39]. Our model preserves the main features of excitable systems, and by implementing real dendritic structures, we focus on the resultant spatial properties of neurons with active dendrites. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. Mapping techniques using cardiac magnetic resonance imaging have significantly improved the diagnostic accuracy for myocarditis with focal myocardial injuries. The aim of our study was to determine whether T1 and T2 mapping techniques could identify diffuse myocardial injuries in 'normal-appearing' myocardium in pediatric patients with clinically suspected myocarditis and to evaluate the associations between diffuse myocardial injuries and cardiac function parameters.</ns0:p><ns0:p>Methods. Forty-six subjects were included in this study: 20 acute myocarditis patients, 11 subacute/chronic myocarditis patients and 15 control children. T2 values, native T1 values and the extracellular volume (ECV) of 'normal-appearing' myocardium were compared among the three groups of patients. Associations between diffuse myocardial injuries and cardiac function parameters were also evaluated.</ns0:p></ns0:div> <ns0:div><ns0:head>Results.</ns0:head><ns0:p>The ECV of 'normal-appearing' myocardium was significantly higher in the subacute/chronic myocarditis group than in the control group (30.1&#177;0.9 vs 27.0&#177;0.6, P=0.004). No significant differences in T1 and T2 values between the acute myocarditis and control groups were found. In the subacute/chronic myocarditis group, a significant association between ECV and left ventricle ejection fraction was found (P=0.03).</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions.</ns0:head><ns0:p>Diffuse myocardial injuries are likely to occur in subacute/chronic myocarditis patients with prolonged inflammatory responses. Mapping techniques have great value for the diagnosis and monitoring of myocarditis.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Myocarditis is a myocardial inflammatory disease associated with various injuries, clinical manifestations and outcomes. <ns0:ref type='bibr' target='#b0'>[1,</ns0:ref><ns0:ref type='bibr' target='#b1'>2,</ns0:ref><ns0:ref type='bibr' target='#b2'>3]</ns0:ref> Myocarditis has been identified as a significant cause of sudden death in children. <ns0:ref type='bibr' target='#b3'>[4,</ns0:ref><ns0:ref type='bibr' target='#b4'>5]</ns0:ref> In addition, myocarditis may be an underlying cause of dilated cardiomyopathy (DCM) (up to 40% of DCM cases are caused by myocarditis) <ns0:ref type='bibr' target='#b5'>[6]</ns0:ref> and may result in death or cardiac transplantation as long as 12 years after diagnosis. <ns0:ref type='bibr' target='#b6'>[7]</ns0:ref> Cardiac magnetic resonance (CMR) has been an established noninvasive tool for the diagnosis and evaluation of myocarditis. <ns0:ref type='bibr' target='#b8'>[8]</ns0:ref> Conventional CMR imaging, including T2 weighted imaging, T1 weighted imaging and late gadolinium enhancement (LGE) imaging, is most useful for evaluating focal myocardial injuries by visually comparing the affected area with the normal myocardium. <ns0:ref type='bibr' target='#b10'>[9]</ns0:ref><ns0:ref type='bibr' target='#b12'>[10]</ns0:ref> These combined imaging sequences are an essential part of the 'Lake Louise' criteria (2009) <ns0:ref type='bibr' target='#b10'>[9]</ns0:ref> and have considerable diagnostic accuracy in myocarditis patients with angina-like symptoms and recent symptom onset <ns0:ref type='bibr' target='#b13'>[11]</ns0:ref><ns0:ref type='bibr' target='#b15'>[12]</ns0:ref><ns0:ref type='bibr' target='#b17'>[13]</ns0:ref> .</ns0:p><ns0:p>Diffuse myocardial injuries in myocarditis may present as 'normal-appearing' myocardium if it is not compared to normal Manuscript to be reviewed reference muscles <ns0:ref type='bibr' target='#b10'>[9,</ns0:ref><ns0:ref type='bibr' target='#b18'>14]</ns0:ref> .</ns0:p><ns0:p>Currently, T1 and T2 mapping techniques are applied to determine the diagnosis and prognosis of myocarditis. Mapping techniques offer a quantitative assessment of the myocardium by using standardized, reproducible T1 and T2 values and have the potential to identify both focal and diffuse myocardial injuries from myocarditis <ns0:ref type='bibr' target='#b12'>[10]</ns0:ref> . Extracellular volume (ECV), which is derived from the ratio of pre-and postcontrast T1 values, can measure the fraction of volume occupied by the extracellular space in the myocardium and has become a marker of myocardial tissue remodeling [15] . In 2018, updated 'Lake Louise' criteria <ns0:ref type='bibr' target='#b22'>[16]</ns0:ref> were published, and parametric mapping techniques were included in the diagnostic criteria for myocardial inflammation. Compared with that of the original 'Lake Louise' criteria, significantly improved diagnostic accuracy has been reported in patients with myocarditis using mapping techniques <ns0:ref type='bibr' target='#b15'>[12]</ns0:ref><ns0:ref type='bibr' target='#b17'>[13]</ns0:ref><ns0:ref type='bibr' target='#b25'>17]</ns0:ref> . In addition, diffuse myocardial injuries in DCM <ns0:ref type='bibr' target='#b27'>[18]</ns0:ref> , myocardial infarctions <ns0:ref type='bibr' target='#b28'>[19]</ns0:ref><ns0:ref type='bibr' target='#b29'>[20]</ns0:ref> and heart failure <ns0:ref type='bibr' target='#b30'>[21]</ns0:ref><ns0:ref type='bibr' target='#b32'>[22]</ns0:ref> have been reported by mapping techniques. Myocarditis with focal myocardial injuries has been fully shown using conventional CMR and mapping techniques. However, myocarditis with 'normal-appearing' myocardium that might result from diffuse myocardial injuries has received less attention.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>In our study, we focused on the 'normal-appearing' myocardiummyocardium without focal myocardial edema or necrosis/fibrosis visible on conventional CMR-in pediatric patients with clinically suspected myocarditis. We attempted to determine whether T1 and T2 mapping techniques could identify diffuse myocardial injuries in pediatric myocarditis patients, and we then evaluated whether there were associations between diffuse myocardial injuries and cardiac function in these patients.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and methods</ns0:head><ns0:p>In this prospective study, pediatric patients with clinically suspected myocarditis from Feb 2016 to Jan 2018 in our hospital were included. All patients were diagnosed by an experienced pediatrician according to the myocardial diagnostic criteria proposed by the European Society of Cardiology Working Group on Myocardial and Pericardial Diseases <ns0:ref type='bibr' target='#b33'>[23]</ns0:ref> .</ns0:p><ns0:p>According to the duration of symptoms from onset to CMR examinations, myocarditis patients were divided into 2 groups: the acute myocarditis (AM) group (&#8804; 3 months) and the subacute/chronic myocarditis (CM) group (&gt;3 months). Exclusion criteria were contraindications for CMR, coronary artery diseases, congenital heart diseases, cardiomyopathies, or other medical history of cardiac disease <ns0:ref type='bibr' target='#b13'>[11]</ns0:ref> . Clinical manifestations, immunological </ns0:p></ns0:div> <ns0:div><ns0:head>CMR imaging protocol</ns0:head><ns0:p>CMR imaging was performed using a MAGNETOM Skyra 3T MR scanner (Siemens Healthcare, Erlangen, Germany) with an 18-channel body matrix coil. All data acquired was retrospectively gated based on the ECG results.</ns0:p><ns0:p>Respiratory gating was applied in pediatric patients who could cooperate for a breath-hold during the CMR examinations (usually patients older than 6 years old), and CMR images were acquired at the end-expiratory point.</ns0:p><ns0:p>Patients who could not hold their breath (usually younger than 6 years old)</ns0:p><ns0:p>were sedated with 10% chloral hydrate solution and examined under freebreathing conditions.</ns0:p><ns0:p>The CMR imaging protocols included T2-weighted imaging, LGE imaging, T1 mapping was performed with 3(3)5 modified Look-Locker inversion recovery (MOLLI) sequences in the HLA and three SA orientations (basal, mid and apical ventricular SA planes) <ns0:ref type='bibr' target='#b15'>[12,</ns0:ref><ns0:ref type='bibr' target='#b35'>24]</ns0:ref> Manuscript to be reviewed size=1.4x1.4x8.0 mm&#179;. T2 mapping was acquired using a SSFP sequence with three different T2 preparation times in the HLA and three SA orientations (basal, mid and apical ventricular SA planes). The parameters were as follows: TE=0 ms, 25 ms, 55 ms; TR=3 x RR; FA=50&#176;; FOV= 300x225 mm 2 ; acquisition matrix= 256x384 mm 2 ; and voxel size= 0.9x0.9x8.0 mm&#179;.</ns0:p></ns0:div> <ns0:div><ns0:head>CMR image analysis</ns0:head><ns0:p>All the original image data were processed on the workstation (Siemens Medical Systems). Two experienced CMR radiologists (C.Y.W and H.P.W),</ns0:p><ns0:p>who were blinded to patient information, independently analyzed all CMR images.</ns0:p><ns0:p>Left ventricular (LV) cardiac function parameters were evaluated in the cine images. LV endocardial and epicardial contours were drawn manually for each diastolic and systolic frame in the sequential SA cine images, and LV cardiac function parameters, including end-diastolic volume (EDV), endsystolic volume (ESV), left ventricle ejection fraction (LVEF), LV mass and stroke volume (SV), were automatically acquired on the workstation. LV cardiac function parameters were standardized as follows <ns0:ref type='bibr' target='#b36'>[25]</ns0:ref> : Manuscript to be reviewed parameters/ body surface area (BSA).</ns0:p><ns0:formula xml:id='formula_0'>Standardized</ns0:formula><ns0:p>The papillary muscles and trabeculations were included as part of ventricular cavity <ns0:ref type='bibr' target='#b37'>[26]</ns0:ref> .</ns0:p><ns0:p>Myocardial edema and necrosis/fibrosis were defined by visual assessment in the T2-weighted images and LGE images. The presence and location of myocardial edema or fibrosis were independently evaluated by two CMR radiologists according to the 17-segment model proposed by the American Heart Association (AHA) <ns0:ref type='bibr' target='#b38'>[27]</ns0:ref> . For the contradictory findings regarding myocardial injuries after independent evaluation, two CMR radiologists would discuss the findings together and reach a consensus.</ns0:p><ns0:p>The myocardium without edema or necrosis/fibrosis was defined as 'normal-appearing' myocardium, which might include normal myocardium and abnormal myocardium with diffuse myocardial injuries.</ns0:p><ns0:p>T1 and T2 values of 'normal-appearing' myocardium in the HLA and SA orientations were measured directly in their T1 and T2 maps. Endocardial Manuscript to be reviewed (ECV) of the 'normal-appearing' myocardium was calculated using native and postcontrast T1 values of the myocardium and blood pools as well as hematocrit (HCT), as follows <ns0:ref type='bibr' target='#b8'>[8]</ns0:ref> :</ns0:p><ns0:formula xml:id='formula_1'>ECV (%) = (1-HCT) &#215; (&#916;R1 of myocardium/&#916;R1 of blood pool) R1=1/T1; &#916;R1=postcontrast R1 -native R1</ns0:formula><ns0:p>The native and postcontrast T1 values of the blood pools were also measured directly in the LV cavity, avoiding the papillary muscle.</ns0:p><ns0:p>Myocardium with higher T1 and T2 values and ECV was identified as abnormal myocardium with diffuse myocardial injuries. </ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analysis</ns0:head></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Twenty pediatric patients with acute myocarditis (10 male; median age, 9 years old), 11 patients with subacute/chronic myocarditis (9 male; median age, 6 years old) and 15 control children (9 male; median age, 11 years old)</ns0:p><ns0:p>were included in the study.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Clinical characteristics</ns0:head><ns0:p>The clinical characteristics of all pediatric patients are shown in Table <ns0:ref type='table' target='#tab_5'>1</ns0:ref>.</ns0:p><ns0:p>The most common clinical manifestation in the AM group was chest pain/distress, which was present in eight AM patients (40.0%). In the CM group, six patients (54.5%) experienced palpitation. Abnormal cardiac troponin T (cTnT) or brain natriuretic peptide (BNP) levels were observed in nine AM patients (45.0%) and seven CM patients (63.6%). ECG abnormalities were detected in all AM patients and ten CM patients (90.9%).</ns0:p><ns0:p>The most common ECG finding in the AM group was ST-T changes (45.0%), while ventricular premature beats (VPBs) were common in the CM group (45.5%).</ns0:p></ns0:div> <ns0:div><ns0:head>CMR findings</ns0:head><ns0:p>The standard LV cardiac function parameters and myocardial tissue characterizations in the AM, CM and NC groups are shown in Manuscript to be reviewed parameters in the CM group are shown in Table <ns0:ref type='table'>4</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>In our study, we evaluated the tissue-related changes of 'normalappearing' myocardium in pediatric patients with clinically suspected myocarditis using mapping techniques. We found that ECV could detect diffuse myocardial injuries in 'normal-appearing' myocardium in pediatric CM patients, and ECV was associated with LVEF. Therefore, mapping techniques could increase the sensitivity of CMR for monitoring diffuse myocardial injuries in patients with clinically suspected myocarditis.</ns0:p><ns0:p>Mapping technologies could be influenced by numerous factors, including the MR scanner, magnetic field strength, exact sequence used, image acquisition plane, contrast agent dose and patient's physiological differences <ns0:ref type='bibr' target='#b12'>[10,</ns0:ref><ns0:ref type='bibr' target='#b28'>19,</ns0:ref><ns0:ref type='bibr' target='#b39'>[28]</ns0:ref><ns0:ref type='bibr' target='#b41'>[29]</ns0:ref><ns0:ref type='bibr' target='#b42'>[30]</ns0:ref> . In our study, the scanning protocols of the different mapping technologies were identical, and interaction tests and covariate screenings were performed to adjust for BSA, sex, age, heart rate and HCT of subjects and could minimize the influence of confounding variables.</ns0:p><ns0:p>LGE has been an established noninvasive tool to evaluate focal myocardial necrosis/fibrosis and has shown excellent correlation with pathology <ns0:ref type='bibr' target='#b8'>[8]</ns0:ref> . In acute 'infarct-like' myocarditis, a high sensitivity of LGE has Manuscript to be reviewed been reported <ns0:ref type='bibr' target='#b43'>[31]</ns0:ref> . However, it is not very sensitive in very mild myocarditis cases, which might have diffuse myocardial tissue-related changes. In contrast to LGE, ECV is well suited to measure focal and diffuse myocardial fibrosis and exhibits the best agreement with histological measures of the collagen volume fraction. ECV has been shown to be reproducible, predict outcomes and provide 'added prognostic value' in myocardial disease <ns0:ref type='bibr' target='#b22'>[16,</ns0:ref><ns0:ref type='bibr' target='#b44'>32]</ns0:ref> .</ns0:p><ns0:p>For myocarditis, ECV has been included in the updated 'Lake Louise' criteria <ns0:ref type='bibr' target='#b22'>[16]</ns0:ref> , which could certainly greatly improve the diagnostic sensitivity for myocarditis over that of the original 'Lake Louise' criteria, especially in myocarditis with diffuse myocardial injuries.</ns0:p><ns0:p>In our study, we found that the ECV of 'normal-appearing' myocardium was significantly higher in pediatric CM patients than in NC patients, which indicated diffuse myocardial injuries. Myocarditis has been identified as an underlying cause of DCM, and up to 40% of DCM cases are caused by myocarditis <ns0:ref type='bibr' target='#b5'>[6]</ns0:ref> . The availability of murine models of myocarditis has facilitated much of our understanding of the pathogenesis of myocarditis-DCM <ns0:ref type='bibr' target='#b47'>[33]</ns0:ref> . During the progression of myocarditis, inflammatory cells embedded in the interstitial matrix contribute to the inflammatory response and cardiac remodeling. The expansive interstitial matrix could be measured by ECV <ns0:ref type='bibr' target='#b20'>[15]</ns0:ref> . In our study, diffuse myocardial injuries were more likely to occur in CM patients than in AM patients. Abnormal cTnT or BNP was observed in 63.6% of CM patients during CMR examination, which was higher than that in AM patients (45.0%). We hypothesized that expansive interstitial matrix deposition was likely to occur in CM patients with prolonged and recurrent inflammatory responses. ECV might be a marker of myocarditis leading to DCM. The values of ECV related to the outcomes of CM patients have been followed up and will be discussed in future studies.</ns0:p><ns0:p>ECV quantification of interstitial expansion remains a powerful tool to investigate diffuse myocardial injuries.</ns0:p><ns0:p>In our study, native T1 values of the 'normal-appearing' myocardium were not significantly higher in AM and CM patients than in NC patients, which was inconsistent with recent data by Radunski UK et al. <ns0:ref type='bibr' target='#b18'>[14]</ns0:ref> . Radunski UK et al. found that native T1 values in the 'normal-appearing' myocardium of AM patients were significantly higher than the reference values from the myocardium of healthy volunteers. This discrepancy could be explained by the fact that all the AM patients who Radunski UK included had typical focal myocardial LGE findings, while the inflammatory response in our study was mild. Despite this, a higher ECV of 'normal-appearing' myocardium was observed in the CM group. Native T1 values perform as composite indicators of both intracellular and extracellular compartments <ns0:ref type='bibr' target='#b48'>[34]</ns0:ref> and,</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed therefore, can be less sensitive to increased extracellular space or more sensitive to other characteristics of the tissue (such as increased iron content, fatty deposition, and edema) <ns0:ref type='bibr' target='#b48'>[34]</ns0:ref> . ECV is derived from the ratio of T1 signal values and simply quantifies the interstitial presence of gadolinium relative to plasma <ns0:ref type='bibr' target='#b20'>[15]</ns0:ref> . ECV represents a physiological parameter, and its values are therefore reproducible. Therefore, ECV could reflect diffuse myocardial injuries with more sensitivity than native T1 values.</ns0:p><ns0:p>In our study, T2 values in the 'normal-appearing' myocardium of AM patients was not significantly higher than those in the NC group, which was in agreement with the findings of Radunski UK et al. <ns0:ref type='bibr' target='#b18'>[14]</ns0:ref> . In addition to the disadvantages of T2 mapping due to unstable myocardial edema <ns0:ref type='bibr' target='#b18'>[14]</ns0:ref> , we also reasoned that mild myocardial inflammation in our study would have influenced the results.</ns0:p><ns0:p>In our study, we found associations between ECV and LVEF in CM patients, which have also been reported in patients with diabetic cardiomyopathy, myocardial infarction, hypertrophic cardiomyopathy and heart failure <ns0:ref type='bibr' target='#b27'>[18]</ns0:ref><ns0:ref type='bibr' target='#b28'>[19]</ns0:ref><ns0:ref type='bibr' target='#b29'>[20]</ns0:ref><ns0:ref type='bibr' target='#b30'>[21]</ns0:ref><ns0:ref type='bibr' target='#b32'>[22]</ns0:ref> . The pathophysiology of myocarditis in murine models suggests that a persistent inflammatory response in the chronic phase of myocarditis leads to ventricular remodeling, which is characterized by myocyte hypertrophy, myocyte apoptosis, contractile dysfunction and Manuscript to be reviewed extracellular matrix volume expansion <ns0:ref type='bibr' target='#b0'>[1,</ns0:ref><ns0:ref type='bibr' target='#b1'>2,</ns0:ref><ns0:ref type='bibr' target='#b25'>17,</ns0:ref><ns0:ref type='bibr' target='#b50'>35]</ns0:ref> . ECV has become a marker of myocardial tissue remodeling <ns0:ref type='bibr' target='#b20'>[15]</ns0:ref> , and it could predict outcomes and provide 'added prognostic value' in myocardial disease <ns0:ref type='bibr' target='#b22'>[16,</ns0:ref><ns0:ref type='bibr' target='#b44'>32]</ns0:ref> . Early data indicate that ECV appears to be as prognostically important as LVEF <ns0:ref type='bibr' target='#b51'>[36,</ns0:ref><ns0:ref type='bibr' target='#b52'>37]</ns0:ref> ,</ns0:p><ns0:p>which underestimates the biological importance of the interstitium. In our study, CM patients had increased ECV and normal LVEF. ECV is comparable to LVEF as a marker to evaluate myocardial injuries.</ns0:p><ns0:p>This study has several potential limitations. First, the myocarditis patients involved in our study were diagnosed according to the diagnostic criteria for clinically suspected myocarditis proposed by the ESC Working Group on Myocardial and Pericardial Diseases <ns0:ref type='bibr' target='#b33'>[23]</ns0:ref> . Endomyocardial biopsy should be the gold standard for the definitive diagnosis of myocarditis. However, it might be unrealistic to perform biopsies in most pediatric myocarditis patients. In our study, 85.0% AM patients and 72.7% CM patients fulfilled more than 3 criteria for clinically suspected myocarditis, which increased the strength of the suspicion for myocarditis. Second, the severity of myocardial inflammation was less severe than that reported in other studies. We did not acquire significant results with native T1 mapping and T2 mapping. The diagnostic efficacy for myocarditis according to the 'Lake Louise' criteria was low. Third, the intervals from onset to CMR examinations varied based Manuscript to be reviewed on the patient's condition, which might have influenced the CMR findings.</ns0:p><ns0:p>Fourth, the number of pediatric myocarditis patients included in the study was limited. Analyses of larger populations should be performed in the future.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>In conclusion, diffuse myocardial injuries are likely to occur in CM patients with prolonged inflammatory responses. Mapping techniques have great value for the diagnosis and monitoring of myocarditis.</ns0:p><ns0:note type='other'>Figure 1</ns0:note><ns0:p>Comprehensive cardiac magnetic resonance images of a 14-year-old child with acute myocarditis.</ns0:p><ns0:p>He was hospitalized after four days of chest pain. LGE, late gadolinium enhancement; ECV, extracellular volume; ROI, region of interest; HLA, horizontal long axis; SA, short axis; ECV, extracellular volume.</ns0:p><ns0:note type='other'>Figure 2</ns0:note><ns0:p>The T1 and T2 values of 'normal-appearing' myocardium in AM, CM and NC groups.</ns0:p><ns0:p>Compared with NC group, the ECV of 'normal-appearing' myocardium significantly increased in CM group (C) after adjusted for BSA, sex, heart rate or HCT (SA: 30.1&#177;0.9 VS 27.0&#177;0. Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>myocardium. It can also be quantitatively analyzed by normalizing the signals of the myocardium to remote myocardium or skeletal muscles, although the diagnostic accuracy might be affected by abnormal signals of PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>before and 15 minutes after Gd-DTPA administration with the following parameters: TR/TE=2.4/1.1 ms, FA=35&#176;, FOV=300&#215;225 mm 2 , acquisition matrix=256&#215;192 mm 2 , and voxel PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>LV cardiac function parameters= LV cardiac function PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>and epicardial borders were carefully contoured to exclude artifacts, epicardial fat and blood pools. Then, the T2 values, native T1 values, and postcontrast T1 values of 'normal-appearing' myocardium in the HLA and three SA orientations were acquired (Fig 1). T1 and T2 values in three SA orientations were averaged for data analysis. The extracellular volume PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>Regional mid-wall myocardial edema of the interventricular septum and epicardial edema of the anterior, lateral, and inferior walls are shown in the end-diastolic (A, I) and end-systolic (B, J) cine images and T2-weighted images (C). Regional myocardial necrosis/fibrosis was also found in the identical location on LGE imaging (D, K). In the T2 maps (E, L), native T1 maps (F, M), post-contrast T1 maps (G, N) and ECV maps (H, O), the dotted line shows the ROI of the 'normal-appearing' myocardium excluding visible myocardial edema or necrosis/fibrosis on conventional MRI. T1 values, T2 values and ECVs of 'normal-appearing' myocardium were measured as follows: T2 values (HLA)=37.2ms, Native T1 values (HLA)=1292.4ms, ECV (HLA)=25.7%; T2 values (SA)=37.8ms, Native T1 values (SA)=1297.5ms, ECV (SA)=25.9%.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='33,42.52,276.49,525.00,294.75' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>. Two</ns0:cell></ns0:row></ns0:table><ns0:note>underwent CMR examinations with respiratory gating. There were no statistically significant differences in standardized EDV, ESV, LV mass, SVPeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020) Manuscript to be reviewed and LVEF among the AM, CM and NC groups. Regional myocardial edema or necrosis/fibrosis was found in 7 AM patients (35.0%) and four CM heart rate or HCT. The associations between ECV and LV cardiac function PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head /><ns0:label /><ns0:figDesc>6, P=0.004). No significantly statistical differences were found between T1 and T2 values in AM and NC group.</ns0:figDesc><ns0:table /><ns0:note>AM, acute myocarditis; CM, subacute/chronic myocarditis; NC, normal control; HLA, horizontal long axis; SA, short axis; ECV, extracellular volume</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Baseline characteristics of children</ns0:cell></ns0:row><ns0:row><ns0:cell>Values are presented as N (%), mean &#177; SE or median (range). *P values&lt;0.05.</ns0:cell></ns0:row><ns0:row><ns0:cell>NC, normal control; AM, acute myocarditis; CM, subacute/chronic myocarditis; HCT, hematocrit; HR, Heart rate; CMR, cardiac magnetic resonance; cTnT, cardiac troponin T; BNP, brain natriuretic peptide; ECG, electrocardiography; AVB, atrioventricular block; IVCB, intra-ventricular conduction block; APB, atrial premature beats; VPB, ventricular premature beat.</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020) Manuscript to be reviewed PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>The CMR findings in AM, CM and NC groupsValues are presented as mean &#177; SE. P1: values comparison between AM and NC; P2: values comparison between CM and NC; P3: values comparison between AM and CM; *P values adjusted for: None; &#8224; P values adjusted for: BSA and heart rate; &#8225; P values adjusted for: BSA, heart rate, hematocrit and sex . NC, normal control; AM, acute myocarditis; CM, subacute/chronic myocarditis; HLA, horizontal long axis; SA, short axis; ECV, extracellular volume; EDV, end-diastolic volume; ESV, end-systolic volume; LVM, LV mass; SV, stroke volume; LVEF, left ventricle ejection fraction.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Groups</ns0:cell><ns0:cell>NC(n=15)</ns0:cell><ns0:cell>AM (n=20)</ns0:cell><ns0:cell>CM (n=11)</ns0:cell><ns0:cell /><ns0:cell>P-values</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>Standardized cardiac morphology and function</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>EDV(mm)</ns0:cell><ns0:cell>76.8&#177;4.3</ns0:cell><ns0:cell>74.2&#177;3.4</ns0:cell><ns0:cell>78.3&#177;2.5</ns0:cell><ns0:cell /><ns0:cell>0.73</ns0:cell></ns0:row><ns0:row><ns0:cell>ESV(mm)</ns0:cell><ns0:cell>30.3&#177;2.3</ns0:cell><ns0:cell>30.1&#177;2.0</ns0:cell><ns0:cell>32.4&#177;1.7</ns0:cell><ns0:cell /><ns0:cell>0.75</ns0:cell></ns0:row><ns0:row><ns0:cell>LVM(g/mm 2 )</ns0:cell><ns0:cell>48.8&#177;2.5</ns0:cell><ns0:cell>47.8&#177;1.9</ns0:cell><ns0:cell>44.6&#177;2.7</ns0:cell><ns0:cell /><ns0:cell>0.48</ns0:cell></ns0:row><ns0:row><ns0:cell>SV (ml -1 )</ns0:cell><ns0:cell>46.6&#177;2.4</ns0:cell><ns0:cell>44.2&#177;1.6</ns0:cell><ns0:cell>45.9&#177;2.4</ns0:cell><ns0:cell /><ns0:cell>0.68</ns0:cell></ns0:row><ns0:row><ns0:cell>LVEF(%)</ns0:cell><ns0:cell>61.1&#177;1.3</ns0:cell><ns0:cell>60.1&#177;1.1</ns0:cell><ns0:cell>58.6&#177;2.0</ns0:cell><ns0:cell /><ns0:cell>0.51</ns0:cell></ns0:row><ns0:row><ns0:cell cols='3'>Myocardial tissue characterization</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>T2 (%)</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>6 (30.0%)</ns0:cell><ns0:cell>2 (18.2%)</ns0:cell><ns0:cell /><ns0:cell>0.31</ns0:cell></ns0:row><ns0:row><ns0:cell>LGE (%)</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>7 (35.0%)</ns0:cell><ns0:cell>4 (36.4%)</ns0:cell><ns0:cell /><ns0:cell>0.94</ns0:cell></ns0:row><ns0:row><ns0:cell cols='4'>T1 and T2 values of 'normal-appearing' myocardium</ns0:cell><ns0:cell>P 1</ns0:cell><ns0:cell>P 2</ns0:cell><ns0:cell>P 3</ns0:cell></ns0:row><ns0:row><ns0:cell>T2 SA , (ms)</ns0:cell><ns0:cell>37.2&#177;0.3</ns0:cell><ns0:cell>37.4&#177;0.5</ns0:cell><ns0:cell>37.1&#177;0.2</ns0:cell><ns0:cell cols='2'>0.54 &#8225; 0.65 &#8225; 0.09 &#8225;</ns0:cell></ns0:row><ns0:row><ns0:cell>T1 SA (ms)</ns0:cell><ns0:cell>1297.6&#177;8.0</ns0:cell><ns0:cell>1328.4&#177;8.0</ns0:cell><ns0:cell cols='3'>1320.8&#177;13.0 0.09 &#8225; 0.50 &#8225; 0.38 &#8225;</ns0:cell></ns0:row><ns0:row><ns0:cell>ECV SA (%)</ns0:cell><ns0:cell>27.0&#177;0.6</ns0:cell><ns0:cell>28.1&#177;0.5</ns0:cell><ns0:cell>30.1&#177;0.9</ns0:cell><ns0:cell cols='2'>0.20* 0.004* 0.57*</ns0:cell></ns0:row><ns0:row><ns0:cell>T2 HLA (ms)</ns0:cell><ns0:cell>37.1&#177;0.5</ns0:cell><ns0:cell>36.7&#177;0.4</ns0:cell><ns0:cell>37.2&#177;0.5</ns0:cell><ns0:cell cols='2'>0.08 &#8225; 0.90 &#8225; 0.60 &#8225;</ns0:cell></ns0:row><ns0:row><ns0:cell>T1 HLA (ms)</ns0:cell><ns0:cell>1323.3&#177;8.6</ns0:cell><ns0:cell>1336.0&#177;11.5</ns0:cell><ns0:cell>1305.1&#177;8.0</ns0:cell><ns0:cell cols='2'>0.56 &#8225; 0.44 &#8225; 0.05 &#8225;</ns0:cell></ns0:row><ns0:row><ns0:cell>ECV HLA (%)</ns0:cell><ns0:cell>28.6&#177;0.5</ns0:cell><ns0:cell>28.5&#177;0.7</ns0:cell><ns0:cell>29.8&#177;1.5</ns0:cell><ns0:cell cols='2'>0.90* 0.35* 0.58*</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)Manuscript to be reviewed</ns0:note></ns0:figure> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:06:50534:1:1:NEW 6 Sep 2020)</ns0:note> </ns0:body> "

"Dear editors and reviewers: Thank you for your letter and for the referees’ comments concerning our manuscript (Article ID: 50534 Identifying myocardial injuries of “normal-appearing” myocardium in pediatric patients with clinical suspected myocarditis using mapping techniques). Those comments are all very valuable and helpful for revising and improving our paper. We have tried our best to revise our manuscript according to the comments. And we hope that it will meet your request and get your approval. Revised portion are marked in the revised manuscript. I am looking forward to having the paper published in our respected journal of PeerJ. Please feel free to contact me if you have more questions and need any further information about our manuscript. Thank you very much! Best wishes! Yours sincerely, Cuiyan Wang Department of MR Imaging, Shandong Medical Imaging Research Institute, Shandong University, Jinan, China Email: [email protected] Reviewers' comments: Editor comments (Feng Liu) MAJOR REVISIONS The concerns that the reviewers raised should be carefully addressed. [# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #] Reply: We ensure that all review comments have been addressed in the rebuttal letter and any edits or clarifications have been inserted into the revised manuscript. [# PeerJ Staff Note: The review process has identified that the English language must be improved. PeerJ can provide language editing services - please contact us at [email protected] for pricing (be sure to provide your manuscript number and title) #] Reply: Our manuscript has been edited by American Journal Experts (AJE) and Ximing Wang. Reviewer 1 (Anonymous) Basic reporting This is an interesting study which focused on 'normal-appearing' myocardium in pediatric patients with clinical suspected myocarditis. The authors try to identify myocardial injuries of 'normal-appearing' myocardium using T1 mapping and T2mapping techniques. They compared the T2 values, native T1 values and ECV of 'normal-appearing' myocardium among acute myocarditis patients, subacute/chronic myocarditis patients and healthy children. The results showed that diffuse myocardial injuries are prone to occur in subacute/chronic myocarditis with prolonged inflammatory response. The study affirmed the value on the diagnosis and monitoring of myocarditis of mapping techniques. I have the following comments for the authors to embellish: 1. In the “Methodology” (line 36), “among” maybe better than “between”. “T2 values, native T1 values and extracellular volume (ECV) 36 of “normal-appearing” myocardium between three groups were compared. ” Reply: We have modified our text as advised. (see line 37, 214, 250) 2. In the “Discussion” (line 279), “characteristic” maybe appropriate than “characterization”. 'However, it is not very sensitive in very mild cases, which might perform diffuse myocardial tissue characterization changes.' Reply: We have modified our text as advised. (see line 290) 3. The sentence in line 297 maybe unnecessary. 'Diffuse myocardial injuries in DCM have been reported by mapping techniques.' Reply: We have deleted this sentence. Experimental design The study design is sound for purpose and the results are well presented. CMR imaging protocol: How many SA slices were performed during mapping sequences? And how to decide the position, for example “basal, mid and apical ventricular SA planes”. Reply: Three SA slices were performed during mapping sequences. We decided the position as reviewer mentioned: basal, mid and apical ventricular SA planes. We have modified our text as advised. (see line 147, 152) Validity of the findings Please provide the p values between AM and CM in table 2. Reply: We have added the p values between AM and CM in table 2. (see Table 2 revised) Comments for the Author No comment Reviewer 2 (Anonymous) Basic reporting This manuscript was well-written with clear and unambiguous professional English. Introduction part and references gave adequate background information, and demonstrated the novelty of this study. Tables and figures were well-prepared. Experimental design This manuscript addressed an interesting topic of diffused injury in “normal-appearing” myocardium of patients with myocarditis, demonstrating that subacute/chronic myocarditis patients may show higher ECV even in non-LGE non-edema myocardium, and higher ECV may be correlated to impaired LVEF. The authors employed T1/T2 mapping technique, and provided plenty of details of this study in Methods part. Line 165-166 states that “The papillary muscles and trabeculations were included as part of LV mass”, while reference 26 says “For calculation of global ventricular volumes, mass and function the papillary muscles were included in the ventricular cavity”. I think it might be a typo. Reply: In our study, the papillary muscles and trabeculations were included as part of ventricular cavity. It was a typo. We have modified our text in line 171. It would be better if the authors gave more information about the criteria of included region (normal-appearing myocardium)/excluded region (focal myocardial edema or necrosis/fibrosis). For example, (line 168-170,177-178) Were focal myocardial edema in T2WI and necrosis/fibrosis in LGE defined by visual assessment? Reply: In the study, focal myocardial edema in T2WI and necrosis/fibrosis in LGE were defined by visual assessment. After independent evaluation, two CMR radiologists discussed the findings together and reach a consensus. We have added this information in line 180-182. Validity of the findings The authors described results of their study comprehensively and provided robust raw dataset of studied CMR parameters, which supported the conclusion of this study. Comments for the Author no comment Reviewer 3 (Ning Mao) Basic reporting no comment Experimental design no comment Validity of the findings no comment Comments for the Author In this study, the authors analyzed diffuse myocardial injuries of “normal-appearing” myocardium in pediatric patients with clinical suspected myocarditis using T1 and T2 mapping techniques and evaluated the associations between diffuse myocardial injuries and cardiac function parameters. The authors found that the extracellular volume of “normal-appearing” myocardium significantly increased in subacute/chronic myocarditis compared with controls and it was associated with LVEF. The authors need to address the following: 1. There are too many language questions in this article. I suggest the manuscript be edited by a native speaker, or correct the grammar issues cautiously. Reply: Our manuscript has been edited by American Journal Experts (AJE) and Ximing Wang. 2. Abstract: Line 33: “Methodology” or “Methods” ? Reply: We have modified our text as advised. (see line 34) 3. Line 64-66: Diffuse, as opposed to focal, myocardial injuries in myocarditis may perform as “normal-appearing” myocardium without comparison of normal myocardium. This sentence is confusing. Reply: We have modified this sentence: Diffuse myocardial injuries in myocarditis may present as “normal-appearing” myocardium if it is not compared to normal myocardium. (see line 65-67) 4. Line 108: 15control Reply: We have modified our text as advised. (see line 112) 5. How were 15 control children included in this study? Please add the corresponding inclusion and exclusion criteria. Reply: Children with some mild nonspecific symptoms (such as fatigue, chest congestion) performed CMR examinations to rule out myocarditis. We included 15 control children with normal immunological features, electrocardiography (ECG) and CMR in our study as normal group (NC group). We have shown in our text in line 110-114. 6. The authors focused on the “normal-appearing” myocardium, which was defined as no focal myocardial edema or necrosis/fibrosis in the T2-weighted and LGE images in this study (line 176-178). Did it also assess normal myocardium? How to distinguish between normal myocardium and diffuse myocardial injuries, I think it should be explained in the Materials and methods. Reply: In the study, focal myocardial edema in T2WI and necrosis/fibrosis in LGE were defined by visual assessment. Then the other myocardium was defined as “normal-appearing” myocardium, which might include normal myocardium and abnormal myocardium with diffuse myocardial injuries. We attempted to determine whether T1 and T2 mapping techniques could identify diffuse myocardial injuries in pediatric myocarditis. Myocardium with higher T1 and T2 values and ECV was identified as abnormal myocardium with diffuse myocardial injuries. We have modified our text as advised. (see line 180-182; line 197-198) 7. Sample size was small and all the subjects were male (line 216-219), the results were limited and it might not be sufficient to support the conclusion. Reply: One of important limitations in our study was that the number of pediatric myocarditis patients included in the study was limited. Large sample analysis would be performed in the future. Gender composition was shown in line 226 and Table 1. Groups NC(n=15) AM (n=20) CM (n=11) P-values Sex (M, %) 9 (60.0%) 10 (50.0%) 9 (81.8%) 0.20 8. Line 275-277: LGE has become the “golden standard” to evaluate focal myocardial necrosis/fibrosis or other forms of irreversible injury infiltration in myocardial diseases. I think this sentence is not accurate. Pathological examination is usually the gold standard to evaluate the degree of myocardial necrosis and injury, but it is difficult to carry out in living people. Reply: We have modified this sentence as advised: LGE has been an established noninvasive tool to evaluate focal myocardial necrosis/fibrosis and has shown excellent correlation with pathology. (see line 287-289) 9. The duration of symptoms to CMR timing range is broad in CM group. Does this affect results? Reply: The duration of symptoms to CMR timing range varied from 3months to 3 years. No statistical differences between CMR timing range and T1, T2 values were found in CM groups. We have added this potential limitation in our text as advised (see line 369-370 Limitations) 10. Table 4 shows the associations between ECV and cardiac function in subacute/chronic myocarditis patients. Is there the data that shows the associations between ECV and cardiac function in all groups? Reply : The associations between ECV and cardiac function in all groups were shown in table below. NC AM CM EDV 0.0 (-0.1, 0.1) 0.805 0.0 (-0.1, 0.1) 0.735 -0.1 (-0.2, 0.1) 0.296 ESV 0.0 (-0.1, 0.2) 0.741 0.1 (-0.1, 0.2) 0.528 -0.1 (-0.4, 0.3) 0.782 LVM -0.0 (-0.1, 0.1) 0.509 -0.0 (-0.1, 0.0) 0.486 -0.1 (-0.3, 0.1) 0.396 SV 0.0 (-0.1, 0.1) 0.912 -0.0 (-0.2, 0.2) 0.942 -0.2 (-0.3, 0.0) 0.151 LVEF -0.0 (-0.3, 0.3) 0.889 -0.1 (-0.4, 0.2) 0.407 -0.4 (-0.7, -0.1) 0.029 "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>What is the intra and inter-rater reliability and concurrent validity of the weight-bearing lunge test within a Congenital Talipes Equinovarus population? Design: Test retest design for reliability and validity. The measure was taken, following preconditioning of the participants, using distance from wall, angle at distal posterior tibia using a digital inclinometer and the iPhone level function, twice by each rater. The raters included a clinician, clinician in training and a parent/carer.</ns0:p><ns0:p>Outcome measures: Weight bearing lunge test as a measure of ankle dorsiflexion.</ns0:p><ns0:p>Results: Twelve children aged 5-10 years were eligible to participate and consented, along with their parents. Intra-reliability of distance measures for all raters were good to excellent (ICC clinician 0.95, ICC training clinician 0.98 and ICC parent 0.89). Intra-rater reliability of the iPhone for all raters was good (ICCs &gt; 0.751) and good to excellent for the inclinometer (ICC clinician 0.87, ICC training clinician 0.90). Concurrent validity between the clinician's and parents distance measure was also high with ICC of 0.899. Inter-rater reliability was excellent for distance measure (ICC = 0.948), good for the inclinometer (ICC = 0.801) and moderate for the iPhone (ICC = 0.68). Standard error of measurement ranged from 0.70-2.05, whilst the minimal detectable change ranged from 1.90-5.70.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion:</ns0:head><ns0:p>The use of the WBLT within this CTEV population has demonstrated good to excellent reliability and validity amongst clinicians, clinicians in training and parents/carers, supporting its use as an assessment measure of dorsiflexion range of motion. There is support for parents/carers to use the WBLT at home as a monitoring assessment measure which may assist with early detection of a relapse.</ns0:p><ns0:p>Trial registration: University of South Australia's ethics committee (ID: 201397); Women's and Children's Hospital ethics committee (AU/1/4BD7310).</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>'The reliability and validity of the weight-bearing lunge test in a paediatric Congenital Talipes Equinovarus (CTEV) population' Background Congenital Talipes Equinovarus (CTEV), frequently known as clubfoot, is a congenital, idiopathic abnormality affecting the lower limb in newborns. <ns0:ref type='bibr' target='#b0'>1,</ns0:ref><ns0:ref type='bibr' target='#b1'>2</ns0:ref> Global prevalence of CTEV is approximated at 1.2 per 1000 livebirths, with a male to female predilection of approximately 2.4:1. <ns0:ref type='bibr' target='#b2'>3</ns0:ref> Within Australia, the Aboriginal and Torres Strait Islander population experiences a greater prevalence with 3.5 per 1000 livebirths compared to 1.1 per 1000 within a Caucasian population. <ns0:ref type='bibr' target='#b0'>1</ns0:ref> This condition causes the foot to be in an 'equinovarus' foot posture with adductus and cavus deformities also present. <ns0:ref type='bibr' target='#b3'>[4]</ns0:ref><ns0:ref type='bibr' target='#b4'>[5]</ns0:ref><ns0:ref type='bibr' target='#b5'>[6]</ns0:ref> Management of CTEV via the Ponseti method includes a serial casting process of approximately six-weeks, followed by a percutaneous elongation of tendo-achilles and finally a bracing period lasting until age four. <ns0:ref type='bibr' target='#b4'>5</ns0:ref> Unfortunately, the relapse rate remains a significant problem within this population with rates ranging from 5% to 68%, more frequently observed in those unable to comply with the bracing protocol. <ns0:ref type='bibr' target='#b4'>5,</ns0:ref><ns0:ref type='bibr' target='#b6'>7</ns0:ref> One study reported that at age two, the relapse rate was 30%. <ns0:ref type='bibr' target='#b7'>8</ns0:ref> By the time the child was four, this was then 45% and 52% by age six. <ns0:ref type='bibr' target='#b7'>8</ns0:ref> One of the primary signs of relapse is a reduction in ankle joint range of motion (ROM). <ns0:ref type='bibr' target='#b4'>5</ns0:ref> The weight-bearing lunge test (WBLT), is a commonly used measure of ankle ROM (Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). <ns0:ref type='bibr' target='#b8'>9</ns0:ref> This test has been determined as reliable within healthy adult and paediatric populations as well as some pathological groups including Charcot-Marie Tooth. <ns0:ref type='bibr' target='#b8'>[9]</ns0:ref><ns0:ref type='bibr' target='#b9'>[10]</ns0:ref><ns0:ref type='bibr' target='#b10'>[11]</ns0:ref> Monitoring of children with CTEV by health professionals decreases exponentially over time, therefore raising concern that the identification of changes in ankle joint ROM may be delayed. <ns0:ref type='bibr' target='#b4'>5</ns0:ref> Ideally, ankle joint ROM would be assessed regularly, more frequently than standard monitoring allows, to avoid delays in identifying those requiring further intervention. <ns0:ref type='bibr' target='#b7'>8</ns0:ref> It has been reported that the use of self-management in families enhances adherence to treatment plans and provides families with greater abilities to solve problems. <ns0:ref type='bibr' target='#b12'>12</ns0:ref> This raises the consideration that parent/carers may be useful in early identification of relapses.</ns0:p><ns0:p>The WBLT can be measured in a variety of different ways, all with reported reliability and/or validity. In healthy adults, this test originally was investigated for reliability using a toe to wall measure and an angular measurement along the anterior tibia. <ns0:ref type='bibr' target='#b8'>9</ns0:ref> Another study, investigating the use of the Tiltmeter App, used the angle at the posterior tibia, measuring when the knee was both extended and flexed. <ns0:ref type='bibr' target='#b13'>13</ns0:ref> This study determined good to excellent reliability and validity comparing a now outdated iPhone application (the Tiltometer) with a digital inclinometer in a healthy adult population. This outcome was recently repeated using the new level function of the measure application, available within the Apple suite (Apple Inc., Cupertino, CA, USA), also with reported good to excellent reliability within a healthy adult population. <ns0:ref type='bibr' target='#b14'>14</ns0:ref> With the increase in technological advances globally, the movement of using applications in clinical settings is becoming increasingly relevant. One study found that a majority of health care providers own a smartphone with over half of those regularly using them in practice. <ns0:ref type='bibr' target='#b15'>15</ns0:ref> As these tools are being used so often, it is prudent to establish their psychometric properties.</ns0:p><ns0:p>This study aims to determine the reliability and validity of two methods of measuring ankle joint ROM during the weight bearing lunge test (i.e. distance from wall and posterior angle of tibia) when conducted by a clinician, a clinician in training and a parent/caregiver. Methods This study followed a test-retest design to determine the intra and inter-rater reliabilities of the WBLT when measured by an experienced clinician, clinician in training, and the parent/carer of participants. Concurrent validity was established for the iPhone Measure app when compared to the digital inclinometer and between the experienced clinician and the parent or carer of participants. The two measures of the WBLT included distance from wall (mm) as well as posterior angle of tibia (degrees). The angle of the tibia was measured via two tools; the inclinometer within the iPhone Measure App and a digital inclinometer by the clinician and clinician in training. The parent/carer did not use the digital inclinometer due to consideration they would not have access to this tool at home. All raters were blinded to each other's measures.</ns0:p></ns0:div> <ns0:div><ns0:head>Raters</ns0:head><ns0:p>Three raters conducted each measurement. The clinician and clinician in training (AM and GG) were consistent for each participant, the third rater, a parent/carer, was unique to each participant. The clinician (AM) had thirty years clinical experience with specific involvement in paediatric orthopaedics for approximately seven years, where the WBLT is often used in practice. The clinician in training (GG) was a final year undergraduate student and had been trained in the procedure within the previous six months. The parent/carers were not familiar with the measure but were given explanations on how to perform the test and had the opportunity to observe the raters prior to each of their measures.</ns0:p><ns0:p>The clinician and clinician in training were involved in the development of the protocol. To allow for testing and revision of protocol, the study was piloted twice (at six months and one week) prior to commencing formal study on a child with typical development.</ns0:p></ns0:div> <ns0:div><ns0:head>Participants</ns0:head><ns0:p>A sample of convenience was recruited from the Women's and Children's Hospital (Adelaide, South Australia) Physiotherapy outpatient clinic. Potential participants were identified and informed of the study by the treating clinician via a phone call or conversation when they were present for an appointment. A participant information pack was supplied where interest was indicated. Written informed consent was obtained from the parent and verbal assent gained from the child prior to commencing the measures. Participants were informed of their right to withdraw from the study via written and verbal notification.</ns0:p><ns0:p>Inclusion criteria included children aged 4-18 years born with unilateral or bilateral idiopathic CTEV, managed via the Ponseti method. The children also were required to be able to perform a WBLT without pain and have a parent/carer able to be present and conduct measures. Exclusion criteria included current pain or lower limb injury, an inability to perform the WBLT or a parent unable to measure. Reasons for being unable to measure included inability to assume a measuring posture on the floor or other physical limitations, impaired cognitive ability or previous experience in the WBLT. A sample of n=13 was calculated to power the study in order to obtain 80% power, or 0.8, to detect an Intraclass Correlation Coefficient (ICC) of &#8805; 0.75 with a desired confidence interval width of 0.5 (0.5-1.0). <ns0:ref type='bibr' target='#b16'>16</ns0:ref> In the event of a child presenting with bilateral CTEV, both feet were used as separate participant data when two parents/carers were present, willing and able to measure, ensuring each parent/carer was a unique rater.</ns0:p><ns0:p>The protocol was approved by the University of South Australia Human Research Ethics Committee (approval 201397) and the Women's and Children's Hospital Research Ethics Committee (approval AU/1/4BD7310).</ns0:p></ns0:div> <ns0:div><ns0:head>Procedure</ns0:head><ns0:p>The tools used within the study included the Geo Fennel S-Digit Mini Inclinometer (digital inclinometer), (GSR Laser Tools, Perth, Australia) and the inclinometer function within the iPhone Measure application. This application is free and automatically installed on the iPhone smartphone (iOS 7 and above). Within this study, an iPhone 8 was used (Apple Inc., Cupertino, CA, USA). Prior to beginning the study, the digital inclinometer and iPhone Measure application were compared for consistency on identical, hard flat and angled surfaces across three trials.</ns0:p><ns0:p>During the study the digital inclinometer was calibrated in accordance to industry requirements (Laser-Liner, UK), whilst the iPhone was calibrated to zero degrees by placing it on the long axis on the floor.</ns0:p><ns0:p>For the participants convenience, testing was conducted in conjunction to scheduled appointments. Preconditioning required participants to perform a WBLT stance for 30 seconds, three times, to demonstrate understanding of the technique and reduce joint stiffness. A small mark was made on the back of the child's heel to indicate one centimeter superior to the posterior calcaneal tuberosity as this was the point of measurement. <ns0:ref type='bibr' target='#b13'>13</ns0:ref> The WBLT was performed using a modified version of methods described by previous studies and Figure <ns0:ref type='figure' target='#fig_1'>2</ns0:ref> shows the position in which the measure was taken. 9 </ns0:p></ns0:div> <ns0:div><ns0:head>FIGURE 2 APPROXIMATED HERE</ns0:head><ns0:p>Unilateral CTEV participants used their affected foot. Bilateral CTEV participants with only one rater available used the foot with the higher birth Pirani score or in the case of equal scores, the child's preferred foot.</ns0:p><ns0:p>The order in which the measurements were taken were pseudo-randomised via computer programming and sealed in an envelope and labelled to corresponding participant number. For the purpose of training, the parents/carers were always the third rater. The order of the clinician and clinician in training, along with the order of measures was randomised.</ns0:p><ns0:p>The distance measure was marked on a blank piece of paper secured to the floor alongside the affected foot. If the child was unable to touch the wall with their heel on the ground, the paper was placed between the wall and the most anterior point of the knee. This resulted in a negative value. The angle measurements of the posterior leg remained the same. The measure marked on the blank piece of paper was placed in a sealed envelope until the end of the study. All distance measures were measured at the same time point at the completion of the study.</ns0:p><ns0:p>To measure the angle, the short arm of the digital inclinometer was placed flat against the posterior heel along the marked position. This was held in position, with the screen facing away from the rater for blinding until the rater stated they were pleased with the position. An Manuscript to be reviewed independent research assistant noted the angle. The same protocol was performed with the iPhone.</ns0:p><ns0:p>Between each measure, the child was allowed to rest as needed to relieve any discomfort potentially caused by a sustained end range position and due to the child's attention span.</ns0:p></ns0:div> <ns0:div><ns0:head>Data Analysis</ns0:head><ns0:p>All data analysis was conducted using SPSS Statistics 21 software package was used (IBM Statistics, United States). Participants data were described in means (SD) and frequencies (%).</ns0:p><ns0:p>The intra-rater reliability for each tool was determined using the intraclass correlation coefficients (ICC) (Model 3,1) (two-way mixed with absolute agreement), the minimal detectable change and standard error of the mean (SEM). The interrater reliability was determined using ICCs (Model 3,1) (two-way mixed with absolute agreement), SEM and the minimal detectable change. In consideration that joint stiffness may be present and impact the first measure of testing session, an apriori decision was made that the second measure of each of the raters were to be used for each of the tools. The concurrent validity of the parent/carer population was explored using ICCs (Model 2,1) (Two-way random with absolute agreement).</ns0:p><ns0:p>The minimal detectable change is the minimal amount of change that is likely not to be due to error. The SEM was used to calculate the minimal detectable change using the equation 1.96 x SEM x &#8730;2. <ns0:ref type='bibr' target='#b14'>14</ns0:ref> A smaller minimal detectable change is ideal as it improves confidence in difference observed, however, it does not ensure clinical relevance. <ns0:ref type='bibr' target='#b17'>17</ns0:ref> Based on an expected minimum ICC of 0.75 and a desired confidence interval (CI) width of 0.5 (i.e., the 95% CI of 0.50 to 1.00) for the intra-rater reliability analysis, it was estimated that the minimum sample size should be 13 feet.</ns0:p><ns0:p>For the reliability or validity, an ICC value of &#61619; 0.75 with confidence interval of width 0.5 (range 0.5 -1.0) was ideal. Ranges were determined, as per Portney and Watkins <ns0:ref type='bibr' target='#b16'>16</ns0:ref> to report ICC data: &lt;0.5 = poor reliability, 0.5 to 0.75 = moderate reliability, 0.76 to 0.9 = good reliability, and &gt; 0.90 = excellent reliability. Manuscript to be reviewed All data was graphically represented on a Bland-Altmann plot. These plots provide a visual spread, illustrative of differences between methods against the mean and assists with the decision of whether the observed error is acceptable. <ns0:ref type='bibr' target='#b16'>16</ns0:ref> It was used to assess the degree of agreement between the two tools in all positions, by both raters, across the two timepoints.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Participant characteristics</ns0:head><ns0:p>Twelve participants and their parents/carers met eligibility criteria with both parent and child consenting to being involved in the study. Participants characteristics were recorded (Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>).</ns0:p><ns0:p>Additionally, the carer filled out a purpose-built questionnaire (Additional file 8) to determine the child's CTEV experience. Seven out of the twelve participants (58.3%) had bilateral CTEV.</ns0:p><ns0:p>A slight gender bias existed with 66.7% being males (8:4), in keeping with expected gender prevalence of CTEV.</ns0:p></ns0:div> <ns0:div><ns0:head>TABLE 1 HERE</ns0:head></ns0:div> <ns0:div><ns0:head>Study findings</ns0:head><ns0:p>Measures were taken on thirteen feet (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>). A negative recording on the knee to wall measure (i.e. unable to touch the wall) was recorded for five (42.7%) measures. Two hundred and eight measures were recorded during the study.</ns0:p><ns0:p>The concurrent validity between the iPhone and digital inclinometer on flat and angled surface (15 degrees) was determined prior to the study. The validity was excellent, indicated by an ICC of 0.99 (95% confidence interval -0.58 to 1.58).</ns0:p><ns0:p>The intra-rater reliability between measures for the distance measure was excellent (ICC = 0.96 -0.99), very good for the digital inclinometer (ICC = 0.85 -0.90) and good for the iPhone measure app (ICC = 0.75 -0.90) (Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>). Inter-rater reliability between the clinician and clinician in training was excellent using the distance measure (ICC = 0.95), good when using the inclinometer (ICC=0.80) and moderate for the iPhone measure application (ICC=0.68) (Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>). </ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The standard error of measurement (SEM) and minimal detectable change was determined for the intra-reliability of each of the measures (Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>). The minimal detectable change ranged from 1.90 -5.70 with the clinician in training's measures, using the digital inclinometer, having the lowest minimal detectable change.</ns0:p><ns0:p>Concurrent validity between the clinician and parent/carer was good (ICC = 0.90) for distance as displayed by the Bland-Altmann plot below. The iPhone tool provided moderate validity between the clinician and parent/carer (ICC = 0.62). </ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The Bland-Altmann plot (Figure <ns0:ref type='figure' target='#fig_5'>3</ns0:ref>) shows the agreement between the clinician and parents/carers distance. All data points, except for one outlier, were between the limits of agreement. This demonstrates the consistency and therefore concurrent validity of the measures. </ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>This study is the first to explore the reliability of the WBLT within a CTEV population. The WBLT is used by clinicians to assess ankle joint ROM and has been deemed reliable within pathological paediatric populations, such as Charcot-Marie Tooth 11 , calcaneal apophysitis <ns0:ref type='bibr' target='#b18'>18</ns0:ref> and idiopathic toe walking. <ns0:ref type='bibr' target='#b19'>19</ns0:ref> The current study followed the protocol of these previous studies, which is an adapted version of the original WBLT by Bennell and Talbot. <ns0:ref type='bibr' target='#b8'>9</ns0:ref> This study has determined that identifying a change in ankle joint ROM using distance of toes from wall, and inclinometer has good to excellent intra and inter-rater reliability and iPhone measure has good intra-reliability. The measures can be used with credence by parents/carers to identify change in ankle ROM, potentially indicating early CTEV relapse. As stated earlier, a reduction in ankle joint ROM is one of the primary signs of relapse and early detection of change leads to earlier intervention. <ns0:ref type='bibr' target='#b4'>5,</ns0:ref><ns0:ref type='bibr' target='#b7'>8</ns0:ref> The literature reports the relapse involved with CTEV continues to be high. Children with CTEV are reviewed by health professionals less frequently as they grow older; at a time when their risk for relapse continues. <ns0:ref type='bibr' target='#b4'>5</ns0:ref> Having parents/carers able to identify early changes in ankle joint ROM improves monitoring abilities, detecting joint changes and relapses sooner for better outcomes.</ns0:p><ns0:p>Our sample was a population presenting to a metropolitan hospital were but given the ease of this measure, it can be used anywhere. This is particularly significant in the Aboriginal and Torres Strait Islander community where there is a much higher prevalence of CTEV. Given 11.9% of Aboriginal and Torres Strait Islander people live in areas classified as very remote, and due to inherent difficulties in receiving adequate health-care in remote areas, a heavier reliance on selfmonitoring is required. <ns0:ref type='bibr' target='#b20'>20</ns0:ref> The use of simple tools like the distance or measure application can allow people to identify concerns with their own health and seek more timely and appropriate intervention.</ns0:p><ns0:p>The distance measure proved to be most reliable from the WBLT measure options reviewed, potentially due to ease of application. However, this study determined the WBLT within a CTEV population can be measured by a variety of people, in a variety of ways, with confidence. It is noted the low minimal detectable change results across all measures suggest a small change in measure cannot be attributed to an error in measurement and further boosts confidence that Manuscript to be reviewed measurers are observing true change. These results are in keeping with previous investigations of the reliability and validity WBLT in adult, paediatric and pathological populations. <ns0:ref type='bibr' target='#b14'>14</ns0:ref> These outcomes should be considered against a number of limitations. Firstly, due to the CTEV presentation, the children measured had feet with a soft heel and rounded lateral border (Figure <ns0:ref type='figure'>4</ns0:ref>). This potentially increased the difficulty of obtaining consistent measures.</ns0:p></ns0:div> <ns0:div><ns0:head>FIGURE 4 HERE</ns0:head><ns0:p>The inquisitive nature of the children along with the repetitive nature of three measuring tools, lead to frequent movement, with children attempting to change body position to gain a better view of what was occurring. This occasionally meant there was some movement of the foot, requiring realignment. It is also important to mention also that this study only measured ankle dorsiflexion. A relapse of CTEV could, potentially, occur in multiple planes due to the nature of the condition. It is important that this is deliberated when considered for application. This study only measured the reliability of an iPhone with regards to phone type. The results are therefore most relevant to Apple users. Although the distance measure can be used by all and is most reliable, there is potential to assess this measure using different technologies. Future studies are required for the long term follow up of the use of the WBLT by carers as a self-monitoring tool.</ns0:p><ns0:p>This should be followed in relation to reported relapse identification. Particularly in remote areas to determine the efficiency of the tool.</ns0:p><ns0:p>Converse to much of the literature the clinician in training and parent/carer were observed to have moderately smaller SEMs to the clinician. <ns0:ref type='bibr' target='#b22'>22</ns0:ref> This may reflect care and concentration of the novice users and suggests future studies should consider using more than one representative for each user group involved.</ns0:p><ns0:p>Future studies should involve the development and testing of a WBL protocol for use at home by parents/carers in relation to the sensitivity and specificity of the measure. This protocol could involve a prospective long-term investigation prior to determining if the WBLT measure alone is competent in detecting a CTEV relapse in the home setting.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>The WBLT within a paediatric CTEV population has good to excellent reliability when used by either a clinician, clinician in training or parent/carer, for distance from the wall, or the angle of the posterior lower leg when using an inclinometer or iPhone (intra-reliability only). Good concurrent validity is also demonstrated for the distance measure. The results of this study are encouraging as a tool for increasing self-monitoring of this condition and potential earlier detection of relapses. This will be particularly useful in remote areas with limited health-care services. Ankle dorsiflexion is, however, just one of the signs of relapse and it would be prudent for clinicians to consider other signs and symptoms prior to diagnosis. Future studies should aim to develop a protocol for this measure at home with parents and test the effectiveness of relapse prediction and associated outcomes. Manuscript to be reviewed Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure 1</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>FIGURE 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>FIGURE 1 APPROXIMATED HERE</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 describes the protocol of measures.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:45213:1:2:CHECK 19 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:45213:1:2:CHECK 19 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:45213:1:2:CHECK 19 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>FIGURE 3 HERE</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>FIGURE 3 HERE</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:45213:1:2:CHECK 19 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:01:45213:1:2:CHECK 19 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1 Position of weight bearing lunge test with iPhone positioning and screen positioning demonstrated (authors own image)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>TABLE 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>AND 3 HERE</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:01:45213:1:2:CHECK 19 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 :</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Participant data</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Characteristic</ns0:cell><ns0:cell>Mean (&#177; SD)</ns0:cell><ns0:cell>Range</ns0:cell></ns0:row><ns0:row><ns0:cell>Age (years)</ns0:cell><ns0:cell>7.00 (+/-1.80)</ns0:cell><ns0:cell>5-10</ns0:cell></ns0:row><ns0:row><ns0:cell>Weight (kg)</ns0:cell><ns0:cell>22.90 (+/-7.60)</ns0:cell><ns0:cell>15-39</ns0:cell></ns0:row><ns0:row><ns0:cell>Height (cm)</ns0:cell><ns0:cell>121.90 (+/-14.60)</ns0:cell><ns0:cell>102-148</ns0:cell></ns0:row><ns0:row><ns0:cell>Shin length (cm)</ns0:cell><ns0:cell>28.20 (+/-4.90)</ns0:cell><ns0:cell>21-35</ns0:cell></ns0:row><ns0:row><ns0:cell>Foot length (cm)</ns0:cell><ns0:cell>16.60 (+/-2.80)</ns0:cell><ns0:cell>14-22</ns0:cell></ns0:row><ns0:row><ns0:cell>Pirani score (from birth)</ns0:cell><ns0:cell>5.00 (+/-1.03)</ns0:cell><ns0:cell>3-6</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Table of raw measurements</ns0:figDesc><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>TABLE OF RAW RESULTS Distance score (mm) Angle at back of tibia (inclinometer) (degrees) Angle at back of tibia (iPhone compass app) (degrees)</ns0:head><ns0:label>OF</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Clinician in</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Clinician in</ns0:cell><ns0:cell /><ns0:cell>Clinician in</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Foot #</ns0:cell><ns0:cell>Clinician</ns0:cell><ns0:cell>training</ns0:cell><ns0:cell>Parent/Carer</ns0:cell><ns0:cell>Clinician</ns0:cell><ns0:cell>training</ns0:cell><ns0:cell>Clinician</ns0:cell><ns0:cell>training</ns0:cell><ns0:cell>Parent/Carer</ns0:cell></ns0:row><ns0:row><ns0:cell>1</ns0:cell><ns0:cell>-40</ns0:cell><ns0:cell>-71</ns0:cell><ns0:cell>-22</ns0:cell><ns0:cell>19.4</ns0:cell><ns0:cell>19.4</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell>-30</ns0:cell><ns0:cell>-29</ns0:cell><ns0:cell>-28</ns0:cell><ns0:cell>29.6</ns0:cell><ns0:cell>28.8</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>25</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>3</ns0:cell><ns0:cell>-10</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>26.2</ns0:cell><ns0:cell>22.8</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>21</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>4</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>27.5</ns0:cell><ns0:cell>27.5</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>28</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>5</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>21</ns0:cell><ns0:cell>23.9</ns0:cell><ns0:cell>20.7</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>6</ns0:cell><ns0:cell>-11</ns0:cell><ns0:cell>-18</ns0:cell><ns0:cell>-3</ns0:cell><ns0:cell>23.8</ns0:cell><ns0:cell>22.4</ns0:cell><ns0:cell>26</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>7</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>19.8</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell>25</ns0:cell><ns0:cell>25</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>8</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>0</ns0:cell><ns0:cell>15</ns0:cell><ns0:cell>26</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>9</ns0:cell><ns0:cell>-1</ns0:cell><ns0:cell>-16</ns0:cell><ns0:cell>-12</ns0:cell><ns0:cell>20.6</ns0:cell><ns0:cell>19.1</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>18</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>10</ns0:cell><ns0:cell>32</ns0:cell><ns0:cell>40</ns0:cell><ns0:cell>66</ns0:cell><ns0:cell>27.1</ns0:cell><ns0:cell>28.2</ns0:cell><ns0:cell>26</ns0:cell><ns0:cell>28</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>11</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>35</ns0:cell><ns0:cell>17.1</ns0:cell><ns0:cell>24.3</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>12</ns0:cell><ns0:cell>29</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>50</ns0:cell><ns0:cell>27.2</ns0:cell><ns0:cell>27.8</ns0:cell><ns0:cell>25</ns0:cell><ns0:cell>26</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>13</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>25.6</ns0:cell><ns0:cell>26</ns0:cell><ns0:cell>24</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Study results</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='2'>INTRA-RATER RELIABILITIES</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Rater</ns0:cell><ns0:cell>Mean (SD)</ns0:cell><ns0:cell>ICC</ns0:cell><ns0:cell>95% CI</ns0:cell><ns0:cell>SEM</ns0:cell><ns0:cell>MDC</ns0:cell></ns0:row><ns0:row><ns0:cell>Digital inclinometer</ns0:cell><ns0:cell>Clinician</ns0:cell><ns0:cell>-1.50 (+/-2.30)</ns0:cell><ns0:cell>0.87</ns0:cell><ns0:cell>0.52, 0.96</ns0:cell><ns0:cell>0.83</ns0:cell><ns0:cell>2.30</ns0:cell></ns0:row><ns0:row><ns0:cell>(degrees)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='2'>Clinician in training 0.90 (2.20)</ns0:cell><ns0:cell>0.90</ns0:cell><ns0:cell>0.68, 0.97</ns0:cell><ns0:cell>0.70</ns0:cell><ns0:cell>1.93</ns0:cell></ns0:row><ns0:row><ns0:cell>iPhone (degrees)</ns0:cell><ns0:cell>Clinician</ns0:cell><ns0:cell>-0.50 (4.10)</ns0:cell><ns0:cell>0.75</ns0:cell><ns0:cell>0.16, 0.92</ns0:cell><ns0:cell>2.05</ns0:cell><ns0:cell>5.68</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='2'>Clinician in training 0.30 (2.60)</ns0:cell><ns0:cell>0.90</ns0:cell><ns0:cell>0.68, 0.97</ns0:cell><ns0:cell>0.82</ns0:cell><ns0:cell>2.28</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>PC</ns0:cell><ns0:cell>-1.80 (2.40)</ns0:cell><ns0:cell>0.90</ns0:cell><ns0:cell>0.49, 0.97</ns0:cell><ns0:cell>0.76</ns0:cell><ns0:cell>2.10</ns0:cell></ns0:row><ns0:row><ns0:cell>Distance (mm)</ns0:cell><ns0:cell>Clinician</ns0:cell><ns0:cell>-2.20 (10.00)</ns0:cell><ns0:cell>0.96</ns0:cell><ns0:cell>0.86, 0.99</ns0:cell><ns0:cell>2.00</ns0:cell><ns0:cell>5.54</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='2'>Clinician in training -2.00 (7.10)</ns0:cell><ns0:cell>0.98</ns0:cell><ns0:cell>0.96, 0.99</ns0:cell><ns0:cell>1.00</ns0:cell><ns0:cell>2.78</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>PC</ns0:cell><ns0:cell>0.43 (7.80)</ns0:cell><ns0:cell>0.97</ns0:cell><ns0:cell>0.88, 0.99</ns0:cell><ns0:cell>1.35</ns0:cell><ns0:cell>3.74</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>INTER-RATER RELIABILITIES</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Raters</ns0:cell><ns0:cell>Mean (SD)</ns0:cell><ns0:cell>ICC</ns0:cell><ns0:cell>95% CI</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Digital inclinometer</ns0:cell><ns0:cell>Clinician/clinician</ns0:cell><ns0:cell>-0.01 (2.90)</ns0:cell><ns0:cell>0.80</ns0:cell><ns0:cell>0.32 -0 .94</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>(degrees) iPhone (degrees)</ns0:cell><ns0:cell>in training Clinician/clinician</ns0:cell><ns0:cell>-0.90 (4.60)</ns0:cell><ns0:cell>0.68</ns0:cell><ns0:cell>0.06 -0.90</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Distance (mm)</ns0:cell><ns0:cell>in training Clinician/clinician</ns0:cell><ns0:cell>3.60 (11.10)</ns0:cell><ns0:cell>0.95</ns0:cell><ns0:cell>0.84 -0.98</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>in training</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>CRITERION VALIDITY</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Raters</ns0:cell><ns0:cell>Mean (SD)</ns0:cell><ns0:cell>ICC</ns0:cell><ns0:cell>95% CI</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>iPhone (degrees)</ns0:cell><ns0:cell>Clinician/PC</ns0:cell><ns0:cell>-2.3 (4.90)</ns0:cell><ns0:cell>0.62</ns0:cell><ns0:cell>-0.11, 0.88</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Distance (mm)</ns0:cell><ns0:cell>Clinician/PC</ns0:cell><ns0:cell>-8.8 (12.80)</ns0:cell><ns0:cell>0.89</ns0:cell><ns0:cell>0.58, 0.97</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>Abbreviations: SDstandard deviation; ICCintraclass correlation coefficient; CIconfidence interval; SEMstandard error of measurement; MDCminimal detectable change; PCparent/carer PeerJ reviewing PDF | (2020:01:45213:1:2:CHECK 19 Sep 2020)</ns0:note></ns0:figure> </ns0:body> "

"Response to comments The authors would like to thank the reviewers for the time taken to review the paper and for their comments. REVIEWER 1: Comment 1: Line 100 – the authors refer to a ‘six-week casting process. Consider adding – ‘approximately’ as some take longer. Response: approximately has been added to this sentence. Comment 2: Line 103 – states ‘in those who do not comply’. Consider reframing to ‘unable to comply’. There is some anectodal thought in this space that compliance may be related to an uncompliant foot rather than an incompliant patient/ family. Response: Thank for this comment, it is an interesting thought. It has been changed to unable to comply. Comment 3: Line 107 – states that ‘The primary sign of relapse is a reduction in ankle range of motion’. As this is a deformity which occurs in multiple planes, relapse can also occur in multiple planes. Consider revising to ‘One of the primary signs of relapse is a reduction in ankle range of motion’. Response: This has been revised as suggested. Comment 4: Line 142 – consider changing WBL to WBLT for consistency or define WBL in addition to WBLT. Response: This has been changed to WBLT throughout Comment 5: Line 119 – This is a good paragraph which highlights the need for regular monitoring. Consider adding a sentence around early identification of relapse to minimise the intervention required. This could link nicely to the final sentence around ‘useful in early identification of relapses.’ Response: Thank you for this comment. The reference used highlighted the importance of avoiding delays for improved outcomes, however we have reviewed some of the literature and have been unable to find a source which speaks to decreasing the amount of intervention required. This evidence seems to be anecdotal reports. If the reviewer has a source we would be most grateful to read and include. Comment 6: Methods – consider stating if participants were blinded to each other’s measures. Response: This has been added at line 149. Comment 7: Line 172 – Inclusion criteria – Please state if idiopathic cases were only included, or if atypical, those associated with syndromes included. Response: All cases were idiopathic presentations in keeping with the inclusion criteria stated in line 175: “Inclusion criteria included children aged 4-18 years born with unilateral or bilateral idiopathic CTEV” Comment 8: Table 2 presents reliability and validity data. I am wondering if the Mean (SD) column could please be revised for greater clarity. I am unable to ascertain what this data specifically represents. Response: This table has now been labelled as Table 3 to accommodate for the new results table. The mean data is the average and standard deviation of the measures detailed. The units have been added to the rows, however could the reviewer please specify what they would like clarified? Comment 9: I would be interested to know what ranges / averages / median (appropriate measure) were found in this cohort? My query relates to whether, if there was wide variability in the ranges we could be more confident that these tools could measure a wide range of DF scores reliably. If, however, the range of DF was small, we could only be confident in the reliability within that range. It may be possible that the data provided covers this, apologies if this was the data in Table 2 which I misinterpreted. Response: Thank you for this suggestion. An extra table, Table 3, has been added with the raw data from the measures. REVIEWER 2: Comment 1: Line 69 - What was the intra-rater reliability of the inclinometer? Should this be present too? Response: This has been added to the abstract at line 69. Comment 2: Line 73 - Similarly, what was the inter-rater reliability of the iphone measure? Should this not be present here? Response: This has been added to the abstract at line 73. Thank you for these comments on the abstract. Comment 3: A key here is whether detecting a reducing ROM early can make a significant difference to the care issued and the outcomes. It seems to make logical sense but it may be correlation as opposed to causation. This may be something for the discussion or even beyond such a reliability/validity paper. Response: Thank you for this comment. It has not been sourced within the literature at this stage but would be interesting to see. This would be part of a long-term follow up plan, using the methods detailed in this paper. It is good to know this measure is reliable but as the reviewer has stated, the key is determining whether this can have a significant impact on care outcomes. Comment 4: What about android users? It may be worth highlighting the fact that similar tech is available on that system too. There are studies that look at the Shoulder and knee that use android systems. Response: Thank you for the suggestion. We purposely did not discuss Android alternatives here as our study was limited to investigating the Apple app only. We discuss the limitation of only using an iPhone in (Line 379, page 14), which we feel may be less confusing for readers. Comment 5: Line 134 - Typo/simple error? Response: The authors have reviewed the spelling of “psychometric properties” and were unable to identify any typographical errors. If the reviewer could please specify their concerns we would be grateful. Comment 6: Please see O'Shea & Grafton 2013 for an example of testing considerations such as hand on wall or not, fix the heel or not, set foot alignment, blind from the distance measures as able and total reps/rest between to consider. Its also worth noting that this measure was superior to Bennell’s but admittedly needs a small clinic table and as such means it is not reproducible at home. Response: Line 194 - The O’Shea and Grafton is an excellent resource with useful considerations for future practice. Our protocol followed the Bennell article (predominately) as it has been used successfully in the authors previous work (Banwell 2019) and can be easily adopted for home use by our parent population. Comment 7: Can this be supported by literature regarding response to stretches and the impact on reliability or not? In a busy clinic the test would ordinarily just be done once so taking the 2nd measure poses a challenge here and needs further justification. Response: Line 261 – thank you for highlighting this concern. Given an aim of the study was to establish the reliability of the measure between people taken at the same session, the discarding of the first measure was considered prudent to remove any initial joint stiffness that would impact on consistency of further measures. We agree that in clinical practice the ‘first measure’ is the most likely to be used, however, this would also be the measure that is used consistently at each consult, negating the concern that it would skew clinical outcomes recorded. The following has been added at line 265, page 9 - In consideration that joint stiffness may be present and impact the first measure of testing session, an apriori decision was made that the second measure of each of the raters were to be used for each of the tools. Comment 8: A smaller MDC means the ability to detect change is better but the clinical relevance is not proven. You may be able to demonstrate very precisely that there is a difference in ROM at 2 time points. The clinical relevance though is more complex than just accuracy. How does ROM translate to pain, function, satisfaction etc. Smaller MDC enables us to show changes are not attributable to measurement error and enables more detection of differences with greater confidence. May just need re-wording here to be crystal clear. Response: Line 269 – We have altered the explanation of the smaller minimal detectable change to not be as definitive (Line 269, page 9) – “A smaller minimal detectable change is ideal as it improves confidence in difference observed, however, it does not ensure clinical relevance.” Comment 9: You seem to be referencing your stats to this one textbook from 1993. There are a range of relevant statistical papers that apply to reliability measurement, ICC, Bland and Altman plots etc that could be utilised to increase the strength of this section. Response: This has since been revised to the 3rd edition of the textbook published in 2015. Thank you for commenting on this. Comment 10: It may be worth considering placing SEM and MDC figures in the abstract too as clinicians should be very interested in these figures. Response: These figures are included in “Table 3 – Study Results”. If the reviewer thinks they may be clearer as a separate abstract the authors will take on this advice. Comment 11: This seems a rather wide range and could benefit from further analysis/discussion later in the article. I note that AM seemed to have a much higher SEM and MDC compared to the student and parent/carers which may be worth discussion. It also highlights the point about whether in hindsight another additional experienced clinician would have been of use too. Response: A sentence has been added to the discussion at line 386, page 14 - ‘Converse to much of the literature the clinician in training and parent/carer were observed to have moderately smaller SEMs to the clinician.22 This may reflect care and concentration of the novice users, and suggests future studies should consider using more than one representative for each user group involved.” Comment 12: Should this read: “Bennell and Talbot” Response: Thank you for identifying this error. This has been rectified at line 335, page 13) Comment 13: Consider re-wording. Did you canvass opinion from the carers and parents about their confidence using it? They may be reliable but under-confident, put upon, nervous to make an error etc. Response: Thank you for making this comment. At line 338 this has been changed to “with credence” as we are suggesting that parents can use it with the confidence that this measure is in fact reliable with their use. Comment 14: Can you bolster this claim further with evidence if possible. Can you bring literature showing decline in ROM then early intervention has led to better long term outcomes. I'm unable to offer this for you with regards this pathology but an example from a different cohort includes spinal surgery for severe scoliosis: change to ROM and position + the speed of change & the impact on the long term outcomes with regards pain/function/position. Response: Thank you for this comment. The reference used highlighted the importance of avoiding delays for improved outcomes, however we have reviewed some of the literature and have been unable to find a source which speaks to decreasing the amount of intervention required. This evidence seems to be anecdotal reports. If the reviewer has a source we would be most grateful to read and include. Line 340 (page 13) has been added to re-iterate the importance of ROM as far as we are aware. Comment 15: Line 352 - Did you manage to record what community your sample was taken from/the parents and carers community background? For all the reader knows, you could have recruited middle class white patients that were tech enabled, health literate individuals which makes the claim that Aboriginal and Torres Strait Islander communities will use these methods weaker. Response: The following statement has been added to the discussion - “Our sample was a population presenting to a metropolitan hospital were but given the ease of this measure, it can be used anywhere” (Line 350, page 13). The authors have discussed this and the measurement of distance with a tape measure requires a relatively low level of tech literacy. Additionally, currently in Australia, the majority of children with CTEV are treated in the major public hospitals. A random population at such a hospital could potentially be seen to be a cross section that is representative of those treated around Australia. Although there was no official recording of geographical location or ethnicity, there was a range of metropolitan and rural clients of various backgrounds noted. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>To improve the performance of NPC screening, we used a combination based on the IgA antibody against the Epstein-Barr virus (EBV) capsid antigen (VCA-IgA) and the IgA antibody against Epstein-Barr virus nuclear antigen 1 (EBNA1-IgA) to NPC screening by enzyme-linked immunosorbent assay (ELISA). A multiplication model was applied to measure the level of the combination. We evaluated the NPC screening effect of the markers. A case-control study was performed to assess the NPC screening effect of the markers. A total of 10,894 serum specimens were collected, including 554 samples from NPC patients and 10,340 samples from healthy controls. In the training stage, 640 subjects were randomly selected, including 320 NPC cases and 320 healthy controls. In the verification stage, 10,254 subjects were used to verify the NPC screening effect of the combination. Receiver operating characteristic (ROC) analysis was performed. A combination of two ELISA tests based on VCA-IgA and EBNA1-IgA was successfully developed to improve the effect of NPC screening by using a multiplication model. In the verification stage, the combination achieved an overall sensitivity of 91.45%, a sensitivity for early-stage NPC detection of 93.94%, a specificity of 93.45%, and an AUC of 0.978 (95% CI: 0.968, 0.987). We successfully applied a combination of two ELISA tests based on VCA-IgA and EBNA1-IgA for NPC screening by using a multiplication model. Compared with</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>In southern China and southeast Asia, nasopharyngeal carcinoma (NPC) is a common malignant tumour, with an incidence rate of 10-40/100,000 per year <ns0:ref type='bibr' target='#b27'>(Ng et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b32'>Torre et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b35'>Wei &amp; Sham 2005;</ns0:ref><ns0:ref type='bibr' target='#b36'>Yang et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b38'>Yu &amp; Yuan 2002)</ns0:ref>. Jiangmen city, an endemic area of NPC located along the Zhujiang River in the central southern area of Guangdong province, has a high-risk NPC population.</ns0:p><ns0:p>The NPC incidence rate in the Jiangmen urban area is 14.99/10 5 <ns0:ref type='bibr' target='#b33'>(Wei et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The population-based cancer registry was established in Jiangmen to report the incidence and mortality of cancers. Population-based NPC screening was performed in the Jiangmen urban area by Jiangmen Central Hospital from June 2018 to March 2020.</ns0:p><ns0:p>The occurrence of NPC is strongly associated with Epstein-Barr virus (EBV) infection <ns0:ref type='bibr' target='#b10'>(Fachiroh et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b13'>Gulley, 2001;</ns0:ref><ns0:ref type='bibr' target='#b15'>Henle &amp; Henle, 1976;</ns0:ref><ns0:ref type='bibr'>Sam, Abu-Samah &amp; Prasad,1994)</ns0:ref>. Furthermore, host genetics, smoking, the consumption of salted fish and occupational exposures are contributors to the pathogenesis of NPC <ns0:ref type='bibr' target='#b3'>(Chang &amp; Adami, 2006;</ns0:ref><ns0:ref type='bibr' target='#b4'>Chang et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b5'>Chen et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b37'>Yong et al., 2017)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The development mechanisms of NPC are unclear. Mass screening is the main effective measure to detect NPC early in endemic areas.</ns0:p><ns0:p>EBV antibodies are widely used as markers in NPC screening <ns0:ref type='bibr' target='#b6'>(Chien et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b18'>Ji et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b19'>Ji et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b27'>Ng et al., 2005;</ns0:ref><ns0:ref type='bibr'>Tan et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b40'>Zeng et al., 1982)</ns0:ref>. A number of studies have shown that screening for NPC by using EBV antibodies is an effective measure to improve the survival rate of NPC patients <ns0:ref type='bibr' target='#b7'>(Choi et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b19'>Ji et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b20'>Jia et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b26'>Ng et al., 2010)</ns0:ref>. The combined serological test based on the IgA antibody against the EBV capsid antigen (VCA-IgA) and the IgA antibody against EBV nuclear antigen 1 (EBNA1-IgA) by enzyme-linked immunosorbent assay (ELISA) was used for NPC screening in endemic areas in China <ns0:ref type='bibr' target='#b11'>(Gao et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b22'>Liu et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b39'>Yu et al., 2018)</ns0:ref>. In previous studies, the probability (PROB) calculated by logistic regression based on VCA-IgA and EBNA1-IgA was applied to NPC screening in China <ns0:ref type='bibr' target='#b11'>(Gao et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b22'>Liu et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b39'>Yu et al., 2018)</ns0:ref>.</ns0:p><ns0:p>Multiplication model was applied to make new maker to improve diagnostic effect <ns0:ref type='bibr'>(Attila et al., 2020)</ns0:ref>. In this study, a combination of two ELISA tests based on VCA-IgA and EBNA1-IgA was applied to improve the effect of NPC screening by using a multiplication model and the NPC screening effect of the markers was evaluated.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Study population</ns0:head><ns0:p>A case-control study was performed to compare the effect of the NPC screening of markers, including 554 NPC cases and 10340 healthy controls. This study included the training stage and the verification stage. The inclusion criteria for NPC cases included being histologically confirmed by biopsy, aged between 30 and 69 years, and residing in Jiangmen. A total of 554 serum specimens were continuously collected from NPC patients at Jiangmen Central Hospital from June 2018 to March 2020. Among the 554 cases, 7 (1.26%) participated in the NPC screening program. NPC stages were classified according to the 2008 staging system of China <ns0:ref type='bibr' target='#b21'>(Lin ZX et al., 2009)</ns0:ref> The information on age, sex, smoking history and family history of NPC for the cases and healthy controls were collected by inquiring medical records and using a questionnaire survey.</ns0:p></ns0:div> <ns0:div><ns0:head>Serological test</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>In total, 10894 serum samples were collected and underwent serological tests in separate batches at Jiangmen Central Hospital. The samples were separated and stored at -40&#176;C. In this study, the NPC screening markers included VCA/IgA, EBNA1/IgA and combination. The antibodies VCA/IgA (Euroimmun, Lubeck, Germany) and EBNA1/IgA (Zhongshan Bio-tech, Zhongshan, China) were tested by ELISA on a TECAN Freedom EVOlyzer 200/8 platform according to the manufacturer's specifications. EBNA1s in Zhongshan Bio-tech kit were produced with purified recombinant peptide specified by EBV BKRF1 (72 kD) <ns0:ref type='bibr' target='#b14'>(He et al. 2018)</ns0:ref>. The EBV VCAs in Euroimmun kit were obtained from the pyrolysis products of human B lymphocytes (P3HR1cell line) infected by EBV <ns0:ref type='bibr' target='#b11'>(Gao et al., 2017)</ns0:ref>. The levels of the antibodies were assessed by the relative optical density (rOD) calculated according to the manufacturers' instructions by dividing the optical density (OD) value by a reference control <ns0:ref type='bibr' target='#b16'>(Ji et al., 2014)</ns0:ref>. In this study, the multiplication model based on VCA-IgA and EBNA1-IgA was calculated by using the following formula:</ns0:p><ns0:p>. The formula for </ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analysis</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed The base information of different populations was described and compared by the </ns0:p><ns0:formula xml:id='formula_0'>&#967;</ns0:formula></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Baseline information</ns0:head><ns0:p>The characteristics of the 554 cases and 10340 healthy controls are shown in Table Manuscript to be reviewed &#177; 11.60 years. Among the 10340 healthy controls, 1670 (16.15%) had a smoking history, and 198 (1.91%) had a family history of NPC (Table <ns0:ref type='table' target='#tab_3'>1</ns0:ref>).</ns0:p><ns0:p>The differences in age, sex, smoking history and NPC family history were significant between NPC cases and healthy controls (Table <ns0:ref type='table' target='#tab_3'>1</ns0:ref>). There were no statistically significant differences in age, sex, smoking history and NPC family history between the early-stage and advanced-stage cases (Table <ns0:ref type='table' target='#tab_3'>1</ns0:ref>).</ns0:p><ns0:p>The characteristics of the 320 cases and 320 healthy controls in the training stage are shown in Table <ns0:ref type='table' target='#tab_4'>2</ns0:ref>. In this stage, the controls and NPC cases were matched by sex and age to prevent bias. Differences in age, smoking history and sex were not statistically significant, while differences in NPC family history were significant between the cases and controls. There were no statistically significant differences in sex, age, smoking history, or NPC family history between the earlystage and advanced-stage cases (Table <ns0:ref type='table' target='#tab_4'>2</ns0:ref>).</ns0:p><ns0:p>In the verification stage, a total of 10254 subjects were enrolled, including 234 NPC cases and 10020 healthy controls. Of the 10254 subjects, 3897 (38.00%) were men, and the mean age was 48.57 &#177; 11.61 years. Among the 10254 subjects, 1664 (16.23%) had a smoking history, and 215 (2.10%) had a family history of NPC.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparison of levels of markers in NPC patients and healthy controls</ns0:head><ns0:p>The rODs of VCA/IgA and EBNA1/IgA, PROB value and combination value in NPC patients and healthy controls were showed in Figure <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>. The t tests showed that the means of markers in NPC patients were all significantly higher than those in healthy controls (p&lt;0.001). </ns0:p></ns0:div> <ns0:div><ns0:head>Diagnostic value of the markers</ns0:head><ns0:p>The diagnostic performance of the markers is shown in Compared to the AUCs of VCA-IgA (p&lt;0.001) ,EBNA1-IgA (p&lt;0.001), and PROB (p&lt;0.01), the combination yielded a higher AUC (Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref> and Figure <ns0:ref type='figure'>3</ns0:ref>).</ns0:p><ns0:p>The differences in the sensitivities of the markers between early-stage and advanced-stage NPC patients were not significant (p&gt;0.05, Table <ns0:ref type='table' target='#tab_6'>4</ns0:ref>). Compared with each marker alone by McNemar test, the combination had a higher sensitivity for early-stage NPC patients (Table <ns0:ref type='table' target='#tab_6'>4</ns0:ref>). The differences in sensitivities of EBNA1- Manuscript to be reviewed</ns0:p><ns0:p>IgA, PROB and the combination between man and female NPC patients were not significant (p&gt;0.05), while the sensitivity of VCA-IgA in man NPC patients was higher than in female NPC patients (p&lt;0.05, Table <ns0:ref type='table' target='#tab_7'>5</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Verifying the effect of the combination on NPC screening</ns0:head><ns0:p>A total of 10253 subjects were enrolled to verify the NPC screening effect, including 234 NPC cases and 10020 healthy controls sourced from the screening field. In this stage, the combination achieved an overall sensitivity of 91.45%</ns0:p><ns0:p>(214/234), a sensitivity for early-stage NPC detection of 93.94% (31/33), a specificity of 93.45% (9364/10020), and an AUC of 0.978 (95% CI: 0.968, 0.987).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>NPC is a main health problem that leads to a high health burden in southern China, especially in Guangdong province <ns0:ref type='bibr' target='#b2'>(Cao et al., 2011)</ns0:ref>. EBV antibodies are widely applied in NPC screening. PROB calculated by logistic model were applied in NPC screening based on VCA-IgA and EBNA1-IgA <ns0:ref type='bibr' target='#b11'>(Gao et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b24'>Liu et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b39'>Yu et al., 2018)</ns0:ref>. In this study, a combination calculated by multiplication Manuscript to be reviewed 0.968, 0.987). We found that the combination calculated by using a multiplication model can be a applied to NPC screening.</ns0:p><ns0:p>In the present study, we found that the combination as a marker for NPC screening achieved the highest diagnostic effect among the combination, PROB, VCA-IgA and EBNA1-IgA markers. In the training stage, compared with PROB, VCA-IgA and EBNA1-IgA individually, the combination yielded a higher AUC for NPC screening. These findings suggested that the combination had a better performance than the individual PROB, VCA-IgA and EBNA1-IgA markers.</ns0:p><ns0:p>In this study, a large number of healthy controls and 554 NPC patients were collected from the endemic areas, which is favourable for evaluating the performance of the markers for NPC screening. In the verification stage, 10254 subjects were enrolled to verify the NPC screening effect. The combination achieved a sensitivity of 91.45%, a specificity of 93.45% and an AUC of 0.978 (95% CI: 0.968, 0.987). These results demonstrated that the combination calculated by using a multiplication model was effective for NPC screening.</ns0:p><ns0:p>In this study, the levels of markers (PROB, VCA-IgA, EBNA1-IgA and combination) in NPC patients were higher than in healthy controls. It was consistent with the results of previous reports <ns0:ref type='bibr' target='#b22'>(Liu et al., 2012)</ns0:ref>. We found the sensitivity of combination was high (93.94%) in verifying stage, although the differences in the sensitivities of the markers between early-stage and advancedstage NPC were not significant. We found the difference in sensitivities of the combination between man and female NPC patients was not significant.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The present study had some limitations. First, there was some bias in identifying the 10340 subjects as healthy controls because not all healthy controls underwent an examination by fibreoptic endoscopic examination. Second, since the study population was obtained from provinces with a high risk of NPC, the results may be limited for application in other populations.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>We successfully developed a combination of two ELISA tests based on VCA-IgA and EBNA1-IgA to improve the effect of NPC screening by using a multiplication model. Compared with VCA-IgA and EBNA1-IgA individually, the combination had an improved diagnostic accuracy. The results suggested that the combination was effective and can be a option for NPC screening. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 2</ns0:note><ns0:p>Comparison of levels of markers in early-stage and advanced-stage NPC patients by t tests.</ns0:p><ns0:p>The dotted lines represent cut-off values of the markers.</ns0:p><ns0:note type='other'>Figure 3</ns0:note><ns0:p>ROC curves for combination, PROB, VCA-IgA and EBNA1-IgA.</ns0:p><ns0:p>The axes are expressed as percentages.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>. The stages were divided into early-stage (stage I and stage II) and advanced-stage (stage III and stage IV) disease. A total of 554 cases comprised 73 early-stage cases and 481 advanced-stage cases. A total of 320 NPC training samples were randomly selected from the 554 NPC cases, and the remaining 234 of 554 NPC cases were used as validation samples. A total of 10,340 healthy controls were obtained from an NPC screening programme performed in a population aged 30-69 years in the Jiangmen City urban area from June 2018 to March 2020. The healthy controls resided in Jiangmen of Guangdong province. A total of 320 training samples were randomly selected from the 10340 healthy controls and were frequency matched to the 320 training NPC cases by age (5-year age groups) and sex. The remaining 10020 of 10340 healthy controls were used as the validation samples.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>2018). In the formulas, VCA-IgA and EBNA1-IgA represent the rOD values for VCA-IgA and EBNA1-IgA, respectively, which were tested by ELISA.The written informed consent was obtained from healthy controls. The serum samples of NPC patients were collected after clinical use which were exempted from informed consent. This study was approved by the Clinical Research Ethics Committee of the Jiangmen Central Hospital (2019-28).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Categorical variables are described as numbers and percentages. Continuous variables are shown as the means and standard deviations (SDs). The levels of VCA/IgA, EBNA1/IgA, PROB and combination were compared by t tests in different population. Receiver operating characteristic (ROC) curve analysis was performed. The cut-off value of each marker was defined with the largest Youden Index selected from each ROC curve. The effects of the screening markers were measured using the sensitivity, specificity and area under the ROC curve (AUC).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020) Manuscript to be reviewed Comparison of levels of markers in early-stage and advanced-stage NPC patients Of the 554 NPC patients, 73 (13.18%) were early-stage. The levels of VCA/IgA EBNA1/IgA, PROB and combination in early-stage and advanced-stage NPC patients were showed in Figure 2. The differences in VCA/IgA, EBNA1/IgA, PROB and combination were not significant between early-stage and advancedstage NPC patients by t tests (p&gt;0.05).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>model based on VCA-IgA and EBNA1-IgA was applied to NPC screening. The NPC screening effect of combination was evaluated and compared with the individual screening markers, PROB, VCA-IgA and EBNA1-IgA. Compared with PROB, VCA-IgA and EBNA1-IgA, the combination had the best performance, with an AUC of 0.978 (95% CI: 0.969, 0.986). In the verification stage, the combination yielded an overall sensitivity of 91.45%, a sensitivity for early-stage NPC detection of 93.94%, a specificity of 93.45% , and an AUC of 0.978 (95% CI: PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>. The combination</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Characteristics of the total population Differences in sex, age, smoking history and NPC family history between early-stage and advanced-stage NPC cases were compared by the &#967; 2 test.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell cols='3'>NPC cases (N=554), n (%)</ns0:cell><ns0:cell /><ns0:cell cols='2'>Controls (N=10340)</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Early-stage</ns0:cell><ns0:cell cols='2'>Advanced-stage</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Categories</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>NPC cases</ns0:cell><ns0:cell>NPC</ns0:cell><ns0:cell>cases</ns0:cell><ns0:cell>Total</ns0:cell><ns0:cell>P *</ns0:cell><ns0:cell>n (%)</ns0:cell><ns0:cell>P &#8224;</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>(n=73)</ns0:cell><ns0:cell>(n=481)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Sex</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.356</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Male</ns0:cell><ns0:cell>49(67.12)</ns0:cell><ns0:cell>348(72.35)</ns0:cell><ns0:cell /><ns0:cell>397(71.66)</ns0:cell><ns0:cell /><ns0:cell>3959(38.29)</ns0:cell></ns0:row><ns0:row><ns0:cell>Female</ns0:cell><ns0:cell>24(32.88)</ns0:cell><ns0:cell>133(27.65)</ns0:cell><ns0:cell /><ns0:cell>157(28.34)</ns0:cell><ns0:cell /><ns0:cell>6381(61.71)</ns0:cell></ns0:row><ns0:row><ns0:cell>Age (years)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.546</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>30~7(9.60)</ns0:cell><ns0:cell>26(5.41)</ns0:cell><ns0:cell /><ns0:cell>33(5.96)</ns0:cell><ns0:cell /><ns0:cell>1405(13.59)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>35~4(5.48)</ns0:cell><ns0:cell>35(7.28)</ns0:cell><ns0:cell /><ns0:cell>39(7.04)</ns0:cell><ns0:cell /><ns0:cell>1439(13.92)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>40~6(8.22)</ns0:cell><ns0:cell>64(13.31)</ns0:cell><ns0:cell /><ns0:cell>70(12.64)</ns0:cell><ns0:cell /><ns0:cell>1366(13.21)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>45~15(20.55)</ns0:cell><ns0:cell>94(19.54)</ns0:cell><ns0:cell /><ns0:cell>109(19.68)</ns0:cell><ns0:cell /><ns0:cell>1512(14.62)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>50~14(19.18)</ns0:cell><ns0:cell>86(17.88)</ns0:cell><ns0:cell /><ns0:cell>100(18.05)</ns0:cell><ns0:cell /><ns0:cell>1244(12.03)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>55~8(3.70)</ns0:cell><ns0:cell>73(15.18)</ns0:cell><ns0:cell /><ns0:cell>81(14.62)</ns0:cell><ns0:cell /><ns0:cell>997(9.64)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>60~11(15.07)</ns0:cell><ns0:cell>71(14.76)</ns0:cell><ns0:cell /><ns0:cell>82(14.80)</ns0:cell><ns0:cell /><ns0:cell>878(8.49)</ns0:cell></ns0:row><ns0:row><ns0:cell>65~69</ns0:cell><ns0:cell>8(10.96)</ns0:cell><ns0:cell>32(6.65)</ns0:cell><ns0:cell /><ns0:cell>40(7.22)</ns0:cell><ns0:cell /><ns0:cell>1499(14.50)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Smoking history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.584</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Yes</ns0:cell><ns0:cell>24(32.88)</ns0:cell><ns0:cell>174(36.17)</ns0:cell><ns0:cell /><ns0:cell>198(35.74)</ns0:cell><ns0:cell /><ns0:cell>1670(16.15)</ns0:cell></ns0:row><ns0:row><ns0:cell>No</ns0:cell><ns0:cell>49(67.12)</ns0:cell><ns0:cell>307(63.83)</ns0:cell><ns0:cell /><ns0:cell>356(64.26)</ns0:cell><ns0:cell /><ns0:cell>8670(83.85)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>NPC family history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.566</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Yes</ns0:cell><ns0:cell>6(8.22)</ns0:cell><ns0:cell>50(10.4)</ns0:cell><ns0:cell /><ns0:cell>56(10.11)</ns0:cell><ns0:cell /><ns0:cell>198(1.91)</ns0:cell></ns0:row><ns0:row><ns0:cell>No</ns0:cell><ns0:cell>67(91.78)</ns0:cell><ns0:cell>431(89.60)</ns0:cell><ns0:cell /><ns0:cell>498(89.89)</ns0:cell><ns0:cell /><ns0:cell>10142(98.09)</ns0:cell></ns0:row></ns0:table><ns0:note>*</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Characteristics of the training stage population</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell cols='3'>NPC cases (N=320), n (%)</ns0:cell><ns0:cell /><ns0:cell cols='2'>Controls (N=320)</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Early-stage</ns0:cell><ns0:cell>Advanced-</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Categories</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>NPC cases</ns0:cell><ns0:cell>stage NPC</ns0:cell><ns0:cell>Total</ns0:cell><ns0:cell>P *</ns0:cell><ns0:cell>n (%)</ns0:cell><ns0:cell>P &#8224;</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>(n=40)</ns0:cell><ns0:cell>cases(n=280)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Sex</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.377</ns0:cell><ns0:cell /><ns0:cell>0.661</ns0:cell></ns0:row><ns0:row><ns0:cell>Male</ns0:cell><ns0:cell>26 (67.74)</ns0:cell><ns0:cell>201 (74.89)</ns0:cell><ns0:cell>227(70.94)</ns0:cell><ns0:cell /><ns0:cell>232 (72.50)</ns0:cell></ns0:row><ns0:row><ns0:cell>Female</ns0:cell><ns0:cell>14 (32.26)</ns0:cell><ns0:cell>79 (25.11)</ns0:cell><ns0:cell>93 (29.06)</ns0:cell><ns0:cell /><ns0:cell>88(27.50)</ns0:cell></ns0:row><ns0:row><ns0:cell>Age (years)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.419</ns0:cell><ns0:cell /><ns0:cell>0.967</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>30~3 (7.50)</ns0:cell><ns0:cell>16 (5.71)</ns0:cell><ns0:cell>19 (5.94)</ns0:cell><ns0:cell /><ns0:cell>23 (7.19)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>35~2 (5.00)</ns0:cell><ns0:cell>23 (8.21)</ns0:cell><ns0:cell>25 (7.81)</ns0:cell><ns0:cell /><ns0:cell>30 (9.38)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>40~1 (2.50)</ns0:cell><ns0:cell>41 (14.64)</ns0:cell><ns0:cell>42 (13.13)</ns0:cell><ns0:cell /><ns0:cell>40 (12.50)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>45~8 (20.00)</ns0:cell><ns0:cell>55 (19.64)</ns0:cell><ns0:cell>63 (19.69)</ns0:cell><ns0:cell /><ns0:cell>58 (18.13)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>50~7 (17.50)</ns0:cell><ns0:cell>46 (16.43)</ns0:cell><ns0:cell>53 (16.56)</ns0:cell><ns0:cell /><ns0:cell>48 (15.00)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>55~6 (15.00)</ns0:cell><ns0:cell>42 (15.00)</ns0:cell><ns0:cell>48 (15.00)</ns0:cell><ns0:cell /><ns0:cell>45 (14.06)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>60~9 (22.50)</ns0:cell><ns0:cell>42 (15.00)</ns0:cell><ns0:cell>51 (15.94)</ns0:cell><ns0:cell /><ns0:cell>53 (16.56)</ns0:cell></ns0:row><ns0:row><ns0:cell>65~69</ns0:cell><ns0:cell>4 (10.00)</ns0:cell><ns0:cell>15 (5.36)</ns0:cell><ns0:cell>19 (5.94)</ns0:cell><ns0:cell /><ns0:cell>23 (7.19)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Smoking history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>0.824</ns0:cell><ns0:cell /><ns0:cell>0.235</ns0:cell></ns0:row><ns0:row><ns0:cell>Yes</ns0:cell><ns0:cell>13 (32.50)</ns0:cell><ns0:cell>96 (34.29)</ns0:cell><ns0:cell>109 (34.06)</ns0:cell><ns0:cell /><ns0:cell>95 (29.69)</ns0:cell></ns0:row><ns0:row><ns0:cell>No</ns0:cell><ns0:cell>27 (67.50)</ns0:cell><ns0:cell>184 (65.71)</ns0:cell><ns0:cell>211 (65.94)</ns0:cell><ns0:cell /><ns0:cell>225 (70.31)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>NPC family history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>0.097</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Yes</ns0:cell><ns0:cell>1 (2.50)</ns0:cell><ns0:cell>32 (11.42)</ns0:cell><ns0:cell>33 (10.31)</ns0:cell><ns0:cell /><ns0:cell>6 (1.88)</ns0:cell></ns0:row><ns0:row><ns0:cell>No</ns0:cell><ns0:cell>39 (97.50)</ns0:cell><ns0:cell>248(88.58)</ns0:cell><ns0:cell>287 (89.69)</ns0:cell><ns0:cell /><ns0:cell>314 (98.12)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>2 * Differences in sex and smoking history between early-stage and advanced-stage NPC cases were compared by the</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>3 &#967; 2 test. Differences in age and NPC family history between early-stage and advanced-stage NPC cases were</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>4 compared by Fisher's exact test.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>5</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>&#8224; Differences in the baseline information distributions of the NPC cases and controls were compared by the &#967; 2 test.6</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Diagnostic value of the markers</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>Cut-off</ns0:cell><ns0:cell>Sensitivity (%)</ns0:cell><ns0:cell>Specificity (%)</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Marker</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>AUC (95% CI)</ns0:cell><ns0:cell>P *</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>value</ns0:cell><ns0:cell>(95% CI)</ns0:cell><ns0:cell>(95% CI)</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>VCA-IgA &#215;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.429</ns0:cell><ns0:cell>90.94 (87.2, 93.8)</ns0:cell><ns0:cell>92.50 (89.0,95.1)</ns0:cell><ns0:cell>0.978 (0.969, 0.986)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>PROB</ns0:cell><ns0:cell>0.949</ns0:cell><ns0:cell>87.81 (83.7,91.2)</ns0:cell><ns0:cell>95.94 (93.2,97.8)</ns0:cell><ns0:cell>0.972 (0.962, 0.982)</ns0:cell><ns0:cell>&lt;0.01</ns0:cell></ns0:row><ns0:row><ns0:cell>VCA-IgA</ns0:cell><ns0:cell>1.194</ns0:cell><ns0:cell>84.06 (79.6, 87.9)</ns0:cell><ns0:cell>91.25 (87.6, 94.1)</ns0:cell><ns0:cell>0.947 (0.932, 0.963)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell>0.397</ns0:cell><ns0:cell>87.81 (83.7, 91.2)</ns0:cell><ns0:cell>85.00(80.6, 88.7)</ns0:cell><ns0:cell>0.935(0.917, 0.953)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Sensitivity differences for early-stage and advanced-stage NPC by using different markers The sensitivity differences between early-stage and advanced-stage NPC were compared by Fisher's exact test. Compared with combination, the PROB had a lower sensitivity for early-stage NPC patients by McNemar test (p&lt;0.001). # Compared with combination, the VCA-IgA had a lower sensitivity for early-stage NPC patients by McNemar test (p&lt;0.001). * compared with combination, the EBNA1-IgA had a lower sensitivity for early-stage NPC patients by McNemar test (p&lt;0.001).</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Sensitivity (%)</ns0:cell></ns0:row></ns0:table><ns0:note>&#402; PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Sensitivity differences for man and female NPC by using different markers</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_8'><ns0:head>Table 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Sensitivity differences for man and female NPC by using different markers Sensitivity (%) for NPC cases</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Marker</ns0:cell><ns0:cell>Cut-off value</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>P &#8224;</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Man</ns0:cell><ns0:cell>Female</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>VCA-IgA&#215;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.429</ns0:cell><ns0:cell>91.76</ns0:cell><ns0:cell>90.63</ns0:cell><ns0:cell>0.781</ns0:cell></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>PROB</ns0:cell><ns0:cell>0.949</ns0:cell><ns0:cell>85.29</ns0:cell><ns0:cell>81.25</ns0:cell><ns0:cell>0.450</ns0:cell></ns0:row><ns0:row><ns0:cell>VCA-IgA</ns0:cell><ns0:cell>1.194</ns0:cell><ns0:cell>84.71</ns0:cell><ns0:cell>73.44</ns0:cell><ns0:cell>0.047</ns0:cell></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell>0.397</ns0:cell><ns0:cell>85.88</ns0:cell><ns0:cell>85.93</ns0:cell><ns0:cell>0.991</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>&#8224; The sensitivity differences between man and female NPC were compared by &#967; 2 test.PeerJ reviewing PDF | (2020:05:48783:1:2:NEW 17 Aug 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Jiangmen Central Hospital No.23, Beijie Haibang Street, Pengjiang District, Jiangmen, Guangdong, 529030, China Tel:+86-750-3165500 Fax:+86-750- 3375441 http://www.jmszxyy.com.cn/ [email protected] Dear Editors We thank the reviewers for their generous comments on the manuscript and have edited the manuscript to address their concerns. In revised manuscript, we add a statistic software ( GraphPad Prism software version 8.0) and the McNemar test to analyse the data. We apply McNemar test to compare the sensitivities for early-stage NPC patients by using different markers (table 4) . The result of comparison of smoking history between the cases and controls is correct in table 2. The p value for comparison of AUCs between VCA-IgA and the combination is corrected in table 3. We updated the information of the authors. Dongping Rao, PhD On behalf of all authors. Reviewer 1 (Allan Hildesheim) Basic reporting No comments Experimental design See comments below Validity of the findings See comments below Comments for the Author In this study, the authors evaluated the performance of EBV VCA and EBNA1 IgA antibody screening for NPC detection. Using data from over 550 NPC hospital-based cases and over 10,000 individuals who participated in an NPC screening program, the authors evaluate the performance characteristics of VCA IgA alone, EBNA1 IgA alone and a multiplicative combination of these 2 assay results for the identification of NPC. This is a large effort that explores a question of public health importance in regions with high incidence of NPC. Of note, performance of these same antibody tests has previously been evaluated/published using a combination risk score based on a logistic model, as appropriately noted by the authors. The following suggestions/questions are offered to the authors: 1. It is unclear how many of the 550+ hospital cases included in this study derived from individuals who participated in the 10,000+ screening program. Assuming a subset of the 550+ cases were identified via screening, an additional analysis that restricts to individuals who participated in the screening study would be of interest (i.e., exclude NPC cases identified via self-referral of symptomatic individuals). Such an analysis would more accurately evaluate the performance of EBV-based antibody screening for the detection of NPC in the study population. 2. Since the same two assays have been previously used for NPC screening using a scoring system defined using a logistic model, it would be of interest to directly compare the performance of the published logistic model score to the present multiplicative score. Such an analysis would be highly informative to determine whether the multiplicative approach has improved performance compared to the already existent logistic model-based score. 3. It is unclear why a multiplicative score was chosen. The choice of such an approach should be further justified/explained. In addition, other methods of defining the VCA/EBNA1 combined risk score could be considered. At a minimum, an approach that considered the additive effect of the 2 assays could be considered. 4. While 70% of cases were male, <40% of controls were male. Given that rates of NPC differ considerably by sex, an analysis that evaluates the performance of the antibody-based score separately for men and women would be informative. Apply to Reviewer 1 (Allan Hildesheim) To Question1 In this study, we collected 554 NPC patients. Among the 554 cases, 7 (1.26%) participated in the NPC screening program. To Question 2 In revised manuscript, we compared the performance of the published logistic model score to the present multiplicative score according to reviewer’s advice. To Question 3 We found some literature that applied multiplication model to make new marker to improve diagnostic performance (DOI 10.1016 /j.cca. 2019. 10. 010.). To Question4 In revised manuscript, we compared the sensitivities between men and women according to reviewer’s advice. Apply to Reviewer 2 (Anonymous) Basic reporting 1) literature reference is needed for the multiplication model. In the revised manuscript, we add a literature reference for the multiplication model (DOI 10.1016 /j.cca. 2019. 10. 010.). 2) Figure 1 and Figure 2 should be converted to boxplot with marker cut-off value indicated in graphs. According to review’s suggestion, Figure 1 and Figure 2 were converted to boxplot with marker cut-off value indicated in graphs in the revised manuscript. Experimental design 1) Line 226 to 232 in manuscript - The description of results in these lines seems more appropriate to be under the Results sub-title 'Diagnostic value of the markers' than under the Results sub-title 'Diagnostic accuracies of the markers'. For results that come under diagnostic accuracy, it is hoped that findings related to true positive (TP), false positive (FP), true negative (TN), false negative (FN), accuracy [formula = (TP + TN)/(TP + TN + FP + FN)] would be reported. According to review’s suggestion, Line 226 to 232 in manuscript was moved to be under the Results sub-title 'Diagnostic value of the markers' in the revised manuscript. 2) Diagnostic values of combined VCA/IgA and EBNA1/IgA markers had been reported by other case-control and prospective studies and shown to have higher diagnostic values than single markers (Gao et al., 2017; Liu et al., 2012; Yu et al., 2018). These studies utilized probability calculated by logistic regression while the authors of this manuscript applied multiplication model. This manuscript could provide a bit more justification about the usage of multiplication model and also perhaps conduct more analysis to cover the knowledge gap - compare the performance of these two modeling methods using same data set and discuss about their practicability and limitations. Validity of the findings 1) In discussion, the authors mentioned that 'The cost of NPC screening with EBV DNA test was expensive (Harris et al., 2019)...'. However, this sentence is referencing to a report that made estimation from non-endemic area (Harris et al., 2019). We found this Paragraph about 'The cost of NPC screening with EBV DNA test was expensive (Harris et al., 2019)...' were not appropriate. So this Paragraph was deleted in the revised manuscript. 2) In discussion, the authors mentioned that 'The diagnostic performance of EBV DNA test for early-stage NPC patients was not satisfactory (Ji et al., 2014)'. The authors should include more recent studies in discussion (for examples, PMID: 28792880 and PMID: 31469434). We found this Paragraph about were not appropriate. So this Paragraph was deleted in the revised manuscript. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>To improve the performance of NPC screening, we used a combination based on the IgA antibody against the Epstein-Barr virus (EBV) capsid antigen (VCA-IgA) and the IgA antibody against Epstein-Barr virus nuclear antigen 1 (EBNA1-IgA) to NPC screening by enzyme-linked immunosorbent assay (ELISA). A multiplication model was applied to measure the level of the combination. We evaluated the NPC screening effect of the markers. A case-control study was performed to assess the NPC screening effect of the markers. A total of 10,894 serum specimens were collected, including 554 samples from NPC patients and 10,340 samples from healthy controls. In the training stage, 640 subjects were randomly selected, including 320 NPC cases and 320 healthy controls. In the verification stage, 10,254 subjects were used to verify the NPC screening effect of the combination. Receiver operating characteristic (ROC) analysis was performed. In the verification stage, the combination achieved an sensitivity of 91.45%, a specificity of 93.45%, and an area under the ROC curve (AUC) of 0.978 (95% CI: 0.968, 0.987).</ns0:p><ns0:p>Compared with VCA-IgA and EBNA1-IgA individually, the combination had an improved screening performance. A probability (PROB) calculated by logistic regression model based on VCA-IgA and EBNA1-IgA was applied to NPC screening by ELISA in China. The AUC of the combination was a little bit larger than the PROB. There was a slight increase (3.13%) in</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>In southern China and southeast Asia, nasopharyngeal carcinoma (NPC) is a common malignant tumour, with an incidence rate of 10-40/100,000 per year <ns0:ref type='bibr' target='#b28'>(Ng et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b34'>Torre et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b36'>Wei &amp; Sham 2005;</ns0:ref><ns0:ref type='bibr' target='#b37'>Yang et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b39'>Yu &amp; Yuan 2002)</ns0:ref>. Jiangmen city, an endemic area of NPC located along the Zhujiang River in the central southern area of Guangdong province, has a high-risk NPC population.</ns0:p><ns0:p>The NPC incidence rate in the Jiangmen urban area is 14.99/10 5 <ns0:ref type='bibr' target='#b35'>(Wei et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The population-based cancer registry was established in Jiangmen to report the incidence and mortality of cancers. Population-based NPC screening was performed in the Jiangmen urban area by Jiangmen Central Hospital from June 2018 to March 2020.</ns0:p><ns0:p>The occurrence of NPC is strongly associated with Epstein-Barr virus (EBV) infection <ns0:ref type='bibr' target='#b10'>(Fachiroh et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b13'>Gulley, 2001;</ns0:ref><ns0:ref type='bibr' target='#b16'>Henle &amp; Henle, 1976;</ns0:ref><ns0:ref type='bibr'>Sam, Abu-Samah &amp; Prasad,1994)</ns0:ref>. Furthermore, host genetics, smoking, the consumption of salted fish and occupational exposures are contributors to the pathogenesis of NPC <ns0:ref type='bibr' target='#b3'>(Chang &amp; Adami, 2006;</ns0:ref><ns0:ref type='bibr' target='#b4'>Chang et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b6'>Chen et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b38'>Yong et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The development mechanisms of NPC are unclear. Mass screening is the main effective measure to detect NPC early in endemic areas.</ns0:p><ns0:p>EBV antibodies are widely used as markers in NPC screening <ns0:ref type='bibr' target='#b7'>(Chien et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b18'>Ji et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b19'>Ji et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b28'>Ng et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b30'>Tan et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b42'>Zeng et al., 1982)</ns0:ref>. A number of studies have shown that screening for NPC by using EBV antibodies is an effective measure to improve the survival rate of NPC patients <ns0:ref type='bibr' target='#b8'>(Choi et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b19'>Ji et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b20'>Jia et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b27'>Ng et al., 2010)</ns0:ref>. The combined serological test based on the IgA antibody against the EBV capsid antigen (VCA-IgA) and the IgA antibody against EBV nuclear antigen 1 (EBNA1-IgA) by enzyme-linked immunosorbent assay (ELISA) was used for NPC screening in endemic areas in China <ns0:ref type='bibr' target='#b11'>(Gao et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b23'>Liu et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b40'>Yu et al., 2018)</ns0:ref>. In previous studies, the probability (PROB) calculated by logistic regression based on VCA-IgA and EBNA1-IgA was applied to NPC screening in China <ns0:ref type='bibr' target='#b11'>(Gao et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b23'>Liu et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b40'>Yu et al., 2018)</ns0:ref>.</ns0:p><ns0:p>Multiplication model was applied to make new maker to improve diagnostic effect <ns0:ref type='bibr'>(Attila et al., 2020)</ns0:ref>. In this study, a combination of two ELISA tests based on VCA-IgA and EBNA1-IgA was applied to improve the effect of NPC screening by using a multiplication model and the NPC screening effect of the markers was evaluated. The information on age, sex, smoking history and family history of NPC for the cases and healthy controls were collected by inquiring medical records and using a questionnaire survey.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>PeerJ</ns0:head></ns0:div> <ns0:div><ns0:head>Serological test</ns0:head><ns0:p>In total, 10894 serum samples were collected and underwent serological tests in separate batches at Jiangmen Central Hospital. The samples were separated and stored at -40&#176;C. In this study, the NPC screening markers included VCA-IgA, EBNA1/IgA and combination. The antibodies VCA-IgA (Euroimmun, Lubeck, Germany) and EBNA1-IgA (Zhongshan Bio-tech, Zhongshan, China) were tested by ELISA on a TECAN Freedom EVOlyzer 200/8 platform according to the manufacturer's specifications. EBNA1s in Zhongshan Bio-tech kit were produced with purified recombinant peptide specified by EBV BKRF1 (72 kD) <ns0:ref type='bibr' target='#b14'>(He et al. 2018)</ns0:ref>. The EBV VCAs in Euroimmun kit were obtained from the pyrolysis products of human B lymphocytes (P3HR1cell line) infected by EBV <ns0:ref type='bibr' target='#b11'>(Gao et al., 2017)</ns0:ref>. The levels of the antibodies were assessed by the relative optical density (rOD) calculated according to the manufacturers' instructions by dividing the optical density (OD) value by a reference control <ns0:ref type='bibr' target='#b17'>(Ji et al., 2014)</ns0:ref>. In this study, the multiplication model based on VCA-IgA and EBNA1-IgA was calculated by using the following formula:</ns0:p><ns0:p>. The formula for </ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Baseline information</ns0:head><ns0:p>The characteristics of the 554 cases and 10340 healthy controls are shown in Table Manuscript to be reviewed &#177; 11.60 years. Among the 10340 healthy controls, 1670 (16.15%) had a smoking history, and 198 (1.91%) had a family history of NPC (Table <ns0:ref type='table' target='#tab_2'>1</ns0:ref>).</ns0:p><ns0:p>The differences in age, sex, smoking history and NPC family history were significant between NPC cases and healthy controls (Table <ns0:ref type='table' target='#tab_2'>1</ns0:ref>). There were no statistically significant differences in age, sex, smoking history and NPC family history between the early-stage and advanced-stage cases (Table <ns0:ref type='table' target='#tab_2'>1</ns0:ref>).</ns0:p><ns0:p>The characteristics of the 320 cases and 320 healthy controls in the training stage are shown in Table <ns0:ref type='table' target='#tab_3'>2</ns0:ref>. In this stage, the controls and NPC cases were matched by sex and age to prevent bias. Differences in age, smoking history and sex were not statistically significant, while differences in NPC family history were significant between the cases and controls. There were no statistically significant differences in sex, age, smoking history, or NPC family history between the earlystage and advanced-stage cases (Table <ns0:ref type='table' target='#tab_3'>2</ns0:ref>).</ns0:p><ns0:p>In the verification stage, a total of 10254 subjects were enrolled, including 234 NPC cases and 10020 healthy controls. Of the 10254 subjects, 3897 (38.00%) were men, and the mean age was 48.57 &#177; 11.61 years. Among the 10254 subjects, 1664 (16.23%) had a smoking history, and 215 (2.10%) had a family history of NPC.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparison of levels of markers in NPC patients and healthy controls</ns0:head><ns0:p>The rODs of VCA-IgA and EBNA1-IgA, PROB value and combination value in NPC patients and healthy controls were showed in Figure <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>. The t tests showed that the means of markers in NPC patients were all significantly higher than those in healthy controls (p&lt;0.001). </ns0:p></ns0:div> <ns0:div><ns0:head>Diagnostic value of the markers</ns0:head><ns0:p>The diagnostic performance of the markers is shown in Compared to the AUCs of VCA-IgA (p&lt;0.001) ,EBNA1-IgA (p&lt;0.001), and PROB (p&lt;0.01), the combination yielded a higher AUC (Table <ns0:ref type='table' target='#tab_1'>3</ns0:ref> and Figure <ns0:ref type='figure'>3</ns0:ref>) by using training samples. The differences in the sensitivities of the markers between early-stage and advanced-stage NPC patients were not significant by using verification samples(p&gt;0.05, Table <ns0:ref type='table' target='#tab_5'>4</ns0:ref>). Compared with each marker alone by Manuscript to be reviewed</ns0:p><ns0:p>McNemar test, the combination had a higher sensitivity for early-stage NPC patients (Table <ns0:ref type='table' target='#tab_5'>4</ns0:ref>).</ns0:p><ns0:p>The differences in sensitivities of EBNA1-IgA, PROB and the combination between man and female NPC patients were not significant by using verification samples (p&gt;0.05), while the sensitivity of VCA-IgA in man NPC patients was higher than in female NPC patients (p=0.047, Table <ns0:ref type='table' target='#tab_6'>5</ns0:ref>). The sensitivity differences of the markers in different age, smoking history and NPC family history were not statistically significant by by using verification samples (p&gt;0.05, Table <ns0:ref type='table' target='#tab_7'>6</ns0:ref>, Table <ns0:ref type='table' target='#tab_8'>7</ns0:ref>, Table <ns0:ref type='table' target='#tab_9'>8</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Verifying the effect of the combination on NPC screening</ns0:head><ns0:p>A total of 10253 subjects were enrolled to verify the NPC screening effect, including 234 NPC cases and 10020 healthy controls sourced from the screening field. In this stage, the combination achieved an overall sensitivity of 91.45%</ns0:p><ns0:p>(214/234), a sensitivity for early-stage NPC detection of 93.94% (31/33), a specificity of 93.45% (9364/10020), and an AUC of 0.978 (95% CI: 0.968, 0.987).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>NPC is a main health problem that leads to a high health burden in southern China, especially in Guangdong province <ns0:ref type='bibr' target='#b2'>(Cao et al., 2011)</ns0:ref>. EBV antibodies are widely applied in NPC screening. PROB calculated by logistic model were applied in NPC screening based on VCA-IgA and EBNA1-IgA <ns0:ref type='bibr' target='#b11'>(Gao et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b25'>Liu et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b40'>Yu et al., 2018)</ns0:ref>. In this study, a combination calculated by multiplication model based on VCA-IgA and EBNA1-IgA was applied to NPC screening. The NPC screening effect of combination was evaluated and compared with the Manuscript to be reviewed individual screening markers, PROB, VCA-IgA and EBNA1-IgA. Compared with PROB, VCA-IgA and EBNA1-IgA, the combination had a higher AUC of 0.978 (95% CI: 0.969, 0.986). We found that the combination calculated by using a multiplication model can be applied to NPC screening.</ns0:p><ns0:p>In this study, a large number of healthy controls and 554 NPC patients were collected from the endemic areas, which is favourable for evaluating the performance of the markers for NPC screening. In the verification stage, 10254 subjects were enrolled to verify the NPC screening effect. The combination achieved a sensitivity of 91.45%, a specificity of 93.45% and an AUC of 0.978 (95% CI: 0.968, 0.987). These results demonstrated that the combination calculated by using a multiplication model was effective for NPC screening.</ns0:p><ns0:p>In this study, the levels of markers (PROB, VCA-IgA, EBNA1-IgA and combination) in NPC patients were higher than in healthy controls. It was consistent with the results of previous reports <ns0:ref type='bibr' target='#b23'>(Liu et al., 2012)</ns0:ref>. We found the difference in sensitivities of the combination in different age, sex, smoking history and NPC family history were not statistically significant. The VCA-IgA had a higher sensitivity for man NPC patients than female NPC patients by using verification samples. Since the P value (0.047) was very close to 0.05, and the verification sample size was not very large. The difference in sensitivity of VCA-IgA between man and female NPC patients may be due to the random fluctuation.</ns0:p><ns0:p>In the present study, the AUCS, sensitivities and specificities of VCA-IgA and EBNA1-IgA were lower than those of the combination, showing that the combination was more effective in diagnosis. The AUC of the combination was a little bit larger than the PROB. There was a slight increase (3.13%) in the Manuscript to be reviewed sensitivity of the combination compared to the sensitivity of the PROB. The specificity was lower for the combination (92.50%) than for the PROB (95.94%).</ns0:p><ns0:p>In areas with high NPC incidence, the increased sensitivity means that more earlystage NPC patients will be detected and treated early, while the decreased specificity may lead to an increased false positive rate and increased costs of the screening program.</ns0:p><ns0:p>The present study had some limitations. First, there was some bias in identifying the 10340 subjects as healthy controls because not all healthy controls underwent an examination by fibreoptic endoscopic examination. Second, since the study population was obtained from provinces with a high risk of NPC, the results may be limited for application in other populations. Third, the sample size of the earlystage NPC patients was not large enough in this study. There was some bias in estimating sensitivity for early-stage NPC patients.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>We successfully developed a combination of two ELISA tests based on VCA-IgA and EBNA1-IgA to improve the effect of NPC screening by using a multiplication model. Compared with VCA-IgA and EBNA1-IgA individually, the combination had an improved diagnostic performance. The AUC and sensitivity of the combination were slightly higher than those of the PROB, while the specificity was lower for the combination than for the PROB. The results suggested that the combination was effective and can be an option for NPC screening. Manuscript to be reviewed Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020) Manuscript to be reviewed Study population A case-control study was performed to compare the effect of the NPC screening of markers, including 554 NPC cases and 10340 healthy controls. This study included the training stage and the verification stage. The inclusion criteria for NPC cases included being histologically confirmed by biopsy, aged between 30 and 69 years, and residing in Jiangmen. A total of 554 serum specimens were continuously collected from NPC patients at Jiangmen Central Hospital from June 2018 to March 2020. Among the 554 cases, 7 (1.26%) participated in the NPC screening program. NPC stages were classified according to the 2008 staging system of China (Lin ZX et al., 2009). The stages were divided into early-stage (stage I and stage II) and advanced-stage (stage III and stage IV) disease. A total of 554 cases comprised 73 early-stage cases and 481 advanced-stage cases. A total of 320 NPC training samples were randomly selected from the 554 NPC cases, and the remaining 234 of 554 NPC cases were used as validation samples. A total of 10,340 healthy controls were obtained from an NPC screening programme performed in a population aged 30-69 years in the Jiangmen City urban area from June 2018 to March 2020. The healthy controls resided in Jiangmen of Guangdong province. A total of 320 training samples were randomly selected from the 10340 healthy controls and were frequency matched to the 320 training NPC cases by age (5-year age groups) and sex. The remaining 10020 of 10340 healthy controls were used as the validation samples.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>2018). In the formulas, VCA-IgA and EBNA1-IgA represent the rOD values for VCA-IgA and EBNA1-IgA, respectively, which were tested by ELISA.The written informed consent was obtained from healthy controls. The serum samples of NPC patients were collected after clinical use which were exempted from informed consent. This study was approved by the Clinical Research Ethics Committee of the Jiangmen Central Hospital (2019-28).PeerJ reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020)Manuscript to be reviewedStatistical analysisCategorical variables are described as numbers and percentages. Continuous variables are shown as the means and standard deviations (SDs). The levels of VCA-IgA, EBNA1-IgA, PROB and combination were compared by t tests in different population. Receiver operating characteristic (ROC) curve analysis was performed. The cut-off value of each marker was defined with the largest Youden Index selected from each ROC curve. The effects of the screening markers were measured using the sensitivity, specificity and area under the ROC curve (AUC).The base information of different populations was described and compared by the &#967; 2 test and Fisher's exact test. The difference in sensitivities of markers were compared by &#967; 2 test, Fisher's exact test and McNemar test.The differences in AUCs were compared using the Z test according to the DeLong method<ns0:ref type='bibr' target='#b9'>( DeLong et al., 1988)</ns0:ref>. The 95% confidence intervals (CIs) of the sensitivities, specificities and AUCs were calculated. The statistical analyses were carried out using MedCalc Statistical Software version 15.2.2 (MedCalc Software bvba, Ostend, Belgium) and GraphPad Prism software version 8.0 (San Diego, CA, USA) and were two-sided, with significance set at p&lt;0.05.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020) Manuscript to be reviewed Comparison of levels of markers in early-stage and advanced-stage NPC patients Of the 554 NPC patients, 73 (13.18%) were early-stage. The levels of VCA-IgA EBNA1-IgA, PROB and combination in early-stage and advanced-stage NPC patients were showed in Figure 2. The differences in VCA-IgA, EBNA1-IgA, PROB and combination were not significant between early-stage and advancedstage NPC patients by t tests (p&gt;0.05).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>by using training</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Characteristics of the total population Differences in sex, age, smoking history and NPC family history between early-stage and advanced-stage NPC cases were compared by the &#967; 2 test.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell cols='3'>NPC cases (N=554), n (%)</ns0:cell><ns0:cell /><ns0:cell cols='2'>Controls (N=10340)</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Early-stage</ns0:cell><ns0:cell cols='2'>Advanced-stage</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Categories</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>NPC cases</ns0:cell><ns0:cell>NPC</ns0:cell><ns0:cell>cases</ns0:cell><ns0:cell>Total</ns0:cell><ns0:cell>P *</ns0:cell><ns0:cell>n (%)</ns0:cell><ns0:cell>P &#8224;</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>(n=73)</ns0:cell><ns0:cell>(n=481)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Sex</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.356</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Male</ns0:cell><ns0:cell>49(67.12)</ns0:cell><ns0:cell>348(72.35)</ns0:cell><ns0:cell /><ns0:cell>397(71.66)</ns0:cell><ns0:cell /><ns0:cell>3959(38.29)</ns0:cell></ns0:row><ns0:row><ns0:cell>Female</ns0:cell><ns0:cell>24(32.88)</ns0:cell><ns0:cell>133(27.65)</ns0:cell><ns0:cell /><ns0:cell>157(28.34)</ns0:cell><ns0:cell /><ns0:cell>6381(61.71)</ns0:cell></ns0:row><ns0:row><ns0:cell>Age (years)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.546</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>30~7(9.60)</ns0:cell><ns0:cell>26(5.41)</ns0:cell><ns0:cell /><ns0:cell>33(5.96)</ns0:cell><ns0:cell /><ns0:cell>1405(13.59)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>35~4(5.48)</ns0:cell><ns0:cell>35(7.28)</ns0:cell><ns0:cell /><ns0:cell>39(7.04)</ns0:cell><ns0:cell /><ns0:cell>1439(13.92)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>40~6(8.22)</ns0:cell><ns0:cell>64(13.31)</ns0:cell><ns0:cell /><ns0:cell>70(12.64)</ns0:cell><ns0:cell /><ns0:cell>1366(13.21)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>45~15(20.55)</ns0:cell><ns0:cell>94(19.54)</ns0:cell><ns0:cell /><ns0:cell>109(19.68)</ns0:cell><ns0:cell /><ns0:cell>1512(14.62)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>50~14(19.18)</ns0:cell><ns0:cell>86(17.88)</ns0:cell><ns0:cell /><ns0:cell>100(18.05)</ns0:cell><ns0:cell /><ns0:cell>1244(12.03)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>55~8(3.70)</ns0:cell><ns0:cell>73(15.18)</ns0:cell><ns0:cell /><ns0:cell>81(14.62)</ns0:cell><ns0:cell /><ns0:cell>997(9.64)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>60~11(15.07)</ns0:cell><ns0:cell>71(14.76)</ns0:cell><ns0:cell /><ns0:cell>82(14.80)</ns0:cell><ns0:cell /><ns0:cell>878(8.49)</ns0:cell></ns0:row><ns0:row><ns0:cell>65~69</ns0:cell><ns0:cell>8(10.96)</ns0:cell><ns0:cell>32(6.65)</ns0:cell><ns0:cell /><ns0:cell>40(7.22)</ns0:cell><ns0:cell /><ns0:cell>1499(14.50)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Smoking history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.584</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Yes</ns0:cell><ns0:cell>24(32.88)</ns0:cell><ns0:cell>174(36.17)</ns0:cell><ns0:cell /><ns0:cell>198(35.74)</ns0:cell><ns0:cell /><ns0:cell>1670(16.15)</ns0:cell></ns0:row><ns0:row><ns0:cell>No</ns0:cell><ns0:cell>49(67.12)</ns0:cell><ns0:cell>307(63.83)</ns0:cell><ns0:cell /><ns0:cell>356(64.26)</ns0:cell><ns0:cell /><ns0:cell>8670(83.85)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>NPC family history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.566</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Yes</ns0:cell><ns0:cell>6(8.22)</ns0:cell><ns0:cell>50(10.4)</ns0:cell><ns0:cell /><ns0:cell>56(10.11)</ns0:cell><ns0:cell /><ns0:cell>198(1.91)</ns0:cell></ns0:row><ns0:row><ns0:cell>No</ns0:cell><ns0:cell>67(91.78)</ns0:cell><ns0:cell>431(89.60)</ns0:cell><ns0:cell /><ns0:cell>498(89.89)</ns0:cell><ns0:cell /><ns0:cell>10142(98.09)</ns0:cell></ns0:row></ns0:table><ns0:note>*</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Characteristics of the training stage population</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell cols='3'>NPC cases (N=320), n (%)</ns0:cell><ns0:cell /><ns0:cell cols='2'>Controls (N=320)</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Early-stage</ns0:cell><ns0:cell>Advanced-</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Categories</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>NPC cases</ns0:cell><ns0:cell>stage NPC</ns0:cell><ns0:cell>Total</ns0:cell><ns0:cell>P *</ns0:cell><ns0:cell>n (%)</ns0:cell><ns0:cell>P &#8224;</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>(n=40)</ns0:cell><ns0:cell>cases(n=280)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Sex</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.377</ns0:cell><ns0:cell /><ns0:cell>0.661</ns0:cell></ns0:row><ns0:row><ns0:cell>Male</ns0:cell><ns0:cell>26 (67.74)</ns0:cell><ns0:cell>201 (74.89)</ns0:cell><ns0:cell>227(70.94)</ns0:cell><ns0:cell /><ns0:cell>232 (72.50)</ns0:cell></ns0:row><ns0:row><ns0:cell>Female</ns0:cell><ns0:cell>14 (32.26)</ns0:cell><ns0:cell>79 (25.11)</ns0:cell><ns0:cell>93 (29.06)</ns0:cell><ns0:cell /><ns0:cell>88(27.50)</ns0:cell></ns0:row><ns0:row><ns0:cell>Age (years)</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>0.419</ns0:cell><ns0:cell /><ns0:cell>0.967</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>30~3 (7.50)</ns0:cell><ns0:cell>16 (5.71)</ns0:cell><ns0:cell>19 (5.94)</ns0:cell><ns0:cell /><ns0:cell>23 (7.19)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>35~2 (5.00)</ns0:cell><ns0:cell>23 (8.21)</ns0:cell><ns0:cell>25 (7.81)</ns0:cell><ns0:cell /><ns0:cell>30 (9.38)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>40~1 (2.50)</ns0:cell><ns0:cell>41 (14.64)</ns0:cell><ns0:cell>42 (13.13)</ns0:cell><ns0:cell /><ns0:cell>40 (12.50)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>45~8 (20.00)</ns0:cell><ns0:cell>55 (19.64)</ns0:cell><ns0:cell>63 (19.69)</ns0:cell><ns0:cell /><ns0:cell>58 (18.13)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>50~7 (17.50)</ns0:cell><ns0:cell>46 (16.43)</ns0:cell><ns0:cell>53 (16.56)</ns0:cell><ns0:cell /><ns0:cell>48 (15.00)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>55~6 (15.00)</ns0:cell><ns0:cell>42 (15.00)</ns0:cell><ns0:cell>48 (15.00)</ns0:cell><ns0:cell /><ns0:cell>45 (14.06)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>60~9 (22.50)</ns0:cell><ns0:cell>42 (15.00)</ns0:cell><ns0:cell>51 (15.94)</ns0:cell><ns0:cell /><ns0:cell>53 (16.56)</ns0:cell></ns0:row><ns0:row><ns0:cell>65~69</ns0:cell><ns0:cell>4 (10.00)</ns0:cell><ns0:cell>15 (5.36)</ns0:cell><ns0:cell>19 (5.94)</ns0:cell><ns0:cell /><ns0:cell>23 (7.19)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>Smoking history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>0.824</ns0:cell><ns0:cell /><ns0:cell>0.235</ns0:cell></ns0:row><ns0:row><ns0:cell>Yes</ns0:cell><ns0:cell>13 (32.50)</ns0:cell><ns0:cell>96 (34.29)</ns0:cell><ns0:cell>109 (34.06)</ns0:cell><ns0:cell /><ns0:cell>95 (29.69)</ns0:cell></ns0:row><ns0:row><ns0:cell>No</ns0:cell><ns0:cell>27 (67.50)</ns0:cell><ns0:cell>184 (65.71)</ns0:cell><ns0:cell>211 (65.94)</ns0:cell><ns0:cell /><ns0:cell>225 (70.31)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>NPC family history</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>0.097</ns0:cell><ns0:cell /><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>Yes</ns0:cell><ns0:cell>1 (2.50)</ns0:cell><ns0:cell>32 (11.42)</ns0:cell><ns0:cell>33 (10.31)</ns0:cell><ns0:cell /><ns0:cell>6 (1.88)</ns0:cell></ns0:row><ns0:row><ns0:cell>No</ns0:cell><ns0:cell>39 (97.50)</ns0:cell><ns0:cell>248(88.58)</ns0:cell><ns0:cell>287 (89.69)</ns0:cell><ns0:cell /><ns0:cell>314 (98.12)</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>2 * Differences in sex and smoking history between early-stage and advanced-stage NPC cases were compared by the</ns0:cell></ns0:row><ns0:row><ns0:cell cols='7'>3 &#967; 2 test. Differences in age and NPC family history between early-stage and advanced-stage NPC cases were</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>4 compared by Fisher's exact test.</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>5</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>&#8224; Differences in the baseline information distributions of the NPC cases and controls were compared by the &#967; 2 test.6</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Diagnostic value of the markers</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>Cut-off</ns0:cell><ns0:cell>Sensitivity (%)</ns0:cell><ns0:cell>Specificity (%)</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Marker</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>AUC (95% CI)</ns0:cell><ns0:cell>P *</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>value</ns0:cell><ns0:cell>(95% CI)</ns0:cell><ns0:cell>(95% CI)</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>VCA-IgA &#215;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.429</ns0:cell><ns0:cell>90.94 (87.2, 93.8)</ns0:cell><ns0:cell>92.50 (89.0,95.1)</ns0:cell><ns0:cell>0.978 (0.969, 0.986)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>PROB</ns0:cell><ns0:cell>0.949</ns0:cell><ns0:cell>87.81 (83.7,91.2)</ns0:cell><ns0:cell>95.94 (93.2,97.8)</ns0:cell><ns0:cell>0.972 (0.962, 0.982)</ns0:cell><ns0:cell>&lt;0.01</ns0:cell></ns0:row><ns0:row><ns0:cell>VCA-IgA</ns0:cell><ns0:cell>1.194</ns0:cell><ns0:cell>84.06 (79.6, 87.9)</ns0:cell><ns0:cell>91.25 (87.6, 94.1)</ns0:cell><ns0:cell>0.947 (0.932, 0.963)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell>0.397</ns0:cell><ns0:cell>87.81 (83.7, 91.2)</ns0:cell><ns0:cell>85.00(80.6, 88.7)</ns0:cell><ns0:cell>0.935(0.917, 0.953)</ns0:cell><ns0:cell>&lt;0.001</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Sensitivity differences for early-stage and advanced-stage NPC by using different markers</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Sensitivity (%)</ns0:cell></ns0:row></ns0:table><ns0:note>&#8224; The sensitivity differences between early-stage and advanced-stage NPC were compared by Fisher's exact test.&#402; Compared with combination, the PROB had a lower sensitivity for early-stage NPC patients by McNemar test (p&lt;0.001). # Compared with combination, the VCA-IgA had a lower sensitivity for early-stage NPC patients by McNemar test (p&lt;0.001). * compared with combination, the EBNA1-IgA had a lower sensitivity for early-stage NPC patients by McNemar test (p&lt;0.001).</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Sensitivity differences for man and female NPC by using different markers</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell cols='2'>Sensitivity (%) for NPC cases</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>Marker</ns0:cell><ns0:cell>Cut-off value</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>P &#8224;</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Man</ns0:cell><ns0:cell>Female</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>VCA-IgA&#215;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.429</ns0:cell><ns0:cell>91.76</ns0:cell><ns0:cell>90.63</ns0:cell><ns0:cell>0.781</ns0:cell></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>PROB</ns0:cell><ns0:cell>0.949</ns0:cell><ns0:cell>85.29</ns0:cell><ns0:cell>81.25</ns0:cell><ns0:cell>0.450</ns0:cell></ns0:row><ns0:row><ns0:cell>VCA-IgA</ns0:cell><ns0:cell>1.194</ns0:cell><ns0:cell>84.71</ns0:cell><ns0:cell>73.44</ns0:cell><ns0:cell>0.047</ns0:cell></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell>0.397</ns0:cell><ns0:cell>85.88</ns0:cell><ns0:cell>85.93</ns0:cell><ns0:cell>0.991</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Sensitivity differences for different ages of NPC patients by using different markers Sensitivity (%) for different ages (years) of NPC patients</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Marker</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>P &#8224;</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='8'>30~35~40~45~50~55~60~65~69</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>VCA-IgA&#215;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>100.00</ns0:cell><ns0:cell>85.71</ns0:cell><ns0:cell>89.29</ns0:cell><ns0:cell>91.30</ns0:cell><ns0:cell cols='3'>85.11 100.00 93.55</ns0:cell><ns0:cell>90.48</ns0:cell><ns0:cell>0.274</ns0:cell></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>PROB</ns0:cell><ns0:cell>85.71</ns0:cell><ns0:cell>78.57</ns0:cell><ns0:cell>78.57</ns0:cell><ns0:cell>84.78</ns0:cell><ns0:cell>83.00</ns0:cell><ns0:cell>90.91</ns0:cell><ns0:cell>87.10</ns0:cell><ns0:cell>80.95</ns0:cell><ns0:cell>0.904</ns0:cell></ns0:row><ns0:row><ns0:cell>VCA-IgA</ns0:cell><ns0:cell>78.57</ns0:cell><ns0:cell>78.57</ns0:cell><ns0:cell>85.71</ns0:cell><ns0:cell>80.43</ns0:cell><ns0:cell>78.72</ns0:cell><ns0:cell>84.85</ns0:cell><ns0:cell>87.10</ns0:cell><ns0:cell>76.19</ns0:cell><ns0:cell>0.950</ns0:cell></ns0:row><ns0:row><ns0:cell>EBNA1-IgA</ns0:cell><ns0:cell>92.86</ns0:cell><ns0:cell>78.57</ns0:cell><ns0:cell>85.71</ns0:cell><ns0:cell>86.96</ns0:cell><ns0:cell>85.11</ns0:cell><ns0:cell>93.94</ns0:cell><ns0:cell>83.87</ns0:cell><ns0:cell>76.19</ns0:cell><ns0:cell>0.674</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_8'><ns0:head>Table 7 .</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Sensitivity differences for different smoking history NPC by using different markers The sensitivity differences for different smoking history NPC were compared by &#967; 2 test.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Sensitivity (%) for NPC</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_9'><ns0:head>Table 8 (on next page)</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Sensitivity differences for NPC with and without NPC family history by using different</ns0:figDesc><ns0:table /><ns0:note>markers PeerJ reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_10'><ns0:head>Table 8 .</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Sensitivity differences for NPC with and without NPC family history by using different markers</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Sensitivity (%)</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020)</ns0:note> <ns0:note place='foot'>&#8224; The sensitivity differences between NPC with and without NPC family history were compared by &#967; 2 test.PeerJ reviewing PDF | (2020:05:48783:2:0:NEW 21 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Jiangmen Central Hospital No.23, Beijie Haibang Street, Pengjiang District, Jiangmen, Guangdong, 529030, China Tel:+86-750-3165500 Fax:+86-750- 3375441 http://www.jmszxyy.com.cn/ [email protected] Dear Editors We thank the reviewers for their generous comments on the manuscript and have edited the manuscript to address their concerns. We revised the manuscript according to the suggestions of reviewers. The sensitivity differences of different age, smoking history and family history of nasopharyngeal carcinoma were analyzed (Table 6, Table 7 and Table 8). The abstract and discussion section are supplemented according to the reviewer's comments. Figure 1 and Figure 2 were modified. Dongping Rao, PhD On behalf of all authors. Reviewer 1 (Allan Hildesheim) Basic reporting No new comment Experimental design No new comment Validity of the findings No new comment Comments for the Author I have reviewed the changes made to the manuscript and thank the authors for taking the time to respond to my previous comments. I have a couple remaining comments related to the new results summarized in Table 3. 1. Could the authors please confirm that the p-value comparing the AUC for the multiplicative (0.978; 95% CI = 0.969-0.986) and PROB (0.972; 95% CI = 0.962-0.982) models is <0.01? The 2 AUC estimates differ only in the 3rd decimal place so it is strange that the p-value reported is so small. 2. Regardless of whether or not the AUC for these 2 approaches is statistically significantly different, the difference is very minor and the authors should therefore comment on the practical implications of such a small change when deciding whether or not the multiplicative model truly improves performance over the currently used PROB model. 3. In responding to #2 above, please account for the fact that the sensitivity for the 2 approaches is very similar (91% and 88%) and that the specificity is lower for the multiplicative model (92%) than for the PROB model (96%). Since every 1% decrement in Specificity has a big impact on false(+) and programmatic costs, the fact that the PROB model has improved specificity over the newly evaluated multiplicative approach should be discussed. It is important for both the Abstract and Discussion to reflect the important finding that the PROB model is still likely the preferred way to utilize VCA/EBNA1 IgA antibody results for NPC screening and that the multiplicative model does not greatly improve on that approach overall and, in fact, has worst specificity and positive predictive value than the PROB approach. Apply to Reviewer 1 (Allan Hildesheim) To Question1 The co-author Professor Liu, an expert in epidemiology and health statistics at Sun Yat-sen University Cancer Center, verified the results again. We confirmed that the p-value comparing the AUC for the multiplicative (0.978; 95% CI = 0.969-0.986) and PROB (0.972; 95% CI = 0.962-0.982) models was <0.01. The screenshot of statistical software analysis results is as follows. To Question 2 and 3 According to reviewer’s advice, we compared the sensitivities and specificities of the combination to the PROB, and the abstract and discussion sections have been modified in revised manuscript. There was a small increase (3.13%) in the sensitivity of the combination compared to the sensitivity of the PROB. The specificity was lower for the combination (92.50%) than for the PROB (95.94%). In areas with high NPC incidence, the increased sensitivity means that more early-stage NPC patients will be detected and treated early, while the decreased specificity may lead to an increased false positive rate and increased costs of the screening program. Apply to Reviewer 2 (Anonymous) Basic reporting 1) Raw data of this study (peerj-48783-raw_data.xls): column B title 'NA1-IgA rOD' should be 'EBNA1-IgA rOD' list 'PROB' values for each individual Reply: in the revised manuscript, we changed 'NA1-IgA rOD' to 'EBNA1-IgA rOD' and listed 'PROB' values for each individual in the raw data. 2) change whiskers of box plots in Figure 1 and 2 to indicate the 10th percentile and 90th percentile and describe this in figure legend. Reply: Figure 1, Figure 2 and the their legends were modified according to the review’s advice in the revised manuscript. 3) when describing the serological results, be consistent in using '/' or '-' (e.g. VCA-IgA or VCA/IgA) Reply:We change the “VCA/IgA” to “VCA/IgA” according to the review’s advice in the revised manuscript. 4) Sensitivity and specificity values are stated using percentage in Table 3 but mentioned as fractions in manuscript (line 227 to 235). Reply:Sensitivities and specificities were expressed as percentages in the revised manuscript. 4) are Figure 3, Table 3, Table 4 and Table 5 showing results from all or just samples the training stage? please state this in the manuscript. Reply: The training sample data set was used to make Figure 3 and Table 3 Figure 3. The verification sample data set was used to make Table 4 ,Table 5,Table 6,Table 7 and Table 8. We state those in the revised manuscript. Experimental design no comment Validity of the findings no comment Comments for the Author 1) Serological results for male NPC patients and female NPC patients are not shown but VCA-IgA was reported as having higher sensitivity in detecting male NPC patients as compared to female NPC patients (Table 5). There should be some explanation or speculation about this difference in Discussion. Reply: we explained it in the discussion section in the revised manuscript. Since the P value (0.047) was very close to 0.05, and the verification sample size was not very large. The difference in sensitivity of VCA-IgA between man and female NPC patients may be due to the random fluctuation. 2) Serological results may or may not be affected by other factors stated in Table 1 (age, NPC family history and smoking history). The authors should analyse and report the findings. Reply: the sensitivity differences of different age, smoking history and family history of nasopharyngeal carcinoma were analyzed (Table 6, Table 7 and Table 8) in the revised manuscript. 3) As compared to the logistic regression model ('PROB'), the multiplication model ('combination') developed in this study had small decrease in specificity to detect all NPC (Table 3), but slight increase in sensitivity to detect all NPC (Table 3) and remarkable improvement in sensitivity to detect early stage NPC (Table 5). Are these results consistent in the training stage as well as in the verification stage? If so, what are the implications? Reply: the data of Table 3 were from training samples and the data to detect early stage NPC (Table 4,not Table 5) were from verification samples. Compared with PROB, the difference between the increased sensitivity in the training sample and the increased sensitivity in the verification sample may be due to the small sample size of early-stage NPC patients. The sample size of the early-stage NPC patients was not large enough in this study. There was some bias in estimating sensitivity for early-stage NPC patients. We expected it in the revised manuscript. 3) The results of verification stage were mentioned twice in separate paragraphs within Discussion. Reply: we deleted duplicate part and kept one of them in the revised manuscript. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Salmonella enterica serovar Javiana is the fourth most reported serotype of laboratoryconfirmed human Salmonella infections in the U.S. and in Tennessee (TN). Although Salmonella ser. Javiana is a common cause of human infection, the majority of cases are sporadic in nature rather than outbreak-associated. To better understand Salmonella ser.</ns0:p><ns0:p>Javiana microbial population structure in TN, we completed a phylogenetic analysis of 111 Salmonella ser. Javiana clinical isolates from TN collected from Jan. 2017 to Oct. 2018. We identified mobile genetic elements and genes known to confer antibiotic resistance present in the isolates, and performed a pan-genome-wide association study (pan-GWAS) to compare gene content between clades identified in this study. The population structure of TN Salmonella ser. Javiana clinical isolates consisted of three genetic clades: TN clade I (n= 54), TN clade II (n=4), and TN clade III (n=48). Using a 5, 10, and 25 hqSNP distance threshold for cluster identification, nine, 12, and 10 potential epidemiologically-relevant clusters were identified, respectively. The majority of genes that were found to be overrepresented in specific clades were located in mobile genetic element (MGE) regions, including genes encoding integrases and phage structures (91.5%). Additionally, a large portion of the over-represented genes from TN clade II (44.9%) were located on an 87.5 kb plasmid containing genes encoding a toxin/antitoxin system (ccdAB). Additionally, we completed phylogenetic analyses of global Salmonella ser. Javiana datasets to gain a broader insight into the population structure of this serovar. We found that the global phylogeny consisted of three major clades (one of which all of the TN isolates belonged to) and two cgMLST eBurstGroups (ceBGs) and that the branch length between the two Salmonella ser. Javiana ceBGs (1,423 allelic differences) was comparable to those from other serovars that have been reported as polyphyletic (929-2,850 allelic differences). This study demonstrates the population structure of TN and global Salmonella ser. Javiana</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Salmonella enterica subspecies enterica serovar Javiana (Salmonella ser. Javiana) was ranked the fourth most reported serotype (behind Enteritidis, Typhimurium, and Newport) in the United States in 2015, accounting for 7.4% (n=575) of laboratory confirmed human Salmonella infections (Centers for Disease Control and Prevention (CDC), 2017a). The incidence rate (IR) was 1.17 per 100,000 persons (Centers for Disease Control and Prevention (CDC), 2017a). In 2016, 2,719 culture-confirmed human Salmonella ser. Javiana infections were reported to the Laboratory-based Enteric Disease Surveillance (LEDS) system (9.8% of Salmonella infections; IR of 1.43 per 100,000 persons) (Centers for Disease Control and Prevention (CDC), 2018). The number of actual illnesses is likely higher according to CDC estimates of 29.3 actual cases per each laboratory-reported case <ns0:ref type='bibr' target='#b110'>(Scallan et al., 2011)</ns0:ref>. Nationally, Salmonella ser. Javiana IRthey may employ a large number of residents in the area. These employees may be directly exposed to Salmonella occupationally and indirectly expose others in those communities via items like clothes and shoes <ns0:ref type='bibr' target='#b118'>(Shaw et al., 2016)</ns0:ref>. The high density of these operations could also lead to environmental transmission via contamination of groundwater and surface water with untreated animal waste <ns0:ref type='bibr' target='#b118'>(Shaw et al., 2016)</ns0:ref>. <ns0:ref type='bibr'>Shaw, et al.</ns0:ref> did not find any statistically significant correlations between rurality or presence of broiler, cattle, dairy, or hog operations and IR ratios of Salmonella ser. Javiana in TN <ns0:ref type='bibr' target='#b118'>(Shaw et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Salmonella ser. Javiana outbreaks have been linked to chicken <ns0:ref type='bibr' target='#b69'>(Jackson et al., 2013)</ns0:ref>, pork <ns0:ref type='bibr' target='#b69'>(Jackson et al., 2013)</ns0:ref>, cheese <ns0:ref type='bibr' target='#b6'>(Alley &amp; Pijoan, 1942;</ns0:ref><ns0:ref type='bibr' target='#b66'>Hedberg et al., 1992)</ns0:ref>, shrimp <ns0:ref type='bibr' target='#b132'>(Venkat et al., 2018)</ns0:ref>, produce <ns0:ref type='bibr' target='#b16'>(Bennett et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b17'>Blostein, 1993</ns0:ref>; Centers for Disease Control and Prevention (CDC), 2005; Centers for Disease Control and Prevention (CDC), 2007; <ns0:ref type='bibr' target='#b64'>Hanning et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b69'>Jackson et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b107'>Sandt et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b119'>Sivapalasingam et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b121'>Srikantiah et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b129'>Toth et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b134'>Walsh et al., 2014)</ns0:ref>, spices <ns0:ref type='bibr' target='#b81'>(Lehmacher et al., 1995;</ns0:ref><ns0:ref type='bibr' target='#b149'>Zweifel &amp; Stephan, 2012)</ns0:ref>, ill foodhandlers <ns0:ref type='bibr' target='#b47'>(Elward et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b79'>Lee et al., 1998)</ns0:ref>, and contact with amphibians <ns0:ref type='bibr' target='#b122'>(Srikantiah et al., 2004)</ns0:ref>. According to the National Outbreak Reporting System (NORS), there have been eight Salmonella ser. Javiana outbreaks involving TN, five multistate and three singlestate and all were foodborne. Identified vehicles included tomatoes, cucumbers, tilapia, fajita (beef), and iceberg lettuce. All of the TN outbreaks were in restaurant settings.</ns0:p><ns0:p>Salmonella ser. Javiana has been isolated from a variety of foods, including seafood <ns0:ref type='bibr' target='#b88'>(Mezal et al., 2013)</ns0:ref>, white pepper <ns0:ref type='bibr' target='#b88'>(Mezal et al., 2013)</ns0:ref>, produce <ns0:ref type='bibr' target='#b44'>(Duffy et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b46'>Elviss et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b88'>Mezal et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b101'>Reddy et al., 2016)</ns0:ref>, and pecans <ns0:ref type='bibr' target='#b20'>(Brar et al., 2016)</ns0:ref>. Environmentally, Salmonella ser. Javiana has been isolated from surface water and sediment <ns0:ref type='bibr' target='#b14'>(Bell et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b84'>Li et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b89'>Micallef et al., 2012)</ns0:ref>, poultry farms <ns0:ref type='bibr' target='#b58'>(Gama et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b103'>Rodriguez et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b109'>Santos et al., 2007)</ns0:ref>, dairy and livestock farms <ns0:ref type='bibr' target='#b3'>(Adesiyun et al., 1996;</ns0:ref><ns0:ref type='bibr' target='#b96'>Oliveira et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b103'>Rodriguez et al., 2006)</ns0:ref>, irrigation water <ns0:ref type='bibr' target='#b44'>(Duffy et al., 2005)</ns0:ref>, and packing shed equipment surfaces <ns0:ref type='bibr' target='#b44'>(Duffy et al., 2005)</ns0:ref>. It has also been recovered from wildlife <ns0:ref type='bibr' target='#b43'>(Drake et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b62'>Gruszynski et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b87'>Lockhart et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b92'>Miller et al., 2014)</ns0:ref>, pets <ns0:ref type='bibr' target='#b2'>(Adesiyun et al., 1997;</ns0:ref><ns0:ref type='bibr' target='#b78'>Leahy et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b113'>Seepersadsingh et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b137'>Woodward et al., 1997)</ns0:ref>, and zoo animals <ns0:ref type='bibr' target='#b61'>(Gopee et al., 2000)</ns0:ref>. The diversity of animals found carrying Salmonella ser. Javiana includes amphibians <ns0:ref type='bibr' target='#b43'>(Drake et al., 2013)</ns0:ref>, reptiles <ns0:ref type='bibr' target='#b87'>(Lockhart et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b137'>Woodward et al., 1997)</ns0:ref>, birds <ns0:ref type='bibr' target='#b61'>(Gopee et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b62'>Gruszynski et al., 2014)</ns0:ref>, and mammals <ns0:ref type='bibr' target='#b2'>(Adesiyun et al., 1997;</ns0:ref><ns0:ref type='bibr' target='#b61'>Gopee et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b62'>Gruszynski et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b68'>Iveson &amp; Bradshaw, 1973;</ns0:ref><ns0:ref type='bibr' target='#b78'>Leahy et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b92'>Miller et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b113'>Seepersadsingh et al., 2004)</ns0:ref>. As Salmonella ser. Javiana has been isolated from and associated with contact with reptiles and amphibians, this may play a role in contamination of plant-based food commodities (Centers for Disease Control and Prevention (CDC), 2002; <ns0:ref type='bibr' target='#b36'>Clarkson et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b69'>Jackson et al., 2013)</ns0:ref>. A recently published systematic review identified the following risk factors associated with Salmonella ser. Javiana infection: consumption of fresh produce (tomatoes and watermelons), herbs (paprika-spice), dairy products (cheese), drinking contaminated well water, and animal contact <ns0:ref type='bibr' target='#b93'>(Mukherjee et al., 2019)</ns0:ref>. <ns0:ref type='bibr'>Clarkson, et al.</ns0:ref> found consumption of well water, reptile/amphibian contact, and exposure to recreational water associated with Salmonella ser. Javiana infection in GA and TN, but found consumption of tomatoes and poultry protective <ns0:ref type='bibr' target='#b36'>(Clarkson et al., 2010)</ns0:ref>.</ns0:p><ns0:p>Though antibiotics are generally not used to treat uncomplicated Salmonella infections, when necessary, antibiotics most commonly used include ampicillin (penicillin), chloramphenicol (phenicol), ciprofloxacin (fluoroquinolone), ceftriaxone (cephalosporin), trimethoprim-sulfamethoxazole (folate pathway inhibitor, sulfonamide), amoxicillin (penicillin), and azithromycin (macrolide) <ns0:ref type='bibr' target='#b39'>(Cuypers et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b48'>Eng et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b60'>Gilbert et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b72'>Jajere, 2019;</ns0:ref><ns0:ref type='bibr' target='#b116'>Shane et al., 2017)</ns0:ref>. The 2019 'Antibiotic Resistance Threats in the United States' report lists drug-resistant nontyphoidal Salmonella as a 'serious threat' and details increasing numbers of isolates ciprofloxacin nonsusceptible, ceftriaxone resistant, or with decreased susceptibility to azithromycin (Centers for Disease Control and Prevention (CDC), 2019a). From the National Antimicrobial Resistance Monitoring System (NARMS) Now Salmonella ser. Javiana human isolate data from 1996-2019 (Centers for Disease Control and Prevention (CDC), 2019b), the highest prevalences of phenotypic antibiotic resistance were to streptomycin (2.27%; aminoglycoside), ampicillin (1.39%), and tetracycline (1.05%). Resistance to amoxicillinclavulanic acid, cefoxitin (cephalosporin), ceftiofur (cephalosporin), ceftriaxone, cephalothin (cephalosporin), chloramphenicol, sulfamethoxazole/sulfisoxazole (sulfonamides), and trimethoprim-sulfamethoxazole were all less than 1% (Centers for Disease Control and Prevention (CDC), 2019b). Resistance to azithromycin or ciprofloxacin was not reported (Centers for Disease Control and Prevention (CDC), 2019b). Resistance among Salmonella ser. Javiana isolates may be lower due to the association with wild animal (e.g., reptile and amphibian) and other environmental reservoirs in contrast to food animal-associated serovars.</ns0:p><ns0:p>Though Salmonella ser. Javiana is a prevalent serotype in both the US and TN, little is known about the genomic population structure. The objectives of this study were to retrospectively study isolates of Salmonella ser. Javiana from patients in TN in 2017-2018 in order to identify epidemiologically-relevant trends, determine the genomic population structure, and describe the defining genomic features of major clades. Additionally, we studied expanded datasets representing global diversity to determine the overall population structure of Salmonella ser. Javiana and to compare it to other Salmonella serovars.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head><ns0:p>Sequencing, preprocessing, and genome assembly of TN isolates. BioSample numbers and metadata for Salmonella ser. Javiana (n=111) isolates from patients in TN from January 2017 through October 2018 were obtained from the Tennessee Department of Health (TDH) (Data S1). Tennessee population data (2018) used for calculating incidence rates (IR) wasobtained from the U.S. Census Bureau (U.S. Census Bureau) and IR per county were mapped using Tableau Desktop Public Edition (v2019.2.1) <ns0:ref type='bibr' target='#b126'>(Tableau Software, 2019)</ns0:ref>. PFGE and wholegenome sequencing were performed by the TDH Division of Laboratory Services according to PulseNet protocols (Centers for Disease Control and Prevention (CDC), 2016; Centers for Disease Control and Prevention (CDC), 2017b). For PFGE, XbaI was used as the primary restriction enzyme. Genomic DNA was extracted using Qiagen DNeasy Blood &amp; Tissue kits, libraries were prepared using Nextera XT kits, and sequencing was performed on an Illumina MiSeq platform using Illumina MiSeq v2 chemistry (500 cycle) to produce 250bp paired-end reads. Raw reads were downloaded from the NCBI SRA database, trimmed using Trimmomatic v0.35 <ns0:ref type='bibr' target='#b18'>(Bolger et al., 2014)</ns0:ref> (with the following parameters: ILLUMINACLIP: NexteraPE-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36), and quality checked using FastQC v0.11.7 <ns0:ref type='bibr' target='#b7'>(Andrews, 2010)</ns0:ref> and MultiQC v1.5 <ns0:ref type='bibr' target='#b51'>(Ewels et al., 2016)</ns0:ref> to combine the results. The trimmed reads were assembled into contigs using SPAdes v3.12.0 <ns0:ref type='bibr' target='#b12'>(Bankevich et al., 2012)</ns0:ref> with the careful option. Assembly statistics were generated by BBMap v38.88 <ns0:ref type='bibr' target='#b23'>(Bushnell, 2018</ns0:ref><ns0:ref type='bibr'>), SAMtools v0.1.8 (Li et al., 2009</ns0:ref><ns0:ref type='bibr'>), and QUAST v4.6.3 (Gurevich et al., 2013)</ns0:ref>. SeqSero <ns0:ref type='bibr' target='#b143'>(Zhang et al., 2015)</ns0:ref> was used to confirm serotype designations.</ns0:p><ns0:p>SNP Detection and phylogenetic analyses. A reference-free SNP detection analysis was initially performed with the TN isolates to determine the overall population structure free of reference choice bias. The assemblies were analyzed using KSNP3.1 <ns0:ref type='bibr'>(Gardner et al., 2015)</ns0:ref> and the resulting core SNP matrix fasta file was then used to construct a phylogenetic tree in Mega7 <ns0:ref type='bibr' target='#b77'>(Kumar et al., 2016)</ns0:ref> with 100 bootstrap replicates <ns0:ref type='bibr' target='#b52'>(Felsenstein, 1985)</ns0:ref>. The evolutionary distances were computed using the number of differences method <ns0:ref type='bibr' target='#b95'>(Nei &amp; Kumar, 2000)</ns0:ref> and the evolutionary history was inferred using the Neighbor-Joining method <ns0:ref type='bibr' target='#b105'>(Saitou &amp; Nei, 1987)</ns0:ref>. The final tree was visualized and annotated using iTOL <ns0:ref type='bibr' target='#b83'>(Letunic &amp; Bork, 2016)</ns0:ref>. Isolates that weren't serotype Javiana (based on SeqSero results) and were very divergent based on the KSNP analysis were removed from the analysis. Major clades (defined as groups of three or more isolates that were all within 500 SNPs of each other) were identified. Next, reference-based hqSNP analyses were performed for each TN clade independently to determine high-resolution SNP differences between isolates. For the hqSNP analyses, an appropriate internal reference genome assembly (with adequate assembly quality and expected assembly size and G+C content) for each clade was identified (SRS2420927 for TN clade I, SRS2822480 for TN clade II, and SRS3010019 for TN clade III). Additionally, the Salmonella enterica subsp. enterica serovar Javiana str. CFSAN001992 assembly (GCF_000341425.1) was downloaded from the NCBI RefSeq database for use as an external and closed reference genome. The hqSNP analyses were performed, both with the internal and external references and for the 111 isolates together and for each TN clade individually. For each analysis, high quality single nucleotide polymorphisms (hqSNPs) were identified using the CFSAN SNP Pipeline v1.0.1 <ns0:ref type='bibr' target='#b40'>(Davis et al., 2015)</ns0:ref>. The resulting hqSNP matrix fasta files were then used to construct phylogenetic trees as described above. The matrices were sorted and clustered using the hclust function (gtools package) in R studio. For the individual clade analyses using internal references, clusters of two or more related isolates were identified at hqSNP distance threshold levels of 5, 10 and 25; isolation date and other epidemiological information were not considered.</ns0:p><ns0:p>Genome annotation and pan-GWAS. TN isolate assemblies were annotated using Prokka v1.14-dev <ns0:ref type='bibr' target='#b112'>(Seemann, 2014)</ns0:ref> and RASTtk <ns0:ref type='bibr' target='#b21'>(Brettin et al., 2015)</ns0:ref>. A pangenome-wide association study (pan-GWAS) was performed to compare gene content among the isolates using Roary v3.12.0 (with Prokka annotation output files, previously described, used as input files) <ns0:ref type='bibr' target='#b97'>(Page et al., 2015)</ns0:ref> and statistical analysis was done using Scoary v1.6.16 (with the following arguments: -c I B BH PW EPW P -p 0.05 -e 100) <ns0:ref type='bibr' target='#b22'>(Brynildsrud et al., 2016)</ns0:ref> to identify genes or markers associated with inclusion in each clade. Genes predominantly present or absent among isolates in each clade were identified. Genes or clusters of genes (loci) were considered significantly associated with a clade or cluster if they had a Bonferroni-corrected P-value &lt;0.05. From the pan-GWAS, the positively and negatively associated genes were classified by having an Odds Ratio of &gt;1 and &lt;1, respectively. To further analyze the results in a genomic context, loci that were adjacent or located in close proximity were combined into a single region.</ns0:p><ns0:p>In silico Identification of genomic features and genes. Phage regions were identified in a diverse representative subset of the TN isolates (n=31) using Phaster <ns0:ref type='bibr' target='#b9'>(Arndt et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b146'>Zhou et al., 2011)</ns0:ref>. Potential plasmids were predicted and classified using PlasmidFinder v2.0.2 (database version 2019-05-16) <ns0:ref type='bibr' target='#b25'>(Carattoli et al., 2014)</ns0:ref>, Unicycler v0.4.8-beta <ns0:ref type='bibr' target='#b135'>(Wick et al., 2017)</ns0:ref>, and plasmidSPAdes <ns0:ref type='bibr' target='#b8'>(Antipov et al., 2016)</ns0:ref> and visualized using Bandage <ns0:ref type='bibr' target='#b136'>(Wick et al., 2015)</ns0:ref>. They were further confirmed by examining the associated assembly contigs for plasmidassociated genes, comparing to known plasmids using PLSDB <ns0:ref type='bibr' target='#b57'>(Galata et al., 2018)</ns0:ref> and BLASTn, and comparing coverage and G+C content to the whole assembly. Antibiotic resistance (ABR) determinants in genomes were predicted using ResFinder (90% threshold for identity and 60% for minimum length) <ns0:ref type='bibr' target='#b140'>(Zankari et al., 2012)</ns0:ref> to identify acquired ABR genes and PointFinder (90% threshold for identity and 60% for minimum length) <ns0:ref type='bibr' target='#b139'>(Zankari et al., 2017)</ns0:ref> to identify point mutations conferring ABR. The representative subset of the isolates (n=31) was also examined for virulence factors using VirulenceFinder <ns0:ref type='bibr' target='#b73'>(Joensen et al., 2014)</ns0:ref> and VFDB VFanalyzer <ns0:ref type='bibr' target='#b86'>(Liu et al., 2018)</ns0:ref> and Salmonella Pathogenicity Islands (SPIs) using SPIFinder (v1.0; 95% threshold for identity and 60% for minimum length) <ns0:ref type='bibr' target='#b104'>(Roer et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Global phylogenetic analysis. The Salmonella database <ns0:ref type='bibr' target='#b4'>(Alikhan et al., 2018)</ns0:ref> on EnteroBase <ns0:ref type='bibr' target='#b147'>(Zhou et al., 2019)</ns0:ref> was queried for isolates with 'human' listed as source niche in the strain metadata and 'Javiana' listed as serovar in the strain metadata or experimental data (SISTR1 <ns0:ref type='bibr' target='#b138'>(Yoshida et al., 2016)</ns0:ref> or SeqSero2 <ns0:ref type='bibr' target='#b142'>(Zhang et al., 2019a)</ns0:ref>). Only strains with country (and state for strains from the United States) included in the metadata were retained. A cgMLST + HierCC minimal spanning tree (RapidNJ algorithm) was created with GrapeTree <ns0:ref type='bibr' target='#b148'>(Zhou et al., 2018)</ns0:ref> on EnteroBase using all of the resulting strains. Strains that were likely not Javiana (conflicting serovar designations and distant on the tree) were removed from the dataset, leaving 466 strains (Data S2). The dataset was further refined to select representative strain(s) for each HC100 level cluster (&#61603;100 cgMLST allelic differences). For each HC100 cluster, a single strain from each country/state was retained. If there were more than one strain from a country/state, the representative strain was chosen based on assembly quality (N50; and if N50 values were identical or similar, coverage and number of contigs were also considered). At least one TN strain representing each HC100 cluster (if available) was chosen to be included in the final dataset of genomes representing global diversity of of Salmonella ser. Javiana clinical isolates. The final dataset consisted of 162 strains: 29 TN isolates (11 from TN clade I, 3 from TN clade II, 10 from TN clade III, and the five isolates that didn't fall into the main clades), 43 strains from other states in the US, and 90 isolates from other countries (Data S2). Collection date years ranged from 2002 to 2020. Assemblies for the non-TN strains were downloaded from Enterobase. All assemblies were analyzed using KSNP3.1 <ns0:ref type='bibr'>(Gardner et al., 2015)</ns0:ref> and the resulting core SNP matrix fasta file was then used to construct a phylogenetic tree in Mega7 <ns0:ref type='bibr' target='#b77'>(Kumar et al., 2016)</ns0:ref> with 100 bootstrap replicates <ns0:ref type='bibr' target='#b52'>(Felsenstein, 1985)</ns0:ref>. The evolutionary distances were computed using the number of differences method <ns0:ref type='bibr' target='#b95'>(Nei &amp; Kumar, 2000)</ns0:ref> and the evolutionary history was inferred using the Neighbor-Joining method <ns0:ref type='bibr' target='#b105'>(Saitou &amp; Nei, 1987)</ns0:ref>. The final tree was visualized and annotated using iTOL <ns0:ref type='bibr' target='#b83'>(Letunic &amp; Bork, 2016)</ns0:ref>.</ns0:p><ns0:p>Comparison to polyphyletic serovars. Eight strain datasets were created: one for serovar Javiana and one each for other serovars that have been reported as polyphyletic (Derby, Kentucky, Mississippi, Montevideo, Newport, Saintpaul, and Senftenberg). The Salmonella database <ns0:ref type='bibr' target='#b4'>(Alikhan et al., 2018)</ns0:ref> on EnteroBase <ns0:ref type='bibr' target='#b147'>(Zhou et al., 2019)</ns0:ref> was queried for isolates with the specified serovar listed as serovar in the experimental data (SISTR1 <ns0:ref type='bibr' target='#b138'>(Yoshida et al., 2016)</ns0:ref> or SeqSero2 <ns0:ref type='bibr' target='#b142'>(Zhang et al., 2019a)</ns0:ref>). For each, a cgMLST + HierCC minimal spanning tree (RapidNJ algorithm) was created. Strains that were likely not the serovar of interest (conflicting serovar designations and distant on the tree) were removed from the datasets. The final datasets (Data S3) were used to create cgMLST + HierCC minimal spanning trees (improved minimal spanning tree algorithm, MSTree V2) using GrapeTree <ns0:ref type='bibr' target='#b148'>(Zhou et al., 2018)</ns0:ref> on EnteroBase. The branch lengths between the cgMLST eBurstGroups (ceBGs) of the other polyphyletic serovars were used for comparison to the branch length between the two Javiana ceBGs. ceBG designations associated with each serovar were retrieved from the EnteroBase documentation (EnteroBase Team, 2018).</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Tennessee Salmonella ser. Javiana Population Structure. This analysis included a diverse set of 111 Salmonella ser. Javiana clinical isolates from TN (Data S1). On average, the assembled genomes from this study had 74.6x coverage, contained 71.7 contigs (34.8 contigs &#8805; 1 kb), were 46.45 kb in length, and had 52.11% GC content (Data S1). Based on the KSNPanalysis, the Salmonella ser. Javiana isolates from TN displayed a population structure with three main clades (Fig. <ns0:ref type='figure'>1</ns0:ref>). TN Clade I contained 54 isolates, TN clade II contained four, TN clade III contained 48 isolates, and five isolates didn't fall into the main clades (Fig. <ns0:ref type='figure'>1 and Table 1</ns0:ref>). Isolates in TN clades I, II, and III had average hqSNP distances of 119.4 (range 0 to 631), 210.3 (range <ns0:ref type='table'>3 to 396), and 66 (range 0 to 361), respectively (Table 1 and Data S4</ns0:ref>).</ns0:p><ns0:p>The 111 TN Salmonella ser. Javiana clinical isolates represented 47 different PFGE patterns (Fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref> High-quality single nucleotide polymorphism (hqSNP) analysis for cluster detection. Using a 5, 10, and 25 hqSNP distance threshold for cluster identification, 9, 12, and 10 potential clusters were identified, respectively (Data S4). The number of clusters decreases from thresholds of 10 to 25, as with the larger threshold, some of the clusters contain multiple subclusters identified at the lower threshold. Within TN clade I, five clusters were identified at each hqSNP distance thresholds of 5 and 10, and four clusters at 25 (Data S4). Only one cluster was identified at each of the distance thresholds for TN clade II (Data S4). Within TN clade III, three clusters were identified at a distance threshold of 5 hqSNPs, six clusters at 10 hqSNPs, and five clusters at hq25 SNPs (Data S4).</ns0:p><ns0:p>To evaluate the effects of reference choice and isolate diversity, we ran our hqSNP analyses on the entire TN dataset (111 isolates) and on the three clades individually and with both internal draft assemblies and an external closed assembly as reference genomes. When all isolates were analyzed together using different reference genomes, the average hqSNP distance was lowest when using the internal reference from TN clade I and highest when using the external closed genome and the average percentage of reads mapped differed by up to 1.57% (Table <ns0:ref type='table'>1 and Data S4</ns0:ref>). It should be noted that the closed external reference assembly we used (GCF_000341425.1) was most closely related to TN clade II in our original KSNP analysis (Fig. <ns0:ref type='figure'>1</ns0:ref>) and not representative of the overall population (at the time that this analysis was performed, there was only one closed Salmonella ser. Javiana genome available on NCBI RefSeq). For all three clades, regardless of the reference genome used, hqSNP distances were higher when they were analyzed independently, with the differences being only slightly higher for clades I and III. The average hqSNP distances for clades I and II were lower when using the internal references, but were slightly higher for TN clade III. For all three clades, the average percent reads mapped was higher when using the internal reference genome than the external reference genome, which is to be expected.</ns0:p><ns0:p>Epidemiological Trends. The TN Salmonella ser. Javiana isolates were sourced from patients with an average of 40.0 (range of 1 month to 90 years; standard deviation of 29.1). The highest incidence was in patients &#8804;4 (6.64 per 100,000) and &#8805;85 (4.16) years-old. Previous studies have reported that Salmonella ser. Javiana infections are more prevalent in infants and young children than for other serovars <ns0:ref type='bibr' target='#b74'>(Jones et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b118'>Shaw et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b122'>Srikantiah et al., 2004)</ns0:ref>. Overall, 51.4% of isolates were from male patients (incidence of 1.73) and 46.8% from female (incidence of 1.50; Table <ns0:ref type='table'>2</ns0:ref>). TN clades I and II contained more isolates from male patients than female, 57.4% and 75%, respectively. Conversely, 52.1% of TN clade III isolates were from female patients.</ns0:p><ns0:p>Most of the TN Salmonella ser. Javiana isolates were taken from stool samples (84.7%, n=94), followed by urine (6.3%, n=7) and blood (5.4%, n=6) (Table <ns0:ref type='table'>2</ns0:ref>). The portion of isolates taken from blood samples exceeds the 2.8% invasive disease outcome (defined by isolation from blood, cerebrospinal fluid, bone or joint fluid, or another sterile site; does not include urine, wound, abscess cultures) reported for this serovar in FoodNet states <ns0:ref type='bibr' target='#b74'>(Jones et al., 2008)</ns0:ref>. Of the urine isolates, most (n=6) belonged to TN clade III and all were from females, with an average patient age of 55.1 (standard deviation of 26.2). All of the isolates recovered from blood samples belonged to TN clades I (n=3) and III (n=3) and most were from males (n=4), with an average patient age of 71.8 (standard deviation of 15.2). The majority of isolates recovered from extraintestinal sites were collected from elderly patients, which may indicate a correlation between invasive infection and age.</ns0:p><ns0:p>Geographical and Temporal Distribution. A geographical distribution can be seen for the TN isolates, with 65.8% (n=73) isolated in counties in the western region of TN (Table <ns0:ref type='table'>2</ns0:ref>; Data S1). In contrast, only 17.1% (n=19) and 16.2% (n=18) were isolated in counties in east and middle TN, respectively. Incorporating county population data, the west region had an IR of 4.69 clinical isolates per 100,000 population, while the east had an IR of 0.79 and the middle had an IR of 0.64, with an overall IR of 1.62 per 100,000 for the state (Fig. <ns0:ref type='figure' target='#fig_2'>S2</ns0:ref>). Three counties had noticeably higher IR: Madison with 31.0, Crockett with 27.9, and Carroll with 25.0. As was the trend for all isolates, the majority of TN clade I and III isolates originated in the west region (59.3% and 83.3%, respectively; Table <ns0:ref type='table'>2</ns0:ref>). However, a sizable amount of TN clade I isolates also originated in the east region (25.9%). Additionally, a temporal distribution was also clear, with 68.5% (n=76) of isolates collected in July through September (Table <ns0:ref type='table'>2</ns0:ref>; Data S1). This trend was also seen within the three TN clades.</ns0:p><ns0:p>Identification of Mobile Genetic Elements (MGEs). All of the TN isolates were examined for plasmids and 32 putative plasmids (19 unique) were identified in 30 isolates (Table <ns0:ref type='table'>3</ns0:ref>). They ranged in size from 23 to 108 kb and included replicon types (a plasmid typing scheme based on replication control regions <ns0:ref type='bibr' target='#b25'>(Carattoli et al., 2014)</ns0:ref> Most identified virulence genes were present in all of the TN isolates analyzed (Data S6), including the three genes (cdtB, pltA, and pltB) encoding the subunits of the cytolethal distending toxin (CDT) <ns0:ref type='bibr' target='#b90'>(Miller et al., 2018)</ns0:ref>. Only the TN clade II isolates contained the pefC and pefD genes, which were on plasmid-associated contigs, that are part of the pef (plasmid-encoded fimbriae) operon and associated with fimbrial adherence <ns0:ref type='bibr' target='#b13'>(B&#228;umler et al., 1996)</ns0:ref>. Some of the isolates (two from TN clade I and three that were not part of a clade) contained genes from the saf (Salmonella atypical fimbria) operon on putative plasmid-associated contigs <ns0:ref type='bibr' target='#b54'>(Folkesson et al., 1999)</ns0:ref>. One isolate (SRS2442415, no clade) contained 11 genes associated with the yersiniabactin iron uptake system on a plasmid-associated contig <ns0:ref type='bibr' target='#b26'>(Carniel, 2001)</ns0:ref>.</ns0:p><ns0:p>Identification of Antibiotic Resistance Genes. All 111 TN Salmonella ser. Javiana isolates analyzed in the present study contained the aac(6')-Iaa gene, which has been previously reported to confer aminoglycoside resistance <ns0:ref type='bibr' target='#b117'>(Shaw et al., 1993)</ns0:ref>. One isolate (SRS2783476; TN clade I) contained the aph(3')-Ia and sul3 genes on a contig (contig 32) that associated with a putative plasmid. The aph(3')-Ia gene has been found to confer resistance to aminoglycosides <ns0:ref type='bibr' target='#b117'>(Shaw et al., 1993)</ns0:ref> and sul3 gene has been shown to confer resistance to sulfonamides/sulfones through antibiotic target replacement and has been shown to be associated with resistance to sulfamethoxazole <ns0:ref type='bibr' target='#b98'>(Perreten &amp; Boerlin, 2003)</ns0:ref>.</ns0:p><ns0:p>Additionally, one isolate (SRS2628542; no clade) contained the qnrB19 gene, which has been shown to confer resistance to fluoroquinolones through physical protection of the antibiotic target <ns0:ref type='bibr' target='#b37'>(Correia et al., 2017)</ns0:ref>. The qnr gene is plasmid-associated and has been linked with reduced susceptibility to ciprofloxacin <ns0:ref type='bibr' target='#b27'>(Casas et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b38'>Crump et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b102'>Redgrave et al., 2014)</ns0:ref>. It is unclear if this gene in SRS2628542 is on a plasmid, as it is located on a small (703 bp) contig and no plasmids were predicted in this isolate. However, the gene showed 100% identity over only 72.6% of the alignment with the reference gene (accession EU432277), so it may not be functionally capable of conferring the quinolone resistance phenotype.</ns0:p><ns0:p>Clade-Enriched Genes. A pangenome analysis of the TN isolates revealed that the core genome (genes contained in &#61619;99% of isolates) consisted of 4,022 genes and the accessory genome consisted of 3,920 genes (Table <ns0:ref type='table'>1</ns0:ref>). The difference in gene content between the identified clades were mostly found in mobile genetic elements (91.5%).</ns0:p><ns0:p>TN clade I isolates had a core genome of 4,106 genes and an accessory genome of 2,513 genes (Table <ns0:ref type='table'>1</ns0:ref>). This clade has a much larger accessory genome than the other two clades identified in this study. This is likely due to the large variety of mobile genetic elements (i.e., plasmids, prophages) present in isolates from this clade, which is also reflected in the much larger number of PFGE patterns (n=28) displayed by these isolates as compared to other clades (n=3 for TN clade II and n=11 for TN clade III). The pan-GWAS revealed 153 loci (genes or groups of genes) to be significantly associated with inclusion in this clade (54 positively associated and 99 negatively associated) (Table <ns0:ref type='table'>1 and Data S7</ns0:ref>). These loci consisted of 338 total genes (94 positively associated and 243 negatively associated) (Table <ns0:ref type='table'>1</ns0:ref>). The positively associated loci are found in 29 distinct genomic regions and the majority of the genes overrepresented in TN clade I (73 genes) were located in eight prophage regions (Table <ns0:ref type='table'>4</ns0:ref>).</ns0:p><ns0:p>Twelve of the overrepresented genes in TN clade I correspond to pathogenicity-related protein families (as identified by PathogenFinder): DNA damage-inducible protein I, phenolic acid decarboxylase subunit D, small toxic polypeptide LdrD, PTS system fructose-specific EIIB'BC component, PTS system mannose/fructose/sorbose family IID component, prepilin peptidase dependent protein A precursor, phage DNA binding protein, and other hypothetical proteins. Overexpression of ldrD, which is part of a chromosomal toxin-antitoxin gene system <ns0:ref type='bibr' target='#b5'>(Alix &amp; Blanc-Potard, 2009;</ns0:ref><ns0:ref type='bibr' target='#b76'>Kawano et al., 2002)</ns0:ref>, is toxic to the cell and leads to growth inhibition and rapid cell killing <ns0:ref type='bibr' target='#b56'>(Fozo et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b76'>Kawano et al., 2002)</ns0:ref>. ldrD homologs have not been found in plasmids, but may be involved in cellular response to environmental stress <ns0:ref type='bibr' target='#b76'>(Kawano et al., 2002)</ns0:ref>. Prepilin peptidase dependent protein A precursor is known to be plasmidassociated <ns0:ref type='bibr' target='#b100'>(Raspoet et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b141'>Zhang et al., 1994)</ns0:ref> and is involved in processing of the major pilus subunit <ns0:ref type='bibr' target='#b53'>(Filloux et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b141'>Zhang et al., 1994)</ns0:ref>. Other genes of interest enriched in isolates from TN clade I include those encoding autotransporter adhesin SadA, which is associated with pathogenesis, and virulence protein MsgA, which is involved with survival within macrophage <ns0:ref type='bibr' target='#b120'>(Skyberg et al., 2006)</ns0:ref>. Mezal, et al. identified msgA virulence gene in 7 (out of 50) Salmonella ser. Javiana isolates, all of which were clinical <ns0:ref type='bibr' target='#b88'>(Mezal et al., 2013)</ns0:ref>.</ns0:p><ns0:p>TN clade II isolates had a core genome of 4,290 genes and an accessory genome of 322 genes (Table <ns0:ref type='table'>1</ns0:ref>). The pan-GWAS revealed 22 loci to be significantly associated with inclusion in this clade (16 positively associated and 6 negatively associated) (Table <ns0:ref type='table'>1 and Data S7</ns0:ref>). These loci consisted of 221 total genes (207 positively associated and 14 negatively associated) (Table <ns0:ref type='table'>1</ns0:ref>). The positively associated loci are found in 17 distinct genomic regions and many of the genes over-represented in TN clade II (93 genes) were located in the 87.5 kb IncFII type plasmid identified in SRS2922480 (Table <ns0:ref type='table'>4</ns0:ref> and Fig. <ns0:ref type='figure' target='#fig_3'>S3</ns0:ref>). Among the over-represented genes contained on this plasmid are ccdAB, which are part of a toxin/antitoxin system. This system contributes to stability of the plasmid through post-segregational killing (killing new cells that do not inherit a plasmid copy during cell division) <ns0:ref type='bibr' target='#b131'>(Van Melderen, 2001)</ns0:ref>. Additionally, 72 over-represented genes were located in four predicted prophage regions and 33 in three other potential MGE regions (indicated by gene annotations, clustering of genes, and/or close proximity to predicted prophage regions; Table <ns0:ref type='table'>4</ns0:ref>). One of the overrepresented genes, alpha-xylosidase, corresponds to a pathogenicity-related protein family (as identified by PathogenFinder). VFDB identified pefC and pefD, fimbrial adherence determinants, on the plasmid (contig 13); sinH, a nonfrimbrial adherence determinant; and pipB, a TTSS-2 translocated effector.</ns0:p><ns0:p>TN clade III isolates had a core genome of 4,115 genes and an accessory genome of 889 genes (Table <ns0:ref type='table'>1</ns0:ref>). The pan-GWAS revealed 155 loci to be significantly associated with inclusion in this clade (101 positively associated and 54 negatively associated) (Table <ns0:ref type='table'>1 and Data S7</ns0:ref>). These groups contained 332 total genes (238 positively associated and 94 negatively associated) (Table <ns0:ref type='table'>1</ns0:ref>). The positively associated loci are found in 29 distinct genomic regions and the majority of the genes over-represented in TN clade III were located in four predicted prophage regions (88 genes) or nine other putative MGE regions (134 genes) (Table <ns0:ref type='table'>4</ns0:ref>). Four of the overrepresented genes correspond to pathogenicity-related protein families (as identified by PathogenFinder): arginine/lysine/ornithine decarboxylase) and other hypothetical proteins.</ns0:p><ns0:p>Global Population Structure. The KSNP analysis of the diverse set of global clinical Salmonella ser. Javiana strains revealed three major clades (Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>; Figure <ns0:ref type='figure'>S1</ns0:ref>). Major clade I contained 107 strains, including TN isolates (from TN clades I, II, and III and the five isolates that didn't fall into the main clades). Major clade II contained 23 strains and major clade III contained 31 strains. Strains from major clades I and II belong to the 590 cgMLST eBurstGroup (ceBG) and strains from major clade III belong to the 204 ceBG; both of these are associated with this serovar <ns0:ref type='bibr'>(EnteroBase Team, 2018)</ns0:ref>.</ns0:p><ns0:p>To further explore if Salmonella ser. Javiana is polyphyletic, we constructed minimal spanning trees based on cgMLST allele distances of all available Salmonella ser. Javiana strains and of other Salmonella serovars previously described as polyphyletic (Derby, Kentucky, <ns0:ref type='bibr'>Mississippi, Montevideo, Newport, Saintpaul, and Senftenberg (Achtman et al., 2012;</ns0:ref><ns0:ref type='bibr'>Alikhan et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b11'>Banerji et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b24'>Cao et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b108'>Sangal et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b114'>S&#233;vellec et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b127'>Tang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b128'>Timme et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b133'>Vosik et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b144'>Zhang et al., 2019b</ns0:ref>)) (Figure <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>; Figure <ns0:ref type='figure' target='#fig_2'>S2</ns0:ref>). The branch length between the two ecBG clusters on the ser. Javiana tree was 1,423 allelic differences. The branch lengths between ecBG clusters on the other trees ranged from 2,280-2,769 allelic differences for ser. Derby, 2,452-2,756 for ser. Kentucky, 929-2,850 for ser.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The main objective of this study was to use WGS data to retrospectively examine the population structure of Salmonella ser. Javiana, both from a local (state of TN) and global perspective. The phylogenetic analysis of the 111 Salmonella ser. Javiana isolates from TN revealed a population structure with three main clades, with the majority of isolates found in TN clades I and III. Research published on the population structure of this serovar is limited. One comparable study, conducted by <ns0:ref type='bibr'>Mezal, et al., used PFGE</ns0:ref> to assess the relatedness of 50 Salmonella ser. Javiana isolates from food, environmental, and clinical sources. They found that the isolates represented 34 distinct PFGE patterns and grouped into five clusters of two or more isolates; the 30 clinical isolates represented 23 distinct PFGE patterns (compared to the 111 TN clinical isolates in the present study representing 47 distinct PFGE patterns) and spanned all five clusters. The diversity of PFGE isolates suggested that differences in genome content between Salmonella ser. Javiana isolates is common. In this study, we found that differences in gene content between the TN clades were mostly attributed to mobile genetic elements (i.e., prophage regions and plasmids), with TN clade I exhibiting the highest level of accessory genome diversity.</ns0:p><ns0:p>The phylogenetic analysis of the diverse set of global clinical Salmonella ser. Javiana strains revealed three major clades (Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>; Figure <ns0:ref type='figure'>S1</ns0:ref>). Major clade I contained most of the strains, including all of the TN isolates. This indicates that the population of this serovar in TN represents only a portion of the global genomic diversity. Strains from major clades I and II belong to the 590 cgMLST eBurstGroup (ceBG) and strains from major clade III belong to the 204 ceBG. ceBGs are equivalent to eBurstGroups (eBGs; in legacy 7-gene MLST), which have been shown to correspond to serovar designations <ns0:ref type='bibr'>(EnteroBase Team, 2018;</ns0:ref><ns0:ref type='bibr' target='#b147'>Zhou et al., 2019)</ns0:ref>. Typically, monophyletic serovar isolates will belong to a single eBG, while polyphyletic serovar isolates will belong to multiple eBGs <ns0:ref type='bibr' target='#b1'>(Achtman et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b4'>Alikhan et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b11'>Banerji et al., 2020)</ns0:ref>.The observation that the global clinical Salmonella ser. Javiana isolates consisted of multiple major clusters and two ceBGs suggests that this serovar may be polyphyletic. <ns0:ref type='bibr'>Ashton, et al. characterized</ns0:ref> serovars in lineage 3 of S. enterica subspecies I (which includes serovars Bredeney, Chester, Javiana, Montevideo, Oranienburg, and Poona) as polyphyletic and containing multiple eBGs <ns0:ref type='bibr' target='#b10'>(Ashton et al., 2016)</ns0:ref>. The branch length between the two ecBG clusters on the ser. Javiana tree (1,423 allelic differences) was comparable to the branch lengths between ecBGs on the other serovar trees (929-2,850 allelic differences) (Figure <ns0:ref type='figure' target='#fig_4'>4</ns0:ref> and Figure <ns0:ref type='figure' target='#fig_2'>S2</ns0:ref>). Based on this comparison, Salmonella ser. Javiana may be considered a polyphyletic serovar, although this depends on the branch length cutoff that is applied.</ns0:p><ns0:p>As WGS is becoming more commonly used for public health applications (e.g., cluster detection and outbreak investigation), it is important to understand genomic population structure of surveilled disease-causing microorganisms, specifically at the serovar level for Salmonella. Genomic distance thresholds (based on hqSNP or allelic distances) are an important factor used for identifying potential disease clusters of public health importance, but other factors are typically considered, including isolation date, number of isolates, and epidemiological data. In the present study, we found that using different hqSNP distance thresholds for cluster identification resulted in different numbers of potential clusters and associated isolates (Data S4). The selected threshold for cluster detection should be empirically determined so that it is larger than typical inter-genomic distances between outbreak strains, but smaller than typical inter-genomic distances between outbreak and background (non-outbreak) isolates. Intergenomic SNP distances among Salmonella outbreak strains are typically small (in the 2 to 12 SNP range), but in some cases can be quite large (up to 249 SNPs) and likely vary from serovar to serovar <ns0:ref type='bibr' target='#b80'>(Leekitcharoenphon et al., 2014)</ns0:ref>. Thresholds can have impacts on epidemiological investigations; if they are set too low, isolates belonging to the same outbreak event may be mistakenly excluded from the cluster or separated into different clusters and, if they are set too high, background isolates may be inadvertently included in the cluster, making epidemiological investigations difficult, particularly source attribution. In the present study, as the hqSNP distance threshold was increased, the number of included isolates also increased. Increases in numbers and/or sizes of potential clusters may impact the ability of public health departments to further investigate them due to resource constraints. Thresholds may also need to be adjusted based on the timeline of the suspected outbreak (lower for short-term and higher for prolonged outbreaks). As we move forward with using WGS for routine surveillance and cluster detection of this serovar, more clusters may be successfully detected and investigated. In turn, this will provide information on typical genomic distances that can be used to establish and evaluate an appropriate serovar-specific threshold for cluster detection.</ns0:p><ns0:p>Another important consideration when using hqSNP calling analyses for epidemiological cluster detection is whether polyphyletic serovars or those with genetically diverse clades should be analyzed together or if each clade should be analyzed independently. An additional consideration is the choice of reference genome. These choices can affect the percentage of reads mapped to the reference genome and, in turn, the results of the analysis (primarily, hqSNP distances). Better performance (i.e., higher read mapping) would be expected when using closed genomes as references for hqSNP calling. However, some research has shown that using closed vs draft genomes as references have limited impact on hqSNP calling phylogeny reconstruction <ns0:ref type='bibr' target='#b71'>(Jagadeesan et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b99'>Portmann et al., 2018)</ns0:ref>. In the current study, we still achieved a level of high-quality mapping (&gt;95%, as recommended by <ns0:ref type='bibr' target='#b75'>(Katz et al., 2017)</ns0:ref>; Table <ns0:ref type='table'>1</ns0:ref>) when using draft genomes as references. As these types of studies are performed, representatives from each clade should be selected for long-read sequencing to establish high quality reference genomes that can be used to further evaluate hqSNP distances. Additionally, when analyzing the TN isolates together or each clade separately and with internal or external reference genomes, similar levels of performance were achieved. This is likely due to the lack of diversity in the core genome of the isolates and the fact that the majority of the gene content differences between isolates from each clade were attributed to MGEs (plasmids and prophage regions). Commonly used hqSNP pipelines filter out SNPs that are found in close proximity and/or mask phage regions <ns0:ref type='bibr' target='#b75'>(Katz et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b123'>Strain et al.)</ns0:ref> and only SNPs present in genomic regions shared between isolates and the reference genome are identified in the analysis.</ns0:p><ns0:p>Notable geographical and temporal patterns were observed for the Salmonella ser. Javiana isolates from TN. The geographical distribution within the state (most isolates from patients in counties in the western region; Table <ns0:ref type='table'>2 and Figure S3</ns0:ref>) is consistent with other reported data (Centers for Disease Control and Prevention (CDC), 2013; <ns0:ref type='bibr' target='#b94'>Mukherjee et al., 2020)</ns0:ref>. This geographical distribution may be associated with the higher percentage of fresh forested/scrub-shrub wetlands in these west TN counties <ns0:ref type='bibr' target='#b67'>(Huang et al., 2017)</ns0:ref>. A similar geographical distribution has been described in GA, with Salmonella ser. Javiana cases occurring more frequently in the southern part of state <ns0:ref type='bibr' target='#b36'>(Clarkson et al., 2010)</ns0:ref>. Despite this, Harris, et al. were unable to isolate Salmonella ser. Javiana from storm runoff or irrigation ponds used by fresh produce growers in South Georgia even though this is a high incidence area <ns0:ref type='bibr' target='#b65'>(Harris et al., 2018)</ns0:ref>. The temporal distribution (most isolates collected July-September; Table <ns0:ref type='table'>2</ns0:ref>) is in accordance with the notable seasonality of this serovar reported elsewhere <ns0:ref type='bibr' target='#b36'>(Clarkson et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b122'>Srikantiah et al., 2004)</ns0:ref>.</ns0:p><ns0:p>Salmonella virulence factors aid in host colonization and pathogenicity by assisting the pathogen in attaching to, invading, and replicating within host cells, intra-and extracellular survival, evading host defenses, and outcompeting the gut microbiome and include adhesion systems, capsule, flagella, and toxins <ns0:ref type='bibr' target='#b72'>(Jajere, 2019)</ns0:ref>. Virulence factors and related genes are frequently clustered together in pathogenicity islands, which are often found on mobile genetic elements (MGEs), such as plasmids and prophages <ns0:ref type='bibr' target='#b35'>(Cheng et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b70'>Jacobsen et al., 2011)</ns0:ref>. Eight Salmonella Pathogenicity Islands (SPIs) or islets (SPI-1, SPI-2, SPI-4, SPI-5, SPI-9, SPI-11, SPI-12 and CS54) are commonly found in most non-typhoidal serovars (den <ns0:ref type='bibr' target='#b41'>Bakker et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b70'>Jacobsen et al., 2011)</ns0:ref>. All of the representative subset of TN isolates analyzed for SPIs contained C63PI, SPI-13, and SPI-14 (Data S6). C63PI, which is located within SPI-1, contains the sit operon that encodes an iron uptake system <ns0:ref type='bibr' target='#b111'>(Schmidt &amp; Hensel, 2004;</ns0:ref><ns0:ref type='bibr' target='#b145'>Zhou et al., 1999)</ns0:ref>. SPI-13 has been associated with macrophage internalization and virulence in chickens and mice <ns0:ref type='bibr' target='#b35'>(Cheng et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b45'>Elder et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b50'>Espinoza et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b115'>Shah et al., 2005)</ns0:ref>. SPI-14 is involved in epithelial invasion and pathogenicity in chickens <ns0:ref type='bibr' target='#b35'>(Cheng et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b55'>Fookes et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b115'>Shah et al., 2005)</ns0:ref>. Most of the representative subset of TN isolates analyzed for SPI contained SPI-2 and SPI-4. SPI-2 encodes a type III secretion system 1 (TTSS-2), which is involved in intracellular survival and replication, immune evasion, and systemic pathogenicity <ns0:ref type='bibr' target='#b111'>(Schmidt &amp; Hensel, 2004;</ns0:ref><ns0:ref type='bibr' target='#b130'>Tsai &amp; Coombes, 2019)</ns0:ref>, replication within macrophages, and systemic infections <ns0:ref type='bibr' target='#b72'>(Jajere, 2019)</ns0:ref>. SPI-4 encodes genes for toxin secretion and apoptosis and is involved in intracellular (macrophage) survival <ns0:ref type='bibr' target='#b72'>(Jajere, 2019)</ns0:ref>. All three genes associated with the cytolethal distending toxin were identified all of the representative subset of TN isolates, which is in agreement with other studies that have identified these three genes in all Salmonella ser. Javiana isolates tested <ns0:ref type='bibr' target='#b88'>(Mezal et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b91'>Miller &amp; Wiedmann, 2016)</ns0:ref>. Other virulence genes that differed among isolates were mainly associated with mobile genetic elements.</ns0:p><ns0:p>All 111 TN Salmonella ser. Javiana isolates analyzed in the present study contained the aac(6')-Iaa gene, which is associated with aminoglycoside resistance <ns0:ref type='bibr' target='#b117'>(Shaw et al., 1993)</ns0:ref>. However, there is evidence that this gene is cryptic and no longer confers phenotypic aminoglycoside resistance <ns0:ref type='bibr' target='#b82'>(Leon et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b106'>Salipante &amp; Hall, 2003)</ns0:ref>, which is consistent with the low prevalence of phenotypic resistance to amikacin and gentamicin (0.04%) in U.S. clinical Salmonella ser. Javiana isolates (Centers for Disease Control and Prevention (CDC), 2019b). Taken together, these findings highlight the complexity of antimicrobial resistance. The three other antibiotic resistance genes identified in this study (aph(3')-Ia, sul3, and qnrB19 gene) were each only present in a single isolate. The low prevalence of these three genes is consistent with the low phenotypic prevalence of resistance to gentamicin and kanamycin (0.12%), sulfamethoxazole/sulfisoxazole (0.63%), trimethoprim-sulfamethoxazole (0.21%), and ciprofloxacin (0%) seen in U.S. clinical Salmonella ser. Javiana isolates (Centers for Disease Control and Prevention (CDC), 2019b). Additionally, The hypothesis that the qnrB19 gene may not be functional is further supported by the fact that phenotypic ciprofloxacin resistance has not been reported in Salmonella ser. Javiana clinical isolates (Centers for Disease Control and Prevention (CDC), 2019b). As aminoglycosides are not typically used to treat Salmonella infections, the presence of the aac(6')-Iaa and aph(3')-Ia genes is of little clinical significance. Overall, these data show a low prevalence of genes associated antibiotic resistance in Salmonella ser. Javiana from TN. However, antibiotic susceptibility testing would need to be performed on these isolates to confirm.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study demonstrates the population structure of Salmonella ser. Javiana in Tennessee and globally. As this is a clinically important Salmonella serotype, understanding the phylogeny can provide guidance for phylogenetic analyses and cluster detection for public health surveillance and response. We show that Salmonella ser. Javiana clinical isolates from TN show geospatial and temporal distribution, with most isolates originating from the western part of the state and during the summer months (July, August, and September). Based on the results of the pan-GWAS, it is clear that MGEs (namely plasmids and prophage regions) in the genome account for most of the differences in gene content between the three main clades of this serovar. This is noteworthy, as clinically-relevant genes (like ABR-conferring or virulence-related genes) can be found in these regions and they could potentially be used for isolate characterization.</ns0:p><ns0:p>Additionally, we found that when performing hqSNP analysis for epidemiological cluster detection with the TN isolates, it is not necessary to first divide the isolates into clades, as we found this only minimally increases the SNP differences between isolates; however the TN isolates all belonged to a single lineage, so this may only be applicable to less diverse populations. Further research should include clinical Salmonella ser. Javiana isolates and associated metadata from other states to obtain a more complete representation of the population structure of and epidemiological information about Salmonella ser. Javiana in the United States and an analysis of disease severity and gene content could assist in the identification of genes that may be involved in virulence. Another research direction would be to include isolates from other sources (i.e., environmental, animal, food) in a phylogenetic analysis, which may expand our understanding of the population structure and including isolates with diverse isolation sources may provide insight into source attribution and potential recommendations to prevent morbidity.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>Unrooted neighbor-joining KSNP tree of Tennessee clinical Salmonella ser. Javiana isolates.</ns0:p><ns0:p>Tree was constructed based on core SNPs determined by KSNP3 <ns0:ref type='bibr'>(Gardner et al., 2015)</ns0:ref>. The optimal tree with the sum of branch length of 5,916.1 is shown. TN clades I (highlighted in purple), II (green), and III (blue) are indicated. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test are indicated below branches. The tree is drawn to scale, with branch lengths (above branches) representing the number of base differences at core SNP positions per isolate (SNP distance). The analysis involved 112 isolates and 5,870 total SNP positions. Tree was constructed based on core SNPs determined by KSNP3 <ns0:ref type='bibr'>(Gardner et al., 2015)</ns0:ref>. The optimal tree with the sum of branch length of 31,777.6 is shown. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test that are &#8804;0.8 are represented by branch color (maximum as green, midpoint as yellow, and minimum as red).</ns0:p><ns0:p>The tree is drawn to scale, with branch lengths (above branches) representing the number of base differences at core SNP positions per isolate (SNP distance). The analysis involved 161 isolates and 30,657 total SNP positions. The three major clades are labeled. HC900 (ceBG) clusters are indicated (590 is not shaded and 204 is shaded in gray). TN isolates belonging to TN clades I, II, and III from our original analysis (Fig. <ns0:ref type='figure'>1</ns0:ref>) are highlighted in purple, green, and blue, respectively. A standard tree with additional metadata can be found in the supplemental files (Figure <ns0:ref type='figure'>S1</ns0:ref>). Table <ns0:ref type='table'>1</ns0:ref>. Tennessee Clade Statistics and Details Tennessee clade statistics and details for all isolates and individual clades, including number of isolates, hqSNP analyses details and statistics (reference genome used, mean hqSNP distance and range, and mean percent reads mapped and range), core and accessory genomes as determined by Roary <ns0:ref type='bibr' target='#b97'>(Page et al., 2015)</ns0:ref>, and loci associated with inclusion in each clade as determined by Scoary <ns0:ref type='bibr' target='#b22'>(Brynildsrud et al., 2016)</ns0:ref>. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>; Data S1). The most common PFGE patterns were JGGX01.0012 (n=18), JGGX01.0065 (n=17), and JGGX01.0072 (n=10). TN clade I isolates represented 28 different PFGE patterns, with the most common being JGGX01.0012 (n=18). TN clade II isolates represented three different PFGE patterns. TN clade III isolates represented 11 different PFGE patterns, with the most common being JGGX01.0065 (n=17) and JGGX01.0072 (n=10). Each of the five isolates that did not belong to a clade had a distinct PFGE pattern. All PFGE patterns were unique to only one TN clade.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>) IncFIB, IncFII, IncI1, IncN3, and IncX4. In the representative subset of TN isolates (n=31), Phaster predicted an average of 8.90 [range of 5-13] prophage regions per isolate (2.29 intact, 4.94 incomplete, and 1.68 questionable) (Data S5). The TN clade I isolates had the highest number of predicted prophage regions (average of 9.64 and range of 8-11), followed by TN clade II (average of 8.25 and range of 8-9) and TN clade III (average of 8.09 and range of 5-10). Identification of Virulence Factors and Pathogenicity Islands. All of the representative subset of TN isolates (n=31) contained pathogenicity islands C63PI, SPI-13, and SPI-14 (Data S6). Most of the TN isolates examined contained SPI-2 (except for SRS2442409 [TN clade II] and SRS2998834 [TN clade III]) and SPI-4 (except SRS3453943 [TN clade I], SRS3643364 [TN clade III], and SRS2998834 [TN clade III]).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>reviewed a Reference Isolate: (a) SRS2420927, (b) SRS2628565, (c) SRS2822480, (d) SRS3010019, (e) SRS3643364, (f) SRS3721796, (g) SRS3799118 b MGE Region: Prophage (PP), Putative mobile genetic element (MGE), Plasmid (PL) PeerJ reviewing PDF | (2020:05:49215:1:1:NEW 9 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='33,42.52,70.87,525.00,399.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='37,42.52,70.87,525.00,514.50' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49215:1:1:NEW 9 Sep 2020)</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell cols='2'>hqSNP Analysis</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='2'>Clade</ns0:cell><ns0:cell /><ns0:cell>No. Isolates</ns0:cell><ns0:cell>Reference</ns0:cell><ns0:cell /><ns0:cell cols='3'>Avg hqSNP distance [range] analyzed together analyzed separately 66,512</ns0:cell><ns0:cell>Reads Mapped (%) [range] 66,652</ns0:cell><ns0:cell>Core Genome (genes) d</ns0:cell><ns0:cell>Accessory Genome (genes) 2 77,581 No. of Loci a Significantly Associated with Inclusion [No. genes] 100,603 MGE No. of Significant Positively Associated Loci a [No. genes]</ns0:cell></ns0:row><ns0:row><ns0:cell>a</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell cols='2'>294,839 304,113</ns0:cell><ns0:cell>PP</ns0:cell><ns0:cell>c</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>134</ns0:cell><ns0:cell>2,179</ns0:cell><ns0:cell>d</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>560,052</ns0:cell><ns0:cell>571,035 MGE</ns0:cell></ns0:row><ns0:row><ns0:cell cols='2'>a a a a a Isolates All a a</ns0:cell><ns0:cell /><ns0:cell cols='3'>GCF_000341425.1 195,020 195,127 235,725 236,411 SRS2420927 269,009 270,619 335,429 335,854 SRS2822480 111 350,250 350,489 60,039 60,707 60,750 60,974</ns0:cell><ns0:cell>645.3 [0-1427] c c c 627.5 c [0-1416] 631.6 c c [0-1404]</ns0:cell><ns0:cell>7 7 9 9 13 18</ns0:cell><ns0:cell cols='2'>-125,002 125,955 96.14 [90.44-182,477 183,643 98.44] 96.91 79,782 80,006 -[90.35-99,100 99,297 99.70] -95.92 [90.35-158 87,203 PL 5,004 6,047 99.77]</ns0:cell><ns0:cell>d d d d 4,022 d d d</ns0:cell><ns0:cell>3 3 4 4 4 5 5</ns0:cell><ns0:cell>3,920</ns0:cell><ns0:cell>331,513 492,689 39 190,030 190,329 1,595 119,382</ns0:cell><ns0:cell>355,434 MGE 492,952 620 190,365 -190,424 7,589 MGE 120,038</ns0:cell><ns0:cell>-</ns0:cell></ns0:row><ns0:row><ns0:cell>a a</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>681 1,638</ns0:cell><ns0:cell cols='2'>SRS3010019 1,367 1,892</ns0:cell><ns0:cell>630.2 [0-1429</ns0:cell><ns0:cell /><ns0:cell>-</ns0:cell><ns0:cell>97.59 [89.55-99.85]</ns0:cell><ns0:cell>d d</ns0:cell><ns0:cell>9 11</ns0:cell><ns0:cell>684 3,722</ns0:cell><ns0:cell>7,579 27,925 MGE PP</ns0:cell></ns0:row><ns0:row><ns0:cell>a a a a a b b</ns0:cell><ns0:cell>I II</ns0:cell><ns0:cell>11 12 15 15</ns0:cell><ns0:cell cols='3'>GCF_000341425.1 197,439 205,343 PP 54 SRS2420927 33,863 33,967 3,452 5,467 PP 1 618 4 GCF_000341425.1 5,734 6,108 1,642 2,379 109,453 114,795 PP</ns0:cell><ns0:cell>118.8 [0-605] 114 [0-594] 193.8 [3-362]</ns0:cell><ns0:cell cols='2'>119.8 [0-618] 119.4 [0 -631] 210.3 [3 -396]</ns0:cell><ns0:cell>96.33 [90.44-98.38] 97.72 [90.35-99.70] 97.60 [96.73-98.44]</ns0:cell><ns0:cell>d 4,106 e f f f 4,290 f g</ns0:cell><ns0:cell>32 177 2,513 3 5 9 14 322 1</ns0:cell><ns0:cell>3 12 470,622 231,826 204,729 75,550 1,076</ns0:cell><ns0:cell>236 149 MGE 54 471,176 MGE 153 [338] [94] 232,047 247,594 PP 22 16 76,125 [221] [207] 1,198 MGE</ns0:cell></ns0:row><ns0:row><ns0:cell>b</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell cols='2'>675,050 696,164</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49215:1:1:NEW 9 Sep 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49215:1:1:NEW 9 Sep 2020)</ns0:note> </ns0:body> "

"September 9, 2020 RE: Resubmission of manuscript 49215 Dear Dr. Mossong and reviewers, Thank you for the opportunity to revise and resubmit our manuscript entitled “Genomic characterization and phylogenetic analysis of Salmonella enterica serovar Javiana” (ID 49215). We appreciate the reviewers’ comments and constructive suggestions. We believe that the manuscript has been improved after adding the recommended analyses and making the suggested edits. We have provided the revised manuscript (both a clean version and one with tracked changes) and a document with the reviewer comments and our responses in blue (starts on the next page). This revised version has been approved by all authors. Please feel free to contact me if you have any questions. Thank you for your consideration of our revised manuscript. We look forward to your decision. Sincerely, Thomas Denes, Ph.D. Assistant Professor in Molecular Food Microbiology Department of Food Science University of Tennessee, Knoxville Office phone: 865-974-7425 e-mail: [email protected] EDITOR'S DECISION: MAJOR REVISIONS The reviewers generally liked your manuscript, but asked for some changes. I agree that comparing your findings with a wider sample of other publicly available genomes, e.g. on Enterobase, would render results more robust. We performed additional analyses that included a wider sample of Salmonella ser. Javiana genomes (see response to Reviewer 2 comments below). Due to the inclusion of isolates from broader geographical origins, we have modified the title to remove “from Tennessee.” Additionally, we have made the following changes that were requested from the PeerJ Team following our initial re-submission: • Divided the Results and Discussion section into separate sections, • Added the mapping software used to create Figure S3 (lines 177-178), and • Adjusted the colors used in Figures 2, 3, and 4 to palettes that are accessible to those with color blindness. REVIEWER: EIJA TREES Dr. Trees, thank you for thoroughly reviewing our manuscript and providing these helpful comments. Basic reporting The manuscript is written with very good scientific English. It is structured clearly. The Background the authors provide for the investigation is very thorough with adequate references. The manuscript is self-contained with the results that are relevant to the objectives. The number of the figures included in the manuscript itself is appropriate. I think Table 3 could be included in the supplemental material and table 4 is not needed since the same information is included in the supplemental table 4. The following edits should be made: 1. Line 21 and throughout the manuscript: S. Javiana is not correct Salmonella nomenclature. The genus name Salmonella cannot be shortened as “S.” without spelling out the species name enterica. So after first mentioning and spelling out the entire genus-species-serovar name, the following references to it are acceptable moving forward: “S. enterica serovar Javiana”, “Salmonella ser. Javiana or “ser. Javiana”. Please check the Pasteur Institute's guidance at: https://www.pasteur.fr/sites/default/files/veng_0.pdf. Thank you for pointing this out; it was corrected throughout the manuscript. 2. Line 107: delete the repeated “cucumbers”. This was deleted (line 114). 3. Line 165, Supplemental table 1: for each strain, please indicate whether it was part of a known outbreak or considered sporadic. We added a column to Table S1 and indicated which isolates were part of multistate outbreaks (there were no local outbreaks during this time period). 4. Line 242: “multiple sub-clusters” instead of “multiple of the clusters”. This was changed (line 315-316). 5. Line 243: “potential disease clusters of public health importance” instead of “potential clusters in public health”. This change was made (line 539). 6. Line 277: comma after “blood”. A comma was added after blood (line 352). 7. Line 303: “of” after the percentage. This was added (line 371). 8. Line 360: ‘is in agreement with” instead of “is comparable to”. This was changed (line 630). 9. Line 369: ‘it” instead of “this”. This was changed (line 414). Experimental design Research questions are well defined and fill a gap in the current state of knowledge. AS for the methods I have the following comments: 1. Lines 163-176: include a brief description (library prep method and sequencing chemistry at a minimum) of the sequencing methods. This following sentence was added: “Genomic DNA was extracted using Qiagen DNeasy Blood & Tissue kits, libraries were prepared using Nextera XT kits, and sequencing was performed on an Illumina MiSeq platform using Illumina MiSeq v2 chemistry (500 cycle) to produce 250bp paired-end reads.”(lines 182-185). 2. Lines 178-198: please clarify what was the reasoning for using the two different SNP discovery methods in this study: the reference-free KSNP and the reference-based CFSAN pipeline? You state that you used the core SNP matrices from the KSNP to evaluate the population structure, not matrices based on all (core and ancillary) SNPs and given that the CFSAN pipeline removes mobile elements from hqSNP calling, the results should be expected to be close the same from the two pipelines. If the reason was that you were concerned the reference-based analysis would bias the population structure then that should be clearly stated over here. We used the reference-free KSNP analysis as a “first step” in order to remove any isolates that were not likely serovar Javiana, to get an overall understanding of the population structure and divide the isolates into discrete clades, and to choose appropriate reference genomes. We have made this clarification in the methods section by adding the following sentences: “A referencefree SNP detection analysis was initially performed to determine the overall population structure free of reference choice bias.”(lines 194-196) and “Next, reference-based hqSNP analyses were performed for each clade independently to determine high-resolution SNP differences between isolates.” (lines 204-206). 3. Lines 187-192: the choice of the hqSNP reference sequence for each lineage: typically you want the reference sequence to be closely related to the study population, so what exactly do the authors mean when they state that one criterium for the appropriate reference sequence was that is was “not closely related to other isolates”? Also what was the rationale of using internal references for clades I and III but an external reference for clade II? We agree that the “not closely related to other isolates” wording was confusing, so we removed it (line 207). At the time, the external reference was the only closed S. Javiana assembly on NCBI RefSeq. The external reference was most closely related to clade II isolates, so we used it as the clade II reference. If there had been RefSeq assemblies that were part of clades I and III, we would have used those as references for those clades, but since there were not, we used internal references. 4. Lines 223-227: what was the reason for only using the 3 reference sequences to identify the virulence factors? Given, how poorly understood the virulence markers currently are in Salmonella, I would determine the virulence factors either in all sequences or at least in a subset of strains from each clade to get an idea how much strain level variation there is within the clade. We went back and identified virulence factors in a subset of the isolates (n=31), including the internal references, multistate outbreak isolates, isolates from clades I and III representing genomic diversity, all isolates from clade II, and all of the isolates that didn’t fall into one of the three clades. We have updated this in the materials and methods section (lines 234-248), described the interesting results in results and discussion sections (lines 384-397 and 597-620), and provided the complete results in Data S6. Validity of the findings For the findings and conclusions I have the following comments/suggestions: 1. Lines 275-284: the sample source being extra-intestinal may be a poor indication of severe disease. The number of hospitalizations and deaths would be better. TN is a FoodNet site, so the disease outcome information should be available for these isolates and should be included in Table 2 and it should be discussed whether severe outcome was overrepresented in any of the clades. We agree that adding disease outcome information would be helpful, but we do not have this data. We reached out to our co-authors at TDH; however, they unfortunately do not have the staffing to aggregate the data for us at this time due to burdens of the COVID response. 2. Lines 445-448: what was the reasoning to use the clade II reference as a reference when analyzing all isolates together? Because it was closed and the clade I and III references were not? Clade II appears to be the least representative of the overall Javiana population. I would like to see this analysis being performed also using the clade I and III references. As you state on lines 459-462, the use of closed vs. draft reference should not have a drastic impact and sometimes using a draft reference that is more closely related to the study population actually gives better results than using a more distantly related closed reference. In the case of Javiana, the choice of reference may not make much difference because it looks like there may not be that much diversity in the core genome, but the authors should at least attempt to prove that by performing the overall analysis of the 111 sequences using also the clade I and III references. We re-ran the hqSNP analysis on all of the isolates using the three internal references (one for each clade). Additionally, we provided data on the results of using the external reference for the analyzing each clade separately. We have updated the Methods section to reflect this (lines 211-213), updated Table 1, provided the hqSNP matrices and statistics in Data S4, and further discussed it in the Results and Discussion sections (lines 322-337 and 562-581). 3. Lines 475-477: this is an over-statement unless the overall analysis is also performed using the clade I and the clade III references to prove that for Javiana the choice of reference does not make much difference. We kept this statement, but added that it was specifically true for the TN dataset and that it may only be applicable to less diverse populations. This is the updated sentence: “Additionally, we found that when performing hqSNP analysis for epidemiological cluster detection with the TN isolates, it is not necessary to first divide the isolates into clades, as we found this only minimally increases the SNP differences between isolates; however the TN isolates all belonged to a single lineage, so this may only be applicable to less diverse populations.” (lines 655-659). 4. Lines 481-483: more importantly, a larger dataset, particularly from other FoodNet sites where the information about disease severity (hospitalizations, death) is known would help shed light on the role of potential virulence genes. We modified this sentence to reflect this: “Further research should include clinical Salmonella ser. Javiana isolates and associated metadata from other states to obtain a more complete representation of the population structure of and epidemiological information about Salmonella ser. Javiana in the United States and an analysis of disease severity and gene content could assist in the identification of genes that may be involved in virulence.” (lines 659663). Comments for the author No additional comments REVIEWER 2 Reviewer 2, thank you for taking the time to review our manuscript. We feel that your suggestion to analyzed a larger dataset have helped to improve the understanding of the population structure of this serovar and provide a better context for the TN Salmonella ser. Javiana population. Basic reporting The basic reporting is excellent. Experimental design The manuscript is well written and clear. The Introduction is well presented, highlights the relevant aspects of why the research was undertaken, and provides an appropriate, easy to read introduction. It highlights that S. Javiana is a highly-prevalent enteric food pathogen of concern, and discusses its potential as a carrier of antimicrobial resistance. The authors are correct in their assertion that SJ’s population structure is important to study. The Materials and Methods are well presented and logical, and they use well-respected bioinformatics tools in the appropriate contexts. On Line 170: I recommend that they make it clear that (ILLUMINACLIP:etc are parameters passed for Trimmomatic to use. This clarification was added “…trimmed using Trimmomatic v0.35 (Bolger et al., 2014) (with the following parameters: ILLUMINACLIP: NexteraPE-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36),…”(lines 186-187). The Results & Discussion are also clearly presented, and I found all of the Figure, Tables and Supplementary information appropriately tagged and in the appropriate places. The authors present a well supported case that 106 of the 111 SJ genomes that were sequenced fall into three discrete clades. If they were to suggest that and leave it there, I’d have accepted the manuscript pretty quickly without major revisions. Validity of the findings I have huge doubts that selecting, sequencing and analysing 110 strains from Tennessee, collected over 18 months, is sufficient to then declare that S. Javiana is polyphyletic. I suggest that the authors provide better context especially with regard to the worldwide distribution of SJ – which is readily available. I would like the authors to put their analyses in the context of many more genomes of SJ, including those found elsewhere in the US as well as those found internationally. These genomes are readily available. We used EnteroBase to create a larger set of clinical Salmonella ser. Javiana strains from other states and countries and then ran a SNP analysis and created a phylogenetic tree (Figure 3 and Figure S1). This has been added to the Methods (lines 250-274), Results (lines 478-484), and Discussion (lines 516-521) sections. Furthermore, I’d like to see these analyses presented in the context of a global analysis of Salmonella genomes – most of which are in Enterobase, to see if the branch lengths of their proposed polyphyletic clades bear similar relationships to other polyphyletic serotypes of Salmonella e.g. Newport, Java, etc. Even a simple minimum spanning tree would be sufficient. Please perform those requested analyses, and add them to the manuscript, adjusting the conclusions to accommodate the enlarged analysis, OR, rewrite the manuscript removing the assertion that SJ is polyphyletic and replace it with the finding that it has three highly diverse clades. We used EnteroBase to create a dataset of Salmonella ser. Javiana strains and created a minimal spanning tree based on cgMLST data. We did the same for some other serovars reported as polyphyletic in the literature (serovars Derby, Kentucky, Mississippi, Montevideo, Newport, Saintpaul, and Senftenberg) in order to compare branch lengths between lineages. The trees are presented in Figure 4 and Figure S2. This has been added to the Methods (lines 276-289), Results (lines 486-496), and Discussion (lines 529-533) sections. We found that the branch length between the two Salmonella ser. Javiana ecBG clusters (1,423 allelic differences) was comparable to the distances seen for the other serovars (929-2,850 allelic differences). Comments for the author Other than my above comments, it is a highly polished manuscript and a pleasure to read. Thank you! "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Salmonella enterica serovar Javiana is the fourth most reported serotype of laboratoryconfirmed human Salmonella infections in the U.S. and in Tennessee (TN). Although Salmonella ser. Javiana is a common cause of human infection, the majority of cases are sporadic in nature rather than outbreak-associated. To better understand Salmonella ser.</ns0:p><ns0:p>Javiana microbial population structure in TN, we completed a phylogenetic analysis of 111 Salmonella ser. Javiana clinical isolates from TN collected from Jan. 2017 to Oct. 2018. We identified mobile genetic elements and genes known to confer antibiotic resistance present in the isolates, and performed a pan-genome-wide association study (pan-GWAS) to compare gene content between clades identified in this study. The population structure of TN Salmonella ser. Javiana clinical isolates consisted of three genetic clades: TN clade I (n= 54), TN clade II (n=4), and TN clade III (n=48). Using a 5, 10, and 25 hqSNP distance threshold for cluster identification, nine, 12, and 10 potential epidemiologically-relevant clusters were identified, respectively. The majority of genes that were found to be overrepresented in specific clades were located in mobile genetic element (MGE) regions, including genes encoding integrases and phage structures (91.5%). Additionally, a large portion of the over-represented genes from TN clade II (44.9%) were located on an 87.5 kb plasmid containing genes encoding a toxin/antitoxin system (ccdAB). Additionally, we completed phylogenetic analyses of global Salmonella ser. Javiana datasets to gain a broader insight into the population structure of this serovar. We found that the global phylogeny consisted of three major clades (one of which all of the TN isolates belonged to) and two cgMLST eBurstGroups (ceBGs) and that the branch length between the two Salmonella ser. Javiana ceBGs (1,423 allelic differences) was comparable to those from other serovars that have been reported as polyphyletic (929-2,850 allelic differences). This study demonstrates the population structure of TN and global Salmonella ser. Javiana</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Salmonella enterica subspecies enterica serovar Javiana (Salmonella ser. Javiana) was ranked the fourth most reported serotype (behind Enteritidis, Typhimurium, and Newport) in the United States in 2015, accounting for 7.4% (n=575) of laboratory confirmed human Salmonella infections (Centers for Disease Control and Prevention (CDC), 2017a). The incidence rate (IR) was 1.17 per 100,000 persons (Centers for Disease Control and Prevention (CDC), 2017a). In 2016, 2,719 culture-confirmed human Salmonella ser. Javiana infections were reported to the Laboratory-based Enteric Disease Surveillance (LEDS) system (9.8% of Salmonella infections; IR of 1.43 per 100,000 persons) (Centers for Disease Control and Prevention (CDC), 2018). The number of actual illnesses is likely higher according to CDC estimates of 29.3 actual cases per each laboratory-reported case <ns0:ref type='bibr' target='#b113'>(Scallan et al., 2011)</ns0:ref>. Nationally, Salmonella ser. Javiana IRthey may employ a large number of residents in the area. These employees may be directly exposed to Salmonella occupationally and indirectly expose others in those communities via items like clothes and shoes <ns0:ref type='bibr' target='#b121'>(Shaw et al., 2016)</ns0:ref>. The high density of these operations could also lead to environmental transmission via contamination of groundwater and surface water with untreated animal waste <ns0:ref type='bibr' target='#b121'>(Shaw et al., 2016)</ns0:ref>. <ns0:ref type='bibr'>Shaw, et al.</ns0:ref> did not find any statistically significant correlations between rurality or presence of broiler, cattle, dairy, or hog operations and IR ratios of Salmonella ser. Javiana in TN <ns0:ref type='bibr' target='#b121'>(Shaw et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Salmonella ser. Javiana outbreaks have been linked to chicken <ns0:ref type='bibr' target='#b71'>(Jackson et al., 2013)</ns0:ref>, pork <ns0:ref type='bibr' target='#b71'>(Jackson et al., 2013)</ns0:ref>, cheese <ns0:ref type='bibr' target='#b6'>(Alley &amp; Pijoan, 1942;</ns0:ref><ns0:ref type='bibr' target='#b67'>Hedberg et al., 1992)</ns0:ref>, shrimp <ns0:ref type='bibr' target='#b133'>(Venkat et al., 2018)</ns0:ref>, produce <ns0:ref type='bibr' target='#b16'>(Bennett et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b18'>Blostein, 1993</ns0:ref>; Centers for Disease Control and Prevention (CDC), 2005; Centers for Disease Control and Prevention (CDC), 2007; <ns0:ref type='bibr' target='#b65'>Hanning et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b71'>Jackson et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b109'>Sandt et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b122'>Sivapalasingam et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b124'>Srikantiah et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b130'>Toth et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b135'>Walsh et al., 2014)</ns0:ref>, spices <ns0:ref type='bibr' target='#b83'>(Lehmacher et al., 1995;</ns0:ref><ns0:ref type='bibr' target='#b150'>Zweifel &amp; Stephan, 2012)</ns0:ref>, ill foodhandlers <ns0:ref type='bibr' target='#b48'>(Elward et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b81'>Lee et al., 1998)</ns0:ref>, and contact with amphibians <ns0:ref type='bibr' target='#b125'>(Srikantiah et al., 2004)</ns0:ref>. According to the National Outbreak Reporting System (NORS), there have been eight Salmonella ser. Javiana outbreaks involving TN, five multistate and three singlestate and all were foodborne. Identified vehicles included tomatoes, cucumbers, tilapia, fajita (beef), and iceberg lettuce. All of the TN outbreaks were in restaurant settings.</ns0:p><ns0:p>Salmonella ser. Javiana has been isolated from a variety of foods, including seafood <ns0:ref type='bibr' target='#b90'>(Mezal et al., 2013)</ns0:ref>, white pepper <ns0:ref type='bibr' target='#b90'>(Mezal et al., 2013)</ns0:ref>, produce <ns0:ref type='bibr' target='#b45'>(Duffy et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b47'>Elviss et al., 2009;</ns0:ref><ns0:ref type='bibr' target='#b90'>Mezal et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b103'>Reddy et al., 2016)</ns0:ref>, and pecans <ns0:ref type='bibr' target='#b21'>(Brar et al., 2016)</ns0:ref>. Environmentally, Salmonella ser. Javiana has been isolated from surface water and sediment <ns0:ref type='bibr' target='#b14'>(Bell et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b86'>Li et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b91'>Micallef et al., 2012)</ns0:ref>, poultry farms <ns0:ref type='bibr' target='#b59'>(Gama et al., 2003;</ns0:ref><ns0:ref type='bibr' target='#b105'>Rodriguez et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b112'>Santos et al., 2007)</ns0:ref>, dairy and livestock farms <ns0:ref type='bibr' target='#b3'>(Adesiyun et al., 1996;</ns0:ref><ns0:ref type='bibr' target='#b98'>Oliveira et al., 2002;</ns0:ref><ns0:ref type='bibr' target='#b105'>Rodriguez et al., 2006)</ns0:ref>, irrigation water <ns0:ref type='bibr' target='#b45'>(Duffy et al., 2005)</ns0:ref>, and packing shed equipment surfaces <ns0:ref type='bibr' target='#b45'>(Duffy et al., 2005)</ns0:ref>. It has also been recovered from wildlife <ns0:ref type='bibr' target='#b44'>(Drake et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b63'>Gruszynski et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b89'>Lockhart et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b94'>Miller et al., 2014)</ns0:ref>, pets <ns0:ref type='bibr' target='#b2'>(Adesiyun et al., 1997;</ns0:ref><ns0:ref type='bibr' target='#b80'>Leahy et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b116'>Seepersadsingh et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b138'>Woodward et al., 1997)</ns0:ref>, and zoo animals <ns0:ref type='bibr' target='#b62'>(Gopee et al., 2000)</ns0:ref>. The diversity of animals found carrying Salmonella ser. Javiana includes amphibians <ns0:ref type='bibr' target='#b44'>(Drake et al., 2013)</ns0:ref>, reptiles <ns0:ref type='bibr' target='#b89'>(Lockhart et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b138'>Woodward et al., 1997)</ns0:ref>, birds <ns0:ref type='bibr' target='#b62'>(Gopee et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b63'>Gruszynski et al., 2014)</ns0:ref>, and mammals <ns0:ref type='bibr' target='#b2'>(Adesiyun et al., 1997;</ns0:ref><ns0:ref type='bibr' target='#b62'>Gopee et al., 2000;</ns0:ref><ns0:ref type='bibr' target='#b63'>Gruszynski et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b70'>Iveson &amp; Bradshaw, 1973;</ns0:ref><ns0:ref type='bibr' target='#b80'>Leahy et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b94'>Miller et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b116'>Seepersadsingh et al., 2004)</ns0:ref>. As Salmonella ser. Javiana has been isolated from and associated with contact with reptiles and amphibians, this may play a role in contamination of plant-based food commodities (Centers for Disease Control and Prevention (CDC), 2002; <ns0:ref type='bibr' target='#b37'>Clarkson et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b71'>Jackson et al., 2013)</ns0:ref>. A recently published systematic review identified the following risk factors associated with Salmonella ser. Javiana infection: consumption of fresh produce (tomatoes and watermelons), herbs (paprika-spice), dairy products (cheese), drinking contaminated well water, and animal contact <ns0:ref type='bibr' target='#b95'>(Mukherjee et al., 2019)</ns0:ref>. <ns0:ref type='bibr'>Clarkson, et al.</ns0:ref> found consumption of well water, reptile/amphibian contact, and exposure to recreational water associated with Salmonella ser. Javiana infection in GA and TN, but found consumption of tomatoes and poultry protective <ns0:ref type='bibr' target='#b37'>(Clarkson et al., 2010)</ns0:ref>.</ns0:p><ns0:p>Though antibiotics are generally not used to treat uncomplicated Salmonella infections, when necessary, antibiotics most commonly used include ampicillin (penicillin), chloramphenicol (phenicol), ciprofloxacin (fluoroquinolone), ceftriaxone (cephalosporin), trimethoprim-sulfamethoxazole (folate pathway inhibitor, sulfonamide), amoxicillin (penicillin), and azithromycin (macrolide) <ns0:ref type='bibr' target='#b40'>(Cuypers et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b49'>Eng et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b61'>Gilbert et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b74'>Jajere, 2019;</ns0:ref><ns0:ref type='bibr' target='#b119'>Shane et al., 2017)</ns0:ref>. The 2019 'Antibiotic Resistance Threats in the United States' report lists drug-resistant nontyphoidal Salmonella as a 'serious threat' and details increasing numbers of isolates ciprofloxacin nonsusceptible, ceftriaxone resistant, or with decreased susceptibility to azithromycin (Centers for Disease Control and Prevention (CDC), 2019a). From the National Antimicrobial Resistance Monitoring System (NARMS) Now Salmonella ser. Javiana human isolate data from 1996-2019 (Centers for Disease Control and Prevention (CDC), 2019b), the highest prevalences of phenotypic antibiotic resistance were to streptomycin (2.27%; aminoglycoside), ampicillin (1.39%), and tetracycline (1.05%). Resistance to amoxicillinclavulanic acid, cefoxitin (cephalosporin), ceftiofur (cephalosporin), ceftriaxone, cephalothin (cephalosporin), chloramphenicol, sulfamethoxazole/sulfisoxazole (sulfonamides), and trimethoprim-sulfamethoxazole were all less than 1% (Centers for Disease Control and Prevention (CDC), 2019b). Resistance to azithromycin or ciprofloxacin was not reported (Centers for Disease Control and Prevention (CDC), 2019b). Resistance among Salmonella ser. Javiana isolates may be lower due to the association with wild animal (e.g., reptile and amphibian) and other environmental reservoirs in contrast to food animal-associated serovars.</ns0:p><ns0:p>Though Salmonella ser. Javiana is a prevalent serotype in both the US and TN, little is known about the genomic population structure. The objectives of this study were to retrospectively study isolates of Salmonella ser. Javiana from patients in TN in 2017-2018 in order to identify epidemiologically-relevant trends, determine the genomic population structure, and describe the defining genomic features of major clades. Additionally, we studied expanded datasets representing global diversity to determine the overall population structure of Salmonella ser. Javiana and to compare it to other Salmonella serovars.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head><ns0:p>Sequencing, preprocessing, and genome assembly of TN isolates. BioSample numbers and metadata for Salmonella ser. Javiana (n=111) isolates from patients in TN from January 2017 through October 2018 were obtained from the Tennessee Department of Health (TDH) (Data S1). Tennessee population data (2018) used for calculating incidence rates (IR) wasobtained from the U.S. Census Bureau (U.S. Census Bureau) and IR per county were mapped using Tableau Desktop Public Edition (v2019.2.1) <ns0:ref type='bibr'>(Tableau Software, 2019)</ns0:ref>. PFGE and wholegenome sequencing were performed by the TDH Division of Laboratory Services according to PulseNet protocols (Centers for Disease Control and Prevention (CDC), 2016; Centers for Disease Control and Prevention (CDC), 2017b). For PFGE, XbaI was used as the primary restriction enzyme. Genomic DNA was extracted using Qiagen DNeasy Blood &amp; Tissue kits, libraries were prepared using Nextera XT kits, and sequencing was performed on an Illumina MiSeq platform using Illumina MiSeq v2 chemistry (500 cycle) to produce 250bp paired-end reads. Raw reads were downloaded from the NCBI SRA database, trimmed using Trimmomatic v0.35 <ns0:ref type='bibr' target='#b19'>(Bolger et al., 2014)</ns0:ref> (with the following parameters: ILLUMINACLIP: NexteraPE-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36), and quality checked using FastQC v0.11.7 <ns0:ref type='bibr' target='#b7'>(Andrews, 2010)</ns0:ref> and MultiQC v1.5 <ns0:ref type='bibr' target='#b52'>(Ewels et al., 2016)</ns0:ref> to combine the results. The trimmed reads were assembled into contigs using SPAdes v3.12.0 <ns0:ref type='bibr' target='#b12'>(Bankevich et al., 2012)</ns0:ref> with the careful option. Assembly statistics were generated by BBMap v38.88 <ns0:ref type='bibr' target='#b24'>(Bushnell, 2018</ns0:ref><ns0:ref type='bibr'>), SAMtools v0.1.8 (Li et al., 2009</ns0:ref><ns0:ref type='bibr'>), and QUAST v4.6.3 (Gurevich et al., 2013)</ns0:ref>. SeqSero <ns0:ref type='bibr' target='#b144'>(Zhang et al., 2015)</ns0:ref> was used to confirm serotype designations.</ns0:p><ns0:p>SNP Detection and phylogenetic analyses. A reference-free SNP detection analysis was initially performed with the TN isolates to determine the overall population structure free of reference choice bias. The assemblies were analyzed using KSNP3.1 <ns0:ref type='bibr' target='#b60'>(Gardner et al., 2015)</ns0:ref> and the resulting core SNP matrix fasta file was then used to construct a phylogenetic tree in Mega7 <ns0:ref type='bibr' target='#b79'>(Kumar et al., 2016)</ns0:ref> with 100 bootstrap replicates <ns0:ref type='bibr' target='#b53'>(Felsenstein, 1985)</ns0:ref>. The evolutionary distances were computed using the number of differences method <ns0:ref type='bibr' target='#b97'>(Nei &amp; Kumar, 2000)</ns0:ref> and the evolutionary history was inferred using the Neighbor-Joining method <ns0:ref type='bibr' target='#b107'>(Saitou &amp; Nei, 1987)</ns0:ref>. The final tree was visualized and annotated using iTOL <ns0:ref type='bibr' target='#b85'>(Letunic &amp; Bork, 2016)</ns0:ref>. Isolates that weren't serotype Javiana (based on SeqSero results) and were very divergent based on the KSNP analysis were removed from the analysis. Major clades (defined as groups of three or more isolates that were all within 500 SNPs of each other) were identified. Next, reference-based hqSNP analyses were performed for each TN clade independently to determine high-resolution SNP differences between isolates. For the hqSNP analyses, an appropriate internal reference genome assembly (with adequate assembly quality and expected assembly size and G+C content) for each clade was identified (SRS2420927 for TN clade I, SRS2822480 for TN clade II, and SRS3010019 for TN clade III). Additionally, the Salmonella enterica subsp. enterica serovar Javiana str. CFSAN001992 assembly (GCF_000341425.1) was downloaded from the NCBI RefSeq database for use as an external and closed reference genome. The hqSNP analyses were performed, both with the internal and external references and for the 111 isolates together and for each TN clade individually. For each analysis, high quality single nucleotide polymorphisms (hqSNPs) were identified using the CFSAN SNP Pipeline v1.0.1 <ns0:ref type='bibr' target='#b41'>(Davis et al., 2015)</ns0:ref>. The resulting hqSNP matrix fasta files were then used to construct phylogenetic trees as described above. The matrices were sorted and clustered using the hclust function (gtools package) in R studio. For the individual clade analyses using internal references, clusters of two or more related isolates were identified at hqSNP distance threshold levels of 5, 10 and 25; isolation date and other epidemiological information were not considered.</ns0:p><ns0:p>Genome annotation and pan-GWAS. TN isolate assemblies were annotated using Prokka v1.14-dev <ns0:ref type='bibr' target='#b115'>(Seemann, 2014)</ns0:ref> and RASTtk <ns0:ref type='bibr' target='#b22'>(Brettin et al., 2015)</ns0:ref>. A pangenome-wide association study (pan-GWAS) was performed to compare gene content among the isolates using Roary v3.12.0 (with Prokka annotation output files, previously described, used as input files) <ns0:ref type='bibr' target='#b99'>(Page et al., 2015)</ns0:ref> and statistical analysis was done using Scoary v1.6.16 (with the following arguments: -c I B BH PW EPW P -p 0.05 -e 100) <ns0:ref type='bibr' target='#b23'>(Brynildsrud et al., 2016)</ns0:ref> to identify genes or markers associated with inclusion in each clade. Genes predominantly present or absent among isolates in each clade were identified. Genes or clusters of genes (loci) were considered significantly associated with a clade or cluster if they had a Bonferroni-corrected P-value &lt;0.05. From the pan-GWAS, the positively and negatively associated genes were classified by having an Odds Ratio of &gt;1 and &lt;1, respectively. To further analyze the results in a genomic context, loci that were adjacent or located in close proximity were combined into a single region.</ns0:p><ns0:p>In silico Identification of genomic features and genes. Phage regions were identified in a diverse representative subset of the TN isolates (n=31) using Phaster <ns0:ref type='bibr' target='#b9'>(Arndt et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b147'>Zhou et al., 2011)</ns0:ref>. Potential plasmids were predicted and classified using PlasmidFinder v2.0.2 (database version 2019-05-16) <ns0:ref type='bibr' target='#b26'>(Carattoli et al., 2014)</ns0:ref>, Unicycler v0.4.8-beta <ns0:ref type='bibr' target='#b136'>(Wick et al., 2017)</ns0:ref>, and plasmidSPAdes <ns0:ref type='bibr' target='#b8'>(Antipov et al., 2016)</ns0:ref> and visualized using Bandage <ns0:ref type='bibr' target='#b137'>(Wick et al., 2015)</ns0:ref>. They were further confirmed by examining the associated assembly contigs for plasmidassociated genes, comparing to known plasmids using PLSDB <ns0:ref type='bibr' target='#b58'>(Galata et al., 2018)</ns0:ref> and BLASTn, and comparing coverage and G+C content to the whole assembly. Antibiotic resistance (ABR) determinants in genomes were predicted using ResFinder (90% threshold for identity and 60% for minimum length) <ns0:ref type='bibr' target='#b141'>(Zankari et al., 2012)</ns0:ref> to identify acquired ABR genes and PointFinder (90% threshold for identity and 60% for minimum length) <ns0:ref type='bibr' target='#b140'>(Zankari et al., 2017)</ns0:ref> to identify point mutations conferring ABR. The representative subset of the isolates (n=31) was also examined for virulence factors using VirulenceFinder <ns0:ref type='bibr' target='#b75'>(Joensen et al., 2014)</ns0:ref> and VFDB VFanalyzer <ns0:ref type='bibr' target='#b88'>(Liu et al., 2018)</ns0:ref> and Salmonella Pathogenicity Islands (SPIs) using SPIFinder (v1.0; 95% threshold for identity and 60% for minimum length) <ns0:ref type='bibr' target='#b106'>(Roer et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Global phylogenetic analysis. The Salmonella database <ns0:ref type='bibr' target='#b4'>(Alikhan et al., 2018)</ns0:ref> on EnteroBase <ns0:ref type='bibr' target='#b148'>(Zhou et al., 2019)</ns0:ref> was queried for isolates with 'human' listed as source niche in the strain metadata and 'Javiana' listed as serovar in the strain metadata or experimental data (SISTR1 <ns0:ref type='bibr' target='#b139'>(Yoshida et al., 2016)</ns0:ref> or SeqSero2 <ns0:ref type='bibr' target='#b143'>(Zhang et al., 2019a)</ns0:ref>). Only strains with country (and state for strains from the United States) included in the metadata were retained. A cgMLST + HierCC minimal spanning tree (RapidNJ algorithm) was created with GrapeTree <ns0:ref type='bibr' target='#b149'>(Zhou et al., 2018)</ns0:ref> on EnteroBase using all of the resulting strains. Strains that were likely not Javiana (conflicting serovar designations and distant on the tree) were removed from the dataset, leaving 466 strains (Data S2). The dataset was further refined to select representative strain(s) for each HC100 level cluster (&#61603;100 cgMLST allelic differences). For each HC100 cluster, a single strain from each country/state was retained. If there were more than one strain from a country/state, the representative strain was chosen based on assembly quality (N50; and if N50 values were identical or similar, coverage and number of contigs were also considered). At least one TN strain representing each HC100 cluster (if available) was chosen to be included in the final dataset of genomes representing global diversity of of Salmonella ser. Javiana clinical isolates. The final dataset consisted of 162 strains: 29 TN isolates (11 from TN clade I, 3 from TN clade II, 10 from TN clade III, and the five isolates that didn't fall into the main clades), 43 strains from other states in the US, and 90 isolates from other countries (Data S2). Collection date years ranged from 2002 to 2020. Assemblies for the non-TN strains were downloaded from Enterobase. All assemblies were analyzed using KSNP3.1 <ns0:ref type='bibr' target='#b60'>(Gardner et al., 2015)</ns0:ref> and the resulting core SNP matrix fasta file was then used to construct a phylogenetic tree in Mega7 <ns0:ref type='bibr' target='#b79'>(Kumar et al., 2016)</ns0:ref> with 100 bootstrap replicates <ns0:ref type='bibr' target='#b53'>(Felsenstein, 1985)</ns0:ref>. The evolutionary distances were computed using the number of differences method <ns0:ref type='bibr' target='#b97'>(Nei &amp; Kumar, 2000)</ns0:ref> and the evolutionary history was inferred using the Neighbor-Joining method <ns0:ref type='bibr' target='#b107'>(Saitou &amp; Nei, 1987)</ns0:ref>. The final tree was visualized and annotated using iTOL <ns0:ref type='bibr' target='#b85'>(Letunic &amp; Bork, 2016)</ns0:ref>.</ns0:p><ns0:p>Comparison to polyphyletic serovars. Eight strain datasets were created: one for serovar Javiana and one each for other serovars that have been reported as polyphyletic (Derby, Kentucky, Mississippi, Montevideo, Newport, Saintpaul, and Senftenberg). The Salmonella database <ns0:ref type='bibr' target='#b4'>(Alikhan et al., 2018)</ns0:ref> on EnteroBase <ns0:ref type='bibr' target='#b148'>(Zhou et al., 2019)</ns0:ref> was queried for isolates with the specified serovar listed as serovar in the experimental data (SISTR1 <ns0:ref type='bibr' target='#b139'>(Yoshida et al., 2016)</ns0:ref> or SeqSero2 <ns0:ref type='bibr' target='#b143'>(Zhang et al., 2019a)</ns0:ref>). For each, a cgMLST + HierCC minimal spanning tree (RapidNJ algorithm) was created. Strains that were likely not the serovar of interest (conflicting serovar designations and distant on the tree) were removed from the datasets. The final datasets (Data S3) were used to create cgMLST + HierCC minimal spanning trees (improved minimal spanning tree algorithm, MSTree V2) using GrapeTree <ns0:ref type='bibr' target='#b149'>(Zhou et al., 2018)</ns0:ref> on EnteroBase. The branch lengths between the cgMLST eBurstGroups (ceBGs) of the other polyphyletic serovars were used for comparison to the branch length between the two Javiana ceBGs. ceBG designations associated with each serovar were retrieved from the EnteroBase documentation (EnteroBase Team, 2018).</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Tennessee Salmonella ser. Javiana Population Structure. This analysis included a diverse set of 111 Salmonella ser. Javiana clinical isolates from TN (Data S1). On average, the assembled genomes from this study had 74.6x coverage, contained 71.7 contigs (34.8 contigs &#8805; 1 kb), were 46.45 kb in length, and had 52.11% GC content (Data S1). Based on the KSNPanalysis, the Salmonella ser. Javiana isolates from TN displayed a population structure with three main clades (Fig. <ns0:ref type='figure'>1</ns0:ref>). TN Clade I contained 54 isolates, TN clade II contained four, TN clade III contained 48 isolates, and five isolates didn't fall into the main clades (Fig. <ns0:ref type='figure'>1 and Table 1</ns0:ref>). Isolates in TN clades I, II, and III had average hqSNP distances of 119.4 (range 0 to 631), 210.3 (range <ns0:ref type='table'>3 to 396), and 66 (range 0 to 361), respectively (Table 1 and Data S4</ns0:ref>).</ns0:p><ns0:p>The 111 TN Salmonella ser. Javiana clinical isolates represented 47 different PFGE patterns (Fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref> High-quality single nucleotide polymorphism (hqSNP) analysis for cluster detection. Using a 5, 10, and 25 hqSNP distance threshold for cluster identification, 9, 12, and 10 potential clusters were identified, respectively (Data S4). The number of clusters decreases from thresholds of 10 to 25, as with the larger threshold, some of the clusters contain multiple subclusters identified at the lower threshold. Within TN clade I, five clusters were identified at each hqSNP distance thresholds of 5 and 10, and four clusters at 25 (Data S4). Only one cluster was identified at each of the distance thresholds for TN clade II (Data S4). Within TN clade III, three clusters were identified at a distance threshold of 5 hqSNPs, six clusters at 10 hqSNPs, and five clusters at hq25 SNPs (Data S4).</ns0:p><ns0:p>To evaluate the effects of reference choice and isolate diversity, we ran our hqSNP analyses on the entire TN dataset (111 isolates) and on the three clades individually and with both internal draft assemblies and an external closed assembly as reference genomes. When all isolates were analyzed together using different reference genomes, the average hqSNP distance was lowest when using the internal reference from TN clade I and highest when using the external closed genome and the average percentage of reads mapped differed by up to 1.57% (Table <ns0:ref type='table'>1 and Data S4</ns0:ref>). It should be noted that the closed external reference assembly we used (GCF_000341425.1) was most closely related to TN clade II in our original KSNP analysis (Fig. <ns0:ref type='figure'>1</ns0:ref>) and not representative of the overall population (at the time that this analysis was performed, there was only one closed Salmonella ser. Javiana genome available on NCBI RefSeq). For all three clades, regardless of the reference genome used, hqSNP distances were higher when they were analyzed independently, with the differences being only slightly higher for clades I and III. The average hqSNP distances for clades I and II were lower when using the internal references, but were slightly higher for TN clade III. For all three clades, the average percent reads mapped was higher when using the internal reference genome than the external reference genome, which is to be expected.</ns0:p><ns0:p>Epidemiological Trends. The TN Salmonella ser. Javiana isolates were sourced from patients with an average age of 40.0 (range of 1 month to 90 years; standard deviation of 29.1). The highest incidence was in patients &#8804;4 (6.64 per 100,000) and &#8805;85 (4.16) years-old. Previous studies have reported that Salmonella ser. Javiana infections are more prevalent in infants and young children than for other serovars <ns0:ref type='bibr' target='#b76'>(Jones et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b121'>Shaw et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b125'>Srikantiah et al., 2004)</ns0:ref>. Overall, 51.4% of isolates were from male patients (incidence of 1.73) and 46.8% from female (incidence of 1.50; Table <ns0:ref type='table'>2</ns0:ref>). TN clades I and II contained more isolates from male patients than female, 57.4% and 75%, respectively. Conversely, 52.1% of TN clade III isolates were from female patients.</ns0:p><ns0:p>Most of the TN Salmonella ser. Javiana isolates were taken from stool samples (84.7%, n=94), followed by urine (6.3%, n=7) and blood (5.4%, n=6) (Table <ns0:ref type='table'>2</ns0:ref>). The portion of isolates taken from blood samples exceeds the 2.8% invasive disease outcome (defined by isolation from blood, cerebrospinal fluid, bone or joint fluid, or another sterile site; does not include urine, wound, abscess cultures) reported for this serovar in FoodNet states <ns0:ref type='bibr' target='#b76'>(Jones et al., 2008)</ns0:ref>. Of the urine isolates, most (n=6) belonged to TN clade III and all were from females, with an average patient age of 55.1 (standard deviation of 26.2). All of the isolates recovered from blood samples belonged to TN clades I (n=3) and III (n=3) and most were from males (n=4), with an average patient age of 71.8 (standard deviation of 15.2). The majority of isolates recovered from extraintestinal sites were collected from elderly patients, which may indicate a correlation between invasive infection and age.</ns0:p><ns0:p>Geographical and Temporal Distribution. A geographical distribution can be seen for the TN isolates, with 65.8% (n=73) isolated in counties in the western region of TN (Table <ns0:ref type='table'>2</ns0:ref>; Data S1). In contrast, only 17.1% (n=19) and 16.2% (n=18) were isolated in counties in east and middle TN, respectively. Incorporating county population data, the west region had an IR of 4.69 clinical isolates per 100,000 population, while the east had an IR of 0.79 and the middle had an IR of 0.64, with an overall IR of 1.62 per 100,000 for the state (Fig. <ns0:ref type='figure' target='#fig_2'>S2</ns0:ref>). Three counties had noticeably higher IR: Madison with 31.0, Crockett with 27.9, and Carroll with 25.0. As was the trend for all isolates, the majority of TN clade I and III isolates originated in the west region (59.3% and 83.3%, respectively; Table <ns0:ref type='table'>2</ns0:ref>). However, a sizable amount of TN clade I isolates also originated in the east region (25.9%). Additionally, a temporal distribution was also clear, with 68.5% (n=76) of isolates collected in July through September (Table <ns0:ref type='table'>2</ns0:ref>; Data S1). This trend was also seen within the three TN clades.</ns0:p><ns0:p>Identification of Mobile Genetic Elements (MGEs). All of the TN isolates were examined for plasmids and 32 putative plasmids (19 unique) were identified in 30 isolates (Table <ns0:ref type='table'>3</ns0:ref>). They ranged in size from 23 to 108 kb and included replicon types (a plasmid typing scheme based on replication control regions <ns0:ref type='bibr' target='#b26'>(Carattoli et al., 2014)</ns0:ref> Most identified virulence genes were present in all of the TN isolates analyzed (Data S6), including the three genes (cdtB, pltA, and pltB) encoding the subunits of the cytolethal distending toxin (CDT) <ns0:ref type='bibr' target='#b92'>(Miller et al., 2018)</ns0:ref>. Only the TN clade II isolates contained the pefC and pefD genes, which were on plasmid-associated contigs, that are part of the pef (plasmid-encoded fimbriae) operon and associated with fimbrial adherence <ns0:ref type='bibr' target='#b13'>(B&#228;umler et al., 1996)</ns0:ref>. Some of the isolates (two from TN clade I and three that were not part of a clade) contained genes from the saf (Salmonella atypical fimbria) operon on putative plasmid-associated contigs <ns0:ref type='bibr' target='#b55'>(Folkesson et al., 1999)</ns0:ref>. One isolate (SRS2442415, no clade) contained 11 genes associated with the yersiniabactin iron uptake system on a plasmid-associated contig <ns0:ref type='bibr' target='#b27'>(Carniel, 2001)</ns0:ref>.</ns0:p><ns0:p>Identification of Antibiotic Resistance Genes. All 111 TN Salmonella ser. Javiana isolates analyzed in the present study contained the aac(6')-Iaa gene, which has been previously reported to confer aminoglycoside resistance <ns0:ref type='bibr' target='#b120'>(Shaw et al., 1993)</ns0:ref>. One isolate (SRS2783476; TN clade I) contained the aph(3')-Ia and sul3 genes on a contig (contig 32) that associated with a putative plasmid. The aph(3')-Ia gene has been found to confer resistance to aminoglycosides <ns0:ref type='bibr' target='#b120'>(Shaw et al., 1993)</ns0:ref> and sul3 gene has been shown to confer resistance to sulfonamides/sulfones through antibiotic target replacement and has been shown to be associated with resistance to sulfamethoxazole <ns0:ref type='bibr' target='#b100'>(Perreten &amp; Boerlin, 2003)</ns0:ref>.</ns0:p><ns0:p>Additionally, one isolate (SRS2628542; no clade) contained the qnrB19 gene, which has been shown to confer resistance to fluoroquinolones through physical protection of the antibiotic target <ns0:ref type='bibr' target='#b38'>(Correia et al., 2017)</ns0:ref>. The qnr gene is plasmid-associated and has been linked with reduced susceptibility to ciprofloxacin <ns0:ref type='bibr' target='#b28'>(Casas et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b39'>Crump et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b104'>Redgrave et al., 2014)</ns0:ref>. It is unclear if this gene in SRS2628542 is on a plasmid, as it is located on a small (703 bp) contig and no plasmids were predicted in this isolate. However, the gene showed 100% identity over only 72.6% of the alignment with the reference gene (accession EU432277), so it may not be functionally capable of conferring the quinolone resistance phenotype.</ns0:p><ns0:p>Clade-Enriched Genes. A pangenome analysis of the TN isolates revealed that the core genome (genes contained in &#61619;99% of isolates) consisted of 4,022 genes and the accessory genome consisted of 3,920 genes (Table <ns0:ref type='table'>1</ns0:ref>). The difference in gene content between the identified clades were mostly found in mobile genetic elements (91.5%).</ns0:p><ns0:p>TN clade I isolates had a core genome of 4,106 genes and an accessory genome of 2,513 genes (Table <ns0:ref type='table'>1</ns0:ref>). This clade has a much larger accessory genome than the other two clades identified in this study. This is likely due to the large variety of mobile genetic elements (i.e., plasmids, prophages) present in isolates from this clade, which is also reflected in the much larger number of PFGE patterns (n=28) displayed by these isolates as compared to other clades (n=3 for TN clade II and n=11 for TN clade III). The pan-GWAS revealed 153 loci (genes or groups of genes) to be significantly associated with inclusion in this clade (54 positively associated and 99 negatively associated) (Table <ns0:ref type='table'>1 and Data S7</ns0:ref>). These loci consisted of 338 total genes (94 positively associated and 243 negatively associated) (Table <ns0:ref type='table'>1</ns0:ref>). The positively associated loci are found in 29 distinct genomic regions and the majority of the genes overrepresented in TN clade I (73 genes) were located in eight prophage regions (Table <ns0:ref type='table'>4</ns0:ref>).</ns0:p><ns0:p>Twelve of the overrepresented genes in TN clade I correspond to pathogenicity-related protein families (as identified by PathogenFinder): DNA damage-inducible protein I, phenolic acid decarboxylase subunit D, small toxic polypeptide LdrD, PTS system fructose-specific EIIB'BC component, PTS system mannose/fructose/sorbose family IID component, prepilin peptidase dependent protein A precursor, phage DNA binding protein, and other hypothetical proteins. Overexpression of ldrD, which is part of a chromosomal toxin-antitoxin gene system <ns0:ref type='bibr' target='#b5'>(Alix &amp; Blanc-Potard, 2009;</ns0:ref><ns0:ref type='bibr' target='#b78'>Kawano et al., 2002)</ns0:ref>, is toxic to the cell and leads to growth inhibition and rapid cell killing <ns0:ref type='bibr' target='#b57'>(Fozo et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b78'>Kawano et al., 2002)</ns0:ref>. ldrD homologs have not been found in plasmids, but may be involved in cellular response to environmental stress <ns0:ref type='bibr' target='#b78'>(Kawano et al., 2002)</ns0:ref>. Prepilin peptidase dependent protein A precursor is known to be plasmidassociated <ns0:ref type='bibr' target='#b102'>(Raspoet et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b142'>Zhang et al., 1994)</ns0:ref> and is involved in processing of the major pilus subunit <ns0:ref type='bibr' target='#b54'>(Filloux et al., 1998;</ns0:ref><ns0:ref type='bibr' target='#b142'>Zhang et al., 1994)</ns0:ref>. Other genes of interest enriched in isolates from TN clade I include those encoding autotransporter adhesin SadA, which is associated with pathogenesis, and virulence protein MsgA, which is involved with survival within macrophage <ns0:ref type='bibr' target='#b123'>(Skyberg et al., 2006)</ns0:ref>. Mezal, et al. identified msgA virulence gene in 7 (out of 50) Salmonella ser. Javiana isolates, all of which were clinical <ns0:ref type='bibr' target='#b90'>(Mezal et al., 2013)</ns0:ref>.</ns0:p><ns0:p>TN clade II isolates had a core genome of 4,290 genes and an accessory genome of 322 genes (Table <ns0:ref type='table'>1</ns0:ref>). The pan-GWAS revealed 22 loci to be significantly associated with inclusion in this clade (16 positively associated and 6 negatively associated) (Table <ns0:ref type='table'>1 and Data S7</ns0:ref>). These loci consisted of 221 total genes (207 positively associated and 14 negatively associated) (Table <ns0:ref type='table'>1</ns0:ref>). The positively associated loci are found in 17 distinct genomic regions and many of the genes over-represented in TN clade II (93 genes) were located in the 87.5 kb IncFII type plasmid identified in SRS2922480 (Table <ns0:ref type='table'>4</ns0:ref> and Fig. <ns0:ref type='figure' target='#fig_3'>S3</ns0:ref>). Among the over-represented genes contained on this plasmid are ccdAB, which are part of a toxin/antitoxin system. This system contributes to stability of the plasmid through post-segregational killing (killing new cells that do not inherit a plasmid copy during cell division) <ns0:ref type='bibr' target='#b132'>(Van Melderen, 2001)</ns0:ref>. Additionally, 72 over-represented genes were located in four predicted prophage regions and 33 in three other potential MGE regions (indicated by gene annotations, clustering of genes, and/or close proximity to predicted prophage regions; Table <ns0:ref type='table'>4</ns0:ref>). One of the overrepresented genes, alpha-xylosidase, corresponds to a pathogenicity-related protein family (as identified by PathogenFinder). VFDB identified pefC and pefD, fimbrial adherence determinants, on the plasmid (contig 13); sinH, a nonfrimbrial adherence determinant; and pipB, a TTSS-2 translocated effector.</ns0:p><ns0:p>TN clade III isolates had a core genome of 4,115 genes and an accessory genome of 889 genes (Table <ns0:ref type='table'>1</ns0:ref>). The pan-GWAS revealed 155 loci to be significantly associated with inclusion in this clade (101 positively associated and 54 negatively associated) (Table <ns0:ref type='table'>1 and Data S7</ns0:ref>). These groups contained 332 total genes (238 positively associated and 94 negatively associated) (Table <ns0:ref type='table'>1</ns0:ref>). The positively associated loci are found in 29 distinct genomic regions and the majority of the genes over-represented in TN clade III were located in four predicted prophage regions (88 genes) or nine other putative MGE regions (134 genes) (Table <ns0:ref type='table'>4</ns0:ref>). Four of the overrepresented genes correspond to pathogenicity-related protein families (as identified by PathogenFinder): arginine/lysine/ornithine decarboxylase) and other hypothetical proteins.</ns0:p><ns0:p>Global Population Structure. The KSNP analysis of the diverse set of global clinical Salmonella ser. Javiana strains revealed three major clades (Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>; Figure <ns0:ref type='figure'>S1</ns0:ref>). Major clade I contained 107 strains, including TN isolates (from TN clades I, II, and III and the five isolates that didn't fall into the main clades). Major clade II contained 23 strains and major clade III contained 31 strains. Strains from major clades I and II belong to the 590 cgMLST eBurstGroup (ceBG) and strains from major clade III belong to the 204 ceBG; both of these are associated with this serovar <ns0:ref type='bibr'>(EnteroBase Team, 2018)</ns0:ref>.</ns0:p><ns0:p>To further explore if Salmonella ser. Javiana is polyphyletic, we constructed minimal spanning trees based on cgMLST allele distances of all available Salmonella ser. Javiana strains and of other Salmonella serovars previously described as polyphyletic (Derby, Kentucky, <ns0:ref type='bibr'>Mississippi, Montevideo, Newport, Saintpaul, and Senftenberg (Achtman et al., 2012;</ns0:ref><ns0:ref type='bibr'>Alikhan et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b11'>Banerji et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b25'>Cao et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b110'>Sangal et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b117'>S&#233;vellec et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b128'>Tang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b129'>Timme et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b134'>Vosik et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b145'>Zhang et al., 2019b</ns0:ref>)) (Figure <ns0:ref type='figure' target='#fig_4'>4</ns0:ref>; Figure <ns0:ref type='figure' target='#fig_2'>S2</ns0:ref>). The branch length between the two ecBG clusters on the ser. Javiana tree was 1,423 allelic differences. The branch lengths between ecBG clusters on the other trees ranged from 2,280-2,769 allelic differences for ser. Derby, 2,452-2,756 for ser. Kentucky, 929-2,850 for ser.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The main objective of this study was to use WGS data to retrospectively examine the population structure of Salmonella ser. Javiana, both from a local (state of TN) and global perspective. The phylogenetic analysis of the 111 Salmonella ser. Javiana isolates from TN revealed a population structure with three main clades, with the majority of isolates found in TN clades I and III. Research published on the population structure of this serovar is limited. One comparable study, conducted by <ns0:ref type='bibr'>Mezal, et al., used PFGE</ns0:ref> to assess the relatedness of 50 Salmonella ser. Javiana isolates from food, environmental, and clinical sources. They found that the isolates represented 34 distinct PFGE patterns and grouped into five clusters of two or more isolates; the 30 clinical isolates represented 23 distinct PFGE patterns (compared to the 111 TN clinical isolates in the present study representing 47 distinct PFGE patterns) and spanned all five clusters. The diversity of PFGE patterns suggested that differences in genome content between Salmonella ser. Javiana isolates are common. In this study, we found that differences in gene content between the TN clades were mostly attributed to mobile genetic elements (i.e., prophage regions and plasmids), with TN clade I exhibiting the highest level of accessory genome diversity.</ns0:p><ns0:p>The phylogenetic analysis of the diverse set of global clinical Salmonella ser. Javiana strains revealed three major clades (Figure <ns0:ref type='figure' target='#fig_3'>3</ns0:ref>; Figure <ns0:ref type='figure'>S1</ns0:ref>). Major clade I contained most of the strains, including all of the TN isolates. This indicates that the population of this serovar in TN represents only a portion of the global genomic diversity. Strains from major clades I and II belong to the 590 cgMLST eBurstGroup (ceBG) and strains from major clade III belong to the 204 ceBG. ceBGs are equivalent to eBurstGroups (eBGs; in legacy 7-gene MLST), which have been shown to correspond to serovar designations <ns0:ref type='bibr'>(EnteroBase Team, 2018;</ns0:ref><ns0:ref type='bibr' target='#b148'>Zhou et al., 2019)</ns0:ref>. Typically, monophyletic serovar isolates will belong to a single eBG, while polyphyletic serovar isolates will belong to multiple eBGs <ns0:ref type='bibr' target='#b1'>(Achtman et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b4'>Alikhan et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b11'>Banerji et al., 2020)</ns0:ref>.The observation that the global clinical Salmonella ser. Javiana isolates consisted of multiple major clusters and two ceBGs suggests that this serovar may be polyphyletic. <ns0:ref type='bibr'>Ashton, et al. characterized</ns0:ref> serovars in lineage 3 of S. enterica subspecies I (which includes serovars Bredeney, Chester, Javiana, Montevideo, Oranienburg, and Poona) as polyphyletic and containing multiple eBGs <ns0:ref type='bibr' target='#b10'>(Ashton et al., 2016)</ns0:ref>. The branch length between the two ecBG clusters on the ser. Javiana tree (1,423 allelic differences) was comparable to the branch lengths between ecBGs on the other serovar trees (929-2,850 allelic differences) (Figure <ns0:ref type='figure' target='#fig_4'>4</ns0:ref> and Figure <ns0:ref type='figure' target='#fig_2'>S2</ns0:ref>). Based on this comparison, Salmonella ser. Javiana may be considered a polyphyletic serovar, although this depends on the branch length cutoff that is applied.</ns0:p><ns0:p>As WGS is becoming more commonly used for public health applications (e.g., cluster detection and outbreak investigation), it is important to understand genomic population structure of surveilled disease-causing microorganisms, specifically at the serovar level for Salmonella. Genomic distance thresholds (based on hqSNP or allelic distances) are an important factor used for identifying potential disease clusters of public health importance, but other factors are typically considered, including isolation date, number of isolates, and epidemiological data. In the present study, we found that using different hqSNP distance thresholds for cluster identification resulted in different numbers of potential clusters and associated isolates (Data S4). The selected threshold for cluster detection should be empirically determined so that it is larger than typical inter-genomic distances between outbreak strains, but smaller than typical inter-genomic distances between outbreak and background (non-outbreak) isolates. Intergenomic SNP distances among Salmonella outbreak strains are typically small (in the 2 to 12 SNP range), but in some cases can be quite large (up to 249 SNPs) and likely vary from serovar to serovar <ns0:ref type='bibr' target='#b82'>(Leekitcharoenphon et al., 2014)</ns0:ref>. Isolates from zoonotic or prolonged (e.g., persistent contamination from production environments) outbreaks will likely have larger genomic distances and outbreaks with very large genomic distances are typically polyclonal events <ns0:ref type='bibr' target='#b17'>(Besser et al., 2019)</ns0:ref>. For Salmonella, the CDC uses a working definition of &#61619;3 cases within a 60day period with &#61603;10 cgMLST allele differences, with ~2 cases that have &#61603;5 allele differences <ns0:ref type='bibr' target='#b17'>(Besser et al., 2019)</ns0:ref>. Thresholds can have impacts on epidemiological investigations; if they are set too low, isolates belonging to the same outbreak event may be mistakenly excluded from the cluster or separated into different clusters and, if they are set too high, background isolates may be inadvertently included in the cluster, making epidemiological investigations difficult, particularly source attribution. In the present study, as the hqSNP distance threshold was increased, the number of included isolates also increased. Increases in numbers and/or sizes of potential clusters may impact the ability of public health departments to further investigate them due to resource constraints. Thresholds may also need to be adjusted based on the timeline of the suspected outbreak (lower for short-term and higher for prolonged outbreaks). As we move forward with using WGS for routine surveillance and cluster detection of this serovar, more clusters may be successfully detected and investigated. In turn, this will provide information on typical genomic distances that can be used to establish and evaluate an appropriate serovarspecific threshold for cluster detection.</ns0:p><ns0:p>Another important consideration when using hqSNP calling analyses for epidemiological cluster detection is whether polyphyletic serovars or those with genetically diverse clades should be analyzed together or if each clade should be analyzed independently. An additional consideration is the choice of reference genome. These choices can affect the percentage of reads mapped to the reference genome and, in turn, the results of the analysis (primarily, hqSNP distances). Better performance (i.e., higher read mapping) would be expected when using closed genomes as references for hqSNP calling. However, some research has shown that using closed vs draft genomes as references have limited impact on hqSNP calling phylogeny reconstruction <ns0:ref type='bibr' target='#b73'>(Jagadeesan et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b101'>Portmann et al., 2018)</ns0:ref>. In the current study, we still achieved a level of high-quality mapping (&gt;95%, as recommended by <ns0:ref type='bibr' target='#b77'>(Katz et al., 2017)</ns0:ref>; Table <ns0:ref type='table'>1</ns0:ref>) when using draft genomes as references. As these types of studies are performed, representatives from each clade should be selected for long-read sequencing to establish high quality reference genomes that can be used to further evaluate hqSNP distances. Additionally, when analyzing the TN isolates together or each clade separately and with internal or external reference genomes, similar levels of performance were achieved. This is likely due to the lack of diversity in the core genome of the isolates and the fact that the majority of the gene content differences between isolates from each clade were attributed to MGEs (plasmids and prophage regions). Commonly used hqSNP pipelines filter out SNPs that are found in close proximity and/or mask phage regions <ns0:ref type='bibr' target='#b77'>(Katz et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b126'>Strain et al.)</ns0:ref> and only SNPs present in genomic regions shared between isolates and the reference genome are identified in the analysis. When viewed from a global context, the TN isolates were all part of a single major clade and a single ceBG, which may also explain the similar levels of performance seen with the different analysis strategies.</ns0:p><ns0:p>Notable geographical and temporal patterns were observed for the Salmonella ser. Javiana isolates from TN. The geographical distribution within the state (most isolates from patients in counties in the western region; Table <ns0:ref type='table'>2 and Figure S3</ns0:ref>) is consistent with other reported data (Centers for Disease Control and Prevention (CDC), 2013; <ns0:ref type='bibr' target='#b96'>Mukherjee et al., 2020)</ns0:ref>. This geographical distribution may be associated with the higher percentage of fresh forested/scrub-shrub wetlands in these west TN counties <ns0:ref type='bibr' target='#b68'>(Huang et al., 2017)</ns0:ref>. A similar geographical distribution has been described in GA, with Salmonella ser. Javiana cases occurring more frequently in the southern part of state <ns0:ref type='bibr' target='#b37'>(Clarkson et al., 2010)</ns0:ref>. Despite this, <ns0:ref type='bibr'>Harris, et al.</ns0:ref> were unable to isolate Salmonella ser. Javiana from storm runoff or irrigation ponds used by fresh produce growers in South Georgia even though this is a high incidence area <ns0:ref type='bibr' target='#b66'>(Harris et al., 2018)</ns0:ref>. The temporal distribution (most isolates collected July-September; Table <ns0:ref type='table'>2</ns0:ref>) is in accordance with the notable seasonality of this serovar reported elsewhere <ns0:ref type='bibr' target='#b37'>(Clarkson et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b125'>Srikantiah et al., 2004)</ns0:ref>.</ns0:p><ns0:p>Salmonella virulence factors aid in host colonization and pathogenicity by assisting the pathogen in attaching to, invading, and replicating within host cells, intra-and extracellular survival, evading host defenses, and outcompeting the gut microbiome and include adhesion systems, capsule, flagella, and toxins <ns0:ref type='bibr' target='#b74'>(Jajere, 2019)</ns0:ref>. Virulence factors and related genes are frequently clustered together in pathogenicity islands, which are often found on mobile genetic elements (MGEs), such as plasmids and prophages <ns0:ref type='bibr' target='#b36'>(Cheng et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b72'>Jacobsen et al., 2011)</ns0:ref>. Eight Salmonella Pathogenicity Islands (SPIs) or islets (SPI-1, SPI-2, SPI-4, SPI-5, SPI-9, SPI-11, SPI-12 and CS54) are commonly found in most non-typhoidal serovars (den <ns0:ref type='bibr' target='#b42'>Bakker et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b72'>Jacobsen et al., 2011)</ns0:ref>. All of the representative subset of TN isolates analyzed for SPIs contained C63PI, SPI-13, and SPI-14 (Data S6). C63PI, which is located within SPI-1, contains the sit operon that encodes an iron uptake system <ns0:ref type='bibr' target='#b114'>(Schmidt &amp; Hensel, 2004;</ns0:ref><ns0:ref type='bibr' target='#b146'>Zhou et al., 1999)</ns0:ref>. SPI-13 has been associated with macrophage internalization and virulence in chickens and mice <ns0:ref type='bibr' target='#b36'>(Cheng et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b46'>Elder et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b51'>Espinoza et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b118'>Shah et al., 2005)</ns0:ref>. SPI-14 is involved in epithelial invasion and pathogenicity in chickens <ns0:ref type='bibr' target='#b36'>(Cheng et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b56'>Fookes et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b118'>Shah et al., 2005)</ns0:ref>. Most of the representative subset of TN isolates analyzed for SPI contained SPI-2 and SPI-4. SPI-2 encodes a type III secretion system 1 (TTSS-2), which is involved in intracellular survival and replication, immune evasion, and systemic pathogenicity <ns0:ref type='bibr' target='#b114'>(Schmidt &amp; Hensel, 2004;</ns0:ref><ns0:ref type='bibr' target='#b131'>Tsai &amp; Coombes, 2019)</ns0:ref>, replication within macrophages, and systemic infections <ns0:ref type='bibr' target='#b74'>(Jajere, 2019)</ns0:ref>. SPI-4 encodes genes for toxin secretion and apoptosis and is involved in intracellular (macrophage) survival <ns0:ref type='bibr' target='#b74'>(Jajere, 2019)</ns0:ref>. All three genes associated with the cytolethal distending toxin were identified in all of the representative subset of TN isolates, which is in agreement with other studies that have identified these three genes in all Salmonella ser. Javiana isolates tested <ns0:ref type='bibr' target='#b90'>(Mezal et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b93'>Miller &amp; Wiedmann, 2016)</ns0:ref>. Other virulence genes that differed among isolates were mainly associated with mobile genetic elements.</ns0:p><ns0:p>All 111 TN Salmonella ser. Javiana isolates analyzed in the present study contained the aac(6')-Iaa gene, which is associated with aminoglycoside resistance <ns0:ref type='bibr' target='#b120'>(Shaw et al., 1993)</ns0:ref>. However, there is evidence that this gene is cryptic and no longer confers phenotypic aminoglycoside resistance <ns0:ref type='bibr' target='#b84'>(Leon et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b108'>Salipante &amp; Hall, 2003)</ns0:ref>, which is consistent with the low prevalence of phenotypic resistance to amikacin and gentamicin (0.04%) in U.S. clinical Salmonella ser. Javiana isolates (Centers for Disease Control and Prevention (CDC), 2019b). Taken together, these findings highlight the complexity of antimicrobial resistance. The three other antibiotic resistance genes identified in this study (aph(3')-Ia, sul3, and qnrB19 gene) were each only present in a single isolate. The low prevalence of these three genes is consistent with the low phenotypic prevalence of resistance to gentamicin and kanamycin (0.12%), sulfamethoxazole/sulfisoxazole (0.63%), trimethoprim-sulfamethoxazole (0.21%), and ciprofloxacin (0%) seen in U.S. clinical Salmonella ser. Javiana isolates (Centers for Disease Control and Prevention (CDC), 2019b). Additionally, The hypothesis that the qnrB19 gene may not be functional is further supported by the fact that phenotypic ciprofloxacin resistance has not been reported in Salmonella ser. Javiana clinical isolates (Centers for Disease Control and Prevention (CDC), 2019b). As aminoglycosides are not typically used to treat Salmonella infections, the presence of the aac(6')-Iaa and aph(3')-Ia genes is of little clinical significance. Overall, these data show a low prevalence of genes associated antibiotic resistance in Salmonella ser. Javiana from TN. However, antibiotic susceptibility testing would need to be performed on these isolates to confirm.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study demonstrates the population structure of Salmonella ser. Javiana in Tennessee and globally. As this is a clinically important Salmonella serotype, understanding the phylogeny can provide guidance for phylogenetic analyses and cluster detection for public healthsurveillance and response. We show that Salmonella ser. Javiana clinical isolates from TN show geospatial and temporal distribution, with most isolates originating from the western part of the state and during the summer months (July, August, and September). Based on the results of the pan-GWAS, it is clear that MGEs (namely plasmids and prophage regions) in the genome account for most of the differences in gene content between the three main clades of this serovar. This is noteworthy, as clinically-relevant genes (like ABR-conferring or virulence-related genes) can be found in these regions and they could potentially be used for isolate characterization. Additionally, we found that when performing hqSNP analysis for epidemiological cluster detection with the TN isolates, it is not necessary to first divide the isolates into clades, as we found this only minimally increases the SNP differences between isolates; however the TN isolates all belonged to a single global major clade and single ceBG, so this may only be applicable to less diverse populations. Further research should include clinical Salmonella ser. Javiana isolates and associated metadata from other states to obtain a more complete representation of the population structure of and epidemiological information about Salmonella ser. Javiana in the United States and an analysis of disease severity and gene content could assist in the identification of genes that may be involved in virulence. Another research direction would be to include isolates from other sources (i.e., environmental, animal, food) in a phylogenetic analysis, which may expand our understanding of the population structure and including isolates with diverse isolation sources may provide insight into source attribution and potential recommendations to prevent morbidity.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>Unrooted neighbor-joining KSNP tree of Tennessee clinical Salmonella ser. Javiana isolates.</ns0:p><ns0:p>Tree was constructed based on core SNPs determined by KSNP3 <ns0:ref type='bibr' target='#b60'>(Gardner et al., 2015)</ns0:ref>. The optimal tree with the sum of branch length of 5,916.1 is shown. TN clades I (highlighted in purple), II (green), and III (blue) are indicated. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test are indicated below branches. The tree is drawn to scale, with branch lengths (above branches) representing the number of base differences at core SNP positions per isolate (SNP distance). The analysis involved 112 isolates and 5,870 total SNP positions. Tree was constructed based on core SNPs determined by KSNP3 <ns0:ref type='bibr' target='#b60'>(Gardner et al., 2015)</ns0:ref>. The optimal tree with the sum of branch length of 31,777.6 is shown. The percentage of replicate trees in which the associated taxa clustered together in the bootstrap test that are &#8804;0.8 are represented by branch color (maximum as green, midpoint as yellow, and minimum as red).</ns0:p><ns0:p>The tree is drawn to scale, with branch lengths (above branches) representing the number of base differences at core SNP positions per isolate (SNP distance). The analysis involved 161 isolates and 30,657 total SNP positions. The three major clades are labeled. HC900 (ceBG) clusters are indicated (590 is not shaded and 204 is shaded in gray). TN isolates belonging to TN clades I, II, and III from our original analysis (Fig. <ns0:ref type='figure'>1</ns0:ref>) are highlighted in purple, green, and blue, respectively. A standard tree with additional metadata can be found in the supplemental files (Figure <ns0:ref type='figure'>S1</ns0:ref>). </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>; Data S1). The most common PFGE patterns were JGGX01.0012 (n=18), JGGX01.0065 (n=17), and JGGX01.0072 (n=10). TN clade I isolates represented 28 different PFGE patterns, with the most common being JGGX01.0012 (n=18). TN clade II isolates represented three different PFGE patterns. TN clade III isolates represented 11 different PFGE patterns, with the most common being JGGX01.0065 (n=17) and JGGX01.0072 (n=10). Each of the five isolates that did not belong to a clade had a distinct PFGE pattern. All PFGE patterns were unique to only one TN clade.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>) IncFIB, IncFII, IncI1, IncN3, and IncX4. In the representative subset of TN isolates (n=31), Phaster predicted an average of 8.90 [range of 5-13] prophage regions per isolate (2.29 intact, 4.94 incomplete, and 1.68 questionable) (Data S5). The TN clade I isolates had the highest number of predicted prophage regions (average of 9.64 and range of 8-11), followed by TN clade II (average of 8.25 and range of 8-9) and TN clade III (average of 8.09 and range of 5-10). Identification of Virulence Factors and Pathogenicity Islands. All of the representative subset of TN isolates (n=31) contained pathogenicity islands C63PI, SPI-13, and SPI-14 (Data S6). Most of the TN isolates examined contained SPI-2 (except for SRS2442409 [TN clade II] and SRS2998834 [TN clade III]) and SPI-4 (except SRS3453943 [TN clade I], SRS3643364 [TN clade III], and SRS2998834 [TN clade III]).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49215:2:0:NEW 30 Sep 2020) Manuscript to be reviewed a Reference Isolate: (a) SRS2420927, (b) SRS2628565, (c) SRS2822480, (d) SRS3010019, (e) SRS3643364, (f) SRS3721796, (g) SRS3799118 b MGE Region: Prophage (PP), Putative mobile genetic element (MGE), Plasmid (PL) PeerJ reviewing PDF | (2020:05:49215:2:0:NEW 30 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='33,42.52,70.87,525.00,399.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='37,42.52,70.87,525.00,514.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='39,42.52,70.87,525.00,426.00' type='bitmap' /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49215:2:0:NEW 30 Sep 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49215:2:0:NEW 30 Sep 2020)</ns0:note> </ns0:body> "

"EDITOR COMMENTS (Joël Mossong) MINOR REVISIONS Please address the few remaining suggestions for changes by the reviewer. [# PeerJ Staff Note: It is PeerJ policy that additional references suggested during the peerreview process should only be included if the authors are in agreement that they are relevant and useful #] REVIEWER 1 (Eija Trees) Thank you for the additional edits and comments. Basic reporting No comment Experimental design The authors have adequately addressed my concerns in the revision. Validity of the findings 1. Lines 545-560: SNP distances in an epidemiologically verified outbreak that exceed > 25-30 SNPs typically indicate the presence of polyclonal contamination, i.e. multiple different strains causing an outbreak. An outbreak with >200 plus SNPs certainly is a polyclonal one and should be noted here if the authors wish to use this reference. Cluster detection thresholds really don’t apply to polyclonal outbreaks which are challenging to investigate no matter what typing method is used. A vast majority of the Salmonella outbreaks are within 5-20 SNP range, the upper range often seen in zoonotic outbreaks or long lasting outbreaks involving persistent environmental contamination. An article discussing outbreak ecology for enteric organisms is here: Besser, J.M., Carleton, H.A., Trees, E., Stroika, S.G., Hise, K., Wise, M., Gerner-Smidt, P. (2019) Interpretation of Whole-Genome Sequencing for Enteric Disease Surveillance and Outbreak Investigation. Foodborne Path. Dis. 16. Published Online:9 Jul 2019https://doi.org/10.1089/fpd.2019.2636 The following sentences were added: “Isolates from zoonotic or prolonged (e.g., persistent contamination from production environments) outbreaks will likely have larger genomic distances and outbreaks with very large genomic distances are typically polyclonal events (Besser et al., 2019). For Salmonella, the CDC uses a working definition of 3 cases within a 60day period with 10 cgMLST allele differences, with ~2 cases that have 5 allele differences (Besser et al., 2019).” (lines 548- 551). 2. Lines 574-581: also when put in the global context, the TN strains all belonged to the same eBurst group and clade. So while three clades appeared to be separating in the local analysis containing just the TN strains, from the global context the TN strains are monophyletic which may explain the equal performance of the different references. This was clarified by adding the following sentence: “When viewed from a global context, the TN isolates were all part of a single major clade and a single ceBG, which may also explain the similar levels of performance seen with the different analysis strategies.” (lines 586-588). Comments for the Author 1. Line 340: add “age’ after “an average” “Age” was added (line 340). 2. Line 511: “are common” instead of “is common” “Is” was changed to “are” (line 511). 3. Line 617: “in all of the representative…” “In” was added (line 624). 4. Line 658: clarify that the TN isolates belong to a single global lineage and single eBurst group This has been clarified and now reads “…however the TN isolates all belonged to a single global major clade and single ceBG, …” (lines 664-665). "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. Jixi is a typical mining city in China that has undergone dramatic changes in its land-use pattern of mining areas over the development of its coal resources. Impacts of coal mining activities have greatly affected the regional land surface temperature and ecological system.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods.</ns0:head><ns0:p>The Landsat 8 Operational Land Imager (OLI) data from 2015 and 2019 were used from the Jiguan, Didao, and Chengzihe District of Jixi in Heilongjiang, China as the study area. The calculations to determine the land-use classification, vegetation coverage, and land surface temperature (LST) were performed using ArcGIS10.5 and ENVI 5.3 software packages. A correlation analysis revealed the impact of land-use type, vegetation coverage, and coal mining activities on LSTs.</ns0:p><ns0:p>Results. The results show significant spatial differentiation in the LSTs of Jixi City. The LSTs for various land-use types were ranked from high to low as follows: mining land &gt; construction land &gt; grassland &gt; cultivated land &gt; forest land &gt; water area. The LST was lower in areas with high vegetation coverage than in other areas. For every 0.1 increase in vegetation coverage, the LST is expected to drop by approximately 0.75 &#8451;. An analysis of mining land patches indicates that the patch area of mining lands has a significant positive correlation with both the average and maximum patch temperatures. The average patch temperature shows a logarithmic increase with the growth of the patch area, and within 200,000 m 2 , the average patch temperature increases significantly. The maximum patch temperature shows a linear increase with the patch area growth, and for every 100,000 m 2 increase in the patch area of mining lands, the maximum patch temperature increases by approximately 0.81 &#8451;. The higher the average patch temperature of mining land, the higher the temperature in its buffer zone, and the greater its influence scope. This study provides a useful reference for exploring the warming effects caused by coal mining activities and the definition of its influence scope.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The land surface temperature (LST) comprehensively reflects the energy exchange between land and the atmosphere, which is an important geophysical parameter in the ground-air system <ns0:ref type='bibr' target='#b26'>(Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b63'>Zhu et al., 2016)</ns0:ref>. Coupling the inversion results of LST with other parameters, such as land-use type and vegetation coverage, provides a scientific basis for ecological environmental protection <ns0:ref type='bibr'>(Li et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b27'>Liang, &amp; Zhai, 2014;</ns0:ref><ns0:ref type='bibr' target='#b48'>Xu, He &amp; Huang, 2013;</ns0:ref><ns0:ref type='bibr'>Zhang et al., 2013)</ns0:ref>. The commonly used LST inversion algorithms are divided primarily into the single-channel algorithm, multi-channel algorithm, and split-window algorithm <ns0:ref type='bibr' target='#b63'>(Zhu et al., 2016)</ns0:ref>. Among them, the single-channel algorithms include the atmospheric correction method, Mono-window algorithm, and the Jim&#233;nez-Mu&#241;oz J.C single-channel algorithm <ns0:ref type='bibr'>(Qin, Karnieli &amp; Berliner, 2001;</ns0:ref><ns0:ref type='bibr'>Jim&#233;nez-Mu&#241;oz et al., 2008)</ns0:ref>. The multi-channel algorithms mainly include the day-night method, temperature emissivity separation algorithm, and graybody emissivity method <ns0:ref type='bibr'>(Gan et al., 2006;</ns0:ref><ns0:ref type='bibr'>Gillespie, Rokugawa &amp; Matsunaga, 2002;</ns0:ref><ns0:ref type='bibr'>Zhang et al., 2000)</ns0:ref>. The split window algorithm is based mostly on data from the Landsat-TIRS, NOAA-AVHRR, and TERRA-MODIS <ns0:ref type='bibr'>(Rozenstein et al., 2014;</ns0:ref><ns0:ref type='bibr'>Qin &amp; Karnieli, 2011;</ns0:ref><ns0:ref type='bibr'>Mao et al., 2005)</ns0:ref>.</ns0:p><ns0:p>Due to aggravation of the heat island effect, current research on LSTs is mostly focused on urban areas. Analyzing differences in LSTs for different land-use types optimizes the distribution of green space from the perspective of landscape patterning to reduce the heat island effect <ns0:ref type='bibr'>(Liu, 2016)</ns0:ref>. However, mining areas, which are often affected by high temperatures and cause safety problems, have not attracted sufficient attention and are rarely studied. Some research has shown that in the resource development process for resource-based cities, the land-use patterns in mining areas are constantly changing, which causes a series of impacts on the regional ecological environment <ns0:ref type='bibr' target='#b6'>(Li et al.,2018;</ns0:ref><ns0:ref type='bibr' target='#b2'>Chabukdhara &amp; Singh, 2016;</ns0:ref><ns0:ref type='bibr' target='#b44'>Xie et al., 2011)</ns0:ref>. Therefore, research focusing on coupling between land-use patterns in mining areas and the ecological environment indicators, such as the LST, water environment quality, and biodiversity, has become vital to environmental sustainability <ns0:ref type='bibr' target='#b61'>(Zhou &amp; Wang, 2014;</ns0:ref><ns0:ref type='bibr' target='#b43'>Xiao, Hu &amp; Fu, 2014;</ns0:ref><ns0:ref type='bibr' target='#b18'>Hu, Duo &amp; Wang, 2018;</ns0:ref><ns0:ref type='bibr' target='#b0'>Bian et al., 2018)</ns0:ref>. Current research on land surface temperatures in mining areas mainly includes the temporal and spatial distribution characteristics of the surface temperature, the impact of ecological disturbance on the surface temperature, and others, where the scales are mostly at macro-regions <ns0:ref type='bibr'>(Li, Yang &amp; Lei, 2017;</ns0:ref><ns0:ref type='bibr'>Qiu &amp; Hou, 2013;</ns0:ref><ns0:ref type='bibr' target='#b44'>Xie et al., 2011;</ns0:ref><ns0:ref type='bibr'>)</ns0:ref>. This study specifically analyzes the overall and local distribution characteristics of LSTs from smaller scales to explore the radius of influence of high-temperature points. This provides a reference to establish heat alerts in mining areas.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Overview of the study area</ns0:head><ns0:p>The study area encompasses the Jiguan, Didao, and Chengzihe District of Jixi, which are the main mining lands with a total area of 827.87 km 2 . Jixi is located in the southeast of Heilongjiang Province, between 130&#176;24&#8242;24&#8243;-133&#176;56&#8242;30&#8243; E, 44&#176;51&#8242;12&#8243;-46&#176;36&#8242;55&#8243; N. To the southeast and across the ocean in Russia, while to the west and south are Mudanjiang, and to the north is Qitaihe (Fig. <ns0:ref type='figure'>1</ns0:ref>). The province comprises Mishan, Hulin, and Jidong Counties and six other districts (Jiguan, Hengshan, Didao, Chengzihe, Lishu, and Mashan). The study area is part of the cold-temperate continental monsoon climate, where the average annual temperature is 3.7 &#8451;, the average precipitation is 537.5 mm, the annual sunshine is 2709 h and the average frostfree period is 140 d. The terrain is composed primarily of mountains, hills and plains.</ns0:p><ns0:p>Jixi is relatively rich in mineral resources with mutiple mining areas. However, there also are several abandoned mines that severely damage the ecological environment. In addition, urban construction and industrial development have encroached on grasslands, woodlands, and wetlands, which increases the ecological vulnerability and risks in these ecosystems <ns0:ref type='bibr' target='#b12'>(He, 2010)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Data sources and preprocessing treatments</ns0:head><ns0:p>This paper is based on the Landsat 8 OLI remote sensing images from 2015 and 2019, all of which are from the US Geological Survey (http://glovis.usgs.gov/). All images have a spatial resolution of 30 m. The image strip numbers/rows used in this study are 115/28 and 115/29, respectively, and the imaging time was from July to September. Cloud cover in these images was less than 2%, and they were interpreted and classified based on a series of preprocessing treatments, including radiation calibration, atmospheric correction, band synthesis and image cropping.</ns0:p></ns0:div> <ns0:div><ns0:head>Analytical methods</ns0:head><ns0:p>The spatial differentiation characteristics of the LST in the Jiguan, Didao, and Chengzihe Districts of Jixi were used to identify heat islands and their influencing factors. We selected a single-window algorithm for inversion of the LSTs. These results were used to analyze the effects of the land-use type, vegetation coverage and coal mining activities on the spatial distribution of LSTs.</ns0:p></ns0:div> <ns0:div><ns0:head>Determining land-use classification and vegetation coverage</ns0:head><ns0:p>Land use is the most direct manifestation of the interaction between human activities and the natural environment as it reflects this close relationship in both time and space <ns0:ref type='bibr' target='#b35'>(Mooney, Duraiappah &amp; Larigauderie, 2013;</ns0:ref><ns0:ref type='bibr' target='#b29'>Liu et al., 2014)</ns0:ref>. Typically, areas designated as land resources reflects the status of natural resources within the study area. Changes in land-use patterns inevitably cause changes in the LSTs and ecosystem functionality. Therefore, the study of land use is of great importance for regional ecological analyses <ns0:ref type='bibr' target='#b32'>(Marceau et al., 2003)</ns0:ref>.</ns0:p><ns0:p>The relationship between vegetation coverage and the LST has become a focus of research on heat islands <ns0:ref type='bibr' target='#b39'>(Wang et al., 2011)</ns0:ref>. Green vegetation affects LSTs through photosynthesis, transpiration and evapotranspiration. <ns0:ref type='bibr' target='#b30'>Ma et al. (2010)</ns0:ref> compared and analyzed five correlation degrees among planting parameters and LSTs, including the normalized difference vegetation index (NDVI), ratio vegetation index (RVI), greenness vegetation index (GVI), modified soil to adjust vegetation index (MSAVI) and vegetation coverage. They concluded that the correlation between vegetation coverage and the LST was both high and stable because it is not markedly influenced by spatial location or changes in the fraction or type of surface coverage. Therefore, the relationship between vegetation coverage and the LST was selected to study heat island effects within different land surfaces.</ns0:p></ns0:div> <ns0:div><ns0:head>Land-use classification</ns0:head><ns0:p>The ENVI 5.3.1 (L3Harris Geospatial Solutions, Inc., Melbourne, FL, USA) and ArcGIS 10.5 (Esri, Corp., Redlands, CA, USA) were used to preprocess the original image data, which includes geometric correction, mosaic compilation, fusion, clipping, research scope extraction, image enhancement and supervised classification, before interpreting and analyzing the remote sensing imagery. The classification of land-use types in the study area was consistent with the standard land-use classification (GB/T 21010-2017). The study area was divided into six categories: forest lands, grasslands, construction lands, cultivated lands, mining lands and water areas. A maximum-likelihood approach was used for the classification. In the final stage of the study, the remote sensing image interpretation was validated by site surveys. The accuracy of the results was verified by establishing a confusion matrix. Random points were selected in the Erdas Imagine 2015 software for classification, where a certain number of random points were selected for each category. The classification of each random point was distinguished visually so that the category to which each random point belongs is defined in the software. The user accuracy, producer accuracy, and Kappa coefficient of the overall classification of each category were then calculated.</ns0:p></ns0:div> <ns0:div><ns0:head>Vegetation coverage calculation</ns0:head><ns0:p>Plant coverage information is typically extracted from remote sensing images. Given the high accuracy of NDVI values estimated using remote sensing, it is one of the most widely used indexes <ns0:ref type='bibr' target='#b36'>(Mu et al., 2012)</ns0:ref>. A common method to calculate vegetation coverage is based on the hybrid pixel decomposition method, where it is assumed that each pixel of the remote sensing image is composed of soil and vegetation components. Thus, the information includes both a pure soil component and a pure vegetation component. In this case, we assumed that the NDVI value is a weighted average sum of the index values from both soil and vegetation information <ns0:ref type='bibr' target='#b22'>(Li, Fan, &amp; Wang, 2010)</ns0:ref>, which is given as follows:</ns0:p><ns0:p>,</ns0:p><ns0:p>(1)</ns0:p><ns0:formula xml:id='formula_0'>&#119873;&#119863;&#119881;&#119868; = &#119891; &#119907; &#215; &#119873;&#119863;&#119881;&#119868; &#119907;&#119890;&#119892; + (1 -&#119891; &#119907; ) &#215; &#119873;&#119863;&#119881;&#119868; &#119904;&#119900;&#119894;&#119897;</ns0:formula><ns0:p>where NDVI is the vegetation index value of mixed pixels; NDVI veg is the vegetation index of pure vegetation pixels; NDVI soil is the vegetation index value of pure soil pixels; and &#402; v is the vegetation coverage. Thus, the formula for vegetation coverage (&#402; v ) becomes: ,</ns0:p><ns0:p>(2)</ns0:p><ns0:formula xml:id='formula_1'>&#119891; &#119907; = (&#119873;&#119863;&#119881;&#119868; -&#119873;&#119863;&#119881;&#119868; &#119904;&#119900;&#119894;&#119897; ) (&#119873;&#119863;&#119881;&#119868; &#119907;&#119890;&#119892; -&#119873;&#119863;&#119881;&#119868; &#119904;&#119900;&#119894;&#119897; )</ns0:formula><ns0:p>In practice, the parameters can be selected in the following ways. (1) Take different NDVI veg and NDVI soil values for different soil and vegetation types. (2) Use the maximum and minimum NDVIs of the study area, NDVI veg =NDVI max , NDVI soil =NDVI min . (3) Determine the NDVI value of the corresponding pixel based on measured data <ns0:ref type='bibr' target='#b46'>(Li et al., 2015)</ns0:ref>. Under the influence of varying meteorological conditions, vegetation type and distribution, seasons, and other factors, both the NDVI soil and NDVI veg values for different images vary to some extent.</ns0:p><ns0:p>The maximum and minimum values of the given confidence interval are selected, and the confidence value is determined primarily from the image size and clarity. As a comparison, the maximum NDVI images of 2015 and 2019 were extracted. In the NDVI frequency accumulation table, the NDVI with a frequency of 5% was selected for NDVI soil , and the NDVI with a frequency of 95% was selected for NDVI veg . Finally, the vegetation coverage was obtained from Eq. (2).</ns0:p></ns0:div> <ns0:div><ns0:head>Land surface temperature inversion</ns0:head><ns0:p>The LST inversion algorithms for single-infrared-band Landsat 8 OLI remote sensing data are based primary on the radioactive transfer equation (RTE), a universal single-channel algorithm, and a single-window algorithm <ns0:ref type='bibr' target='#b8'>(Ding &amp; Xu, 2008)</ns0:ref>. Therefore, the RTE was selected to invert the LSTs in this study.</ns0:p></ns0:div> <ns0:div><ns0:head>Calculation of specific surface emissivity</ns0:head><ns0:p>Remote sensing images were firstly classified into three types: water bodies, towns and natural surfaces. The specific emissivity of water pixels is 0.995, where other surface emissivity estimates were based on the following formulas <ns0:ref type='bibr' target='#b5'>(Chi, Zeng, &amp; Wang, 2016)</ns0:ref>: ,</ns0:p><ns0:p>(3) &#120576; surface = 0.9625 + 0.0614&#119891; &#119907; -0.0461&#119891; &#119907; 2 , (4) &#120576; building = 0.9589 + 0.086&#119891; &#119907; -0.0671&#119891; &#119907; 2 where &#949; surface and &#949; building represent the specific emissivity of natural surface pixels and urban pixels, respectively.</ns0:p></ns0:div> <ns0:div><ns0:head>Radioactive transfer equation</ns0:head><ns0:p>The RTE is also called the atmospheric correction method. It firstly estimates the impact of the atmosphere on the surface thermal radiation based on the information received by the satellite thermal infrared sensor. This is then subtracted from the total thermal radiation obtained by the sensor. The impact of the atmosphere on the surface can be used to obtain the intensity of surface thermal radiation. Assuming that the surface and the atmosphere have Lambertian properties for thermal radiation, the corresponding LST can be obtained as <ns0:ref type='bibr' target='#b52'>(You, &amp; Yan, 2009;</ns0:ref><ns0:ref type='bibr' target='#b54'>Yue et al., 2019)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_2'>, (<ns0:label>5</ns0:label></ns0:formula><ns0:formula xml:id='formula_3'>)</ns0:formula><ns0:formula xml:id='formula_4'>&#119871; &#120582; = [&#120576; &#8901; &#119861;(&#119879; &#119878; ) + (1 -&#120576;)&#119871; &#8595; ] &#8901; &#120591; + &#119871; &#8593;</ns0:formula><ns0:p>where L &#955; is the intensity of thermal radiation received by the satellite sensor, &#949;(K) is the surface emissivity, T S is the true LST, B(T S ) (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) is the black body brightness corresponding to temperature T S derived from Planck's law, &#964; is the transmittance of the atmosphere at thermal infrared wavelengths, L &#8593; (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) is the atmospheric upward radiance, and L &#8595; (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) is the atmospheric downward radiance. Based on the RTE, the B(T S ) can be obtained as <ns0:ref type='bibr' target='#b42'>(Wu et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b13'>Hou, &amp; Zhang, 2019)</ns0:ref>: , ( <ns0:ref type='formula'>6</ns0:ref>)</ns0:p><ns0:formula xml:id='formula_5'>&#119861;(&#119879; &#119878; ) = [&#119871; &#120582; -&#119871; &#8593; -&#120591; &#8901; (1 -&#120576;)&#119871; &#8595; ]/&#120591; &#8901; &#120576;</ns0:formula><ns0:p>where &#964;, L &#8593; (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) and L &#8595; (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) were determined from the official NASA website (http://atmcorr.gsfc.nasa.gov/) by inputting the imaging time, latitude and longitude, air pressure and other relevant information to the study area. After estimating the of black body radiance B(T S ), which is the same as the real temperature on the ground, the inverse function of Planck's law gives the real temperature on the ground as <ns0:ref type='bibr' target='#b3'>(Chen, 2014)</ns0:ref> :</ns0:p><ns0:formula xml:id='formula_6'>, (<ns0:label>7</ns0:label></ns0:formula><ns0:formula xml:id='formula_7'>)</ns0:formula><ns0:formula xml:id='formula_8'>&#119879; &#119878; = &#119870; 2 /&#119897;&#119899; ( &#119870; 1 &#119861;(&#119879; &#119878; ) + 1 )</ns0:formula><ns0:p>where K 1 and K 2 are constants obtained by querying the Landsat metadata file. In this case, K 1 =774.8853 and K 2 =1321.0789 for Landsat 8 TIRS band 10.</ns0:p></ns0:div> <ns0:div><ns0:head>Normalized temperature index and temperature classification</ns0:head><ns0:p>The ecological environment of coal mining areas is damaged to varying degrees, this changes their LSTs and causes a series of significant ecological effects and environmental problems, such as vegetation degradation and soil erosion <ns0:ref type='bibr' target='#b10'>(Dutta &amp; Agrawal, 2003;</ns0:ref><ns0:ref type='bibr' target='#b62'>Zhou &amp; Zhang, 2005)</ns0:ref>. We used the urban heat island effect to explore the impact of coal mining activities on LSTs <ns0:ref type='bibr' target='#b51'>(Ye et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b23'>Li et al., 2019)</ns0:ref>. The formula for the normalized temperature index is:</ns0:p><ns0:formula xml:id='formula_9'>, (8) &#119879; &#119903; = &#120549;&#119879; &#119879; &#119903;&#119886;&#119899;&#119892;&#119890; = &#119879; -&#119879; &#119898;&#119894;&#119899; &#119879; max -&#119879; min</ns0:formula><ns0:p>where T r is the normalized temperature index, T is the temperature at any spatial position in the region, T max and T min are the highest and lowest temperature in the region, respectively.</ns0:p><ns0:p>The method of equal intervals is used to divide the temperature based on the site conditions and existing research <ns0:ref type='bibr'>(Sheng et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b19'>Jia &amp; Liu, 2006)</ns0:ref>. Once the maximum and minimum values of the inversion temperature are taken as endpoints, the temperature is divided into five equal-spaced intervals. These are a low-temperature zone, a low-middle-temperature zone, a middle-temperature zone, a middle-high-temperature zone, and a high-temperature zone. The normalized temperature indices for these levels were 0.0-0.2, 0.2-0.4, 0.4-0.6, 0.6-0.8, and 0.8-1.0, respectively (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). Analyzing changes in the LST index at different distances from the mine allows evaluating the intensity and range of the heat island effect as caused by coal-mining activities.</ns0:p></ns0:div> <ns0:div><ns0:head>Analytical method of factors affecting land surface temperature</ns0:head><ns0:p>The terrain over the study area is relatively flat, which facilitates farming, town construction, and coal mining activities. We analyzed the spatial differentiation of LSTs in this area, which was linked to land use, vegetation coverage and coal mining activities.</ns0:p></ns0:div> <ns0:div><ns0:head>The influence of land-use classification on land surface temperature</ns0:head><ns0:p>The area and proportion of different types of land use were counted separately. Subsequently, the land-use and the LST maps were superimposed to obtain statistical data on the LSTs of various land-use types.</ns0:p></ns0:div> <ns0:div><ns0:head>The influence of vegetation coverage on land surface temperature</ns0:head><ns0:p>A profile analysis more intuitively reflected the relationship between changes in LST and vegetation coverage at a given geographical location. Using the interpolation line function in ArcGIS 10.5 to view profile values of LST and vegetation coverage from 2015 and 2019 to compare and analyze their associated changes along profiles to evaluate the relationships between these variables.</ns0:p></ns0:div> <ns0:div><ns0:head>The influence of coal mining activities on land surface temperature</ns0:head></ns0:div> <ns0:div><ns0:head>The influence of patch area</ns0:head><ns0:p>Firstly, all mining areas within a distance of 1500 m from the edge of the study area were screened. These selected mining area patches were then counted and grouped based on area. We then combined these data with our LST inversion to determine the maximum, minimum, and average LSTs for different patches. Finally, the influence of these mining land patches on the LSTs were evaluated.</ns0:p></ns0:div> <ns0:div><ns0:head>The influence of buffer range</ns0:head><ns0:p>Buffers with a range of 100-1500 m at intervals of 100 m were set for each of the patches. The average LST in each buffer zone was extracted, and the trends in the LSTs at varying distances from the mining area were analyzed.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Land surface temperature inversion</ns0:head><ns0:p>The LST results for the Jiguan, Didao and Chengzihe Districts of Jixi in 2015 and 2019 are shown in Fig. <ns0:ref type='figure'>2</ns0:ref> and Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>. The temperatures in 2015 were in general higher than those in 2019. The average LST over the entire study area was 25.64 &#8451; in 2015 and 22.10 &#8451; in 2019. There is a similarity in the spatial distribution patterns of their LSTs. High temperatures are concentrated in the south-central and southeast parts of the study area, while the temperatures in the west and north are relatively low. In these two years, the average LST in the Jiguan District was higher than averages in the other two districts, but its highest temperature was lower than the maximum recorded in the Didao and Chengzihe Districts. The highest temperatures over the entire study area were 42.29 &#8451;, which was recorded at Shenghe Coal Mine in the Didao District. Likewise, the highest temperature in the Chengzihe District was recorded at Chengshan Coal Mine. Thus, mining areas had much higher LSTs than average. While only two years were selected for the analysis, similar results validate the conclusions.</ns0:p><ns0:p>The LSTs from 2015 and 2019 were normalized and divided into five levels, as shown in Fig. <ns0:ref type='figure' target='#fig_1'>3</ns0:ref> and Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref>. The LSTs in the study area were assigned primarily to the low-temperature, lowmiddle-temperature, and middle-temperature zones, which covered the LST range of 19.16-33.04 &#8451; in 2015 and 16.29-29.37 &#8451; in 2019. Among them, the low-middle-temperature zone had the largest area as it accounted for more than 70% of the total study area. The hightemperature and middle-high-temperature zones had smaller areas. The high-temperature zone was distributed primarily within the Didao and Chengzihe Districts. The Shenghe Coal Mine accounted for 53.08% of the total area of the high-temperature zone in 2015 and rose to 59.04% in 2019. The proportion of the Chengshan Coal Mine in the total area of the high-temperature zone increased from 8.17% to 34.47% over these four years. Meanwhile, the low-temperature and low-middle-temperature zones were distributed mostly in the Didao and Chengzihe Districts, giving a large temperature difference between them. Therefore, local heat island effects were obvious within the study area.</ns0:p></ns0:div> <ns0:div><ns0:head>Land-use classification</ns0:head><ns0:p>Land-use types in the Jiguan, Didao, and Chengzihe Districts of Jixi in 2015 and 2019 are shown in Fig. <ns0:ref type='figure' target='#fig_2'>4</ns0:ref> and Table <ns0:ref type='table' target='#tab_7'>4</ns0:ref>. From 2015 to 2019, the area of forest land increased while the area of cultivated land decreased. However, the dominant land-use types in the study area are still forest land and cultivated land. The forest land is distributed mostly in the northern part of the study area, while the cultivated land is distributed in the middle and southern parts. Construction land is concentrated in the Jiguan District, which increased significantly from 109.94 km 2 to 133.69 km 2 in the four considered years. The mining land is defined primarily by the Shenghe Coal Mine in the Didao District and the Chengshan Coal Mine in the Chengzihe District. The accuracy of the land-use classification was verified by establishing a confusion matrix. The matrix showed that the Kappa coefficients of the land-use maps in the interpreted periods are all above 0.8, which meets the accuracy requirements for this study (Table <ns0:ref type='table' target='#tab_10'>5</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Vegetation coverage</ns0:head><ns0:p>The remote sensing images of the study area were processed according to the mixed pixel decomposition method to obtain the vegetation coverage of the Jiguan, Didao, and Chengzihe District of Jixi (Fig. <ns0:ref type='figure'>5</ns0:ref>). The construction land in the eastern Jiguan District, Shenghe Coal Mine in the Didao District and Chengshan Coal Mine in the Chengzihe District had the lowest vegetation coverage. However, ongoing urbanization and coal mining activities have markedly affected vegetation coverage in many other areas as well.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and land-use types</ns0:head><ns0:p>The main land types in the low-temperature and low-middle-temperature zone are water areas, forest land, grassland and cultivated land. The main land types in the high-temperature, middlehigh-temperature, and middle-temperature zones are construction land and mining land. There are large difference in the average LSTs among these land-use types (Table <ns0:ref type='table' target='#tab_15'>6</ns0:ref>). The average LSTs for mining land, construction land and grassland were higher than the average LST for the study area. Among them, mining land had the highest average LSTs (33.33 &#8451; in 2015 and 29.63 &#8451; in 2019), yielding temperature anomalies of 7.69 &#8451;in 2015 and 7.53 &#8451; in 2019. The water area had the lowest average <ns0:ref type='bibr'>LSTs (21.72 &#8451; in 2015 and</ns0:ref><ns0:ref type='bibr'>19.31 &#8451; in 2019)</ns0:ref>. At the same time, the temperature standard deviation within the mining land was also relatively large, with a difference of 18.02 &#8451; between the minimum and maximum temperatures.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and vegetation coverage</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed An east-west transect was drawn across the study are, and the data from 2019 were used to analyze changes in the LSTs with vegetation coverage. Every 25 pixel points on the profile were assigned to a group, and the average value of the vegetation coverage and LST in each group was calculated to obtain 56 data sets. Finally, a linear fit was performed between the vegetation coverage and average LST, and the coefficient of determination was assessed (Fig. <ns0:ref type='figure' target='#fig_4'>6</ns0:ref>). Areas with low vegetation coverage were associated with higher LSTs. In addition, as vegetation coverage decreased, the LSTs increased. The trends in LST and vegetation coverage were opposite with reciprocal change patterns.</ns0:p><ns0:p>The linear fit of the average LST and vegetation coverage (Fig. <ns0:ref type='figure' target='#fig_5'>7</ns0:ref>) shows that if the vegetation coverage increases by 0.1, the average LST is expected to decrease by approximately 0.75 &#8451;. This constitutes a strong negative relationship between the LST and vegetation coverage. Using the SPSS 24 (IBM, Corp., Armonk, NY, USA) indicated a correlation coefficient of R = &#8722;0.780. This indicates a significant correlation at the 0.01 confidence level (both sides). Thus, green vegetation has a significant cooling effect on the land surface.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and coal mining activities</ns0:head><ns0:p>This study mainly considers spatial variations when exploring the correlation between the LST and mining activities. Therefore, the data of the most recent year (2019) is selected for the analysis, and the spatial distribution of the LST is analyzed based on the patch area and buffer sizes.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and patch area of mining lands</ns0:head><ns0:p>The mining areas were grouped based on patch area after screening them within 1500 m of the edge of the study area. The maximum, minimum and average LSTs of each patch were calculated from the 52 data sets (Table <ns0:ref type='table'>7</ns0:ref>). Correlations among the average patch area and the average and maximum patch temperatures were analyzed using SPSS 24. Our analysis indicates that the patch was strongly positively correlated with the average and maximum patch temperatures.</ns0:p><ns0:p>Correlation between the patch area and average patch temperature (Fig. <ns0:ref type='figure' target='#fig_6'>8</ns0:ref>) yielded R = 0.571. This indicates a significant correlation at the 0.01 confidence level (both sides). The determination coefficient of the fit logarithmic function was R 2 = 0.487, indicating that larger patch sizes promote a greater average patch temperature. Within 200,000 m 2 , the average patch temperature increases rapidly with the size of the patch area. Once above 200,000 m 2 , the average patch temperature increases more slowly.</ns0:p><ns0:p>The correlation between the patch area and maximum patch temperature (Fig. <ns0:ref type='figure' target='#fig_7'>9</ns0:ref>) yielded R = 0.645. This indicates a significant correlation at the 0.01 confidence level (both sides). The determination coefficient of the linear fit was R 2 = 0.415, indicating that larger patch sizes promote a greater maximum patch temperature. If the patch area of mining land increases by 100,000 m 2 , the maximum patch temperature will increase by approximately 0.81&#8451;.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and various buffer sizes</ns0:head><ns0:p>The schematic diagram of buffer zone in mining land patch is shown in Fig 10 <ns0:ref type='figure'>.</ns0:ref> A correlation analysis was performed on average patch area, average patch temperature, maximum patch temperature of mining land and the average LST in buffer zones at 100-1500 m reviewed at 100m intervals (Table <ns0:ref type='table' target='#tab_18'>8</ns0:ref>). The temperature of the buffer zones within 0-100 m was strongly correlated with the patch area, average patch temperature, and maximum patch temperature of the mining land. In the 100-200 m buffer zone, the correlation between the temperature and the average area was not significant. Therefore, a higher correlation was found for the entire buffer zone with the average and maximum patch temperatures, while a lower correlation was found with the patch area. Thus, the correlation between the temperature in the buffer zone and the average patch temperature was most relevant.</ns0:p><ns0:p>To further study the correspondence between the average patch temperature of mining land and the temperature in the buffer zones, the 52 data sets were sorted based on their average patch temperatures from smallest to largest. Each of the 13 groups was then compiled into a new group. The average number and the average temperature of the corresponding buffer zone in each new group were calculated to obtain four new data sets (Table <ns0:ref type='table' target='#tab_20'>9</ns0:ref>).</ns0:p><ns0:p>Figure <ns0:ref type='figure' target='#fig_0'>11</ns0:ref> shows that the further the buffer zone was from the mine land patch, the lower its temperature. In 0-200 m buffer zones, the average temperature changed drastically, while the average temperature outside the 200 m zone varied little. The range of this heating effect is approximately 700 m in Group 1, 1200 m in Group 2 and 3, and more than 1400 m in Group 4. Therefore, a larger average patch temperature in the mining land causes a higher temperature in its buffer zone, and the greater the scope of its influence.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head>Impact of coal mining activities on surface temperatures</ns0:head><ns0:p>As the largest coal city in Heilongjiang Province, Jixi has always utilized coal as its leading industry. The main types of coal mining wasteland in Jixi City include mining subsidence, land occupation, polluted wasteland, and excavated land, which account for 0.48%, 82.0%, 6.82%, and 10.71% of the total coal mining wasteland, respectively <ns0:ref type='bibr'>(Di, Guan &amp; Zheng, 2015)</ns0:ref>. Coal mining activities generate a significant amount of heat. Thus, regional heating within the city has intensified when coupled with their high-energy consumption and high-heat producing enterprises <ns0:ref type='bibr' target='#b17'>(Hu, Zhao &amp; Dong, 2010)</ns0:ref>. The ongoing economic development of mining areas has increased both the population density and heat production from urban infrastructure.</ns0:p><ns0:p>The correlation between LST and coal mining activities has resulted in larger mining lands with higher average and maximum patch temperatures. The available literature has shown that the size, shape, number, and boundary properties of these patches affect their energy transmissions. According to landscape ecological theory, the size and shape of these patches also affect their energy accumulation. Likewise, some researchers have recognized that larger patches of construction land have higher degrees of aggregation, more regular shapes, higher LSTs, and more significant heat island effects <ns0:ref type='bibr' target='#b53'>(Yu, 2006;</ns0:ref><ns0:ref type='bibr' target='#b11'>Fu, 2001;</ns0:ref><ns0:ref type='bibr' target='#b44'>Xie, Wang &amp; Fu, 2011;</ns0:ref><ns0:ref type='bibr' target='#b46'>Xu et al., 2015)</ns0:ref>. Some studies have analyzed different types of disturbances at the interior of mining lands, among which dumps, opencast coal pits, and industrial centers have higher contributions to local warming <ns0:ref type='bibr' target='#b44'>(Xie et al., 2011;</ns0:ref><ns0:ref type='bibr'>Liu J, 2016)</ns0:ref>. Exposed coal and coal gangue easily absorb heat and cause increased temperatures, while piled coal gangue hills are prone to heat and spontaneous combustion <ns0:ref type='bibr'>(Hao, 2011)</ns0:ref>. Therefore, many factors cause high temperatures in mining land.</ns0:p><ns0:p>Quantitative research on the impact of mining land indicates a strong warming effect within a buffer zone of 0-200 m around mining land patches. As the distance from the mining land increases, the warming effects gradually weakens. Mining land patches with higher average patch temperatures have larger temperature-affected buffer zones. Changes in the local meteorological conditions, such as temperature rise, affect local species, which impacts the ecological conditions of the entire region. However, the strength of the warming effect and the size of its influence range are not only related to the distance from the mining land patch but may also be related to the average temperature of the entire area during the analysis <ns0:ref type='bibr' target='#b28'>(Liao, 2009)</ns0:ref>. This specific correlation requires further study.</ns0:p><ns0:p>To date, regulations on the ecological and environmental protection are aimed only at the ecological and environmental indicators within the mining area, which cannot achieve regional ecological protection. Although it seems intuitive that coal production enterprises or units engaged in corresponding activities have taken the responsibility of protecting the ecology and environment, this does not cover the entire affected area of coal mining production activities. To protect the ecological quality of the area while developing coal resources, the scope of environmental protection in mining areas should be defined more scientifically and rationally.</ns0:p></ns0:div> <ns0:div><ns0:head>Impact of different land-use types on surface temperature</ns0:head><ns0:p>Our results show that land-use types have a dominating impact on the LST. The LSTs of the Jiguan, Didao, and Chengzihe District of Jixi were primarily within the range of 16.29-42.29 &#8451; in the two considered years. The low-middle-temperature zone had the largest area, which accounted for 70.53% and 72.21% of the total area. The low-temperature zone was distributed primarily over water areas, forest lands and cultivated lands. The high-temperature zone was distributed mostly over the construction land and mining land, especially the Shenghe Coal Mine in the Didao District and the Chengshan Coal Mine in the Chengzihe District.</ns0:p><ns0:p>The temperatures in 2019 were generally lower than those in 2015. From a normalized comparison, it is seen that the high-temperature and low-temperature zones increased in 2019. Along with the clustered development of mining land patches, the land surface temperature shows a polarizing trend. The expansion of some high-temperature zones may be due to the continued development of coal mines. The increased low-temperature areas may be due to the reclamation and restoration of vegetation in mining areas. Based on governmental planning ('Mineral Resources Planning of Jixi City (2016-2020)' and 'Special Planning for Reclamation and Utilization of Desert Land of Industrial Mining Area and Mining Subsidence Area in Jixi City (2014-2020)') from 2015 to 2019, the coal industry wastelands in Chengzihe and Didao Districts were treated to a certain extent, and the reclaimed land was converted into cultivated land, forest land, and construction land. These lands will be used for agricultural production, creating recreational landscapes, and improving the ecological environment.</ns0:p><ns0:p>In recent years, the development of coal resources in Jixi has been rapid. Additionally, the spatial distribution of mines has also changed <ns0:ref type='bibr' target='#b50'>(Yang, 2013)</ns0:ref>. Construction and mining activities have reduced the 'cooling' land-use types, such as forest and cultivated lands, and replaced them with 'warming' types, like construction and mining lands. The available literature has shown that with changes in land-use types, natural vegetation has been replaced by impervious concrete and construction land, which has caused significant changes like heat radiation from the underlying city surface <ns0:ref type='bibr'>(Wang et al., 2013)</ns0:ref>. These man-made surfaces have a strong light absorptive effect and can quickly raise the local LST <ns0:ref type='bibr' target='#b16'>(Hien et al., 2011)</ns0:ref>. In addition, building facades can reflect light multiple times, heating the near-surface atmosphere and cause LSTs to rise significantly <ns0:ref type='bibr' target='#b34'>(Miao et al., 2009)</ns0:ref>. Among the six considered land-use types, the LSTs of water area, forest land, and cultivated land were lower than the average LST for the study area. Water-permeable areas of the study region, such as water areas and forest land, ensure efficient heat exchange between the soil and the atmosphere. Water can evaporate, which absorbs heat in the environment and has an overall cooling effect <ns0:ref type='bibr'>(Zhang et al., 2013)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Impact of vegetation coverage on land surface temperatures</ns0:head><ns0:p>Our coupling analysis showed that changes in vegetation coverage are very important factors that affecting ecological status change. There is a significant negative correlation between LST and vegetation coverage, which has also been confirmed by other works <ns0:ref type='bibr' target='#b20'>(Jiang, Zeng &amp; Zeng, 2015;</ns0:ref><ns0:ref type='bibr' target='#b9'>Duan &amp; Zhang, 2012;</ns0:ref><ns0:ref type='bibr' target='#b40'>Wu, Xu &amp; Tan, 2007;</ns0:ref><ns0:ref type='bibr' target='#b55'>Yue, Xu &amp; Xu, 2006)</ns0:ref>. As vegetation blocks sunlight, it reduces the amount of solar radiation that reaches the surface, while plant transpiration also reduces the LST <ns0:ref type='bibr' target='#b6'>(Cui, Li &amp; Ji, 2018)</ns0:ref>. In areas with high vegetation coverage, the LST was lower than in other areas, illustrating the degree to which vegetation could effectively alleviate heat island effect. Therefore, municipal bodies should carefully consider the balance between ecological protection and economic development. The focus should be on vegetation restoration and environmental governance in areas where heat emissions are concentrated, such as abandoned mine sites and barren areas. Meanwhile, increasing the proportion of green space, improving the diversity and complexity of the landscape, and dividing the impervious surface with vegetation when developing urban construction land and coal mines can significantly reduce the LST and alleviate heat island effects.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Our findings show that coal mining activities and urban expansion are the primary factors affecting LSTs. These two factors change land-use types and vegetation coverage, which results in an abnormal heat flux. There were large differences in the LSTs among the various land-use types in Jixi City. The LSTs for the considered land-use types were ranked from high to low, as follows: mining land &gt; construction land &gt; grassland &gt; cultivated land &gt; forest land &gt; water area. The average LST difference between the mining land and water area was more than 10 &#8451; each year.</ns0:p><ns0:p>Correlations between LST and vegetation coverage indicate that they have a significant negative relationship. The LST was lower in areas with higher vegetation coverage than in other areas. For every 0.1 increase in vegetation coverage, the surface temperature is expected to drop by approximately 0.75 &#8451;, indicating the extent to which vegetation can effectively alleviate warming effects.</ns0:p><ns0:p>The correlation between the LST and coal mining activities indicates the patch area of the mining land has a significant positive correlation with both the average and maximum patch temperatures. The average patch temperature shows a logarithmic increase with the growth of the patch area; thus, the average patch temperature increases significantly within 200,000 m 2 . The maximum patch temperature shows a linear increase with the growth of the patch area; thus, the maximum patch temperature increases by approximately 0.81 &#8451; for every 100,000 m 2 increase in the patch area of mining land. A higher correlation was found between the average patch temperature and the temperature in the buffer zone. This study found that the higher the average patch temperature of mining land, the higher the temperature in its buffer zone, and the greater the scope of its influence. As the distance from the mining land increased, its heating effect weakened.</ns0:p><ns0:p>Full consideration should be given to vegetation restoration in mining areas to reduce the warming effect from coal mining activities, especially in abandoned mining land, by increasing the total vegetation coverage in the study area. The existing large coal mine land patches need to be divided by plants or water areas. Thus, the scope of environmental protection in mining areas needs to be correctly defined. Meanwhile, in future urban layouts, downtown areas should maintain a proper distance from coal mining land. This study provides a useful reference to explore the warming effects caused by coal mining activities and the definition of its influence scope.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref> The relationship between the normalized temperature index values and assigned temperature grades PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 2</ns0:note><ns0:p>Land surface temperature (&#176;C) results for the three districts of Jixi in 2019</ns0:p><ns0:p>The legend has been noted in the figure.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure 3</ns0:note><ns0:note type='other'>Figure 4</ns0:note><ns0:note type='other'>Figure 6</ns0:note><ns0:note type='other'>Figure 7</ns0:note><ns0:note type='other'>Figure 8</ns0:note><ns0:note type='other'>Figure 9</ns0:note><ns0:note type='other'>Figure 10</ns0:note><ns0:note type='other'>Figure 11</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 Figure 1</ns0:head><ns0:label>11</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3 Spatial distribution of land surface temperature levels of the study area in 2015 and 2019</ns0:figDesc><ns0:graphic coords='41,42.52,224.62,525.00,218.25' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4 Land-use types of the study area in 2015 and 2019</ns0:figDesc><ns0:graphic coords='42,42.52,204.37,525.00,218.25' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 5 Figure 5</ns0:head><ns0:label>55</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6 Variation in land surface temperature (LST) and vegetation coverage in pixel groups (1-56) along an E-W profile</ns0:figDesc><ns0:graphic coords='44,42.52,199.12,525.00,216.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 7</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7 Correlation between land surface temperature (LST) and vegetation coverage of the study area</ns0:figDesc><ns0:graphic coords='45,42.52,199.12,525.00,258.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8 Correlation between patch area and average patch temperature of mining lands</ns0:figDesc><ns0:graphic coords='46,42.52,224.62,525.00,258.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 9</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Figure 9 Correlation between patch area and maximum patch temperature of mining lands</ns0:figDesc><ns0:graphic coords='47,42.52,224.62,525.00,258.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 10</ns0:head><ns0:label>10</ns0:label><ns0:figDesc>Figure 10 Schematic diagram of buffer zone in mining land patch</ns0:figDesc><ns0:graphic coords='48,42.52,204.37,525.00,376.50' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 11</ns0:head><ns0:label>11</ns0:label><ns0:figDesc>Figure 11 Variation of land surface temperature (LST) with bu &#161;&#162; &#163;&#164;&#165;&#161; &#164;&#166; &#167;&#168;&#165;&#168;&#165;&#169; &#165;</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='40,42.52,204.37,525.00,218.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 The relationship between the normalized temperature index values and assigned temperature grades Normalized temperature index Temperature grade</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>0.0-0.2</ns0:cell><ns0:cell>Low temperature zone</ns0:cell></ns0:row><ns0:row><ns0:cell>0.2-0.4</ns0:cell><ns0:cell>Low-middle temperature zone</ns0:cell></ns0:row><ns0:row><ns0:cell>0.4-0.6</ns0:cell><ns0:cell>Middle temperature zone</ns0:cell></ns0:row><ns0:row><ns0:cell>0.6-0.8</ns0:cell><ns0:cell>Middle-high temperature zone</ns0:cell></ns0:row><ns0:row><ns0:cell>0.8-1.0</ns0:cell><ns0:cell>High temperature zone</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Statistics on LST for the study area in 2015 and 2019</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)Manuscript to be reviewed 1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 2 Statistics on LST for the study area in 2015 and 2019 Land surface temperature/&#8451;</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Range</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>2015</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>2019</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>MEAN</ns0:cell><ns0:cell>MIN</ns0:cell><ns0:cell>MAX</ns0:cell><ns0:cell>STD</ns0:cell><ns0:cell>MEAN</ns0:cell><ns0:cell>MIN</ns0:cell><ns0:cell>MAX</ns0:cell><ns0:cell>STD</ns0:cell></ns0:row><ns0:row><ns0:cell>Jiguan District</ns0:cell><ns0:cell>27.16</ns0:cell><ns0:cell>21.58</ns0:cell><ns0:cell>38.97</ns0:cell><ns0:cell>2.52</ns0:cell><ns0:cell>23.24</ns0:cell><ns0:cell>17.42</ns0:cell><ns0:cell>33.64</ns0:cell><ns0:cell>2.23</ns0:cell></ns0:row><ns0:row><ns0:cell>Didao District</ns0:cell><ns0:cell>25.23</ns0:cell><ns0:cell>19.16</ns0:cell><ns0:cell>42.29</ns0:cell><ns0:cell>1.92</ns0:cell><ns0:cell>21.75</ns0:cell><ns0:cell>17.18</ns0:cell><ns0:cell>38.08</ns0:cell><ns0:cell>1.63</ns0:cell></ns0:row><ns0:row><ns0:cell>Chengzihe District</ns0:cell><ns0:cell>25.53</ns0:cell><ns0:cell>19.45</ns0:cell><ns0:cell>39.13</ns0:cell><ns0:cell>2.48</ns0:cell><ns0:cell>22.34</ns0:cell><ns0:cell>16.29</ns0:cell><ns0:cell>35.26</ns0:cell><ns0:cell>2.14</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>25.64</ns0:cell><ns0:cell>19.16</ns0:cell><ns0:cell>42.29</ns0:cell><ns0:cell>2.28</ns0:cell><ns0:cell>22.10</ns0:cell><ns0:cell>16.29</ns0:cell><ns0:cell>38.08</ns0:cell><ns0:cell>1.95</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>LST normalization results for the study area in 2015 and 2019</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 3 LST normalization results for the study area in 2015 and 2019 2015 2019 Temperature grade</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell>Normalized</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>temperature</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>index</ns0:cell><ns0:cell>LST / &#8451;</ns0:cell><ns0:cell>Percentage</ns0:cell><ns0:cell>LST / &#8451;</ns0:cell><ns0:cell>Percentage</ns0:cell></ns0:row><ns0:row><ns0:cell>Low</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.0-0.2</ns0:cell><ns0:cell>19.16-23.78</ns0:cell><ns0:cell>18.19%</ns0:cell><ns0:cell>16.29-20.65</ns0:cell><ns0:cell>19.31%</ns0:cell></ns0:row><ns0:row><ns0:cell>temperature zone</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Low-middle temperature zone</ns0:cell><ns0:cell>0.2-0.4</ns0:cell><ns0:cell>23.78-28.41</ns0:cell><ns0:cell>70.53%</ns0:cell><ns0:cell>20.65-25.01</ns0:cell><ns0:cell>72.21%</ns0:cell></ns0:row><ns0:row><ns0:cell>Middle</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.4-0.6</ns0:cell><ns0:cell>28.41-33.04</ns0:cell><ns0:cell>10.34%</ns0:cell><ns0:cell>25.01-29.37</ns0:cell><ns0:cell>7.79%</ns0:cell></ns0:row><ns0:row><ns0:cell>temperature zone</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Middle-high</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.6-0.8</ns0:cell><ns0:cell>33.04-37.66</ns0:cell><ns0:cell>0.90%</ns0:cell><ns0:cell>29.37-33.72</ns0:cell><ns0:cell>0.66%</ns0:cell></ns0:row><ns0:row><ns0:cell>temperature zone</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>High</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.8-1.0</ns0:cell><ns0:cell>37.66-42.29</ns0:cell><ns0:cell>0.04%</ns0:cell><ns0:cell>33.72-38.08</ns0:cell><ns0:cell>0.03%</ns0:cell></ns0:row><ns0:row><ns0:cell>temperature zone</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>0.0-1.0</ns0:cell><ns0:cell>19.16-42.29</ns0:cell><ns0:cell>100.00%</ns0:cell><ns0:cell>16.29-38.08</ns0:cell><ns0:cell>100.00%</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 4 (on next page)</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_8'><ns0:head>Table 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Land-use structure for the study area in 2015 and 2019</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_9'><ns0:head>Table 4 Land-use structure for the study area in 2015 and 2019 2015 2019 Land-use</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell>Area / km 2</ns0:cell><ns0:cell>Percentage / %</ns0:cell><ns0:cell>Area / km 2</ns0:cell><ns0:cell>Percentage / %</ns0:cell></ns0:row><ns0:row><ns0:cell>Forest land</ns0:cell><ns0:cell>294.07</ns0:cell><ns0:cell>35.52%</ns0:cell><ns0:cell>304.18</ns0:cell><ns0:cell>36.74%</ns0:cell></ns0:row><ns0:row><ns0:cell>Grassland</ns0:cell><ns0:cell>52.95</ns0:cell><ns0:cell>6.39%</ns0:cell><ns0:cell>80.4</ns0:cell><ns0:cell>9.71%</ns0:cell></ns0:row><ns0:row><ns0:cell>Construction land</ns0:cell><ns0:cell>109.94</ns0:cell><ns0:cell>13.28%</ns0:cell><ns0:cell>133.69</ns0:cell><ns0:cell>16.15%</ns0:cell></ns0:row><ns0:row><ns0:cell>Cultivated land</ns0:cell><ns0:cell>357.39</ns0:cell><ns0:cell>43.17%</ns0:cell><ns0:cell>295.07</ns0:cell><ns0:cell>35.64%</ns0:cell></ns0:row><ns0:row><ns0:cell>Mining land</ns0:cell><ns0:cell>7.10</ns0:cell><ns0:cell>0.86%</ns0:cell><ns0:cell>6.76</ns0:cell><ns0:cell>0.82%</ns0:cell></ns0:row><ns0:row><ns0:cell>Water area</ns0:cell><ns0:cell>6.42</ns0:cell><ns0:cell>0.78%</ns0:cell><ns0:cell>7.77</ns0:cell><ns0:cell>0.94%</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>827.87</ns0:cell><ns0:cell>100.00%</ns0:cell><ns0:cell>827.87</ns0:cell><ns0:cell>100.00%</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_10'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_11'><ns0:head>Table 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Accuracy evaluation of land use classification for the study area in 2015 and 2019</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_13'><ns0:head>Table 5 Accuracy evaluation of land use classification for the study area in 2015 and 2019 2015 Land-use Forest land Grassland Construction land Cultivated land Mining land Water area Total</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Forest land</ns0:cell><ns0:cell>1646</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>1648</ns0:cell></ns0:row><ns0:row><ns0:cell>Grassland</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>150</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>150</ns0:cell></ns0:row><ns0:row><ns0:cell>Construction land</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>2406</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>2409</ns0:cell></ns0:row><ns0:row><ns0:cell>Cultivated land</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>1737</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>1743</ns0:cell></ns0:row><ns0:row><ns0:cell>Mining land</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>346</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>363</ns0:cell></ns0:row><ns0:row><ns0:cell>Water area</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>319</ns0:cell><ns0:cell>319</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>1649</ns0:cell><ns0:cell>156</ns0:cell><ns0:cell>2425</ns0:cell><ns0:cell>1737</ns0:cell><ns0:cell>346</ns0:cell><ns0:cell>319</ns0:cell><ns0:cell>6632</ns0:cell></ns0:row><ns0:row><ns0:cell>Producers Accuracy</ns0:cell><ns0:cell>99.82</ns0:cell><ns0:cell>96.15</ns0:cell><ns0:cell>99.22</ns0:cell><ns0:cell>1000</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>98.46</ns0:cell><ns0:cell>-</ns0:cell></ns0:row><ns0:row><ns0:cell>Users Accuracy</ns0:cell><ns0:cell>99.88</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>99.67</ns0:cell><ns0:cell>99.66</ns0:cell><ns0:cell>95.32</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>-</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>2019</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_14'><ns0:head>Land-use Forest land Grassland Construction land Cultivated land Mining land Water area Total</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>860</ns0:cell><ns0:cell>83</ns0:cell><ns0:cell>1765</ns0:cell><ns0:cell>866</ns0:cell><ns0:cell>284</ns0:cell><ns0:cell>231</ns0:cell><ns0:cell>4089</ns0:cell></ns0:row><ns0:row><ns0:cell>Producers Accuracy</ns0:cell><ns0:cell>99.77</ns0:cell><ns0:cell>44.58</ns0:cell><ns0:cell>96.88</ns0:cell><ns0:cell>94.8</ns0:cell><ns0:cell>92.61</ns0:cell><ns0:cell>92.4</ns0:cell><ns0:cell>-</ns0:cell></ns0:row><ns0:row><ns0:cell>Users Accuracy</ns0:cell><ns0:cell>96.08</ns0:cell><ns0:cell>45.12</ns0:cell><ns0:cell>96.07</ns0:cell><ns0:cell>95.8</ns0:cell><ns0:cell>99.25</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>-</ns0:cell></ns0:row><ns0:row><ns0:cell cols='6'>Note: In 2015, Overall Classification Accuracy=99.50%; Overall Kappa Statistics=0.9932;</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='6'>In 2019, Overall Classification Accuracy=95.42%; Overall Kappa Statistics=0.9361.</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Forest land</ns0:cell><ns0:cell>858</ns0:cell><ns0:cell>35</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>893</ns0:cell></ns0:row><ns0:row><ns0:cell>Grassland</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>37</ns0:cell><ns0:cell>34</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>82</ns0:cell></ns0:row><ns0:row><ns0:cell>Construction land</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>1710</ns0:cell><ns0:cell>35</ns0:cell><ns0:cell>18</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>1763</ns0:cell></ns0:row><ns0:row><ns0:cell>Cultivated land</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>821</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>855</ns0:cell></ns0:row><ns0:row><ns0:cell>Mining land</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>263</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>265</ns0:cell></ns0:row><ns0:row><ns0:cell>Water area</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>231</ns0:cell><ns0:cell>231</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_15'><ns0:head>Table 6 (on next page)</ns0:head><ns0:label>6</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_16'><ns0:head>Table 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Statistics on LST of different land-use types in 2015 and 2019</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_17'><ns0:head>Table 6 Statistics on LST of different land-use types in 2015 and 2019 Land surface temperature/&#8451;</ns0:head><ns0:label>6</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Land use types</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>2015</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>2019</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>MEAN</ns0:cell><ns0:cell>MIN</ns0:cell><ns0:cell>MAX</ns0:cell><ns0:cell>STD</ns0:cell><ns0:cell>MEAN</ns0:cell><ns0:cell>MIN</ns0:cell><ns0:cell>MAX</ns0:cell><ns0:cell>STD</ns0:cell></ns0:row><ns0:row><ns0:cell>Forest land</ns0:cell><ns0:cell>23.95</ns0:cell><ns0:cell>20.79</ns0:cell><ns0:cell>30.89</ns0:cell><ns0:cell>1.01</ns0:cell><ns0:cell>21.07</ns0:cell><ns0:cell>17.38</ns0:cell><ns0:cell>26.41</ns0:cell><ns0:cell>0.97</ns0:cell></ns0:row><ns0:row><ns0:cell>Grassland</ns0:cell><ns0:cell>26.55</ns0:cell><ns0:cell>21.94</ns0:cell><ns0:cell>36.27</ns0:cell><ns0:cell>1.45</ns0:cell><ns0:cell>23.21</ns0:cell><ns0:cell>18.77</ns0:cell><ns0:cell>30.56</ns0:cell><ns0:cell>1.43</ns0:cell></ns0:row><ns0:row><ns0:cell>Construction land</ns0:cell><ns0:cell>29.12</ns0:cell><ns0:cell>20.59</ns0:cell><ns0:cell>41.74</ns0:cell><ns0:cell>2.26</ns0:cell><ns0:cell>24.62</ns0:cell><ns0:cell>17.24</ns0:cell><ns0:cell>35.04</ns0:cell><ns0:cell>1.96</ns0:cell></ns0:row><ns0:row><ns0:cell>Cultivated land</ns0:cell><ns0:cell>25.74</ns0:cell><ns0:cell>21.35</ns0:cell><ns0:cell>33.71</ns0:cell><ns0:cell>1.20</ns0:cell><ns0:cell>21.73</ns0:cell><ns0:cell>18.26</ns0:cell><ns0:cell>29.14</ns0:cell><ns0:cell>1.09</ns0:cell></ns0:row><ns0:row><ns0:cell>Mining land</ns0:cell><ns0:cell>33.33</ns0:cell><ns0:cell>24.27</ns0:cell><ns0:cell>42.29</ns0:cell><ns0:cell>2.50</ns0:cell><ns0:cell>29.63</ns0:cell><ns0:cell>20.35</ns0:cell><ns0:cell>38.08</ns0:cell><ns0:cell>2.31</ns0:cell></ns0:row><ns0:row><ns0:cell>Water area</ns0:cell><ns0:cell>21.72</ns0:cell><ns0:cell>19.16</ns0:cell><ns0:cell>29.12</ns0:cell><ns0:cell>2.30</ns0:cell><ns0:cell>19.31</ns0:cell><ns0:cell>16.29</ns0:cell><ns0:cell>27.56</ns0:cell><ns0:cell>1.74</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_18'><ns0:head>Table 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Correlation between LST and buffer zone within the mining lands</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_19'><ns0:head>Table 8 Correlation between LST and buffer zone within the mining lands Factor Average Area Average Temperature Maximum</ns0:head><ns0:label>8</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Temperature</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_20'><ns0:head>Table 9 (on next page)</ns0:head><ns0:label>9</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_21'><ns0:head>Table 9</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Correspondence between LST and buffer zone within the mining lands</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)Manuscript to be reviewed 1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_22'><ns0:head>Table 9 Correspondence between LST and buffer zone within the mining lands</ns0:head><ns0:label>9</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell cols='2'>Average Temperature/&#8451;</ns0:cell><ns0:cell>27.00</ns0:cell><ns0:cell>28.20</ns0:cell><ns0:cell>29.05</ns0:cell><ns0:cell>30.78</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>100m</ns0:cell><ns0:cell>25.15</ns0:cell><ns0:cell>25.84</ns0:cell><ns0:cell>26.01</ns0:cell><ns0:cell>27.17</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>200m</ns0:cell><ns0:cell>24.39</ns0:cell><ns0:cell>24.75</ns0:cell><ns0:cell>24.43</ns0:cell><ns0:cell>25.36</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>300m</ns0:cell><ns0:cell>24.34</ns0:cell><ns0:cell>24.65</ns0:cell><ns0:cell>24.16</ns0:cell><ns0:cell>25.11</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>400m</ns0:cell><ns0:cell>24.22</ns0:cell><ns0:cell>24.64</ns0:cell><ns0:cell>24.07</ns0:cell><ns0:cell>25.00</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>500m</ns0:cell><ns0:cell>24.06</ns0:cell><ns0:cell>24.69</ns0:cell><ns0:cell>24.04</ns0:cell><ns0:cell>24.97</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>600m</ns0:cell><ns0:cell>23.87</ns0:cell><ns0:cell>24.63</ns0:cell><ns0:cell>24.12</ns0:cell><ns0:cell>24.78</ns0:cell></ns0:row><ns0:row><ns0:cell>Average</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>temperature in</ns0:cell><ns0:cell>700m</ns0:cell><ns0:cell>23.76</ns0:cell><ns0:cell>24.53</ns0:cell><ns0:cell>24.14</ns0:cell><ns0:cell>24.59</ns0:cell></ns0:row><ns0:row><ns0:cell>different scale</ns0:cell><ns0:cell>800m</ns0:cell><ns0:cell>23.70</ns0:cell><ns0:cell>24.44</ns0:cell><ns0:cell>23.95</ns0:cell><ns0:cell>24.52</ns0:cell></ns0:row><ns0:row><ns0:cell>buffers</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>900m</ns0:cell><ns0:cell>23.64</ns0:cell><ns0:cell>24.24</ns0:cell><ns0:cell>23.80</ns0:cell><ns0:cell>24.47</ns0:cell></ns0:row><ns0:row><ns0:cell>/&#8451;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>1000m</ns0:cell><ns0:cell>23.59</ns0:cell><ns0:cell>24.06</ns0:cell><ns0:cell>23.77</ns0:cell><ns0:cell>24.41</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1100m</ns0:cell><ns0:cell>23.54</ns0:cell><ns0:cell>23.87</ns0:cell><ns0:cell>23.72</ns0:cell><ns0:cell>24.29</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1200m</ns0:cell><ns0:cell>23.48</ns0:cell><ns0:cell>23.68</ns0:cell><ns0:cell>23.71</ns0:cell><ns0:cell>24.21</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1300m</ns0:cell><ns0:cell>23.43</ns0:cell><ns0:cell>23.57</ns0:cell><ns0:cell>23.68</ns0:cell><ns0:cell>24.07</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1400m</ns0:cell><ns0:cell>23.43</ns0:cell><ns0:cell>23.55</ns0:cell><ns0:cell>23.66</ns0:cell><ns0:cell>23.96</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1500m</ns0:cell><ns0:cell>23.42</ns0:cell><ns0:cell>23.52</ns0:cell><ns0:cell>23.51</ns0:cell><ns0:cell>23.92</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)</ns0:note> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:04:47707:1:1:NEW 10 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

" College of Landscape Architecture Key Laboratory for Garden Plant Germplasm Development & Landscape Eco-Restoration in Cold Regions of Heilongjiang Province Northeast Forestry University 26 Hexing Road Harbin, Heilongjiang, 150040, China Tel: 0086-451-82191573 https://www.nefu.edu.cn/ [email protected] August 29th, 2020 Dear Editors We thank the reviewers for their generous comments on the manuscript and have edited the manuscript to address their concerns. We believe that the manuscript is now suitable for publication in PeerJ.   Looking forward to hearing from you. We would be glad to respond to any further questions and comments that you and reviewers may have. Thank you and best regards.    Jia-shuo Cao On behalf of all authors. Reviewer 1 Basic reporting The introduction has sufficient literature references and reasonable hypothesis. Experimental design The experimental design is good. Validity of the findings The findings are solid and valid. Comments for the author This study investigated the spatial variation of Land Surface Temperature over Mining Areas in Southeastern China using Landsat-8 imagery. The results indicated that the mining activities have led to significant increases in LSTs, linked to vegetation loss and environmental degradation. In general, this manuscript is well written and easy to follow, making significant contributions to the literature. Thank you for your comments concerning our manuscript. We are greatly encouraged by your affirmation of the research. Reviewer 2 Basic reporting The standardization of spatial thematic mapping should be strengthened. The legend should include all the data-layers. We have modified and supplemented the image and described it accurately in the legend. Experimental design Methods described with sufficient detail & information to replicate. Validity of the findings The conclusions can be further refined, and the tables and charts should be compressed. The conclusion has been revised and refined. (Pg 14 line 472-503) Table 1 has been deleted. In Table 2 and Table 5, standard deviation has been added. Comments for the author Mining area is a kind of complex human activity, its internal type is complex, including mining site and industrial facility site. The mining area with high surface temperature is mainly caused by the operation of factory facilities. The current conclusion generally says that the temperature in the mining area is higher than that in the urban area, and there may be some problems. Through research and reference to the existing literature, two aspects of mining site and industrial facility site are analyzed. One the one hand, the environmental disturbances, such as surface destruction, reduced vegetation coverage and spontaneous combustion of coal, have led to temperature rise. On the other hand, the operation of the factory produces a large amount of heat, which leads to an increase in temperature. We have revised this part of the discussion. (Pg 11 line 382-418) It is suggested that higher resolution remote sensing images can be used to obtain the data of inner structure or field operation of the mining area, and the reasons of influencing the temperature level should be discussed more pertinently. We are very grateful for the valuable ideas. Some of our colleagues are doing research in this area. Due to different authors, the results cannot be used directly. However, we found some relevant literature on this issue. For the inner structure of mine land, Dr. Xie’s research have analyzed different types of disturbances, among which dumps, opencast coal pit and industrial centers have a higher contribution rate to warming (Xie et al). We put this quote in the discussion section. (Pg 12 line 398-402) The reasons of influencing the temperature level in this study focuses on coal mining activities and urban expansion. When exploring the correlation between land surface temperature and mining activities, we conducted research from two aspects: patch area and buffer sizes. Reviewer 3 Basic reporting The manuscript is well within the scope of the journal. However, it requires few improvements before being accepted. Experimental design The framework and structure of the manuscript is alright. Validity of the findings The manuscript presents a good overview over the relationship between LULC and LST. Comments for the author The present work is very interesting. However, I have observed few basic fundamental issues in the manuscript, which needs to be addressed by the authors before the acceptance of this manuscript. Hence, I recommend major recommendation before being accepted. Specific Comments to the Authors: 1. The authors have used maximum likelihood classifier for the image classification. It is not clear why the authors have employed such outdated techniques, when more updated and better methods like random forest etc. are available. It has received wide applicability in producing comparatively better LULC. We are very grateful for the valuable ideas. Maximum likelihood classification (MLC) is a primer supervised classification scheme used in remote sensing tactics for data-image information. It has the advantages of clear parameter interpretation, easy integration with prior knowledge, and easy to satisfy special classification requirements (such as mine land). The classification results of the MLC can meet the needs of this research. It is very regrettable that the authors have only a preliminary understanding of the method of using random forests for land use classification, and have not fully grasped the operation methods, so it cannot be used in this study for the time being. We have read some relevant literature on this issue and strive to apply better methods to future research work. 2. In the methodology section, authors have mentioned about confusion matrix for the validation of LULC. Again, in the result section, they showed the values of Kappa coefficient. In this case, the authors have not provided any clear view on the number of samples that are adopted for validation and how the sample size is determined. In the selection of sample points, there are the following principles: 1. The sample points are evenly distributed; 2. The sample points are representative; 3. The sample points contain all the forms of different land-use types. For example, forest land in remote sensing images shows rough texture, dark green color, irregular shape, and clustered distribution. We have added Table 5 to clearly show the results of the accuracy evaluation. 3. In case of vegetation coverage estimation, the authors have mentioned NDVIsoil and NDVIveg. It is not clear how the authors have obtained the NDVI value of pure soil and pure vegetation. There are also no citations against those arguments. The parameters can be selected in the following ways. (1) Take different NDVIveg and NDVIsoil values for different soil and vegetation types. (2) Use the maximum and minimum NDVIs of the study area, NDVIveg =NDVImax, NDVIsoil=NDVImin. (3) Determine the NDVI value of the corresponding pixel based on measured data. In this paper, the maximum and minimum values of the given confidence interval are selected, and the confidence value is determined primarily from the image size and clarity. As a comparison, the maximum NDVI images of 2015 and 2019 were extracted. In the NDVI frequency accumulation table, the NDVI with a frequency of 5% was selected for NDVIsoil, and the NDVI with a frequency of 95% was selected for NDVIveg. We have added these in the manuscript. (Pg 5 line 165-175) Reviewer 4 Basic reporting The paper mainly deals with the assessment of spatial variation of Land Surface Temperature (LST) over a Mining area of China using GIS and RS techniques. Most of the methods used in this study are backdated and these were used widely used in many previous research studies. However, a number of serious issues preclude me from positively recommending the paper for publication. 1. The introduction is too short to raise the scientific contribution of the study. 2. The introduction fails to address the novelty of the work. Author should properly address the previous literatures dealing with the assessment LST over the mining cities. Thanks for your comments. We have rewritten the introduction, summarized the relevant literature, and clarified the significance of this research. (Pg 2 line 42-85) 3. Language needs to be changed. Corrected. For this submission, we have polished the manuscript through a professional language editing agency. 4. Line 40, author states “In the process of resource development in resource-based cities, the land-use patterns in mining areas are constantly changing, which brings about a series of impacts on the regional ecological environment” without any valid scientific reference. Corrected. This view comes from the following research: Li J, Miao H, Yang Z, Han Y. 2018. Spatial variation of land surface temperature in Yanzhou coalfield. Journal of China Coal Society 43(09):2595-2604; Chabukdhara M, Singh OP. 2016. Coal mining in northeast India: an overview of environmental issues and treatment approaches. International Journal of Coal Science & Technology 3(2):87-96; Xie MM, Bai ZK, Fu MC, Zhou W, Yuan T. 2011. Effects of land disturbance on surface temperature in large opencast coal mine. Journal of China Coal Society 36(04): 643-647. We have added the reference for this statement to the manuscript. (Pg 2 line 62-65) 5. Table 1 is unnecessary. So it would better to remove the Table 1 Agreed. We have deleted the Table 1. 6. In Table 2 and 4, author calculated normalized temperature index but how they have identified the threshold value for each class? The method of equal intervals is used to divide the temperature based on the site conditions and existing research. Once the maximum and minimum values of the inversion temperature are taken as endpoints, the temperature is divided into five equal-spaced intervals. These are a low-temperature zone, a low-middle-temperature zone, a middle-temperature zone, a middle-high-temperature zone, and a high-temperature zone. The normalized temperature indices for these levels were 0.0–0.2, 0.2–0.4, 0.4–0.6, 0.6–0.8, and 0.8–1.0, respectively. (Pg 7 line 223-229) 7. In Table 3 and6, I hope It would be better to add; Standard Deviation. Agreed. We have added the standard deviation in Table 2 and Table 6. 8. Authors analyzed buffer zone but not showed on maps. Agreed. We have added the schematic diagram of buffer zone in mining land patch (Fig. 10). Experimental design 1. The authors just considered year 2019 for showing the spatial vitiation of LST over the study landscapes. But without temporal analysis, it has no scientific base. If one never analyzes the temporal pattern of LST then how one can know whether the LST has changed or not even how fat different geophysical parameters have a role on LST or over the study area? This is a valuable argument. Due to the long history of coal mining in Jixi City and the limitations of data, it is difficult to compare and analyze the changes in land surface temperature before and after mining activities. We added data of 2015 for comparison. When exploring the correlation between land surface temperature, land-use types and vegetation coverage, we found that although there are differences in land surface temperature between the two years, there are similarities in regional spatial variation. 2. The author should change the discussion part. In discussion part author gave more focus on the result of the study. In discussion part author must deal the rationality of the result of the other studies. We have rewritten the discussion part. After the revision, we discussed and compared with other research results while analyzing the research results. 3. The research questions of the study needs to be addressed properly Corrected. Through remote sensing inversion and normalization, the spatial variation of the land surface temperature of the study area is obtained. With the correlation analysis, we revealed the impact of land-use types, vegetation coverage and coal mining activities on land surface temperature. 4. The methods needs to be more scientific and updated Thanks for your pertinent comments. The method used in this research is relatively traditional and not novel. However, it has good applicability and operability for the research, and is widely recognized. The innovation of this study lies in the influence mechanism and effect of coal mining activities on land surface temperature. There are few quantitative research on the mine land patch size and scope of the mine land buffer zone in the existing literature. Validity of the findings 1. The heading of the discussion part creates ambiguities. Author should correctly write the subheading in discussion part. Corrected. The subheading of the discussion part has been modified. (Pg 11 line 382, Pg 12 line 420, Pg 13 line 455) 2. Author must address the major driers of spatial variation of LST of the study area. Our findings showed that the coal mining activities and urban expansion are the primary factors affecting land surface temperature. These two factors changed land-use types and vegetation coverage, resulting in abnormal heat flux. (Pg 14 line 473-475) 3. The findings of the result were not properly addressed. Corrected. The findings of the result have been modified. 4. The authors should clearly focus the literatures of the pervious research study and relevant literatures needs to be used. Agreed. We have focused and summarized the existing literature related to this research, and added them to the corresponding part of the manuscript. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. Jixi is a typical mining city in China that has undergone dramatic changes in its land-use pattern of mining areas over the development of its coal resources. Impacts of coal mining activities have greatly affected the regional land surface temperature and ecological system.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods.</ns0:head><ns0:p>The Landsat 8 Operational Land Imager (OLI) data from 2015 and 2019 were used from the Jiguan, Didao, and Chengzihe District of Jixi in Heilongjiang, China as the study area. The calculations to determine the land-use classification, vegetation coverage, and land surface temperature (LST) were performed using ArcGIS10.5 and ENVI 5.3 software packages. A correlation analysis revealed the impact of land-use type, vegetation coverage, and coal mining activities on LSTs.</ns0:p><ns0:p>Results. The results show significant spatial differentiation in the LSTs of Jixi City. The LSTs for various land-use types were ranked from high to low as follows: mining land &gt; construction land &gt; grassland &gt; cultivated land &gt; forest land &gt; water area. The LST was lower in areas with high vegetation coverage than in other areas. For every 0.1 increase in vegetation coverage, the LST is expected to drop by approximately 0.75 &#8451;. An analysis of mining land patches indicates that the patch area of mining lands has a significant positive correlation with both the average and maximum patch temperatures. The average patch temperature shows a logarithmic increase with the growth of the patch area, and within 200,000 m 2 , the average patch temperature increases significantly. The maximum patch temperature shows a linear increase with the patch area growth, and for every 100,000 m 2 increase in the patch area of mining lands, the maximum patch temperature increases by approximately 0.81 &#8451;. The higher the average patch temperature of mining land, the higher the temperature in its buffer zone, and the greater its influence scope. This study provides a useful reference for exploring the warming effects caused by coal mining activities and the definition of its influence scope.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The land surface temperature (LST) comprehensively reflects the energy exchange between land and the atmosphere, which is an important geophysical parameter in the ground-air system <ns0:ref type='bibr' target='#b28'>(Li et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b68'>Zhu et al., 2016)</ns0:ref>. Coupling the inversion results of LST with other parameters, such as land-use type and vegetation coverage, provides a scientific basis for ecological environmental protection <ns0:ref type='bibr'>(Li et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b29'>Liang, &amp; Zhai, 2014;</ns0:ref><ns0:ref type='bibr' target='#b53'>Xu, He &amp; Huang, 2013;</ns0:ref><ns0:ref type='bibr'>Zhang et al., 2013)</ns0:ref>. The commonly used LST inversion algorithms are divided primarily into the single-channel algorithm, multi-channel algorithm, and split-window algorithm <ns0:ref type='bibr' target='#b68'>(Zhu et al., 2016)</ns0:ref>. Among them, the single-channel algorithms include the atmospheric correction method, Mono-window algorithm, and the Jim&#233;nez-Mu&#241;oz J.C single-channel algorithm <ns0:ref type='bibr'>(Qin, Karnieli &amp; Berliner, 2001;</ns0:ref><ns0:ref type='bibr'>Jim&#233;nez-Mu&#241;oz et al., 2008)</ns0:ref>. The multi-channel algorithms mainly include the day-night method, temperature emissivity separation algorithm, and graybody emissivity method <ns0:ref type='bibr'>(Gan et al., 2006;</ns0:ref><ns0:ref type='bibr'>Gillespie, Rokugawa &amp; Matsunaga, 2002;</ns0:ref><ns0:ref type='bibr'>Zhang et al., 2000)</ns0:ref>. The split window algorithm is based mostly on data from the Landsat-TIRS, NOAA-AVHRR, and TERRA-MODIS <ns0:ref type='bibr'>(Rozenstein et al., 2014;</ns0:ref><ns0:ref type='bibr'>Qin &amp; Karnieli, 2011;</ns0:ref><ns0:ref type='bibr'>Mao et al., 2005)</ns0:ref>.</ns0:p><ns0:p>Due to aggravation of the heat island effect, current research on LSTs is mostly focused on urban areas. Analyzing differences in LSTs for different land-use types optimizes the distribution of green space from the perspective of landscape patterning to reduce the heat island effect <ns0:ref type='bibr'>(Liu, 2016)</ns0:ref>. However, mining areas, which are often affected by high temperatures and cause safety problems, have not attracted sufficient attention and are rarely studied. Some research has shown that in the resource development process for resource-based cities, the land-use patterns in mining areas are constantly changing, which causes a series of impacts on the regional ecological environment <ns0:ref type='bibr' target='#b6'>(Li et al.,2018;</ns0:ref><ns0:ref type='bibr' target='#b2'>Chabukdhara &amp; Singh, 2016;</ns0:ref><ns0:ref type='bibr' target='#b49'>Xie et al., 2011)</ns0:ref>. Therefore, research focusing on coupling between land-use patterns in mining areas and the ecological environment indicators, such as the LST, water environment quality, and biodiversity, has become vital to environmental sustainability <ns0:ref type='bibr' target='#b66'>(Zhou &amp; Wang, 2014;</ns0:ref><ns0:ref type='bibr' target='#b48'>Xiao, Hu &amp; Fu, 2014;</ns0:ref><ns0:ref type='bibr' target='#b20'>Hu, Duo &amp; Wang, 2018;</ns0:ref><ns0:ref type='bibr' target='#b0'>Bian et al., 2018)</ns0:ref>. Current research on land surface temperatures in mining areas mainly includes the temporal and spatial distribution characteristics of the surface temperature, the impact of ecological disturbance on the surface temperature, and others, where the scales are mostly at macro-regions <ns0:ref type='bibr'>(Li, Yang &amp; Lei, 2017;</ns0:ref><ns0:ref type='bibr'>Qiu &amp; Hou, 2013;</ns0:ref><ns0:ref type='bibr' target='#b49'>Xie et al., 2011;</ns0:ref><ns0:ref type='bibr'>)</ns0:ref>. This study specifically analyzes the overall and local distribution characteristics of LSTs from smaller scales to explore the radius of influence of high-temperature points. This provides a reference to establish heat alerts in mining areas.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Overview of the study area</ns0:head><ns0:p>The study area encompasses the Jiguan, Didao, and Chengzihe District of Jixi, which are the main mining lands with a total area of 827.87 km 2 . Jixi is located in the southeast of Heilongjiang Province, between 130&#176;24&#8242;24&#8243;-133&#176;56&#8242;30&#8243; E, 44&#176;51&#8242;12&#8243;-46&#176;36&#8242;55&#8243; N. To the southeast and across the ocean in Russia, while to the west and south are Mudanjiang, and to the north is Qitaihe (Fig. <ns0:ref type='figure'>1</ns0:ref>). The province comprises Mishan, Hulin, and Jidong Counties and six other districts (Jiguan, Hengshan, Didao, Chengzihe, Lishu, and Mashan). The study area is part of the cold-temperate continental monsoon climate, where the average annual temperature is 3.7 &#8451;, the average precipitation is 537.5 mm, the annual sunshine is 2709 h and the average frostfree period is 140 d. The terrain is composed primarily of mountains, hills and plains.</ns0:p><ns0:p>Jixi is relatively rich in mineral resources with mutiple mining areas. However, there also are several abandoned mines that severely damage the ecological environment. In addition, urban construction and industrial development have encroached on grasslands, woodlands, and wetlands, which increases the ecological vulnerability and risks in these ecosystems <ns0:ref type='bibr'>(He, 2010)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Data sources and preprocessing treatments</ns0:head><ns0:p>This paper is based on the Landsat 8 OLI remote sensing images from 2015 and 2019, all of which are from the US Geological Survey (http://glovis.usgs.gov/). All images have a spatial resolution of 30 m. The image strip numbers/rows used in this study are 115/28 and 115/29, respectively, and the imaging time was from July to September. Cloud cover in these images was less than 2%, and they were interpreted and classified based on a series of preprocessing treatments, including radiation calibration, atmospheric correction, band synthesis and image cropping.</ns0:p></ns0:div> <ns0:div><ns0:head>Analytical methods</ns0:head><ns0:p>The spatial differentiation characteristics of the LST in the Jiguan, Didao, and Chengzihe Districts of Jixi were used to identify heat islands and their influencing factors. We selected a single-window algorithm for inversion of the LSTs. These results were used to analyze the effects of the land-use type, vegetation coverage and coal mining activities on the spatial distribution of LSTs.</ns0:p></ns0:div> <ns0:div><ns0:head>Determining land-use classification and vegetation coverage</ns0:head><ns0:p>Land use is the most direct manifestation of the interaction between human activities and the natural environment as it reflects this close relationship in both time and space <ns0:ref type='bibr' target='#b38'>(Mooney, Duraiappah &amp; Larigauderie, 2013;</ns0:ref><ns0:ref type='bibr' target='#b31'>Liu et al., 2014)</ns0:ref>. Typically, areas designated as land resources reflects the status of natural resources within the study area. Changes in land-use patterns inevitably cause changes in the LSTs and ecosystem functionality. Therefore, the study of land use is of great importance for regional ecological analyses <ns0:ref type='bibr' target='#b34'>(Marceau et al., 2003)</ns0:ref>.</ns0:p><ns0:p>The relationship between vegetation coverage and the LST has become a focus of research on heat islands <ns0:ref type='bibr' target='#b44'>(Wang et al., 2011)</ns0:ref>. Green vegetation affects LSTs through photosynthesis, transpiration and evapotranspiration. <ns0:ref type='bibr' target='#b32'>Ma et al. (2010)</ns0:ref> compared and analyzed five correlation degrees among planting parameters and LSTs, including the normalized difference vegetation index (NDVI), ratio vegetation index (RVI), greenness vegetation index (GVI), modified soil to adjust vegetation index (MSAVI) and vegetation coverage. They concluded that the correlation between vegetation coverage and the LST was both high and stable because it is not markedly influenced by spatial location or changes in the fraction or type of surface coverage. Therefore, the relationship between vegetation coverage and the LST was selected to study heat island effects within different land surfaces.</ns0:p></ns0:div> <ns0:div><ns0:head>Land-use classification</ns0:head><ns0:p>The ENVI 5.3.1 (L3Harris Geospatial Solutions, Inc., Melbourne, FL, USA) and ArcGIS 10.5 (Esri, Corp., Redlands, CA, USA) were used to preprocess the original image data, which includes geometric correction, mosaic compilation, fusion, clipping, research scope extraction, image enhancement and supervised classification, before interpreting and analyzing the remote sensing imagery. The classification of land-use types in the study area was consistent with the standard land-use classification (GB/T 21010-2017). The study area was divided into six categories: forest lands, grasslands, construction lands, cultivated lands, mining lands and water areas. A maximum-likelihood approach was used for the classification. In the final stage of the study, the remote sensing image interpretation was validated by site surveys. The accuracy of the results was verified by establishing a confusion matrix. Random points were selected in the Erdas Imagine 2015 software for classification, where a certain number of random points were selected for each category. The classification of each random point was distinguished visually so that the category to which each random point belongs is defined in the software. The user accuracy, producer accuracy, and Kappa coefficient of the overall classification of each category were then calculated.</ns0:p></ns0:div> <ns0:div><ns0:head>Vegetation coverage calculation</ns0:head><ns0:p>Plant coverage information is typically extracted from remote sensing images. Given the high accuracy of NDVI values estimated using remote sensing, it is one of the most widely used indexes <ns0:ref type='bibr' target='#b39'>(Mu et al., 2012)</ns0:ref>. A common method to calculate vegetation coverage is based on the hybrid pixel decomposition method, where it is assumed that each pixel of the remote sensing image is composed of soil and vegetation components. Thus, the information includes both a pure soil component and a pure vegetation component. In this case, we assumed that the NDVI value is a weighted average sum of the index values from both soil and vegetation information <ns0:ref type='bibr' target='#b24'>(Li, Fan, &amp; Wang, 2010)</ns0:ref>, which is given as follows:</ns0:p><ns0:p>,</ns0:p><ns0:p>(1)</ns0:p><ns0:formula xml:id='formula_0'>&#119873;&#119863;&#119881;&#119868; = &#119891; &#119907; &#215; &#119873;&#119863;&#119881;&#119868; &#119907;&#119890;&#119892; + (1 -&#119891; &#119907; ) &#215; &#119873;&#119863;&#119881;&#119868; &#119904;&#119900;&#119894;&#119897;</ns0:formula><ns0:p>Where NDVI is the vegetation index value of mixed pixels; NDVI veg is the vegetation index of pure vegetation pixels; NDVI soil is the vegetation index value of pure soil pixels; and &#402; v is the vegetation coverage. Thus, the formula for vegetation coverage (&#402; v ) becomes: ,</ns0:p><ns0:p>(2)</ns0:p><ns0:formula xml:id='formula_1'>&#119891; &#119907; = (&#119873;&#119863;&#119881;&#119868; -&#119873;&#119863;&#119881;&#119868; &#119904;&#119900;&#119894;&#119897; ) (&#119873;&#119863;&#119881;&#119868; &#119907;&#119890;&#119892; -&#119873;&#119863;&#119881;&#119868; &#119904;&#119900;&#119894;&#119897; )</ns0:formula><ns0:p>In practice, the parameters can be selected in the following ways. (1) Take different NDVI veg and NDVI soil values for different soil and vegetation types. (2) Use the maximum and minimum NDVIs of the study area, NDVI veg =NDVI max , NDVI soil =NDVI min . (3) Determine the NDVI value of the corresponding pixel based on measured data <ns0:ref type='bibr' target='#b51'>(Li et al., 2015)</ns0:ref>. Under the influence of varying meteorological conditions, vegetation type and distribution, seasons, and other factors, both the NDVI soil and NDVI veg values for different images vary to some extent.</ns0:p><ns0:p>The maximum and minimum values of the given confidence interval are selected, and the confidence value is determined primarily from the image size and clarity. As a comparison, the maximum NDVI images of 2015 and 2019 were extracted. In the NDVI frequency accumulation table, the NDVI with a frequency of 5% was selected for NDVI soil , and the NDVI with a frequency of 95% was selected for NDVI veg . Finally, the vegetation coverage was obtained from Eq. (2).</ns0:p></ns0:div> <ns0:div><ns0:head>Land surface temperature inversion</ns0:head><ns0:p>The LST inversion algorithms for single-infrared-band Landsat 8 OLI remote sensing data are based primary on the radioactive transfer equation (RTE), a universal single-channel algorithm, and a single-window algorithm <ns0:ref type='bibr' target='#b11'>(Ding &amp; Xu, 2008)</ns0:ref>. Therefore, the RTE was selected to invert the LSTs in this study.</ns0:p></ns0:div> <ns0:div><ns0:head>Calculation of specific surface emissivity</ns0:head><ns0:p>Remote sensing images were firstly classified into three types: water bodies, towns and natural surfaces. The specific emissivity of water pixels is 0.995, where other surface emissivity estimates were based on the following formulas <ns0:ref type='bibr' target='#b5'>(Chi, Zeng, &amp; Wang, 2016)</ns0:ref>: ,</ns0:p><ns0:p>(3) &#120576; surface = 0.9625 + 0.0614&#119891; &#119907; -0.0461&#119891; &#119907; 2 , (4) &#120576; building = 0.9589 + 0.086&#119891; &#119907; -0.0671&#119891; &#119907;</ns0:p></ns0:div> <ns0:div><ns0:head>2</ns0:head><ns0:p>Where &#949; surface and &#949; building represent the specific emissivity of natural surface pixels and urban pixels, respectively.</ns0:p></ns0:div> <ns0:div><ns0:head>Radioactive transfer equation</ns0:head><ns0:p>The RTE is also called the atmospheric correction method. It firstly estimates the impact of the atmosphere on the surface thermal radiation based on the information received by the satellite thermal infrared sensor. This is then subtracted from the total thermal radiation obtained by the sensor. The impact of the atmosphere on the surface can be used to obtain the intensity of surface thermal radiation. Assuming that the surface and the atmosphere have Lambertian properties for thermal radiation, the corresponding LST can be obtained as <ns0:ref type='bibr' target='#b56'>(You, &amp; Yan, 2009;</ns0:ref><ns0:ref type='bibr' target='#b58'>Yue et al., 2019)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_2'>, (<ns0:label>5</ns0:label></ns0:formula><ns0:formula xml:id='formula_3'>)</ns0:formula><ns0:formula xml:id='formula_4'>&#119871; &#120582; = [&#120576; &#8901; &#119861;(&#119879; &#119878; ) + (1 -&#120576;)&#119871; &#8595; ] &#8901; &#120591; + &#119871; &#8593;</ns0:formula><ns0:p>Where L &#955; is the intensity of thermal radiation received by the satellite sensor, &#949;(K) is the surface emissivity, T S is the true LST, B(T S ) (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) is the black body brightness corresponding to temperature T S derived from Planck's law, &#964; is the transmittance of the atmosphere at thermal infrared wavelengths, L &#8593; (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) is the atmospheric upward radiance, and L &#8595; (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) is the atmospheric downward radiance. Based on the RTE, the B(T S ) can be obtained as <ns0:ref type='bibr' target='#b47'>(Wu et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b16'>Hou, &amp; Zhang, 2019)</ns0:ref>: , ( <ns0:ref type='formula'>6</ns0:ref>)</ns0:p><ns0:formula xml:id='formula_5'>&#119861;(&#119879; &#119878; ) = [&#119871; &#120582; -&#119871; &#8593; -&#120591; &#8901; (1 -&#120576;)&#119871; &#8595; ]/&#120591; &#8901; &#120576;</ns0:formula><ns0:p>Where &#964;, L &#8593; (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) and L &#8595; (W m &#8722;2 sr &#8722;1 &#956;m &#8722;1 ) were determined from the official NASA website (http://atmcorr.gsfc.nasa.gov/) by inputting the imaging time, latitude and longitude, air pressure and other relevant information to the study area. After estimating the of black body radiance B(T S ), which is the same as the real temperature on the ground, the inverse function of Planck's law gives the real temperature on the ground as <ns0:ref type='bibr' target='#b3'>(Chen, 2014)</ns0:ref> :</ns0:p><ns0:formula xml:id='formula_6'>, (<ns0:label>7</ns0:label></ns0:formula><ns0:formula xml:id='formula_7'>)</ns0:formula><ns0:formula xml:id='formula_8'>&#119879; &#119878; = &#119870; 2 /&#119897;&#119899; ( &#119870; 1 &#119861;(&#119879; &#119878; ) + 1 )</ns0:formula><ns0:p>Where K 1 and K 2 are constants obtained by querying the Landsat metadata file. In this case, K 1 =774.8853 and K 2 =1321.0789 for Landsat 8 TIRS band 10.</ns0:p></ns0:div> <ns0:div><ns0:head>Normalized temperature index and temperature classification</ns0:head><ns0:p>The ecological environment of coal mining areas is damaged to varying degrees, this changes their LSTs and causes a series of significant ecological effects and environmental problems, such as vegetation degradation and soil erosion <ns0:ref type='bibr' target='#b13'>(Dutta &amp; Agrawal, 2003;</ns0:ref><ns0:ref type='bibr' target='#b67'>Zhou &amp; Zhang, 2005)</ns0:ref>. We used the urban heat island effect to explore the impact of coal mining activities on LSTs <ns0:ref type='bibr' target='#b55'>(Ye et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b25'>Li et al., 2019)</ns0:ref>. The formula for the normalized temperature index is:</ns0:p><ns0:formula xml:id='formula_9'>, (8) &#119879; &#119903; = &#120549;&#119879; &#119879; &#119903;&#119886;&#119899;&#119892;&#119890; = &#119879; -&#119879; &#119898;&#119894;&#119899; &#119879; max -&#119879; min</ns0:formula><ns0:p>Where T r is the normalized temperature index, T is the temperature at any spatial position in the region, T max and T min are the highest and lowest temperature in the region, respectively.</ns0:p><ns0:p>The method of equal intervals is used to divide the temperature based on the site conditions and existing research <ns0:ref type='bibr'>(Sheng et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b21'>Jia &amp; Liu, 2006)</ns0:ref>. Once the maximum and minimum values of the inversion temperature are taken as endpoints, the temperature is divided into five equal-spaced intervals. These are a low-temperature zone, a low-middle-temperature zone, a middle-temperature zone, a middle-high-temperature zone, and a high-temperature zone. The normalized temperature indices for these levels were 0.0-0.2, 0.2-0.4, 0.4-0.6, 0.6-0.8, and 0.8-1.0, respectively (Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). Analyzing changes in the LST index at different distances from the mine allows evaluating the intensity and range of the heat island effect as caused by coal-mining activities.</ns0:p></ns0:div> <ns0:div><ns0:head>Analytical method of factors affecting land surface temperature</ns0:head><ns0:p>The terrain over the study area is relatively flat, which facilitates farming, town construction, and coal mining activities. We analyzed the spatial differentiation of LSTs in this area, which was linked to land use, vegetation coverage and coal mining activities.</ns0:p></ns0:div> <ns0:div><ns0:head>The influence of land-use classification on land surface temperature</ns0:head><ns0:p>The area and proportion of different types of land use were counted separately. Subsequently, the land-use and the LST maps were superimposed to obtain statistical data on the LSTs of various land-use types.</ns0:p></ns0:div> <ns0:div><ns0:head>The influence of vegetation coverage on land surface temperature</ns0:head><ns0:p>A profile analysis more intuitively reflected the relationship between changes in LST and vegetation coverage at a given geographical location. Using the interpolation line function in ArcGIS 10.5 to view profile values of LST and vegetation coverage from 2015 and 2019 to compare and analyze their associated changes along profiles to evaluate the relationships between these variables.</ns0:p></ns0:div> <ns0:div><ns0:head>The influence of coal mining activities on land surface temperature</ns0:head></ns0:div> <ns0:div><ns0:head>The influence of patch area</ns0:head><ns0:p>Firstly, all mining areas within a distance of 1500 m from the edge of the study area were screened. These selected mining area patches were then counted and grouped based on area. We then combined these data with our LST inversion to determine the maximum, minimum, and average LSTs for different patches. Finally, the influence of these mining land patches on the LSTs were evaluated.</ns0:p></ns0:div> <ns0:div><ns0:head>The influence of buffer range</ns0:head><ns0:p>Buffers with a range of 100-1500 m at intervals of 100 m were set for each of the patches. The average LST in each buffer zone was extracted, and the trends in the LSTs at varying distances from the mining area were analyzed.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Land surface temperature inversion</ns0:head><ns0:p>The LST results for the Jiguan, Didao and Chengzihe Districts of Jixi in 2015 and 2019 are shown in Fig. <ns0:ref type='figure' target='#fig_1'>2</ns0:ref> and Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>. The temperatures in 2015 were in general higher than those in 2019. The average LST over the entire study area was 25.64 &#8451; in 2015 and 22.10 &#8451; in 2019. There is a similarity in the spatial distribution patterns of their LSTs. High temperatures are concentrated in the south-central and southeast parts of the study area, while the temperatures in the west and north are relatively low. In these two years, the average LST in the Jiguan District was higher than averages in the other two districts, but its highest temperature was lower than the maximum recorded in the Didao and Chengzihe Districts. The highest temperatures over the entire study area were 42.29 &#8451;, which was recorded at Shenghe Coal Mine in the Didao District. Likewise, the highest temperature in the Chengzihe District was recorded at Chengshan Coal Mine. Thus, mining areas had much higher LSTs than average. While only two years were selected for the analysis, similar results validate the conclusions.</ns0:p><ns0:p>The LSTs from 2015 and 2019 were normalized and divided into five levels, as shown in Fig. <ns0:ref type='figure' target='#fig_2'>3</ns0:ref> and Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref>. The LSTs in the study area were assigned primarily to the low-temperature, lowmiddle-temperature, and middle-temperature zones, which covered the LST range of 19.16-33.04 &#8451; in 2015 and 16.29-29.37 &#8451; in 2019. Among them, the low-middle-temperature zone had the largest area as it accounted for more than 70% of the total study area. The hightemperature and middle-high-temperature zones had smaller areas. The high-temperature zone was distributed primarily within the Didao and Chengzihe Districts. The Shenghe Coal Mine accounted for 53.08% of the total area of the high-temperature zone in 2015 and rose to 59.04% in 2019. The proportion of the Chengshan Coal Mine in the total area of the high-temperature zone increased from 8.17% to 34.47% over these four years. Meanwhile, the low-temperature and low-middle-temperature zones were distributed mostly in the Didao and Chengzihe Districts, giving a large temperature difference between them. Therefore, local heat island effects were obvious within the study area.</ns0:p></ns0:div> <ns0:div><ns0:head>Land-use classification</ns0:head><ns0:p>Land-use types in the Jiguan, Didao, and Chengzihe Districts of Jixi in 2015 and 2019 are shown in Fig. <ns0:ref type='figure' target='#fig_3'>4</ns0:ref> and Table <ns0:ref type='table'>4</ns0:ref>. From 2015 to 2019, the area of forest land increased while the area of cultivated land decreased. However, the dominant land-use types in the study area are still forest land and cultivated land. The forest land is distributed mostly in the northern part of the study area, while the cultivated land is distributed in the middle and southern parts. Construction land is concentrated in the Jiguan District, which increased significantly from 109.94 km 2 to 133.69 km 2 in the four considered years. The mining land is defined primarily by the Shenghe Coal Mine in the Didao District and the Chengshan Coal Mine in the Chengzihe District. The accuracy of the land-use classification was verified by establishing a confusion matrix. The matrix showed that the Kappa coefficients of the land-use maps in the interpreted periods are all above 0.8, which meets the accuracy requirements for this study (Table <ns0:ref type='table' target='#tab_7'>5</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Vegetation coverage</ns0:head><ns0:p>The remote sensing images of the study area were processed according to the mixed pixel decomposition method to obtain the vegetation coverage of the Jiguan, Didao, and Chengzihe District of Jixi (Fig. <ns0:ref type='figure' target='#fig_4'>5</ns0:ref>). The construction land in the eastern Jiguan District, Shenghe Coal Mine in the Didao District and Chengshan Coal Mine in the Chengzihe District had the lowest vegetation coverage. However, ongoing urbanization and coal mining activities have markedly affected vegetation coverage in many other areas as well.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and land-use types</ns0:head><ns0:p>The main land types in the low-temperature and low-middle-temperature zone are water areas, forest land, grassland and cultivated land. The main land types in the high-temperature, middlehigh-temperature, and middle-temperature zones are construction land and mining land. There are large difference in the average LSTs among these land-use types (Table <ns0:ref type='table' target='#tab_9'>6</ns0:ref>). The average LSTs for mining land, construction land and grassland were higher than the average LST for the study area. Among them, mining land had the highest average LSTs (33.33 &#8451; in 2015 and 29.63 &#8451; in 2019), yielding temperature anomalies of 7.69 &#8451;in 2015 and 7.53 &#8451; in 2019. The water area had the lowest average <ns0:ref type='bibr'>LSTs (21.72 &#8451; in 2015 and</ns0:ref><ns0:ref type='bibr'>19.31 &#8451; in 2019)</ns0:ref>. At the same time, the temperature standard deviation within the mining land was also relatively large, with a difference of 18.02 &#8451; between the minimum and maximum temperatures.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and vegetation coverage</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed An east-west transect was drawn across the study are, and the data from 2019 were used to analyze changes in the LSTs with vegetation coverage. Every 25 pixel points on the profile were assigned to a group, and the average value of the vegetation coverage and LST in each group was calculated to obtain 56 data sets. Finally, a linear fit was performed between the vegetation coverage and average LST, and the coefficient of determination was assessed (Fig. <ns0:ref type='figure' target='#fig_5'>6</ns0:ref>). Areas with low vegetation coverage were associated with higher LSTs. In addition, as vegetation coverage decreased, the LSTs increased. The trends in LST and vegetation coverage were opposite with reciprocal change patterns.</ns0:p><ns0:p>The linear fit of the average LST and vegetation coverage (Fig. <ns0:ref type='figure' target='#fig_6'>7</ns0:ref>) shows that if the vegetation coverage increases by 0.1, the average LST is expected to decrease by approximately 0.75 &#8451;. This constitutes a strong negative relationship between the LST and vegetation coverage. Using the SPSS 24 (IBM, Corp., Armonk, NY, USA) indicated a correlation coefficient of R = &#8722;0.780. This indicates a significant correlation at the 0.01 confidence level (both sides). Thus, green vegetation has a significant cooling effect on the land surface.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and coal mining activities</ns0:head><ns0:p>This study mainly considers spatial variations when exploring the correlation between the LST and mining activities. Therefore, the data of the most recent year (2019) is selected for the analysis, and the spatial distribution of the LST is analyzed based on the patch area and buffer sizes.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and patch area of mining lands</ns0:head><ns0:p>The mining areas were grouped based on patch area after screening them within 1500 m of the edge of the study area. The maximum, minimum and average LSTs of each patch were calculated from the 52 data sets (Table <ns0:ref type='table'>7</ns0:ref>). Correlations among the average patch area and the average and maximum patch temperatures were analyzed using SPSS 24. Our analysis indicates that the patch was strongly positively correlated with the average and maximum patch temperatures.</ns0:p><ns0:p>Correlation between the patch area and average patch temperature (Fig. <ns0:ref type='figure' target='#fig_7'>8</ns0:ref>) yielded R = 0.571. This indicates a significant correlation at the 0.01 confidence level (both sides). The determination coefficient of the fit logarithmic function was R 2 = 0.487, indicating that larger patch sizes promote a greater average patch temperature. Within 200,000 m 2 , the average patch temperature increases rapidly with the size of the patch area. Once above 200,000 m 2 , the average patch temperature increases more slowly.</ns0:p><ns0:p>The correlation between the patch area and maximum patch temperature (Fig. <ns0:ref type='figure' target='#fig_8'>9</ns0:ref>) yielded R = 0.645. This indicates a significant correlation at the 0.01 confidence level (both sides). The determination coefficient of the linear fit was R 2 = 0.415, indicating that larger patch sizes promote a greater maximum patch temperature. If the patch area of mining land increases by 100,000 m 2 , the maximum patch temperature will increase by approximately 0.81&#8451;.</ns0:p></ns0:div> <ns0:div><ns0:head>Correlation between land surface temperature and various buffer sizes</ns0:head><ns0:p>The schematic diagram of buffer zone in mining land patch is shown in Fig 10 <ns0:ref type='figure'>.</ns0:ref> A correlation analysis was performed on average patch area, average patch temperature, maximum patch temperature of mining land and the average LST in buffer zones at 100-1500 m reviewed at 100m intervals (Table <ns0:ref type='table' target='#tab_12'>8</ns0:ref>). The temperature of the buffer zones within 0-100 m was strongly correlated with the patch area, average patch temperature, and maximum patch temperature of the mining land. In the 100-200 m buffer zone, the correlation between the temperature and the average area was not significant. Therefore, a higher correlation was found for the entire buffer zone with the average and maximum patch temperatures, while a lower correlation was found with the patch area. Thus, the correlation between the temperature in the buffer zone and the average patch temperature was most relevant.</ns0:p><ns0:p>To further study the correspondence between the average patch temperature of mining land and the temperature in the buffer zones, the 52 data sets were sorted based on their average patch temperatures from smallest to largest. Each of the 13 groups was then compiled into a new group. The average number and the average temperature of the corresponding buffer zone in each new group were calculated to obtain four new data sets (Table <ns0:ref type='table' target='#tab_14'>9</ns0:ref>).</ns0:p><ns0:p>Figure <ns0:ref type='figure' target='#fig_0'>11</ns0:ref> shows that the further the buffer zone was from the mine land patch, the lower its temperature. In 0-200 m buffer zones, the average temperature changed drastically, while the average temperature outside the 200 m zone varied little. The range of this heating effect is approximately 700 m in Group 1, 1200 m in Group 2 and 3, and more than 1400 m in Group 4. Therefore, a larger average patch temperature in the mining land causes a higher temperature in its buffer zone, and the greater the scope of its influence.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head></ns0:div> <ns0:div><ns0:head>Impact of coal mining activities on surface temperatures</ns0:head><ns0:p>As the largest coal city in Heilongjiang Province, Jixi has always utilized coal as its leading industry. The main types of coal mining wasteland in Jixi City include mining subsidence, land occupation, polluted wasteland, and excavated land, which account for 0.48%, 82.0%, 6.82%, and 10.71% of the total coal mining wasteland, respectively <ns0:ref type='bibr'>(Di, Guan &amp; Zheng, 2015)</ns0:ref>. Coal mining activities generate a significant amount of heat. Thus, regional heating within the city has intensified when coupled with their high-energy consumption and high-heat producing enterprises <ns0:ref type='bibr' target='#b19'>(Hu, Zhao &amp; Dong, 2010)</ns0:ref>. The ongoing economic development of mining areas has increased both the population density and heat production from urban infrastructure.</ns0:p><ns0:p>The correlation between LST and coal mining activities has resulted in larger mining lands with higher average and maximum patch temperatures. The available literature has shown that the size, shape, number, and boundary properties of these patches affect their energy transmissions. According to landscape ecological theory, the size and shape of these patches also affect their energy accumulation. Likewise, some researchers have recognized that larger patches of construction land have higher degrees of aggregation, more regular shapes, higher LSTs, and more significant heat island effects <ns0:ref type='bibr' target='#b57'>(Yu, 2006;</ns0:ref><ns0:ref type='bibr' target='#b15'>Fu, 2001;</ns0:ref><ns0:ref type='bibr' target='#b49'>Xie, Wang &amp; Fu, 2011;</ns0:ref><ns0:ref type='bibr' target='#b51'>Xu et al., 2015)</ns0:ref>. Some studies have analyzed different types of disturbances at the interior of mining lands, among which dumps, opencast coal pits, and industrial centers have higher contributions to local warming <ns0:ref type='bibr' target='#b49'>(Xie et al., 2011;</ns0:ref><ns0:ref type='bibr'>Liu J, 2016)</ns0:ref>. Exposed coal and coal gangue easily absorb heat and cause increased temperatures, while piled coal gangue hills are prone to heat and spontaneous combustion <ns0:ref type='bibr'>(Hao, 2011)</ns0:ref>. Therefore, many factors cause high temperatures in mining land.</ns0:p><ns0:p>Quantitative research on the impact of mining land indicates a strong warming effect within a buffer zone of 0-200 m around mining land patches. As the distance from the mining land increases, the warming effects gradually weakens. Mining land patches with higher average patch temperatures have larger temperature-affected buffer zones. Changes in the local meteorological conditions, such as temperature rise, affect local species, which impacts the ecological conditions of the entire region. However, the strength of the warming effect and the size of its influence range are not only related to the distance from the mining land patch but may also be related to the average temperature of the entire area during the analysis <ns0:ref type='bibr' target='#b30'>(Liao, 2009)</ns0:ref>. This specific correlation requires further study.</ns0:p><ns0:p>To date, regulations on the ecological and environmental protection are aimed only at the ecological and environmental indicators within the mining area, which cannot achieve regional ecological protection. Although it seems intuitive that coal production enterprises or units engaged in corresponding activities have taken the responsibility of protecting the ecology and environment, this does not cover the entire affected area of coal mining production activities. To protect the ecological quality of the area while developing coal resources, the scope of environmental protection in mining areas should be defined more scientifically and rationally.</ns0:p></ns0:div> <ns0:div><ns0:head>Impact of different land-use types on surface temperature</ns0:head><ns0:p>Our results show that land-use types have a dominating impact on the LST. The LSTs of the Jiguan, Didao, and Chengzihe District of Jixi were primarily within the range of 16.29-42.29 &#8451; in the two considered years. The low-middle-temperature zone had the largest area, which accounted for 70.53% and 72.21% of the total area. The low-temperature zone was distributed primarily over water areas, forest lands and cultivated lands. The high-temperature zone was distributed mostly over the construction land and mining land, especially the Shenghe Coal Mine in the Didao District and the Chengshan Coal Mine in the Chengzihe District.</ns0:p><ns0:p>The temperatures in 2019 were generally lower than those in 2015. From a normalized comparison, it is seen that the high-temperature and low-temperature zones increased in 2019. Along with the clustered development of mining land patches, the land surface temperature shows a polarizing trend. The expansion of some high-temperature zones may be due to the continued development of coal mines. The increased low-temperature areas may be due to the reclamation and restoration of vegetation in mining areas. Based on governmental planning ('Mineral Resources Planning of Jixi City (2016-2020)' and 'Special Planning for Reclamation and Utilization of Desert Land of Industrial Mining Area and Mining Subsidence Area in Jixi City (2014-2020)') from 2015 to 2019, the coal industry wastelands in Chengzihe and Didao Districts were treated to a certain extent, and the reclaimed land was converted into cultivated land, forest land, and construction land. These lands will be used for agricultural production, creating recreational landscapes, and improving the ecological environment.</ns0:p><ns0:p>In recent years, the development of coal resources in Jixi has been rapid. Additionally, the spatial distribution of mines has also changed <ns0:ref type='bibr' target='#b54'>(Yang, 2013)</ns0:ref>. Construction and mining activities have reduced the 'cooling' land-use types, such as forest and cultivated lands <ns0:ref type='bibr' target='#b43'>(Wang et al., 2020)</ns0:ref>, and replaced them with 'warming' types, like construction and mining lands. The available literature has shown that urban expansion is the main driving process of land cover changes and consequently rise of LST <ns0:ref type='bibr' target='#b40'>(Pal &amp; Ziaul, 2017)</ns0:ref>, which is consistent with our findings. With changes in land-use types, natural vegetation has been replaced by impervious concrete and construction land, which has caused significant changes like heat radiation from the underlying city surface <ns0:ref type='bibr'>(Wang et al., 2013)</ns0:ref>. These man-made surfaces have a strong light absorptive effect and can quickly raise the local LST <ns0:ref type='bibr' target='#b18'>(Hien et al., 2011)</ns0:ref>. In addition, building facades can reflect light multiple times, heating the near-surface atmosphere and cause LSTs to rise significantly <ns0:ref type='bibr' target='#b36'>(Miao et al., 2009)</ns0:ref>. Some studies have also shown that the heating effect of construction lands, especially compact low-rise buildings, is very obvious <ns0:ref type='bibr' target='#b9'>(Das, Das &amp; Mandal, 2020)</ns0:ref>. Among the six considered land-use types, the LSTs of water area, forest land, and cultivated land were lower than the average LST for the study area. Water-permeable areas of the study region, such as water areas and forest land, ensure efficient heat exchange between the soil and the atmosphere. Water can evaporate, which absorbs heat in the environment and has an overall cooling effect <ns0:ref type='bibr'>(Zhang et al., 2013)</ns0:ref>. Therefore, not only by balancing the land-use types, but also by optimizing appropriate urban planning, the increase in LST can be adjusted to reduce the impact of urbanization on the ecological environment <ns0:ref type='bibr'>(Das &amp; Das, 2020)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Impact of vegetation coverage on land surface temperatures</ns0:head><ns0:p>Our coupling analysis showed that changes in vegetation coverage are very important factors that affecting ecological status change. There is a significant negative correlation between LST and vegetation coverage, which has also been confirmed by other works <ns0:ref type='bibr' target='#b14'>(Estoque, Murayama &amp; Myint, 2017;</ns0:ref><ns0:ref type='bibr' target='#b22'>Jiang, Zeng &amp; Zeng, 2015;</ns0:ref><ns0:ref type='bibr' target='#b12'>Duan &amp; Zhang, 2012;</ns0:ref><ns0:ref type='bibr' target='#b45'>Wu, Xu &amp; Tan, 2007;</ns0:ref><ns0:ref type='bibr' target='#b59'>Yue, Xu &amp; Xu, 2006)</ns0:ref>. As vegetation blocks sunlight, it reduces the amount of solar radiation that reaches the surface, while plant transpiration also reduces the LST <ns0:ref type='bibr' target='#b6'>(Cui, Li &amp; Ji, 2018)</ns0:ref>. In areas with high vegetation coverage, the LST was lower than in other areas, illustrating the degree to which vegetation could effectively alleviate heat island effect. Therefore, municipal bodies should carefully consider the balance between ecological protection and economic development. The focus should be on vegetation restoration and environmental governance in areas where heat emissions are concentrated, such as abandoned mine sites and barren areas. Meanwhile, increasing the proportion of green space, improving the diversity and complexity of the landscape, and dividing the impervious surface with vegetation when developing urban construction land and coal mines can significantly reduce the LST and alleviate heat island effects.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Our findings show that coal mining activities and urban expansion are the primary factors affecting LSTs. These two factors change land-use types and vegetation coverage, which results in an abnormal heat flux. There were large differences in the LSTs among the various land-use types in Jixi City. The LSTs for the considered land-use types were ranked from high to low, as follows: mining land &gt; construction land &gt; grassland &gt; cultivated land &gt; forest land &gt; water area. The average LST difference between the mining land and water area was more than 10 &#8451; each year.</ns0:p><ns0:p>Correlations between LST and vegetation coverage indicate that they have a significant negative relationship. The LST was lower in areas with higher vegetation coverage than in other areas. For every 0.1 increase in vegetation coverage, the surface temperature is expected to drop by approximately 0.75 &#8451;, indicating the extent to which vegetation can effectively alleviate warming effects.</ns0:p><ns0:p>The correlation between the LST and coal mining activities indicates the patch area of the mining land has a significant positive correlation with both the average and maximum patch temperatures. The average patch temperature shows a logarithmic increase with the growth of the patch area; thus, the average patch temperature increases significantly within 200,000 m 2 . The maximum patch temperature shows a linear increase with the growth of the patch area; thus, the maximum patch temperature increases by approximately 0.81 &#8451; for every 100,000 m 2 increase in the patch area of mining land. A higher correlation was found between the average patch temperature and the temperature in the buffer zone. This study found that the higher the average patch temperature of mining land, the higher the temperature in its buffer zone, and the greater the scope of its influence. As the distance from the mining land increased, its heating effect weakened.</ns0:p><ns0:p>Full consideration should be given to vegetation restoration in mining areas to reduce the warming effect from coal mining activities, especially in abandoned mining land, by increasing the total vegetation coverage in the study area. The existing large coal mine land patches need to be divided by plants or water areas. Thus, the scope of environmental protection in mining areas needs to be correctly defined. Meanwhile, in future urban layouts, downtown areas should maintain a proper distance from coal mining land. This study provides a useful reference to explore the warming effects caused by coal mining activities and the definition of its influence scope.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref> The relationship between the normalized temperature index values and assigned temperature grades PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure 3</ns0:note><ns0:note type='other'>Figure 4</ns0:note><ns0:note type='other'>Figure 5</ns0:note><ns0:note type='other'>Figure 6</ns0:note><ns0:note type='other'>Figure 7</ns0:note><ns0:note type='other'>Figure 8</ns0:note><ns0:note type='other'>Figure 9</ns0:note><ns0:note type='other'>Figure 10</ns0:note><ns0:note type='other'>Figure 11</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 Figure 1</ns0:head><ns0:label>11</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3 Spatial distribution of land surface temperature levels of the study area in 2015 and 2019</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4 Land-use types of the study area in 2015 and 2019</ns0:figDesc><ns0:graphic coords='43,42.52,204.37,525.00,218.25' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5 Vegetation coverage of the study area in 2015 and 2019</ns0:figDesc><ns0:graphic coords='44,42.52,204.37,525.00,218.25' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6 Variation in land surface temperature (LST) and vegetation coverage in pixel groups (1-56) along an E-W profile</ns0:figDesc><ns0:graphic coords='45,42.52,199.12,525.00,216.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 7</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7 Correlation between land surface temperature (LST) and vegetation coverage of the study area</ns0:figDesc><ns0:graphic coords='46,42.52,199.12,525.00,258.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8 Correlation between patch area and average patch temperature of mining lands</ns0:figDesc><ns0:graphic coords='47,42.52,224.62,525.00,258.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 9</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Figure 9 Correlation between patch area and maximum patch temperature of mining lands</ns0:figDesc><ns0:graphic coords='48,42.52,224.62,525.00,258.00' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 10</ns0:head><ns0:label>10</ns0:label><ns0:figDesc>Figure 10 Schematic diagram of buffer zone in mining land patch</ns0:figDesc><ns0:graphic coords='49,42.52,204.37,525.00,376.50' type='bitmap' /></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 11</ns0:head><ns0:label>11</ns0:label><ns0:figDesc>Figure 11 Variation of land surface temperature (LST) with bu &#161;&#162; &#163;&#164;&#165;&#161; &#164;&#166; &#167;&#168;&#165;&#168;&#165;&#169; &#165;</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 The relationship between the normalized temperature index values and assigned temperature grades Normalized temperature index Temperature grade</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>0.0-0.2</ns0:cell><ns0:cell>Low temperature zone</ns0:cell></ns0:row><ns0:row><ns0:cell>0.2-0.4</ns0:cell><ns0:cell>Low-middle temperature zone</ns0:cell></ns0:row><ns0:row><ns0:cell>0.4-0.6</ns0:cell><ns0:cell>Middle temperature zone</ns0:cell></ns0:row><ns0:row><ns0:cell>0.6-0.8</ns0:cell><ns0:cell>Middle-high temperature zone</ns0:cell></ns0:row><ns0:row><ns0:cell>0.8-1.0</ns0:cell><ns0:cell>High temperature zone</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Statistics on LST for the study area in 2015 and 2019</ns0:figDesc><ns0:table><ns0:row><ns0:cell>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 2 Statistics on LST for the study area in 2015 and 2019 Land surface temperature/&#8451;</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Range</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>2015</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>2019</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>MEAN</ns0:cell><ns0:cell>MIN</ns0:cell><ns0:cell>MAX</ns0:cell><ns0:cell>STD</ns0:cell><ns0:cell>MEAN</ns0:cell><ns0:cell>MIN</ns0:cell><ns0:cell>MAX</ns0:cell><ns0:cell>STD</ns0:cell></ns0:row><ns0:row><ns0:cell>Jiguan District</ns0:cell><ns0:cell>27.16</ns0:cell><ns0:cell>21.58</ns0:cell><ns0:cell>38.97</ns0:cell><ns0:cell>2.52</ns0:cell><ns0:cell>23.24</ns0:cell><ns0:cell>17.42</ns0:cell><ns0:cell>33.64</ns0:cell><ns0:cell>2.23</ns0:cell></ns0:row><ns0:row><ns0:cell>Didao District</ns0:cell><ns0:cell>25.23</ns0:cell><ns0:cell>19.16</ns0:cell><ns0:cell>42.29</ns0:cell><ns0:cell>1.92</ns0:cell><ns0:cell>21.75</ns0:cell><ns0:cell>17.18</ns0:cell><ns0:cell>38.08</ns0:cell><ns0:cell>1.63</ns0:cell></ns0:row><ns0:row><ns0:cell>Chengzihe District</ns0:cell><ns0:cell>25.53</ns0:cell><ns0:cell>19.45</ns0:cell><ns0:cell>39.13</ns0:cell><ns0:cell>2.48</ns0:cell><ns0:cell>22.34</ns0:cell><ns0:cell>16.29</ns0:cell><ns0:cell>35.26</ns0:cell><ns0:cell>2.14</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>25.64</ns0:cell><ns0:cell>19.16</ns0:cell><ns0:cell>42.29</ns0:cell><ns0:cell>2.28</ns0:cell><ns0:cell>22.10</ns0:cell><ns0:cell>16.29</ns0:cell><ns0:cell>38.08</ns0:cell><ns0:cell>1.95</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>LST normalization results for the study area in 2015 and 2019</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 3 LST normalization results for the study area in 2015 and 2019 2015 2019 Temperature grade</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell /><ns0:cell>Normalized</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>temperature</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>index</ns0:cell><ns0:cell>LST / &#8451;</ns0:cell><ns0:cell>Percentage</ns0:cell><ns0:cell>LST / &#8451;</ns0:cell><ns0:cell>Percentage</ns0:cell></ns0:row><ns0:row><ns0:cell>Low</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.0-0.2</ns0:cell><ns0:cell>19.16-23.78</ns0:cell><ns0:cell>18.19%</ns0:cell><ns0:cell>16.29-20.65</ns0:cell><ns0:cell>19.31%</ns0:cell></ns0:row><ns0:row><ns0:cell>temperature zone</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Low-middle temperature zone</ns0:cell><ns0:cell>0.2-0.4</ns0:cell><ns0:cell>23.78-28.41</ns0:cell><ns0:cell>70.53%</ns0:cell><ns0:cell>20.65-25.01</ns0:cell><ns0:cell>72.21%</ns0:cell></ns0:row><ns0:row><ns0:cell>Middle</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.4-0.6</ns0:cell><ns0:cell>28.41-33.04</ns0:cell><ns0:cell>10.34%</ns0:cell><ns0:cell>25.01-29.37</ns0:cell><ns0:cell>7.79%</ns0:cell></ns0:row><ns0:row><ns0:cell>temperature zone</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Middle-high</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.6-0.8</ns0:cell><ns0:cell>33.04-37.66</ns0:cell><ns0:cell>0.90%</ns0:cell><ns0:cell>29.37-33.72</ns0:cell><ns0:cell>0.66%</ns0:cell></ns0:row><ns0:row><ns0:cell>temperature zone</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>High</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>0.8-1.0</ns0:cell><ns0:cell>37.66-42.29</ns0:cell><ns0:cell>0.04%</ns0:cell><ns0:cell>33.72-38.08</ns0:cell><ns0:cell>0.03%</ns0:cell></ns0:row><ns0:row><ns0:cell>temperature zone</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>0.0-1.0</ns0:cell><ns0:cell>19.16-42.29</ns0:cell><ns0:cell>100.00%</ns0:cell><ns0:cell>16.29-38.08</ns0:cell><ns0:cell>100.00%</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 5 Accuracy evaluation of land use classification for the study area in 2015 and 2019 2015 Land-use Forest land Grassland Construction land Cultivated land Mining land Water area Total</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Forest land</ns0:cell><ns0:cell>1646</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>1648</ns0:cell></ns0:row><ns0:row><ns0:cell>Grassland</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>150</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>150</ns0:cell></ns0:row><ns0:row><ns0:cell>Construction land</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>2406</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>2409</ns0:cell></ns0:row><ns0:row><ns0:cell>Cultivated land</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>1737</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>1743</ns0:cell></ns0:row><ns0:row><ns0:cell>Mining land</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>346</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>363</ns0:cell></ns0:row><ns0:row><ns0:cell>Water area</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>319</ns0:cell><ns0:cell>319</ns0:cell></ns0:row><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>1649</ns0:cell><ns0:cell>156</ns0:cell><ns0:cell>2425</ns0:cell><ns0:cell>1737</ns0:cell><ns0:cell>346</ns0:cell><ns0:cell>319</ns0:cell><ns0:cell>6632</ns0:cell></ns0:row><ns0:row><ns0:cell>Producers Accuracy</ns0:cell><ns0:cell>99.82</ns0:cell><ns0:cell>96.15</ns0:cell><ns0:cell>99.22</ns0:cell><ns0:cell>1000</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>98.46</ns0:cell><ns0:cell>-</ns0:cell></ns0:row><ns0:row><ns0:cell>Users Accuracy</ns0:cell><ns0:cell>99.88</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>99.67</ns0:cell><ns0:cell>99.66</ns0:cell><ns0:cell>95.32</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>-</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>2019</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_8'><ns0:head>Land-use Forest land Grassland Construction land Cultivated land Mining land Water area Total</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Total</ns0:cell><ns0:cell>860</ns0:cell><ns0:cell>83</ns0:cell><ns0:cell>1765</ns0:cell><ns0:cell>866</ns0:cell><ns0:cell>284</ns0:cell><ns0:cell>231</ns0:cell><ns0:cell>4089</ns0:cell></ns0:row><ns0:row><ns0:cell>Producers Accuracy</ns0:cell><ns0:cell>99.77</ns0:cell><ns0:cell>44.58</ns0:cell><ns0:cell>96.88</ns0:cell><ns0:cell>94.8</ns0:cell><ns0:cell>92.61</ns0:cell><ns0:cell>92.4</ns0:cell><ns0:cell>-</ns0:cell></ns0:row><ns0:row><ns0:cell>Users Accuracy</ns0:cell><ns0:cell>96.08</ns0:cell><ns0:cell>45.12</ns0:cell><ns0:cell>96.07</ns0:cell><ns0:cell>95.8</ns0:cell><ns0:cell>99.25</ns0:cell><ns0:cell>100</ns0:cell><ns0:cell>-</ns0:cell></ns0:row><ns0:row><ns0:cell cols='6'>Note: In 2015, Overall Classification Accuracy=99.50%; Overall Kappa Statistics=0.9932;</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell cols='6'>In 2019, Overall Classification Accuracy=95.42%; Overall Kappa Statistics=0.9361.</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>Forest land</ns0:cell><ns0:cell>858</ns0:cell><ns0:cell>35</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>893</ns0:cell></ns0:row><ns0:row><ns0:cell>Grassland</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>37</ns0:cell><ns0:cell>34</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>1</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>82</ns0:cell></ns0:row><ns0:row><ns0:cell>Construction land</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>1710</ns0:cell><ns0:cell>35</ns0:cell><ns0:cell>18</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>1763</ns0:cell></ns0:row><ns0:row><ns0:cell>Cultivated land</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>11</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>821</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>855</ns0:cell></ns0:row><ns0:row><ns0:cell>Mining land</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>263</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>265</ns0:cell></ns0:row><ns0:row><ns0:cell>Water area</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>231</ns0:cell><ns0:cell>231</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_9'><ns0:head>Table 6 (on next page)</ns0:head><ns0:label>6</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_10'><ns0:head>Table 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Statistics on LST of different land-use types in 2015 and 2019</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_11'><ns0:head>Table 6 Statistics on LST of different land-use types in 2015 and 2019 Land surface temperature/&#8451;</ns0:head><ns0:label>6</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Land use types</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>2015</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>2019</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>MEAN</ns0:cell><ns0:cell>MIN</ns0:cell><ns0:cell>MAX</ns0:cell><ns0:cell>STD</ns0:cell><ns0:cell>MEAN</ns0:cell><ns0:cell>MIN</ns0:cell><ns0:cell>MAX</ns0:cell><ns0:cell>STD</ns0:cell></ns0:row><ns0:row><ns0:cell>Forest land</ns0:cell><ns0:cell>23.95</ns0:cell><ns0:cell>20.79</ns0:cell><ns0:cell>30.89</ns0:cell><ns0:cell>1.01</ns0:cell><ns0:cell>21.07</ns0:cell><ns0:cell>17.38</ns0:cell><ns0:cell>26.41</ns0:cell><ns0:cell>0.97</ns0:cell></ns0:row><ns0:row><ns0:cell>Grassland</ns0:cell><ns0:cell>26.55</ns0:cell><ns0:cell>21.94</ns0:cell><ns0:cell>36.27</ns0:cell><ns0:cell>1.45</ns0:cell><ns0:cell>23.21</ns0:cell><ns0:cell>18.77</ns0:cell><ns0:cell>30.56</ns0:cell><ns0:cell>1.43</ns0:cell></ns0:row><ns0:row><ns0:cell>Construction land</ns0:cell><ns0:cell>29.12</ns0:cell><ns0:cell>20.59</ns0:cell><ns0:cell>41.74</ns0:cell><ns0:cell>2.26</ns0:cell><ns0:cell>24.62</ns0:cell><ns0:cell>17.24</ns0:cell><ns0:cell>35.04</ns0:cell><ns0:cell>1.96</ns0:cell></ns0:row><ns0:row><ns0:cell>Cultivated land</ns0:cell><ns0:cell>25.74</ns0:cell><ns0:cell>21.35</ns0:cell><ns0:cell>33.71</ns0:cell><ns0:cell>1.20</ns0:cell><ns0:cell>21.73</ns0:cell><ns0:cell>18.26</ns0:cell><ns0:cell>29.14</ns0:cell><ns0:cell>1.09</ns0:cell></ns0:row><ns0:row><ns0:cell>Mining land</ns0:cell><ns0:cell>33.33</ns0:cell><ns0:cell>24.27</ns0:cell><ns0:cell>42.29</ns0:cell><ns0:cell>2.50</ns0:cell><ns0:cell>29.63</ns0:cell><ns0:cell>20.35</ns0:cell><ns0:cell>38.08</ns0:cell><ns0:cell>2.31</ns0:cell></ns0:row><ns0:row><ns0:cell>Water area</ns0:cell><ns0:cell>21.72</ns0:cell><ns0:cell>19.16</ns0:cell><ns0:cell>29.12</ns0:cell><ns0:cell>2.30</ns0:cell><ns0:cell>19.31</ns0:cell><ns0:cell>16.29</ns0:cell><ns0:cell>27.56</ns0:cell><ns0:cell>1.74</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:figure type='table' xml:id='tab_12'><ns0:head>Table 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Correlation between LST and buffer zone within the mining lands</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_13'><ns0:head>Table 8 Correlation between LST and buffer zone within the mining lands Factor Average Area Average Temperature Maximum</ns0:head><ns0:label>8</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>Temperature</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_14'><ns0:head>Table 9 (on next page)</ns0:head><ns0:label>9</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_15'><ns0:head>Table 9</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Correspondence between LST and buffer zone within the mining lands</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)Manuscript to be reviewed 1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_16'><ns0:head>Table 9 Correspondence between LST and buffer zone within the mining lands</ns0:head><ns0:label>9</ns0:label><ns0:figDesc /><ns0:table><ns0:row><ns0:cell cols='2'>Average Temperature/&#8451;</ns0:cell><ns0:cell>27.00</ns0:cell><ns0:cell>28.20</ns0:cell><ns0:cell>29.05</ns0:cell><ns0:cell>30.78</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>100m</ns0:cell><ns0:cell>25.15</ns0:cell><ns0:cell>25.84</ns0:cell><ns0:cell>26.01</ns0:cell><ns0:cell>27.17</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>200m</ns0:cell><ns0:cell>24.39</ns0:cell><ns0:cell>24.75</ns0:cell><ns0:cell>24.43</ns0:cell><ns0:cell>25.36</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>300m</ns0:cell><ns0:cell>24.34</ns0:cell><ns0:cell>24.65</ns0:cell><ns0:cell>24.16</ns0:cell><ns0:cell>25.11</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>400m</ns0:cell><ns0:cell>24.22</ns0:cell><ns0:cell>24.64</ns0:cell><ns0:cell>24.07</ns0:cell><ns0:cell>25.00</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>500m</ns0:cell><ns0:cell>24.06</ns0:cell><ns0:cell>24.69</ns0:cell><ns0:cell>24.04</ns0:cell><ns0:cell>24.97</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>600m</ns0:cell><ns0:cell>23.87</ns0:cell><ns0:cell>24.63</ns0:cell><ns0:cell>24.12</ns0:cell><ns0:cell>24.78</ns0:cell></ns0:row><ns0:row><ns0:cell>Average</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>temperature in</ns0:cell><ns0:cell>700m</ns0:cell><ns0:cell>23.76</ns0:cell><ns0:cell>24.53</ns0:cell><ns0:cell>24.14</ns0:cell><ns0:cell>24.59</ns0:cell></ns0:row><ns0:row><ns0:cell>different scale</ns0:cell><ns0:cell>800m</ns0:cell><ns0:cell>23.70</ns0:cell><ns0:cell>24.44</ns0:cell><ns0:cell>23.95</ns0:cell><ns0:cell>24.52</ns0:cell></ns0:row><ns0:row><ns0:cell>buffers</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>900m</ns0:cell><ns0:cell>23.64</ns0:cell><ns0:cell>24.24</ns0:cell><ns0:cell>23.80</ns0:cell><ns0:cell>24.47</ns0:cell></ns0:row><ns0:row><ns0:cell>/&#8451;</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>1000m</ns0:cell><ns0:cell>23.59</ns0:cell><ns0:cell>24.06</ns0:cell><ns0:cell>23.77</ns0:cell><ns0:cell>24.41</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1100m</ns0:cell><ns0:cell>23.54</ns0:cell><ns0:cell>23.87</ns0:cell><ns0:cell>23.72</ns0:cell><ns0:cell>24.29</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1200m</ns0:cell><ns0:cell>23.48</ns0:cell><ns0:cell>23.68</ns0:cell><ns0:cell>23.71</ns0:cell><ns0:cell>24.21</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1300m</ns0:cell><ns0:cell>23.43</ns0:cell><ns0:cell>23.57</ns0:cell><ns0:cell>23.68</ns0:cell><ns0:cell>24.07</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1400m</ns0:cell><ns0:cell>23.43</ns0:cell><ns0:cell>23.55</ns0:cell><ns0:cell>23.66</ns0:cell><ns0:cell>23.96</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>1500m</ns0:cell><ns0:cell>23.42</ns0:cell><ns0:cell>23.52</ns0:cell><ns0:cell>23.51</ns0:cell><ns0:cell>23.92</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:04:47707:2:1:NEW 2 Oct 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

" College of Landscape Architecture Key Laboratory for Garden Plant Germplasm Development & Landscape Eco-Restoration in Cold Regions of Heilongjiang Province Northeast Forestry University 26 Hexing Road Harbin, Heilongjiang, 150040, China Tel: 0086-451-82191573 https://www.nefu.edu.cn/ [email protected] September 29th, 2020 Dear Editors We thank the reviewers for their generous comments on the manuscript and have edited the manuscript to address their concerns. We believe that the manuscript is now suitable for publication in PeerJ.   Looking forward to hearing from you. We would be glad to respond to any further questions and comments that you and reviewers may have. Thank you and best regards.    Jia-shuo Cao On behalf of all authors. Reviewer 3 Basic reporting The authors have used Maximum likelihood classifier for the image classification. It is not clear why the authors have employed such outdated techniques when more updated and better methods like random forest etc. are available. It has received wide applicability in producing comparatively better LULC. We are very grateful for the valuable ideas. Maximum likelihood classification (MLC) is a primer supervised classification scheme used in remote sensing tactics for data-image information. It has the advantages of clear parameter interpretation, easy integration with prior knowledge, and easy to satisfy special classification requirements (such as mine land). The classification results of the MLC can meet the needs of this research. It is very regrettable that the authors have only a preliminary understanding of the method of using random forests for land use classification, and have not fully grasped the operation methods, so it cannot be used in this study for the time being. We have read some relevant literature on this issue and strive to apply better methods to future research work. Experimental design no comment. Validity of the findings no comment. Reviewer 4 Basic reporting Although author revised the paper as per as suggestions but still there is a lack of important literatures. Therefore, I would suggest author to use following references for enrichment of the papers. (1) Das, M., & Das, A. (2020). Assessing the relationship between local climatic zones (LCZs) and land surface temperature (LST)–A case study of Sriniketan-Santiniketan Planning Area (SSPA), West Bengal, India. Urban Climate, 32, 100591. https://doi.org/10.1016/j.uclim.2020.100591 (2) Das, M., Das, A., & Mandal, S. (2020). Outdoor thermal comfort in different settings of a tropical planning region of Eastern India by adopting LCZs approach: A case study on Sriniketan-Santiniketan Planning Area (SSPA). Sustainable Cities and Society, 102433.https://doi.org/10.1016/j.scs.2020.102433 (3) Estoque, R. C., Murayama, Y., & Myint, S. W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. Science of the Total Environment, 577, 349-359. (4) Pal, S., & Ziaul, S. K. (2017). Detection of land use and land cover change and land surface temperature in English Bazar urban centre. The Egyptian Journal of Remote Sensing and Space Science, 20(1), 125-145. (5) Wang, R., Hou, H., Murayama, Y., & Derdouri, A. (2020). Spatiotemporal Analysis of Land Use/Cover Patterns and Their Relationship with Land Surface Temperature in Nanjing, China. Remote Sensing, 12(3), 440. We are very grateful for the valuable ideas. We have read these mentioned literatures and cited them in the discussion section to improve the comprehensiveness of the related content research. (Pg 13 line 442-465) Experimental design The contents are very suitable for this journal. But it has few common mistakes. I can't identity the research gaps. Please identify and specify. Thanks for your comments. We have carefully checked the manuscript and corrected the mistakes. Validity of the findings I would suggest author to add above mentioned literature to stand the novelty of the paper. Without this, I can't recommend to accept the paper. Agreed. We have added these mentioned literatures in the manuscript. Comments for the author Although the authors have made a good attempt to all the responses. But still i found some mistakes. (i) In figure 2 red color denotes 'high' but in figure 5 it denotes 'low'. Please use same color scheme. Even use common knowledge in using color scheme. When you are using red color it never treats as low, it has its own significance. (ii) In line 161, it should be 'Where' not 'where'. Please check all the mistakes. Corrected. (i) The color of Figure 5 has been modified. Now, the red color denotes 'high' and the blue color denotes 'low'. (ii) The textual and other mistakes have been modified. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The persistence of antimicrobial resistant (AMR) genes in the soil-environment is a concern, yet practices that mitigate AMR are poorly understood, especially in the US' largest agricultural land-use or grasslands. Animal manures, which are valuable sources of nutrients, may also contain AMR genes. The aim of this study was to enumerate AMR genes in grassland soils following 14-years of poultry litter and cattle manure deposition and evaluate if pasture management [continuously grazed (CG), hayed (H), rotationally grazed with a fenced riparian buffer (RBR), and a fenced riparian buffer strip (RBS), which excluded cattle grazing and poultry litter applications] impacts the presence and amount of AMR genes. Quantitative PCR (Q-PCR) was performed to enumerate four AMR genes (ermB, sulI, intlI, and bla ctx-m-32 ) in soil, cattle manure, and poultry litter environments. Six soil samples were additionally subjected to metagenomic sequencing and resistance genes were identified from assembled sequences. Following 14-years of continuous management, ermB, sulI, and intlI genes in soil were the highest (P&lt;0.05) following longterm continuous grazing (relative to conservation best management practices), suggesting overgrazing and continuous cattle manure deposition may increase AMR gene presence. In general, AMR gene prevalence increased downslope, suggesting potential lateral movement and accumulation based on landscape position. Poultry litter had lower abundance of AMR genes (ermB, sulI, and intlI) relative to cattle manure. Long-term applications of poultry litter increased the abundance of sulI and intlI genes in soil</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Veterinary pharmaceutical usage is a fundamental component of conventional poultry and bovine production for treating microbial infections and increasing weight gains <ns0:ref type='bibr' target='#b7'>(Collignon et al., 2009)</ns0:ref>. Repeated use of antibiotics during food-animal production may provide selection pressure for the evolutionary phenomenon known as antimicrobial resistance (AMR). Genes encoding resistance to antimicrobials and antibiotics, which can also naturally be found in many bacteria, can be transferred between organisms via horizontal gene transfer <ns0:ref type='bibr' target='#b19'>(Juhas, 2015)</ns0:ref>. Agricultural practices influence the prevalence and occurrence of AMR genes in soils. For example, soils amended with cattle manure not treated with antibiotics contained higher abundance of &#946;-lactam resistant bacteria than soils with inorganic fertilizer inputs <ns0:ref type='bibr'>(Udikovic-Kolica et al., 2014)</ns0:ref>. In another study, soil applications of swine manure increased erythromycin resistance gene abundance and remained high for a decade post-application <ns0:ref type='bibr' target='#b37'>(Scott et al., 2018)</ns0:ref>. However, it should also be noted that AMR genes can be found naturally <ns0:ref type='bibr' target='#b11'>(Durso et al., 2012)</ns0:ref>; for example, <ns0:ref type='bibr' target='#b5'>Cadena et al. (2018)</ns0:ref> identified tetracycline and sulfonamide resistant genes in organic farms without routine antibiotic usage.</ns0:p><ns0:p>There is recent interest in monitoring the dissemination of AMR genes into the environment, particularly those directly relevant to human and animal health, as consumers and producers are increasingly concerned about antibiotic resistance in food systems <ns0:ref type='bibr' target='#b11'>(Durso et al., 2012)</ns0:ref>. One goal of sustainable agriculture is to close nutrient cycles by applying animal manures to neighboring cropping systems. Additionally, depending on antibiotic properties, large quantities of PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed undegraded antibiotics exit animals to manures, including poultry litter (a combination of bedding material and excreta); for example, up to 90% of sulfonamides and 25-75% of tetracyclines may be excreted into manure as the parent compound <ns0:ref type='bibr' target='#b24'>(Kulshrestha et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b42'>Thiele-Bruhn et al., 2004)</ns0:ref>. From manure, antibiotics, genes encoding AMR, and microbes may be transferred to soil <ns0:ref type='bibr' target='#b8'>(Cook et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b18'>Heuer et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b50'>Zhang et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b17'>He et al., 2014)</ns0:ref>.</ns0:p><ns0:p>Therefore, cattle manure and poultry litter applications, which are valuable sources of nutrients such as N, P, and potassium (K), may also be a pathway for AMR bacteria and genes into the environment <ns0:ref type='bibr' target='#b48'>(Yang et al., 2019a)</ns0:ref>.</ns0:p><ns0:p>The ability of pasture management practices (i.e., filter strips and rotational grazing) to reduce AMR gene presence, prevalence, and movement to soils is largely unknown. Our previous work indicated that continuously grazed systems increased soil microbial community richness and diversity owing to greater organic animal inputs <ns0:ref type='bibr' target='#b49'>(Yang et al., 2019b)</ns0:ref>, which suggests manure increases microbiome diversity and improves soil health. However, animal manure may also be a source for AMR genes. Therefore, the current work aims to understand the impacts of pasture management on AMR bacteria and gene presence. This study focused on quantifying four AMR associated genes [i.e., erythromycin resistance gene (ermB), sulfonamide resistance gene (sulI), integrase gene (intlI), and &#946;-lactam resistance gene (bla ctx-m-32 )] present in pasture soil, cattle manure, and poultry broiler litter using Q-PCR in an effort balance human, animal, and environmental priorities. These four genes are useful for understanding the ecology and biology of agricultural AMR genes in soil and manure systems <ns0:ref type='bibr' target='#b11'>(Durso et al., 2012)</ns0:ref>. We additionally applied metagenomic sequencing to reveal the suite of resistance genes in the soil community and evaluate best management practices that may reduce the presence of AMR genes from manure and poultry litter applications to the soil.</ns0:p></ns0:div> <ns0:div><ns0:head>Material and Method</ns0:head></ns0:div> <ns0:div><ns0:head>Experimental Design</ns0:head><ns0:p>In 2004, a field study was initiated by <ns0:ref type='bibr' target='#b31'>Pilon et al. (2017a;</ns0:ref><ns0:ref type='bibr' target='#b32'>2017b;</ns0:ref><ns0:ref type='bibr'>2018)</ns0:ref> at the USDA-ARS Unit in Booneville, Arkansas to evaluate how pasture management affects water quality. Nine watersheds (average slope of 8%) were constructed on Enders and Leadvale silt loams. Each watershed had a total area of 0.14 ha, with the dominant grass species being bermudagrass (Cynodon dactylon L.). Briefly, three grazing strategies were implemented from 2004-2017 with three replications, including: continuously grazed (CG), hayed (H), and rotationally grazed with an ungrazed, fenced riparian strip (RBR; <ns0:ref type='bibr'>Yang et al., 2019)</ns0:ref> (Fig. <ns0:ref type='figure' target='#fig_2'>1</ns0:ref>). The CG treatment was consistently grazed by one to two calves during the year <ns0:ref type='bibr' target='#b31'>(Pilon et al., 2017a)</ns0:ref>. The H treatment was hayed three times annually (April, June, and October) to a height of 10 cm (no cattle in these watersheds). The RBR system is considered a best management strategy and was rotationally grazed based on forage height <ns0:ref type='bibr' target='#b31'>(Pilon et al., 2017a;</ns0:ref><ns0:ref type='bibr' target='#b32'>2017b;</ns0:ref><ns0:ref type='bibr'>2018)</ns0:ref>. Calves (three) were placed in rotationally grazed watersheds based on forage height (when heights were 20 to 25 cm) and removed (10 to 15 cm) <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Each watershed was divided into 3 zones (perpendicular to slope) given that topography widely affects the microbial biogeography <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Landscape positions corresponded to upper slope (zone 1), mid-slope (2), and downslope positions (3), whereas the RBR represented zone 4 <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. The riparian buffer strip (RBS) and served as the nested control. The length of the 3 zones in CG and H was 57 m and the length of the 3 zones in RBR was 42.75 m. Broiler litter was surface applied at 5.6</ns0:p><ns0:p>Mg dry matter per ha in April-May of each year per watershed (excluding the RBS). All poultry litter rates were equivalent on an aerial basis <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Broiler litter was obtained protocol. Extracted DNA were quantified using Quant-iT&#8482; PicoGreen&#8482; dsDNA Assay Kit (ThermoFisher Scientific, Cat. P7589) and used directly in quantitative Q-PCR. All 120, 6, and 12 soil, cattle manure, and poultry litter DNA samples, respectively, were subjected to Q-PCR for detection of four genes associated with AMR as described in the clinical isolates, which included ermB <ns0:ref type='bibr' target='#b13'>(Florez et al., 2014)</ns0:ref>, sulI <ns0:ref type='bibr' target='#b2'>(Barraud et al., 2010)</ns0:ref>, intlI <ns0:ref type='bibr' target='#b30'>(Pei et al., 2006)</ns0:ref>, and bla ctxm-32 <ns0:ref type='bibr' target='#b39'>(Szczepanowski et al., 2009)</ns0:ref>, using previously published primers (Table <ns0:ref type='table' target='#tab_2'>1</ns0:ref> <ns0:ref type='table' target='#tab_2'>1</ns0:ref>. The amplification efficiency was between 92% and 105%, and the R 2 value was above 0.98. Baseline and threshold calculations were performed using QuantStudio &#174; Design &amp; Analysis software. Amplified products were visualized on a 1% agarose gel with an ethidium bromide stain. The quantities of gene copy numbers were then determined using standard curves. Gene copy abundances were then normalized per gram dry weight of soil, cattle manure, and poultry litter after measuring the moisture content of each sample. Finally, the gene copy numbers per gram dry weight were transformed into log10 values for further statistical analysis as they were not normally distributed <ns0:ref type='bibr' target='#b15'>(Ganger et al., 2017)</ns0:ref>.</ns0:p><ns0:p>To detect significant differences for fixed effects (pasture management, sample collection timing, and zone) an analysis of variance (ANOVA) was conducted on log transformed data using JMP software [JMP&#174;12 <ns0:ref type='bibr'>(SAS Institute, 2007)</ns0:ref>] with replicate as a random effect.</ns0:p><ns0:p>Probability values less than 0.05 were considered significant and pairwise posthoc comparisons were made using Tukey's honestly significant differences Samples below detection limit were excluded in the analysis.</ns0:p></ns0:div> <ns0:div><ns0:head>Metagenomic sequencing and data analysis</ns0:head><ns0:p>To evaluate long-term effects of pasture management on AMR genes, metagenomic sequencing was applied for 6 soil samples [post-application zone 3, CG; post-application zone 3 H; post-application zone 3 RBR, post-application zone 3, RBS all replication 1; and, postapplication zone 3 RBR, post-application zone 3, RBS replication 2) ]. Sequencing libraries were prepared according to the Illumina Miseq sample preparation guide. Metagenomic sequencing was performed using Miseq Reagent Kits v2 with paired-end 2 x 250 bp reads on the MiSeq platform (University of Tennessee Genomics Core; Knoxville, TN). Raw data were uploaded to NCBI with the accession number of SAMN 14783573-14783584. Read trimming and assembly were performed according to <ns0:ref type='bibr' target='#b43'>Tyson (2015)</ns0:ref>. Genomes were annotated using the AmrPlusPlus pipeline <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. All samples resulted in a total of 5.19 Gb of sequence data.</ns0:p><ns0:p>Trimmomatic was used for removal of low-quality bases and sequences <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>.</ns0:p><ns0:p>Reads classified as host genome (Bos tarrus and Gallus gallus) were removed from further analysis. The adapter contamination and low-quality reads were also removed. The database 'MEGARes' has been integrated inside the pipeline and used for identification of AMR genes.</ns0:p><ns0:p>AMR genes with a gene fraction (i.e. proportion of nucleotides that aligned with at least one query read) of &gt;85% coverage across all alignments were considered to be positively identified in a sample <ns0:ref type='bibr' target='#b27'>(Noyes et al., 2016a)</ns0:ref>. The minimum length of a read was 150 and the mean Phred score was above 30. The AMR gene analysis was carried out using the Resistome Analyzer tool <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. Utilizing this tool, three annotation levels were produced, which include gene-level (sequencing-level), mechanism-level, and class-level counts.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Distribution of four AMR associated genes in soil based on pasture management, landscape position, and sampling time</ns0:head><ns0:p>Soil ermB gene detection varied among treatments (CG, H, RBR, and RBS) and zones (1, 2, 3, and 4) (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_7'>2A</ns0:ref>), although, sample collection time (pre or post poultry litter applications; P&gt;0.05) had no impact on the detection of ermB gene (Table <ns0:ref type='table'>2</ns0:ref>; Fig. <ns0:ref type='figure' target='#fig_7'>2B</ns0:ref>). There was an interaction effect from pasture management and zone on the abundance of ermB genes.</ns0:p><ns0:p>Across pasture management, the highest abundance of ermB gene was found in the CG treatment (&#181; log gene copies per gram dry weight soil =3.03), followed by H (2.86 gene copies per gram dry weight soil), RBR (2.72 gene copies per gram dry weight soil) and RBS (0.73 gene copies per gram dry weight soil) (Fig. <ns0:ref type='figure' target='#fig_7'>2A</ns0:ref>). Compared with RBS, CG increased the abundance of ermB by 2.3 log, H increased the abundance of ermB by 2.13 log, and RB increased the abundance of ermB by 1.99 log. Among zones, the greatest abundance of ermB occurred in zone 3 (&#181; log gene copy numbers per dry weight=2.92), followed by zone 2 (2.91 gene copy numbers per dry weight), zone 1 (2.78 gene copy numbers per dry weight), and zone 4 (0.73 gene copy numbers per dry weight) (Fig. <ns0:ref type='figure' target='#fig_7'>2C</ns0:ref>). Compared with zone 4, zone 3 increased the abundance of ermB by 2.19 log, zone 2 increased the abundance of ermB by 2.18 log, zone 1 increased the abundance of ermB by 2.05 log. However, no abundance differences occurred between pre and post poultry litter applications (&#181; log gene copy numbers per gram dry weight in pre-sampling time = 2.86 vs.</ns0:p><ns0:p>post-sampling time=2.45) (Fig. <ns0:ref type='figure' target='#fig_7'>2B</ns0:ref>). There were differences in the detection of the gene sulI among all three factors, including treatments, sampling time, and zone (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>). For pasture management, the highest abundance was found under CG (&#181; log gene copy numbers per dry weight=4.83), followed by RB (4.46), H (4.42), and RBS (2.93) (Fig. <ns0:ref type='figure' target='#fig_7'>2A</ns0:ref>). Among zones, the greatest abundance was found in zone 2 (&#181; log gene copy numbers per gram dry weight =4.66), followed by zone 1 (4.66), zone 3 (4.38), and zone 4 (2.93) (Fig. <ns0:ref type='figure' target='#fig_7'>2C</ns0:ref>). Differences in abundance were identified between pre and post poultry litter sampling time, with a higher abundance of sulI occurring post poultry litter applications (Fig. <ns0:ref type='figure' target='#fig_7'>2B</ns0:ref>; log gene copy numbers per gram dry weight=4.77 vs. pre-sampling= 4.03). There was also an interaction for pasture management x zone for the sulI gene. Similar to sulI, there were differences in the intlI gene based on all three factors (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>). Based on the influence from pasture management, ANOVA tests indicated that greatest abundances were found under long-term CG (&#181; log gene copy numbers per gram dry weight=3.41), followed by H (3.11), and RB (3.07). The least abundance of AMR genes were found in RBS (1.54) (Fig. <ns0:ref type='figure' target='#fig_7'>2A</ns0:ref>), with greatest intlI gene detection occurring in zone 2 (&#181; log gene copy numbers per gram dry weight =3.22), then zone 1 (3.19), zone 3 (3.18), and zone 4 (1.54) (Fig. <ns0:ref type='figure' target='#fig_7'>2C</ns0:ref>). The abundance of the intlI gene differed between pre and post sampling, with higher abundances in soil samples collected after poultry litter application (&#181; log gene copy numbers</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed per dry weight in post-sampling time=3.79 vs. pre-sampling =2.28) (Fig. <ns0:ref type='figure' target='#fig_7'>2B</ns0:ref>). There was pasture management x zone, pasture management x timing, and zone x timing interaction for the abundance of the intlI gene. After finding differences following long-term pasture management on the abundance of these three AMR associated genes, further analyses were conducted to illustrate the abundance of each AMR associated gene based on the pasture management treatments. Among these 93 samples, ermB was found in 77% of samples, while only one amplification was from the RBS (8% of RBS was amplified), and 92 samples were from all treatment groups (85% of treatment samples were amplified). Among these 92 positive samples from treatment groups, it included 78% of RBR samples, 92% of CG, 86% of H, and 8% of RBS. Gene sulI was detected in 119 out of 120 samples (99%) and intlI were detected in all samples (100%), while bla ctx-m-32 was not found in any soils except two (following poultry litter application in zone 2 of CG in 2016 and one in zone 3 of the H treatment in 2017). The gene bla ctx-m-32 was not included in the Table <ns0:ref type='table'>2</ns0:ref> and Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>, due to no amplification. Abundance of these three AMR associated genes indicates there are greater abundances of each AMR associated genes found in CG, RBR and H, relative to RBS (P&lt;0.05; Fig. <ns0:ref type='figure' target='#fig_7'>2A</ns0:ref>). For the RBS (no grazing or direct manure or poultry litter deposition), there was no amplification of ermB gene from all samples during 2016, while only one sample included an ermB gene in 2017.</ns0:p><ns0:p>Overall, post poultry litter applications, soil samples had greater abundance of sulI and intlI genes than pre-application soils. In Fig. <ns0:ref type='figure' target='#fig_7'>2C</ns0:ref>, the abundance of these three AMR associated genes were split out based on zones. Based on the factor of zone, differences were observed in these three AMR associated genes, ermB, sulI, and intlI (P&lt;0.05). Among these four zones, lowest abundance was found in zone 4 (no cattle manure or poultry litter) among these three genes.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed Distribution of four AMR associated genes in cattle manure and poultry litter Considering continuous annual applications of cattle and poultry manure were applied to soils (over 14-years), authors were interested in the presence of the four AMR associated genes and whether the abundance varied between soils with manure applied from the two sources.</ns0:p><ns0:p>Results from Q-PCR indicated these three AMR associated genes (ermB, sulI and intlI) were found in all poultry litter samples collected in 2019; however, the abundance of AMR-associated genes from poultry litter in the year of 2018 were below the detection threshold. The gene of bla ctx-m-32 was not found in any poultry litter and cattle manure samples (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>). Based on the ANOVA, there were differences in these three AMR associated genes between cattle manure and poultry litter, with greater abundances occurring in cattle manure than poultry litter (53, 95, and 100% greater mean value of gene copies per gram dry weight for ermB, sulI, and intlI in cattle manure than poultry litter, respectively) (P&lt;0.05) (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>). The impact of sampling year on the abundance of ermB gene was found (P&lt;0.05), with greater abundance in 2019 compared to 2018.</ns0:p></ns0:div> <ns0:div><ns0:head>Prevalence of antimicrobial resistance genes based on pasture management</ns0:head><ns0:p>Purified genomic DNA extracts from six soil samples were chosen for shotgun metagenomic sequencing to evaluate the impact of pasture management on AMR genes. Several unique AMR genes per treatment were identified (Table <ns0:ref type='table' target='#tab_4'>4</ns0:ref>). The number of unique AMR genes, mechanisms, and classes identified in H was lower than other treatments, including the RBS. Resistome Analyzer in AmrPlusPlus pipeline provided four levels of annotation database hierarchy, at levels of gene, group, mechanism, and class. In each level, the counts of each gene can be found in the output file (Supplementary Table <ns0:ref type='table' target='#tab_2'>1</ns0:ref>). These identified resistance genes were listed from the greatest numbers of hits (multi-drug resistance class) to least (Bacitracin). Based on the database of MEGARes 2.0, the multi-drug resistance was defined as genes and</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed mechanisms that cause resistance to two or more different antibiotic classes. Typically, such mechanisms involve active extrusion of antibiotic molecules from the bacterial cell or mechanisms that prevent the drug from reaching its target <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. The class of multi-drug resistance genes were identified as greater than other resistance gene classes among all treatments and RBS (Supplementary Table <ns0:ref type='table' target='#tab_2'>1</ns0:ref>). Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref> shows relative proportion of hits in each class level by treatments. Overall, the greatest (i.e., 33%) of identified genes from the multi-drug resistance class were found in the CG treatment, followed by RBR watersheds (28%), the RBS (24%), and H watersheds (15%).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Distribution of four AMR associated genes in soils based on pasture management, landscape position, and sampling time AMR is a naturally occurring phenomenon and soils are considered a reservoir for AMR genes <ns0:ref type='bibr' target='#b21'>(Kieser et al., 2000)</ns0:ref>. Overall, pasture management (CG, H, RBR, and RBS) had an effect on three AMR-associated genes, ermB, sulI, and intlI (P&lt;0.05). Greater abundance of these three AMR associated gene in soils were detected in treatments receiving either long-term poultry litter or cattle manure inputs (CG, H, and RBR), while lower AMR gene abundances were found in RBS, which was not grazed and did not receive direct poultry litter applications. This indicates these three AMR-associated genes were potentially transmitted via animal feces and may be transferred into the soil through animal movement and land application. This finding was consistent with other studies which found that the repeated application of animal manure increased antibiotic resistance genes in agricultural soils <ns0:ref type='bibr' target='#b26'>(Luby et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b22'>Kim et al., 2017)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The sample collection timing (pre or post poultry litter application) had an effect on two AMR-associated genes, sulI and intlI (P&lt;0.05). A greater abundance of these two genes in soils were found in samples collected after poultry litter application (July) rather than before poultry litter application (April). The abundance of sulI and intlI genes increased after poultry litter application, indicating poultry litter may include sulI and intlI genes and the application increased the abundance of sulI and intlI genes in the soil. This result is consistent with previous work using 16S rRNA sequencing, which found that poultry litter timing greatly influenced soil community structure and gene abundance <ns0:ref type='bibr'>(Yang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b0'>Ashworth et al., 2017)</ns0:ref>. However, poultry litter application timing did not influence the other two genes, ermB and bla ctx-m-32 .</ns0:p><ns0:p>Another study pointed out that the concentration of AMR genes [sulI, intlI, tetracycline (tetW), and streptomycin (strpB)] in soil following poultry litter fertilization were greater following 21 to 133 days after application <ns0:ref type='bibr' target='#b9'>(Cook et al., 2017)</ns0:ref>. These data suggest poultry litter applications may increase the abundance and persistence of AMR-associated genes within the soil. The factor of zone had an effect on the abundance of these three AMR-associated genes (ermB, sulI, and intlI) within the soil (P&lt;0.05), with higher abundance in zone 1, zone 2, and zone 3, and lowest abundance in zone 4. This result suggests that animal manure played an important role in enhancing the abundance of AMR associated genes into the soil. We also found that genes of sulI and intlI existed in the soil of zone 4, even though there was no input from animal manure in this region, thus indicating that these two AMR-associated genes may be inherent to the soil. Since some AMR genes were found in non-agricultural and un-grazed native soils, they were considered as a natural part of pristine habitats <ns0:ref type='bibr' target='#b11'>(Durso et al., 2012 and</ns0:ref><ns0:ref type='bibr'>2016)</ns0:ref>.</ns0:p><ns0:p>This result showcases the importance of evaluating baseline and background levels of AMR PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed genes when investigating the impact of human input in the occurrence of AMR bacteria and genes <ns0:ref type='bibr' target='#b11'>(Durso et al., 2012)</ns0:ref>.</ns0:p><ns0:p>The gene bla ctx-m-32 was not found in most soil samples, indicating that bla ctx-m-32 was not prevalent in the locations sampled. Having information on AMR presence in soils is valuable, as previous observations have shown antibiotics may impact the soil microbial community composition and structure, which will ultimately influence ecosystem-scale processes by maintaining these AMR bacteria and genes <ns0:ref type='bibr' target='#b16'>(Gutierrez et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b41'>Toth et al., 2011)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Distribution of four AMR associated genes in cattle manure and poultry litter</ns0:head><ns0:p>Three AMR associated genes (ermB, sulI, and intlI) were more abundant in cattle manure compared to poultry litter, while there was no difference of bla ctx-m-32 genes between cattle manure and poultry litter. Although, previous studies derived the opposite conclusion. <ns0:ref type='bibr' target='#b46'>Wang et al. (2016)</ns0:ref> indicated that the ermB gene levels in poultry litter were greater than that of cattle manure. Cattle antibiotics and drugs were used over the course of this experiment (Supplementary Table <ns0:ref type='table'>2</ns0:ref>); though, without the information of antibiotics used during poultry production, it is difficult to ascertain that AMR associated genes were related to specific animal management practices. Regardless of where these AMR associated genes originate, we should pay attention to the abundance and movement of these resistance genes, such as ermB, because macrolides are a major broad-spectrum antibiotic for human use and play an important role in controlling Gram-positive bacterium infection clinically <ns0:ref type='bibr' target='#b20'>(Kanoh and Rubin, 2010)</ns0:ref>. We also Manuscript to be reviewed abundance in 2018. However, it is difficult to ascertain whether this difference was caused by animal inputs without the drug usage information on cattle and poultry in these two years.</ns0:p><ns0:p>Prevalence of antimicrobial resistance genes from shotgun sequencing following pasture management Quantifying the prevalence of specific AMR genes in the soil relies on culture-independent methods, such as Q-PCR, as well as metagenomic sequencing <ns0:ref type='bibr' target='#b1'>(Agga et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b11'>Durso et al., 2012)</ns0:ref>. Metagenomic sequencing allows for the tracking of AMR genes and identification of transmission of AMR from animals to the environment <ns0:ref type='bibr' target='#b29'>(Oniciuc et al., 2018)</ns0:ref>. Recent studies using functional metagenomic screening of cattle feces reported the maximum number of AMR genes found per animal was 26 <ns0:ref type='bibr' target='#b47'>(Wichmann et al., 2014)</ns0:ref>, which was much lower than the number identified from soil samples in this experiment. The identified AMR genes have broad biological activities and might have other functions, rather than only AMR gene encoding. Take the efflux pumps as an example, as it is usually one of the largest AMR mechanisms; however, clinical and laboratory studies suggest efflux pumps have a role in virulence and the adaptive responses as well <ns0:ref type='bibr' target='#b10'>(Du et al., 2018)</ns0:ref>. The multi-drug resistance gene classes were conferred to phenicol, lincosamide, oxazolidinones (linezolid), pleuromutilin, and streptogramin <ns0:ref type='bibr' target='#b27'>(Noyes et al., 2016a)</ns0:ref>. However, in the RBS (down slope, but no direct animal input from cattle manure and poultry litter), multidrug resistance genes were identified. Therefore, it is possible some AMR genes were not from anthropogenic sources, but rather a naturally occurring community component <ns0:ref type='bibr' target='#b3'>(Bhullar et al., 2012)</ns0:ref>, or that surface runoff moved AMR genes downslope. Similarly, <ns0:ref type='bibr' target='#b35'>Rothrock et al. (2016)</ns0:ref> indicated antibiotic resistant Listeria and Salmonella spp. occur in all-natural, antibiotic-free, pasture-raised broiler flocks. Future work is needed evaluating the potential movement of AMR PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed genes via surface water runoff. <ns0:ref type='bibr' target='#b12'>Durso et al. (2016)</ns0:ref> also characterized native Nebraska prairie soils that had not been affected by human or food-animal waste products and found that all prairies contained tetracycline and cefotaxime-resistant bacteria, and 48% of soil bacteria were resistant to two or more antibiotics. <ns0:ref type='bibr' target='#b3'>Bhullar et al. (2012)</ns0:ref> also reported that AMR bacteria and genes can be found from in pristine soil environments that have not been exposed to human antibiotic use, from which, some strains were resistant to a wide range of different commercially available antibiotics. <ns0:ref type='bibr' target='#b5'>Cadena et al. (2018)</ns0:ref> also reported that tetracycline and sulfonamide antibiotic resistance genes can be identified from organic farming operations.</ns0:p><ns0:p>Based on the MEGARes database, the macrolides, lincosamides, and streptogramins (MLS)</ns0:p><ns0:p>A and B were classified as MLS drugs <ns0:ref type='bibr'>(Lakin et al., 2016)</ns0:ref>, and were identified in soil samples in the present experiment. The MLS class, according to <ns0:ref type='bibr' target='#b40'>Tenson et al. (2003)</ns0:ref>, 'contains structurally different but functionally similar drugs acting by binding to the 50S ribosomal subunit and blocking the path where nascent peptides exit the ribosome.' <ns0:ref type='bibr' target='#b28'>Noyes et al. (2016b)</ns0:ref> reported that MLS resistance genes can be found in both cattle and calves and were equally abundant between dairy and beef herds. Overall, the resistance classes of metronidazole and thiostrepton were identified only from the RBR group, and bacitracin resistance genes were found only in the CG treatment. Due to the limitation of the sample number for metagenomic sequencing, further studies are necessary to estimate the influence of animal inputs on AMR genes.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Results characterized the abundance of AMR genes following 14-years of pasture management using Q-PCR and metagenomics sequencing. The quantitative amplification method suggests increased abundances in three AMR-associated genes (ermB, sulI, and intlI) in Manuscript to be reviewed Manuscript to be reviewed Pasture treatments include: CG (continuously grazed), H (hayed), and RBR (rotationally grazed with a fenced off riparian buffer). The RBR treatment consists of an additional fenced riparian buffer strip (RBS) that was ungrazed (no cattle manure) without direct poultry litter applications.</ns0:p><ns0:note type='other'>Figure Captions</ns0:note><ns0:p>Grey=CG, Yellow=H, Blue=RBR, and Orange=RBS.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 1</ns0:note><ns0:p>Schematic representation of the experimental set-up. </ns0:p><ns0:note type='other'>Figure 3</ns0:note><ns0:p>Relative proportion of AMR genes in grassland soils based on pasture managment. Manuscript to be reviewed Resistance genes in three features Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>found three AMR associated genes(ermB, sulI, and intlI) in poultry litter in 2019, but not in 2018. These differing results between years indicates gene presence varied annually perhaps due to differences in environmental or animal management factors. There was a difference identified from the ermB gene between 2018 and 2019 with a greater abundance in 2019 and less PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Diagram of the experimental set-up (nine watersheds total, consistently managed from</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Mean abundances of three AMR associated genes, ermB, sulI and intlI amplified from</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. The relative proportion of AMR resistance gene classes in soils from different pasture</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Schematic representation of the experimental set-up. Randomized complete block design with three replications (nine watersheds total) from 2004-2018. All areas have received annual poultry litter applications (except for the RBS area). The RBS received neither poultry litter nor cattle manure inputs. CG and RBR received cattle manure. Each watershed was divided, perpendicular to the slope into three zones [corresponding to shoulder (A), upper backslope (B), and lower backslope (C) positions], whereas the RBR consisted of these three zones plus the RBS (zone 4). [Soil samples, n = 120; cattle manure, n = 12; poultry litter, n = 6; and, shotgun sequencing, soil, n=6].</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Mean abundances of three AMR associated genes, ermB, sulI and intlI amplified from soil genomic DNA samples based on (A) pasture management (CG, RBR, H, and RBS), (B) sampling time (pre and post poultry litter application) and (C) zone (zone 1, zone 2, zone 3, and zone 4). Error bars represent standard errors. The star indicates a significant difference at an alpha level of 0.05.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='27,42.52,70.87,525.00,393.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='31,42.52,70.87,525.00,455.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head /><ns0:label /><ns0:figDesc>soils may be due to long-term cattle manure deposition and poultry litter applications to a lesser extent. Using shotgun metagenomic sequencing, we identified the relative abundance of AMR genes were greater in CG than H, indicating that cattle manure deposition may serve as an AMR source to the environment (relative to poultry litter applications). Additionally, conservation pasture management practices such as rotationally grazing and filter strips decreased soil AMR gene presence, as the unfertilized fenced riparian buffer strip displayed 31.58% lower gene abundance (relative to the CG treatment, based on the AMR gene numbers identified through metagenomic sequencing).While the metagenomic approach has important applications in investigating AMR genes, it is noteworthy that metagenomic methods do have limitations and results may be affected by incomplete resistome databases. Overall, results illustrate that cattle manure inputs may influence AMR abundance in soils and conservation management may minimize AMR gene presence in the environment.</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Sequence and properties of the Q-PCR primers used in this project.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Figure 3. The relative proportion of AMR resistance gene classes in soils from different</ns0:cell></ns0:row><ns0:row><ns0:cell>pasture management systems. Six soil genomic DNA extracts were sequenced by using</ns0:cell></ns0:row><ns0:row><ns0:cell>shotgun metagenomic sequencing to evaluate the impact of pasture management on</ns0:cell></ns0:row><ns0:row><ns0:cell>antibiotic resistant genes. Each AMR gene classes was normalized to 100% for identifying the</ns0:cell></ns0:row><ns0:row><ns0:cell>percentage of resistance genes from each treatment (CG, H, RBR, and RBS) in each class of</ns0:cell></ns0:row><ns0:row><ns0:cell>resistance gene. Pasture management includes continuously grazed (CG), hayed (H), and</ns0:cell></ns0:row><ns0:row><ns0:cell>rotational grazed with a fenced riparian buffer (RBR). The RBR treatment consists of an</ns0:cell></ns0:row><ns0:row><ns0:cell>additional fenced riparian buffer strip (RBS) that was a non-grazed zone without direct</ns0:cell></ns0:row><ns0:row><ns0:cell>addition of poultry litter or grazing that had trees. Grey=CG, Yellow=H, Blue=RBR, and</ns0:cell></ns0:row><ns0:row><ns0:cell>Orange=RBS.</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>ANOVA results illustrating the differences of the abundance of three AMR associated genes were impacted by the single factor, animals (cattle manure vs. poultry litter), and year(2018 vs. 2019), and interaction between these two factors in cattle manure and poultry litter samples collected from 2018-2019.</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='2'>Parameter Factor</ns0:cell><ns0:cell>Quantity per gram</ns0:cell><ns0:cell cols='2'>F-value P-value</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>(log gene copies/gram</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>dry weight manure)</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>ermB</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.66&#61617;0.39 6.298</ns0:cell><ns0:cell>0.023*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 2.45&#61617;0.99</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 2.77&#61617;0.64</ns0:cell><ns0:cell>8.433</ns0:cell><ns0:cell>0.010*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 5.08&#61617;0.47</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>0.141</ns0:cell><ns0:cell>0.711</ns0:cell></ns0:row><ns0:row><ns0:cell>sulI</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.60&#61617;0.17 6.815</ns0:cell><ns0:cell>0.0189*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 2.40&#61617;1.18</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 3.07&#61617;0.79</ns0:cell><ns0:cell>3.452</ns0:cell><ns0:cell>0.082</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 4.66&#61617;0.34</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>3.893</ns0:cell><ns0:cell>0.062</ns0:cell></ns0:row><ns0:row><ns0:cell>intI</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.93&#61617;0.52 29.524</ns0:cell><ns0:cell>0.001*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 0.50&#61617;0.50</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 2.87&#61617;0.94</ns0:cell><ns0:cell>0.865</ns0:cell><ns0:cell>0.366</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 4.04&#61617;0.85</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>0.461</ns0:cell><ns0:cell>0.505</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 4 (on next page)</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Resistance genes in three features (gene level, mechanism level, and class level).The number of genes, mechanism and class is the total number of unique AMR gene found without duplication. The gene hits are used as a count of how many times a given gene is found in the data. n= 6 soil samples [one replication of CG and H, with two replications for RBR and the RBS at a consistent landscape position landscape position, and sampling timing (i.e., zone 3 and post poultry litter applications)].</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Resistance genes in three features (gene level, mechanism level, and class level). The number of genes, mechanism and class is the total number of unique AMR gene found without duplication. The gene hits are used as a count of how many times a given gene is found in the data. n= 6 soil samples [one replication of CG and H, with two replications for RBR and the RBS at a consistent landscape position landscape position, and sampling timing (i.e., zone 3 and post poultry litter applications)].</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>CG</ns0:cell><ns0:cell>H</ns0:cell><ns0:cell>RBR</ns0:cell><ns0:cell>RBS</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Number</ns0:cell><ns0:cell>210</ns0:cell><ns0:cell>105</ns0:cell><ns0:cell>208</ns0:cell><ns0:cell>143</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Mechanism Number</ns0:cell><ns0:cell>55</ns0:cell><ns0:cell>42</ns0:cell><ns0:cell>53</ns0:cell><ns0:cell>40</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Class Number</ns0:cell><ns0:cell>18</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>17</ns0:cell></ns0:row><ns0:row><ns0:cell>Hits</ns0:cell><ns0:cell>308</ns0:cell><ns0:cell>139</ns0:cell><ns0:cell>312</ns0:cell><ns0:cell>192</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48736:1:2:NEW 5 Aug 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Editor's Decision MAJOR REVISIONS We received two very detailed reviews of your submission about AMR genes in grassland systems. Both reviewers found the manuscript scientifically relevant but that major revisions are needed. The text needs revision for style and length. I provide some specific examples below, but this is not a comprehensive list. Response: Authors appreciate the time and consideration of this Editor on our manuscript. All the suggestions provided by the Editor and Reviewers were made where appropriate and have greatly improved the paper. Data presentation: 1) Reformat Figures 2 and 3 to jitter, violin or box plots that allow readers to visualize the distribution of data. 2) Present the number or Miseq reads (raw and after QC) 3) Provide SRA ascension numbers in Methods. Response: 1) Figure 2 has been converted to a Box plot. Authors considered converting Figure 3 to a box plot, however, based on data type (relative proportion) and other previously published work reporting shotgun sequencing using the AMR++ pipeline. Therefore, the resolution has been improved and betalactams corrected as requested, but presentation was kept the same. 2) Supplementary Table 1 showed the Miseq read after QC. 3) Authors added the SRA accession numbers in methods. Specific examples: Line 40. Did you look at bacteria or just genes? Looking at bacteria would require culturing or live-dead metagenomic techniques (https://microbiomejournal.biomedcentral.com/articles/10.1186/s40168-017-0285-3). Response: Thanks for your comment. Yes, we only looked at genes, ‘bacteria’ was deleted. Line 49. Only Muhammad Ali is “the greatest.” Revise. Response: Appreciated, thank you. This change was made. Line 53. This sentence needs revision. Here and throughout, use the word “however” carefully and write more succinctly and directly. For example, replace “Additionally, soil sulI and intlI gene abundance increased following poultry litter applications, however, ermB, sulI, and intlI had greater gene copy abundances per gram dry weight in cattle manure than poultry litter” with “Poultry litter had lower abundance of AMR genes ermB, sulI, and intlI relative to cattle manure. Long term application of this litter increased the abundance of sulI and intI genes in soil but the abundance of ermB …” Also, what happened to blactx-m-32?R Response: Agreed, ‘however’ was altered throughout the manuscript, as well was the suggested sentence integrated in the abstract. Per results in the original submission “blactx-m-32 was not found in any soils except two samples collected following poultry litter application in zone 2 of CG in 2016 and in zone 3 of the H treatment in 2017. The gene blactx-m-32 was not included in Table 2 and Fig. 2, due to no amplification.” Line 58. Replace “illustrate” with “suggest” Response: replaced. Line 62. As I understand most antibiotic use in animal husbandry is to increase weight gain not to treat infections. These antibiotic usages are not considered essential (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4638249/). Response: Essential meaning ‘fundamental’; revised per this point. Additionally, ‘weight gain’ was added. Line 63. Here and throughout, write succinctly. Replace “may provide selection pressure for the evolutionary phenomenon known as antibiotic …” with “selects for antibiotic…” Response: ‘May’ was used to highlight that repeated antibiotic use does not always result in AMR gene presence. Likewise, pristine, non-disturbed samples may have AMR genes. If authors alter the sentence as suggested, it will be an untrue statement (i.e., does not always select for AMR). Line 66. Delete “may,” unless you doubt the papers you present as examples. Response: Again, “may” because AMR is an evolutionary phenomenon and may occur without human impacts. Nonetheless, this change was made. Line 88. Delete “had” Response: Agreed; this change was made. Line 89 Delete “owing to greater organic animal inputs” (Yang et al., 2019b) and replace “suggesting” with “which suggests” Response: This suggestion was integrated into the revised manuscript. Line 90 Replace “increases microbiome diversity and may be a mechanism for improved soil health.” with “improves soil health.” Response: Done. Line 143. Delete “(C2H6O)” Response: Done. Line 147. Delete “which was used to present data per gram dry weight” Response: Erased. Line 210. Say what the difference is, instead of “There were differences in soil ermB gene detection among the treatments.” See also lines 221 and 231. Response: This sentence is confirming main effect differences, which is common at first mention of ANOVA results. This sentence was altered to be more to the point. Line 284. Here and throughout, delete “in order” Response: Agreed, this was deleted in two places. Line 386. Delete “work from” Response: Agreed, this was deleted. Line 392. How are “soil samples resistant”? Response: Meaning samples tested were resistant to specific chemicals listed. “Samples” was replaced with ‘bacteria”. Line 416. Conclusions should be one paragraph and not repeat previous sections (Methods, Results..) Response: Methods-focused sentences were removed and the paragraphs merged into one. References do not follow a consistent pattern. I provide examples below but this is not a comprehensive list. Please identify an author that is specifically responsible for proofreading references. Response: YY responsible for proofreading references. All references have been checked. Line 635. Provide vol:page-page. Response: Done. Line 640. Either period after abbreviations (Proc.) or not (Proc) consistently. Response: Done. Line 647l Why is this journal not abbreviated but most others are. Response: Done. Line 740 Use a consistent format for all references (Soil Biol. Biochem. 43, 2470 –…) should be 43:2470..). See also 751 and 756. Response: Done. Line 747. Why cap “Antibiotic” Response: Changed. Line 755. Only cap proper nouns in article titles. Response: Changed. Line 756. Vol: page-page only (no issue) Response: Done. Line 758 No period after Mbio see also 764. Response: Done. Reviewer 1 Basic reporting The aim of this study was to determine how the combination manure and litter application along with 3 different grazing procedures affects AMR gene levels in soil. The study is well justified in that there are few studies highlighting the effects of pasture management on AMR gene abundance. The figures are mostly effective, but a few modifications are necessary. The sequences are available on NCBI based on the links given on the website, but the links and accession numbers are not in the text. Response: Thank you for taking the time to review our manuscript and for the comment about this project being well-justified. Figures were revised and the accession numbers (SAMN 14783573-14783584) provided in the text. Fig 1 explains the experimental design clearly and was helpful to reference while reading through results. Response: Thank you for this comment. Fig 2 is also well labeled, except number of samples for each mean abundance (n) should be specified. It would be preferable to achieve a similar resolution as Fig 1 and 3, where there’s no obvious pixelation. Response: Figure 2 has been changed into box plot figure and pixilation improved. N was specified in the revised version. Fig 3 is clear, but it could be a helpful reminder in the legend to note how many of each of the soil samples (n) were used for shotgun sequencing. Response: Thank you for this comment; ‘Six soil genomic DNA extracts were sequenced by using shotgun metagenomic sequencing in…” was provided in the original version. Experimental design The use of 3 different pasture management practices allows for a comprehensive study and were described well, especially in fig 1. Sampling the soils and the manure and litter was informative, but would have been stronger if performed in the same year. A few more details in the stats and shotgun metagenomics are needed for clarification. Response: authors agree, unfortunately samples were not available during the same sampling years. The stats and shotgun method details are further explained in the revised version. Lines 183-185: Was Tukey’s HSD also applied for multiple comparisons? Response: Yes, verbiage was added. Lines 188-191: For clarification, which time point was chosen for CG and H, and was a pre- and post- application soil sample chosen for RBR and RBS each? It could be clearer to just list explicitly what the 6 samples are (for example, post-application zone 1 CG, post-application zone 1 H, post-application zone 1 RBR, etc.) Response: Agreed. This change was made. Lines 200-202: Is a positive hit 85% of the query read aligns with a subject AMR gene, or is a positive hit 85% of the subject AMR gene aligns with the query reads? Does the 85% refer to coverage or identity? What is the minimum length of a read? Response: Authors appreciate this question. The positive hit is 85% of the subject AMR gene aligns with the query reads. The 85% refer to coverage. The minimum length of a read is 150 and the mean Phred score is above 30. A statement per this effect was added. Validity of the findings There is an interesting story in the results, especially with the interaction effects, but more statistical methods need to be described to verify the analyses for the QPCR data. For example, how were the multiple comparisons made, and what were the detection limits for each of the genes? For values not detected for certain genes in the samples, were those values excluded, or were they substituted with a number at or below the detection limit? Response: JMP software was used to do the ANOVA. In JMP, fitted Y by X to fit the model, as well as were two multiple comparison techniques used: each pair Student's t, and Tukey-Kramer HSD (verbiage was added per this point). Regarding detection limits for each genes, the qPCR machine calculated and reported the quantity (gene copy numbers) based on the standard curve. The limit of detection (LOD) is 3 copies per reaction. Authors used 38 cycles as the accepted Cq value in a 100% efficient. For values not detected for certain genes in the samples, the quantity was 0, and log value was marked as 0.5 during ANOVA analysis or written as under detection limits. For example, there is no quantity of blactx-m-32 detected from all samples, so authors wrote it as below the detection limit and did not conduct ANOVA. For other genes, if some samples were under detection, the quantity is 0 and log value is 0.5. Lines 215-216: It would be clearer to note the units after the numbers. Rather than listing the mean log gene copy numbers measured from all the treatments, it could be more informative in the text to state by how many logs the grazing treatments increase the ermB compared to RBS. Same comment with lines 217-218. Response: Thanks for your comments. Log information was added. If something different is being requested, please specifiy and it can be addressed in the next iteration. Line 219-220: If there are no significant differences between treatments, it is necessary to state the means or log difference of those treatments. Response: Thanks for your comments. Log information was added when significant differences were found. Per previous comments, this section was too long and reviewers and the Editor requested it be shortened. Further, Authors feel that discussing non-sigificant results for every treatment and individual main effect is superfluous. Lines 233-235: These statements as they are structured appear like CG has significantly the greatest abundance of the 3 genes compared to the other treatments, but then the figure has only the star to indicate that RBS is significantly the least abundance of the genes. If CG is also significantly greater in gene abundances than the other grazing methods as well, it would be clearer to change the stars in the figure to connecting letters. Or if it’s a more interesting story, the text may also be reworded to note that the grazing methods that were coupled with manure and litter application were all significantly greater in gene abundances than RBS by over x log. This comment applies to all 3 genes and the other 2 factors. Response: Thanks for these comments. There is no significant difference among CG, H and RBR. Only significant differences were found is the least abundance of genes from RBS. That is also why Authors put a star on RBS to indicate RBS is significantly the least abundant of the genes. The text has been changed according to your suggestions. Lines 242-244: This paragraph describes detection and non-detection more than the abundance of each gene. This paragraph would be more useful in the beginning of the results to help give context of how many samples were used for comparisons by ANOVA. Response: Good suggestion, this paragraph was moved towards closer to the beginning of this section. Lines 245-247: Remove this sentence fragment and just skip to “Among these 93 samples…” and then use the absolute number of samples instead of the percentages in the list. Response: Thank you, this change was made. Line 250: change “ collected following” to “, one following”. Response: This change was made. Line 251: insert “one” between “and” and “in”. Response: Thank you, this was added. Lines 253-265: This paragraph is very interesting in that it highlights the main story told in the Q-PCR data, but it also seems redundant. If the first 3 paragraphs could be reframed as suggested in an earlier comment, this paragraph could be excluded. Response: Authors agree that information could be condensed—this was done in the revised version. However, there is pertinent information in this section (e.g. landscape position, poultry litter application timing, year, and management effects) per AMR gene and sample source (litter, manure, soil) and therefore cannot be erased outright. Lines 280-281: How were the abundances of sul1 and intI1 not significantly different between years when they were detected in one year but not the other? The statistics section of the methods also needs to have a statement of how non-detectable values were incorporated into the analysis if this is the case. Response: The abundance of sulI and intlI was detected in both years, but no significant difference found based on the year factor. This is different to the gene of blactx-m-32, because the gene of blactx-m-32 cannot be detected in any poultry litter and cattle manure sample. One sentence had been added in the method section per this point. Lines 285-289: These numbers are already listed in the table, so these sentences can be omitted. Response: Authors felt that this was important information to include in the text but it is now erased in the revised version. Lines 323-324: In general, specific CTX-M genes can be difficult to detect using PCR methods since many similar genes are hybrids of 2 or more other CTX-M genes. In the future, Birkett et al. 2007 could be a good resource for detecting a range of CTX-M genes. Response: Thank you, that reference will be included in the future. Lines 342-345: This citation is a useful reference when discussing the importance of many classes of AMR genes in soil and the connection to human pathogens, but it does not connect well to the point that blaCTX-M-32 was not detected in soils in this study. Are there other studies that point out blaCTX-M-32 in soils or manure? Response: Not to the authors knowledge. Please suggest if there is one and it will be added. Line 392: Bacteria from soil samples? Response: Yes, it is now specified. Line 423: While interesting to point out, this is not pointed out in fig 2, but using letters instead of the stars would help depict this. Did the RBR practice also result in greater gene abundance than H as well since cattle manure was used here too? Response: Fig. 2 showed the result from qPCR, however, line 423 was talking about shotgun metagenomic sequencing results. Yes, shotgun metagenomic sequencing results indicated that RBR had greater numbers of AMR genes than H. Table S1: The legend appears missing. Response: It is unclear why this was removed when converted to a pdf; this heading is clearly in the word document. Please advise. Comments for the author The use of “AMR genes” and “ARGs” seems to be used interchangeably, but it looks like “AMR genes” is used more often, so for consistency, use only one term. Response: Agreed; AMR is now used exclusively. Reviewer 2 Basic reporting - Line 30: typo on Antibiotic resistance- please fix. Response: Thank you! - Line 40 (Abstract): What type of residues? If not focusing on this in the study, it would probably be better to remove, or if not, to clarify what type of residues the authors are referring to. Response: Erased. - Line 58-59: Saying as a conclusion in the abstract that poultry litter may minimize AMR genes might be a stretch given what this study showed. I would suggest removing that idea. Response: Indeed, poultry litter did result in fewer AMR genes. Nonetheless, the conclusions statement was reworded per this point. - Line 64: AMR is defined as antibiotic resistance, but usually AMR is referred as antimicrobial resistance. I would suggest defining AMR as antimicrobial resistance. Response: Thanks; indeed antimicrobial was used throughout but in this sentence, it is now corrected. - Line 71: on what type of soil was that application? I would suggest adding that information. Response: Authors are unclear by ‘type’—does this Reviewer mean Order, Class, or texture (e.g. silt loam), etc. Please specify. Also, if this added for this reference, it should also be added when referencing other soil-based AMR studies, which would add to the length substantially. - Line 72: Please add a citation for 'ARGs can be found naturally'. Response: Added. - Line 79: un-degraded is one word: undegraded. Response: Combined. - Line 83: Here, the authors talk about poultry litter for the 1st time but there were no previous studies in the background/Intro section that referred to poultry litter and ARGs. It would be nice to have some context about poultry litter the same way the other manures were mentioned. Response: ‘Manure’ includes any byproduct of animal husbandry and is used as a catch-all. Many of the studies referenced were based on poultry litter. This was clarified. - Line 97: any specific manure? If so, I would suggest being specific in the aims about the type of manure the authors evaluated. Response: “Broiler” poultry litter was added. - Line 643 (References): typo on the reference re: the word 'antibiotics'. Response: Thank you! Experimental design - Lines 105 and then line 109: It is a bit confusing to first read the experiment had 9 watersheds and then refer to only 3 watersheds in line 109. I would suggest clarifying this. Response: This was clarified, agreed! - Line 115: Please provide a reference to 'the best management strategy'. Response: This was added. - Lines 119-123: This portion is a bit confusing. I would suggest either removing some of it if it is not relevant, or adding a bit more detail to the figure to show what it means by shoulder, upper, etc. Response: This was clarified. - Line 127: Did this commercial farm give antibiotics to the broilers? That would be good to mention, and if known, it would be ideal to mention which specific antibiotics. Response: This was clarified in “Cattle antibiotics and drugs were used over the course of this experiment (Supplementary Table 2); although, without the information of antibiotics used during poultry production, it is difficult to ascertain that AMR associated genes were related to specific animal management practices.” Unfortunately, antibiotic use and growth production information is kept proprietary by broiler producers and is not provided to government researchers. - Line 131: I would suggest removing the plural in 'collections'. The sample collection section could be reworked a little bit to be clearer about the type of samples, timing, and number of samples of each type. Response: Subheading was changed as was the sample information per this request. - Lines 135-136: Please clarify if the soil samples were taken manually or with a robot of some sort. Response: ‘manuallly’ was added. - Line 140: Please clarify what the authors mean by in-house piles. Response: Specified. - I am a bit confused about the timing of sampling of poultry and cattle manure. Why was the cattle manure collected in 2018-2019 and poultry in 2016-2017?. Also, it is unclear how many times cattle manure samples were collected. Response: Both cattle manure and poultry litter samples were collected once per year (2 times total). Unfortunately, data were not available during the same years. - Line 150: when the authors say 'cattle manure, or poultry litter...'- so not all samples were analyzed the same way? Or should that 'or' be 'and'? Response: Now reads: cattle manure, and poultry litter. - Why were these four genes in particular chosen? Some explanation related to the decision behind choosing these genes would be good. Response: Thanks for your comments. Some sentences have been added to the last paragraph of introduction. - Line 165 is redundant. I would suggest removing it. Response: Erased. - I appreciated the authors giving lots of details on the steps from the qpcr and the manipulation of the data. It is not as common to find all these details. This makes it more transparent and reproducible. Repsonse: Thank you for this comment, it is greatly appreciated. - Line 184: is the log transformed data referring to each of the genes? I would suggest explaining this/expanding on it. Was each one of the 4 genes analyzed used as a dependent variable in the analyses, or were the 4 genes analyzed altogether? Response: Yes, each of the genes is based on the log transformed data. Authors mentioned this in the text previously, “an analysis of variance (ANOVA) was conducted on log transformed data using JMP software”. Indeed each gene was analyzed separately. - Line 189: Why were those 6 samples chosen for the metagenomics analyses? Some explanation about this would be good. Response: Only 6 were chosen due to costs. Also, the same rep and landscape position (the one with the least variability) was used. This information can be added if this Reviewer deems it necessary. Validity of the findings - The results section is a bit long. I would suggest the authors trying to summarize the results further. Some suggestions below. Response: This section is now shortened per this point. - Figure 2 has low resolution- the text is a bit blurry. Also, I could not see in the figure the A, B, C for each panel of figure 2. Also, I am a bit confused about the quantities mentioned for each gene and each part of the figure. In the tex, the quantities are referred to as micro log gene copy numbers per dry weight while in the figure the y axis is log only and it is hard to know the quantities exactly only inferred by the figure. Please clarify and be consistent with the text and figure. Response: Thanks for your comments. Figure 2 has been changed. - Lines 257-258: 'The gene...': Please reword/fix this sentence. Response: This change was made. - The paragraph that goes from line 253-265 can probably be integrated in the previous results. Some of the information is redundant and it makes the results too long. Response: This section was condensed and largely erased; however, there is pertinent information in this subheading (e.g. landscape position, poultry litter application timing, year, and management effects) per AMR gene and sample source (litter, manure, soil) and therefore cannot be erased outright. - Supplementary Table 1 would need a repeated heading as it extends beyond one page. Response: “Supplementary Table 1.” Was added - Line 271: I would suggest removing the word 'these'. Response: Removed. - Line 277: Here please clarify the units again as mentioned before for the micro gene- is this log or gene copies and in micro? Response: This µ refers to a population mean. It means the mean of log gene copies per gram dry weight. The text has been changed here. - Line 296: How was multi-drug resistance defined? How many resistance genes? Reponse: Based on the database of MEGARes 2.0, the multi-drug resistance was defined as genes and mechanisms that cause resistance to two or more different antibiotic classes. Typically, such mechanisms involve active extrusion of antibiotic molecules from the bacterial cell or mechanisms that prevent the drug from reaching its target. Text was added per this point. - Figure 3. Please capitalize betalactams to be consistent with the other headings. Reponse: Thanks for your comment. It has been corrected. Discussion: - Line 305: Please rephrase 'AMR genes is an evolutionary phenomenon' to something like ' AMR, including AMR genes is a naturally occurring phenomenon', something along those lines. Response: This change was made. - Line 325: add ' of' before the word ' AMR genes. Response: Added. - Line 326: add either 'to' or 'in' before 'fertilized soils'. Response: Added. - Line 343-344: I do not understand this sentence. There seem to be two ideas- finding the ctx-m and beta-lactamase genes and that they might be the same as the ones found in human pathogens. But finding these in soil does not necessarily imply they are in human pathogens. Please clarify the ideas. Response: Authors aimed at using this reference for indicating that blactx-m-32 is not a common AMR gene in soil, but it is the genes identified from human pathogens. That is also why we sampled soil samples and cannot find this gene. Nonetheless, authors deleted this sentence. - Somewhere in the intro and/or discussion it would be good to mention if these experimental watersheds receive the input potentially from other sources- human or other animals, etc. Response: No other animal or human inputs were applied. “Watersheds received no other human or animal inputs during the project duration” was added. - Line 354: Please also make a point to comment about the use of antimicrobials in your experimental design under your comparison sites and when talking about the animals. Response: This was clarified in “Cattle antibiotics and drugs were used over the course of this experiment (Supplementary Table 2); although, without the information of antibiotics used during poultry production, it is difficult to ascertain that AMR associated genes were related to specific animal management practices.” Unfortunately, antibiotic use and growth production information is kept proprietary by broiler producers and is not provided to government researchers. - Line 361: remove the word 'that'. Response: Removed. - Line 361- 362: Given only 2 years of data, I would suggest not making strong conclusions about the differences related to the temporal component. I think more years would be needed to compare that factors. Response: Authors were simply stating that year effects could have been due to environmental or management differences and did not feel that this was a strong statement in the least. Wording was revised but authors are unclear on this comment. Please advise. - Lines 376-380: Please rephrase this section. Response: This statement was revised. - Lines 390-397: This paragraph should be better integrated into the results of the experiment. It seems like floating there with two different ideas but are not well connected to the previous paragraph. Response: This paragraph is discussion and cannot be placed into the results section, per the guideline of PeerJ. This paragraph is now merged in with the preceding paragraph. - Lines 400-403. Please connect the idea about the use of beta-lactam antibiotics and the finding of beta-lactamase gene in your experiment., As it is, it reads as two different ideas not well connected. Response: This entire paragraph was erased. - Line 416: change 'characterize' for 'characterized'. Response: This change was made. - Line 418: remove the word 'these'. Response: Carried out. - Line 421: This idea of live and dead bacteria is the 1st time it appears. I would suggest talking about this during the discussion, or removing it if not relevant. Response: This was erased. - Supplementary Table 2: Please try to make the table more consistent. For example, Reason for the drug used includes deworm, parasites- what does it mean parasites vs deworm?; for Amount, also include route of administration and duration if that information is available. Response: This information is not available. If this Reviewer requests it, this Supplementary Table can be removed outright. Comments for the author This study presents an interesting contribution related to the potential dissemination of antimicrobial resistance (AMR) genes in the environment, specifically in soil. There is still a need for more studies evaluating AMR in soil. I have made specific suggestions and comments for this section. Overall I feel the paper can be more concise. I think once the concerns have been addressed, this paper will be worthy of publication and will add an important contribution to the field. Response: This paper has been condensed and revised per this Reviewers suggestions. Thank you again for your encouraging comments and your time. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The persistence of antimicrobial resistant (AMR) genes in the soil-environment is a concern, yet practices that mitigate AMR are poorly understood, especially in the US' largest agricultural land-use or grasslands. Animal manures, which are valuable sources of nutrients, may also contain AMR genes. The aim of this study was to enumerate AMR genes in grassland soils following 14-years of poultry litter and cattle manure deposition and evaluate if pasture management [continuously grazed (CG), hayed (H), rotationally grazed with a fenced riparian buffer (RBR), and a fenced riparian buffer strip (RBS), which excluded cattle grazing and poultry litter applications] impacts the presence and amount of AMR genes. Quantitative PCR (Q-PCR) was performed to enumerate four AMR genes (ermB, sulI, intlI, and bla ctx-m-32 ) in soil, cattle manure, and poultry litter environments. Six soil samples were additionally subjected to metagenomic sequencing and resistance genes were identified from assembled sequences. Following 14-years of continuous management, ermB, sulI, and intlI genes in soil were the highest (P&lt;0.05) following longterm continuous grazing (relative to conservation best management practices), suggesting overgrazing and continuous cattle manure deposition may increase AMR gene presence. In general, AMR gene prevalence increased downslope, suggesting potential lateral movement and accumulation based on landscape position. Poultry litter had lower abundance of AMR genes (ermB, sulI, and intlI) relative to cattle manure. Long-term applications of poultry litter increased the abundance of sulI and intlI genes in soil</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Veterinary pharmaceutical usage is a fundamental component of conventional poultry and bovine production for treating microbial infections and increasing weight gains <ns0:ref type='bibr' target='#b7'>(Collignon et al., 2009)</ns0:ref>. Repeated use of antibiotics during food-animal production may provide selection pressure for the evolutionary phenomenon known as antimicrobial resistance (AMR). Genes encoding resistance to antimicrobials and antibiotics, which can also naturally be found in many bacteria, can be transferred between organisms via horizontal gene transfer <ns0:ref type='bibr' target='#b19'>(Juhas, 2015)</ns0:ref>. Agricultural practices influence the prevalence and occurrence of AMR genes in soils. For example, soils amended with cattle manure not treated with antibiotics contained higher abundance of &#946;-lactam resistant bacteria than soils with inorganic fertilizer inputs <ns0:ref type='bibr'>(Udikovic-Kolica et al., 2014)</ns0:ref>. In another study, soil applications of swine manure increased erythromycin resistance gene abundance and remained high for a decade post-application <ns0:ref type='bibr' target='#b37'>(Scott et al., 2018)</ns0:ref>. However, it should also be noted that AMR genes can be found naturally <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>; for example, <ns0:ref type='bibr' target='#b5'>Cadena et al. (2018)</ns0:ref> identified tetracycline and sulfonamide resistant genes in organic farms without routine antibiotic usage.</ns0:p><ns0:p>There is recent interest in monitoring the dissemination of AMR genes into the environment, particularly those directly relevant to human and animal health, as consumers and producers are increasingly concerned about antibiotic resistance in food systems <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>. One goal of sustainable agriculture is to close nutrient cycles by applying animal manures to neighboring cropping systems. Additionally, depending on antibiotic properties, large quantities of Manuscript to be reviewed undegraded antibiotics exit animals to manures, including poultry litter (a combination of bedding material and excreta); for example, up to 90% of sulfonamides and 25-75% of tetracyclines may be excreted into manure as the parent compound <ns0:ref type='bibr' target='#b24'>(Kulshrestha et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b42'>Thiele-Bruhn et al., 2004)</ns0:ref>. From manure, antibiotics, genes encoding AMR, and microbes may be transferred to soil <ns0:ref type='bibr' target='#b8'>(Cook et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b17'>Heuer et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b50'>Zhang et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b16'>He et al., 2014)</ns0:ref>.</ns0:p><ns0:p>Therefore, cattle manure and poultry litter applications, which are valuable sources of nutrients such as N, P, and potassium (K), may also be a pathway for AMR bacteria and genes into the environment <ns0:ref type='bibr' target='#b48'>(Yang et al., 2019a)</ns0:ref>.</ns0:p><ns0:p>The ability of pasture management practices (i.e., filter strips and rotational grazing) to reduce AMR gene presence, prevalence, and movement to soils is largely unknown. Our previous work indicated that continuously grazed systems increased soil microbial community richness and diversity owing to greater organic animal inputs <ns0:ref type='bibr' target='#b49'>(Yang et al., 2019b)</ns0:ref>, which suggests manure increases microbiome diversity and improves soil health. However, animal manure may also be a source for AMR genes. Therefore, the current work aims to understand the impacts of pasture management on AMR bacteria and gene presence. This study focused on quantifying four AMR associated genes [i.e., erythromycin resistance gene (ermB), sulfonamide resistance gene (sulI), integrase gene (intlI), and &#946;-lactam resistance gene (bla ctx-m-32 )] present in pasture soil, cattle manure, and poultry broiler litter using Q-PCR in an effort to balance human, animal, and environmental priorities. These four genes are useful for understanding the ecology and biology of agricultural AMR genes in soil and manure systems <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>. We additionally applied metagenomic sequencing to reveal the suite of resistance genes in the soil community and to evaluate best management practices that may reduce the presence of AMR genes from manure and poultry litter applications to the soil.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Experimental Design</ns0:head><ns0:p>In 2004, a field study was initiated by <ns0:ref type='bibr' target='#b31'>Pilon et al. (2017a;</ns0:ref><ns0:ref type='bibr' target='#b32'>2017b;</ns0:ref><ns0:ref type='bibr'>2018)</ns0:ref> at the USDA-ARS Unit in Booneville, Arkansas to evaluate how pasture management affects water quality. Nine watersheds (average slope of 8%) were constructed on Enders and Leadvale silt loams. Each watershed had a total area of 0.14 ha, with the dominant grass species being bermudagrass (Cynodon dactylon L.). Briefly, three grazing strategies were implemented from 2004-2017 with three replications, including: continuously grazed (CG), hayed (H), and rotationally grazed with an ungrazed, fenced riparian strip (RBR; <ns0:ref type='bibr'>Yang et al., 2019)</ns0:ref> (Fig. <ns0:ref type='figure' target='#fig_4'>1</ns0:ref>). The CG treatment was consistently grazed by one to two calves during the year <ns0:ref type='bibr' target='#b31'>(Pilon et al., 2017a)</ns0:ref>. The H treatment was hayed three times annually (April, June, and October) to a height of 10 cm (no cattle in these watersheds). The RBR system is considered a best management strategy and was rotationally grazed based on forage height <ns0:ref type='bibr' target='#b31'>(Pilon et al., 2017a;</ns0:ref><ns0:ref type='bibr' target='#b32'>2017b;</ns0:ref><ns0:ref type='bibr'>2018)</ns0:ref>. Calves (three) were placed in rotationally grazed watersheds based on forage height (when heights were 20 to 25 cm) and removed (10 to 15 cm) <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Each watershed was divided into 3 zones (perpendicular to slope) given that topography widely affects the microbial biogeography <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Landscape positions corresponded to upper slope (zone 1), mid-slope (2), and downslope positions (3), whereas the RBR represented zone 4 <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. The riparian buffer strip (RBS) and served as the nested control. The length of the 3 zones in CG and H was 57 m and the length of the 3 zones in RBR was 42.75 m. Broiler litter was surface applied at 5.6</ns0:p><ns0:p>Mg dry matter per ha in April-May of each year per watershed (excluding the RBS). All poultry litter rates were equivalent on an aerial basis <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Broiler litter was obtained Isolation Kit (MoBio Laboratories Inc., Cat. 12888-100) according to the manufacturer's protocol. Extracted DNA were quantified using Quant-iT&#8482; PicoGreen&#8482; dsDNA Assay Kit (ThermoFisher Scientific, Cat. P7589) and used directly in quantitative Q-PCR. All 120, 6, and 12 soil, cattle manure, and poultry litter DNA samples, respectively, were subjected to Q-PCR for detection of four genes associated with AMR as described in the clinical isolates, which included ermB <ns0:ref type='bibr' target='#b12'>(Florez et al., 2014)</ns0:ref>, sulI <ns0:ref type='bibr' target='#b2'>(Barraud et al., 2010)</ns0:ref>, intlI <ns0:ref type='bibr' target='#b30'>(Pei et al., 2006)</ns0:ref>, and bla ctxm-32 <ns0:ref type='bibr' target='#b39'>(Szczepanowski et al., 2009)</ns0:ref>, using previously published primers (Table <ns0:ref type='table' target='#tab_3'>1</ns0:ref> Manuscript to be reviewed numbers were then determined using standard curves. Gene copy abundances were then normalized per gram dry weight of soil, cattle manure, and poultry litter after measuring the moisture content of each sample. Finally, the gene copy numbers per gram dry weight were transformed into log10 values for further statistical analysis as they were not normally distributed <ns0:ref type='bibr' target='#b14'>(Ganger et al., 2017)</ns0:ref>.</ns0:p><ns0:p>To detect significant differences for fixed effects (pasture management, sample collection timing, and zone) an analysis of variance (ANOVA) was conducted on log transformed data using JMP software [JMP&#174;12 <ns0:ref type='bibr'>(SAS Institute, 2007)</ns0:ref>] with replicate as a random effect.</ns0:p><ns0:p>Probability values less than 0.05 were considered significant and pairwise posthoc comparisons were made using Tukey's Honestly Significant Difference test. Samples below detection limit were excluded in the analysis.</ns0:p></ns0:div> <ns0:div><ns0:head>Metagenomic sequencing and data analysis</ns0:head><ns0:p>To evaluate long-term effects of pasture management on AMR genes, metagenomic sequencing was applied for 6 soil samples [post-application zone 3, CG; post-application zone 3 H; post-application zone 3 RBR, post-application zone 3, RBS all replication 1; and, postapplication zone 3 RBR, post-application zone 3, RBS replication 2) ]. Sequencing libraries were prepared according to the Illumina Miseq sample preparation guide. Metagenomic sequencing was performed using Miseq Reagent Kits v2 with paired-end 2 x 250 bp reads on the MiSeq platform (University of Tennessee Genomics Core; Knoxville, TN). Raw data were uploaded to NCBI with the accession number of SAMN 14783573-14783584. Read trimming and assembly were performed according to <ns0:ref type='bibr' target='#b43'>Tyson (2015)</ns0:ref>. Genomes were annotated using the AmrPlusPlus pipeline <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. All samples resulted in a total of 5.19 Gb of sequence data.</ns0:p><ns0:p>Trimmomatic was used for removal of low-quality bases and sequences <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Reads classified as host genome (Bos taurus and Gallus gallus) were removed from further analysis. The adapter contamination and low-quality reads were also removed. The database 'MEGARes' has been integrated inside the pipeline and used for identification of AMR genes.</ns0:p><ns0:p>AMR genes with a gene fraction (i.e. proportion of nucleotides that aligned with at least one query read) of &gt;85% coverage across all alignments were considered to be positively identified in a sample <ns0:ref type='bibr' target='#b27'>(Noyes et al., 2016a)</ns0:ref>. The minimum length of a read was 150 and the mean Phred score was above 30. The AMR gene analysis was carried out using the Resistome Analyzer tool <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. Utilizing this tool, three annotation levels were produced, which include gene-level (sequencing-level), mechanism-level, and class-level counts.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Distribution of four AMR associated genes in soil based on pasture management, landscape position, and sampling time</ns0:head><ns0:p>Soil ermB gene abundance varied among treatments (CG, H, RBR, and RBS) and zones (1, 2, 3, and 4) (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_8'>2A</ns0:ref>), although, sample collection time (pre-or post-poultry litter applications; P&gt;0.05) had no impact on the abundance of ermB gene (Table <ns0:ref type='table'>2</ns0:ref>; Fig. <ns0:ref type='figure' target='#fig_8'>2B</ns0:ref>). There was an interaction effect from pasture management and zone on the abundance of ermB genes.</ns0:p><ns0:p>Across pasture management, the highest abundance of ermB gene was found in the CG treatment (&#181; log gene copies per gram dry weight soil =3.03), followed by H (2.86 gene copies per gram dry weight soil), RBR (2.72 gene copies per gram dry weight soil) and RBS (0.73 gene copies per gram dry weight soil) (Fig. <ns0:ref type='figure' target='#fig_8'>2A</ns0:ref>). Compared with RBS, CG increased the abundance of ermB by 2.3 log, H increased the abundance of ermB by 2.13 log, and RB increased the abundance of ermB by 1.99 log. Among zones, the greatest abundance of ermB occurred in zone 3 (&#181; log gene copy numbers per dry weight=2.92), followed by zone 2 (2.91 gene copy numbers per dry weight), zone 1 (2.78 gene copy numbers per dry weight), and zone 4 (0.73 gene copy numbers per dry weight) (Fig. <ns0:ref type='figure' target='#fig_8'>2C</ns0:ref>). Compared with zone 4, zone 3 increased the abundance of ermB by 2.19 log, zone 2 increased the abundance of ermB by 2.18 log, zone 1 increased the abundance of ermB by 2.05 log. However, no abundance differences occurred between pre and post poultry litter applications (&#181; log gene copy numbers per gram dry weight in pre-sampling time = 2.86 vs.</ns0:p><ns0:p>post-sampling time=2.45) (Fig. <ns0:ref type='figure' target='#fig_8'>2B</ns0:ref>). There were differences in the abundance of the gene sulI among all three factors, including treatments, sampling time, and zone (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_5'>2</ns0:ref>). For pasture management, the highest abundance was found under CG (&#181; log gene copy numbers per dry weight=4.83), followed by RB (4.46), H (4.42), and RBS (2.93) (Fig. <ns0:ref type='figure' target='#fig_8'>2A</ns0:ref>). Among zones, the greatest abundance was found in zone 2 (&#181; log gene copy numbers per gram dry weight =4.66), followed by zone 1 (4.66), zone 3 (4.38), and zone 4 (2.93) (Fig. <ns0:ref type='figure' target='#fig_8'>2C</ns0:ref>). Differences in abundance were identified between pre and post poultry litter sampling time, with a higher abundance of sulI occurring post poultry litter applications (Fig. <ns0:ref type='figure' target='#fig_8'>2B</ns0:ref>; log gene copy numbers per gram dry weight=4.77 vs. pre-sampling= 4.03). There was also an interaction for pasture management by zone for the sulI gene. Similar to sulI, there were differences in the intlI gene based on all three factors (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_5'>2</ns0:ref>). Based on the influence from pasture management, ANOVA tests indicated that greatest abundances were found under long-term CG (&#181; log gene copy numbers per gram dry weight=3.41), followed by H (3.11), and RB (3.07). The least abundance of AMR genes were found in RBS (1.54) (Fig. <ns0:ref type='figure' target='#fig_8'>2A</ns0:ref>), with greatest intlI gene occurring in zone 2 (&#181; log gene copy numbers per gram dry weight =3.22), then zone 1 (3.19), zone 3 (3.18), and zone 4 (1.54) (Fig. <ns0:ref type='figure' target='#fig_8'>2C</ns0:ref>). The abundance of the intlI gene differed between pre and post sampling, with higher Manuscript to be reviewed abundances in soil samples collected after poultry litter application (&#181; log gene copy numbers per dry weight in post-sampling time=3.79 vs. pre-sampling =2.28) (Fig. <ns0:ref type='figure' target='#fig_8'>2B</ns0:ref>). There was pasture management by zone, pasture management by timing, and zone by timing interactions for the abundance of the intlI gene. After finding differences following long-term pasture management on the abundance of these three AMR associated genes, further analyses were conducted to illustrate the abundance of each AMR associated gene based on the pasture management treatments. Among these 93 samples, ermB was found in 77% of samples, while only one amplification was from the RBS (8% of RBS was amplified), and 92 samples were from all treatment groups (85% of treatment samples were amplified). Among these 92 positive samples from treatment groups, it included 78% of RBR samples, 92% of CG, 86% of H, and 8% of RBS. Gene sulI was detected in 119 out of 120 samples (99%) and intlI were detected in all samples (100%), while bla ctx-m-32 was not found in any soils except two (following poultry litter application in zone 2 of CG in 2016 and one in zone 3 of the H treatment in 2017). The gene bla ctx-m-32 was not included in the Table <ns0:ref type='table'>2</ns0:ref> and Fig.</ns0:p><ns0:p>2, due to no amplification. Abundance of these three AMR associated genes indicates there are greater abundances of each AMR associated genes found in CG, RBR and H, relative to RBS (P&lt;0.05; Fig. <ns0:ref type='figure' target='#fig_8'>2A</ns0:ref>). For the RBS (no grazing or direct manure or poultry litter deposition), there was no amplification of ermB gene from all samples during 2016, while only one sample included an ermB gene in 2017.</ns0:p><ns0:p>Overall, post poultry litter applications, soil samples had greater abundance of sulI and intlI genes than pre-application soils. In Fig. <ns0:ref type='figure' target='#fig_8'>2C</ns0:ref>, the abundance of these three AMR associated genes were split out based on zones. Based on the factor of zone, differences were observed in these three AMR associated genes, ermB, sulI, and intlI (P&lt;0.05). Among these four zones, the lowest abundance was found in zone 4 (no cattle manure or poultry litter) among these three genes.</ns0:p><ns0:p>Distribution of four AMR associated genes in cattle manure and poultry litter Considering continuous annual applications of cattle and poultry manure were applied to soils (over 14-years), authors were interested in the presence of the four AMR associated genes and whether the abundance varied between soils with manure applied from the two sources.</ns0:p><ns0:p>Results from Q-PCR indicated these three AMR associated genes (ermB, sulI and intlI) were found in all poultry litter samples collected in 2019; however, the abundance of AMR-associated genes from poultry litter in the year of 2018 were below the detection threshold. The gene of bla ctx-m-32 was not found in any poultry litter and cattle manure samples (Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref>). Based on the ANOVA, there were differences in these three AMR associated genes between cattle manure and poultry litter, with greater abundances occurring in cattle manure than poultry litter (53, 95, and 100% greater mean value of gene copies per gram dry weight for ermB, sulI, and intlI in cattle manure than poultry litter, respectively) (P&lt;0.05) (Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref>). The impact of sampling year on the abundance of ermB gene was found (P&lt;0.05), with greater abundance in 2019 compared to 2018.</ns0:p></ns0:div> <ns0:div><ns0:head>Prevalence of antimicrobial resistance genes based on pasture management</ns0:head><ns0:p>Purified genomic DNA extracts from six soil samples were chosen for shotgun metagenomic sequencing to evaluate the impact of pasture management on AMR genes. Several unique AMR genes per treatment were identified ( Manuscript to be reviewed can be found in the output file (Supplementary Table <ns0:ref type='table' target='#tab_3'>1</ns0:ref>). These identified resistance genes were listed from the greatest numbers of hits (multi-drug resistance class) to least (Bacitracin). Based on the database of MEGARes 2.0, the multi-drug resistance was defined as genes and mechanisms that cause resistance to two or more different antibiotic classes. Typically, such mechanisms involve active extrusion of antibiotic molecules from the bacterial cell or mechanisms that prevent the drug from reaching its target <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. The class of multi-drug resistance genes were identified as greater than other resistance gene classes among all treatments and RBS (Supplementary Table <ns0:ref type='table' target='#tab_3'>1</ns0:ref>). Fig. <ns0:ref type='figure' target='#fig_6'>3</ns0:ref> shows relative proportion of hits in each class level by treatments. Overall, the greatest (i.e., 33%) of identified genes from the multi-drug resistance class were found in the CG treatment, followed by RBR watersheds (28%), the RBS (24%), and H watersheds (15%).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Distribution of four AMR associated genes in soils based on pasture management, landscape position, and sampling time AMR is a naturally occurring phenomenon, and soils are considered a reservoir for AMR genes <ns0:ref type='bibr' target='#b21'>(Kieser et al., 2000)</ns0:ref>. Overall, pasture management (CG, H, RBR, and RBS) had an effect on three AMR-associated genes, ermB, sulI, and intlI (P&lt;0.05). Greater abundance of these three AMR associated gene in soils were detected in treatments receiving either long-term poultry litter or cattle manure inputs (CG, H, and RBR), while lower AMR gene abundances were found in RBS, which was not grazed and did not receive direct poultry litter applications. This indicates these three AMR-associated genes were potentially transmitted via animal feces and may be transferred into the soil through animal movement and land application. This finding was</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed consistent with other studies which found that the repeated application of animal manure increased antibiotic resistance genes in agricultural soils <ns0:ref type='bibr' target='#b26'>(Luby et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b22'>Kim et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The sample collection timing (pre or post poultry litter application) had an effect on two AMR-associated genes, sulI and intlI (P&lt;0.05). A greater abundance of these two genes in soils were detected in samples collected after poultry litter applications (July) rather than before poultry litter applications (April). The abundance of sulI and intlI genes increased after poultry litter applications, indicating poultry litter may include sulI and intlI genes and increase the abundance of sulI and intlI genes in soils. This result is consistent with previous work using 16S rRNA sequencing, which found that poultry litter timing greatly influenced soil community structure and gene abundance <ns0:ref type='bibr'>(Yang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b0'>Ashworth et al., 2017)</ns0:ref>. However, poultry litter application timing did not influence the other two genes, ermB and bla ctx-m-32 . Another study pointed out that the concentration of AMR genes [sulI, intlI, tetracycline (tetW), and streptomycin (strpB)] in soil following poultry litter fertilization were greater following 21 to 133 days after application <ns0:ref type='bibr' target='#b8'>(Cook et al., 2014)</ns0:ref>. These data suggest poultry litter applications may increase the abundance and persistence of AMR-associated genes within the soil. The factor of zone had an effect on the abundance of these three AMR-associated genes (ermB, sulI, and intlI) within the soil (P&lt;0.05), with higher abundance in zone 1, zone 2, and zone 3, and lowest abundance in zone 4. This result suggests that animal manure played an important role in enhancing the abundance of AMR associated genes into the soil. We also found that genes of sulI and intlI existed in the soil of zone 4, even though there was no input from animal manure in this region, thus indicating that these two AMR-associated genes may be inherent to the soil. Since some AMR genes were found in non-agricultural and un-grazed native soils, they were considered as a natural part of pristine habitats <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012 and</ns0:ref><ns0:ref type='bibr'>2016)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>This result showcases the importance of evaluating baseline and background levels of AMR genes when investigating the impact of human input in the occurrence of AMR bacteria and genes <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>.</ns0:p><ns0:p>The gene bla ctx-m-32 was not detected in most soil samples, indicating that bla ctx-m-32 was not prevalent in the locations sampled. Having information on AMR presence in soils is valuable, as previous observations have shown antibiotics may impact the soil microbial community composition and structure, which will ultimately influence ecosystem-scale processes by maintaining these AMR bacteria and genes <ns0:ref type='bibr' target='#b15'>(Gutierrez et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b41'>Toth et al., 2011)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Distribution of four AMR associated genes in cattle manure and poultry litter</ns0:head><ns0:p>Three AMR associated genes (ermB, sulI, and intlI) were more abundant in cattle manure compared to poultry litter. Although, previous studies derived the opposite conclusion. <ns0:ref type='bibr' target='#b46'>Wang et al. (2016)</ns0:ref> indicated that the ermB gene levels in poultry litter were greater than that of cattle manure. Cattle antibiotics and drugs were used over the course of this experiment (Supplementary Table <ns0:ref type='table'>2</ns0:ref>); though, without the information of antibiotics used during poultry production, it is difficult to ascertain that AMR associated genes were related to specific animal management practices. Regardless of where these AMR associated genes originate, we should pay attention to the abundance and movement of these resistance genes, such as ermB, because macrolides are a major broad-spectrum antibiotic for human use and play an important role in controlling Gram-positive bacterium infection clinically <ns0:ref type='bibr' target='#b20'>(Kanoh and Rubin, 2010)</ns0:ref>. We also Manuscript to be reviewed abundance in 2018. However, it is difficult to ascertain whether this difference was caused by animal inputs without the drug usage information on cattle and poultry in these two years.</ns0:p><ns0:p>Prevalence of antimicrobial resistance genes from shotgun sequencing following pasture management Quantifying the prevalence of specific AMR genes may use culture-independent methods, such as Q-PCR, as well as metagenomic sequencing <ns0:ref type='bibr' target='#b1'>(Agga et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b10'>Durso et al., 2012)</ns0:ref>.</ns0:p><ns0:p>Metagenomic sequencing allows for the tracking of AMR genes and identification of transmission of AMR from animals to the environment <ns0:ref type='bibr' target='#b29'>(Oniciuc et al., 2018)</ns0:ref>. Recent studies using functional metagenomic screening of cattle feces reported the maximum number of AMR genes detected per animal was 26 <ns0:ref type='bibr' target='#b47'>(Wichmann et al., 2014)</ns0:ref>, which was much lower than the number identified from soil samples in this experiment. The identified AMR genes have broad biological activities and might have other functions, rather than only AMR gene encoding. Take the efflux pumps as an example, as it is usually one of the largest AMR mechanisms; however, clinical and laboratory studies suggest efflux pumps have a role in virulence and the adaptive responses as well <ns0:ref type='bibr' target='#b9'>(Du et al., 2018)</ns0:ref>. The multi-drug resistance gene classes were conferred to phenicol, lincosamide, oxazolidinones (linezolid), pleuromutilin, and streptogramin <ns0:ref type='bibr' target='#b27'>(Noyes et al., 2016a)</ns0:ref>. However, in the RBS (down slope, but no direct animal input from cattle manure and poultry litter), multidrug resistance genes were identified. Therefore, it is possible some AMR genes were not from anthropogenic sources, but rather a naturally occurring community component <ns0:ref type='bibr' target='#b3'>(Bhullar et al., 2012)</ns0:ref>, or that surface runoff moved AMR genes downslope. Similarly, <ns0:ref type='bibr' target='#b35'>Rothrock et al. (2016)</ns0:ref> indicated antibiotic resistant Listeria and Salmonella spp. occur in all-natural, antibiotic-free, pasture-raised broiler flocks. Future work is needed evaluating the potential movement of AMR PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed genes via surface water runoff <ns0:ref type='bibr' target='#b18'>(Jacobs et al., 2019)</ns0:ref>. <ns0:ref type='bibr' target='#b11'>Durso et al. (2016)</ns0:ref> also characterized native Nebraska prairie soils that had not been affected by human or food-animal waste products and found that all prairies contained tetracycline and cefotaxime-resistant bacteria, and 48% of soil bacteria were resistant to two or more antibiotics. <ns0:ref type='bibr' target='#b3'>Bhullar et al. (2012)</ns0:ref> also reported that AMR bacteria and genes can be found from in pristine soil environments that have not been exposed to human antibiotic use, from which, some strains were resistant to a wide range of different commercially available antibiotics. <ns0:ref type='bibr' target='#b5'>Cadena et al. (2018)</ns0:ref> also reported that tetracycline and sulfonamide antibiotic resistance genes can be identified from organic farming operations.</ns0:p><ns0:p>Based on the MEGARes database, the macrolides, lincosamides, and streptogramins (MLS)</ns0:p><ns0:p>A and B were classified as MLS drugs <ns0:ref type='bibr'>(Lakin et al., 2016)</ns0:ref>, and were identified in soil samples in the present experiment. The MLS class, according to <ns0:ref type='bibr' target='#b40'>Tenson et al. (2003)</ns0:ref>, 'contains structurally different but functionally similar drugs acting by binding to the 50S ribosomal subunit and blocking the path where nascent peptides exit the ribosome.' <ns0:ref type='bibr' target='#b28'>Noyes et al. (2016b)</ns0:ref> reported that MLS resistance genes can be detected in both cattle and calves and were equally abundant between dairy and beef herds. Overall, the resistance classes of metronidazole and thiostrepton were identified only from the RBR group, and bacitracin resistance genes were detected only in the CG treatment. Due to the limitation of the sample number for metagenomic sequencing, further studies are necessary to estimate the influence of animal inputs on AMR genes.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Results characterized the abundance of AMR genes following 14-years of pasture management using Q-PCR and metagenomics sequencing. The quantitative amplification method suggests increased abundances in three AMR-associated genes (ermB, sulI, and intlI) in Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure Captions</ns0:note><ns0:note type='other'>Figure 1</ns0:note><ns0:p>Schematic representation of the experimental set-up. Manuscript to be reviewed Resistance genes in three features Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>detected three AMR associated genes (ermB, sulI, and intlI) in poultry litter in 2019, but not in 2018. These differing results between years indicates gene presence varied annually perhaps due to differences in environmental or animal management factors. There was a difference identified from the ermB gene between 2018 and 2019 with a greater abundance in 2019 and less PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Diagram of the experimental set-up (nine watersheds total, consistently managed from</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Mean abundances of three AMR associated genes, ermB, sulI and intlI amplified from</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. The relative proportion of AMR resistance gene classes in soils from different pasture</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Schematic representation of the experimental set-up. Randomized complete block design with three replications (nine watersheds total) from 2004-2018. All areas have received annual poultry litter applications (except for the RBS area). The RBS received neither poultry litter nor cattle manure inputs. CG and RBR received cattle manure. Each watershed was divided, perpendicular to the slope into three zones [corresponding to shoulder (A), upper backslope (B), and lower backslope (C) positions], whereas the RBR consisted of these three zones plus the RBS (zone 4). [Soil samples, n = 120; cattle manure, n = 12; poultry litter, n = 6; and, shotgun sequencing, soil, n=6].</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='27,42.52,70.87,525.00,393.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='29,72.00,72.00,431.90,209.98' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='29,72.00,291.06,401.35,200.40' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='29,72.00,501.13,407.95,208.79' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='31,42.52,70.87,525.00,455.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head /><ns0:label /><ns0:figDesc>Table4). The number of unique AMR genes, mechanisms, and classes identified in H was lower than other treatments, including the RBS.Resistome Analyzer in AmrPlusPlus pipeline provided four levels of annotation database</ns0:figDesc><ns0:table /><ns0:note>hierarchy, at levels of gene, group, mechanism, and class. In each level, the counts of each gene PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head /><ns0:label /><ns0:figDesc>soils may be due to long-term cattle manure deposition and poultry litter applications to a lesser extent. Using shotgun metagenomic sequencing, we identified the relative abundance of AMR genes were greater in CG than H, indicating that cattle manure deposition may serve as an AMR source to the environment (relative to poultry litter applications). Additionally, conservation pasture management practices such as rotationally grazing and filter strips decreased soil AMR gene presence, as the unfertilized fenced riparian buffer strip displayed 31.58% lower gene abundance (relative to the CG treatment, based on the AMR gene numbers identified through metagenomic sequencing).While the metagenomic approach has important applications in investigating AMR genes, it is noteworthy that metagenomic methods do have limitations and results may be affected by incomplete resistome databases. Overall, results illustrate that cattle manure inputs may influence AMR abundance in soils and conservation management may minimize AMR gene presence in the environment.</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Sequence and properties of the Q-PCR primers used in this project.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Figure 3. The relative proportion of AMR resistance gene classes in soils from different</ns0:cell></ns0:row><ns0:row><ns0:cell>pasture management systems. Six soil genomic DNA extracts were sequenced by using</ns0:cell></ns0:row><ns0:row><ns0:cell>shotgun metagenomic sequencing to evaluate the impact of pasture management on</ns0:cell></ns0:row><ns0:row><ns0:cell>antibiotic resistant genes. Each AMR gene classes was normalized to 100% for identifying the</ns0:cell></ns0:row><ns0:row><ns0:cell>percentage of resistance genes from each treatment (CG, H, RBR, and RBS) in each class of</ns0:cell></ns0:row><ns0:row><ns0:cell>resistance gene. Pasture management includes continuously grazed (CG), hayed (H), and</ns0:cell></ns0:row><ns0:row><ns0:cell>rotational grazed with a fenced riparian buffer (RBR). The RBR treatment consists of an</ns0:cell></ns0:row><ns0:row><ns0:cell>additional fenced riparian buffer strip (RBS) that was a non-grazed zone without direct</ns0:cell></ns0:row><ns0:row><ns0:cell>addition of poultry litter or grazing that had trees. Grey=CG, Yellow=H, Blue=RBR, and</ns0:cell></ns0:row><ns0:row><ns0:cell>Orange=RBS.</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>ANOVA results illustrating the differences of the abundance of three AMR associated genes were impacted by the single factor, animals (cattle manure vs. poultry litter), and year(2018 vs. 2019), and interaction between these two factors in cattle manure and poultry litter samples collected from 2018-2019.</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='2'>Parameter Factor</ns0:cell><ns0:cell>Quantity per gram</ns0:cell><ns0:cell cols='2'>F-value P-value</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>(log gene copies/gram</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>dry weight manure) &#61617; SD</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>ermB</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.66&#61617;0.39 6.298</ns0:cell><ns0:cell>0.023*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 2.45&#61617;0.99</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 2.77&#61617;0.64</ns0:cell><ns0:cell>8.433</ns0:cell><ns0:cell>0.010*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 5.08&#61617;0.47</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>0.141</ns0:cell><ns0:cell>0.711</ns0:cell></ns0:row><ns0:row><ns0:cell>sulI</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.60&#61617;0.17 6.815</ns0:cell><ns0:cell>0.0189*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 2.40&#61617;1.18</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 3.07&#61617;0.79</ns0:cell><ns0:cell>3.452</ns0:cell><ns0:cell>0.082</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 4.66&#61617;0.34</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>3.893</ns0:cell><ns0:cell>0.062</ns0:cell></ns0:row><ns0:row><ns0:cell>intI</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.93&#61617;0.52 29.524</ns0:cell><ns0:cell>0.001*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 0.50&#61617;0.50</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 2.87&#61617;0.94</ns0:cell><ns0:cell>0.865</ns0:cell><ns0:cell>0.366</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 4.04&#61617;0.85</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>0.461</ns0:cell><ns0:cell>0.505</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Resistance genes in three features (gene level, mechanism level, and class level).The number of genes, mechanism and class is the total number of unique AMR gene found without duplication. The gene hits are used as a count of how many times a given gene is found in the data. n= 6 soil samples [one replication of CG and H, with two replications for RBR and the RBS at a consistent landscape position landscape position, and sampling timing (i.e., zone 3 and post poultry litter applications)].</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Resistance genes in three features (gene level, mechanism level, and class level). The number of genes, mechanism and class is the total number of unique AMR gene found without duplication. The gene hits are used as a count of how many times a given gene is found in the data. n= 6 soil samples [one replication of CG and H, with two replications for RBR and the RBS at a consistent landscape position landscape position, and sampling timing (i.e., zone 3 and post poultry litter applications)].</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>CG</ns0:cell><ns0:cell>H</ns0:cell><ns0:cell>RBR</ns0:cell><ns0:cell>RBS</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Number</ns0:cell><ns0:cell>210</ns0:cell><ns0:cell>105</ns0:cell><ns0:cell>208</ns0:cell><ns0:cell>143</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Mechanism Number</ns0:cell><ns0:cell>55</ns0:cell><ns0:cell>42</ns0:cell><ns0:cell>53</ns0:cell><ns0:cell>40</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Class Number</ns0:cell><ns0:cell>18</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>17</ns0:cell></ns0:row><ns0:row><ns0:cell>Hits</ns0:cell><ns0:cell>308</ns0:cell><ns0:cell>139</ns0:cell><ns0:cell>312</ns0:cell><ns0:cell>192</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48736:2:0:NEW 2 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Editor's Decision MINOR REVISIONS I agree with the reviewers that Figure 2, while an improvement, needs work. I suggest defining the boxes in the figure, so the reader can identify the treatments. Also, use a consistent format for journals in references. Some are not abbreviated (line 450), some are with a period (line 463) and some without (line 466). Line 474. This reference is incomplete. Line 517. Only capitalize proper nouns in titles (not Antibiotic). See also line 588. Response: Authors appreciate the time and consideration of this Editor for our manuscript. All the suggestions provided by the Editor and Reviewers were made where appropriate and have greatly improved the paper. Specifically, references and captions have been altered to improve clarity. Reviewer 1 Basic reporting The grammar improvements have made this manuscript a smoother experience to read, and their conclusions indeed make sense given their data and past research. Most of the suggestions here are minor, but figure 2 still needs improvement. Response: Thank you for taking the time to improve our manuscript. All changes have been made and have improved the paper. Line 100: insert “to” before “balance”. Response: Added. Line 104: insert “to” before “evaluate”. Response: Added, thank you. Figure 2: The boxplots are much more informative than the bars from before. However, differentiating between the stars indicating significance and the dot plots that indicate the outliers is difficult visually. It would still be more informative to include the exact results of the Tukey’s differences in the figure. JMP is usually pretty clear with providing connecting letters to indicate exactly which pairwise comparisons are significant, and the letters would also be easier to see than the stars. Response: Figure altered per this request. Table 3: For the 3rd column, is this the mean quantity ± standard deviation? Response: Yes, this was added. Experimental design Lines 149-150: When was poultry litter applied? Just wondering how much time passed between application of litter and sampling. Response: Two months was added in parenthesis. Lines 183-184: Thank you for including how you worked with values below detection. What were the detection limits per gram of soil? Response: We set the CT value of 38 as the detection threshold. If the CT value is higher than 38, we considered the DNA quantity is 0. The detection limits of DNA quantity per gram of soil is 0. Lines 208-210: Thank you for indicating that the 85% referred to coverage. For the queries that aligned with the subject AMR genes, did they have a minimum %identity? Response: No, authors did not set the minimum identity. We only set the minimum length of a read at 150. Validity of the findings Line 211: “pre-“ and “post-“ should replace “pre” and “post” Response: Thank you, this was changed. Line 212: I would change “detection” to “abundance” since ANOVA is really comparing the means between the pre- and post-litter application, so all the values that the test is comparing are detected Response: Great point. This was changed throughout. Line 248: I would change “abundance” here to “detection” in this case, or “proportions of detected to non-detected samples” Response: Great point. This was altered. Line 302: insert “,” after phenomenon Response: Added. Line 336: Change “found” to “detected” Response: Thank you, this change was made throughout. Line 343-344: I would just say ctx-m-32 wasn’t detected rather than there was no difference between the manure and litter, or even omit that fragment since it was already stated in the paragraph above Response: Agreed. Erased. Lines 361-362: It would be preferable to reword “relies” here since it’s not the only way to characterize AMR genes. Culture-independent methods are vital for many AMR genes from organisms that are hard to culture, but culture-dependent methods also have importance in AMR research (McLain et al. 2016, JEQ) Response: “relies” was erased. Lines 377, 379-380: Jacobs et al (2019, JEQ) could be a valuable reference here regarding AMR gene movement via storm water runoff Response: This reference was added. Reviewer 2 Basic reporting I feel the authors improved their background and justification of the paper. It now reads more clearly. Response: Thank you very much for this comment, authors appreciate the time and attention taken by this Reviewer. Minor comments: - Line 64: typo before the word 'fundamental'- a instead of an. Response: Authors are confused by this. In the submitted version an ‘a’ was before fundamental. - Line 101: I think there is a missing word between effort and balance. Please check. Response: Thank you, indeed a ‘to’ was added. - Line 115: Materials and Methods Response: Thank you for noticing this! - Line 204: it would be'using Tukey’s honestly significant difference test' Response: Corrected, thank you! - Line 220: Correct Bos taurus Response: Great catch, thank you. - Line 271: Please correct/modify the x before zone. Same for lines 283-284. Please express this using words instead of the x. Response: “By” is now used to replace ‘x’ in interactions. - Line 314: typo in applications Response: Thank you, altered. - Line 318: add 'the' before lowest Response: Added, thank you. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The persistence of antimicrobial resistant (AMR) genes in the soil-environment is a concern, yet practices that mitigate AMR are poorly understood, especially in the US' largest agricultural land-use or grasslands. Animal manures, which are valuable sources of nutrients, may also contain AMR genes. The aim of this study was to enumerate AMR genes in grassland soils following 14-years of poultry litter and cattle manure deposition and evaluate if pasture management [continuously grazed (CG), hayed (H), rotationally grazed with a fenced riparian buffer (RBR), and a fenced riparian buffer strip (RBS), which excluded cattle grazing and poultry litter applications] impacts the presence and amount of AMR genes. Quantitative PCR (Q-PCR) was performed to enumerate four AMR genes (ermB, sulI, intlI, and bla ctx-m-32 ) in soil, cattle manure, and poultry litter environments. Six soil samples were additionally subjected to metagenomic sequencing and resistance genes were identified from assembled sequences. Following 14-years of continuous management, ermB, sulI, and intlI genes in soil were the highest (P&lt;0.05) following longterm continuous grazing (relative to conservation best management practices), suggesting overgrazing and continuous cattle manure deposition may increase AMR gene presence. In general, AMR gene prevalence increased downslope, suggesting potential lateral movement and accumulation based on landscape position. Poultry litter had lower abundance of AMR genes (ermB, sulI, and intlI) relative to cattle manure. Long-term applications of poultry litter increased the abundance of sulI and intlI genes in soil</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Veterinary pharmaceutical usage is a fundamental component of conventional poultry and bovine production for treating microbial infections and increasing weight gains <ns0:ref type='bibr' target='#b7'>(Collignon et al., 2009)</ns0:ref>. Repeated use of antibiotics during food-animal production may provide selection pressure for the evolutionary phenomenon known as antimicrobial resistance (AMR). Genes encoding resistance to antimicrobials and antibiotics, which can also naturally be found in many bacteria, can be transferred between organisms via horizontal gene transfer <ns0:ref type='bibr' target='#b19'>(Juhas, 2015)</ns0:ref>. Agricultural practices influence the prevalence and occurrence of AMR genes in soils. For example, soils amended with cattle manure not treated with antibiotics contained higher abundance of &#946;-lactam resistant bacteria than soils with inorganic fertilizer inputs <ns0:ref type='bibr'>(Udikovic-Kolica et al., 2014)</ns0:ref>. In another study, soil applications of swine manure increased erythromycin resistance gene abundance and remained high for a decade post-application <ns0:ref type='bibr' target='#b37'>(Scott et al., 2018)</ns0:ref>. However, it should also be noted that AMR genes can be found naturally <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>; for example, <ns0:ref type='bibr' target='#b5'>Cadena et al. (2018)</ns0:ref> identified tetracycline and sulfonamide resistant genes in organic farms without routine antibiotic usage.</ns0:p><ns0:p>There is recent interest in monitoring the dissemination of AMR genes into the environment, particularly those directly relevant to human and animal health, as consumers and producers are increasingly concerned about antibiotic resistance in food systems <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>. One goal of sustainable agriculture is to close nutrient cycles by applying animal manures to neighboring cropping systems. Additionally, depending on antibiotic properties, large quantities of Manuscript to be reviewed undegraded antibiotics exit animals to manures, including poultry litter (a combination of bedding material and excreta); for example, up to 90% of sulfonamides and 25-75% of tetracyclines may be excreted into manure as the parent compound <ns0:ref type='bibr' target='#b24'>(Kulshrestha et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b42'>Thiele-Bruhn et al., 2004)</ns0:ref>. From manure, antibiotics, genes encoding AMR, and microbes may be transferred to soil <ns0:ref type='bibr' target='#b8'>(Cook et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b17'>Heuer et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b50'>Zhang et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b16'>He et al., 2014)</ns0:ref>.</ns0:p><ns0:p>Therefore, cattle manure and poultry litter applications, which are valuable sources of nutrients such as N, P, and potassium (K), may also be a pathway for AMR bacteria and genes into the environment <ns0:ref type='bibr' target='#b48'>(Yang et al., 2019a)</ns0:ref>.</ns0:p><ns0:p>The ability of pasture management practices (i.e., filter strips and rotational grazing) to reduce AMR gene presence, prevalence, and movement to soils is largely unknown. Our previous work indicated that continuously grazed systems increased soil microbial community richness and diversity owing to greater organic animal inputs <ns0:ref type='bibr' target='#b49'>(Yang et al., 2019b)</ns0:ref>, which suggests manure increases microbiome diversity and improves soil health. However, animal manure may also be a source for AMR genes. Therefore, the current work aims to understand the impacts of pasture management on AMR bacteria and gene presence. This study focused on quantifying four AMR associated genes [i.e., erythromycin resistance gene (ermB), sulfonamide resistance gene (sulI), integrase gene (intlI), and &#946;-lactam resistance gene (bla ctx-m-32 )] present in pasture soil, cattle manure, and poultry broiler litter using Q-PCR in an effort to balance human, animal, and environmental priorities. These four genes are useful for understanding the ecology and biology of agricultural AMR genes in soil and manure systems <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>. We additionally applied metagenomic sequencing to reveal the suite of resistance genes in the soil community and to evaluate best management practices that may reduce the presence of AMR genes from manure and poultry litter applications to the soil.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Experimental Design</ns0:head><ns0:p>In 2004, a field study was initiated by <ns0:ref type='bibr' target='#b31'>Pilon et al. (2017a;</ns0:ref><ns0:ref type='bibr' target='#b32'>2017b;</ns0:ref><ns0:ref type='bibr'>2018)</ns0:ref> at the USDA-ARS Unit in Booneville, Arkansas to evaluate how pasture management affects water quality. Nine watersheds (average slope of 8%) were constructed on Enders and Leadvale silt loams. Each watershed had a total area of 0.14 ha, with the dominant grass species being bermudagrass (Cynodon dactylon L.). Briefly, three grazing strategies were implemented from 2004-2017 with three replications, including: continuously grazed (CG), hayed (H), and rotationally grazed with an ungrazed, fenced riparian strip (RBR; <ns0:ref type='bibr'>Yang et al., 2019)</ns0:ref> (Fig. <ns0:ref type='figure' target='#fig_8'>1</ns0:ref>). The CG treatment was consistently grazed by one to two calves during the year <ns0:ref type='bibr' target='#b31'>(Pilon et al., 2017a)</ns0:ref>. The H treatment was hayed three times annually (April, June, and October) to a height of 10 cm (no cattle in these watersheds). The RBR system is considered a best management strategy and was rotationally grazed based on forage height <ns0:ref type='bibr' target='#b31'>(Pilon et al., 2017a;</ns0:ref><ns0:ref type='bibr' target='#b32'>2017b;</ns0:ref><ns0:ref type='bibr'>2018)</ns0:ref>. Calves (three) were placed in rotationally grazed watersheds based on forage height (when heights were 20 to 25 cm) and removed (10 to 15 cm) <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Each watershed was divided into 3 zones (perpendicular to slope) given that topography widely affects the microbial biogeography <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Landscape positions corresponded to upper slope (zone 1), mid-slope (2), and downslope positions (3), whereas the RBR represented zone 4 <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. The riparian buffer strip (RBS) and served as the nested control. The length of the 3 zones in CG and H was 57 m and the length of the 3 zones in RBR was 42.75 m. Broiler litter was surface applied at 5.6</ns0:p><ns0:p>Mg dry matter per ha in April-May of each year per watershed (excluding the RBS). All poultry litter rates were equivalent on an aerial basis <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Broiler litter was obtained Isolation Kit (MoBio Laboratories Inc., Cat. 12888-100) according to the manufacturer's protocol. Extracted DNA were quantified using Quant-iT&#8482; PicoGreen&#8482; dsDNA Assay Kit (ThermoFisher Scientific, Cat. P7589) and used directly in quantitative Q-PCR. All 120, 6, and 12 soil, cattle manure, and poultry litter DNA samples, respectively, were subjected to Q-PCR for detection of four genes associated with AMR as described in the clinical isolates, which included ermB <ns0:ref type='bibr' target='#b12'>(Florez et al., 2014)</ns0:ref>, sulI <ns0:ref type='bibr' target='#b2'>(Barraud et al., 2010)</ns0:ref>, intlI <ns0:ref type='bibr' target='#b30'>(Pei et al., 2006)</ns0:ref>, and bla ctxm-32 <ns0:ref type='bibr' target='#b39'>(Szczepanowski et al., 2009)</ns0:ref>, using previously published primers (Table <ns0:ref type='table' target='#tab_3'>1</ns0:ref> Manuscript to be reviewed numbers were then determined using standard curves. Gene copy abundances were then normalized per gram dry weight of soil, cattle manure, and poultry litter after measuring the moisture content of each sample. Finally, the gene copy numbers per gram dry weight were transformed into log10 values for further statistical analysis as they were not normally distributed <ns0:ref type='bibr' target='#b14'>(Ganger et al., 2017)</ns0:ref>.</ns0:p><ns0:p>To detect significant differences for fixed effects (pasture management, sample collection timing, and zone) an analysis of variance (ANOVA) was conducted on log transformed data using JMP software [JMP&#174;12 <ns0:ref type='bibr'>(SAS Institute, 2007)</ns0:ref>] with replicate as a random effect.</ns0:p><ns0:p>Probability values less than 0.05 were considered significant and pairwise posthoc comparisons were made using Tukey's Honestly Significant Difference test. Samples below detection limit were excluded in the analysis.</ns0:p></ns0:div> <ns0:div><ns0:head>Metagenomic sequencing and data analysis</ns0:head><ns0:p>To evaluate long-term effects of pasture management on AMR genes, metagenomic sequencing was applied for 6 soil samples [post-application zone 3, CG; post-application zone 3 H; post-application zone 3 RBR, post-application zone 3, RBS all replication 1; and, postapplication zone 3 RBR, post-application zone 3, RBS replication 2) ]. Sequencing libraries were prepared according to the Illumina Miseq sample preparation guide. Metagenomic sequencing was performed using Miseq Reagent Kits v2 with paired-end 2 x 250 bp reads on the MiSeq platform (University of Tennessee Genomics Core; Knoxville, TN). Raw data were uploaded to NCBI with the accession number of SAMN 14783573-14783584. Read trimming and assembly were performed according to <ns0:ref type='bibr' target='#b43'>Tyson (2015)</ns0:ref>. Genomes were annotated using the AmrPlusPlus pipeline <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. All samples resulted in a total of 5.19 Gb of sequence data.</ns0:p><ns0:p>Trimmomatic was used for removal of low-quality bases and sequences <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Reads classified as host genome (Bos taurus and Gallus gallus) were removed from further analysis. The adapter contamination and low-quality reads were also removed. The database 'MEGARes' has been integrated inside the pipeline and used for identification of AMR genes.</ns0:p><ns0:p>AMR genes with a gene fraction (i.e. proportion of nucleotides that aligned with at least one query read) of &gt;85% coverage across all alignments were considered to be positively identified in a sample <ns0:ref type='bibr' target='#b27'>(Noyes et al., 2016a)</ns0:ref>. The minimum length of a read was 150 and the mean Phred score was above 30. The AMR gene analysis was carried out using the Resistome Analyzer tool (https://github.com/cdeanj/resistomeanalyzer) <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. Utilizing this tool, three annotation levels were produced, which include gene-level (sequencing-level), mechanism-level, and class-level counts.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Distribution of four AMR associated genes in soil based on pasture management, landscape position, and sampling time</ns0:head><ns0:p>Soil ermB gene abundance varied among treatments (CG, H, RBR, and RBS) and zones (1, 2, 3, and 4) (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_12'>2A</ns0:ref>), although, sample collection time (pre-or post-poultry litter applications; P&gt;0.05) had no impact on the abundance of ermB gene (Table <ns0:ref type='table'>2</ns0:ref>; Fig. <ns0:ref type='figure' target='#fig_12'>2B</ns0:ref>). There was an interaction effect from pasture management and zone on the abundance of ermB genes.</ns0:p><ns0:p>Across pasture management, the highest abundance of ermB gene was found in the CG treatment (&#181; log gene copies per gram dry weight soil =3. Manuscript to be reviewed ermB by 1.99 log. Among zones, the greatest abundance of ermB occurred in zone 3 (&#181; log gene copy numbers per dry weight=2.92), followed by zone 2 (2.91 gene copy numbers per dry weight), zone 1 (2.78 gene copy numbers per dry weight), and zone 4 (0.73 gene copy numbers per dry weight) (Fig. <ns0:ref type='figure' target='#fig_12'>2C</ns0:ref>). Compared with zone 4, zone 3 increased the abundance of ermB by 2.19 log, zone 2 increased the abundance of ermB by 2.18 log, zone 1 increased the abundance of ermB by 2.05 log. However, no abundance differences occurred between pre and post poultry litter applications (&#181; log gene copy numbers per gram dry weight in pre-sampling time = 2.86 vs.</ns0:p><ns0:p>post-sampling time=2.45) (Fig. <ns0:ref type='figure' target='#fig_12'>2B</ns0:ref>). There were differences in the abundance of the gene sulI among all three factors, including treatments, sampling time, and zone (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_9'>2</ns0:ref>). For pasture management, the highest abundance was found under CG (&#181; log gene copy numbers per dry weight=4.83), followed by RB (4.46), H (4.42), and RBS (2.93) (Fig. <ns0:ref type='figure' target='#fig_12'>2A</ns0:ref>). Among zones, the greatest abundance was found in zone 2 (&#181; log gene copy numbers per gram dry weight =4.66), followed by zone 1 (4.66), zone 3 (4.38), and zone 4 (2.93) (Fig. <ns0:ref type='figure' target='#fig_12'>2C</ns0:ref>). Differences in abundance were identified between pre and post poultry litter sampling time, with a higher abundance of sulI occurring post poultry litter applications (Fig. <ns0:ref type='figure' target='#fig_12'>2B</ns0:ref>; log gene copy numbers per gram dry weight=4.77 vs. pre-sampling= 4.03). There was also an interaction for pasture management by zone for the sulI gene. Similar to sulI, there were differences in the intlI gene based on all three factors (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_9'>2</ns0:ref>). Based on the influence from pasture management, ANOVA tests indicated that greatest abundances were found under long-term CG (&#181; log gene copy numbers per gram dry weight=3.41), followed by H (3.11), and RB (3.07). The least abundance of AMR genes were found in RBS (1.54) (Fig. <ns0:ref type='figure' target='#fig_12'>2A</ns0:ref>), with greatest intlI gene occurring in zone 2 (&#181; log gene copy numbers per gram dry weight =3.22), then zone 1 (3.19), zone 3 (3.18), and zone 4 (1.54) (Fig. Manuscript to be reviewed 2C). The abundance of the intlI gene differed between pre and post sampling, with higher abundances in soil samples collected after poultry litter application (&#181; log gene copy numbers per dry weight in post-sampling time=3.79 vs. pre-sampling =2.28) (Fig. <ns0:ref type='figure' target='#fig_12'>2B</ns0:ref>). There was pasture management by zone, pasture management by timing, and zone by timing interactions for the abundance of the intlI gene. After finding differences following long-term pasture management on the abundance of these three AMR associated genes, further analyses were conducted to illustrate the abundance of each AMR associated gene based on the pasture management treatments. Among these 93 samples, ermB was found in 77% of samples, while only one amplification was from the RBS (8% of RBS was amplified), and 92 samples were from all treatment groups (85% of treatment samples were amplified). Among these 92 positive samples from treatment groups, it included 78% of RBR samples, 92% of CG, 86% of H, and 8% of RBS. Gene sulI was detected in 119 out of 120 samples (99%) and intlI were detected in all samples (100%), while bla ctx-m-32 was not found in any soils except two (following poultry litter application in zone 2 of CG in 2016 and one in zone 3 of the H treatment in 2017). The gene bla ctx-m-32 was not included in the Table <ns0:ref type='table'>2</ns0:ref> and Fig. <ns0:ref type='figure' target='#fig_9'>2</ns0:ref>, due to no amplification. Abundance of these three AMR associated genes indicates there are greater abundances of each AMR associated genes found in CG, RBR and H, relative to RBS (P&lt;0.05; Fig. <ns0:ref type='figure' target='#fig_12'>2A</ns0:ref>). For the RBS (no grazing or direct manure or poultry litter deposition), there was no amplification of ermB gene from all samples during 2016, while only one sample included an ermB gene in 2017.</ns0:p><ns0:p>Overall, post poultry litter applications, soil samples had greater abundance of sulI and intlI genes than pre-application soils. In Fig. <ns0:ref type='figure' target='#fig_12'>2C</ns0:ref>, the abundance of these three AMR associated genes were split out based on zones. Based on the factor of zone, differences were observed in these three AMR associated genes, ermB, sulI, and intlI (P&lt;0.05). Among these four zones, the lowest abundance was found in zone 4 (no cattle manure or poultry litter) among these three genes.</ns0:p><ns0:p>Distribution of four AMR associated genes in cattle manure and poultry litter Considering continuous annual applications of cattle and poultry manure were applied to soils (over 14-years), authors were interested in the presence of the four AMR associated genes and whether the abundance varied between soils with manure applied from the two sources.</ns0:p><ns0:p>Results from Q-PCR indicated these three AMR associated genes (ermB, sulI and intlI) were found in all poultry litter samples collected in 2019; however, the abundance of AMR-associated genes from poultry litter in the year of 2018 were below the detection threshold. The gene of bla ctx-m-32 was not found in any poultry litter and cattle manure samples (Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref>). Based on the ANOVA, there were differences in these three AMR associated genes between cattle manure and poultry litter, with greater abundances occurring in cattle manure than poultry litter (53, 95, and 100% greater mean value of gene copies per gram dry weight for ermB, sulI, and intlI in cattle manure than poultry litter, respectively) (P&lt;0.05) (Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref>). The impact of sampling year on the abundance of ermB gene was found (P&lt;0.05), with greater abundance in 2019 compared to 2018.</ns0:p></ns0:div> <ns0:div><ns0:head>Prevalence of antimicrobial resistance genes based on pasture management</ns0:head><ns0:p>Purified genomic DNA extracts from six soil samples were chosen for shotgun metagenomic sequencing to evaluate the impact of pasture management on AMR genes. Several unique AMR genes per treatment were identified ( Manuscript to be reviewed can be found in the output file (Supplementary Table <ns0:ref type='table' target='#tab_3'>1</ns0:ref>). These identified resistance genes were listed from the greatest numbers of hits (multi-drug resistance class) to least (Bacitracin). Based on the database of MEGARes 2.0, the multi-drug resistance was defined as genes and mechanisms that cause resistance to two or more different antibiotic classes. Typically, such mechanisms involve active extrusion of antibiotic molecules from the bacterial cell or mechanisms that prevent the drug from reaching its target <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. The class of multi-drug resistance genes were identified as greater than other resistance gene classes among all treatments and RBS (Supplementary Table <ns0:ref type='table' target='#tab_3'>1</ns0:ref>). Fig. <ns0:ref type='figure' target='#fig_10'>3</ns0:ref> shows relative proportion of hits in each class level by treatments. Overall, the greatest (i.e., 33%) of identified genes from the multi-drug resistance class were found in the CG treatment, followed by RBR watersheds (28%), the RBS (24%), and H watersheds (15%).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Distribution of four AMR associated genes in soils based on pasture management, landscape position, and sampling time AMR is a naturally occurring phenomenon, and soils are considered a reservoir for AMR genes <ns0:ref type='bibr' target='#b21'>(Kieser et al., 2000)</ns0:ref>. Overall, pasture management (CG, H, RBR, and RBS) had an effect on three AMR-associated genes, ermB, sulI, and intlI (P&lt;0.05). Greater abundance of these three AMR associated gene in soils were detected in treatments receiving either long-term poultry litter or cattle manure inputs (CG, H, and RBR), while lower AMR gene abundances were found in RBS, which was not grazed and did not receive direct poultry litter applications. This indicates these three AMR-associated genes were potentially transmitted via animal feces and may be transferred into the soil through animal movement and land application. This finding was Manuscript to be reviewed consistent with other studies which found that the repeated application of animal manure increased antibiotic resistance genes in agricultural soils <ns0:ref type='bibr' target='#b26'>(Luby et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b22'>Kim et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The sample collection timing (pre or post poultry litter application) had an effect on two AMR-associated genes, sulI and intlI (P&lt;0.05). A greater abundance of these two genes in soils were detected in samples collected after poultry litter applications (July) rather than before poultry litter applications (April). The abundance of sulI and intlI genes increased after poultry litter applications, indicating poultry litter may include sulI and intlI genes and increase the abundance of sulI and intlI genes in soils. This result is consistent with previous work using 16S rRNA sequencing, which found that poultry litter timing greatly influenced soil community structure and gene abundance <ns0:ref type='bibr'>(Yang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b0'>Ashworth et al., 2017)</ns0:ref>. However, poultry litter application timing did not influence the other two genes, ermB and bla ctx-m-32 . Another study pointed out that the concentration of AMR genes [sulI, intlI, tetracycline (tetW), and streptomycin (strpB)] in soil following poultry litter fertilization were greater following 21 to 133 days after application <ns0:ref type='bibr' target='#b8'>(Cook et al., 2014)</ns0:ref>. These data suggest poultry litter applications may increase the abundance and persistence of AMR-associated genes within the soil. The factor of zone had an effect on the abundance of these three AMR-associated genes (ermB, sulI, and intlI) within the soil (P&lt;0.05), with higher abundance in zone 1, zone 2, and zone 3, and lowest abundance in zone 4. This result suggests that animal manure played an important role in enhancing the abundance of AMR associated genes into the soil. We also found that genes of sulI and intlI existed in the soil of zone 4, even though there was no input from animal manure in this region, thus indicating that these two AMR-associated genes may be inherent to the soil. Since some AMR genes were found in non-agricultural and un-grazed native soils, they were considered as a natural part of pristine habitats <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012 and</ns0:ref><ns0:ref type='bibr'>2016)</ns0:ref>. Manuscript to be reviewed</ns0:p><ns0:p>This result showcases the importance of evaluating baseline and background levels of AMR genes when investigating the impact of human input in the occurrence of AMR bacteria and genes <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>.</ns0:p><ns0:p>The gene bla ctx-m-32 was not detected in most soil samples, indicating that bla ctx-m-32 was not prevalent in the locations sampled. Having information on AMR presence in soils is valuable, as previous observations have shown antibiotics may impact the soil microbial community composition and structure, which will ultimately influence ecosystem-scale processes by maintaining these AMR bacteria and genes <ns0:ref type='bibr' target='#b15'>(Gutierrez et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b41'>Toth et al., 2011)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Distribution of four AMR associated genes in cattle manure and poultry litter</ns0:head><ns0:p>Three AMR associated genes (ermB, sulI, and intlI) were more abundant in cattle manure compared to poultry litter. Although, previous studies derived the opposite conclusion. <ns0:ref type='bibr' target='#b46'>Wang et al. (2016)</ns0:ref> indicated that the ermB gene levels in poultry litter were greater than that of cattle manure. Cattle antibiotics and drugs were used over the course of this experiment (Supplementary Table <ns0:ref type='table'>2</ns0:ref>); though, without the information of antibiotics used during poultry production, it is difficult to ascertain that AMR associated genes were related to specific animal management practices. Regardless of where these AMR associated genes originate, we should pay attention to the abundance and movement of these resistance genes, such as ermB, because macrolides are a major broad-spectrum antibiotic for human use and play an important role in controlling Gram-positive bacterium infection clinically <ns0:ref type='bibr' target='#b20'>(Kanoh and Rubin, 2010)</ns0:ref>. We also Manuscript to be reviewed abundance in 2018. However, it is difficult to ascertain whether this difference was caused by animal inputs without the drug usage information on cattle and poultry in these two years.</ns0:p><ns0:p>Prevalence of antimicrobial resistance genes from shotgun sequencing following pasture management Quantifying the prevalence of specific AMR genes may use culture-independent methods, such as Q-PCR, as well as metagenomic sequencing <ns0:ref type='bibr' target='#b1'>(Agga et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b10'>Durso et al., 2012)</ns0:ref>.</ns0:p><ns0:p>Metagenomic sequencing allows for the tracking of AMR genes and identification of transmission of AMR from animals to the environment <ns0:ref type='bibr' target='#b29'>(Oniciuc et al., 2018)</ns0:ref>. Recent studies using functional metagenomic screening of cattle feces reported the maximum number of AMR genes detected per animal was 26 <ns0:ref type='bibr' target='#b47'>(Wichmann et al., 2014)</ns0:ref>, which was much lower than the number identified from soil samples in this experiment. The identified AMR genes have broad biological activities and might have other functions, rather than only AMR gene encoding. Take the efflux pumps as an example, as it is usually one of the largest AMR mechanisms; however, clinical and laboratory studies suggest efflux pumps have a role in virulence and the adaptive responses as well <ns0:ref type='bibr' target='#b9'>(Du et al., 2018)</ns0:ref>. The multi-drug resistance gene classes were conferred to phenicol, lincosamide, oxazolidinones (linezolid), pleuromutilin, and streptogramin <ns0:ref type='bibr' target='#b27'>(Noyes et al., 2016a)</ns0:ref>. However, in the RBS (down slope, but no direct animal input from cattle manure and poultry litter), multidrug resistance genes were identified. Therefore, it is possible some AMR genes were not from anthropogenic sources, but rather a naturally occurring community component <ns0:ref type='bibr' target='#b3'>(Bhullar et al., 2012)</ns0:ref>, or that surface runoff moved AMR genes downslope. Similarly, Rothrock et al. Manuscript to be reviewed genes via surface water runoff <ns0:ref type='bibr' target='#b18'>(Jacobs et al., 2019)</ns0:ref>. <ns0:ref type='bibr' target='#b11'>Durso et al. (2016)</ns0:ref> also characterized native Nebraska prairie soils that had not been affected by human or food-animal waste products and found that all prairies contained tetracycline and cefotaxime-resistant bacteria, and 48% of soil bacteria were resistant to two or more antibiotics. <ns0:ref type='bibr' target='#b3'>Bhullar et al. (2012)</ns0:ref> also reported that AMR bacteria and genes can be found from in pristine soil environments that have not been exposed to human antibiotic use, from which, some strains were resistant to a wide range of different commercially available antibiotics. <ns0:ref type='bibr' target='#b5'>Cadena et al. (2018)</ns0:ref> also reported that tetracycline and sulfonamide antibiotic resistance genes can be identified from organic farming operations.</ns0:p><ns0:p>Based on the MEGARes database, the macrolides, lincosamides, and streptogramins (MLS)</ns0:p><ns0:p>A and B were classified as MLS drugs <ns0:ref type='bibr'>(Lakin et al., 2016)</ns0:ref>, and were identified in soil samples in the present experiment. The MLS class, according to <ns0:ref type='bibr' target='#b40'>Tenson et al. (2003)</ns0:ref>, 'contains structurally different but functionally similar drugs acting by binding to the 50S ribosomal subunit and blocking the path where nascent peptides exit the ribosome.' <ns0:ref type='bibr' target='#b28'>Noyes et al. (2016b)</ns0:ref> reported that MLS resistance genes can be detected in both cattle and calves and were equally abundant between dairy and beef herds. Overall, the resistance classes of metronidazole and thiostrepton were identified only from the RBR group, and bacitracin resistance genes were detected only in the CG treatment. Due to the limitation of the sample number for metagenomic sequencing, further studies are necessary to estimate the influence of animal inputs on AMR genes.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Results characterized the abundance of AMR genes following 14-years of pasture management using Q-PCR and metagenomics sequencing. The quantitative amplification method suggests increased abundances in three AMR-associated genes (ermB, sulI, and intlI) in Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure Captions</ns0:note><ns0:note type='other'>Figure 1</ns0:note><ns0:p>Schematic representation of the experimental set-up. Manuscript to be reviewed Resistance genes in three features Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>03), followed by H (2.86 gene copies per gram dry weight soil), RBR (2.72 gene copies per gram dry weight soil) and RBS (0.73 gene copies per gram dry weight soil) (Fig. 2A). Compared with RBS, CG increased the abundance of ermB by 2.3 log, H increased the abundance of ermB by 2.13 log, and RB increased the abundance of PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>detected three AMR associated genes (ermB, sulI, and intlI) in poultry litter in 2019, but not in 2018. These differing results between years indicates gene presence varied annually perhaps due to differences in environmental or animal management factors. There was a difference identified from the ermB gene between 2018 and 2019 with a greater abundance in 2019 and less PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>(2016) indicated antibiotic resistant Listeria and Salmonella spp. occur in all-natural, antibiotic-free, pasture-raised broiler flocks. Future work is needed evaluating the potential movement of AMR PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Diagram of the experimental set-up (nine watersheds total, consistently managed from</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Mean abundances of three AMR associated genes, ermB, sulI and intlI amplified from</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. The relative proportion of AMR resistance gene classes in soils from different pasture</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Schematic representation of the experimental set-up. Randomized complete block design with three replications (nine watersheds total) from 2004-2018. All areas have received annual poultry litter applications (except for the RBS area). The RBS received neither poultry litter nor cattle manure inputs. CG and RBR received cattle manure. Each watershed was divided, perpendicular to the slope into three zones [corresponding to shoulder (A), upper backslope (B), and lower backslope (C) positions], whereas the RBR consisted of these three zones plus the RBS (zone 4). [Soil samples, n = 120; cattle manure, n = 12; poultry litter, n = 6; and, shotgun sequencing, soil, n=6].</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='27,42.52,70.87,525.00,393.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='29,72.00,72.00,431.90,209.98' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='29,72.00,291.06,401.35,200.40' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='29,72.00,501.13,407.95,208.79' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='31,42.52,70.87,525.00,455.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head /><ns0:label /><ns0:figDesc>Table4). The number of unique AMR genes, mechanisms, and classes identified in H was lower than other treatments, including the RBS.Resistome Analyzer in AmrPlusPlus pipeline provided four levels of annotation database</ns0:figDesc><ns0:table /><ns0:note>hierarchy, at levels of gene, group, mechanism, and class. In each level, the counts of each genePeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head /><ns0:label /><ns0:figDesc>soils may be due to long-term cattle manure deposition and poultry litter applications to a lesser extent. Using shotgun metagenomic sequencing, we identified the relative abundance of AMR genes were greater in CG than H, indicating that cattle manure deposition may serve as an AMR source to the environment (relative to poultry litter applications). Additionally, conservation pasture management practices such as rotationally grazing and filter strips decreased soil AMR gene presence, as the unfertilized fenced riparian buffer strip displayed 31.58% lower gene abundance (relative to the CG treatment, based on the AMR gene numbers identified through metagenomic sequencing).While the metagenomic approach has important applications in investigating AMR genes, it is noteworthy that metagenomic methods do have limitations and results may be affected by incomplete resistome databases. Overall, results illustrate that cattle manure inputs may influence AMR abundance in soils and conservation management may minimize AMR gene presence in the environment.</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Sequence and properties of the Q-PCR primers used in this project.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Figure 3. The relative proportion of AMR resistance gene classes in soils from different</ns0:cell></ns0:row><ns0:row><ns0:cell>pasture management systems. Six soil genomic DNA extracts were sequenced by using</ns0:cell></ns0:row><ns0:row><ns0:cell>shotgun metagenomic sequencing to evaluate the impact of pasture management on</ns0:cell></ns0:row><ns0:row><ns0:cell>antibiotic resistant genes. Each AMR gene classes was normalized to 100% for identifying the</ns0:cell></ns0:row><ns0:row><ns0:cell>percentage of resistance genes from each treatment (CG, H, RBR, and RBS) in each class of</ns0:cell></ns0:row><ns0:row><ns0:cell>resistance gene. Pasture management includes continuously grazed (CG), hayed (H), and</ns0:cell></ns0:row><ns0:row><ns0:cell>rotational grazed with a fenced riparian buffer (RBR). The RBR treatment consists of an</ns0:cell></ns0:row><ns0:row><ns0:cell>additional fenced riparian buffer strip (RBS) that was a non-grazed zone without direct</ns0:cell></ns0:row><ns0:row><ns0:cell>addition of poultry litter or grazing that had trees. Grey=CG, Yellow=H, Blue=RBR, and</ns0:cell></ns0:row><ns0:row><ns0:cell>Orange=RBS.</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>ANOVA results illustrating the differences of the abundance of three AMR associated genes were impacted by the single factor, animals (cattle manure vs. poultry litter), and year(2018 vs. 2019), and interaction between these two factors in cattle manure and poultry litter samples collected from 2018-2019.</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='2'>Parameter Factor</ns0:cell><ns0:cell>Quantity per gram</ns0:cell><ns0:cell cols='2'>F-value P-value</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>(log gene copies/gram</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>dry weight manure) &#61617; SD</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>ermB</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.66&#61617;0.39 6.298</ns0:cell><ns0:cell>0.023*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 2.45&#61617;0.99</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 2.77&#61617;0.64</ns0:cell><ns0:cell>8.433</ns0:cell><ns0:cell>0.010*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 5.08&#61617;0.47</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>0.141</ns0:cell><ns0:cell>0.711</ns0:cell></ns0:row><ns0:row><ns0:cell>sulI</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.60&#61617;0.17 6.815</ns0:cell><ns0:cell>0.0189*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 2.40&#61617;1.18</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 3.07&#61617;0.79</ns0:cell><ns0:cell>3.452</ns0:cell><ns0:cell>0.082</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 4.66&#61617;0.34</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>3.893</ns0:cell><ns0:cell>0.062</ns0:cell></ns0:row><ns0:row><ns0:cell>intI</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.93&#61617;0.52 29.524</ns0:cell><ns0:cell>0.001*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 0.50&#61617;0.50</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 2.87&#61617;0.94</ns0:cell><ns0:cell>0.865</ns0:cell><ns0:cell>0.366</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 4.04&#61617;0.85</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>0.461</ns0:cell><ns0:cell>0.505</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 5 (on next page)</ns0:head><ns0:label>5</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Resistance genes in three features (gene level, mechanism level, and class level).The number of genes, mechanism and class is the total number of unique AMR gene found without duplication. The gene hits are used as a count of how many times a given gene is found in the data. n= 6 soil samples [one replication of CG and H, with two replications for RBR and the RBS at a consistent landscape position landscape position, and sampling timing (i.e., zone 3 and post poultry litter applications)].</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Resistance genes in three features (gene level, mechanism level, and class level). The number of genes, mechanism and class is the total number of unique AMR gene found without duplication. The gene hits are used as a count of how many times a given gene is found in the data. n= 6 soil samples [one replication of CG and H, with two replications for RBR and the RBS at a consistent landscape position landscape position, and sampling timing (i.e., zone 3 and post poultry litter applications)].</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>CG</ns0:cell><ns0:cell>H</ns0:cell><ns0:cell>RBR</ns0:cell><ns0:cell>RBS</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Number</ns0:cell><ns0:cell>210</ns0:cell><ns0:cell>105</ns0:cell><ns0:cell>208</ns0:cell><ns0:cell>143</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Mechanism Number</ns0:cell><ns0:cell>55</ns0:cell><ns0:cell>42</ns0:cell><ns0:cell>53</ns0:cell><ns0:cell>40</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Class Number</ns0:cell><ns0:cell>18</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>17</ns0:cell></ns0:row><ns0:row><ns0:cell>Hits</ns0:cell><ns0:cell>308</ns0:cell><ns0:cell>139</ns0:cell><ns0:cell>312</ns0:cell><ns0:cell>192</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48736:3:0:NEW 17 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Reviewer 1 Basic reporting Figure 2 looks much clearer, and I believe readers will greatly appreciate the more details added throughout the manuscript. Response: thank you for this comment and revisions provided, it greatly improved the paper. Table 2: If possible, the format at the end of the table might need to be fixed. Line 17 is separated. Response: Thank you for this comment. I request guidance from the online submission system, as the table that was uploaded was 1 page. Figure 2: Lines 432-436, double check the legend reflects the changes. “star” should be changed to “connecting letters” Response: This was corrected, thank you. Overall, double check the formatting and ordering of the figures and tables and their legends at the end of the pdf Response: Ordering is correct. Experimental design Line 204: It would be helpful to provide the URL to the Resistome Analyzer tool Response: The link is: https://github.com/cdeanj/resistomeanalyzer was added. Validity of the findings No further comments Reviewer 2 Basic reporting No comment Experimental design No comment Validity of the findings No comment Comments for the Author I think the authors made nice improvements to the paper and this will be a nice contribution to the field. Response: Thank you for the review and comments provided during the peer-review process. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>environment is a concern, yet practices that mitigate AMR are poorly understood, especially in grasslands. Animal manures are widely deposited on grasslands, which are the largest agricultural land-use in the United States. These nutrient-rich manures may contain AMR genes. The aim of this study was to enumerate AMR genes in grassland soils following 14-years of poultry litter and cattle manure deposition and evaluate if best management practices [rotationally grazed with a riparian (RBR) area and a fenced riparian buffer strip (RBS), which excluded cattle grazing and poultry litter applications] relative to standard pasture management [continuously grazed (CG) and hayed (H)] systems minimize the presence and amount of AMR genes. Quantitative PCR (Q-PCR) was performed to enumerate four AMR genes (ermB, sulI, intlI, and bla ctx-m-32 ) in soil, cattle manure, and poultry litter environments. Six soil samples were additionally subjected to metagenomic sequencing and resistance genes were identified from assembled sequences. Following 14-years of continuous management, ermB, sulI, and intlI genes in soil were highest (P&lt;0.05) in samples collected long-term continuous grazing (relative to conservation best management practices), suggesting overgrazing and continuous cattle manure deposition may increase AMR gene presence. In general, AMR gene prevalence increased downslope, suggesting potential lateral movement and accumulation based on landscape position. Poultry litter had lower abundance of AMR genes (ermB, sulI, and intlI) relative to cattle manure. Long-term applications of poultry litter increased the abundance of sulI and intlI genes in soil (P&lt;0.05). Similarly, metagenomic shotgun sequencing</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Veterinary pharmaceutical usage is a fundamental component of conventional poultry and bovine production for treating microbial infections and increasing weight gains <ns0:ref type='bibr' target='#b7'>(Collignon et al., 2009)</ns0:ref>. Repeated use of antibiotics during food-animal production may provide selection pressure for the evolutionary phenomenon known as antimicrobial resistance (AMR). Genes encoding resistance to antimicrobials and antibiotics, which can also naturally be found in many bacteria, can be transferred between organisms via horizontal gene transfer <ns0:ref type='bibr' target='#b19'>(Juhas, 2015)</ns0:ref>. Agricultural practices influence the prevalence and occurrence of AMR genes in soils. For example, soils amended with cattle manure not treated with antibiotics contained higher abundance of &#946;-lactam resistant bacteria than soils with inorganic fertilizer inputs <ns0:ref type='bibr'>(Udikovic-Kolica et al., 2014)</ns0:ref>. In another study, soil applications of swine manure increased erythromycin resistance gene abundance and remained high for a decade post-application <ns0:ref type='bibr' target='#b38'>(Scott et al., 2018)</ns0:ref>. However, AMR genes occur naturally <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>; for example, <ns0:ref type='bibr' target='#b5'>Cadena et al. (2018)</ns0:ref> identified tetracycline and sulfonamide resistant genes in organic farms without routine antibiotic usage.</ns0:p><ns0:p>There is recent interest in monitoring the dissemination of AMR genes into the environment, particularly those directly relevant to human and animal health, as consumers and producers are increasingly concerned about antibiotic resistance in food systems <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>. One goal of sustainable agriculture is to close nutrient cycles by applying animal manures to neighboring cropping systems. Additionally, depending on antibiotic properties, large quantities of undegraded antibiotics exit animals to manures, including poultry litter (a combination of Manuscript to be reviewed bedding material and excreta); for example, up to 90% of sulfonamides and 25-75% of tetracyclines may be excreted into manure as the parent compound <ns0:ref type='bibr' target='#b24'>(Kulshrestha et al., 2004;</ns0:ref><ns0:ref type='bibr' target='#b43'>Thiele-Bruhn et al., 2004)</ns0:ref>. From manure, antibiotics, genes encoding AMR, and microbes may be transferred to soil <ns0:ref type='bibr' target='#b8'>(Cook et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b17'>Heuer et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b51'>Zhang et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b16'>He et al., 2014)</ns0:ref>.</ns0:p><ns0:p>Therefore, cattle manure and poultry litter applications, which are valuable sources of nutrients such as N, P, and potassium (K), may also be a pathway for AMR bacteria and genes into the environment <ns0:ref type='bibr' target='#b49'>(Yang et al., 2019a)</ns0:ref>.</ns0:p><ns0:p>The ability of pasture management practices (i.e., filter strips and rotational grazing) to reduce AMR gene presence, prevalence, and movement to soils is largely unknown. Our previous work indicated that continuously grazed systems increased soil microbial community richness and diversity owing to greater organic animal inputs <ns0:ref type='bibr' target='#b50'>(Yang et al., 2019b)</ns0:ref>, which suggests manure increases microbiome diversity and improves soil health. However, animal manure may also be a source for AMR genes. Therefore, the current work aims to understand the impacts of pasture management on AMR bacteria and gene presence. This study focused on quantifying four AMR associated genes [i.e., erythromycin resistance gene (ermB), sulfonamide resistance gene (sulI), integrase gene (intlI), and &#946;-lactam resistance gene (bla ctx-m-32 )] present in pasture soil, cattle manure, and poultry broiler litter using Q-PCR in an effort to balance human, animal, and environmental priorities. These four genes are useful for understanding the ecology and biology of agricultural AMR genes in soil and manure systems <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>. We additionally applied metagenomic sequencing to reveal the suite of resistance genes in the soil community and to evaluate best management practices that may reduce the presence of AMR genes from manure and poultry litter applications to the soil.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Experimental Design</ns0:head><ns0:p>In 2004, a field study was initiated by <ns0:ref type='bibr' target='#b32'>Pilon et al. (2017a;</ns0:ref><ns0:ref type='bibr' target='#b33'>2017b;</ns0:ref><ns0:ref type='bibr'>2018)</ns0:ref> at the USDA-ARS Unit in Booneville, Arkansas to evaluate how pasture management affects water quality. Nine watersheds (average slope of 8%) were constructed on Enders and Leadvale silt loams. Each watershed had a total area of 0.14 ha, with the dominant grass species being bermudagrass (Cynodon dactylon L.). Briefly, three grazing strategies were implemented from 2004-2017 with three replications, including: continuously grazed (CG), hayed (H), and rotationally grazed with an ungrazed, fenced riparian strip (RBR; <ns0:ref type='bibr'>Yang et al., 2019)</ns0:ref> (Fig. <ns0:ref type='figure' target='#fig_8'>1</ns0:ref>). The CG treatment was consistently grazed by one to two calves during the year <ns0:ref type='bibr' target='#b32'>(Pilon et al., 2017a)</ns0:ref>. The H treatment was hayed three times annually (April, June, and October) to a height of 10 cm (no cattle in these watersheds). The RBR system is considered a best management strategy and was rotationally grazed based on forage height <ns0:ref type='bibr' target='#b32'>(Pilon et al., 2017a;</ns0:ref><ns0:ref type='bibr' target='#b33'>2017b;</ns0:ref><ns0:ref type='bibr'>2018)</ns0:ref>. Calves (three) were placed in rotationally grazed watersheds based on forage height (when heights were 20 to 25 cm) and removed (10 to 15 cm) <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Each watershed was divided into 3 zones (perpendicular to slope) given that topography widely affects the microbial biogeography <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Landscape positions corresponded to upper slope (zone 1), mid-slope (2), and downslope positions (3), whereas the RBR represented zone 4 <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. The riparian buffer strip (RBS) and served as the nested control. The length of the 3 zones in CG and H was 57 m and the length of the 3 zones in RBR was 42.75 m. Broiler litter was surface applied at 5.6</ns0:p><ns0:p>Mg dry matter per ha in April-May of each year per watershed (excluding the RBS). All poultry litter rates were equivalent on an aerial basis <ns0:ref type='bibr'>(Yang et al., 2019)</ns0:ref>. Broiler litter was obtained Isolation Kit (MoBio Laboratories Inc., Cat. 12888-100) according to the manufacturer's protocol. Extracted DNA were quantified using Quant-iT&#8482; PicoGreen&#8482; dsDNA Assay Kit (ThermoFisher Scientific, Cat. P7589) and used directly in quantitative Q-PCR. All 120, 6, and 12 soil, cattle manure, and poultry litter DNA samples, respectively, were subjected to Q-PCR for detection of four genes associated with AMR as described in the clinical isolates, which included ermB <ns0:ref type='bibr' target='#b12'>(Florez et al., 2014)</ns0:ref>, sulI <ns0:ref type='bibr' target='#b2'>(Barraud et al., 2010)</ns0:ref>, intlI <ns0:ref type='bibr' target='#b30'>(Pei et al., 2006)</ns0:ref>, and bla ctxm-32 <ns0:ref type='bibr' target='#b40'>(Szczepanowski et al., 2009)</ns0:ref>, using previously published primers (Table <ns0:ref type='table' target='#tab_5'>1</ns0:ref> Manuscript to be reviewed numbers were then determined using standard curves. Gene copy abundances were then normalized per gram dry weight of soil, cattle manure, and poultry litter after measuring the moisture content of each sample. Finally, the gene copy numbers per gram dry weight were transformed into log10 values for further statistical analysis as they were not normally distributed <ns0:ref type='bibr' target='#b14'>(Ganger et al., 2017)</ns0:ref>.</ns0:p><ns0:p>To detect significant differences for fixed effects (pasture management, sample collection timing, and zone) an analysis of variance (ANOVA) was conducted on log transformed data using JMP software [JMP&#174;12 <ns0:ref type='bibr'>(SAS Institute, 2007)</ns0:ref>] with replicate as a random effect.</ns0:p><ns0:p>Probability values less than 0.05 were considered significant and pairwise posthoc comparisons were made using Tukey's Honestly Significant Difference test. Samples below detection limit were excluded in the analysis.</ns0:p></ns0:div> <ns0:div><ns0:head>Metagenomic sequencing and data analysis</ns0:head><ns0:p>To evaluate long-term effects of pasture management on AMR genes, metagenomic sequencing was applied for 6 soil samples [post-application zone 3, CG; post-application zone 3 H; post-application zone 3 RBR, post-application zone 3, RBS all replication 1; and, postapplication zone 3 RBR, post-application zone 3, RBS replication 2) ]. Sequencing libraries were prepared according to the Illumina Miseq sample preparation guide. Metagenomic sequencing was performed using Miseq Reagent Kits v2 with paired-end 2 x 250 bp reads on the MiSeq platform (University of Tennessee Genomics Core; Knoxville, TN). Raw data were uploaded to NCBI with the accession number of SAMN 14783573-14783584. Read trimming and assembly were performed according to <ns0:ref type='bibr' target='#b44'>Tyson (2015)</ns0:ref>. Genomes were annotated using the AmrPlusPlus pipeline <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. All samples resulted in a total of 5.19 Gb of sequence data.</ns0:p><ns0:p>Trimmomatic was used for removal of low-quality bases and sequences <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Reads classified as host genome (Bos taurus and Gallus gallus) were removed from further analysis. The adapter contamination and low-quality reads were also removed. The database 'MEGARes' has been integrated inside the pipeline and used for identification of AMR genes.</ns0:p><ns0:p>AMR genes with a gene fraction (i.e. proportion of nucleotides that aligned with at least one query read) of &gt;85% coverage across all alignments were considered to be positively identified in a sample <ns0:ref type='bibr' target='#b27'>(Noyes et al., 2016a)</ns0:ref>. The minimum length of a read was 150 and the mean Phred score was above 30. The AMR gene analysis was carried out using the Resistome Analyzer tool (https://github.com/cdeanj/resistomeanalyzer) <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. Utilizing this tool, three annotation levels were produced, which include gene-level (sequencing-level), mechanism-level, and class-level counts.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Distribution of four AMR associated genes in soil based on pasture management, landscape position, and sampling time</ns0:head><ns0:p>Soil ermB gene abundance varied among treatments (CG, H, RBR, and RBS) and zones (1, 2, 3, and 4) (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_12'>2A</ns0:ref>), although, sample collection time (pre-or post-poultry litter applications; P&gt;0.05) had no impact on the abundance of ermB gene (Table <ns0:ref type='table'>2</ns0:ref>; Fig. <ns0:ref type='figure' target='#fig_12'>2B</ns0:ref>). There was an interaction effect from pasture management and zone on the abundance of ermB genes.</ns0:p><ns0:p>Across pasture management, the highest abundance of ermB gene was found in the CG treatment (&#181; log gene copies per gram dry weight soil =3. Manuscript to be reviewed ermB by 1.99 log. Among zones, the greatest abundance of ermB occurred in zone 3 (&#181; log gene copy numbers per dry weight=2.92), followed by zone 2 (2.91 gene copy numbers per dry weight), zone 1 (2.78 gene copy numbers per dry weight), and zone 4 (0.73 gene copy numbers per dry weight) (Fig. <ns0:ref type='figure' target='#fig_12'>2C</ns0:ref>). Compared with zone 4, zone 3 increased the abundance of ermB by 2.19 log, zone 2 increased the abundance of ermB by 2.18 log, zone 1 increased the abundance of ermB by 2.05 log. However, no abundance differences occurred between pre and post poultry litter applications (&#181; log gene copy numbers per gram dry weight in pre-sampling time = 2.86 vs.</ns0:p><ns0:p>post-sampling time=2.45) (Fig. <ns0:ref type='figure' target='#fig_12'>2B</ns0:ref>). There were differences in the abundance of the gene sulI among all three factors, including treatments, sampling time, and zone (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_9'>2</ns0:ref>). For pasture management, the highest abundance was found under CG (&#181; log gene copy numbers per dry weight=4.83), followed by RB (4.46), H (4.42), and RBS (2.93) (Fig. <ns0:ref type='figure' target='#fig_12'>2A</ns0:ref>). Among zones, the greatest abundance was found in zone 2 (&#181; log gene copy numbers per gram dry weight =4.66), followed by zone 1 (4.66), zone 3 (4.38), and zone 4 (2.93) (Fig. <ns0:ref type='figure' target='#fig_12'>2C</ns0:ref>). Differences in abundance were identified between pre and post poultry litter sampling time, with a higher abundance of sulI occurring post poultry litter applications (Fig. <ns0:ref type='figure' target='#fig_12'>2B</ns0:ref>; log gene copy numbers per gram dry weight=4.77 vs. pre-sampling= 4.03). There was also an interaction for pasture management by zone for the sulI gene. Similar to sulI, there were differences in the intlI gene based on all three factors (P&lt;0.05) (Fig. <ns0:ref type='figure' target='#fig_9'>2</ns0:ref>). Based on the influence from pasture management, ANOVA tests indicated that greatest abundances were found under long-term CG (&#181; log gene copy numbers per gram dry weight=3.41), followed by H (3.11), and RB (3.07). The least abundance of AMR genes were found in RBS (1.54) (Fig. <ns0:ref type='figure' target='#fig_12'>2A</ns0:ref>), with greatest intlI gene occurring in zone 2 (&#181; log gene copy numbers per gram dry weight =3.22), then zone 1 (3.19), zone 3 (3.18), and zone 4 (1.54) (Fig. Manuscript to be reviewed 2C). The abundance of the intlI gene differed between pre and post sampling, with higher abundances in soil samples collected after poultry litter application (&#181; log gene copy numbers per dry weight in post-sampling time=3.79 vs. pre-sampling =2.28) (Fig. <ns0:ref type='figure' target='#fig_12'>2B</ns0:ref>). There was pasture management by zone, pasture management by timing, and zone by timing interactions for the abundance of the intlI gene. After finding differences following long-term pasture management on the abundance of these three AMR associated genes, further analyses were conducted to illustrate the abundance of each AMR associated gene based on the pasture management treatments. Among these 93 samples, ermB was found in 77% of samples, while only one amplification was from the RBS (8% of RBS was amplified), and 92 samples were from all treatment groups (85% of treatment samples were amplified). Among these 92 positive samples from treatment groups, it included 78% of RBR samples, 92% of CG, 86% of H, and 8% of RBS. Gene sulI was detected in 119 out of 120 samples (99%) and intlI were detected in all samples (100%), while bla ctx-m-32 was not found in any soils except two (following poultry litter application in zone 2 of CG in 2016 and one in zone 3 of the H treatment in 2017). The gene bla ctx-m-32 was not included in the Table <ns0:ref type='table'>2</ns0:ref> and Fig. <ns0:ref type='figure' target='#fig_9'>2</ns0:ref>, due to no amplification. Abundance of these three AMR associated genes indicates there are greater abundances of each AMR associated genes found in CG, RBR and H, relative to RBS (P&lt;0.05; Fig. <ns0:ref type='figure' target='#fig_12'>2A</ns0:ref>). For the RBS (no grazing or direct manure or poultry litter deposition), there was no amplification of ermB gene from all samples during 2016, while only one sample included an ermB gene in 2017.</ns0:p><ns0:p>Overall, post poultry litter applications, soil samples had greater abundance of sulI and intlI genes than pre-application soils. In Fig. <ns0:ref type='figure' target='#fig_12'>2C</ns0:ref>, the abundance of these three AMR associated genes were split out based on zones. Based on the factor of zone, differences were observed in these three AMR associated genes, ermB, sulI, and intlI (P&lt;0.05). Among these four zones, the lowest abundance was found in zone 4 (no cattle manure or poultry litter) among these three genes.</ns0:p><ns0:p>Distribution of four AMR associated genes in cattle manure and poultry litter Considering continuous annual applications of cattle and poultry manure were applied to soils (over 14-years), authors were interested in the presence of the four AMR associated genes and whether the abundance varied between soils with manure applied from the two sources.</ns0:p><ns0:p>Results from Q-PCR indicated these three AMR associated genes (ermB, sulI and intlI) were found in all poultry litter samples collected in 2019; however, the abundance of AMR-associated genes from poultry litter in the year of 2018 were below the detection threshold. The gene of bla ctx-m-32 was not found in any poultry litter and cattle manure samples (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>). Based on the ANOVA, there were differences in these three AMR associated genes between cattle manure and poultry litter, with greater abundances occurring in cattle manure than poultry litter (53, 95, and 100% greater mean value of gene copies per gram dry weight for ermB, sulI, and intlI in cattle manure than poultry litter, respectively) (P&lt;0.05) (Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref>). The impact of sampling year on the abundance of ermB gene was found (P&lt;0.05), with greater abundance in 2019 compared to 2018.</ns0:p></ns0:div> <ns0:div><ns0:head>Prevalence of antimicrobial resistance genes based on pasture management</ns0:head><ns0:p>Purified genomic DNA extracts from six soil samples were chosen for shotgun metagenomic sequencing to evaluate the impact of pasture management on AMR genes. Several unique AMR genes per treatment were identified ( Manuscript to be reviewed can be found in the output file (Supplementary Table <ns0:ref type='table' target='#tab_5'>1</ns0:ref>). These identified resistance genes were listed from the greatest numbers of hits (multi-drug resistance class) to least (Bacitracin). Based on the database of MEGARes 2.0, the multi-drug resistance was defined as genes and mechanisms that cause resistance to two or more different antibiotic classes. Typically, such mechanisms involve active extrusion of antibiotic molecules from the bacterial cell or mechanisms that prevent the drug from reaching its target <ns0:ref type='bibr' target='#b25'>(Lakin et al., 2017)</ns0:ref>. The class of multi-drug resistance genes were identified as greater than other resistance gene classes among all treatments and RBS (Supplementary Table <ns0:ref type='table' target='#tab_5'>1</ns0:ref>). Fig. <ns0:ref type='figure' target='#fig_10'>3</ns0:ref> shows relative proportion of hits in each class level by treatments. Overall, the greatest (i.e., 33%) of identified genes from the multi-drug resistance class were found in the CG treatment, followed by RBR watersheds (28%), the RBS (24%), and H watersheds (15%).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Distribution of four AMR associated genes in soils based on pasture management, landscape position, and sampling time AMR is a naturally occurring phenomenon, and soils are considered a reservoir for AMR genes <ns0:ref type='bibr' target='#b21'>(Kieser et al., 2000)</ns0:ref>. Overall, pasture management (CG, H, RBR, and RBS) had an effect on three AMR-associated genes, ermB, sulI, and intlI (P&lt;0.05). Greater abundance of these three AMR associated gene in soils were detected in treatments receiving either long-term poultry litter or cattle manure inputs (CG, H, and RBR), while lower AMR gene abundances were found in RBS, which was not grazed and did not receive direct poultry litter applications. This indicates these three AMR-associated genes were potentially transmitted via animal feces and may be transferred into the soil through animal movement and land application. This finding was Manuscript to be reviewed consistent with other studies which found that the repeated application of animal manure increased antibiotic resistance genes in agricultural soils <ns0:ref type='bibr' target='#b26'>(Luby et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b22'>Kim et al., 2017)</ns0:ref>.</ns0:p><ns0:p>The sample collection timing (pre or post poultry litter application) had an effect on two AMR-associated genes, sulI and intlI (P&lt;0.05). A greater abundance of these two genes in soils were detected in samples collected after poultry litter applications (July) rather than before poultry litter applications (April). The abundance of sulI and intlI genes increased after poultry litter applications, indicating poultry litter may include sulI and intlI genes and increase the abundance of sulI and intlI genes in soils. This result is consistent with previous work using 16S rRNA sequencing, which found that poultry litter timing greatly influenced soil community structure and gene abundance <ns0:ref type='bibr'>(Yang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b0'>Ashworth et al., 2017)</ns0:ref>. However, poultry litter application timing did not influence the other two genes, ermB and bla ctx-m-32 . Another study pointed out that the concentration of AMR genes [sulI, intlI, tetracycline (tetW), and streptomycin (strpB)] in soil following poultry litter fertilization were greater following 21 to 133 days after application <ns0:ref type='bibr' target='#b8'>(Cook et al., 2014)</ns0:ref>. These data suggest poultry litter applications may increase the abundance and persistence of AMR-associated genes within the soil. The factor of zone had an effect on the abundance of these three AMR-associated genes (ermB, sulI, and intlI) within the soil (P&lt;0.05), with higher abundance in zone 1, zone 2, and zone 3, and lowest abundance in zone 4. This result suggests that animal manure played an important role in enhancing the abundance of AMR associated genes into the soil. We also found that genes of sulI and intlI existed in the soil of zone 4, even though there was no input from animal manure in this region, thus indicating that these two AMR-associated genes may be inherent to the soil. Since some AMR genes were found in non-agricultural and un-grazed native soils, they were considered as a natural part of pristine habitats <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012 and</ns0:ref><ns0:ref type='bibr'>2016)</ns0:ref>. Manuscript to be reviewed</ns0:p><ns0:p>This result showcases the importance of evaluating baseline and background levels of AMR genes when investigating the impact of human input in the occurrence of AMR bacteria and genes <ns0:ref type='bibr' target='#b10'>(Durso et al., 2012)</ns0:ref>.</ns0:p><ns0:p>The gene bla ctx-m-32 was not detected in most soil samples, indicating that bla ctx-m-32 was not prevalent in the locations sampled. Having information on AMR presence in soils is valuable, as previous observations have shown antibiotics may impact the soil microbial community composition and structure, which will ultimately influence ecosystem-scale processes by maintaining these AMR bacteria and genes <ns0:ref type='bibr' target='#b15'>(Gutierrez et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b42'>Toth et al., 2011)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Distribution of four AMR associated genes in cattle manure and poultry litter</ns0:head><ns0:p>Three AMR associated genes (ermB, sulI, and intlI) were more abundant in cattle manure compared to poultry litter. Although, previous studies derived the opposite conclusion. <ns0:ref type='bibr' target='#b47'>Wang et al. (2016)</ns0:ref> indicated that the ermB gene levels in poultry litter were greater than that of cattle manure. Cattle antibiotics and drugs were used over the course of this experiment (Supplementary Table <ns0:ref type='table'>2</ns0:ref>); though, without the information of antibiotics used during poultry production, it is difficult to ascertain that AMR associated genes were related to specific animal management practices. Regardless of where these AMR associated genes originate, we should pay attention to the abundance and movement of these resistance genes, such as ermB, because macrolides are a major broad-spectrum antibiotic for human use and play an important role in controlling Gram-positive bacterium infection clinically <ns0:ref type='bibr' target='#b20'>(Kanoh and Rubin, 2010)</ns0:ref>. We also Manuscript to be reviewed abundance in 2018. However, it is difficult to ascertain whether this difference was caused by animal inputs without the drug usage information on cattle and poultry in these two years.</ns0:p><ns0:p>Prevalence of antimicrobial resistance genes from shotgun sequencing following pasture management Quantifying the prevalence of specific AMR genes may use culture-independent methods, such as Q-PCR, as well as metagenomic sequencing <ns0:ref type='bibr' target='#b1'>(Agga et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b10'>Durso et al., 2012)</ns0:ref>.</ns0:p><ns0:p>Metagenomic sequencing allows for the tracking of AMR genes and identification of transmission of AMR from animals to the environment <ns0:ref type='bibr' target='#b29'>(Oniciuc et al., 2018)</ns0:ref>. Recent studies using functional metagenomic screening of cattle feces reported the maximum number of AMR genes detected per animal was 26 <ns0:ref type='bibr' target='#b48'>(Wichmann et al., 2014)</ns0:ref>, which was much lower than the number identified from soil samples in this experiment. The identified AMR genes have broad biological activities and might have other functions, rather than only AMR gene encoding. Take the efflux pumps as an example, as it is usually one of the largest AMR mechanisms; however, clinical and laboratory studies suggest efflux pumps have a role in virulence and the adaptive responses as well <ns0:ref type='bibr' target='#b9'>(Du et al., 2018)</ns0:ref>. The multi-drug resistance gene classes were conferred to phenicol, lincosamide, oxazolidinones (linezolid), pleuromutilin, and streptogramin <ns0:ref type='bibr' target='#b27'>(Noyes et al., 2016a)</ns0:ref>. However, in the RBS (down slope, but no direct animal input from cattle manure and poultry litter), multidrug resistance genes were identified. Therefore, it is possible some AMR genes were not from anthropogenic sources, but rather a naturally occurring community component <ns0:ref type='bibr' target='#b3'>(Bhullar et al., 2012)</ns0:ref>, or that surface runoff moved AMR genes downslope. Similarly, Rothrock et al. Manuscript to be reviewed genes via surface water runoff <ns0:ref type='bibr' target='#b18'>(Jacobs et al., 2019)</ns0:ref>. <ns0:ref type='bibr' target='#b11'>Durso et al. (2016)</ns0:ref> also characterized native Nebraska prairie soils that had not been affected by human or food-animal waste products and found that all prairies contained tetracycline and cefotaxime-resistant bacteria, and 48% of soil bacteria were resistant to two or more antibiotics. <ns0:ref type='bibr' target='#b3'>Bhullar et al. (2012)</ns0:ref> also reported that AMR bacteria and genes can be found from in pristine soil environments that have not been exposed to human antibiotic use, from which, some strains were resistant to a wide range of different commercially available antibiotics. <ns0:ref type='bibr' target='#b5'>Cadena et al. (2018)</ns0:ref> also reported that tetracycline and sulfonamide antibiotic resistance genes can be identified from organic farming operations.</ns0:p><ns0:p>Based on the MEGARes database, the macrolides, lincosamides, and streptogramins (MLS)</ns0:p><ns0:p>A and B were classified as MLS drugs <ns0:ref type='bibr'>(Lakin et al., 2016)</ns0:ref>, and were identified in soil samples in the present experiment. The MLS class, according to <ns0:ref type='bibr' target='#b41'>Tenson et al. (2003)</ns0:ref>, 'contains structurally different but functionally similar drugs acting by binding to the 50S ribosomal subunit and blocking the path where nascent peptides exit the ribosome.' <ns0:ref type='bibr' target='#b28'>Noyes et al. (2016b)</ns0:ref> reported that MLS resistance genes can be detected in both cattle and calves and were equally abundant between dairy and beef herds. Overall, the resistance classes of metronidazole and thiostrepton were identified only from the RBR group, and bacitracin resistance genes were detected only in the CG treatment. Due to the limitation of the sample number for metagenomic sequencing, further studies are necessary to estimate the influence of animal inputs on AMR genes.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>Results characterized the abundance of AMR genes following 14-years of pasture management using Q-PCR and metagenomics sequencing. The quantitative amplification method suggests increased abundances in three AMR-associated genes (ermB, sulI, and intlI) in Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure Captions</ns0:note><ns0:note type='other'>Figure 1</ns0:note><ns0:p>Schematic representation of the experimental set-up. </ns0:p><ns0:note type='other'>Figure 3</ns0:note><ns0:p>Relative proportion of AMR genes in grassland soils based on pasture managment. Manuscript to be reviewed Resistance genes in three features Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>03), followed by H (2.86 gene copies per gram dry weight soil), RBR (2.72 gene copies per gram dry weight soil) and RBS (0.73 gene copies per gram dry weight soil) (Fig. 2A). Compared with RBS, CG increased the abundance of ermB by 2.3 log, H increased the abundance of ermB by 2.13 log, and RB increased the abundance of PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>detected three AMR associated genes (ermB, sulI, and intlI) in poultry litter in 2019, but not in 2018. These differing results between years indicates gene presence varied annually perhaps due to differences in environmental or animal management factors. There was a difference identified from the ermB gene between 2018 and 2019 with a greater abundance in 2019 and less PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>(2016) indicated antibiotic resistant Listeria and Salmonella spp. occur in all-natural, antibiotic-free, pasture-raised broiler flocks. Future work is needed evaluating the potential movement of AMR PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Diagram of the experimental set-up (nine watersheds total, consistently managed from</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Mean abundances of three AMR associated genes, ermB, sulI and intlI amplified from</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. The relative proportion of AMR resistance gene classes in soils from different pasture</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Schematic representation of the experimental set-up. Randomized complete block design with three replications (nine watersheds total) from 2004-2018. All areas have received annual poultry litter applications (except for the RBS area). The RBS received neither poultry litter nor cattle manure inputs. CG and RBR received cattle manure. Each watershed was divided, perpendicular to the slope into three zones [corresponding to shoulder (A), upper backslope (B), and lower backslope (C) positions], whereas the RBR consisted of these three zones plus the RBS (zone 4). [Soil samples, n = 120; cattle manure, n = 12; poultry litter, n = 6; and, shotgun sequencing, soil, n=6].</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='27,42.52,70.87,525.00,393.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='31,42.52,70.87,525.00,455.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head /><ns0:label /><ns0:figDesc>Table4). The number of unique AMR genes, mechanisms, and classes identified in H was lower than other treatments, including the RBS.Resistome Analyzer in AmrPlusPlus pipeline provided four levels of annotation database</ns0:figDesc><ns0:table /><ns0:note>hierarchy, at levels of gene, group, mechanism, and class. In each level, the counts of each genePeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head /><ns0:label /><ns0:figDesc>soils may be due to long-term cattle manure deposition and poultry litter applications to a lesser extent. Using shotgun metagenomic sequencing, we identified the relative abundance of AMR genes were greater in CG than H, indicating that cattle manure deposition may serve as an AMR source to the environment (relative to poultry litter applications). Additionally, conservation pasture management practices such as rotationally grazing and filter strips decreased soil AMR gene presence, as the unfertilized fenced riparian buffer strip displayed 31.58% lower gene abundance (relative to the CG treatment, based on the AMR gene numbers identified through metagenomic sequencing).While the metagenomic approach has important applications in investigating AMR genes, it is noteworthy that metagenomic methods do have limitations and results may be affected by incomplete resistome databases. Overall, results illustrate that cattle manure inputs may influence AMR abundance in soils and conservation management may minimize AMR gene presence in the environment.</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>ANOVA results illustrating the abundance of three AMR associated genes in cattle manure and poultry litter.</ns0:figDesc><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>ANOVA results illustrating the differences of the abundance of three AMR associated genes were impacted by the single factor, animals (cattle manure vs. poultry litter), and year(2018 vs. 2019), and interaction between these two factors in cattle manure and poultry litter samples collected from 2018-2019.</ns0:figDesc><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Sequence and properties of the Q-PCR primers used in this project.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Figure 3. The relative proportion of AMR resistance gene classes in soils from different</ns0:cell></ns0:row><ns0:row><ns0:cell>pasture management systems. Six soil genomic DNA extracts were sequenced by using</ns0:cell></ns0:row><ns0:row><ns0:cell>shotgun metagenomic sequencing to evaluate the impact of pasture management on</ns0:cell></ns0:row><ns0:row><ns0:cell>antibiotic resistant genes. Each AMR gene classes was normalized to 100% for identifying the</ns0:cell></ns0:row><ns0:row><ns0:cell>percentage of resistance genes from each treatment (CG, H, RBR, and RBS) in each class of</ns0:cell></ns0:row><ns0:row><ns0:cell>resistance gene. Pasture management includes continuously grazed (CG), hayed (H), and</ns0:cell></ns0:row><ns0:row><ns0:cell>rotational grazed with a fenced riparian buffer (RBR). The RBR treatment consists of an</ns0:cell></ns0:row><ns0:row><ns0:cell>additional fenced riparian buffer strip (RBS) that was a non-grazed zone without direct</ns0:cell></ns0:row><ns0:row><ns0:cell>addition of poultry litter or grazing that had trees. Grey=CG, Yellow=H, Blue=RBR, and</ns0:cell></ns0:row><ns0:row><ns0:cell>Orange=RBS.</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>ANOVA results illustrating the differences of the abundance of three AMR associated genes were impacted by the single factor, animals (cattle manure vs. poultry litter), and year(2018 vs. 2019), and interaction between these two factors in cattle manure and poultry litter samples collected from 2018-2019.</ns0:figDesc><ns0:table><ns0:row><ns0:cell cols='2'>Parameter Factor</ns0:cell><ns0:cell>Quantity per gram</ns0:cell><ns0:cell cols='2'>F-value P-value</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>(log gene copies/gram</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>dry weight manure) &#61617; SD</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell>ermB</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.66&#61617;0.39 6.298</ns0:cell><ns0:cell>0.023*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 2.45&#61617;0.99</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 2.77&#61617;0.64</ns0:cell><ns0:cell>8.433</ns0:cell><ns0:cell>0.010*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 5.08&#61617;0.47</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>0.141</ns0:cell><ns0:cell>0.711</ns0:cell></ns0:row><ns0:row><ns0:cell>sulI</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.60&#61617;0.17 6.815</ns0:cell><ns0:cell>0.0189*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 2.40&#61617;1.18</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 3.07&#61617;0.79</ns0:cell><ns0:cell>3.452</ns0:cell><ns0:cell>0.082</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 4.66&#61617;0.34</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>3.893</ns0:cell><ns0:cell>0.062</ns0:cell></ns0:row><ns0:row><ns0:cell>intI</ns0:cell><ns0:cell cols='3'>Animal (cattle manure vs. poultry litter) Cattle Manure: 4.93&#61617;0.52 29.524</ns0:cell><ns0:cell>0.001*</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Poultry Litter: 0.50&#61617;0.50</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Year (2018 vs. 2019)</ns0:cell><ns0:cell>2018: 2.87&#61617;0.94</ns0:cell><ns0:cell>0.865</ns0:cell><ns0:cell>0.366</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>2019: 4.04&#61617;0.85</ns0:cell><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell>Animal x Year</ns0:cell><ns0:cell /><ns0:cell>0.461</ns0:cell><ns0:cell>0.505</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_7'><ns0:head>Table 4 (on next page)</ns0:head><ns0:label>4</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_8'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Resistance genes in three features (gene level, mechanism level, and class level).The number of genes, mechanism and class is the total number of unique AMR gene found without duplication. The gene hits are used as a count of how many times a given gene is found in the data. n= 6 soil samples [one replication of CG and H, with two replications for RBR and the RBS at a consistent landscape position landscape position, and sampling timing (i.e., zone 3 and post poultry litter applications)].</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_9'><ns0:head>Table 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Resistance genes in three features (gene level, mechanism level, and class level). The number of genes, mechanism and class is the total number of unique AMR gene found without duplication. The gene hits are used as a count of how many times a given gene is found in the data. n= 6 soil samples [one replication of CG and H, with two replications for RBR and the RBS at a consistent landscape position landscape position, and sampling timing (i.e., zone 3 and post poultry litter applications)].</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>CG</ns0:cell><ns0:cell>H</ns0:cell><ns0:cell>RBR</ns0:cell><ns0:cell>RBS</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Number</ns0:cell><ns0:cell>210</ns0:cell><ns0:cell>105</ns0:cell><ns0:cell>208</ns0:cell><ns0:cell>143</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Mechanism Number</ns0:cell><ns0:cell>55</ns0:cell><ns0:cell>42</ns0:cell><ns0:cell>53</ns0:cell><ns0:cell>40</ns0:cell></ns0:row><ns0:row><ns0:cell>AMR Gene Class Number</ns0:cell><ns0:cell>18</ns0:cell><ns0:cell>16</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>17</ns0:cell></ns0:row><ns0:row><ns0:cell>Hits</ns0:cell><ns0:cell>308</ns0:cell><ns0:cell>139</ns0:cell><ns0:cell>312</ns0:cell><ns0:cell>192</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:48736:4:0:CHECK 25 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Editor comments The manuscript appears scientifically sound and is accepted but I have a few suggestions for style and format that should be addressed before we can enter production. Response: Thank you for these suggestions, the manuscript has improved during the four round of reviews. Line 39. I find the phrase “especially in the US’ largest agricultural land-use or grasslands” awkward and the presence of AMR genes in manure is established. I suggest revising to “especially in grasslands. Animal manures are spread widely on grasslands, which are the largest agricultural land-use in the United States. These nutrient-rich manures contain AMR genes. The aim...” Response: Agreed, this change was made and has improved flow. Line 50. Delete “the” in “the highest” and using the word “following” twice is awkward. Revise to “were highest (P < 0.05) in samples collected from continuously grazed plots, which suggests overgrazing increases AMR gene persistence.” Response: “Following” and “the” were erased. Line 75. Replace “However, it should also be noted that AMR genes can be found naturally..” with “However, AMR genes occur naturally..” Response: This was caried out, thank you. Line 499 & 505. Be consistent in journal titles. Either spell them out (Current Opinion in Microbiology) or not (Crit. Rev. Microbiol) and if the title is abbreviated use a consistent format. For example, some references use a period to indicate an abbreviation (Environ. Sci. and Tech.) and some do not (Clin Microbiol Rev). Further, some use the symbol “&” (Environ. Sci. & Tech.) and some do not. Response: Thank you for this comment, titles are now abbreviated and with a period. Also, “&” was only used when in the actual journal title (e.g. Environ. Sci. & Tech.) and therefore cannot be removed. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>A critical lack of personal protective equipment has occurred during the COVID-19 pandemic. Polylactic acid (PLA), a polyester made from renewable natural resources, can be exploited for 3D printing of protective face masks using the Fused Deposition Modelling technique. Since the possible high porosity of this material raised questions regarding its suitability for protection against viruses, we have investigated its microstructure using scanning electron microscopy and aerosol generator and photometer certified as the test system according to the standards EN 143 and EN 149. Moreover, the efficiency of decontaminating PLA surfaces by conventional chemical disinfectants including 96% ethanol, 70% isopropanol, and a commercial disinfectant containing 0.85% sodium hypochlorite has been determined. We confirmed that the structure of PLA protective masks is compact and can be considered a sufficient barrier protection against particles of a size corresponding to microorganisms including viruses. Complete decontamination of PLA surfaces from externally applied Staphylococcus epidermidis, Escherichia coli, Candida albicans and SARS-CoV-2 was achieved using all disinfectants tested, and human adenovirus was completely inactivated by sodium hypochlorite-containing disinfectant.</ns0:p><ns0:p>Natural contamination of PLA masks worn by test persons was decontaminated easily and efficiently by ethanol. No disinfectant caused major changes to the PLA surface properties, and the pore size did not change despite severe mechanical damage of the surface.</ns0:p><ns0:p>Therefore, PLA may be regarded as a suitable material for 3D printing of protective masks during the current or future pandemic crises.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head> <ns0:ref type='bibr'>COVID-19 (coronavirus disease 2019)</ns0:ref> <ns0:p>is the designation of the disease caused by the SARS-CoV-2 infection. The World Health Organization (WHO) declared this epidemic a global pandemic affecting the whole world on March 11, 2020. The infection by SARS-CoV-2 was confirmed for the first time in Wuhan, China, but had a huge impact also in Europe and later in North and South America. Lombardy, Italy was the most severely affected region in Europe. Due to the risk of health care system collapse, the Italian government ordered a nationwide lockdown <ns0:ref type='bibr' target='#b27'>(Spinelli and Pellino 2020)</ns0:ref>. Several studies showed that SARS-CoV-2, similarly to SARS-CoV-1, remains infectious for hours and days in aerosols and on surfaces, respectively <ns0:ref type='bibr' target='#b11'>(Chin et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b13'>Kampf et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b30'>van Doremalen et al. 2020)</ns0:ref>, emphasizing the need for efficient virucidal disinfection. The number of patients suffering from COVID-19 disease and the enormous rate of infection spread caused serious complications in many countries, including a desperate lack of protective equipment <ns0:ref type='bibr' target='#b28'>(Swennen et al. 2020)</ns0:ref>. Sufficient production and distribution of protective equipment has been crucial for sustaining patient care during the pandemic. The current unsatisfactory situation regarding protective equipment in the USA has been described by <ns0:ref type='bibr' target='#b24'>Ranney et al. (2020)</ns0:ref>. Because of the lack of protective equipment including face masks, extended manufacturing facilities have become very important for supporting the health care system. In this regard, the production of protective masks using 3D printing has proven very promising. This technology, often based on Fused Deposition Modelling (FDM) due to its cost and technical benefits, has found various applications in the manufacturing of medical devices such as prosthetic and dental implants or scaffolds in tissue engineering <ns0:ref type='bibr' target='#b25'>(Roopavath and Kalaskar 2017;</ns0:ref><ns0:ref type='bibr' target='#b29'>Tack et al. 2016)</ns0:ref>. The properties of 3D-printed objects render this technology attractive for manufacturing of protective masks. FDM provides adequate dimensional control, good surface finish and adaptability to use a variety of thermoplastic polymer filaments. The technology is based on high-temperature sintering of filaments and subsequent solidification of the printed product at room temperature. The polymers most commonly used for FDM are acrylonitrile-butadiene-styrene copolymers, polycarbonate, polyethylene terephthalate glycol (PETG) and polylactic acid (PLA) <ns0:ref type='bibr' target='#b8'>(Chadha et al. 2019;</ns0:ref><ns0:ref type='bibr' target='#b20'>Ngo et al. 2018)</ns0:ref>. Due to its unique properties, PLA is one of the most attractive materials for 3D printing. Its main advantages include low printing temperatures of 200-210 &#176;C, smooth appearance, low toxicity and favorable mechanical properties, especially a low warping effect and high geometric resolution <ns0:ref type='bibr' target='#b22'>(Pajarito et al. 2019;</ns0:ref><ns0:ref type='bibr' target='#b31'>Vicente et al. 2019)</ns0:ref>. PLA is a biodegradable linear aliphatic polyester produced from renewable natural resources such as corn, wheat or sweet sorghum <ns0:ref type='bibr' target='#b19'>(Nampoothiri et al. 2010)</ns0:ref>. <ns0:ref type='bibr' target='#b19'>Nagarajan et al. (2016)</ns0:ref> comprehensively reviewed its properties and applications. This polymer is produced by acidcatalyzed polycondensation of lactic acid monomers. Lactic acid of any chirality can be used, resulting in either poly-L-lactic acid, poly-D-lactic acid or poly-L,D-lactic acid (consisting of both isomers). Since L-lactic acid is the most common isomer in nature and is easily produced by lactic fermentation of various bio-wastes by bacteria (e.g. Lactobacillus spp.), it is also the most commonly used precursor for PLA manufacturing. The possibility of biotechnological production of the monomer significantly decreases its price, making the production of PLA very cheap. The glass transition temperature of PLA ranges between 50 and 80 &#176;C, and the melting temperature reaches approximately 175 &#176;C. Due to its natural precursor, PLA is easily biodegradable, e.g. by thermal decomposition, enzymatic digestion, oxidation or photolysis. <ns0:ref type='bibr' target='#b5'>Ghorpade et al. (2001)</ns0:ref> studied the outcome of PLA-composting for 90 days and found that the compound was degraded by 70 %. The use of PLA is limited by its poor thermal stability and easy hydrolysis -it degrades more easily than other aliphatic polyesters. Nevertheless, PLA has found many applications in diverse areas including the packaging industry as a food packaging polymer for short shelf life products, the pharmaceutical industry for controlled drug delivery formulations and for tissue regeneration, and agriculture for better herbicide delivery management without negative effects on crop yield <ns0:ref type='bibr' target='#b0'>(Auras et al. 2004;</ns0:ref><ns0:ref type='bibr' target='#b1'>Aziz et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b2'>Farto-Vaamonde et al. 2019)</ns0:ref>. Protective masks made by 3D printing from PLA are designed for repeated use, requiring frequent cleaning and disinfection. The low glass transition temperature and relatively low melting point of PLA makes heat sterilization in an autoclave at 121&#176;C impossible <ns0:ref type='bibr'>(McKeen 2014)</ns0:ref>. The polymer can be sterilized using ethylene oxide, gamma radiation <ns0:ref type='bibr' target='#b4'>(Fleischer et al. 2020)</ns0:ref> or dry heat below 80 &#8451; for no more than 20 min <ns0:ref type='bibr' target='#b34'>(Zou et al. 2011</ns0:ref><ns0:ref type='bibr' target='#b4'>). Fleischer et al. (2020)</ns0:ref> examined the changes of PLA properties after cleaning with chemical disinfectants such as Cidex Opa (Johnson &amp; Johnson) or chlorine solutions. Although these substances caused minor changes in stiffness and strength of 3D-printed PLA, 3D printing at appropriate conditions makes PLA objects mechanically amenable to cleaning and reuse. However, surface porosity of 3Dprinted PLA medical tools should be minimized to prevent exposure of users to residual disinfectants by inhalation or skin contact. <ns0:ref type='bibr' target='#b21'>Oth et al. (2019)</ns0:ref> studied PLA object sterilization by low-temperature hydrogen peroxide gas plasma in the commercially available Sterrad&#174; apparatus <ns0:ref type='bibr'>(Johnson &amp; Johnson)</ns0:ref>. They observed only sub-millimeter deformations induced by this process, rendering it suitable for sterilization in different areas including surgical applications. In contrast to conventional steam autoclaving, sterilization by hydrogen peroxide prevents deformation of 3D-printed objects made from PLA or PETG. <ns0:ref type='bibr' target='#b28'>Swennen et al. (2020)</ns0:ref> presented a prototype of reusable custom-made 3D-printed face masks (produced by a selective laser sintering technique) from polyamide composite components. The authors proposed cleaning by 15 min exposure to a broad-spectrum antimicrobial solution, ANIOS CLEAN EXCEL, containing didecyldimethylammonium chloride and chlorhexidine digluconate. Nevertheless, material leakage and virus decontamination of the reusable face mask components have not been tested upon one or more disinfection cycles.</ns0:p><ns0:p>In the present study, we have investigated FDM 3D-printed PLA structure and porosity after exposure to common chemical disinfectants including ethanol, isopropanol and a commercial disinfectant containing sodium hypochlorite, which are easily accessible. In addition, we examined the efficiency of PLA disinfection after artificial contamination with bacteria (Staphylococcus epidermidis, Escherichia coli), a yeast fungus (Candida albicans), viruses (SARS-CoV-2 and human adenovirus -HAdV) or natural contamination by wearing the masks.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>PLA material and masks preparation by 3D printing</ns0:head><ns0:p>Polylactic acid (PLA) was purchased in the form of filament for FDM 3D printing from Shenzen Creality 3D Technology Co., LTD, China. Protective masks, circular plates (diameter of 10 cm and height of 0.2 cm, printed vertically) and square carriers (1&#215;1 cm, 0.2 cm high) (Fig. <ns0:ref type='figure'>1</ns0:ref>) were prepared using a 3D printer (Prusa i3 MK3, Czech Republic). The printing template was designed with Trimble Sketchup Pro, exported in a stereolithographic (stl) file (freely available at the link https://www.facebook.com/groups/1346383268879783/files/) and used to print the objects of investigation. The printing parameters were as follows: layer height = 0.3 mm, shell thickness (perimeter) = 0.4 mm, bottom/top thickness = 0.2 mm, fill density = 10 %, print speed = 90 mm/s, extrusion temperature = 215 &#176;C, platform temperature = 60 &#176;C, filament flow = 95 %, machine nozzle size 0.4 mm, the infill pattern was grid (i.e., linear tilted 45&#176;) and the total layers = 338.</ns0:p></ns0:div> <ns0:div><ns0:head>Visualization of PLA mask structure using scanning electron microscopy</ns0:head><ns0:p>The structure and porosity of PLA 3D-printed masks were examined using a scanning electron microscope (SEM) Nova NanoSEM 450 (Fei, USA). Approximately 1&#215;1 cm pieces cut from printed masks were completely air-dried and visualized by SEM. Since the material is very sensitive to electron exposure, mild conditions had to be used, i.e. voltage of 5 kV and low vacuum. Images of each visualized position were captured by LVD detector at gradual magnifications 2000&#215;, 1000&#215;, 500&#215;, 100&#215; (focusing on identical position), dwell time 5 &#181;s and spot size 4.5. The size of the pores between PLA filaments was measured and marked using a SEM operating software (xT microscope Control v6.3.4 build 3233), provided by the SEM manufacturer (Fei, USA). The SEM images shown in this study were selected as representative visualizations of the PLA microstructure.</ns0:p></ns0:div> <ns0:div><ns0:head>Visualization of PLA mask structure under stress conditions using scanning electron microscopy</ns0:head><ns0:p>To investigate the impact of possible stress factors for PLA masks, cleaning with chemicals was performed and exposure to wearing-associated contamination was simulated, as outlined below. The effect of immersing in three chemical disinfectants [96% ethanol, 70% isopropanol and the commercial disinfectant and bleach SAVO Original, Unilever &#268;R s.r.o., Czech Republic containing 0.85% sodium hypochlorite diluted with water (2:9)] was tested by repeated (5 x 15 min) cycles and long-term (24 hour) exposure. The simulation of human impact on the PLA structure was performed as follows: extensive exposure to fingers (to simulate incorrect application of the mask), abrasion with paper (minor mechanical stress) and dining fork (strong mechanical stress), immersion in 1.9% sodium chloride solution for 4 hours (to simulate perspiration). Short rinsing with 100% acetone was examined to investigate its effect on PLA surface properties. After each treatment, completely dried PLA carriers were examined using SEM, as described above.</ns0:p></ns0:div> <ns0:div><ns0:head>Aerosol particle passage through PLA material</ns0:head><ns0:p>Surface contamination (and potential surface penetration) with infectious agents was simulated by an aerosol generator and a photometer (Lorenz Me&#946;ger&#228;tebau FMP 03) with a differential pressure sensor (Supplementary Fig. <ns0:ref type='figure'>1</ns0:ref>), providing a suitable test system with stand for facial masks and flat filter materials. The device was certified as a test system according to the standards EN 143 (Respiratory protective devices -Particle filters -Requirements, testing, marking), and EN 149 (Respiratory protective devices -Filtering half masks to protect against particles -Requirements, testing, marking). A sample of the PLA material was attached in the standardized testing cartridge and was sealed with silicone to prevent false positive detection of penetrating particles passing along the edge of the PLA panel (Supplementary Fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). The cartridge was mounted into the Lorenz Me&#946;ger&#228;tebau FMP 03 device, between the aerosol generator and photometer. The aerosol generator produced a defined amount of aerosolized paraffin oil, the test system passed it through the material, and the photometer situated on the other side of the PLA sample measured the aerosol concentration, thereby indicating the retention efficiency. An integrated differential pressure sensor was used to determine the pressure loss during passage through the sample. The particle size distribution was approximately 0.1 -2 &#181;m (geometric mean 0.44 &#181;m), which is close to the most frequently observed penetrating particle size (Supplementary Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>). The output of the aerosol generator was set to 150 &#8240; with flow 95 L/min, atomizer pressure 5 bar and oil temperature 60 &#176;C. The test was performed for 270 s.</ns0:p></ns0:div> <ns0:div><ns0:head>Disinfection of PLA material artificially contaminated with bacteria and yeast fungus</ns0:head><ns0:p>Wild strains of Staphylococcus epidermidis, Escherichia coli and Candida albicans were used as representatives of gram-positive and gram-negative bacteria or yeast fungus, respectively. The concentration of bacteria was adjusted to approximately 1&#215;10 7 colony forming units (CFU) per mL, the fungus concentration was 1&#215;10 6 CFU/mL. Each PLA carrier with a size of 1&#215;1 cm was contaminated with 10 &#181;L of microbial suspension applied to the surface of carriers in 1 &#181;L droplets for 1 h. The disinfection of contaminated carriers was carried out by immersing in 3 mL of 96% ethanol, 70% isopropanol, or 0.85 % sodium hypochlorite (SAVO Original, Unilever &#268;R s.r.o., Czech Republic) for 15 min. After evaporation of disinfectant solutions, the carriers were immersed in 1 mL of sterile saline, vortexed, and the obtained suspensions were inoculated onto appropriate agar plates. Blood agar was used for S. epidermidis, M&#252;ller-Hinton (Oxoid, Czech Republic) agar for E. coli and Sabouraud agar (Oxoid, Czech Republic) for C. albicans. Samples not exposed to treatment by disinfectants were used as controls. The inoculated plates were incubated at 37 &#176;C for 48 h. Each experiment was done in triplicate, and results were obtained by counting the average CFU/mL. Manuscript to be reviewed Disinfection of PLA material artificially contaminated with viruses SARS-CoV-2, the causative agent of the COVID-19 pandemic, was isolated in a biosafety level 3 laboratory from a nasopharyngeal swab by inoculating Vero CCL81 cells (ECACC 84113001) and subsequent expansion by two additional passages in Vero CCL81 cells. Passage 3 was cleared by centrifugation at 1000 g for 5 min, passed through a 0.45 &#181;m filter, and stored at -80 &#176;C until use. In addition to SARS-CoV-2, inactivation of a stable DNA virus, the Human Adenovirus 2 ATCC VR-846 (HAdV) obtained from the American Type Culture Collection (ATCC) was assessed. Similar to the previous set of experiments, PLA carriers of 1&#215;1 cm size were contaminated with 20 &#181;L of a SARS-CoV-2 suspension displaying a median tissue culture infectious dose (TCID50) of 10 6 IU/mL, which was applied to the surface of carriers in 1 &#181;L droplets. An additional set of carriers was covered with 50 &#181;L of HAdV suspension (10 6 virus copies) spread evenly over the entire surface. The contaminated carriers were then immersed in 96% ethanol, 70% isopropanol or 0.85% sodium hypochlorite for 15 min. Subsequently, residual viruses -if present-were washed from the dried surface using 180-200 &#181;L PBS. The solution was used directly for infection of Vero-E6 cells (ATCC CRL-1586), in case of SARS-CoV-2, or A-549 human lung carcinoma cells (DSMZ ACC107 from German Collection of Microorganisms and Cell Cultures), in case of HAdV, respectively. Recovered SARS-CoV-2 was titrated by an immunofluorescence (IF) assay using a 1:2.5 serial dilution of Vero-E6 cells starting from 10 &#181;L. Vero-E6 cells were incubated for 72 hours at 37 &#176;C in a CO 2 incubator prior to the IF assay. Briefly, medium was washed out, cells were fixed using 4% paraformaldehyde (PFA), cell membranes were perforated with 0.2% Triton-X100, and SARS-CoV-2 was labeled with primary mouse anti-SARS-CoV-2 antibody. Secondary anti-mouse antibody was conjugated with a Cy3 fluorophore and a fluorescent microscope (Olympus IX 81, Germany) was used for signal detection. In the case of HAdV, serial dilutions of virus inoculum were used to infect A-549 cells and the cytopathic effect (CPE) was determined using Motic AE21 Inverted Phase Contrast Microscope (Zeiss, Germany). The titers of both recovered viruses infection particles were determined as TCID50 and calculated using the Spearman-K&#228;rber method <ns0:ref type='bibr' target='#b14'>(K&#228;rber 1931;</ns0:ref><ns0:ref type='bibr' target='#b26'>Spearman 1908</ns0:ref>). In addition, recovered HAdV genome copies were determined by real-time quantitative PCR (RQ PCR) as described previously <ns0:ref type='bibr' target='#b16'>(Lion et al. 2003</ns0:ref>) using the ABI Prism Fast 7500 Instrument (Thermo Fisher Scientific, MA, USA).</ns0:p></ns0:div> <ns0:div><ns0:head>Disinfection of PLA masks worn by test persons</ns0:head><ns0:p>To investigate the feasibility of disinfecting PLA protective masks in practical use, three volunteers wore the protective masks of the same type for 4 h. Thereafter, smears from one half of the inner (approximately 80 cm 2 ) or outer surface (approximately 83 cm 2 ) of each mask were performed using sterile cotton swabs. These samples served as a control for natural mask contamination by manual handling, direct skin contact and exhalation. Each cotton swab was transferred into 1 mL of 0.9% saline in a microtube, vortexed and inoculated onto a blood agar plate. Thereafter, the filters were removed from masks and the PLA skeletons of the masks were immersed in 96% ethanol for 15 min. After ethanol evaporation, cotton swab smears were taken from the second halves of the inner and outer mask surfaces, inoculated onto agar plates, and incubated at 37 &#176;C for 48 h. The results were averaged and expressed as CFU/mL.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Investigation of structure and porosity of 3D-printed PLA material</ns0:head><ns0:p>The structure and porosity of PLA masks produced by 3D printing were investigated by SEM. Scanning electron micrographs of gaps between the PLA filaments were captured at four different magnifications (Fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). The PLA filament size determined was 312.8 &#181;m (data not shown) and its surface appeared macroscopically very smooth (Fig. <ns0:ref type='figure' target='#fig_7'>2A</ns0:ref>). Further magnification showed only slight roughness of the surface and very small gaps between filaments (Fig. <ns0:ref type='figure' target='#fig_2'>2B, 2C</ns0:ref>). Additional increase of magnification revealed connecting filaments of PLA, resulting from the high temperature during 3D printing, with only very small pores (6.049 &#181;m in size) in between. The pores appeared to be completely closed deeper in the carrier, as observed at the highest magnification used (2000&#215;) (Fig. <ns0:ref type='figure' target='#fig_2'>2D</ns0:ref>). To further test whether the pores were indeed closed and prevented particles from passing through the printed mask, we determined the number of paraffin oil aerosol particles displaying a size of 0.1 -2 &#181;m using the aerosol generator and photometer, certified as a test system according to the common standards. Maximum pressure loss of the generated aerosol was detected, and absolutely no penetration occurred even though the PLA sample was printed with a diameter of 10 cm (corresponds approximately to the printed height of the masks) in the vertical position, simulated printing at a lower temperature in the upper layers (on the z-axis).</ns0:p></ns0:div> <ns0:div><ns0:head>Effect of ethanol, isopropanol and sodium hypochlorite on disinfection of PLA material contaminated with bacteria, yeast fungus or viruses</ns0:head><ns0:p>The results of disinfection of artificially contaminated PLA are summarized in Tables <ns0:ref type='table'>1 and 2</ns0:ref>. Although the untreated PLA carriers were contaminated by highly concentrated bacterial suspensions of 1&#215;10 5 CFU/mL, complete decontamination by all disinfectants used was achieved. Single colonies were observed in the samples of S. epidermidis and E. coli disinfected by isopropanol, but these isolated findings can reasonably be considered a contamination that occurred after treatment of the samples. The disinfection of PLA carriers contaminated with C. albicans (4&#215;10 4 CFU/mL) was complete in all cases. Titers of SARS-CoV-2 and HAdV recovered from disinfected or untreated carriers were determined by IF-and CPE-based assays, respectively. All disinfection agents tested showed complete virucidal effects against SARS-CoV-2. Disinfectants per se exhibited a cytotoxic effects on Vero-E6 cells (data not shown), but this effect was eliminated by serial dilutions during virus titer determination. HAdV infectivity was reduced by ethanol and isopropanol, and completely abolished by sodium hypochlorite. Similar trends were observed by RQ-PCR performed for detecting the HAdV genome copy numbers (Supplementary Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Investigation of PLA structure after exposure to ethanol, isopropanol and sodium hypochlorite</ns0:head><ns0:p>The effect of disinfectants on the PLA structure was investigated using SEM. PLA structure, gaps between filaments, and the structure of pores after five 15 min cycles of immersing the carrier in different disinfectants are shown in Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>. Treatment with ethanol (Fig. <ns0:ref type='figure' target='#fig_4'>3B</ns0:ref>) resulted in slight melting of the PLA filaments, as compared with untreated PLA (Fig. <ns0:ref type='figure' target='#fig_7'>3A</ns0:ref>). The overall PLA structure and surface did not change , but, interestingly, the gap size between the filaments was reduced from the original 6 &#181;m to approximately 850 nm (Fig. <ns0:ref type='figure' target='#fig_4'>3B</ns0:ref>). This indicates that ethanol treatment may improve the PLA mask properties with regard to structure density. Similarly, isopropanol treatment did not significantly affect the PLA structure (Fig. <ns0:ref type='figure' target='#fig_4'>3C</ns0:ref>). Only slight melting was detectable, resulting in decreased gap size to 3.3 -4 &#181;m, in comparison to 6 &#181;m in control samples. Moreover, the surface of filaments remained undamaged. Fig. <ns0:ref type='figure' target='#fig_4'>3D</ns0:ref> depicts the effect of sodium hypochlorite, which did not alter the surface of filaments, but precipitated disinfectant filled the gaps between them, while the gap size remained almost the same as in the control sample (5 -7 &#181;m). Long-term treatment of PLA by immersion in disinfectants for 24 hours was also investigated using SEM (Fig. <ns0:ref type='figure'>4</ns0:ref>). The effect of long-term treatment with ethanol (Fig. <ns0:ref type='figure'>4B</ns0:ref>) was similar to repeated exposure to sodium hypochlorite (Fig. <ns0:ref type='figure' target='#fig_4'>3D</ns0:ref>), i.e. the gaps between filaments were significantly enlarged to 23.84 &#181;m (Fig. <ns0:ref type='figure'>4B</ns0:ref>), possibly filled with etched polymer. Investigation of aerosol particle passage through the PLA material after 24 hours in ethanol confirmed that the enlarged gaps were sealed, as no penetration was detected. PLA melting was also observed after prolonged isopropanol treatment (Fig. <ns0:ref type='figure'>4C</ns0:ref>). The gaps between filaments were sealed with the polymer in an irregular manner, resulting in variable gap sizes ranging from 1.3 to 4.1 &#181;m. As in all previous tests with ethanol, the surface of PLA filaments remained unaffected. In contrast, long-term treatment with sodium hypochlorite damaged the surface of PLA filaments and revealed precipitation of the disinfectant on the surface (Fig. <ns0:ref type='figure'>4D</ns0:ref>). Similarly to short treatment with sodium hypochlorite, the gaps between filaments, ranging from 2 to 3.5 &#181;m, were completely filled with precipitated sodium hypochlorite (Fig. <ns0:ref type='figure' target='#fig_4'>3D</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Disinfection of PLA masks by ethanol upon wearing by test persons</ns0:head><ns0:p>To complement the results of disinfection upon artificial contamination (Tables. 1 and 2), disinfection of PLA masks after natural use was investigated. The disinfection efficiency with ethanol (96%) is summarized in Table <ns0:ref type='table'>3</ns0:ref>. The microbial load detected on the inner surface of untreated masks varied significantly between different users, ranging from hundreds to thousands CFU/mL. Despite this variation, an average of 7 CFU/mL remained detectable after immersing the masks in ethanol for 15 minutes (short rinsing with ethanol was not sufficiently effective; data not shown). On the outer surface of untreated masks, 50-150 CFU/mL were detected, and an average of 2 CFU/mL remained detectable after disinfection (Fig. <ns0:ref type='figure' target='#fig_5'>5</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Visualization of PLA structure upon mechanical and chemical challenge</ns0:head><ns0:p>The impact on the PLA material by finger contact, abrasion by paper or metal and treatment by sodium chloride solution (mimicking perspiration) was analyzed using SEM (Fig. <ns0:ref type='figure' target='#fig_6'>6</ns0:ref>). Although fingers may be greasy or sweaty, the contact did not cause any marks or alterations on the PLA surface (Fig. <ns0:ref type='figure' target='#fig_7'>6A</ns0:ref>). Similarly, gentle mechanical abrasion with paper did not affect the material (Fig. <ns0:ref type='figure' target='#fig_6'>6B</ns0:ref>). By contrast, intensive mechanical scraping with a dining fork significantly damaged the PLA structure (Fig. <ns0:ref type='figure' target='#fig_6'>6C</ns0:ref>), leading to compression of PLA filaments, reduction of interfilament gaps, and shedding of PLA pieces (Fig. <ns0:ref type='figure' target='#fig_6'>6D</ns0:ref>). However, neither loosening of filaments, nor increase in gap size or other deformations were observed. Soaking in sodium chloride solution did not affect the structure, but salt crystals were present in the gaps between filaments (Fig. <ns0:ref type='figure' target='#fig_6'>6E</ns0:ref>). In addition, the effect of acetone, which is known to damage PLA, was evaluated. Virtually no gap was visible between filaments upon treatment, indicating that even short exposure to acetone smoothens the structure and seals the pores (Fig. <ns0:ref type='figure' target='#fig_6'>6F</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The unexpected and sudden spread of SARS-CoV-2 infection, which resulted in the COVID-19 pandemic, has led to a desperate shortage of personal protective equipment, especially among the frontline workers. Because of this problem, many people started helping each other by manufacturing facial protection equipment from commonly available resources. An intriguing possibility is the production of protective face masks using FDM, the most widespread technique of 3D printing. A variety of polymers are suitable for FDM, including biodegradable PLA as the most affordable and environmentally friendly material because of its natural origin <ns0:ref type='bibr' target='#b20'>(Ngo et al. 2018)</ns0:ref>. Despite the potential benefits, the suitability of PLA-based materials for protection against viruses was questioned due to their possible high porosity. To the best of our knowledge, this report provides the first data addressing this issue by testing 3D-printed PLA masks (Fig. <ns0:ref type='figure'>1</ns0:ref>). The surface and other mechanical properties of products made from PLA or composite filaments were investigated previously <ns0:ref type='bibr' target='#b7'>(Graupner et al. 2009;</ns0:ref><ns0:ref type='bibr' target='#b10'>Chi et al. 2018;</ns0:ref><ns0:ref type='bibr' target='#b12'>Ivanov et al. 2019;</ns0:ref><ns0:ref type='bibr' target='#b32'>Wang et al. 2016)</ns0:ref>. However, the microstructure of 3D-printed PLA objects is highly dependent on the printing parameters, and it is not possible to predict the structure and porosity of a particular object based on published data. To investigate the surface properties of protective face masks made from PLA, examination of structure and porosity is required. We showed by SEM that 3Dprinted PLA masks have a compact structure, with small gaps between filaments. The gaps between individual filaments were 6 &#181;m wide, but higher magnification showed that the pores were not continuous within the PLA carrier (Fig. <ns0:ref type='figure' target='#fig_2'>2D</ns0:ref>) and were actually completely closed. This finding was supported by measurements of the filtering efficiency of PLA, which revealed completely blocked passage of nanometer-sized paraffin aerosol particles. The mask material can therefore be considered impermeable for particles displaying the size range tested, including the fungus, bacteria, and viruses investigated. In combination with the obligatory single-use filters complying with FFP2/3 standards, which are inserted into the mask, spreading of the smallest viruses can also be prevented. Moreover, short exposure to acetone resulted in smoothening of the PLA surface (Fig. <ns0:ref type='figure' target='#fig_6'>6F</ns0:ref>).</ns0:p><ns0:p>A similar 3D-printed reusable face mask prototype was reported by <ns0:ref type='bibr' target='#b28'>Swennen et al. (2020)</ns0:ref>. The material (polyamide composite) and the printing method used (selective laser sintering technique) differ from the approach presented, but it provided a proof of principle for 3D printing of individualized 3D face masks with FFP2/3 filter membranes as a feasible and valuable alternative source for protective equipment. However, the authors of the cited study did not perform any virus decontamination testing of the reusable components of the face masks and were hence unable to assess the impact of repeated cycles of disinfection on the properties of the material. It was important therefore to determine the possibility of disinfecting the reusable face mask matrix. While SARS-CoV-2, being an enveloped RNA virus, belongs to the less challenging pathogens in terms of disinfection, HAdV (non-enveloped DNA virus) is highly resistant to commonly used disinfectants <ns0:ref type='bibr' target='#b6'>(Gordon et al. 1993;</ns0:ref><ns0:ref type='bibr'>Lion et al. 2020)</ns0:ref>. Adenoviruses mostly cause infections with only mild symptoms in immunocompetent hosts <ns0:ref type='bibr' target='#b15'>(Lion 2019)</ns0:ref>, but due to their exceptional stability provide a perfect model for testing the inactivation efficiency. In addition, we examined the disinfection of PLA material from contamination with bacteria (S. epidermidis and E. coli) and yeast fungus (C. albicans). These microorganisms are part of the human microbiome and their persistence on the protective mask surface poses a risk for infection and a health threat to mask users <ns0:ref type='bibr' target='#b3'>(Fisher and Shaffer 2014)</ns0:ref>. All bacterial and fungal microorganisms studied were successfully disinfected using either 96% ethanol, 70% isopropanol or 0.85% sodium hypochlorite, after immersing contaminated PLA carriers in the respective disinfectant for 15 min (Table <ns0:ref type='table'>1</ns0:ref>). Ethanol disinfected the PLA masks contaminated from using by humans (Fig. <ns0:ref type='figure' target='#fig_5'>5</ns0:ref>). In comparison to bacteria or fungi, viruses tend to be 1-2 orders of magnitude smaller, making them prone to enter deep into pores of the PLA material. Nevertheless, our data show that efficient disinfection of the PLA carriers from virus contamination is possible, as all tested disinfectants completely inactivated SARS-CoV-2 (Table <ns0:ref type='table'>2</ns0:ref>). Treatment with sodium hypochlorite for 15 minutes also completely inactivated the highly resistant HAdV, while ethanol and propanol only led to reduced loads of infectious virus (Table <ns0:ref type='table'>2</ns0:ref>). These data are in agreement with the reported sensitivity of both SARS-CoV-2 <ns0:ref type='bibr' target='#b11'>(Chin et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b13'>Kampf et al. 2020)</ns0:ref> and HAdV to specific disinfectants <ns0:ref type='bibr' target='#b6'>(Gordon et al. 1993;</ns0:ref><ns0:ref type='bibr'>Lion et al. 2020)</ns0:ref>. The present findings therefore provide evidence that PLA material disinfection can be performed with comparable efficiency to other surfaces by appropriate exposure to individual disinfectants. The results obtained can conceivably also help design efficient disinfection protocols for protective face masks made from different materials. <ns0:ref type='bibr' target='#b4'>Fleischer et al. (2020)</ns0:ref> examined the changes of PLA material after cleaning with chemical disinfectants (Cidex Opa, Johnson &amp; Johnson and chlorine solutions), revealing mild alterations in the stiffness and strength of 3D-printed PLA samples. However, the authors concluded that high-quality 3D-printed surfaces generated with appropriate printer settings permit cleaning and reuse of 3D-printed medical tools, without compromising their mechanical properties. The authors also stated that immersion in cleaning agents can lead to their absorption into the PLA structure. Thus, additional research is needed to establish efficient and safe chemical cleaning of various 3D-printed surfaces, to prevent health risks associated with tactile and inhalation exposure to chemically cleaned materials. In general, we observed that 5 cycles of PLA treatment for 15 minutes with alcohol-based disinfectants resulted in decreased gap size between PLA filaments, without any remnants of disinfectant visible by SEM. By contrast, sodium hypochlorite precipitate was retained in the PLA structure, filling the gaps between PLA filaments. Disinfection of PLA masks with 0.85% sodium hypochlorite therefore requires further medical investigation to determine whether exposure to the precipitate might be associated with any health risks. Long-term (24-hour) treatment of PLA material with disinfectants resulted in partial melting of the filaments, but no erosions of the material were observed (Fig. <ns0:ref type='figure'>4</ns0:ref>). Ethanol seems to be best suited for the disinfection of PLA masks because it evaporates and does not require removal by rinsing. Moreover, the barrier properties of the mask were not compromised even after long-term exposure, as determined by aerosol challenge. Although the surface of protective equipment should remain intact, inadvertent contacts with the hands and fingers often occur, and the possibility of inappropriate handling has to be considered. The pandemic setting requires medical staff to wear extensive protective equipment (e.g. overalls, gloves, protective shields, and face masks). Such equipment, together with high workload and stress, increases the body temperature and leads to excessive sweating. We mimicked such conditions by mechanical and chemical treatment in order to evaluate alterations of the protective masks. Touching the surface of the PLA material with fingers had no impact, but intensive mechanical stress caused alteration of the PLA filament surface, without affecting the inter-filament gap area. Treatment with sodium chloride (imitating perspiration and sweat) showed salt crystallization in the gaps between filaments (Fig. <ns0:ref type='figure' target='#fig_6'>6E</ns0:ref>). Crystallized salt compounds, such as sodium chloride or sodium hypochlorite (Figs. <ns0:ref type='figure' target='#fig_7'>3D and 4D</ns0:ref>), can cause discomfort by skin irritation and itching. This issue was described in detail by <ns0:ref type='bibr' target='#b23'>Payne (2020)</ns0:ref> and <ns0:ref type='bibr' target='#b33'>Wollina (2020)</ns0:ref> who stated that especially front-line workers obliged to wear a single face mask all day suffer from these problems. The exploitation of PLA may solve this issue, because the fast and cheap manufacturing of protective masks made from this material permits production on a large scale, thereby facilitating more frequent mask changes. Additionally, 3D-printed protective PLA masks are biodegradable, with relatively short decomposition time, thereby providing an environmentally friendly solution.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study shows that PLA material is suitable for protection against various microorganisms as it is not permeable for submicroscopic particles. PLA can be efficiently disinfected from bacteria, yeast fungus, and SARS-CoV-2 by commonly available chemical disinfectants such as ethanol, isopropanol or sodium hypochlorite. However, contamination with HAdV, a highly resistant representative of non-enveloped viruses, could only be completely removed with sodium hypochlorite. PLA material is not altered by the immersion in disinfectant or by manual handling. Possible skin irritation after the use of certain disinfectants needs to be carefully evaluated. Single-use filters meeting the FFP2/3 standards are inserted into the mask structure and will be subject of further research and optimization. Overall, PLA can be recommended as suitable material for the manufacturing of protective face masks at times of epidemic spread of infections, such as the ongoing COVID-19 pandemic.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>Objects made from PLA filaments using 3D printing by the FDM technology. Manuscript to be reviewed Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure 4</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49258:1:1:NEW 6 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>( A )</ns0:head><ns0:label>A</ns0:label><ns0:figDesc>PLA carriers (1&#215;1 cm). (B) Circular plate with a diameter of 10 cm (printed vertically). (C, D, E) Different types of PLA masks. PeerJ reviewing PDF | (2020:05:49258:1:1:NEW 6 Aug 2020)Manuscript to be reviewed</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>( A )</ns0:head><ns0:label>A</ns0:label><ns0:figDesc>Magnification 100&#215;, scale bar 500 &#181;m. (B) Magnification 500&#215;, scale bar 100 &#181;m. (C) Magnification 1000&#215;, scale bar 50 &#181;m. (D) Magnification 2000&#215;, scale bar 30 &#181;m. The observed gaps were measured and marked by black lines. SEM parameters: low vacuum, 5 kV, LVD detector, dwell time 5 &#181;s, spot size 4.5. Images were taken at various magnifications at the same position. PeerJ reviewing PDF | (2020:05:49258:1:1:NEW 6 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>( A )</ns0:head><ns0:label>A</ns0:label><ns0:figDesc>Sample touched by finger. (B) Slightly mechanically stressed sample (paper abrasion). (C) Extremely mechanically stressed sample (scratching by dining fork). (D) Detail of a pore in extremely mechanically stressed sample (dining fork). (E) Sample after immersion in saline solution (perspiration and sweat simulation). (F) Sample after short rinsing with acetone. SEM parameters: low vacuum, 5 kV, LVD detector, magnification 100&#215; or 500&#215;, dwell time 5 &#181;s, spot size 4.5, scale bar 500 or 100 &#181;m.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='19,42.52,326.62,525.00,377.25' type='bitmap' /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49258:1:1:NEW 6 Aug 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49258:1:1:NEW 6 Aug 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"First of all, the authors would like to acknowledge the valuable suggestions and comments of reviewers, hopefully resulting to the improvement of our manuscript. Reviewer 1: Basic reporting This work evaluates fused deposition modeling 3D printed PLA materials as protective shields against bacteria and viruses. It analyzes material porosity in the context of repeated disinfections and mechanical wear. Tightness is also tested using certified equipment, specifically designed to test the effectiveness of respiratory protective devices. The paper is clearly written and well structured. The introduction provides the necessary background and explains the motivation in light of the relevant literature. The illustrations are of good quality, but I would eliminate the low-magnification (left) panels of Figs. 3 and 4. The panels with low magnification (left) were removed from Figures 3 and 4 according to the reviewer’s recommendation. The text of the manuscript was correspondingly changed. 1.1. There is one reporting flaw in this paper. SAVO is a brand name (https://www.unilever.com/news/press-releases/2013/13-04-08-Unilever-Czech-Republic-acquires-SAVO-brand.html), not a product name. Several chlorine-free disinfectants are commercialized under the same brand name (https://www.drogeria-vmd.com/savo-washing-gel-20pcs-white-linen-6278/). Thus, it is important to give a more precise description of the product employed for the disinfection of the PLA samples in this study. To refer to it, please propose an acronym based on chemical composition (e.g. 0.85% NaOCl or NaOCl). The brand name will be mentioned just in the Materials and Methods section, as usual for reagents and instruments. The designation of used disinfectant was changed to 0.85% sodium hypochlorite, as reviewer proposed. The name SAVO remained only in the disinfectant’s description in methodology with proper determination of the product. Experimental design The methodology is ample and well explained. The work can be replicated based on the text. I would improve the following: 2.1. The term 'cytopathic effects' refers to structural changes in cells elicited by viral invasion. If you wish to refer to the impact of a chemical, consider using the term 'cytotoxicity'. Therefore, on line 265, I would replace 'exhibited a cytopathic effects' with 'exhibited cytotoxic effects'. The reviewer is correct, the sentence was rewritten according to his/her suggestion. 2.2. Some raw data is missing: - Please also present the raw data of filament size measurement (mentioned on line 239). The SEM image with filament size measurement was added into the raw data files. - Please provide the raw data for the statement 'Disinfectants per se exhibited ... (data not shown)...' (line 265). The table providing raw data for this statement was added. These data indicate that there is still an infectious virus in the control sample at the same dilution (2.5-fold) in which ethanol is non-toxic to cells. Validity of the findings While this work is vast, encompassing several techniques, I have two concerns regarding the validity of the results and the strength of the conclusions: 3.1. Figures 2-4 nicely illustrate the impact of disinfectants on the surface microstructure of the 3D printed samples. Unfortunately, the SEM analysis has not been performed on several spots of each sample to provide descriptive statistics of pore sizes in various conditions (mean+-standard deviation). I would perform such a quantitative image analysis of at least 100 sites per condition and apply the analysis of variance (ANOVA) to test whether the mean gap sizes differ significantly between the 4 groups (untreated, 96% ethanol, 70% isopropanol, and 0.85% NaOCl). In this work, SEM merely highlights certain spots, so quantitative assessments and their interpretation is speculative. We would like to thank the reviewer for the valuable comment. It is true that a careful statistical analysis of samples leads to excellent and reproducible results. On the contrary, the SEM images used in our work serve primarily for PLA samples visualization rather than for their quantification. The measurement of gap sizes was prepared merely as an example of PLA porosity which is highly dependent on 3D printing settings, filament manufacturer etc. Our recommendation of PLA as a suitable protection against microorganisms was based primarily on the results of the measurement of aerosol passage through PLA using a certified device. Due to these facts and our efforts to provide the obtained information as soon as possible to people all over the world who are fighting the COVID-19 pandemic, we hope that we can decently refuse the reviewer’s (very time-consuming) recommendation to measure 100 parallel gap sizes. On the other hand, we agree that we forgot to add raw data for SEM images stated in this work, thus we have corrected this omission. The raw data contain three spots for each sample. Simultaneously, we added information about representative SEM images selected in this work to the text in the methodology. For example, it is not clear why long-term exposure to SAVO leads to smaller gaps (Fig. 4D2) than short-term exposure (Fig 3D2). A solid statistical analysis of the change in porosity caused by 5 cycles of 15 minutes of alcohol-based treatments would strengthen the recommendations given in Discussion (lines 387-395) as well as the Conclusions. It is unquestionably true that we have not a satisfactory explanation why long-term exposure to SAVO leads to smaller gaps (Fig. 4D2) than short-term exposure (Fig 3D2). We can try to find some theoretical explanation, but we think that it is not the main content of this work. We recommend the disinfection of PLA masks by ethanol primarily since it is gentle to PLA material as well as to human skin and its effectivity against bacteria, yeast fungus and viruses is sufficient (with the only exception of adenovirus which is not the main problem during COVID-19 pandemic). 3.2. Also, NaOCl precipitates on the mask surface represent a safety concern, acknowledged by the authors (line 391). Since NaOCl is water-soluble, the PLA sample could be washed thoroughly with water after disinfection. The SEM analysis would have been more informative after extensive rinsing. Did it help to remove NaOCl? How are the pores left behind? This question has been already answered in the previous comment. “We recommend the disinfection of PLA masks by ethanol primarily since it is gentle to PLA material as well as to human skin and its effectivity against bacteria, yeast fungus and viruses is sufficient (with the only exception of adenovirus which is not the main problem during COVID-19 pandemic).” Comments for the author PeerJ addresses a broad readership, not just the 3D printing community. Therefore, the Supplementary Material would be much more useful as a single narrative text, written as a complement of the paper's Results section. In this text, please provide a caption for each illustration. We are not sure we understand the reviewer’s comment correctly, however, we assume that the Supplementary Material contents only Figures referenced from the main text of the manuscript and another description in the Supplement would be redundant to the original text. Moreover, the Supplementary Figures are not crucial for the confirmation of the claims given in our work and their understanding. Besides the 4 illustrations currently given as Supplementary Material, I would include at least one more figure, representing the digital models of the 3D printed structures that were tested in the paper. (Porosity and sturdiness do depend on the design.) Such a figure would render the text between lines 250-252 clearer. We added the link to the original .stl file for mask model which is freely available for everybody and was used for the mask printing. Reviewer: Stelian Arjoca Basic reporting This paper investigates polylactic acid as a suitable material for 3D printed personal protective masks. Overall, the manuscript is well structured and professionally written using clear language. The illustrations used are thoughtfully chosen and appropriately described and discussed. However, several discrepancies appear between the scale bar size depicted in several figures (2B, 2D, 3A2-D2, 4A2-D2) and their description in the corresponding figure captions. I recommend the authors to resolve or explain these discrepancies in the revised version of the manuscript. In addition, the authors might consider improving the clarity of Figures 2, 3, 4 and 6. For example, by increasing thickness of the yellow segments (used to mark and measure gap width), and/or changing their color, to improve their contrast. Further, the legend containing the SEM parameters could the magnified to increase readability or removed completely (since the relevant information is also included in the figure captions). We thank to the reviewer for the notice of mistakes in the figures’ description. Of course, we fixed it. The legends and marks in the SEM figures were changed into the distinctive and large ones, hopefully for better visibility and clarity to the readers of the article. Experimental design I commend the authors for the experimental design of this study. The methodology was appropriately chosen to consider all the practical aspects regarding material decontamination and degradation. In addition, the employed methods are sufficiently explained to enable the replication of their work. Validity of the findings The obtained results and their discussion are meaningful. Aware of the limitations of the study (especially related to the retention of sodium hypochlorite precipitate in the masks and its uncertain health risk), the authors proved that PLA is suitable material for the manufacturing of protective masks. Considering the ongoing COVID-19 pandemic and the associated shortage of protective equipment, this study is particularly interesting and useful. I congratulate the authors for the excellent work and recommend their manuscript for publication in PeerJ. Comments for the author On line 6, there is a typo – the first affiliated institution is marked with letter “a”, while the others are numbered. We thank the reviewer for pointing that out. The wrong marking was corrected. Reviewer 3 Basic reporting How about printing a flexible mask? It could combine PLA with TPU. Check reference: 3D-printed flexible polymer stents for potential applications in inoperable esophageal malignancies. Of course, there is still a lot of space for improvement of our proposed solution with PLA masks. More flexible material for the face masks preparation would be undoubtedly beneficial. However, we evaluated PLA filament due to cheap manufacturing cost, the composability and easy working properties. In addition, any other change will probably lead to an extension of the mask printing process which is not desirable in the case of an acute lack of protective equipment. The flexible material can also change the possibility of easy disinfection (as we tested also the flexible military face masks which were not possible to disinfect by ethanol – data will be a part of another project in the future). In conclusion, the combination of more materials for 3D printed face masks can be beneficial, but it opens a new call for another huge investigation project. Experimental design What is the mechanical property after printing? The author should provide more details about the structure, like dimensions. what is the porosity parameter? It is true that PLA masks are quite fragile, but on the other hand, for the face mask usage, it is mechanically resistant enough. Unfortunately, we have no laboratory measurement supporting this claim, but these masks were used by doctors and nurses in the hospitals in the Czech Republic (at their own discretion and knowledge of the risk, so far PLA was only the currently tested material) and the use of these masks was in normal operation without any problem. Unfortunately, it was not in our power to include more far-reaching results in such a short time and our study is focused mainly on the microbiological side of this problem. Dimensions of the masks were provided in the link to the original .std file in the previous comment from another reviewer. The porosity of PLA masks is discussed in the text of the manuscript. Validity of the findings PLA is a biodegradable material. How does PLA behave under a mask situation? Generally, PLA is proved to be biodegradable. Since we used only PLA for the printing of masks, such biodegradability should be met in this case also. We have unfortunately not done any experiments on the composability of our masks since such a process would take 3 or more months at least. We wanted to publish our work as soon as possible to help others in times of need. Since the threat of COVID-19 is more than real in most states, the alternative source of protective equipment is sought. The additional experiment on the perishable character of our masks can always be carried out in the future without the time pressure. Comments for the author How does the structure effectively protect? The mask is designed to cover the user’s face firmly, so there would not be any space between the material and skin. Such wearing together with almost no permeability of PLA material and proper filter would ensure, that the wearer would not get infected from air contaminated with bacteria, yeast, or viruses. The protectivity of this material lies in the low porosity and relatively high tolerance to disinfectants. Under proper wearing conditions, our masks should fulfill the requirements of respiratory masks routinely used in medicine. The main advantage of our masks in comparison with those routinely used is the reusability and the composability since most of the medical equipment is meant only for one use and most of them are not biodegradable (e.g. plastic materials). What is the reaction between PLA and viruses? Will the mask contain the virus? Do you need to clean it after multiple uses? In the case of contact with infected patient/person, the masks will be highly probably in contact with the virus. Also, the droplets from the user's mouth contain a high number of bacteria and yeast (or viruses) which fall on the surface of the mask. Therefore, the cleaning of the masks is absolutely necessary. PLA polymer is not permeable for viruses as we have evaluated. For proper decontamination of the mask which was in the contact with SARS-CoV-2, we have proposed several disinfectants (and highly recommended disinfection with ethanol), which are able to sterilize the PLA mask completely. The cleaning after the use is strongly recommended and there also lies the novelty of our research, since the material is both biodegradable but also reusable and disinfectable by chemical disinfectants. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>A critical lack of personal protective equipment has occurred during the COVID-19 pandemic. Polylactic acid (PLA), a polyester made from renewable natural resources, can be exploited for 3D printing of protective face masks using the Fused Deposition Modelling technique. Since the possible high porosity of this material raised questions regarding its suitability for protection against viruses, we have investigated its microstructure using scanning electron microscopy and aerosol generator and photometer certified as the test system according to the standards EN 143 and EN 149. Moreover, the efficiency of decontaminating PLA surfaces by conventional chemical disinfectants including 96% ethanol, 70% isopropanol, and a commercial disinfectant containing 0.85% sodium hypochlorite has been determined. We confirmed that the structure of PLA protective masks is compact and can be considered a sufficient barrier protection against particles of a size corresponding to microorganisms including viruses. Complete decontamination of PLA surfaces from externally applied Staphylococcus epidermidis, Escherichia coli, Candida albicans and SARS-CoV-2 was achieved using all disinfectants tested, and human adenovirus was completely inactivated by sodium hypochlorite-containing disinfectant.</ns0:p><ns0:p>Natural contamination of PLA masks worn by test persons was decontaminated easily and efficiently by ethanol. No disinfectant caused major changes to the PLA surface properties, and the pore size did not change despite severe mechanical damage of the surface.</ns0:p><ns0:p>Therefore, PLA may be regarded as a suitable material for 3D printing of protective masks during the current or future pandemic crises.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head> <ns0:ref type='bibr'>COVID-19 (coronavirus disease 2019)</ns0:ref> <ns0:p>is the designation of the disease caused by the SARS-CoV-2 infection. The World Health Organization (WHO) declared this epidemic a global pandemic affecting the whole world on March 11, 2020. The infection by SARS-CoV-2 was confirmed for the first time in Wuhan, China, but had a huge impact also in Europe and later in North and South America. Lombardy, Italy was the most severely affected region in Europe. Due to the risk of health care system collapse, the Italian government ordered a nationwide lockdown <ns0:ref type='bibr' target='#b27'>(Spinelli and Pellino 2020)</ns0:ref>. Several studies showed that SARS-CoV-2, similarly to SARS-CoV-1, remains infectious for hours and days in aerosols and on surfaces, respectively <ns0:ref type='bibr' target='#b11'>(Chin et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b13'>Kampf et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b30'>van Doremalen et al. 2020)</ns0:ref>, emphasizing the need for efficient virucidal disinfection. The number of patients suffering from COVID-19 disease and the enormous rate of infection spread caused serious complications in many countries, including a desperate lack of protective equipment <ns0:ref type='bibr' target='#b28'>(Swennen et al. 2020)</ns0:ref>. Sufficient production and distribution of protective equipment has been crucial for sustaining patient care during the pandemic. The current unsatisfactory situation regarding protective equipment in the USA has been described by <ns0:ref type='bibr' target='#b24'>Ranney et al. (2020)</ns0:ref>. Because of the lack of protective equipment including face masks, extended manufacturing facilities have become very important for supporting the health care system. In this regard, the production of protective masks using 3D printing has proven very promising. This technology, often based on Fused Deposition Modelling (FDM) due to its cost and technical benefits, has found various applications in the manufacturing of medical devices such as prosthetic and dental implants or scaffolds in tissue engineering <ns0:ref type='bibr' target='#b25'>(Roopavath and Kalaskar 2017;</ns0:ref><ns0:ref type='bibr' target='#b29'>Tack et al. 2016)</ns0:ref>. The properties of 3D-printed objects render this technology attractive for manufacturing of protective masks. FDM provides adequate dimensional control, good surface finish and adaptability to use a variety of thermoplastic polymer filaments. The technology is based on high-temperature sintering of filaments and subsequent solidification of the printed product at room temperature. The polymers most commonly used for FDM are acrylonitrile-butadiene-styrene copolymers, polycarbonate, polyethylene terephthalate glycol (PETG) and polylactic acid (PLA) <ns0:ref type='bibr' target='#b8'>(Chadha et al. 2019;</ns0:ref><ns0:ref type='bibr' target='#b20'>Ngo et al. 2018)</ns0:ref>. Due to its unique properties, PLA is one of the most attractive materials for 3D printing. Its main advantages include low printing temperatures of 200-210 &#176;C, smooth appearance, low toxicity and favorable mechanical properties, especially a low warping effect and high geometric resolution <ns0:ref type='bibr' target='#b22'>(Pajarito et al. 2019;</ns0:ref><ns0:ref type='bibr' target='#b31'>Vicente et al. 2019)</ns0:ref>. PLA is a biodegradable linear aliphatic polyester produced from renewable natural resources such as corn, wheat or sweet sorghum <ns0:ref type='bibr' target='#b19'>(Nampoothiri et al. 2010)</ns0:ref>. <ns0:ref type='bibr' target='#b19'>Nagarajan et al. (2016)</ns0:ref> comprehensively reviewed its properties and applications. This polymer is produced by acidcatalyzed polycondensation of lactic acid monomers. Lactic acid of any chirality can be used, resulting in either poly-L-lactic acid, poly-D-lactic acid or poly-L,D-lactic acid (consisting of both isomers). Since L-lactic acid is the most common isomer in nature and is easily produced by lactic fermentation of various bio-wastes by bacteria (e.g. Lactobacillus spp.), it is also the most commonly used precursor for PLA manufacturing. The possibility of biotechnological production of the monomer significantly decreases its price, making the production of PLA very cheap. The glass transition temperature of PLA ranges between 50 and 80 &#176;C, and the melting temperature reaches approximately 175 &#176;C. Due to its natural precursor, PLA is easily biodegradable, e.g. by thermal decomposition, enzymatic digestion, oxidation or photolysis. <ns0:ref type='bibr' target='#b5'>Ghorpade et al. (2001)</ns0:ref> studied the outcome of PLA-composting for 90 days and found that the compound was degraded by 70 %. The use of PLA is limited by its poor thermal stability and easy hydrolysis -it degrades more easily than other aliphatic polyesters. Nevertheless, PLA has found many applications in diverse areas including the packaging industry as a food packaging polymer for short shelf life products, the pharmaceutical industry for controlled drug delivery formulations and for tissue regeneration, and agriculture for better herbicide delivery management without negative effects on crop yield <ns0:ref type='bibr' target='#b0'>(Auras et al. 2004;</ns0:ref><ns0:ref type='bibr' target='#b1'>Aziz et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b2'>Farto-Vaamonde et al. 2019)</ns0:ref>. Protective masks made by 3D printing from PLA are designed for repeated use, requiring frequent cleaning and disinfection. The low glass transition temperature and relatively low melting point of PLA makes heat sterilization in an autoclave at 121&#176;C impossible <ns0:ref type='bibr'>(McKeen 2014)</ns0:ref>. The polymer can be sterilized using ethylene oxide, gamma radiation <ns0:ref type='bibr' target='#b4'>(Fleischer et al. 2020)</ns0:ref> or dry heat below 80 &#8451; for no more than 20 min <ns0:ref type='bibr' target='#b34'>(Zou et al. 2011</ns0:ref><ns0:ref type='bibr' target='#b4'>). Fleischer et al. (2020)</ns0:ref> examined the changes of PLA properties after cleaning with chemical disinfectants such as Cidex Opa (Johnson &amp; Johnson) or chlorine solutions. Although these substances caused minor changes in stiffness and strength of 3D-printed PLA, 3D printing at appropriate conditions makes PLA objects mechanically amenable to cleaning and reuse. However, surface porosity of 3Dprinted PLA medical tools should be minimized to prevent exposure of users to residual disinfectants by inhalation or skin contact. <ns0:ref type='bibr' target='#b21'>Oth et al. (2019)</ns0:ref> studied PLA object sterilization by low-temperature hydrogen peroxide gas plasma in the commercially available Sterrad&#174; apparatus <ns0:ref type='bibr'>(Johnson &amp; Johnson)</ns0:ref>. They observed only sub-millimeter deformations induced by this process, rendering it suitable for sterilization in different areas including surgical applications. In contrast to conventional steam autoclaving, sterilization by hydrogen peroxide prevents deformation of 3D-printed objects made from PLA or PETG. <ns0:ref type='bibr' target='#b28'>Swennen et al. (2020)</ns0:ref> presented a prototype of reusable custom-made 3D-printed face masks (produced by a selective laser sintering technique) from polyamide composite components. The authors proposed cleaning by 15 min exposure to a broad-spectrum antimicrobial solution, ANIOS CLEAN EXCEL, containing didecyldimethylammonium chloride and chlorhexidine digluconate. Nevertheless, material leakage and virus decontamination of the reusable face mask components have not been tested upon one or more disinfection cycles.</ns0:p><ns0:p>In the present study, we have investigated FDM 3D-printed PLA structure and porosity after exposure to common chemical disinfectants including ethanol, isopropanol and a commercial disinfectant containing sodium hypochlorite, which are easily accessible. In addition, we examined the efficiency of PLA disinfection after artificial contamination with bacteria (Staphylococcus epidermidis, Escherichia coli), a yeast fungus (Candida albicans), viruses (SARS-CoV-2 and human adenovirus -HAdV) or natural contamination by wearing the masks.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>PLA material and masks preparation by 3D printing</ns0:head><ns0:p>Polylactic acid (PLA) was purchased in the form of filament for FDM 3D printing from Shenzen Creality 3D Technology Co., LTD, China. Protective masks, circular plates (diameter of 10 cm and height of 0.2 cm, printed vertically) and square carriers (1&#215;1 cm, 0.2 cm high) (Fig. <ns0:ref type='figure'>1</ns0:ref>) were prepared using a 3D printer (Prusa i3 MK3, Czech Republic). The printing template was designed with Trimble Sketchup Pro, exported in a stereolithographic (stl) file (freely available at the link https://www.facebook.com/groups/1346383268879783/files/) and used to print the objects of investigation. The printing parameters were as follows: layer height = 0.3 mm, shell thickness (perimeter) = 0.4 mm, bottom/top thickness = 0.2 mm, fill density = 10 %, print speed = 90 mm/s, extrusion temperature = 215 &#176;C, platform temperature = 60 &#176;C, filament flow = 95 %, machine nozzle size 0.4 mm, the infill pattern was grid (i.e., linear tilted 45&#176;) and the total layers = 338.</ns0:p></ns0:div> <ns0:div><ns0:head>Visualization of PLA mask structure using scanning electron microscopy</ns0:head><ns0:p>The structure and porosity of PLA 3D-printed masks were examined using a scanning electron microscope (SEM) Nova NanoSEM 450 (Fei, USA). Approximately 1&#215;1 cm pieces cut from printed masks were completely air-dried and visualized by SEM. Since the material is very sensitive to electron exposure, mild conditions had to be used, i.e. voltage of 5 kV and low vacuum. Images of each visualized position were captured by LVD detector at gradual magnifications 2000&#215;, 1000&#215;, 500&#215;, 100&#215; (focusing on identical position), dwell time 5 &#181;s and spot size 4.5. The size of the pores between PLA filaments was measured and marked using a SEM operating software (xT microscope Control v6.3.4 build 3233), provided by the SEM manufacturer (Fei, USA). The SEM images shown in this study were selected as representative visualizations of the PLA microstructure. The SEM analysis merely illustrates the 3D printed PLA surface morphology, and gap width measurements are not analyzed statistically.</ns0:p></ns0:div> <ns0:div><ns0:head>Visualization of PLA mask structure under stress conditions using scanning electron microscopy</ns0:head><ns0:p>To investigate the impact of possible stress factors for PLA masks, cleaning with chemicals was performed and exposure to wearing-associated contamination was simulated, as outlined below. The effect of immersing in three chemical disinfectants [96% ethanol, 70% isopropanol and the commercial disinfectant and bleach SAVO Original, Unilever &#268;R s.r.o., Czech Republic containing 0.85% sodium hypochlorite diluted with water (2:9)] was tested by repeated (5 x 15 min) cycles and long-term (24 hour) exposure. The simulation of human impact on the PLA structure was performed as follows: extensive exposure to fingers (to simulate incorrect application of the mask), abrasion with paper (minor mechanical stress) and dining fork (strong mechanical stress), immersion in 1.9% sodium chloride solution for 4 hours (to simulate perspiration). Short rinsing with 100% acetone was examined to investigate its effect on PLA surface properties. After each treatment, completely dried PLA carriers were examined using SEM, as described above.</ns0:p></ns0:div> <ns0:div><ns0:head>Aerosol particle passage through PLA material</ns0:head><ns0:p>Surface contamination (and potential surface penetration) with infectious agents was simulated by an aerosol generator and a photometer (Lorenz Me&#946;ger&#228;tebau FMP 03) with a differential pressure sensor (Supplementary Fig. <ns0:ref type='figure'>1</ns0:ref>), providing a suitable test system with stand for facial masks and flat filter materials. The device was certified as a test system according to the standards EN 143 (Respiratory protective devices -Particle filters -Requirements, testing, marking), and EN 149 (Respiratory protective devices -Filtering half masks to protect against particles -Requirements, testing, marking). A sample of the PLA material was attached in the standardized testing cartridge and was sealed with silicone to prevent false positive detection of penetrating particles passing along the edge of the PLA panel (Supplementary Fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). The cartridge was mounted into the Lorenz Me&#946;ger&#228;tebau FMP 03 device, between the aerosol generator and photometer. The aerosol generator produced a defined amount of aerosolized paraffin oil, the test system passed it through the material, and the photometer situated on the other side of the PLA sample measured the aerosol concentration, thereby indicating the retention efficiency. An integrated differential pressure sensor was used to determine the pressure loss during passage through the sample. The particle size distribution was approximately 0.1 -2 &#181;m (geometric mean 0.44 &#181;m), which is close to the most frequently observed penetrating particle size (Supplementary Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>). The output of the aerosol generator was set to 150 &#8240; with flow 95 L/min, atomizer pressure 5 bar and oil temperature 60 &#176;C. The test was performed for 270 s.</ns0:p></ns0:div> <ns0:div><ns0:head>Disinfection of PLA material artificially contaminated with bacteria and yeast fungus</ns0:head><ns0:p>Wild strains of Staphylococcus epidermidis, Escherichia coli and Candida albicans were used as representatives of gram-positive and gram-negative bacteria or yeast fungus, respectively. The concentration of bacteria was adjusted to approximately 1&#215;10 7 colony forming units (CFU) per mL, the fungus concentration was 1&#215;10 6 CFU/mL. Each PLA carrier with a size of 1&#215;1 cm was contaminated with 10 &#181;L of microbial suspension applied to the surface of carriers in 1 &#181;L droplets for 1 h. The disinfection of contaminated carriers was carried out by immersing in 3 mL of 96% ethanol, 70% isopropanol, or 0.85 % sodium hypochlorite (SAVO Original, Unilever &#268;R s.r.o., Czech Republic) for 15 min. After evaporation of disinfectant solutions, the carriers were immersed in 1 mL of sterile saline, vortexed, and the obtained suspensions were inoculated onto appropriate agar plates. Blood agar was used for S. epidermidis, M&#252;ller-Hinton (Oxoid, Czech Republic) agar for E. coli and Sabouraud agar (Oxoid, Czech Republic) for C. albicans. Samples not exposed to treatment by disinfectants were used as controls. The inoculated plates were Manuscript to be reviewed incubated at 37 &#176;C for 48 h. Each experiment was done in triplicate, and results were obtained by counting the average CFU/mL.</ns0:p></ns0:div> <ns0:div><ns0:head>Disinfection of PLA material artificially contaminated with viruses</ns0:head><ns0:p>SARS-CoV-2, the causative agent of the COVID-19 pandemic, was isolated in a biosafety level 3 laboratory from a nasopharyngeal swab by inoculating Vero CCL81 cells (ECACC 84113001) and subsequent expansion by two additional passages in Vero CCL81 cells. Passage 3 was cleared by centrifugation at 1000 g for 5 min, passed through a 0.45 &#181;m filter, and stored at -80 &#176;C until use. In addition to SARS-CoV-2, inactivation of a stable DNA virus, the Human Adenovirus 2 ATCC VR-846 (HAdV) obtained from the American Type Culture Collection (ATCC) was assessed. Similar to the previous set of experiments, PLA carriers of 1&#215;1 cm size were contaminated with 20 &#181;L of a SARS-CoV-2 suspension displaying a median tissue culture infectious dose (TCID50) of 10 6 IU/mL, which was applied to the surface of carriers in 1 &#181;L droplets. An additional set of carriers was covered with 50 &#181;L of HAdV suspension (10 6 virus copies) spread evenly over the entire surface. The contaminated carriers were then immersed in 96% ethanol, 70% isopropanol or 0.85% sodium hypochlorite for 15 min. Subsequently, residual viruses -if present-were washed from the dried surface using 180-200 &#181;L PBS. The solution was used directly for infection of Vero-E6 cells (ATCC CRL-1586), in case of SARS-CoV-2, or A-549 human lung carcinoma cells (DSMZ ACC107 from German Collection of Microorganisms and Cell Cultures), in case of HAdV, respectively. Recovered SARS-CoV-2 was titrated by an immunofluorescence (IF) assay using a 1:2.5 serial dilution of Vero-E6 cells starting from 10 &#181;L. Vero-E6 cells were incubated for 72 hours at 37 &#176;C in a CO 2 incubator prior to the IF assay. Briefly, medium was washed out, cells were fixed using 4% paraformaldehyde (PFA), cell membranes were perforated with 0.2% Triton-X100, and SARS-CoV-2 was labeled with primary mouse anti-SARS-CoV-2 antibody. Secondary anti-mouse antibody was conjugated with a Cy3 fluorophore and a fluorescent microscope (Olympus IX 81, Germany) was used for signal detection. In the case of HAdV, serial dilutions of virus inoculum were used to infect A-549 cells and the cytopathic effect (CPE) was determined using Motic AE21 Inverted Phase Contrast Microscope (Zeiss, Germany). The titers of both recovered viruses infection particles were determined as TCID50 and calculated using the Spearman-K&#228;rber method <ns0:ref type='bibr' target='#b14'>(K&#228;rber 1931;</ns0:ref><ns0:ref type='bibr' target='#b26'>Spearman 1908</ns0:ref>). In addition, recovered HAdV genome copies were determined by real-time quantitative PCR (RQ PCR) as described previously <ns0:ref type='bibr' target='#b16'>(Lion et al. 2003</ns0:ref>) using the ABI Prism Fast 7500 Instrument (Thermo Fisher Scientific, MA, USA).</ns0:p></ns0:div> <ns0:div><ns0:head>Disinfection of PLA masks worn by test persons</ns0:head><ns0:p>To investigate the feasibility of disinfecting PLA protective masks in practical use, three volunteers wore the protective masks of the same type for 4 h. Thereafter, smears from one half of the inner (approximately 80 cm 2 ) or outer surface (approximately 83 cm 2 ) of each mask were performed using sterile cotton swabs. These samples served as a control for natural mask contamination by manual handling, direct skin contact and exhalation. Each cotton swab was transferred into 1 mL of 0.9% saline in a microtube, vortexed and inoculated onto a blood agar plate. Thereafter, the filters were removed from masks and the PLA skeletons of the masks were immersed in 96% ethanol for 15 min. After ethanol evaporation, cotton swab smears were taken from the second halves of the inner and outer mask surfaces, inoculated onto agar plates, and incubated at 37 &#176;C for 48 h. The results were averaged and expressed as CFU/mL.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Investigation of structure and porosity of 3D-printed PLA material</ns0:head><ns0:p>The structure and porosity of PLA masks produced by 3D printing were investigated by SEM. Scanning electron micrographs of gaps between the PLA filaments were captured at four different magnifications (Fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). The PLA filament size determined was 312.8 &#181;m ( Supplementary Fig. <ns0:ref type='figure'>4</ns0:ref>) and its surface appeared macroscopically very smooth (Fig. <ns0:ref type='figure' target='#fig_7'>2A</ns0:ref>). Further magnification showed only slight roughness of the surface and very small gaps between filaments (Fig. <ns0:ref type='figure' target='#fig_2'>2B, 2C</ns0:ref>). Additional increase of magnification revealed connecting filaments of PLA, resulting from the high temperature during 3D printing, with only very small pores (6.049 &#181;m in size) in between. The pores appeared to be completely closed deeper in the carrier, as observed at the highest magnification used (2000&#215;) (Fig. <ns0:ref type='figure' target='#fig_2'>2D</ns0:ref>). To further test whether the pores were indeed closed and prevented particles from passing through the printed mask, we determined the number of paraffin oil aerosol particles displaying a size of 0.1 -2 &#181;m using the aerosol generator and photometer, certified as a test system according to the common standards. Maximum pressure loss of the generated aerosol was detected, and absolutely no penetration occurred even though the PLA sample was printed with a diameter of 10 cm (corresponds approximately to the printed height of the masks) in the vertical position, simulated printing at a lower temperature in the upper layers (on the z-axis).</ns0:p></ns0:div> <ns0:div><ns0:head>Effect of ethanol, isopropanol and sodium hypochlorite on disinfection of PLA material contaminated with bacteria, yeast fungus or viruses</ns0:head><ns0:p>The results of disinfection of artificially contaminated PLA are summarized in Tables <ns0:ref type='table'>1 and 2</ns0:ref>. Although the untreated PLA carriers were contaminated by highly concentrated bacterial suspensions of 1&#215;10 5 CFU/mL, complete decontamination by all disinfectants used was achieved. Single colonies were observed in the samples of S. epidermidis and E. coli disinfected by isopropanol, but these isolated findings can reasonably be considered a contamination that occurred after treatment of the samples. The disinfection of PLA carriers contaminated with C. albicans (4&#215;10 4 CFU/mL) was complete in all cases. Titers of SARS-CoV-2 and HAdV recovered from disinfected or untreated carriers were determined by IF-and CPE-based assays, respectively. All disinfection agents tested showed complete virucidal effects against SARS-CoV-2. Disinfectants per se exhibited a cytotoxic effects on Vero-E6 cells (Supplementary Table <ns0:ref type='table'>1</ns0:ref>), but this effect was eliminated by serial dilutions during virus titer determination. HAdV infectivity was reduced by ethanol and isopropanol, and completely abolished by sodium hypochlorite. Similar trends were observed by RQ-PCR performed for detecting the HAdV genome copy numbers (Supplementary Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Investigation of PLA structure after exposure to ethanol, isopropanol and sodium hypochlorite</ns0:head><ns0:p>The effect of disinfectants on the PLA structure was investigated using SEM. PLA structure, gaps between filaments, and the structure of pores after five 15 min cycles of immersing the carrier in different disinfectants are shown in Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>. Treatment with ethanol (Fig. <ns0:ref type='figure' target='#fig_4'>3B</ns0:ref>) resulted in slight melting of the PLA filaments, as compared with untreated PLA (Fig. <ns0:ref type='figure' target='#fig_7'>3A</ns0:ref>). The overall PLA structure and surface did not change , but, interestingly, the gap size between the filaments was reduced from the original 6 &#181;m to approximately 850 nm (Fig. <ns0:ref type='figure' target='#fig_4'>3B</ns0:ref>). This indicates that ethanol treatment may improve the PLA mask properties with regard to structure density. Similarly, isopropanol treatment did not significantly affect the PLA structure (Fig. <ns0:ref type='figure' target='#fig_4'>3C</ns0:ref>). Only slight melting was detectable, resulting in decreased gap size to 3.3 -4 &#181;m, in comparison to 6 &#181;m in control samples. Moreover, the surface of filaments remained undamaged. Fig. <ns0:ref type='figure' target='#fig_4'>3D</ns0:ref> depicts the effect of sodium hypochlorite, which did not alter the surface of filaments, but precipitated disinfectant filled the gaps between them, while the gap size remained almost the same as in the control sample (5 -7 &#181;m). Long-term treatment of PLA by immersion in disinfectants for 24 hours was also investigated using SEM (Fig. <ns0:ref type='figure'>4</ns0:ref>). The effect of long-term treatment with ethanol (Fig. <ns0:ref type='figure'>4B</ns0:ref>) was similar to repeated exposure to sodium hypochlorite (Fig. <ns0:ref type='figure' target='#fig_4'>3D</ns0:ref>), i.e. the gaps between filaments were significantly enlarged to 23.84 &#181;m (Fig. <ns0:ref type='figure'>4B</ns0:ref>), possibly filled with etched polymer. Investigation of aerosol particle passage through the PLA material after 24 hours in ethanol confirmed that the enlarged gaps were sealed, as no penetration was detected. PLA melting was also observed after prolonged isopropanol treatment (Fig. <ns0:ref type='figure'>4C</ns0:ref>). The gaps between filaments were sealed with the polymer in an irregular manner, resulting in variable gap sizes ranging from 1.3 to 4.1 &#181;m. As in all previous tests with ethanol, the surface of PLA filaments remained unaffected. In contrast, long-term treatment with sodium hypochlorite damaged the surface of PLA filaments and revealed precipitation of the disinfectant on the surface (Fig. <ns0:ref type='figure'>4D</ns0:ref>). Similarly to short treatment with sodium hypochlorite, the gaps between filaments, ranging from 2 to 3.5 &#181;m, were completely filled with precipitated sodium hypochlorite (Fig. <ns0:ref type='figure' target='#fig_4'>3D</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Disinfection of PLA masks by ethanol upon wearing by test persons</ns0:head><ns0:p>To complement the results of disinfection upon artificial contamination (Tables. 1 and 2), disinfection of PLA masks after natural use was investigated. The disinfection efficiency with ethanol (96%) is summarized in Table <ns0:ref type='table'>3</ns0:ref>. The microbial load detected on the inner surface of untreated masks varied significantly between different users, ranging from hundreds to thousands CFU/mL. Despite this variation, an average of 7 CFU/mL remained detectable after immersing the masks in ethanol for 15 minutes (short rinsing with ethanol was not sufficiently effective;Supplementary Fig. <ns0:ref type='figure' target='#fig_5'>5</ns0:ref>). On the outer surface of untreated masks, 50-150 CFU/mL were detected, and an average of 2 CFU/mL remained detectable after disinfection (Fig. <ns0:ref type='figure' target='#fig_5'>5</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Visualization of PLA structure upon mechanical and chemical challenge</ns0:head><ns0:p>The impact on the PLA material by finger contact, abrasion by paper or metal and treatment by sodium chloride solution (mimicking perspiration) was analyzed using SEM (Fig. <ns0:ref type='figure' target='#fig_6'>6</ns0:ref>). Although fingers may be greasy or sweaty, the contact did not cause any marks or alterations on the PLA surface (Fig. <ns0:ref type='figure' target='#fig_7'>6A</ns0:ref>). Similarly, gentle mechanical abrasion with paper did not affect the material (Fig. <ns0:ref type='figure' target='#fig_6'>6B</ns0:ref>). By contrast, intensive mechanical scraping with a dining fork significantly damaged the PLA structure (Fig. <ns0:ref type='figure' target='#fig_6'>6C</ns0:ref>), leading to compression of PLA filaments, reduction of interfilament gaps, and shedding of PLA pieces (Fig. <ns0:ref type='figure' target='#fig_6'>6D</ns0:ref>). However, neither loosening of filaments, nor increase in gap size or other deformations were observed. Soaking in sodium chloride solution did not affect the structure, but salt crystals were present in the gaps between filaments (Fig. <ns0:ref type='figure' target='#fig_6'>6E</ns0:ref>). In addition, the effect of acetone, which is known to damage PLA, was evaluated. Virtually no gap was visible between filaments upon treatment, indicating that even short exposure to acetone smoothens the structure and seals the pores (Fig. <ns0:ref type='figure' target='#fig_6'>6F</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>The unexpected and sudden spread of SARS-CoV-2 infection, which resulted in the COVID-19 pandemic, has led to a desperate shortage of personal protective equipment, especially among the frontline workers. Because of this problem, many people started helping each other by manufacturing facial protection equipment from commonly available resources. An intriguing possibility is the production of protective face masks using FDM, the most widespread technique of 3D printing. A variety of polymers are suitable for FDM, including biodegradable PLA as the most affordable and environmentally friendly material because of its natural origin <ns0:ref type='bibr' target='#b20'>(Ngo et al. 2018)</ns0:ref>. Despite the potential benefits, the suitability of PLA-based materials for protection against viruses was questioned due to their possible high porosity. To the best of our knowledge, this report provides the first data addressing this issue by testing 3D-printed PLA masks (Fig. <ns0:ref type='figure'>1</ns0:ref>). The surface and other mechanical properties of products made from PLA or composite filaments were investigated previously <ns0:ref type='bibr' target='#b7'>(Graupner et al. 2009;</ns0:ref><ns0:ref type='bibr' target='#b10'>Chi et al. 2018;</ns0:ref><ns0:ref type='bibr' target='#b12'>Ivanov et al. 2019;</ns0:ref><ns0:ref type='bibr' target='#b32'>Wang et al. 2016)</ns0:ref>. However, the microstructure of 3D-printed PLA objects is highly dependent on the printing parameters, and it is not possible to predict the structure and porosity of a particular object based on published data. To investigate the surface properties of protective face masks made from PLA, examination of structure and porosity is required. We showed by SEM that 3Dprinted PLA masks have a compact structure, with small gaps between filaments. The gaps between individual filaments were 6 &#181;m wide, but higher magnification showed that the pores were not continuous within the PLA carrier (Fig. <ns0:ref type='figure' target='#fig_2'>2D</ns0:ref>) and were actually completely closed. This finding was supported by measurements of the filtering efficiency of PLA, which revealed completely blocked passage of nanometer-sized paraffin aerosol particles. The mask material can therefore be considered impermeable for particles displaying the size range tested, including the fungus, bacteria, and viruses investigated. In combination with the obligatory single-use filters complying with FFP2/3 standards, which are inserted into the mask, spreading of the smallest viruses can also be prevented. Moreover, short exposure to acetone resulted in smoothening of the PLA surface (Fig. <ns0:ref type='figure' target='#fig_6'>6F</ns0:ref>).</ns0:p><ns0:p>A similar 3D-printed reusable face mask prototype was reported by <ns0:ref type='bibr' target='#b28'>Swennen et al. (2020)</ns0:ref>. The material (polyamide composite) and the printing method used (selective laser sintering technique) differ from the approach presented, but it provided a proof of principle for 3D printing of individualized 3D face masks with FFP2/3 filter membranes as a feasible and valuable alternative source for protective equipment. However, the authors of the cited study did not perform any virus decontamination testing of the reusable components of the face masks and were hence unable to assess the impact of repeated cycles of disinfection on the properties of the material. It was important therefore to determine the possibility of disinfecting the reusable face mask matrix. While SARS-CoV-2, being an enveloped RNA virus, belongs to the less challenging pathogens in terms of disinfection, HAdV (non-enveloped DNA virus) is highly resistant to commonly used disinfectants <ns0:ref type='bibr' target='#b6'>(Gordon et al. 1993;</ns0:ref><ns0:ref type='bibr'>Lion et al. 2020)</ns0:ref>. Adenoviruses mostly cause infections with only mild symptoms in immunocompetent hosts <ns0:ref type='bibr' target='#b15'>(Lion 2019)</ns0:ref>, but due to their exceptional stability provide a perfect model for testing the inactivation efficiency. In addition, we examined the disinfection of PLA material from contamination with bacteria (S. epidermidis and E. coli) and yeast fungus (C. albicans). These microorganisms are part of the human microbiome and their persistence on the protective mask surface poses a risk for infection and a health threat to mask users <ns0:ref type='bibr' target='#b3'>(Fisher and Shaffer 2014)</ns0:ref>. All bacterial and fungal microorganisms studied were successfully disinfected using either 96% ethanol, 70% isopropanol or 0.85% sodium hypochlorite, after immersing contaminated PLA carriers in the respective disinfectant for 15 min (Table <ns0:ref type='table'>1</ns0:ref>). Ethanol disinfected the PLA masks contaminated from using by humans (Fig. <ns0:ref type='figure' target='#fig_5'>5</ns0:ref>). In comparison to bacteria or fungi, viruses tend to be 1-2 orders of magnitude smaller, making them prone to enter deep into pores of the PLA material. Nevertheless, our data show that efficient disinfection of the PLA carriers from virus contamination is possible, as all tested disinfectants completely inactivated SARS-CoV-2 (Table <ns0:ref type='table'>2</ns0:ref>). Treatment with sodium hypochlorite for 15 minutes also completely inactivated the highly resistant HAdV, while ethanol and propanol only led to reduced loads of infectious virus (Table <ns0:ref type='table'>2</ns0:ref>). These data are in agreement with the reported sensitivity of both SARS-CoV-2 <ns0:ref type='bibr' target='#b11'>(Chin et al. 2020;</ns0:ref><ns0:ref type='bibr' target='#b13'>Kampf et al. 2020)</ns0:ref> and HAdV to specific disinfectants <ns0:ref type='bibr' target='#b6'>(Gordon et al. 1993;</ns0:ref><ns0:ref type='bibr'>Lion et al. 2020)</ns0:ref>. The present findings therefore provide evidence that PLA material disinfection can be performed with comparable efficiency to other surfaces by appropriate exposure to individual disinfectants. The results obtained can conceivably also help design efficient disinfection protocols for protective face masks made from different materials. <ns0:ref type='bibr' target='#b4'>Fleischer et al. (2020)</ns0:ref> examined the changes of PLA material after cleaning with chemical disinfectants (Cidex Opa, Johnson &amp; Johnson and chlorine solutions), revealing mild alterations in the stiffness and strength of 3D-printed PLA samples. However, the authors concluded that high-quality 3D-printed surfaces generated with appropriate printer settings permit cleaning and reuse of 3D-printed medical tools, without compromising their mechanical properties. The authors also stated that immersion in cleaning agents can lead to their absorption into the PLA structure. Thus, additional research is needed to establish efficient and safe chemical cleaning of various 3D-printed surfaces, to prevent health risks associated with tactile and inhalation exposure to chemically cleaned materials. In general, we observed that 5 cycles of PLA treatment for 15 minutes with alcohol-based disinfectants resulted in decreased gap size between PLA filaments, without any remnants of disinfectant visible by SEM. By contrast, sodium hypochlorite precipitate was retained in the PLA structure, filling the gaps between PLA filaments. Disinfection of PLA masks with 0.85% sodium hypochlorite therefore requires further medical investigation to determine whether exposure to the precipitate might be associated with any health risks. Long-term (24-hour) treatment of PLA material with disinfectants resulted in partial melting of the filaments, but no erosions of the material were observed (Fig. <ns0:ref type='figure'>4</ns0:ref>). Ethanol seems to be best suited for the disinfection of PLA masks because it evaporates and does not require removal by rinsing. Moreover, the barrier properties of the mask were not compromised even after long-term exposure, as determined by aerosol challenge. Although the surface of protective equipment should remain intact, inadvertent contacts with the hands and fingers often occur, and the possibility of inappropriate handling has to be considered. The pandemic setting requires medical staff to wear extensive protective equipment (e.g. overalls, gloves, protective shields, and face masks). Such equipment, together with high workload and stress, increases the body temperature and leads to excessive sweating. We mimicked such conditions by mechanical and chemical treatment in order to evaluate alterations of the protective masks. Touching the surface of the PLA material with fingers had no impact, but intensive mechanical stress caused alteration of the PLA filament surface, without affecting the inter-filament gap area. Treatment with sodium chloride (imitating perspiration and sweat) showed salt crystallization in the gaps between filaments (Fig. <ns0:ref type='figure' target='#fig_6'>6E</ns0:ref>). Crystallized salt compounds, such as sodium chloride or sodium hypochlorite (Figs. <ns0:ref type='figure' target='#fig_7'>3D and 4D</ns0:ref>), can cause discomfort by skin irritation and itching. This issue was described in detail by <ns0:ref type='bibr' target='#b23'>Payne (2020)</ns0:ref> and <ns0:ref type='bibr' target='#b33'>Wollina (2020)</ns0:ref> who stated that especially front-line workers obliged to wear a single face mask all day suffer from these problems. The exploitation of PLA may solve this issue, because the fast and cheap manufacturing of protective masks made from this material permits production on a large scale, thereby facilitating more frequent mask changes. Additionally, 3D-printed protective PLA masks are biodegradable, with relatively short decomposition time, thereby providing an environmentally friendly solution.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>This study shows that PLA material is suitable for protection against various microorganisms as it is not permeable for submicroscopic particles. PLA can be efficiently disinfected from bacteria, yeast fungus, and SARS-CoV-2 by commonly available chemical disinfectants such as ethanol, isopropanol or sodium hypochlorite. However, contamination with HAdV, a highly resistant representative of non-enveloped viruses, could only be completely removed with sodium hypochlorite. PLA material is not altered by the immersion in disinfectant or by manual handling. Possible skin irritation after the use of certain disinfectants needs to be carefully evaluated. Single-use filters meeting the FFP2/3 standards are inserted into the mask structure and will be subject of further research and optimization. Overall, PLA can be recommended as suitable material for the manufacturing of protective face masks at times of epidemic spread of infections, such as the ongoing COVID-19 pandemic.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>Objects made from PLA filaments using 3D printing by the FDM technology. Manuscript to be reviewed Manuscript to be reviewed </ns0:p><ns0:note type='other'>Figure 4</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:05:49258:2:0:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>( A )</ns0:head><ns0:label>A</ns0:label><ns0:figDesc>PLA carriers (1&#215;1 cm). (B) Circular plate with a diameter of 10 cm (printed vertically). (C, D, E) Different types of PLA masks. PeerJ reviewing PDF | (2020:05:49258:2:0:NEW 24 Sep 2020)Manuscript to be reviewed</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>( A )</ns0:head><ns0:label>A</ns0:label><ns0:figDesc>Magnification 100&#215;, scale bar 500 &#181;m. (B) Magnification 500&#215;, scale bar 100 &#181;m. (C) Magnification 1000&#215;, scale bar 50 &#181;m. (D) Magnification 2000&#215;, scale bar 30 &#181;m. The observed gaps were measured and marked by black lines. SEM parameters: low vacuum, 5 kV, LVD detector, dwell time 5 &#181;s, spot size 4.5. Images were taken at various magnifications at the same position. PeerJ reviewing PDF | (2020:05:49258:2:0:NEW 24 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>( A )</ns0:head><ns0:label>A</ns0:label><ns0:figDesc>Sample touched by finger. (B) Slightly mechanically stressed sample (paper abrasion). (C) Extremely mechanically stressed sample (scratching by dining fork). (D) Detail of a pore in extremely mechanically stressed sample (dining fork). (E) Sample after immersion in saline solution (perspiration and sweat simulation). (F) Sample after short rinsing with acetone. SEM parameters: low vacuum, 5 kV, LVD detector, magnification 100&#215; or 500&#215;, dwell time 5 &#181;s, spot size 4.5, scale bar 500 or 100 &#181;m.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='19,42.52,326.62,525.00,377.25' type='bitmap' /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49258:2:0:NEW 24 Sep 2020)</ns0:note> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:05:49258:2:0:NEW 24 Sep 2020)Manuscript to be reviewed</ns0:note> </ns0:body> "

"Reviewer 1: Basic reporting The manuscript has been improved in comparison to its original version. The text has been revised, illustrations have been redesigned, and the Supplementary Material has been extended. Nevertheless, I still need to express the following concerns: I further recommended to describe supplementary materials in a single file and provide captions for each illustration. It did not happen. While having a single file would serve the reader's comfort (and, hence, it is optional), figure and table captions are compulsory in scientific writing. The argument that the supplementary materials are commented in the main text of the paper does not hold, since the illustrations included in the paper are also commented and they have a caption, too. For me, Supplementary Figs. 1 and 2 are clear, but I would need a figure caption and English annotations to fully understand Supplementary Fig. 3. The second argument, that supplementary information is unimportant ('not crucial for the confirmation of the claims given in our work and their understanding') is puzzling to me. Why is it supplied then? This problem does not really stem from our efforts to make our work easier, but rather from a misunderstanding of the reviewer's recommendation in the previous round of revisions. Since the title of figures and tables is mandatory for each submitted file (including supplementary files) when entering the publication into the content management system, it was included with each attached file from the first version. We considered these titles to be sufficient. Supplementary figure 1: Testing setup of aerosol generator and photometer Lorenz Meβgerätebau FMP 03 certified as a test system according to the standards EN 143 and EN 149. Supplementary figure 2: PLA sample with diameter 10 cm printed vertically and placed in standardized cartridge for the aerosol generator and photometer Lorenz Meβgerätebau FMP 03. Supplementary figure 3: Aerodynamic particle size distribution in the aerosol generator. However, we acknowledge that the title for Supplementary figure 3 was short and insufficiently descriptive, thus we have expanded it, added a legend and changed the axis labels directly in the image. I strongly recommend to provide captions for supplementary Figures and for the raw data listed in the following files: peerj-49258-Raw_data_adenovirus_contamination.docx peerj-49258-Raw_data_bacteria_and_yeast_fungus_contamination.docx peerj-49258-Raw_data_SARS_CoV-2_contamination.pdf Legends for supplementary figures and this raw data have been added. Also, please eliminate the brand name 'SAVO' from Supplementary Table 1 and from the following raw data files: peerj-49258-Raw_data_adenovirus_contamination.docx peerj-49258-Raw_data_bacteria_and_yeast_fungus_contamination.docx Thanks to the reviewer for noting our inattention. Of course, we fixed it. Experimental design The authors chose not to perform a statistically relevant SEM analysis of inter-filament gap sizes. They consider it too time-consuming. By suggesting it, I did not intend to slow down the publication of this work; I meant to strengthen its message by a thorough analysis of the results. The absence of such an analysis does not invalidate the paper, but it is important to mention, as a limitation of the work, that the SEM analysis merely illustrates the 3D printed PLA surface morphology, and gap width measurements are not analyzed statistically. Yes, we agree with the reviewer’s comment. Already in the previous version of the revision, we have tried to emphasize in the manuscript that this was only a visualization of PLA surface. We have now added another sentence about the lack of statistical analysis of the width of the gaps to the methodology, so perhaps it should already be fully acknowledged and unambiguous. Validity of the findings no comment Comments for the Author I'm sorry that my review is still critical! I tried to respond fast to expedite publication (provided that the other referees recommend it), but I think it is in the interest of all of us (readers and authors) not to leave behind incomplete or confusing text. We understand your comments and perhaps we have already processed them into a form suitable for publication. Reviewer: Stelian Arjoca Basic reporting no comment Experimental design no comment Validity of the findings no comment Comments for the Author The authors addressed previous comments well and modified the manuscript accordingly. For uniformity, the authors might also consider to change the commercial name 'SAVO' to '85% sodium hypochlorite' in the supplemental files and raw data provided. Again, congratulations to the authors for their work! Thanks to the reviewer for noting our inattention. Of course, we changed the commercial name SAVO in supplementary files. We also thank for the congratulations. We appreciate it. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Clinical trial registries can provide important information about relevant studies for a given condition to other researchers and the public. We developed a computerized informatics based approach to provide an overview and analysis of COVID-19 studies registered on ClinicalTrials.gov registry. Using the perspective of analyzing active or completed COVID-19 studies, we identified 401 interventional clinical trials, 287 observational studies and 64 registries. We analyzed features of each study type separately such as location, design, interventions and update history. Our results show that the United States had the most COVID-19 interventional trials, France had the most COVID-19 observational studies and France and the United States tied for the most COVID-19 registries on ClinicalTrials.gov. The majority of studies in all three study types had a single study site.</ns0:p><ns0:p>For update history 'Study Status' is the most updated information and we found that studies located in Canada (2.70 updates per study) and the United States (1.76 updates per study) update their studies more often than studies in any other country. Using normalization and mapping techniques, we identified Hydroxychloroquine (92 studies) as the most common drug intervention, while convalescent plasma (20 studies) is the most common biological intervention. The primary purpose of most interventional trials is for treatment with 298 studies (74.3%). For COVID-19 registries we found the most common proposed follow-up time is one year (15 studies). Of specific importance and interest is COVID-19 vaccine trials, of which 12 were identified. Our informatics based approach allows for constant monitoring and updating as well as multiple applications to other conditions and interests.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head n='1'>Introduction</ns0:head><ns0:p>The purpose of clinical trial registries, among others, is to inform the research community about currently ongoing studies. A registry can also be a sole source of study results for thousands of studies that would otherwise not publish a result article in a journal. <ns0:ref type='bibr'>(Zarin et al., 2019)</ns0:ref> For the current effort to address the COVID-19 epidemic, this function of registries is of great value. The fields of clinical informatics and clinical research informatics have an important role to play in fighting the epidemic. <ns0:ref type='bibr'>(Moore et al., 2020)</ns0:ref> We focus on a single registry, ClinicalTrials.gov <ns0:ref type='bibr'>(CTG)</ns0:ref>, and analyze COVID-19 registered studies. We chose to focus on CTG because it collects a rich set of metadata, supports record updates, <ns0:ref type='bibr'>(Fleminger &amp; Goldacre, 2018)</ns0:ref> allows for basic summary results deposition and studies in CTG make up a large volume of all studies tracked by the World Health Organization registry. <ns0:ref type='bibr'>(Huser &amp; Cimino, 2013)</ns0:ref> The goal of our study is to demonstrate how automated and clinical research informatics <ns0:ref type='bibr'>(Embi &amp; Payne, 2009)</ns0:ref> methods can be used to analyze a set of closely related studies, as well as to use general statistical principles to analyze and understand key metrics for studies on a given condition or in a specific clinical domain. The computer code written in R language is open source and available at the project repository.('regCOVID Project Repository,' 2020) Our project differs from past published analyses of COVID-19 clinical studies <ns0:ref type='bibr'>(Rosa &amp; Santos, 2020;</ns0:ref><ns0:ref type='bibr'>Fragkou et al., 2020;</ns0:ref><ns0:ref type='bibr'>Checcucci et al., 2020)</ns0:ref> by not using manual review of study records and instead relying fully on study metadata recorded in the registry. Unlike manual approaches, our approach of using automation to monitor COVID-19 studies allows for quick and efficient, continuous monitoring of the state of COVID-19 research. Automated queries can provide an instant overview of COVID-19 research. They also allow for computing and visualizing current COVID-19 research trends. Furthermore, the informatics approach we use improves the capability for effective modulation and allows individuals to specifically target the desired information wanted to inform their research decisions (such as on clinical guidelines, and the use of certain interventions). With the gradual publication of COVID-19 study results, this approach also allows for automated detection of registry deposition of basic summary results and the publication of a study result journal article that is clearly tied to a registered COVID-19 trial, study or registry.</ns0:p></ns0:div> <ns0:div><ns0:head n='2'>Materials &amp; Methods</ns0:head><ns0:p>Our study had two aspects. The first aspect was assuming a journalist perspective and the motivation was whether CTG registry can provide a useful overview of COVID-19 studies without any manual curation. We wanted to demonstrate on a COVID-19 use case whether existing study metadata currently collected by CTG registry are accurate and adequate for a journalist interested in a registry-based picture of COVID-19 research. The methods and results sections address mostly this first aspect.</ns0:p><ns0:p>The second aspect was assuming an informatics or data science perspective and the motivation for this was to apply additional rules, data transformations and heuristics to CTG metadata that could characterize the quality of the registry data and possibly narrow the list of all CTG studies to a smaller set. The critical component of this second informatics aspect was a vision to generalize the fully computerized single disease report to all diseases. The discussion section of this article addresses this second aspect.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.1'>Set of analyzed studies</ns0:head><ns0:p>We used the Aggregate Analysis of ClincalTrials.gov (AACT), which is a relational database version of CTG data that is created by parsing the XML (Extensible Markup Language) representation of each study. <ns0:ref type='bibr'>(AACT Team, 2020)</ns0:ref> It is published and maintained by Duke University. AACT data is typically four days behind CTG in terms of content or changes, which we deemed as acceptable. We performed separate analyses of COVID-19 studies based on their CTG study type of (1) interventional trials, (2) observational studies, and (3) registry-based studies (we use the term registries). <ns0:ref type='bibr'>(CTG Team, 2020a)</ns0:ref> We designed several inclusion criteria to focus only on COVID-19 studies in scope for our analysis. This consisted of first, creating a search strategy based on title or study keywords. We also looked at CTG study metadata to select studies with fields that we considered relevant based on the triggering of quality measures and the connection to the regulatory process.</ns0:p><ns0:p>In terms of keyword and title search strategy, we evaluated three search approaches. The first method involved a search for the presence of keywords in the official title of the study. The keywords used were, 'covid <ns0:ref type='bibr'>', 'sars-cov', '2019-ncov', and 'coronavirus'.</ns0:ref> The second method searched for the same keywords in the free text condition field. The third method found studies that had a Medical Subject Heading (MeSH) term for the study of 'coronavirus infections'. We limited our search for each method to only include studies first submitted after 27 December 2019 (the date of the official report from Wuhan hospital to the local center for disease control and prevention). For later analysis, we present data for the first search method (with results for all three methods being available on the study repository at https://github.com/lhncbc/r-snippetsbmi/tree/master/regCOVID). The data presented below reflects the search performed on 11 May 2020. The results of the search methods were validated as appropriate COVID-19 studies via the manual review of the titles of a subset of the search results.</ns0:p><ns0:p>In terms of study inclusion criteria based on structured CTG's study metadata fields we used study status. Study status reflects the progress of the study from 'not yet recruiting' to 'recruiting' to 'completed' (or other statuses such as 'terminated' or 'suspended'). <ns0:ref type='bibr'>(CTG Team, 2020a)</ns0:ref> We elected to limit the scope of our analysis to reflect currently ongoing or completed COVID-19 studies. Given this assumption, we excluded studies with 'not yet recruiting' study status. Under existing quality assurance rules used by CTG, studies in status 'not yet recruiting' do not have to provide the study location (in terms of country) and we considered study country to be essential study metadata. Given our chosen analytical perspective of currently ongoing or completed COVID-19 studies, we excluded studies with an unusual completion status of 'terminated', 'suspended', or 'withdrawn'. However, we provide some results for unusually completed COVID-19 studies because when combined with the 'Reason for termination' field, such studies may provide important insights.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Analysis</ns0:head><ns0:p>For all study types, we analyzed a set of study metadata described below. Study metadata specific to a given study type (e.g., those collected only for observational studies or registries) are described in subsequent sections.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2.1'>Number of studies over time</ns0:head><ns0:p>Using the date when the study was first registered on CTG, we counted the number of total studies for each study type on a given date. We created a plot showing the temporal trend over time.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2.2'>Study sites and country</ns0:head><ns0:p>Despite the existence of national registries, CTG registry contains studies from many countries. For example, as of 2 June 2020, 61% of recruiting studies were located solely outside the US (according to CTG's overview page('Trends, Charts, and Maps -ClinicalTrials.gov')). Additional incentive for registration on CTG are FDA rules that require studies submitted in support of new drug applications to FDA to be registered at CTG. Similar requirements of CTG registration also exist from many study funders such as NIH, and journals such as International Committee of Medical Journal Editors (ICMJE) member journals. We analyzed the geographic data for each study by reviewing the location fields in the CTG study record and counted the number of sites and identified the country of their locations. Each study could consequently include one or multiple countries.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2.3'>Study update activity</ns0:head><ns0:p>The clinical trial registry allows principal investigators to update the public about study completion, the final number of enrolled participants and basic summary results. High public interest in updates about COVID-19 studies was the main motivation for measuring update activity and study record recency.</ns0:p><ns0:p>We quantified the level of update activity for a study by looking at the number of updates and what fields are updated for a given study after its initial registration. We attempted to classify type of updates into technical updates (e.g., study sites changes) and updates of significant public interest (actual primary completion date or deposition of study results). We also evaluated the recency of the CTG study record by evaluating the number of days between the last update and the current date. Study update data is not available via AACT or the CTG Application Protocol Interface (API).(CTG Team, 2020b) However, information about study updates is available via the CTG website. To obtain this information we wrote an R script to scrape the data into a computable form.</ns0:p><ns0:p>We also evaluated the level of update activity for studies based in each country and found studies from which countries were more active in updating CTG study records.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2.4'>Study design</ns0:head><ns0:p>We analyzed CTG metadata pertaining to study design to classify studies. One feature analyzed for all study types was study enrollment (number of participants). CTG allows the reporting of estimated and actual enrollment into the trial. Study record managers can use this mechanism to publicly post updates about the number of enrolled participants.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Study type specific analysis</ns0:head></ns0:div> <ns0:div><ns0:head n='2.3.1'>Interventional trials</ns0:head></ns0:div> <ns0:div><ns0:head n='2.3.1.1'>Interventional trial specific features</ns0:head><ns0:p>We analyzed certain features which are specific to interventional trials alone. This includes phase, primary purpose, and number and type of arms.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.1.2'>Intervention type</ns0:head><ns0:p>For interventional trials specifically we analyzed the intervention types for the collection of COVID-19 studies. To do this we used CTG's metadata field of intervention type. CTG classifies each intervention as drug, device, biological, procedure, radiation, genetic, dietary supplement, behavioral, combination product, diagnostic test, and other. We counted the number of studies associated with each intervention type. Each study could include one or multiple intervention types. If multiple intervention types were included, we counted each study based on the combination of intervention types associated with the study. For example, NCT04334512, a 'Study of Quintuple Therapy to Treat COVID-19 Infection', included two interventions of type 'Drug' (Hydroxychloroquine and Azithromycin) and three interventions of type 'Dietary supplement' <ns0:ref type='bibr'>(Vitamin C, Vitamin D and Zinc)</ns0:ref>. This study was counted exactly once under a composite intervention type that consisted of the alphabetically sorted combination of two types: 'dietary supplement | drug', with the '|' representing the term 'and'.</ns0:p><ns0:p>Our analysis of intervention types and names revealed that placebo as an intervention name is often used and captured under type 'Drug' or 'Biological'. CTG type classification does not include placebo as a separate intervention type, however, we decided to experimentally create it and assign it based on a rule that looked for the term placebo in the intervention name.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.1.3'>Interventions</ns0:head><ns0:p>Researchers and the public are most interested to see which drugs (or other interventions) are being tested in relation to COVID-19. CTG allows study record administrators to specify intervention using free text and further assign interventions to study arms. Because of the vital importance of interventions and the correct counting of studies using the same intervention, we did implement a limited computerized method of processing free text interventions to achieve some semantic harmonization. After free text string transformations into harmonized intervention terms, we counted the number of studies that included a given intervention. We also evaluated the temporal change in the amount of studies for the most common interventions by showing the number of new studies on a weekly scale (as seen in a figure in the Results section).</ns0:p><ns0:p>From prior studies, there is an obvious need to harmonize semantically different interventions expressed as free text across different studies. <ns0:ref type='bibr'>(Cepeda, Lobanov &amp; Berlin, 2013)</ns0:ref> For example, the intervention term 'ruxolitinib' can semantically harmonize entries of 'Ruxolitinib Oral Tablet' (in study NCT04334044), 'Ruxolitinib 10 MG' (NCT04338958) and 'Ruxolitinib' (NCT04331665). Initial normalization involved the removal of extra white space and the conversion of each term to lower case. Representing drug dose form was out of scope so further normalization removed commonly occurring dose form terms, such as, 'tablet', 'injection', and 'pill'.</ns0:p><ns0:p>Studies with multiple interventions were counted multiple times under each individual intervention. In some cases, the free text string for a single intervention (in the CTG data entry field) specified a combination of several interventions. Our transformation approach in such cases kept the combination as well as expanded the single entry into multiple separate interventions and counted each intervention separately. For example, NCT04334928 has an intervention that includes a combination of Emtricitabine and Tenofovir Disoproxil. In this case the study is counted once for Emtricitabine, once for Tenofovir, and once for the combination of Emtricitabine and Tenofovir. In some cases, the manual mapping reduced the term granularity and used a higher-level term.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.1.4'>COVID-19 vaccine trials</ns0:head><ns0:p>A segment of COVID-19 interventional trials with high importance and significant public interest are vaccine trials. CTG maintains a hierarchy of intervention types but vaccine as an intervention does not have a designated intervention type and is subsumed under the intervention type 'Biological'. Because there is no special vaccine intervention type, our method for finding vaccine trials was based on a string search for the term 'vaccine' in the official title of the study. Once we created a COVID-19 vaccine trials subset, we applied on this set the same series of analyses and metrics mentioned above.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.2'>Observational studies and registries</ns0:head><ns0:p>Observational studies and registries have metadata features that are not recorded for interventional trials. Such analyzed features were: time perspective and observational model for the set of observational studies and registries. In addition, one feature recorded and analyzed for only registries was follow up time.</ns0:p></ns0:div> <ns0:div><ns0:head n='3'>Results</ns0:head><ns0:p>We developed a methodology to search and extract metadata on COVID-19 clinical studies. The database is a subset of the AACT database of ClinicalTrials.gov data. The database and result files can be found in our github repository at https://github.com/lhncbc/r-snippetsbmi/tree/master/regCOVID. The repository includes the R code to obtain and analyze the data and all comma separated value (CSV) data files used during the analysis. It also includes additional result data files not included in this paper but described in the repository documentation. The repository also includes a list of descriptions for each data file for easy use. For example, the files, regCovid_all_studies-a.csv, regCovid_int-a.csv, regCovid_obs-a.csv, and regCovid_registry-a.csv are the lists of all studies, interventional trials, observational studies, and registries generated from search method A respectively. These files include all 64 columns from the AACT studies table, such as NCT ID, official title, start date, primary completion data, and enrollment. The description file has more than 80 entries and provides guidance and descriptions for each included file in the analysis. Also included in the repository is an example of part of the code used in the analysis and a quick-start tutorial for users to easily access and use our code and data files.</ns0:p><ns0:p>While this paper includes results from the main analysis done on 11 May 2020, the repository report is updated weekly and offers up to date results.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.1'>Set of analyzed studies</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1.1'>Search strategy</ns0:head><ns0:p>We found that the first search method, using the official title of the study, was the most comprehensive and included the most COVID-19 studies. The numbers listed below reflect only the search strategy and not applying the criteria based on study status. As of 11 May 2020, the first search method returned a total of 1302 studies. The second search method, based on the free text condition field, found fewer records (1165 studies). The third method based on the MeSH term, returned 328 studies. The significant difference in the studies captured in the third search strategy is likely due to the fact, that there is no specific MeSH term for COVID-19 at this point and the MeSH condition field is not required and is left blank for many studies (38.2% of studies captured in the first search method left MeSH condition term blank).</ns0:p><ns0:p>We then applied metadata inclusion criteria (studies that are active, recruiting or completed and are not expanded access). This reduced the set for the first search method to 752 studies, the set from the second search method to 680 studies, and the set from the third search method to 210 studies.</ns0:p><ns0:p>This led us to select the set of COVID-19 studies generated from the first, most comprehensive search method, based on study title.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.1.2'>Final study set</ns0:head><ns0:p>In terms of completion and presence of results, 48 studies in the final set were completed at the time of this analysis. None have provided summary results to this point. It is important to note that studies are typically required to submit results within one year after the primary completion date.('FDAAA 801 and the Final Rule -ClinicalTrials.gov') Also, at the time of the analysis, 106 studies have past their primary completion date (12 studies when using primary completion day + 30 days) declared in the latest study record and have a status that indicates the study is still ongoing. This indicates that the record is possibly not kept current. Administrators do typically have 30 days after a status change to update the record (see 42 Code of Federal Regulation [CFR] 11.64(a)(1)(ii)).('Frequently Asked Questions -ClinicalTrials.gov') In an extreme case, 20 studies of those 106 studies have a status of 'not yet recruiting' and are past their primary completion date.</ns0:p><ns0:p>To understand how our metadata study inclusion criteria affects the final set, we briefly analyzed the set of studies excluded due to our study metadata criteria. The studies removed due to metadata included 516 studies that were not yet recruiting, 10 that were withdrawn, 5 that were suspended and 2 that were terminated. The reasons for termination of the 2 studies were 'We cannot meet number of subjects as recently published similar studies' for NCT04357535 and 'The epidemic of COVID-19 has been controlled well in China, no eligible patients can be enrolled at present' for NCT04257656. The interventions of the terminated studies were ACE-I (angiotensin-converting enzyme inhibitors) and ARB (angiotensin receptor blocker) for the former and Remdesivir for the latter. Our study type criteria also excluded 17 studies with a study type of 'Expanded access'.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>Studies over time</ns0:head><ns0:p>Figure <ns0:ref type='figure' target='#fig_0'>1</ns0:ref> shows the number of registered studies over time by study type. Interventional trials are most numerous. An important regulatory consideration is that, in the US, applicable interventional clinical trials are required to register, 13 while registration of observational studies and registries is optional. When considering the submission date, the first interventional trial, and the first study overall, was submitted to CTG on 23 January 2020, while the first observational study was submitted on 26 January 2020 and the first registry was not submitted until 12 March 2020. </ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>Analysis by study type</ns0:head></ns0:div> <ns0:div><ns0:head n='3.3.1'>Interventional trials</ns0:head><ns0:p>We identified a total of 401 COVID-19 interventional trials from CTG. These 401 studies included a total of 1666 interventions.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.1'>Study sites and country</ns0:head><ns0:p>The majority of interventional trials had just one study site (259 studies, 64.6%%). 41 studies had two sites and 18 studies had three sites, the second and third highest study counts. As for country of operation, Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref> shows the count of interventional trials by the country or countries that have at least one site that is part of the study.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 1.</ns0:head><ns0:p>The vast majority of studies 385 (96.0%) only included sites in a single country. Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref> results indicate that the most common country for interventional trials was the United States with 121 studies (30.2%) followed by China with 49 studies (12.2%).</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.2'>Update activity</ns0:head><ns0:p>We evaluated the amount of interventional trials that had updates after the study was first submitted to CTG (full update data are available in a report and as Comma Separated Value [CSV] files in the study github repository).('regCOVID,' 2020) At the time of the analysis, 71.1% (285 studies) of the 401 interventional trials show the presence of at least one update since first being submitted to CTG. The study with the most updates was NCT04280705, 'Adaptive COVID-19 Treatment Trial (ACTT)' with 18 updates. The most common public interest and overall feature updated for COVID-19 interventional trials was 'Study Status', which was updated 643 times including at least once by each of the 285 studies that had at least one update. Other commonly updated public interest fields include 'Recruitment Status' (212 updates from 199 studies) and 'Outcome Measures' (137 updates from 108 studies).The second most commonly updated field overall, and most common technical field, was 'Contacts/Locations', which was updated 393 times by 223 studies. Using 11 May 2020 as the current date, we also looked at the amount of days since last update to evaluate how current the existing CTG record is and found that the average amount of days since the last update is 20.6 days for all COVID-19 interventional trials.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_2'>2</ns0:ref> shows the amount of updates by studies in each country and the ratio of the number of updates compared to the number of studies in a given country. The table is limited to countries with at least eight studies. The country with the highest update rate is Canada with 2.70 updates per study, followed by the United States with 1.76 updates per study.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_2'>2</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.3'>Study design and interventional trial specific features</ns0:head><ns0:p>Study phase and size: Considering study phase and study size (or enrollment; number of participants), Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref> shows the counts of studies and percentage by study phase, as well as study size indicators: 1 st quartile, median, and 3 rd quartile for the participants enrolled (either actual or anticipated) for the set of studies of each phase.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_4'>3</ns0:ref> shows that the phase with the most studies is N/A with 111 studies (27.7%), which represents studies of intervention type device or behavioral. The second most common phase is Phase 2 with 108 studies (26.9%). Unsurprisingly the phase with the highest enrollment is Phase 3 with a median of 500 participants, while the lowest enrollment is Early Phase 1 with a median enrollment of 10 participants.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 3.</ns0:head><ns0:p>Arms: Considering number of study arms, most interventional trials have two arms (245 studies, 61.1%), while 73 studies (18.2%) have just one arm.</ns0:p><ns0:p>Primary Purpose: Considering study primary purpose, Table <ns0:ref type='table'>4</ns0:ref> presents the breakdown into 8 purpose categories. In 298 (74.3%) of the analyzed COVID-19 interventional trials, the primary purpose was treatment. For 41 (10.2%) the primary purpose was prevention.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 4.</ns0:head><ns0:p>Arm Type: CTG allows study managers to specify the type of each study arm. Each study arm is named and is classified as a specified arm type. Each study could have one or multiple arms of the same type. For example, NCT04321993, 'Treatment of Moderate to Severe Coronavirus Disease in Hospitalized Patients', has three arms of type 'Experimental' and one arm of type 'No Intervention'. One arm in this study has patients receiving an intervention of Lopinavir/Ritonavir, the second has patients receiving an intervention of Hydroxychloroquine, and the third has patients receiving an intervention of Barictinib. This study also has a fourth arm of patients receiving no intervention.</ns0:p><ns0:p>Considering types of all COVID-19 interventional trials, we found that the most common arm type is 'Experimental', which appears 489 times. Table <ns0:ref type='table'>5</ns0:ref> shows the complete data for arm type in the set of 401 interventional trials.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 5.</ns0:head><ns0:p>Different diseases at different maturity of clinical research may be employing a different design, such as the inclusion of a placebo or active comparator. We calculated the placebo index, which is the percentage of interventional trials that have a placebo or sham comparator arm. Each study can have one or multiple arms that are assigned a placebo comparator. For our set of COVID-19 studies, the placebo index was 28.7% (115 of 401 total trials). We also calculated the active comparator index, which is the percentage of trials with at least one active comparator arm, and found that 28.9% (116 trials) have at least one active comparator arm.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.4'>Intervention type</ns0:head><ns0:p>Table <ns0:ref type='table' target='#tab_6'>6</ns0:ref> shows the count of studies by intervention type. Intervention type 'Drug' is the most common (137 studies [34.2%]). The combination of drug and placebo intervention type was the second most prevalent with 75 studies (18.7%). Biological was the next most prevalent type with 32 studies (8.0%). Based on our methodology for classifying intervention types, each study can be counted only under one composite intervention type. Table <ns0:ref type='table' target='#tab_6'>6</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.5'>Interventions</ns0:head><ns0:p>There were a total of 449 distinct interventions listed prior to the implementation of our normalization and mapping process. Once the interventions were mapped the amount of normalized interventions was reduced to 403. The full mapping is available at the study repository (file: intervention_map2.xlsx).('regCOVID Project Repository,' 2020) Table <ns0:ref type='table'>7</ns0:ref> shows the most common interventions used in COVID-19 interventional trials. Given our counting methodology for interventions, each study can be counted multiple times in Table <ns0:ref type='table'>7</ns0:ref> because combined interventions are expanded into their components as well as kept as a combination. The most common drug intervention was Hydroxychloroquine with 92 studies, followed by Azithromycin with 24 studies. The two (Hydroxychloroquine and azithromycin) appeared together four times. The most common combination intervention was Lopinavir/Ritonavir with 16 studies. We also found the presence of interventions most likely listed as a comparator or a non-intervention group, rather than a specific intervention. This is seen as 99 studies have placebo listed as an intervention while another 40 studies have standard care listed.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 7.</ns0:head><ns0:p>As for non-drug interventions, the most common biological is convalescent plasma with 20 studies. Other leading interventions for different types (not shown in Table <ns0:ref type='table'>7</ns0:ref>) include oxygen supplying equipment for device with six studies and Vitamin C for dietary supplements with four studies. We also found that the same intervention can be listed as different intervention types. For example, convalescent plasma was listed for 14 studies as the intervention type biological, three times as other and 3 times as drug. We combined each intervention to count as the most commonly used intervention type when counting the intervention. For this case of convalescent plasma, that would count as 20 studies and categorize convalescent plasma as having the type biological.</ns0:p></ns0:div> <ns0:div><ns0:head>Interventions over time:</ns0:head><ns0:p>We also evaluated the temporal change for the most common interventions by analyzing the amount of new studies weekly for the most common interventions as seen in Figure <ns0:ref type='figure' target='#fig_1'>2</ns0:ref>. </ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.6'>COVID-19 vaccine interventional trials</ns0:head><ns0:p>Our search method for vaccine trial intervention type studies identified 12 COVID-19 vaccine trials, that also met our inclusion criteria of being active, recruiting or completed. Due to their high significance and increased public interest, it is interesting to consider how frequently such trials are updated. A total of 9 trials (75.0% of the 12 vaccine trials) have at least one update and the median amount of updates is two. Considering the study country, six different countries have at least one vaccine trial, with China (5 vaccine trials) having the most, followed by the US with 3 trials. Five of the trials were Phase 1, six were Phase 1/Phase 2 and one was Phase 2. Of note is the fact that Phase 1 trials are not 'applicable clinical trials' (as defined in US regulations) and such trials have no mandatory registration.('FDAAA 801 and the Final Rule -ClinicalTrials.gov') Exactly half of vaccine interventional trials (6 trials) had more than one site. As for design, the average number of arms was 5.4 with a median overall trial enrollment of 119.5 participants. The 12 vaccine interventional trials also included 52 experimental arms and seven placebo comparator arms. The full overview of all metadata parameters for vaccine trials (as well as for observational studies and registries described in subsequent sections) is available at the study repository.('regCOVID,' 2020)</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.2'>Observational studies</ns0:head><ns0:p>We found a total of 287 observational studies. Similarly, to interventional trials, the vast majority of observational studies had just one site (238 studies, 82.9%). The country with the most observational studies was France with 75 (26.1%), followed by the United States with 47 (16.4%). Observational studies are updated less frequently than interventional trials as only 52.6% (151 studies) of the COVID-19 observational studies have been updated since first being submitted to CTG (compared to the 71.1% of interventional trials that have been updated at least once). The observational study with the most updates was NCT04334954 'SARS-COV2 Pandemic Serosurvey and Blood Sampling' with 25 updates since registration on 6 April 2020. The most commonly updated public interest feature for observational studies was the 'Study Status' which was updated 270 times by 151 studies and the most common technical feature updated was 'Contacts/Locations' with 99 updates from 83 studies.</ns0:p><ns0:p>The median enrollment for observational studies was 353 participants. One feature of observational study design is the time perspective. A majority of the observational studies analyzed were prospective (180 studies, 62.7%), as opposed to 58 studies (20.2%) which were retrospective. For observational model, 167 of the observational studies (58.2%) use a cohort model. The second most commonly used model for the analyzed observational studies was case (45 studies, 15.7%).</ns0:p><ns0:p>Contrary to our expectation, we found observational studies that included interventions in their CTG record. Of the 287 observational studies, 179 (62.4%) listed something in the free-text intervention field. However, this number is misleading as in many cases the listed intervention was something that stated that there was no intervention (such as 'no intervention', 'observation <ns0:ref type='bibr'>', 'non-interventional', etc.)</ns0:ref>. Of the listed interventions most are listed as intervention type 'Other' (86 studies, 30.0%) or 'Diagnostic Test' (34, 11.9%).</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.3'>Registries</ns0:head><ns0:p>We analyzed a total of 64 COVID-19 registries (shorter term for registry-based studies). Of these registries 52 (81.3%) were limited to one site. The largest number of sites was 53. The countries with the most COVID-19 registries were France and the United States with 9 studies each. Similar to observational studies, just over half of the analyzed registries, 51.6% (33 registries), have been updated at least once since their first registration. Also similar to observational studies, the most common public interest update for registries is to the study status, which has been updated 56 times by all 33 registries with an update, and the most common technical update is to the contacts and locations with 28 updates from 18 studies.</ns0:p><ns0:p>The median enrollment for the set of registries was 388 participants. Registries have many specific design features that differentiate them from other study types. One is the presence of a targeted follow-up time. The most common follow-up time for the analyzed registries was one year for 15 studies (23.4%), which was listed as either '1 year' or '12 months' and was combined to get the accurate value. The shortest follow-up time was one day for NCT04331171, 'Epidemiological Observation From a Smartphone Self-monitoring Application for Suspected COVID-19 Patients' Triage', while the longest targeted follow-up duration for a registry was 20 years, for NCT04359602, 'COVID-19 Recovered Volunteer Research Participant Pool Registry'. For registries, CTG collects their observational model (similar to observational studies). The majority of registries, 48 (75.0%), use a cohort model. Also similar to observational studies, registries can include a time perspective. However, unlike observational studies, no registries are retrospective. Instead the time perspective is usually either prospective (50 studies, 78.1%), or cross-sectional (6 studies, 9.4%). A cross-sectional perspective means that the observation or intervention is made at a single point in time rather than on a continuous or recurring basis. <ns0:ref type='bibr'>(CTG Team, 2020a)</ns0:ref> Like observational studies, more than half (53.1%, 34 of 64 registries) included an intervention in the free text field. These interventions also include many that are not representative of an actual intervention and rather state the absence of an intervention just like with the previously mentioned observational studies. This is also shown in the intervention type as 19 of the 34 registries (55.9%) have an intervention type of 'other'.</ns0:p></ns0:div> <ns0:div><ns0:head n='4'>Discussion</ns0:head><ns0:p>Based on our two perspectives, we discuss separately COVID-19 studies results (journalist perspective) and data science implications (informatics perspective).</ns0:p></ns0:div> <ns0:div><ns0:head n='4.1'>COVID-19 studies</ns0:head><ns0:p>Our study developed a computerized approach of retrieving COVID-19 studies from CTG registry for analysis. CTG's study metadata facilitates the useful classification of studies into many relevant subgroups (e.g., by study design, size, phase, recruitment status or intervention). Availability of this data in a structured form (either via CTG's API or via structured XML or relational data files) provides analytical views that would be difficult or impossible to achieve without a registry. As of 11 May 2020 ( the date of primary analysis), no study had deposited basic summary results.</ns0:p><ns0:p>The results presented above were summarized as of 11 May 2020. Refreshed and more current data (released weekly) can be obtained at the project repository. ('regCOVID Project Repository,' 2020; 'regCOVID,' 2020). Weekly updated reports allow researchers, journalists or the general public to quickly obtain a snapshot of the ongoing COVID-19 research. For example, a weekly report intervention section (similar to Table <ns0:ref type='table'>7</ns0:ref>) can reveal to many research teams concentrated on COVID-19 what interventions are being studied with what intensity. This analytical view would require tens of manual queries using the generic CTG web interface.</ns0:p></ns0:div> <ns0:div><ns0:head n='4.1.1'>Study limitations</ns0:head><ns0:p>Our study has several limitations. First, we only used CTG registry to look for COVID-19 studies. Within this registry, we evaluated three search strategies, but some relevant COVID-19 studies may possibly be missed. Without a benchmark gold standard of all COVID-19 studies, the recall of our search strategy cannot be evaluated. It was out of scope of this study to establish the precision of our search. Second, our semantic harmonization of interventions is based on manual mapping by a single expert. Third, there are significant limitations of the informaticsbased approach compared to manual review. </ns0:p></ns0:div> <ns0:div><ns0:head n='4.1.2'>Related studies</ns0:head></ns0:div> <ns0:div><ns0:head n='4.2'>Data science perspective</ns0:head><ns0:p>During the creation of a fully computerized, disease-focused report about ongoing or completed clinical studies, we observed several informatics themes described below. Before we describe individual lessons learned, we want to re-emphasize how computable representation of clinical study metadata is a crucial enabler for creating disease-based research snapshots. Moreover, several features of ClinicalTrials.gov registry proved to be highly valuable for our project. Such features are: structured representation of study metadata (XML and relational database format), registry support for result deposition and record updates, and legal and funding source policy requirements to maintain accurate registry records. In our analysis, we were able to build on prior clinical informatics research projects. Our project also shows value in further developing clinical informatics methods for data and metadata representation, semantic harmonization through terminologies and standards. The following informatics lessons were learned:</ns0:p><ns0:p>Updates: Our study is the first to analyze the frequency of updates to a study in CTG. We believe that adding the ability to access study updates to the CTG's API would be a useful addition. Our results indicate that analyzing study update activity is helpful in distinguishing studies with possibly outdated metadata (e.g., studies in status 'not yet recruiting' but are past their anticipated completion date with some grace period allowed for record updating). Our study is also the first to analyze update activity by country of study.</ns0:p><ns0:p>Intervention (free text): CTG collects intervention as free text and for some studies, provides a corresponding concept in Medical Subject Headings (MeSH) terminology. This intervention harmonization as MeSH concept is done post hoc rather than during study metadata entry by the study record manager. We found that the MeSH intervention concept is present in less than half (47%) of COVID-19 analyzed studies. This analysis prompted us to develop the denormalization and mapping method that we used.</ns0:p><ns0:p>Another intervention-related observation is the difference in how intervention combinations are listed in the free text field. In some cases, the combination intervention (e.g., 2 drugs given to some study group in combination) is recorded as two separate entries and the group or arm freetext description provides a way to clarify the combined usage. In other case the same intervention combination is recorded together as a single entry. This dual way of recording combined interventions formed our methodology for the most comprehensive approach of counting interventions (count them as both combinations and as separate interventions). We did not analyze arm description and so we did not combine separated interventions, which may have been assigned to the same arm and used in combination. This may possibly lead to the undercounting of certain intervention combinations.</ns0:p><ns0:p>Registries: We find valuable that CTG currently allows registration of observational studies and registries. Designing a user interface for registration and study representation format that can accommodate various designs and studies is a challenging task. Due to specific characteristics of certain study types, further customization of user interface or additional data quality checks may further improve the registry value to many stakeholders. For example, registries do not typically post one-time study results and may not have the same concept of primary completion date. Instead, annual or other regular interval updates about number of participants and summary results for participant flow may be more applicable. Clarifications in the user interface for entering interventions for registries (and for observational studies) may prevent entries which declare a formally drug typed intervention with the title 'no intervention'.</ns0:p></ns0:div> <ns0:div><ns0:head n='4.2.1'>Generalizing report to other diseases</ns0:head><ns0:p>Our emphasis on fully computerized analysis of a COVID-19 set of studies was motivated by our larger vision to apply the R scripted report for all MeSH encoded diseases found within the CTG registry. We refer to this result as the regCTG project and report repository. regCTG allows analysis of research by MeSH keyword for all clinical domains. We generated reports for all MeSH terms with at least 100 registered studies. A collection of nearly 1000 disease-based reports is available at https://github.com/lhncbc/CRI/tree/master/regCTG. We consider this generalization from a COVID-19 research report to a research report for nearly 1000 diseases an important result of our project.</ns0:p><ns0:p>In another follow-up research project for this COVID-19 case study, we have also built a disease-intervention snapshot knowledge base (called D-SHOT) that lists all interventions appearing in interventional trials for a given condition.('Project Repository for Disease Snapshot') This knowledge base of disease-intervention pairs has many parameters for each intervention, such as date when first introduced, count of regularly completed studies or count of unusually completed studies ('terminated', 'suspended', or 'withdrawn') studying that intervention. Experience from semantic harmonization of CTG's free text field into terminology concepts gained during this COVID-19 project was crucial in these two follow-up projects by our team. A related, non-open source project called Sherlock, proprietary to Johnson and Johnson is similarly parsing CTG's terms into formal concepts. <ns0:ref type='bibr'>(Cepeda, Lobanov &amp; Berlin, 2013)</ns0:ref> </ns0:p></ns0:div> <ns0:div><ns0:head n='4.3'>Weekly results updates</ns0:head><ns0:p>While, the main analysis presented above was done on 11 May 2020 (main analysis date), thanks to the computed nature of the analysis, we have been producing weekly updated reports (available at the github repository). We have also been improving and adding to the automated report since the main analysis date based on the deposition of the first study results and the appearance of study results publications. As of the main analysis date, there were zero studies with results deposited on CTG. Because of data evolution during the article review and revision preparation, the latest weekly report on our github repository (as of 13 August 2020; update analysis date) now snows 3 interventional trials and one registry with results posted. Analysis of linked PubMed publications for completed interventional trials, found that of the 83 completed interventional trials at the point of secondary analysis, 9 had linked pubmed publications (10.8%).</ns0:p><ns0:p>For the weekly reports and data in our github repository, we welcome change requests submitted by interested researchers. For researchers re-using our code and interested in making modifications, a free registration to access the AACT database is required (obtainable within hours).</ns0:p></ns0:div> <ns0:div><ns0:head n='5'>Conclusion</ns0:head><ns0:p>We developed a computerized, data science driven approach to monitoring COVID-19 interventional trials, observational studies and registries. We report on several metrics for the 401 interventional trials, 287 observational studies and 64 registries as of our analysis date on 11 May 2020. More current and weekly refreshed data is available at our github repository. We also demonstrated that our COVID-19 disease focused report can be generalized to all diseases represented within a clinical trial registry. Manuscript to be reviewed Manuscript to be reviewed Overview of studies by study phase and number of participants (study size)</ns0:p></ns0:div> <ns0:div><ns0:head n='6'>Acknowledgement</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:06:50119:1:1:NEW 20 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. COVID-19 studies over time by study type.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. Plot of new studies weekly for selected frequent COVID-19 interventions over time</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>For example, COVID-19 Evidence Service from Centre for Evidence-Based Medicine at University of Oxford offers more comprehensive reviews. It was out of scope of our project to offer results comparable to human review. Fragkou et al. used a search and manual review methodology to compile and analyze a set of COVID-19 interventional trials and their interventions.(Fragkou et al., 2020) Checcucci et al. did a literature and clinical trial registries search based on built-in search criteria to review COVID-19 vaccine trials.(Checcucci et al., 2020) Rosa et al. did a manual search of CTG to analyze COVID-19 trials using repurposed interventions. Considering the existing published studies, we conclude that our study is the first study to rely solely on computerized data science methods to compile and analyze a set of COVID-19 interventional trials, observational studies and registries(Rosa &amp; Santos, 2020). Our approach of using computerized data science methods allows for the continuous monitoring of the current state of COVID-19 research with minimal additional effort compared to a resource intensive manual review methodology. During a continuously changing public health emergency, this ability for any researcher to quickly and efficiently monitor changes and trends in clinical research is invaluable in informing the direction of their research efforts.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='21,42.52,178.87,525.00,405.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='22,42.52,178.87,525.00,405.00' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head /><ns0:label /><ns0:figDesc>The study with the most sites was NCT04292730 ('Study to Evaluate the Safety and Antiviral Activity of Remdesivir in Participants With Moderate Coronavirus Disease (COVID-19) Compared to Standard of Care Treatment') with 183 sites.</ns0:figDesc><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>List of countries where COVID-19 interventional trials are conducted.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Country</ns0:cell><ns0:cell cols='2'>Study Count Percentage</ns0:cell></ns0:row><ns0:row><ns0:cell>United States</ns0:cell><ns0:cell>121</ns0:cell><ns0:cell>30.2%</ns0:cell></ns0:row><ns0:row><ns0:cell>China</ns0:cell><ns0:cell>49</ns0:cell><ns0:cell>12.2%</ns0:cell></ns0:row><ns0:row><ns0:cell>France</ns0:cell><ns0:cell>42</ns0:cell><ns0:cell>10.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Spain</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>5.7%</ns0:cell></ns0:row><ns0:row><ns0:cell>Italy</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>4.7%</ns0:cell></ns0:row><ns0:row><ns0:cell>Brazil</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Canada</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Iran, Islamic Republic of</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Germany</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>2.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>Mexico</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>2.00%</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:06:50119:1:1:NEW 20 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Number of updates per study by country (for countries with at least 8 COVID-19 interventional trials)</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:06:50119:1:1:NEW 20 Aug 2020)Manuscript to be reviewed 1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Number of updates per study by country (for countries with at least 8 COVID-19 2 interventional trials) Country Total Updates Study Count Changes Per Study</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Canada</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.70</ns0:cell></ns0:row><ns0:row><ns0:cell>United States</ns0:cell><ns0:cell>213</ns0:cell><ns0:cell>121</ns0:cell><ns0:cell>1.76</ns0:cell></ns0:row><ns0:row><ns0:cell>Germany</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>1.75</ns0:cell></ns0:row><ns0:row><ns0:cell>Brazil</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>1.70</ns0:cell></ns0:row><ns0:row><ns0:cell>Spain</ns0:cell><ns0:cell>38</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>1.65</ns0:cell></ns0:row><ns0:row><ns0:cell>China</ns0:cell><ns0:cell>65</ns0:cell><ns0:cell>49</ns0:cell><ns0:cell>1.33</ns0:cell></ns0:row><ns0:row><ns0:cell>France</ns0:cell><ns0:cell>53</ns0:cell><ns0:cell>42</ns0:cell><ns0:cell>1.26</ns0:cell></ns0:row><ns0:row><ns0:cell>Iran</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>1.20</ns0:cell></ns0:row><ns0:row><ns0:cell>Mexico</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.88</ns0:cell></ns0:row><ns0:row><ns0:cell>Italy</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>0.68</ns0:cell></ns0:row></ns0:table><ns0:note>3PeerJ reviewing PDF | (2020:06:50119:1:1:NEW 20 Aug 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Overview of studies by study phase and number of participants (study size) * IQR is interquartile range (1 st quartile [25 th percentile] and 3 rd quartile [75 th percentile]</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell># of participants:</ns0:cell><ns0:cell>3rd</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase</ns0:cell><ns0:cell cols='3'>Study Count Percentage 1st Qu.</ns0:cell><ns0:cell>median (IQR)*</ns0:cell><ns0:cell>Qu.</ns0:cell></ns0:row><ns0:row><ns0:cell>N/A</ns0:cell><ns0:cell>111</ns0:cell><ns0:cell>27.7%</ns0:cell><ns0:cell>49.5</ns0:cell><ns0:cell>120</ns0:cell><ns0:cell>330</ns0:cell></ns0:row><ns0:row><ns0:cell>Early Phase 1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>1.7%</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>40</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 1</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>4.2%</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>40</ns0:cell><ns0:cell>54</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 1/Phase 2</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>5.7%</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>72</ns0:cell><ns0:cell>190</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 2</ns0:cell><ns0:cell>108</ns0:cell><ns0:cell>26.9%</ns0:cell><ns0:cell>60</ns0:cell><ns0:cell cols='2'>145 273.75</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 2/Phase 3</ns0:cell><ns0:cell>34</ns0:cell><ns0:cell>8.5%</ns0:cell><ns0:cell>108</ns0:cell><ns0:cell cols='2'>269.5 433.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 3</ns0:cell><ns0:cell>74</ns0:cell><ns0:cell>18.5%</ns0:cell><ns0:cell>245</ns0:cell><ns0:cell>500</ns0:cell><ns0:cell>1215</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 4</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>6.7%</ns0:cell><ns0:cell>83</ns0:cell><ns0:cell>200</ns0:cell><ns0:cell>450</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>1 1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_6'><ns0:head>Table 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Count of intervention types included in interventional trials Composite Intervention Type Study Count PercentageThis row combines rare Composite Intervention Types, such as 'Drug|Biological' , 'Dietary 3 Supplement', or 'Device|Procedure' (see repository report for full table of intervention types)('r-4 snippets-bmi/regCOVID at master &#8226; lhncbc/r-snippets-bmi') 5</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Drug</ns0:cell><ns0:cell>137</ns0:cell><ns0:cell>34.2%</ns0:cell></ns0:row><ns0:row><ns0:cell>Drug|Placebo</ns0:cell><ns0:cell>75</ns0:cell><ns0:cell>18.7%</ns0:cell></ns0:row><ns0:row><ns0:cell>Biological</ns0:cell><ns0:cell>32</ns0:cell><ns0:cell>8.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>Other</ns0:cell><ns0:cell>31</ns0:cell><ns0:cell>7.7%</ns0:cell></ns0:row><ns0:row><ns0:cell>Device</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>5.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Drug|Other</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>5.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Behavioral</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>3.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>Biological|Placebo</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>3.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>Diagnostic Test</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Procedure</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>2.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>All Other Types*</ns0:cell><ns0:cell>40</ns0:cell><ns0:cell>10.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>2 *</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot' n='3'>PeerJ reviewing PDF | (2020:06:50119:1:1:NEW 20 Aug 2020)</ns0:note> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:06:50119:1:1:NEW 20 Aug 2020)</ns0:note> </ns0:body> "

"Dear Dr. Tatiana Tatarinova, We thank you and the reviewers for the input and constructive comments on our manuscript. We have thoroughly reviewed each comment. We have revised our manuscript and supplementary materials, taking into account each comment. We are now submitting the edited and improved version of our manuscript. See below our response to each reviewer comment. Our response are in bold font and follow the reviewer’s comments (shown in regular un-bolded text). Thank you, Craig Mayer and Vojtech Huser Reviewer 1 (Evgenii Chekalin) Basic reporting The paper 'Computerized monitoring of COVID-19 trials, studies and registries in ClinicalTrials.gov registry' by Mayer and Huser summarizes and describes the distribution of more than 1000 COVID-19 studies and divides these studies into several subgroups (e.g. by study design, Country, intervention type, etc). During this study, authors laboriously assembled all available data and joined it in the github repository. However, access to the data is obstructed by poor code commenting. We changed the code to include comments that will better allow researchers to understand and run the code and better use the generated data files. For example, in the first 16 lines of the code file, there is command con <- dbConnect(drv, dbname='aact',host='aact-db.ctti-clinicaltrials.org', port=5432, user= user, password= psw), which shows how to get to the data. The next 24 lines specify the SQL query that is executed against the studies table in the AACT database. To improve access to the data, the readme.md file in GitHub now includes a link to a list of all CSV files described (https://lhncbc.github.io/r-snippets-bmi/regCOVID/regCOVID_data_file_descript.html) . For example, the files, regCovid_all_studies-a.csv, regCovid_int-a.csv, regCovid_obs-a.csv, and regCovid_registry-a.csv are the lists of all studies, interventional trials, observational studies, and registries generated from search method A respectively. The newly created description file has 80+ entries and provides guidance and description for each included file in the analysis. The readme file also provides the following links that allow the download of CTG data using ClinicalTrials.gov’s simple URL based API. • https://clinicaltrials.gov/ct2/results/download_fields?cond=covid-19&down_count=10000&down_flds=all&down_fmt=tsv • https://clinicaltrials.gov/ct2/results/download_fields?cond=covid-19&down_count=10000&down_flds=all&down_fmt=csv • https://clinicaltrials.gov/ct2/results/download_fields?cond=covid-19&down_count=10000&down_flds=all&down_fmt=plain The manuscript has revised sections that refer prominently to the repository. We revised the text to also point to documentation present on the github repository (see changes at the beginning of section 3 (Results). Experimental design The paper fully describes and classifies available COVID-19 studies. However, there are some questions and advice for authors to structures the work and make in to be much more profitable than simple study review: -The comment on github '(will be updated frequently)' status is not enough for treating the study to be completed; This comment has been removed, and the update methodology has been further explained in the github repository and the Discussion section of the manuscript. -Readme file lack of description in the 'code' field; We have made extensive edits and changes to the github repository and the documentation. A new file describing each file has been created. We have also revised the github readme to better explain the code and files included. The revised readme now also includes instructions on how researchers (re-using our code) can register for an AACT username and password that allows for the running of the code. We have also added a breakdown of what each chapter (or section) of the code is for. See chapter list at https://github.com/lhncbc/r-snippets-bmi/blob/master/regCOVID/readme.md#code-files This comment focused on the github repository and we have changed the repository extensively following this comment. In addition, we have also revised the manuscript to better refer to the github repository. We have also included a sentence in new section 4.3 (added due to other comments) to emphasize that access to AACT database (see https://aact.ctti-clinicaltrials.org/download; AACT=Aggregate Analysis of ClinicalTrials.gov (AACT)) is needed to re-run our code (and work on modifications). Such access can be obtained within hours and is free. -The code file 'covid2_cm.R' should contain more commentaries. We agree and the repository now has a revised code file. It now includes more than 30 lines of new comments (throughout the file). To better guide the reader to the code, we have renamed the code file to regCovid_code_for_analysis.R. The comments explain each portion of code and how it is working. This allows users to understand what each section is doing and why a given coding or analytical approach was chosen. This comment focused on the R code and the code was improved. No alterations to the actual manuscript text were made due to this comment. -There should be an obviously called example (e.g. example.R) file to pull data from the repository; We created regCovid_example.R, which shows how to query AACT and generate the files from Chapter 1 (studies by type). We also included how to directly read in these files from the project repository. -Also short quickstart tutorial should be helpful; We created a quick-start tutorial (regCovid_tutorial.md) found on the github repository that shows how to run our analysis code and how to use individual data files present on the project repository, allowing users to better understand how best to use our results and resources. -In my opinion, the results section should start with an overall database description; We agree with the suggestion for more description. We have revised the readme and added a description of the github repository. A new file called regCOVID_data_file_descript.html is now present. See https://lhncbc.github.io/r-snippets-bmi/regCOVID/regCOVID_data_file_descript.html. In the manuscript, we revised the intro paragraph in the results section. It describes the code used to generate the database as well as the data files generated. See also the end of new section 4.3. -The structure of the database is definitely lack study scheme and a listing of available data described with column definitions; As mentioned above, we generated a list of data files and descriptions of each data file to improve the understanding and usability of the data files. This can be found at https://lhncbc.github.io/r-snippets-bmi/regCOVID/regCOVID_data_file_descript.html and allows others to understand what each file represents. The readme file now also links to the AACT database ER diagram and data dictionary. See revised readme section at https://github.com/lhncbc/r-snippets-bmi/blob/master/regCOVID/readme.md#database-form-of-clinicaltrialsgov-data---aact-database. This new section of documentation clearly refers to the listing of all database columns and definitions at https://aact.ctti-clinicaltrials.org/data_dictionary. ER diagram is also linked (available at https://aact.ctti-clinicaltrials.org/schema). CTG’s metadata documentation is also linked in that new documentation section (available at https://prsinfo.clinicaltrials.gov/definitions.html) This comment asked for changes in the github repository and we made all those changes. The comment did not target the manuscript text and hence no alterations to the paper were made due to this specific comment. Validity of the findings The approach designed by the authors is potentially groundbreaking since there are many laboratories concentrated on the COVID-19 problem and the way to quickly determine the specificity of the hypothesis is highly required. But to become so, the paper needs to be reworked to highlight it's perks. The available data is messy and hard-to-understand for someone who did not participate in the study. We agree with increased emphasis of study benefits. We have reworded the introduction to highlight such benefits. A revised section 4.1 now contrasts the default CTG search interface with our pre-scripted COVID-19 analyses. Revised results sections now better point to result files and overviews (available as CSV files). Finally, an additional perk better described now is the ability to generalize the approach to other diseases. The revised section 4.2.1 now additionally points to it. Regarding the messy data: We also further organized and explained the available files in the github repository (discussed regarding previous comments) to ensure the files and analysis are easier for outside parties to understand. We further explained the need for efficient and effective updating of data and trends and how our automated approach contributes to such need. Finally, we made changes to the weekly report and added more descriptive text to some of the sections. We consider the weekly report equally significant (if not more) as the article tables and result sections (since it reflects current status). We also anticipate further improvements based on ongoing feedback via github issues filed by report users. Comments for the Author Instead of data classification, it is probably better to concentrate efforts on the description of the database authors assembled, which will result in the excellent paper many researchers will find very useful. We agree and we have added a section that emphasizes how to obtain the database (beginning of Results). We have revised sections that explain the relationship of our input data to the AACT database (which is a relational database with ClinicalTrials.gov data (from native XML files at ClinicalTrials.gov)). The revised methodology clarifies this. Researchers can also run our script daily to achieve daily updates (although there is a 4 day lag behind CTG; explained in the article). We have revised some sections to better point to the paper perks (per other comment as well). We think the value of the paper is not just in the database, but in the standardized set of queries one can create centered around a disease. We show importance of this set of queries by showing the application of it on nearly 1000 diseases (see discussion). In regards to the download process: We have revised the documentation in github readme to include better instructions on how to download the database. See new section here https://github.com/lhncbc/r-snippets-bmi/blob/master/regCOVID/readme.md#how-to-obtain-a-copy-of-the-database-we-created. Reviewer 2 (Anonymous) Basic reporting The manuscript review is titled Computerized monitoring of COVID-19 trials, studies, and registries in ClinicalTrials.gov registry, submitted to PeerJ for review. The manuscript conforms to the expectations of the PeerJ guidelines, and the needs of the scientific community, especially during the time of this pandemic. The authors of the manuscript have done an excellent job summarizing the context of the use of automation and informatics for repositories like Clinicaltrials.Gov (CTG) using COVID-19 and the ability to repurpose the methodology and design for other disease conditions. Appreciate the high quality and intensive research effort conducted by the authors. The content is very good but could benefit from some restructuring. To improve readability, we made changes to the result section text to better explain the context for some results. To improve the structure, we changed the sections such that the results sections and methods sections better match. The discussion now also better separates COVID-19 snapshot results from informatics results. The level of interest from a methodology perspective is on par, but would greatly benefit from a detailed description of the need for data automation & informatics, specifically in the introduction/background section. Example https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7216865/ Thank you for providing a truly relevant reference. We agree that increasing the level of description is helpful. The revised manuscript now cites the reference. We have revised the introduction to refer to clinical informatics and Clinical Research Informatics (CRI). We have also added a paragraph to the end of the introduction explaining the need for automation and the perks and capabilities of such an approach. A new section on weekly updates (4.3) also further emphasizes informatics approaches. Finally, we modified the text highlighting generalization of this approach to all diseases. Validity of the findings The search strategy is very well written and has supporting raw data and codes available. In the discussion section, the authors have made a good effort in categorizing the two facets to discussion journalist and data science perspective. The data science perspective lacks the description of the need for informatics. Although the authors mention the role of manual vs automation from past studies, would be helpful to acknowledge how automation of such datasets influences research in the area of public health emergencies, etc. We agree with the suggestion. We have expanded the informatics perspective discussion. We added four new sentences to section 4.2 that highlight the need for informatics. We have also added a paragraph in the introduction (mentioned in reference to previous comments) articulating this idea of the need for data science methods. Finally, we also revised discussion (section 4.1.2 Related Studies) to emphasize the importance of using an automated data science approach compared to a manual one, due to the need for up-to-date information and the significant difference in resources needed for a manual approach compared to an automated, data science driven approach. Comments for the Author As a general comment, this manuscript is important and needs to be published. It is outlined like a methods manuscript and how those could be applied to specific studies, with appropriate analysis. Major comments: Row 78: Introduction - you suggest the goal of the study is to demonstrate automated and research informatics methods to analyze a set of closely related studies. I would suggest broadening this to highlight the application of general statistical principles. This would support the discussion in sections methods and results. We added to this sentence to broaden the stated purpose to include the general statistical principles used in the analysis done in the methods and results. In this sentence we now state the two additional concepts of developing a data science approach and using statistical principles to show the current trends for COVID-19 research. Recommendation on restructuring: The draft switches between what a reader would expect from row 108 2.1 Analyzed study section, between analysis of studies based on (1) interventional trials, (2) observational (3) registry studies, to section 2.2 Analysis, 2.3 Intervention Trials 2.4 Observational studies and registries. From a readership, perspective recommends having a section of 2.3 Study types and then sub-sections for interventional and, observational and registries. We fully agree. We generated the extra heading for study type specific analysis, which helps clarify the process and improve the readability and comprehensiveness of the paper. This allows for the reader to more easily follow our methods and results. Minor comments: Row 65: recommend to add: what this kind of analysis will help inform? Just a broad general characterization such as clinical guidelines development, etc. This idea is now included in the newly added paragraph at the end of the introduction, which showcases the perks of our research and its ability to inform research decisions based on current trends. Row 82: COVID-19 clinical studiess , spelling error Thank you, we have fixed all spelling and grammar errors found in the manuscript (including this one). Row 110: (3) Recommend modifying registry studies to registry-based studies We carefully considered two options (first mention and clarification versus changing all instances). We eventually opted for the first option. We changed the first mention of the term and re-state the term definition at the beginning of section 3.3.3. In other parts of the manuscript, we use the shorter term. Row 113: ‘,’ to be removed before We As stated above we have fixed all language and formatting errors For figure 2, a higher resolution image might be helpful. We believe that conversion during review may have caused the resolution to be lower than submitted by us. We will make sure to upload a separate file to the journal submission system with high resolution version of the figure. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Clinical trial registries can provide important information about relevant studies for a given condition to other researchers and the public. We developed a computerized informatics based approach to provide an overview and analysis of COVID-19 studies registered on ClinicalTrials.gov registry. Using the perspective of analyzing active or completed COVID-19 studies, we identified 401 interventional clinical trials, 287 observational studies and 64 registries. We analyzed features of each study type separately such as location, design, interventions and update history. Our results show that the United States had the most COVID-19 interventional trials, France had the most COVID-19 observational studies and France and the United States tied for the most COVID-19 registries on ClinicalTrials.gov. The majority of studies in all three study types had a single study site.</ns0:p><ns0:p>For update history 'Study Status' is the most updated information and we found that studies located in Canada (2.70 updates per study) and the United States (1.76 updates per study) update their studies more often than studies in any other country. Using normalization and mapping techniques, we identified Hydroxychloroquine (92 studies) as the most common drug intervention, while convalescent plasma (20 studies) is the most common biological intervention. The primary purpose of most interventional trials is for treatment with 298 studies (74.3%). For COVID-19 registries we found the most common proposed follow-up time is one year (15 studies). Of specific importance and interest is COVID-19 vaccine trials, of which 12 were identified. Our informatics based approach allows for constant monitoring and updating as well as multiple applications to other conditions and interests.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head n='1'>Introduction</ns0:head><ns0:p>The purpose of clinical trial registries, among others, is to inform the research community about currently ongoing studies. A registry can also be a sole source of study results for thousands of studies that would otherwise not publish a result article in a journal. <ns0:ref type='bibr'>(Zarin et al., 2019)</ns0:ref> For the current effort to address the COVID-19 epidemic, this function of registries is of great value. The fields of clinical informatics and clinical research informatics have an important role to play in fighting the epidemic. <ns0:ref type='bibr'>(Moore et al., 2020)</ns0:ref> We focus on a single registry, ClinicalTrials.gov <ns0:ref type='bibr'>(CTG)</ns0:ref>, and analyze COVID-19 registered studies. We chose to focus on CTG because it collects a rich set of metadata, supports record updates, <ns0:ref type='bibr'>(Fleminger &amp; Goldacre, 2018)</ns0:ref> allows for basic summary results deposition and studies in CTG make up a large volume of all studies tracked by the World Health Organization registry. <ns0:ref type='bibr'>(Huser &amp; Cimino, 2013)</ns0:ref> The goal of our study is to demonstrate how automated and clinical research informatics <ns0:ref type='bibr'>(Embi &amp; Payne, 2009)</ns0:ref> methods can be used to analyze a set of closely related studies, as well as to use general statistical principles to analyze and understand key metrics for studies on a given condition or in a specific clinical domain. The computer code written in R language is open source and available at the project repository.('regCOVID Project Repository,' 2020) Our project differs from past published analyses of COVID-19 clinical studies <ns0:ref type='bibr'>(Rosa &amp; Santos, 2020;</ns0:ref><ns0:ref type='bibr'>Fragkou et al., 2020;</ns0:ref><ns0:ref type='bibr'>Checcucci et al., 2020)</ns0:ref> by not using manual review of study records and instead relying fully on study metadata recorded in the registry.</ns0:p><ns0:p>Unlike manual approaches, our approach of using automation to monitor COVID-19 studies allows for quick and efficient, continuous monitoring of the state of COVID-19 research. Automated queries can provide an instant overview of COVID-19 research. They also allow for computing and visualizing current COVID-19 research trends. Furthermore, the informatics approach we use improves the capability for effective modulation and allows individuals to specifically target the desired information wanted to inform their research decisions (such as on clinical guidelines, and the use of certain interventions). With the gradual publication of COVID-19 study results, this approach also allows for automated detection of registry deposition of basic summary results and the publication of a study result journal article that is clearly tied to a registered COVID-19 trial, study or registry.</ns0:p></ns0:div> <ns0:div><ns0:head n='2'>Materials &amp; Methods</ns0:head><ns0:p>Our study had two aspects. The first aspect was assuming a journalist perspective and the motivation was whether CTG registry can provide a useful overview of COVID-19 studies without any manual curation. We wanted to demonstrate on a COVID-19 use case whether existing study metadata currently collected by CTG registry are accurate and adequate for a journalist interested in a registry-based picture of COVID-19 research. The methods and results sections address mostly this first aspect.</ns0:p><ns0:p>The second aspect was assuming an informatics or data science perspective and the motivation for this was to apply additional rules, data transformations and heuristics to CTG metadata that could characterize the quality of the registry data and possibly narrow the list of all CTG studies to a smaller set. The critical component of this second informatics aspect was a vision to generalize the fully computerized single disease report to all diseases. The discussion section of this article addresses this second aspect.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.1'>Set of analyzed studies</ns0:head><ns0:p>We used the Aggregate Analysis of ClincalTrials.gov (AACT), which is a relational database version of CTG data that is created by parsing the XML (Extensible Markup Language) representation of each study. <ns0:ref type='bibr'>(AACT Team, 2020)</ns0:ref> It is published and maintained by Duke University. AACT data is typically four days behind CTG in terms of content or changes, which we deemed as acceptable. We performed separate analyses of COVID-19 studies based on their CTG study type of (1) interventional trials, (2) observational studies, and (3) registry-based studies (we use the term registries). <ns0:ref type='bibr'>(CTG Team, 2020a)</ns0:ref> We designed several inclusion criteria to focus only on COVID-19 studies in scope for our analysis. This consisted of first, creating a search strategy based on title or study keywords. We also looked at CTG study metadata to select studies with fields that we considered relevant based on the triggering of quality measures and the connection to the regulatory process.</ns0:p><ns0:p>In terms of keyword and title search strategy, we evaluated three search approaches. The first method involved a search for the presence of keywords in the official title of the study. The keywords used were, 'covid <ns0:ref type='bibr'>', 'sars-cov', '2019-ncov', and 'coronavirus'.</ns0:ref> The second method searched for the same keywords in the free text condition field. The third method found studies that had a Medical Subject Heading (MeSH) term for the study of 'coronavirus infections'. We limited our search for each method to only include studies first submitted after 27 December 2019 (the date of the official report from Wuhan hospital to the local center for disease control and prevention). For later analysis, we present data for the first search method (with results for all three methods being available on the study repository at https://github.com/lhncbc/r-snippetsbmi/tree/master/regCOVID). The data presented below reflects the search performed on 11 May 2020. The results of the search methods were validated as appropriate COVID-19 studies via the manual review of the titles of a subset of the search results.</ns0:p><ns0:p>In terms of study inclusion criteria based on structured CTG's study metadata fields we used study status. Study status reflects the progress of the study from 'not yet recruiting' to 'recruiting' to 'completed' (or other statuses such as 'terminated' or 'suspended'). <ns0:ref type='bibr'>(CTG Team, 2020a)</ns0:ref> We elected to limit the scope of our analysis to reflect currently ongoing or completed COVID-19 studies. Given this assumption, we excluded studies with 'not yet recruiting' study status. Under existing quality assurance rules used by CTG, studies in status 'not yet recruiting' do not have to provide the study location (in terms of country) and we considered study country to be essential study metadata. Given our chosen analytical perspective of currently ongoing or completed COVID-19 studies, we excluded studies with an unusual completion status of 'terminated', 'suspended', or 'withdrawn'. However, we provide some results for unusually completed COVID-19 studies because when combined with the 'Reason for termination' field, such studies may provide important insights.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Analysis</ns0:head><ns0:p>For all study types, we analyzed a set of study metadata described below. Study metadata specific to a given study type (e.g., those collected only for observational studies or registries) are described in subsequent sections.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2.1'>Number of studies over time</ns0:head><ns0:p>Using the date when the study was first registered on CTG, we counted the number of total studies for each study type on a given date. We created a plot showing the temporal trend over time.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2.2'>Study sites and country</ns0:head><ns0:p>Despite the existence of national registries, CTG registry contains studies from many countries. For example, as of 2 June 2020, 61% of recruiting studies were located solely outside the US (according to CTG's overview page('Trends, Charts, and Maps -ClinicalTrials.gov')). Additional incentive for registration on CTG are FDA rules that require studies submitted in support of new drug applications to FDA to be registered at CTG. Similar requirements of CTG registration also exist from many study funders such as NIH, and journals such as International Committee of Medical Journal Editors (ICMJE) member journals. We analyzed the geographic data for each study by reviewing the location fields in the CTG study record and counted the number of sites and identified the country of their locations. Each study could consequently include one or multiple countries.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2.3'>Study update activity</ns0:head><ns0:p>The clinical trial registry allows principal investigators to update the public about study completion, the final number of enrolled participants and basic summary results. High public interest in updates about COVID-19 studies was the main motivation for measuring update activity and study record recency.</ns0:p><ns0:p>We quantified the level of update activity for a study by looking at the number of updates and what fields are updated for a given study after its initial registration. We attempted to classify type of updates into technical updates (e.g., study sites changes) and updates of significant public interest (actual primary completion date or deposition of study results). We also evaluated the recency of the CTG study record by evaluating the number of days between the last update and the current date. Study update data is not available via AACT or the CTG Application Protocol Interface (API).(CTG Team, 2020b) However, information about study updates is available via the CTG website. To obtain this information we wrote an R script to scrape the data into a computable form.</ns0:p><ns0:p>We also evaluated the level of update activity for studies based in each country and found studies from which countries were more active in updating CTG study records.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2.4'>Study design</ns0:head><ns0:p>We analyzed CTG metadata pertaining to study design to classify studies. One feature analyzed for all study types was study enrollment (number of participants). CTG allows the reporting of estimated and actual enrollment into the trial. Study record managers can use this mechanism to publicly post updates about the number of enrolled participants.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Study type specific analysis</ns0:head></ns0:div> <ns0:div><ns0:head n='2.3.1'>Interventional trials</ns0:head></ns0:div> <ns0:div><ns0:head n='2.3.1.1'>Interventional trial specific features</ns0:head><ns0:p>We analyzed certain features which are specific to interventional trials alone. This includes phase, primary purpose, and number and type of arms.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.1.2'>Intervention type</ns0:head><ns0:p>For interventional trials specifically we analyzed the intervention types for the collection of COVID-19 studies. To do this we used CTG's metadata field of intervention type. CTG classifies each intervention as drug, device, biological, procedure, radiation, genetic, dietary supplement, behavioral, combination product, diagnostic test, and other. We counted the number of studies associated with each intervention type. Each study could include one or multiple intervention types. If multiple intervention types were included, we counted each study based on the combination of intervention types associated with the study. For example, NCT04334512, a 'Study of Quintuple Therapy to Treat COVID-19 Infection', included two interventions of type 'Drug' (Hydroxychloroquine and Azithromycin) and three interventions of type 'Dietary supplement' <ns0:ref type='bibr'>(Vitamin C, Vitamin D and Zinc)</ns0:ref>. This study was counted exactly once under a composite intervention type that consisted of the alphabetically sorted combination of two types: 'dietary supplement | drug', with the '|' representing the term 'and'.</ns0:p><ns0:p>Our analysis of intervention types and names revealed that placebo as an intervention name is often used and captured under type 'Drug' or 'Biological'. CTG type classification does not include placebo as a separate intervention type, however, we decided to experimentally create it and assign it based on a rule that looked for the term placebo in the intervention name.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.1.3'>Interventions</ns0:head><ns0:p>Researchers and the public are most interested to see which drugs (or other interventions) are being tested in relation to COVID-19. CTG allows study record administrators to specify intervention using free text and further assign interventions to study arms. Because of the vital importance of interventions and the correct counting of studies using the same intervention, we did implement a limited computerized method of processing free text interventions to achieve some semantic harmonization. After free text string transformations into harmonized intervention terms, we counted the number of studies that included a given intervention. We also evaluated the temporal change in the amount of studies for the most common interventions by showing the number of new studies on a weekly scale (as seen in a figure in the Results section).</ns0:p><ns0:p>From prior studies, there is an obvious need to harmonize semantically different interventions expressed as free text across different studies. <ns0:ref type='bibr'>(Cepeda, Lobanov &amp; Berlin, 2013)</ns0:ref> For example, the intervention term 'ruxolitinib' can semantically harmonize entries of 'Ruxolitinib Oral Tablet' (in study NCT04334044), 'Ruxolitinib 10 MG' (NCT04338958) and 'Ruxolitinib' (NCT04331665). Initial normalization involved the removal of extra white space and the conversion of each term to lower case. Representing drug dose form was out of scope so further normalization removed commonly occurring dose form terms, such as, 'tablet', 'injection', and 'pill'.</ns0:p><ns0:p>Studies with multiple interventions were counted multiple times under each individual intervention. In some cases, the free text string for a single intervention (in the CTG data entry field) specified a combination of several interventions. Our transformation approach in such cases kept the combination as well as expanded the single entry into multiple separate interventions and counted each intervention separately. For example, NCT04334928 has an intervention that includes a combination of Emtricitabine and Tenofovir Disoproxil. In this case the study is counted once for Emtricitabine, once for Tenofovir, and once for the combination of Emtricitabine and Tenofovir. In some cases, the manual mapping reduced the term granularity and used a higher-level term.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.1.4'>COVID-19 vaccine trials</ns0:head><ns0:p>A segment of COVID-19 interventional trials with high importance and significant public interest are vaccine trials. CTG maintains a hierarchy of intervention types but vaccine as an intervention does not have a designated intervention type and is subsumed under the intervention type 'Biological'. Because there is no special vaccine intervention type, our method for finding vaccine trials was based on a string search for the term 'vaccine' in the official title of the study. Once we created a COVID-19 vaccine trials subset, we applied on this set the same series of analyses and metrics mentioned above.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3.2'>Observational studies and registries</ns0:head><ns0:p>Observational studies and registries have metadata features that are not recorded for interventional trials. Such analyzed features were: time perspective and observational model for the set of observational studies and registries. In addition, one feature recorded and analyzed for only registries was follow up time.</ns0:p></ns0:div> <ns0:div><ns0:head n='3'>Results</ns0:head><ns0:p>We developed a methodology to search and extract metadata on COVID-19 clinical studies. The database is a subset of the AACT database of ClinicalTrials.gov data. The database and result files can be found in our github repository at https://github.com/lhncbc/r-snippetsbmi/tree/master/regCOVID. The repository includes the R code (https://github.com/lhncbc/rsnippets-bmi/blob/master/regCOVID/regCovid_code_for_analysis.R ), with comments explaining how it works, to obtain and analyze the data, as well as all comma separated value (CSV) data files used during the analysis. The repository also includes additional result data files not included in this paper but described in the repository documentation. The repository also includes a list of descriptions for each data file (https://lhncbc.github.io/r-snippetsbmi/regCOVID/regCOVID_data_file_descript.html ) for easy use. For example, the files, regCovid_all_studies-a.csv, regCovid_int-a.csv, regCovid_obs-a.csv, and regCovid_registrya.csv are the lists of all studies, interventional trials, observational studies, and registries generated from search method A respectively. These files include all 64 columns from the AACT studies table, such as NCT ID, official title, start date, primary completion data, and enrollment. The description file has more than 80 entries and provides guidance and descriptions for each included file in the analysis. Also included in the repository is an example of part of the code used in the analysis (https://github.com/lhncbc/r-snippetsbmi/blob/master/regCOVID/regCovid_example.R ) and a quick-start tutorial (https://github.com/lhncbc/r-snippets-bmi/blob/master/regCOVID/regCovid_Tutorial.md) that shows users how to easily access and use our code and load the data files into R to review our results and perform their own analysis.</ns0:p><ns0:p>While this paper includes results from the main analysis done on 11 May 2020, the repository report is updated weekly and offers up to date results.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.1'>Set of analyzed studies</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1.1'>Search strategy</ns0:head><ns0:p>We found that the first search method, using the official title of the study, was the most comprehensive and included the most COVID-19 studies. The numbers listed below reflect only the search strategy and not applying the criteria based on study status. As of 11 May 2020, the first search method returned a total of 1302 studies. The second search method, based on the free text condition field, found fewer records (1165 studies). The third method based on the MeSH term, returned 328 studies. The significant difference in the studies captured in the third search strategy is likely due to the fact, that there is no specific MeSH term for COVID-19 at this point and the MeSH condition field is not required and is left blank for many studies (38.2% of studies captured in the first search method left MeSH condition term blank).</ns0:p><ns0:p>We then applied metadata inclusion criteria (studies that are active, recruiting or completed and are not expanded access). This reduced the set for the first search method to 752 studies, the set from the second search method to 680 studies, and the set from the third search method to 210 studies. This led us to select the set of COVID-19 studies generated from the first, most comprehensive search method, based on study title.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.1.2'>Final study set</ns0:head><ns0:p>In terms of completion and presence of results, 48 studies in the final set were completed at the time of this analysis. None have provided summary results to this point. It is important to note that studies are typically required to submit results within one year after the primary completion date.('FDAAA 801 and the Final Rule -ClinicalTrials.gov') Also, at the time of the analysis, 106 studies have past their primary completion date (12 studies when using primary completion day + 30 days) declared in the latest study record and have a status that indicates the study is still ongoing. This indicates that the record is possibly not kept current. Administrators do typically have 30 days after a status change to update the record (see 42 Code of Federal Regulation [CFR] 11.64(a)(1)(ii)).('Frequently Asked Questions -ClinicalTrials.gov') In an extreme case, 20 studies of those 106 studies have a status of 'not yet recruiting' and are past their primary completion date.</ns0:p><ns0:p>To understand how our metadata study inclusion criteria affects the final set, we briefly analyzed the set of studies excluded due to our study metadata criteria. The studies removed due to metadata included 516 studies that were not yet recruiting, 10 that were withdrawn, 5 that were suspended and 2 that were terminated. The reasons for termination of the 2 studies were 'We cannot meet number of subjects as recently published similar studies' for NCT04357535 and 'The epidemic of COVID-19 has been controlled well in China, no eligible patients can be enrolled at present' for NCT04257656. The interventions of the terminated studies were ACE-I (angiotensin-converting enzyme inhibitors) and ARB (angiotensin receptor blocker) for the former and Remdesivir for the latter. Our study type criteria also excluded 17 studies with a study type of 'Expanded access'.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2'>Studies over time</ns0:head><ns0:p>Figure <ns0:ref type='figure'>1</ns0:ref> shows the number of registered studies over time by study type. Interventional trials are most numerous. An important regulatory consideration is that, in the US, applicable interventional clinical trials are required to register, 13 while registration of observational studies and registries is optional. When considering the submission date, the first interventional trial, and the first study overall, was submitted to CTG on 23 January 2020, while the first observational study was submitted on 26 January 2020 and the first registry was not submitted until 12 March 2020. </ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>Analysis by study type</ns0:head></ns0:div> <ns0:div><ns0:head n='3.3.1'>Interventional trials</ns0:head><ns0:p>We identified a total of 401 COVID-19 interventional trials from CTG. These 401 studies included a total of 1666 interventions.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.1'>Study sites and country</ns0:head><ns0:p>The majority of interventional trials had just one study site (259 studies, 64.6%%). 41 studies had two sites and 18 studies had three sites, the second and third highest study counts. As for country of operation, Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref> shows the count of interventional trials by the country or countries that have at least one site that is part of the study.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 1.</ns0:head><ns0:p>The vast majority of studies 385 (96.0%) only included sites in a single country. Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref> results indicate that the most common country for interventional trials was the United States with 121 studies (30.2%) followed by China with 49 studies (12.2%).</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.2'>Update activity</ns0:head><ns0:p>We evaluated the amount of interventional trials that had updates after the study was first submitted to CTG (full update data are available in a report and as Comma Separated Value [CSV] files in the study github repository).('regCOVID,' 2020) At the time of the analysis, 71.1% (285 studies) of the 401 interventional trials show the presence of at least one update since first being submitted to CTG. The study with the most updates was NCT04280705, 'Adaptive COVID-19 Treatment Trial (ACTT)' with 18 updates. The most common public interest and overall feature updated for COVID-19 interventional trials was 'Study Status', which was updated 643 times including at least once by each of the 285 studies that had at least one update. Other commonly updated public interest fields include 'Recruitment Status' (212 updates from 199 studies) and 'Outcome Measures' (137 updates from 108 studies).The second most commonly updated field overall, and most common technical field, was 'Contacts/Locations', which was updated 393 times by 223 studies. Using 11 May 2020 as the current date, we also looked at the amount of days since last update to evaluate how current the existing CTG record is and found that the average amount of days since the last update is 20.6 days for all COVID-19 interventional trials.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref> shows the amount of updates by studies in each country and the ratio of the number of updates compared to the number of studies in a given country. The table is limited to countries with at least eight studies. The country with the highest update rate is Canada with 2.70 updates per study, followed by the United States with 1.76 updates per study.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.3'>Study design and interventional trial specific features</ns0:head><ns0:p>Study phase and size: Considering study phase and study size (or enrollment; number of participants), Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref> shows the counts of studies and percentage by study phase, as well as study size indicators: 1 st quartile, median, and 3 rd quartile for the participants enrolled (either actual or anticipated) for the set of studies of each phase.</ns0:p><ns0:p>Table <ns0:ref type='table' target='#tab_3'>3</ns0:ref> shows that the phase with the most studies is N/A with 111 studies (27.7%), which represents studies of intervention type device or behavioral. The second most common phase is Phase 2 with 108 studies (26.9%). Unsurprisingly the phase with the highest enrollment is Phase 3 with a median of 500 participants, while the lowest enrollment is Early Phase 1 with a median enrollment of 10 participants.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 3.</ns0:head><ns0:p>Arms: Considering number of study arms, most interventional trials have two arms (245 studies, 61.1%), while 73 studies (18.2%) have just one arm.</ns0:p><ns0:p>Primary Purpose: Considering study primary purpose, Table <ns0:ref type='table'>4</ns0:ref> presents the breakdown into 8 purpose categories. In 298 (74.3%) of the analyzed COVID-19 interventional trials, the primary purpose was treatment. For 41 (10.2%) the primary purpose was prevention.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 4.</ns0:head><ns0:p>Arm Type: CTG allows study managers to specify the type of each study arm. Each study arm is named and is classified as a specified arm type. Each study could have one or multiple arms of the same type. For example, NCT04321993, 'Treatment of Moderate to Severe Coronavirus Disease in Hospitalized Patients', has three arms of type 'Experimental' and one arm of type 'No Intervention'. One arm in this study has patients receiving an intervention of Lopinavir/Ritonavir, the second has patients receiving an intervention of Hydroxychloroquine, and the third has patients receiving an intervention of Barictinib. This study also has a fourth arm of patients receiving no intervention.</ns0:p><ns0:p>Considering types of all COVID-19 interventional trials, we found that the most common arm type is 'Experimental', which appears 489 times. Table <ns0:ref type='table'>5</ns0:ref> shows the complete data for arm type in the set of 401 interventional trials.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 5.</ns0:head><ns0:p>Different diseases at different maturity of clinical research may be employing a different design, such as the inclusion of a placebo or active comparator. We calculated the placebo index, which is the percentage of interventional trials that have a placebo or sham comparator arm. Each study can have one or multiple arms that are assigned a placebo comparator. For our set of COVID-19 studies, the placebo index was 28.7% (115 of 401 total trials). We also calculated the active comparator index, which is the percentage of trials with at least one active comparator arm, and found that 28.9% (116 trials) have at least one active comparator arm.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.4'>Intervention type</ns0:head><ns0:p>Table <ns0:ref type='table' target='#tab_5'>6</ns0:ref> shows the count of studies by intervention type. Intervention type 'Drug' is the most common (137 studies [34.2%]). The combination of drug and placebo intervention type was the second most prevalent with 75 studies (18.7%). Biological was the next most prevalent type with 32 studies (8.0%). Based on our methodology for classifying intervention types, each study can be counted only under one composite intervention type. Table <ns0:ref type='table' target='#tab_5'>6</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.5'>Interventions</ns0:head><ns0:p>There were a total of 449 distinct interventions listed prior to the implementation of our normalization and mapping process. Once the interventions were mapped the amount of normalized interventions was reduced to 403. The full mapping is available at the study repository (file: intervention_map2.xlsx).('regCOVID Project Repository,' 2020) Table <ns0:ref type='table'>7</ns0:ref> shows the most common interventions used in COVID-19 interventional trials. Given our counting methodology for interventions, each study can be counted multiple times in Table <ns0:ref type='table'>7</ns0:ref> because combined interventions are expanded into their components as well as kept as a combination. The most common drug intervention was Hydroxychloroquine with 92 studies, followed by Azithromycin with 24 studies. The two (Hydroxychloroquine and azithromycin) appeared together four times. The most common combination intervention was Lopinavir/Ritonavir with 16 studies. We also found the presence of interventions most likely listed as a comparator or a non-intervention group, rather than a specific intervention. This is seen as 99 studies have placebo listed as an intervention while another 40 studies have standard care listed.</ns0:p></ns0:div> <ns0:div><ns0:head>Table 7.</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:06:50119:2:0:NEW 23 Sep 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>As for non-drug interventions, the most common biological is convalescent plasma with 20 studies. Other leading interventions for different types (not shown in Table <ns0:ref type='table'>7</ns0:ref>) include oxygen supplying equipment for device with six studies and Vitamin C for dietary supplements with four studies. We also found that the same intervention can be listed as different intervention types. For example, convalescent plasma was listed for 14 studies as the intervention type biological, three times as other and 3 times as drug. We combined each intervention to count as the most commonly used intervention type when counting the intervention. For this case of convalescent plasma, that would count as 20 studies and categorize convalescent plasma as having the type biological.</ns0:p></ns0:div> <ns0:div><ns0:head>Interventions over time:</ns0:head><ns0:p>We also evaluated the temporal change for the most common interventions by analyzing the amount of new studies weekly for the most common interventions as seen in Figure <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>. </ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.1.6'>COVID-19 vaccine interventional trials</ns0:head><ns0:p>Our search method for vaccine trial intervention type studies identified 12 COVID-19 vaccine trials, that also met our inclusion criteria of being active, recruiting or completed. Due to their high significance and increased public interest, it is interesting to consider how frequently such trials are updated. A total of 9 trials (75.0% of the 12 vaccine trials) have at least one update and the median amount of updates is two. Considering the study country, six different countries have at least one vaccine trial, with China (5 vaccine trials) having the most, followed by the US with 3 trials. Five of the trials were Phase 1, six were Phase 1/Phase 2 and one was Phase 2. Of note is the fact that Phase 1 trials are not 'applicable clinical trials' (as defined in US regulations) and such trials have no mandatory registration.('FDAAA 801 and the Final Rule -ClinicalTrials.gov') Exactly half of vaccine interventional trials (6 trials) had more than one site. As for design, the average number of arms was 5.4 with a median overall trial enrollment of 119.5 participants. The 12 vaccine interventional trials also included 52 experimental arms and seven placebo comparator arms. The full overview of all metadata parameters for vaccine trials (as well as for observational studies and registries described in subsequent sections) is available at the study repository.('regCOVID,' 2020)</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.2'>Observational studies</ns0:head><ns0:p>We found a total of 287 observational studies. Similarly, to interventional trials, the vast majority of observational studies had just one site (238 studies, 82.9%). The country with the most observational studies was France with 75 (26.1%), followed by the United States with 47 (16.4%). Observational studies are updated less frequently than interventional trials as only 52.6% (151 studies) of the COVID-19 observational studies have been updated since first being submitted to CTG (compared to the 71.1% of interventional trials that have been updated at least once). The observational study with the most updates was NCT04334954 'SARS-COV2 Pandemic Serosurvey and Blood Sampling' with 25 updates since registration on 6 April 2020. The most commonly updated public interest feature for observational studies was the 'Study Status' which was updated 270 times by 151 studies and the most common technical feature updated was 'Contacts/Locations' with 99 updates from 83 studies.</ns0:p><ns0:p>The median enrollment for observational studies was 353 participants. One feature of observational study design is the time perspective. A majority of the observational studies analyzed were prospective (180 studies, 62.7%), as opposed to 58 studies (20.2%) which were retrospective. For observational model, 167 of the observational studies (58.2%) use a cohort model. The second most commonly used model for the analyzed observational studies was case (45 studies, 15.7%).</ns0:p><ns0:p>Contrary to our expectation, we found observational studies that included interventions in their CTG record. Of the 287 observational studies, 179 (62.4%) listed something in the free-text intervention field. However, this number is misleading as in many cases the listed intervention was something that stated that there was no intervention (such as 'no intervention', 'observation <ns0:ref type='bibr'>', 'non-interventional', etc.)</ns0:ref>. Of the listed interventions most are listed as intervention type 'Other' (86 studies, 30.0%) or 'Diagnostic Test' (34, 11.9%).</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3.3'>Registries</ns0:head><ns0:p>We analyzed a total of 64 COVID-19 registries (shorter term for registry-based studies). Of these registries 52 (81.3%) were limited to one site. The largest number of sites was 53. The countries with the most COVID-19 registries were France and the United States with 9 studies each. Similar to observational studies, just over half of the analyzed registries, 51.6% (33 registries), have been updated at least once since their first registration. Also similar to observational studies, the most common public interest update for registries is to the study status, which has been updated 56 times by all 33 registries with an update, and the most common technical update is to the contacts and locations with 28 updates from 18 studies.</ns0:p><ns0:p>The median enrollment for the set of registries was 388 participants. Registries have many specific design features that differentiate them from other study types. One is the presence of a targeted follow-up time. The most common follow-up time for the analyzed registries was one year for 15 studies (23.4%), which was listed as either '1 year' or '12 months' and was combined to get the accurate value. The shortest follow-up time was one day for NCT04331171, 'Epidemiological Observation From a Smartphone Self-monitoring Application for Suspected COVID-19 Patients' Triage', while the longest targeted follow-up duration for a registry was 20 years, for NCT04359602, 'COVID-19 Recovered Volunteer Research Participant Pool Registry'. For registries, CTG collects their observational model (similar to observational studies). The majority of registries, 48 (75.0%), use a cohort model. Also similar to observational studies, registries can include a time perspective. However, unlike observational studies, no registries are retrospective. Instead the time perspective is usually either prospective (50 studies, 78.1%), or cross-sectional (6 studies, 9.4%). A cross-sectional perspective means that the observation or intervention is made at a single point in time rather than on a continuous or recurring basis. <ns0:ref type='bibr'>(CTG Team, 2020a)</ns0:ref> Like observational studies, more than half (53.1%, 34 of 64 registries) included an intervention in the free text field. These interventions also include many that are not representative of an actual intervention and rather state the absence of an intervention just like with the previously mentioned observational studies. This is also shown in the intervention type as 19 of the 34 registries (55.9%) have an intervention type of 'other'.</ns0:p></ns0:div> <ns0:div><ns0:head n='4'>Discussion</ns0:head><ns0:p>Based on our two perspectives, we discuss separately COVID-19 studies results (journalist perspective) and data science implications (informatics perspective).</ns0:p></ns0:div> <ns0:div><ns0:head n='4.1'>COVID-19 studies</ns0:head><ns0:p>Our study developed a computerized approach of retrieving COVID-19 studies from CTG registry for analysis. CTG's study metadata facilitates the useful classification of studies into many relevant subgroups (e.g., by study design, size, phase, recruitment status or intervention). Availability of this data in a structured form (either via CTG's API or via structured XML or relational data files) provides analytical views that would be difficult or impossible to achieve without a registry. As of 11 May 2020 ( the date of primary analysis), no study had deposited basic summary results.</ns0:p><ns0:p>The results presented above were summarized as of 11 May 2020. Refreshed and more current data (released weekly) can be obtained at the project repository. ('regCOVID Project Repository,' 2020; 'regCOVID,' 2020). Weekly updated reports allow researchers, journalists or the general public to quickly obtain a snapshot of the ongoing COVID-19 research. For example, a weekly report intervention section (similar to Table <ns0:ref type='table'>7</ns0:ref>) can reveal to many research teams concentrated on COVID-19 what interventions are being studied with what intensity. This analytical view would require tens of manual queries using the generic CTG web interface.</ns0:p></ns0:div> <ns0:div><ns0:head n='4.1.1'>Study limitations</ns0:head><ns0:p>Our study has several limitations. First, we only used CTG registry to look for COVID-19 studies. Within this registry, we evaluated three search strategies, but some relevant COVID-19 studies may possibly be missed. Without a benchmark gold standard of all COVID-19 studies, the recall of our search strategy cannot be evaluated. It was out of scope of this study to establish the precision of our search. Second, our semantic harmonization of interventions is based on manual mapping by a single expert. Third, there are significant limitations of the informaticsbased approach compared to manual review. </ns0:p></ns0:div> <ns0:div><ns0:head n='4.1.2'>Related studies</ns0:head></ns0:div> <ns0:div><ns0:head n='4.2'>Data science perspective</ns0:head><ns0:p>During the creation of a fully computerized, disease-focused report about ongoing or completed clinical studies, we observed several informatics themes described below. Before we describe individual lessons learned, we want to re-emphasize how computable representation of clinical study metadata is a crucial enabler for creating disease-based research snapshots. Moreover, several features of ClinicalTrials.gov registry proved to be highly valuable for our project. Such features are: structured representation of study metadata (XML and relational database format), registry support for result deposition and record updates, and legal and funding source policy requirements to maintain accurate registry records. In our analysis, we were able to build on prior clinical informatics research projects. Our project also shows value in further developing clinical informatics methods for data and metadata representation, semantic harmonization through terminologies and standards. The following informatics lessons were learned:</ns0:p><ns0:p>Updates: Our study is the first to analyze the frequency of updates to a study in CTG. We believe that adding the ability to access study updates to the CTG's API would be a useful addition. Our results indicate that analyzing study update activity is helpful in distinguishing studies with possibly outdated metadata (e.g., studies in status 'not yet recruiting' but are past their anticipated completion date with some grace period allowed for record updating). Our study is also the first to analyze update activity by country of study.</ns0:p><ns0:p>Intervention (free text): CTG collects intervention as free text and for some studies, provides a corresponding concept in Medical Subject Headings (MeSH) terminology. This intervention harmonization as MeSH concept is done post hoc rather than during study metadata entry by the study record manager. We found that the MeSH intervention concept is present in less than half (47%) of COVID-19 analyzed studies. This analysis prompted us to develop the denormalization and mapping method that we used.</ns0:p><ns0:p>Another intervention-related observation is the difference in how intervention combinations are listed in the free text field. In some cases, the combination intervention (e.g., 2 drugs given to some study group in combination) is recorded as two separate entries and the group or arm freetext description provides a way to clarify the combined usage. In other case the same intervention combination is recorded together as a single entry. This dual way of recording combined interventions formed our methodology for the most comprehensive approach of counting interventions (count them as both combinations and as separate interventions). We did not analyze arm description and so we did not combine separated interventions, which may have been assigned to the same arm and used in combination. This may possibly lead to the undercounting of certain intervention combinations.</ns0:p><ns0:p>Registries: We find valuable that CTG currently allows registration of observational studies and registries. Designing a user interface for registration and study representation format that can accommodate various designs and studies is a challenging task. Due to specific characteristics of certain study types, further customization of user interface or additional data quality checks may further improve the registry value to many stakeholders. For example, registries do not typically post one-time study results and may not have the same concept of primary completion date. Instead, annual or other regular interval updates about number of participants and summary results for participant flow may be more applicable. Clarifications in the user interface for entering interventions for registries (and for observational studies) may prevent entries which declare a formally drug typed intervention with the title 'no intervention'.</ns0:p></ns0:div> <ns0:div><ns0:head n='4.2.1'>Generalizing report to other diseases</ns0:head><ns0:p>Our emphasis on fully computerized analysis of a COVID-19 set of studies was motivated by our larger vision to apply the R scripted report for all MeSH encoded diseases found within the CTG registry. We refer to this result as the regCTG project and report repository. regCTG allows analysis of research by MeSH keyword for all clinical domains. We generated reports for all MeSH terms with at least 100 registered studies. A collection of nearly 1000 disease-based reports is available at https://github.com/lhncbc/CRI/tree/master/regCTG. We consider this generalization from a COVID-19 research report to a research report for nearly 1000 diseases an important result of our project.</ns0:p><ns0:p>In another follow-up research project for this COVID-19 case study, we have also built a disease-intervention snapshot knowledge base (called D-SHOT) that lists all interventions appearing in interventional trials for a given condition.('Project Repository for Disease Snapshot') This knowledge base of disease-intervention pairs has many parameters for each intervention, such as date when first introduced, count of regularly completed studies or count of unusually completed studies ('terminated', 'suspended', or 'withdrawn') studying that intervention. Experience from semantic harmonization of CTG's free text field into terminology concepts gained during this COVID-19 project was crucial in these two follow-up projects by our team. A related, non-open source project called Sherlock, proprietary to Johnson and Johnson is similarly parsing CTG's terms into formal concepts. <ns0:ref type='bibr'>(Cepeda, Lobanov &amp; Berlin, 2013)</ns0:ref> PeerJ reviewing PDF | (2020:06:50119:2:0:NEW 23 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='4.3'>Weekly results updates</ns0:head><ns0:p>While, the main analysis presented above was done on 11 May 2020 (main analysis date), thanks to the computed nature of the analysis, we have been producing weekly updated reports (available at the github repository). We have also been improving and adding to the automated report since the main analysis date based on the deposition of the first study results and the appearance of study results publications. As of the main analysis date, there were zero studies with results deposited on CTG. Because of data evolution during the article review and revision preparation, the latest weekly report on our github repository (as of 13 August 2020; update analysis date) now snows 3 interventional trials and one registry with results posted. Analysis of linked PubMed publications for completed interventional trials, found that of the 83 completed interventional trials at the point of secondary analysis, 9 had linked PubMed publications (10.8%).</ns0:p><ns0:p>For the weekly reports and data in our github repository, we welcome change requests submitted by interested researchers. For researchers re-using our code and interested in making modifications, a free registration to access the AACT database is required (obtainable within hours).</ns0:p></ns0:div> <ns0:div><ns0:head n='5'>Conclusions</ns0:head><ns0:p>We developed a computerized, data science driven approach to monitoring COVID-19 interventional trials, observational studies and registries. We report on several metrics for the 401 interventional trials, 287 observational studies and 64 registries as of our analysis date on 11 May 2020. More current and weekly refreshed data is available at our github repository. We also demonstrated that our COVID-19 disease focused report can be generalized to all diseases represented within a clinical trial registry. Manuscript to be reviewed Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head n='6'>Acknowledgement</ns0:head></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Figure 1.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>The study with the most sites was NCT04292730 ('Study to Evaluate the Safety and Antiviral Activity of Remdesivir in Participants With Moderate Coronavirus Disease (COVID-19) Compared to Standard of Care Treatment') with 183 sites.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>For example, COVID-19 Evidence Service from Centre for Evidence-Based Medicine at University of Oxford offers more comprehensive reviews. It was out of scope of our project to offer results comparable to human review. Fragkou et al. used a search and manual review methodology to compile and analyze a set of COVID-19 interventional trials and their interventions.(Fragkou et al., 2020) Checcucci et al. did a literature and clinical trial registries search based on built-in search criteria to review COVID-19 vaccine trials.(Checcucci et al., 2020) Rosa et al. did a manual search of CTG to analyze COVID-19 trials using repurposed interventions. Considering the existing published studies, we conclude that our study is the first study to rely solely on computerized data science methods to compile and analyze a set of COVID-19 interventional trials, observational studies and registries(Rosa &amp; Santos, 2020). Our approach of using computerized data science methods allows for the continuous monitoring of the current state of COVID-19 research with minimal additional effort compared to a resource intensive manual review methodology. During a continuously changing public health emergency, this ability for any researcher to quickly and efficiently monitor changes and trends in clinical research is invaluable in informing the direction of their research efforts.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='21,42.52,178.87,525.00,405.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='22,42.52,178.87,525.00,405.00' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>List of countries where COVID-19 interventional trials are conducted.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Country</ns0:cell><ns0:cell cols='2'>Study Count Percentage</ns0:cell></ns0:row><ns0:row><ns0:cell>United States</ns0:cell><ns0:cell>121</ns0:cell><ns0:cell>30.2%</ns0:cell></ns0:row><ns0:row><ns0:cell>China</ns0:cell><ns0:cell>49</ns0:cell><ns0:cell>12.2%</ns0:cell></ns0:row><ns0:row><ns0:cell>France</ns0:cell><ns0:cell>42</ns0:cell><ns0:cell>10.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Spain</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>5.7%</ns0:cell></ns0:row><ns0:row><ns0:cell>Italy</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>4.7%</ns0:cell></ns0:row><ns0:row><ns0:cell>Brazil</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Canada</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Iran, Islamic Republic of</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Germany</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>2.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>Mexico</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>2.00%</ns0:cell></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:06:50119:2:0:NEW 23 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Number of updates per study by country (for countries with at least 8 COVID-19 interventional trials)</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:06:50119:2:0:NEW 23 Sep 2020)Manuscript to be reviewed 1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Number of updates per study by country (for countries with at least 8 COVID-19 2 interventional trials) Country Total Updates Study Count Changes Per Study</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Canada</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.70</ns0:cell></ns0:row><ns0:row><ns0:cell>United States</ns0:cell><ns0:cell>213</ns0:cell><ns0:cell>121</ns0:cell><ns0:cell>1.76</ns0:cell></ns0:row><ns0:row><ns0:cell>Germany</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>1.75</ns0:cell></ns0:row><ns0:row><ns0:cell>Brazil</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>1.70</ns0:cell></ns0:row><ns0:row><ns0:cell>Spain</ns0:cell><ns0:cell>38</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>1.65</ns0:cell></ns0:row><ns0:row><ns0:cell>China</ns0:cell><ns0:cell>65</ns0:cell><ns0:cell>49</ns0:cell><ns0:cell>1.33</ns0:cell></ns0:row><ns0:row><ns0:cell>France</ns0:cell><ns0:cell>53</ns0:cell><ns0:cell>42</ns0:cell><ns0:cell>1.26</ns0:cell></ns0:row><ns0:row><ns0:cell>Iran</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>1.20</ns0:cell></ns0:row><ns0:row><ns0:cell>Mexico</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.88</ns0:cell></ns0:row><ns0:row><ns0:cell>Italy</ns0:cell><ns0:cell>13</ns0:cell><ns0:cell>19</ns0:cell><ns0:cell>0.68</ns0:cell></ns0:row></ns0:table><ns0:note>3PeerJ reviewing PDF | (2020:06:50119:2:0:NEW 23 Sep 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 3 (on next page)</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Overview of studies by study phase and number of participants (study size)</ns0:figDesc><ns0:table /><ns0:note>PeerJ reviewing PDF | (2020:06:50119:2:0:NEW 23 Sep 2020)Manuscript to be reviewed 1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Overview of studies by study phase and number of participants (study size) * IQR is interquartile range (1 st quartile [25 th percentile] and 3 rd quartile [75 th percentile]</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell># of participants:</ns0:cell><ns0:cell>3rd</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase</ns0:cell><ns0:cell cols='3'>Study Count Percentage 1st Qu.</ns0:cell><ns0:cell>median (IQR)*</ns0:cell><ns0:cell>Qu.</ns0:cell></ns0:row><ns0:row><ns0:cell>N/A</ns0:cell><ns0:cell>111</ns0:cell><ns0:cell>27.7%</ns0:cell><ns0:cell>49.5</ns0:cell><ns0:cell>120</ns0:cell><ns0:cell>330</ns0:cell></ns0:row><ns0:row><ns0:cell>Early Phase 1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>1.7%</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>40</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 1</ns0:cell><ns0:cell>17</ns0:cell><ns0:cell>4.2%</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>40</ns0:cell><ns0:cell>54</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 1/Phase 2</ns0:cell><ns0:cell>23</ns0:cell><ns0:cell>5.7%</ns0:cell><ns0:cell>20</ns0:cell><ns0:cell>72</ns0:cell><ns0:cell>190</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 2</ns0:cell><ns0:cell>108</ns0:cell><ns0:cell>26.9%</ns0:cell><ns0:cell>60</ns0:cell><ns0:cell cols='2'>145 273.75</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 2/Phase 3</ns0:cell><ns0:cell>34</ns0:cell><ns0:cell>8.5%</ns0:cell><ns0:cell>108</ns0:cell><ns0:cell cols='2'>269.5 433.5</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 3</ns0:cell><ns0:cell>74</ns0:cell><ns0:cell>18.5%</ns0:cell><ns0:cell>245</ns0:cell><ns0:cell>500</ns0:cell><ns0:cell>1215</ns0:cell></ns0:row><ns0:row><ns0:cell>Phase 4</ns0:cell><ns0:cell>27</ns0:cell><ns0:cell>6.7%</ns0:cell><ns0:cell>83</ns0:cell><ns0:cell>200</ns0:cell><ns0:cell>450</ns0:cell></ns0:row><ns0:row><ns0:cell>2</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>1</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_5'><ns0:head>Table 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Count of intervention types included in interventional trials Composite Intervention Type Study Count PercentageThis row combines rare Composite Intervention Types, such as 'Drug|Biological' , 'Dietary 3 Supplement', or 'Device|Procedure' (see repository report for full table of intervention types)('r-4 snippets-bmi/regCOVID at master &#8226; lhncbc/r-snippets-bmi') 5</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Drug</ns0:cell><ns0:cell>137</ns0:cell><ns0:cell>34.2%</ns0:cell></ns0:row><ns0:row><ns0:cell>Drug|Placebo</ns0:cell><ns0:cell>75</ns0:cell><ns0:cell>18.7%</ns0:cell></ns0:row><ns0:row><ns0:cell>Biological</ns0:cell><ns0:cell>32</ns0:cell><ns0:cell>8.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>Other</ns0:cell><ns0:cell>31</ns0:cell><ns0:cell>7.7%</ns0:cell></ns0:row><ns0:row><ns0:cell>Device</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>5.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Drug|Other</ns0:cell><ns0:cell>22</ns0:cell><ns0:cell>5.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Behavioral</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>3.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>Biological|Placebo</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>3.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>Diagnostic Test</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>2.5%</ns0:cell></ns0:row><ns0:row><ns0:cell>Procedure</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>2.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>All Other Types*</ns0:cell><ns0:cell>40</ns0:cell><ns0:cell>10.0%</ns0:cell></ns0:row><ns0:row><ns0:cell>2 *</ns0:cell><ns0:cell /><ns0:cell /></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:06:50119:2:0:NEW 23 Sep 2020)</ns0:note> <ns0:note place='foot' n='3'>PeerJ reviewing PDF | (2020:06:50119:2:0:NEW 23 Sep 2020)</ns0:note> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:06:50119:2:0:NEW 23 Sep 2020)</ns0:note> </ns0:body> "

"Dear Dr. Tatiana Tatarinova, We thank you and the reviewers for the additional comments and input on our previous revisions and the manuscript as a whole. We have revised our manuscript taking into account the additional comments. We are now submitting the revised version of our manuscript. See below our response to the reviewer’s comments. Our response are in bold font and follow the reviewer’s comments (shown in regular un-bolded text). Thank you, Craig Mayer and Vojtech Huser Even since authors greatly modified the results sections, it is still lack of the newly-added files e.g. regCOVID_data_file_descript.html, regCovid_tutorial.md and regCovid_example.R with links and short descriptions of the file content. We have added to the beginning of the results where we describe the data files, links to these additional files to give the reader easy access to the useful files developed and added to the descriptions to better explain the files and their usage. A huge perk to the understanding of the db structure should be considered a quick-start guide located at regCovid_tutorial.md, HTML with file descriptions located at https://lhncbc.github.io/r-snippets-bmi/regCOVID/regCOVID_data_file_descript.html and regCovid_example.R with example run. However, I failed to find these links in the paper, which can harm the overall impression of the paper. I would advise to aggregate response to reviewers and add them to the paper to make it more clear. The links to these files have now been added to the paper, to allow the reader to directly access these files and understand how they work and fit into the overall database structure. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The rapid assignment of genotypes to phenotypes has been a historically challenging process. The discovery of genes encoding biosynthetic pathway enzymes for defined plant specialized metabolites has been informed and accelerated by the detection of gene clusters. Unfortunately, biosynthetic pathway genes are commonly dispersed across chromosomes or reside in genes clusters that provide little predictive value. More reliably, transcript abundance of genes underlying biochemical pathways for plant specialized metabolites display significant coregulation. By rapidly identifying highly coexpressed transcripts, it is possible to efficiently narrow candidate genes encoding pathway enzymes and more easily predict both functions and functional associations. Mutual Rank-based coexpression analyses in plants accurately demonstrate functional associations for many specialized metabolic pathways; however, despite the clear predictive value of Mutual Rank analyses, the application is uncommonly used to drive new pathway discoveries.</ns0:p><ns0:p>Moreover, many coexpression databases aid in the prediction of both functional associations and gene functions, but lack customizability for refined hypothesis testing. To facilitate and speed flexible Mutual Rank-based hypothesis testing, we developed MutRank, an R Shiny web-application for coexpression analyses. MutRank provides an intuitive graphical user interface with multiple customizable features that integrates userprovided data and supporting information suitable for personal computers. Tabular and graphical outputs facilitate the rapid analyses of both unbiased and user-defined coexpression results that accelerate gene function predictions. We highlight the recent utility of Mutual Rank analyses for functional predictions and discoveries in defining two maize terpenoid antibiotic pathways. Beyond applications in biosynthetic pathway discovery, MutRank provides a simple, customizable and user-friendly interface to enable coexpression analyses relating to a breadth of plant biology inquiries. Data and code are available at GitHub: https://github.com/eporetsky/MutRank.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Visually-apparent biological complexity is greatly exceeded by the extreme diversity of specialized metabolites made by organisms for the mediation of essential biotic and abiotic interactions <ns0:ref type='bibr'>(Dixon, 2001;</ns0:ref><ns0:ref type='bibr'>Gershenzon &amp; Dudareva, 2007;</ns0:ref><ns0:ref type='bibr'>Pichersky &amp; Lewinsohn, 2011)</ns0:ref>. In plants, the ability to identify and control the production of specialized metabolites has significant implications for human health and agriculture; however, efficient tools aiding in biosynthetic pathway discovery remain limited <ns0:ref type='bibr'>(Dixon, 2001;</ns0:ref><ns0:ref type='bibr'>Moghe &amp; Kruse, 2018)</ns0:ref>. Clustering of plant specialized metabolism genes has historically been a useful, but not the sole, indicator of functional associations, and has accelerated the discovery of multiple specialized metabolite biosynthetic pathways <ns0:ref type='bibr'>(Frey, 1997;</ns0:ref><ns0:ref type='bibr'>Osbourn, 2010;</ns0:ref><ns0:ref type='bibr' target='#b4'>Boutanaev et al., 2015)</ns0:ref>. For the discovery of non-clustered metabolic pathway genes, coexpression analyses have emerged as a powerful predictive tool. Genes in specialized metabolic pathways are often highly coregulated based on developmental, spatial, environmental and complex regulatory controls <ns0:ref type='bibr'>(Schmelz et al., 2014;</ns0:ref><ns0:ref type='bibr'>Lacchini &amp; Goossens, 2020)</ns0:ref>. Genes that work together in functional specialized metabolic pathways are likely to require transcriptional coregulation and thus resulting patterns used to predict both functional associations and putative gene functions <ns0:ref type='bibr' target='#b6'>(Chae et al., 2014;</ns0:ref><ns0:ref type='bibr'>Wisecaver et al., 2017)</ns0:ref>. With increasingly affordable and accessible next generation sequencing technologies, new public and private custom large-scale transcriptomic datasets are routinely generated <ns0:ref type='bibr'>(Zhou et al., 2020)</ns0:ref>. Studies in plants often generate hundreds and even thousands of transcriptomic samples from different genotypes, developmental stages, tissues and physiological conditions to understand traits of agronomic significance <ns0:ref type='bibr'>(Sekhon et al., 2011;</ns0:ref><ns0:ref type='bibr'>Stelpflug et al., 2016;</ns0:ref><ns0:ref type='bibr'>Kremling et al., 2018;</ns0:ref><ns0:ref type='bibr'>Machado et al., 2020)</ns0:ref>. Moreover, genomes and transcriptomes from thousands of plant species are expected to speed large-scale gene expression experiments in poorly understood models <ns0:ref type='bibr'>(Twyford, 2018;</ns0:ref><ns0:ref type='bibr'>One Thousand Plant Transcriptomes Initiative, 2019)</ns0:ref>. Public and labspecific transcriptomic resources are far from static, instead they are continuously expanding and dynamic resources that require flexible tools for rapid and effective analyses.</ns0:p><ns0:p>Many databases and webtools, such as PLEXdb <ns0:ref type='bibr'>(Dash et al., 2012</ns0:ref><ns0:ref type='bibr'>), Genevestigator (Hruz et al., 2008)</ns0:ref>, <ns0:ref type='bibr'>PLANEX (Yim et al., 2013)</ns0:ref>, <ns0:ref type='bibr'>CORNET (De Bodt et al., 2010</ns0:ref><ns0:ref type='bibr'>, 2012)</ns0:ref>, ATTED-II <ns0:ref type='bibr'>(Obayashi et al., 2018</ns0:ref><ns0:ref type='bibr'>), COXPRESdb (Obayashi et al., 2012</ns0:ref><ns0:ref type='bibr'>), RiceFREND (Sato et al., 2013</ns0:ref><ns0:ref type='bibr'>), ePlant (Waese et al., 2017</ns0:ref><ns0:ref type='bibr'>) and STRING (Szklarczyk et al., 2019)</ns0:ref> have been developed to facilitate gene coexpression analyses. Coexpression analyses in studies and databases often use the Pearson's Correlation Coefficient (PCC) as a measure of coexpression. Mutual Rank (MR), the geometric mean of the ranked PCCs between a pair of genes, has been further proposed as an alternative measure of coexpression to PCC <ns0:ref type='bibr'>(Obayashi &amp; Kinoshita, 2009)</ns0:ref>. MR-based coexpression analyses provide better indication of functional associations and are more robust to inconsistencies caused by different microarray data processing methods compared to PCC-based coexpression analyses <ns0:ref type='bibr'>(Obayashi &amp; Kinoshita, 2009)</ns0:ref>. Collective findings have driven some coexpression databases to use MR as the primary measure of coexpression <ns0:ref type='bibr'>(Obayashi et al., 2012</ns0:ref><ns0:ref type='bibr'>(Obayashi et al., , 2018;;</ns0:ref><ns0:ref type='bibr'>Sato et al., 2013)</ns0:ref>. When the MR-and PCC-based coexpression databases of multiple plant species from ATTED-II <ns0:ref type='bibr'>(Obayashi et al., 2018)</ns0:ref> Manuscript to be reviewed accurately represent functional associations <ns0:ref type='bibr'>(Wisecaver et al., 2017)</ns0:ref>. MR-based coexpression networks enabled the accurate prediction of clusters enriched for enzymes associated with validated plant specialized metabolic pathways <ns0:ref type='bibr'>(Wisecaver et al., 2017)</ns0:ref>. Wisecaver et al. <ns0:ref type='bibr'>(Wisecaver et al., 2017)</ns0:ref> further demonstrate that MR analyses of transcripts are an improved and powerful tool for the functional prediction of unclustered biosynthetic pathway genes to serve as a springboard for hypothesis testing and validation.</ns0:p><ns0:p>While coexpression databases are useful, few enable flexible hypothesis testing and tool-based simplicity that integrates user-provided data and information. Data integration with coexpression results facilitates the meaningful interpretation of predicted functional associations and assignment of putative gene functions. For example, if a cytochrome P450 monoxygenase (CYP) is hypothesized to perform an oxidation step in a specific biosynthetic pathway, a user might ask 'which of all possible CYP transcripts is most highly coexpressed with an established pathway gene?'. More simply stated, any number of user-defined questions of targeted interest can be precisely examined. For any co-regulated process studied, the identification of 2-3 top candidates from a large gene family can greatly narrow efforts required for defined hypothesis testing and iterative re-testing. Towards this goal, we developed an R Shiny web-application, termed MutRank, to facilitate user control over both targeted and non-targeted MR-based coexpression analyses for rapid hypothesis testing. Using the R Shiny framework, we designed a flexible coexpression analysis platform that combines R packages to easily analyze and integrate userprovided expression data and information. Shiny web-applications are also advantageous for generating highly customizable and user-friendly interfaces that can run on most personal computers. In addition to identifying highly coexpressed genes in any user-provided dataset, Manuscript to be reviewed MutRank automatically integrates supporting information such as gene annotations, differentialexpression data, predicted protein domains and assigned Gene Ontology terms to provide useful tabular and graphical outputs as foundation for empirical hypothesis testing. Confirmed through diverse approaches, targeted and untargeted MR-based coexpression tools were recently leveraged to narrow gene candidates and accurately predict enzymes within multiple maize antibiotic biosynthetic pathways <ns0:ref type='bibr'>(Ding et al., 2019</ns0:ref><ns0:ref type='bibr'>(Ding et al., , 2020))</ns0:ref>. The goal of MutRank is to provide simple, customizable and readily accessible tools to speed research progress by using exploratory targeted coexpression analyses to predict gene functions and functional associations.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods</ns0:head><ns0:p>Software packages and example supporting information used -MutRank was developed as a web application using the Shiny R package (1.4.0.2) <ns0:ref type='bibr'>(Chang et al., 2020)</ns0:ref> that creates the user interface and manages navigation across the different application components (Fig. <ns0:ref type='figure' target='#fig_9'>1A</ns0:ref>). It requires R (3.4.0) and Java (Version 8 Update 261) to be installed by the user, and the following R packages will be automatically installed: shiny (1.4.0.2) <ns0:ref type='bibr'>(Chang et al., 2020)</ns0:ref>, hypergea (1.3.6) <ns0:ref type='bibr' target='#b3'>(Boenn, 2018)</ns0:ref>, ontologyIndex (2.5) <ns0:ref type='bibr'>(Greene, Richardson &amp; Turro, 2017)</ns0:ref> <ns0:ref type='table'>3</ns0:ref>). Additional supporting information can be selected in the main panel (Fig. <ns0:ref type='figure' target='#fig_9'>1A</ns0:ref>). As an example of analyzing a custom dataset, differential expression data was obtained for maize stems 24 hours after treatment with a fungal pathogen, specifically Southern leaf blight (SLB; Cochliobolus heterostrophus) (Ding et al., 2019) (Supplemental Table <ns0:ref type='table'>4</ns0:ref>). The predicted Pfam protein domain annotations and GO term assignments are derived from the Phytozome database (Goodstein et al., 2012) (Supplemental Table <ns0:ref type='table'>5-6</ns0:ref>). The GO-basic and Plant-GO-Slim ontologies are from the GO Consortium <ns0:ref type='bibr'>(Ashburner et al., 2000;</ns0:ref><ns0:ref type='bibr' /> The Gene Ontology Consortium, 2019). Lists of maize terpene synthases (TPS) <ns0:ref type='bibr'>(Ding et al., 2020)</ns0:ref>, cytochrome P450s (CYP) <ns0:ref type='bibr'>(Ding et al., 2019)</ns0:ref> and Pfam protein domains associated with specialized metabolism (SM) <ns0:ref type='bibr'>(Wisecaver et al., 2017)</ns0:ref> were used as categories to assign to coexpressed genes (Supplemental Table <ns0:ref type='table'>7</ns0:ref>).</ns0:p><ns0:formula xml:id='formula_0'>, reshape2 (1.4.3) (Wickham, 2007), RColorBrewer (1.1-2) (Neuwirth, 2014), data.table (1.12.8) (Dowle &amp; Srinivasan, 2020), ggplot2 (3.3.0) (Wickham 2016), visNetwork (2.0.9) (Almende B.V., Thieurmel &amp; Robert, 2019), igraph (1.2.</ns0:formula><ns0:p>Calculating Mutual Rank values -MutRank was developed as a user-friendly tool to quickly identify the most highly coexpressed genes based on MR values for any reference gene and expression dataset. One of the limitations of MutRank is that it does not calculate all pair-wise MR values. Unlike coexpression databases that pre-calculate all pair-wise MR values <ns0:ref type='bibr'>(Obayashi et al., 2012</ns0:ref><ns0:ref type='bibr'>(Obayashi et al., , 2018;;</ns0:ref><ns0:ref type='bibr'>Sato et al., 2013)</ns0:ref>, calculating all pair-wise MR values on the resources available on most personal computers is impractical. Instead, MutRank calculates all PCC values between the user-provided reference gene and all other genes to generate a limited list of genes with the highest PCC values (top 200 genes by default, maximum 1000) for which it is feasible to calculate MR values. This practical trade-off between whole-genome and targeted coexpression analyses allows MutRank to rapidly complete calculations and to run on the resources of most personal computers. In addition to using a single reference gene, MutRank offers two additional methods for user-defined reference gene sets (Fig. <ns0:ref type='figure' target='#fig_10'>1B-2</ns0:ref>). The first method calculates the MR values between all genes in the reference gene set. The second method creates a novel compound reference gene from the average, sum, maximum or minimum expression values of the reference gene set. Using compound reference genes is important for capturing pangenome patterns with key gene family members displaying highly variable expression across the analyzed germplasm <ns0:ref type='bibr'>(Ding et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Integrating user-provided supporting information -As an exploratory targeted coexpression analysis tool, MutRank integrates user-provided supporting information with the identified list of coexpressed genes (Fig. <ns0:ref type='figure' target='#fig_9'>1B</ns0:ref>). Users can provide gene annotations and symbols as easy-to-read information connected to the identified list of coexpressed genes. Additional supporting information in the form of lists of differentially-expressed genes, predicted Pfam domains and assigned Gene Ontology (GO) terms can be integrated with the coexpressed genes. Users can also define custom categories made from lists of genes, Pfam domains or GO terms. The goal of assigning a gene in the MR-based coexpression results as belonging to any of the categories is to have a noticeable indication that the gene is either present in the gene list or is assigned at least one of the Pfam protein domains or GO terms.</ns0:p></ns0:div> <ns0:div><ns0:head>Tabular and graphical outputs for coexpression analyses -</ns0:head><ns0:p>The primary output is provided in the form of an MR coexpression table (Fig. <ns0:ref type='figure' target='#fig_9'>1C</ns0:ref>). User-provided supporting information can be automatically integrated into the table in separate columns for each of the coexpressed genes.</ns0:p><ns0:p>The results from the MR coexpression table are used as the basis for three additional informative outputs: heatmap, network graph and a GO enrichment table (Fig. <ns0:ref type='figure' target='#fig_9'>1C</ns0:ref>). The heatmap, generated using ggplot2 (Wickham 2016), provides an overview of the distribution of MR values among the top coexpressed genes. The R igraph package <ns0:ref type='bibr'>(Csardi &amp; Nepusz, 2005)</ns0:ref> is used to convert the coexpression table into a coexpression network and to annotate the gene vertices with userprovided data. The network graph visualization is produced with visNetwork package <ns0:ref type='bibr' target='#b0'>(Almende B.V., Thieurmel &amp; Robert, 2019)</ns0:ref> which allows the user to explore a dynamic network representation with supporting information. GO term enrichment is calculated using the hypergeometric test based on the GO database and all genes with MR values below a userprovided threshold (default MR &lt; 100). The P-values are adjusted for false discovery rate (FDR) and the results are presented in a separate table.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Example workflow 1: Integrating coexpression analyses of genes encoding a specialized metabolic pathway with supporting information. In maize and other important grain crops, benzoxazinoids (BXs) are a highly-studied class of nitrogen-containing specialized metabolites with critical roles in plant protection against both herbivores and pathogens <ns0:ref type='bibr'>(Frey, 1997;</ns0:ref><ns0:ref type='bibr'>Meihls et al., 2013;</ns0:ref><ns0:ref type='bibr'>Wouters et al., 2016)</ns0:ref>. Genes underlying early steps in the maize BX biosynthetic pathway, namely Bx1 to Bx8, are consitutively expressed in seedlings and drive the production of 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one glucoside (DIMBOA-Glc). A majority of these genes, Bx1 to Bx5 and Bx8, are located together on chromosome 4 and represent the first Manuscript to be reviewed biosynthetic gene cluster ever described in plants <ns0:ref type='bibr'>(Frey, 1997;</ns0:ref><ns0:ref type='bibr'>Dutartre, Hilliou &amp; Feyereisen, 2012)</ns0:ref>. In contrast to largely constitutive production, the late stage BX pathway, namely Bx10 to Bx14 and encoded enzymes, display stress-inducible regulation resulting in the conversion of DIMBOA substrates to 2-(2-hydroxy-4,7dimethoxy-1,4-benzoxazin-3-one)-&#61538;-D-glucopyranose (HDMBOA-Glc) and 2-(2-hydroxy-4,7,8trimethoxy-1,4-benzoxazin-3-one)-&#61538;-D-glucopyranose (HDM 2 BOA-Glc), which upon aglycone liberation (HDMBOA and HDM 2 BOA) result in highly unstable bioactive molecules <ns0:ref type='bibr'>(Maresh, Zhang &amp; Lynn, 2006;</ns0:ref><ns0:ref type='bibr'>Meihls et al., 2013;</ns0:ref><ns0:ref type='bibr'>Wouters et al., 2016)</ns0:ref>. While displaying complex regulation of early-and late-stage Bx genes influenced by development and biotic stress <ns0:ref type='bibr' target='#b5'>(Cambier, Hance &amp; de Hoffmann, 2000;</ns0:ref><ns0:ref type='bibr'>Wouters et al., 2016)</ns0:ref>, BX1 to BX14 collectively catalyze the production of multiple glucoside conjugates that can ultimately act as aglycone defenses <ns0:ref type='bibr'>(Frey, 1997;</ns0:ref><ns0:ref type='bibr'>Jonczyk et al., 2008;</ns0:ref><ns0:ref type='bibr'>Meihls et al., 2013;</ns0:ref><ns0:ref type='bibr'>Handrick et al., 2016)</ns0:ref>. The gene Bx1 encodes an indole-3-glycerol phosphate lyase that cleaves indole-3-glycerolphosphate into free indole, acting as the first committed step in the pathway <ns0:ref type='bibr'>(Frey, 1997)</ns0:ref>.</ns0:p><ns0:p>As an example to demonstrate both the power and remaining challenges of using Mutual Ranks to associate pathway genes to one another, we use the reference gene list method to investigate the coexpression of Bx1 with other Bx pathway genes (Fig. <ns0:ref type='figure' target='#fig_10'>2A</ns0:ref>, Supplemental Table <ns0:ref type='table'>8</ns0:ref>). Users can select which supporting information to automatically integrate with the MR coexpression table generated (Fig. <ns0:ref type='figure' target='#fig_10'>2A</ns0:ref>). The final coexpression table includes columns with the MR values in reference to the first gene in the list (i.e. Bx1), gene symbols and gene annotations, and excludes the categories and fold-change columns (Fig. <ns0:ref type='figure' target='#fig_10'>2A</ns0:ref>). Bx6 and Bx7 were excluded from the coexpression analysis as they were not included in the expression dataset used for this analysis. </ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The coexpression results in the table can be visualized as a coexpression heatmap that readily reveals the highly coexpressed gene cluster of Bx1 through Bx5 and Bx8, as well as separate coexpression of Bx10, Bx11 and Bx13 with one another (Fig. <ns0:ref type='figure' target='#fig_10'>2B</ns0:ref>). Similar association patterns can also be observed using an interactive coexpression network with an MR &lt; 100 threshold for drawing edges between vertices (Fig. <ns0:ref type='figure' target='#fig_10'>2C</ns0:ref>). Using the validated BX pathway as a simplistic MutRank example, we demonstrate the following: 1) the ease of observing strong co-expression of early Bx pathway genes, 2) the partial coexpression of late Bx pathway genes, and 3) remaining challenges of bioinformatically-connecting complex pathways that display differential regulation of early and late steps (Fig. <ns0:ref type='figure' target='#fig_10'>2D</ns0:ref>) <ns0:ref type='bibr'>(Meihls et al., 2013;</ns0:ref><ns0:ref type='bibr'>Handrick et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Importantly, biosynthetic pathways function within the complex context of a living cell. The value in confirming established coexpression patterns is to first undertand how the user-defined dataset is performing. When compelling, these results then encourage further interrogation to address diverse hypotheses and complex surrounding processes, potentially identifying coexpressed transcription factors, transporters, or detoxification enzymes to investigate <ns0:ref type='bibr'>(Lacchini &amp; Goossens, 2020)</ns0:ref>.</ns0:p><ns0:p>Example workflow 2: Using MutRank to predict enzymes in specialized metabolism. In the first example, we used BX-related defenses which have been studied in maize and other cereals for over 60 years <ns0:ref type='bibr'>(Virtanen et al., 1955;</ns0:ref><ns0:ref type='bibr'>Smissman, LaPidus &amp; Beck, 1957)</ns0:ref>. More recently, maize diterpenoid pathways have been implicated in diverse protective roles providing fungal, insect and drought resistance <ns0:ref type='bibr'>(Schmelz et al., 2011;</ns0:ref><ns0:ref type='bibr'>Vaughan et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b9'>Christensen et al., 2018;</ns0:ref><ns0:ref type='bibr'>Ding et al., 2019)</ns0:ref>. Biosynthesis of protective ent-kaurane-related diterpenoids in maize, termed kauralexins, are mediated by multi-gene terpene synthase (TPS) and cytochrome P450 <ns0:ref type='table'>8</ns0:ref>), that encodes an ent-copalyl diphosphate synthase (ent-CPS) responsible for the cyclization of geranylgeranyl diphosphate into bicyclic pathway precursor ent-copalyl diphosphate (ent-CPP) <ns0:ref type='bibr'>(Harris et al., 2005)</ns0:ref>. Derived from 2 different genes encoding ent-CPS, ent-CPP is a key substrate shared by the kauralexin, dolabralexin and gibberellin biosynthetic pathways in maize <ns0:ref type='bibr'>(Mafu et al., 2018;</ns0:ref><ns0:ref type='bibr'>Ding et al., 2019)</ns0:ref>. Using ZmAN2 as a reference gene, we calculated the nontargeted MR values between the top 200 coexpressed genes and integrated the supporting information (Fig. <ns0:ref type='figure' target='#fig_11'>3A</ns0:ref>). For simplification, we then selected the first 12 coexpressed genes and identified 1 TPS gene (Fig. <ns0:ref type='figure' target='#fig_11'>3A and 3B</ns0:ref>: diamond shaped vertex), a type I diterpene synthase: kaurene synthase-like 2 (ZmKSL2) and 2 CYP genes (Fig. <ns0:ref type='figure' target='#fig_11'>3A</ns0:ref> and 3B: square shaped vertices), ZmCYP71Z18 and kaurene oxidase 2 (ZmKO2) that were highly coexpressed (Fig. <ns0:ref type='figure' target='#fig_11'>3A-C</ns0:ref>). A GO-term enrichment analysis of the MR-based coexpression results using the GO-basic database revealed an enrichment of terms associated with defense responses and terpene synthesis (Fig. <ns0:ref type='figure' target='#fig_11'>3D</ns0:ref>). With candidates identified through similar MR-based coexpression relationships to those currently presented (Fig. <ns0:ref type='figure' target='#fig_11'>3A-E</ns0:ref>), a recent study of kauralexin biosynthetic enzymes were systematically validated using genome wide association studies, heterologous enzyme coexpression assays, proteomics and characterization of defined genetic mutants <ns0:ref type='bibr'>(Ding et al., 2019)</ns0:ref>. Two additional genes with defined roles in kauralexin biosynthesis that did not match any of the supporting information categories are the ZmCYP71Z16 that is absent from the currently selected expression dataset and the coexpressed kauralexin reductase2 (ZmKR2) encoding a 5&#61537;steroid reductase that saturates B-series kauralexins (Fig. <ns0:ref type='figure' target='#fig_11'>3A-C</ns0:ref>) <ns0:ref type='bibr'>(Ding et al., 2019)</ns0:ref>. Together the combined use of MR analyses with biochemistry and defined genetic mutants defined roles for Manuscript to be reviewed ZmAn2, ZmKSL2, ZmKO2, ZmKR2, ZmCYP71Z18 and ZmCYP71Z16 in kauralexin biosynthesis and anti-pathogen defense enabling rapid assembly of the entire pathway (Fig. <ns0:ref type='figure' target='#fig_11'>3E</ns0:ref>) <ns0:ref type='bibr'>(Ding et al., 2019)</ns0:ref>. Additional genes identified in the MR-based coexpression analysis encode predicted carrier proteins, pathogenesis-related proteins and kinases that might further contribute to the regulation and transport of diterpenoids (Fig. <ns0:ref type='figure' target='#fig_11'>3A-C</ns0:ref>). In summary, straightforward MR analyses via MutRank provide a powerful starting point for defining networks surrounding specialized metabolism.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>MutRank is a user-friendly and powerful tool for exploratory targeted gene coexpression analyses. MutRank enables the simple calculation of MR values for any reference gene or gene set from user-provided expression data. The Shiny web-application interface is ideal for combining MR-based coexpression analyses with useful R packages that produce informative tabular and graphical outputs. We implemented a number of features that allow users to integrate supporting information with the results of the coexpression analyses to facilitate prediction of putative gene functions. Example workflow 1 surveyed genes in the well-established maize BX biosynthetic pathway. Many of these genes were identified and characterized without the benefit of large-scale transcriptomic data <ns0:ref type='bibr'>(Frey, 1997)</ns0:ref>. The lack of coexpression connections between early and late stage Bx biosynthetic genes (Fig. <ns0:ref type='figure' target='#fig_10'>2A-D</ns0:ref>) likely provides a partial explaination for the relatively recent discovery of the terminal steps <ns0:ref type='bibr'>(Meihls et al., 2013;</ns0:ref><ns0:ref type='bibr'>Handrick et al., 2016)</ns0:ref>. Manuscript to be reviewed currently unknown functions. Example workflow 2 was given as an example where MR-based coexpression analyses were used to guide recent hypothesis testing, and through a combination of diverse approaches, were demonstrated to correctly predict gene functions in the maize kauralexin antibiotic pathway <ns0:ref type='bibr'>(Ding et al., 2019)</ns0:ref>. Importantly, we note here that custom use of further expression datasets were used to correctly predict the function of an additional kauralexin biosynthetic genes (ZmCYP71Z16) within the pathway using MR-based coexpression analyses <ns0:ref type='bibr'>(Ding et al., 2019)</ns0:ref>. In Ding et al. 2019 the expression datasets were derived from the National Center for Biotechnology Information Sequence Read Archive project IDs SRP115041 and SRP011480. This esoteric detail speaks to an essentail point. Different MR coexpression patterns can be found in related datasets depending on sample size, plant growth conditions, genotypes used, tissue types, cell types, developemental age, presence or absence of biotic or aboitic stress and countless other factors important to the questions being examined. Given this, aggregate estimations of gene co-expression available on public websites typically fall short in facilitating elucidation of relationships of interest. Rapid progress requires flexible control over the analyses of precise data subsets or of larger aggregated datasets for cross-comparison. MutRank allows for a large number of different datasets to be selected, and quickly analzyed and assessed. Most commonly, the search for meaningful coexpression relationships, whether of biosynthetic genes or for more complex regulatory processes, is a guided and highly iterative discovery process, relying on partial insights from related experimental systems. A common goal is to generate high-quality gene candidates for improved hypothesis testing that ultimately informs more Manuscript to be reviewed kauralexin biosynthetic genes <ns0:ref type='bibr'>(Ding et al., 2020)</ns0:ref>. Research progress in plant specialized metabolism requires rapid, flexible and easy-to-use tools, through which diverse users of varying expertise levels can quickly compare results generated from public or customized user-provided datasets. We now routinely utilize MutRank as a rapid tool for exploratory targeted coexpression analyses facilitating the prediction of functional associations and putative gene functions. The goal of our current effort was to expand the ease and use of the R Shiny web-application tools to facilitate efforts of any biologists who seek to connect coregulated genes to important phenotypes.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusion</ns0:head><ns0:p>The MutRank R Shiny web application provides an efficient, flexible and simple tool for conducting hypothesis-driven MR-based coexpression analyses. To enable rapid functional discovery, MutRank analyses are integrated with multiple customizable features for narrowing and prioritizing candidate genes and for hypothesis testing in predicted biochemical functions. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>were converted into coexpression networks and compared, the MR-based coexpression networks were more comparable than PCC-based coexpression networks across species, suggesting that MR-based coexpression networks PeerJ reviewing PDF | (2020:08:52213:1:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:52213:1:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>4.2)(Csardi &amp; Nepusz, 2005) and shinythemes (1.1.2)<ns0:ref type='bibr' target='#b7'>(Chang, 2018)</ns0:ref>. To explain the features included in MutRank and to understand the required filestructures we provide example expression data and supporting information. All the files used for examples are based on the Zea mays inbred B73 (RefGen_v3) genome annotation. The expression data is from the Expanded Maize Gene Expression Atlas (Stelpflug et al., 2016) (Fig. 1A, Supplemental Table 1), gene annotations from the Phytozome database (Goodstein et al., 2012) (Fig. 1A, Supplemental Table 2), and gene symbols from MaizeGDB (Portwood et al., 2019) (Fig. 1A, Supplemental Table</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:52213:1:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:52213:1:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:52213:1:0:NEW 25 Sep 2020) Manuscript to be reviewed (CYP) families. Using MR-based coexpression analyses for discovery purposes (Ding et al., 2019) we examined one reference gene termed anther ear 2 (ZmAN2) (Supplemental Table</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:08:52213:1:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>Public coexpression databases and tools, such as MutRank, provide intuitive user control overMR-based coexpression analyses to drive predictions and hypothesis testing of genes withPeerJ reviewing PDF | (2020:08:52213:1:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head /><ns0:label /><ns0:figDesc>expensive and time-consuming in planta analyses of defined mutants. As a further recent example, MR-based coexpression analyses were leveraged and played a key role in defining and disentangling a challenging 10-gene maize sesquiterpenoid antibiotic pathway partially sharing PeerJ reviewing PDF | (2020:08:52213:1:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> </ns0:body> "

"Reviewer 1 Basic reporting The article is well written with very few grammatical errors. It provides a good background of the field in the introduction and has sufficient citations to previous literature throughout. Figures are clear and legends provided a good description of the figures. The introduction provides a nice background on coexpression analyses and methods used to explore datasets to find genes and pathways of interest. It highlights the Mutual Rank method of measuring coexpression and describes the utility of MutRank for coexpression analysis and visualization of results. Line 76 - double word Reply: It has been corrected. Line 78 - Awkward sentence structure Reply: We appreciate the reviewer comment and agree that the sentence could be improved. The sentence now reads: “Collective findings have driven some coexpression databases to use MR as the primary measure of coexpression.” Experimental design MutRank is coded in R, which makes it relatively accessible to a scientist doing this type of research. It should be simple to integrate into existing analysis pipelines and launch the Shiny visualization tool to further analyze the results. I was able to download MutRank and be up and running with the example dataset in a matter of minutes. The documentation is thorough on what data formatting is necessary and example datasets make it easy to emulate the necessary format for input into the application. The application looks coded in a straightforward way that would make it relatively extensible for future researchers to add other types of scoring algorithms and analyses. Validity of the findings No comment Reviewer 2 Basic reporting The manuscript was written in unambiguous English and easy to read. Given that this is a manuscript to introduce new analysis tool (and therefore I do not think authors need to review background biological context in detail), I think literatures provided are good enough. Raw dataset (i.e., sample data) to replicate their results is provided. Two examples were illustrated to show their MutRank application is powerful and user-friendly tool to analyze expression data. Experimental design The manuscript may meet the scope of PeerJ journal, as the illustrated R-shiny application will contribute to many biologists to analyze their expression data. As authors mentioned in the introduction section, it is important to develop a flexible and user-friendly tool. The authors clearly explained how to use MutRank application (such as what kind of input data is needed, what kind of parameters to be specified, and what kind of results to be generated), while some of the implemented statistical methods should be clearly explained. For example: [2.1] In line 149, what is the definition of “top coexpressed genes”? As correlation is assigned for each “pair of two genes”, I could not understand how to define coexpressed genes (e.g., there are top 200 gene pairs showing largest correlation, but what are the top 200 genes?) Reply: We thank the reviewer for the comment. We agree that because both PCC and MR values are a measure of coexpression it is not clear which method “top coexpressed genes” refers to. To clarify, the “top coexpressed genes” refers to the list of genes with the highest PCC values with a given reference gene. The modified part in the method section now reads: “One of the limitations of MutRank is that it does not calculate all pair-wise MR values. Unlike coexpression databases that pre-calculate all pair-wise MR values (Obayashi et al. 2012, 2012; Sato et al. 2013), calculating all pair-wise MR values on the resources available on most personal computers is impractical. Instead, MutRank calculates all PCC values between the user-provided reference gene and all other genes to generate a limited list of genes with the highest PCC values (top 200 genes by default, maximum 1000) for which it is feasible to calculate MR values.” [2.2] In line 181, please describe GO term enrichment analysis more clearly. In the enrichment analysis, we have “full set” (such as all genes in the database or all genes in our dataset) and “subset” (such as genes in a module or genes coexpressed with a gene of interest). According to your example 2, I guess you used all genes in the GO database as a full set, but it is not clear. Reply: We thank the reviewer for the comment and agree that by writing “… using the full GO database” it could be implied that under some circumstances we use a subset of the database to conduct the hypergeometric test, which was not our intention. All GO term enrichment calculations using the hypergeometric test use the basic required 4 numerical values: 1) Total number of genes in the GO database, 2) total number of genes in the GO database containing the specific GO term, 3) total number of genes with MR ≤ threshold and 4) total number of genes with MR ≤ threshold containing the specific GO term. The revised sentences at line 181 now read: “GO term enrichment is calculated using the hypergeometric test based on the GO database and all genes with MR values below a user-provided threshold (default MR ≤ 100). The P-values are adjusted for false discovery rate (FDR) and the results are presented in a separate table.” The revised Figure 3D legend now reads: “The hypergeometric test was used to calculate P-values for GO term enrichment based on the GO-basic database and all genes with MR ≤ 100. The P-values were adjusted using the Bonferroni–Holm method and showed that the top 5 enriched GO terms are associated with biotic stress responses.” There are some additional small comments on the methods. See the general comments section. Validity of the findings The authors provided two examples, which were used in previous studies, to illustrate the usage and potential of the MutRank application. The results imply that MutRank is a powerful tool to analyze expression data to find a biologically meaningful relationship among genes. Conclusion is clearly stated and supported from the two examples. Comments for the Author For me, who usually analyzes expression data in R, the implemented methods (such as calculation of mutual rank, data visualization via heatmap or network analysis, and the GO enrichment analysis) in this shiny application are not new. However, as there are many biologists or biochemists who is not good at using R, I agree that this application will be helpful for many researchers. Methods and results are clearly explained so that everyone can use this application. I have some minor comments to be addressed. Read the below: [4.1] Line 59: Add period after the citation “et al. 2020). Studies in plants” Reply: It has been corrected. [4.2] Line 76: Remove one of the duplicated “analyses” Reply: It has been corrected. [4.3] Line 76-77: Is the phrase “produce improved results when using raw data compared to PCC” correct? Was the raw data better than PCC? Reply: We thank the reviewer for inquiring about the validity of this statement. We agree that the use of the term “raw data” is ambiguous and should be improved. The intended message was that inferring biological significance from PCC values was more sensitive to different microarray data processing methods (i.e. raw data) compared to the more robust results produced when using MR values. The revised sentence now reads: “MR-based coexpression analyses provide better indication of functional associations and are more robust to inconsistencies caused by different microarray data processing methods compared to PCC-based coexpression analyses” [4.4] Line 111-113: This is an optional comment. I am not comfortable with the wrap-up sentence “The goal of MutRank is to... biological goals”, because what we can get from MutRank is the coexpressed genes. Probably you implied GO enrichment analysis by the phrase “connecting metabolic phenotypes to genotypes”, but I am not sure if this phrase is appropriate. When reading this phrase at the first time, I thought that we can analyze some phenotypes (e.g., metabolite abundance measured by mass spectrometry) in this application. Find another phrase if possible. Reply: We thank the reviewer for the comment, and we have restated this sentence to read: “The goal of MutRank is to provide simple, customizable and readily accessible tools to speed research progress by using exploratory targeted coexpression analyses to predict gene functions and functional associations.” [4.5] Line 178: For the coexpression network visualization, how do you draw edges among genes? Do you simply draw edges between genes with smaller MR value than a threshold? Or do you somehow use PCC? Reply: We simply use an MR value threshold to draw edges between genes. [4.6] Line 217: It may be better to rephrase “... displayed, as they are absent from the currently selected expression dataset”. I guess you did not include Bx6 and Bx7 in this analysis from the beginning (as they are not in the list of supplementary table 8), because the maize expression dataset (supplementary table 1) does not have these two genes. Then, for example, you should write “Bx6 and Bx7 were excluded from the analysis as they were not included in the expression dataset for this analysis.” (I mean, the word “displayed” may not be appropriate) Reply: We thank the reviewer for comment and suggestion. The sentence now reads: “Bx6 and Bx7 were excluded from the coexpression analysis as they were not included in the expression dataset used for this analysis.” [4.7] Line 221: Is the threshold 25 correct? In the supplementary document, it seems you used 100. Please confirm and make correction if needed. Reply: We thank the reviewer for observing this mistake. We have corrected it to “MR ≤ 100” in line 221 and in the figure 2C legend. [4.8] Line 249: I think you should not include ZmAN2 in the identified genes, because it is trivial that ZmAN2 is included as a top gene (self-correlation is always one). You should write “identified one additional TPS gene” (and describe it; type I diterpene synthase). Reply: We agree with the reviewer comment that it is redundant to include the reference gene ZmAN2 in the list of coexpressed genes. The sentence now reads: “For simplification, we then selected the first 12 coexpressed genes and identified 1 TPS gene (Fig. 3A and 3B: diamond shaped vertex), and a type I diterpene synthase: kaurene synthase-like 2 (ZmKSL2) and 2 CYP genes (Fig. 3A and 3B: square shaped vertices), ZmCYP71Z18 and kaurene oxidase 2 (ZmKO2) that were highly coexpressed (Fig. 3A-C).” [4.9] Line 256: No need to abbreviate GWAS. This is only used in this sentence, as far as I checked (or you have GWAS in your supplementary files? Then keep this as it is.). Reply: Thank you for noting this. We have removed the GWAS abbreviation as it is not mentioned anywhere else in the paper. [4.10] Line 199, 200, and 261: Some letters are not displayed in the PDF file. Reply: Thank you for noting this. We have changed the font of these symbols to match the rest of the text and think it will solve the PDF conversion error. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. Melanoma is a malignant tumor of melanocytes, and the incidence has increased faster than any other cancer over the past half century. Most primary melanoma can be cured by local excision, but metastatic melanoma has a poor prognosis. Cutaneous melanoma(CM) is prone to metastasis, so the research on the mechanism of melanoma occurrence and metastasis will be beneficial to diagnose early, improve treatment, and prolong life survival. In this study, we compared the gene expression of normal skin (N), primary cutaneous melanoma (PM) and metastatic cutaneous melanoma (MM) in the Gene Expression Omnibus (GEO) database. Then we identified the key genes and molecular pathways that may be involved in the development and metastasis of cutaneous melanoma, thus to discover potential markers or therapeutic targets. Methods. Three gene expression profiles (GSE7553, GSE15605 and GSE46517) were downloaded from the GEO database, which contained 225 tissue samples. R software identified the differentially expressed genes (DEGs) between pairs of N, PM and MM samples in the three sets of data. Subsequently, we analyzed the gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of the DEGs, and constructed a protein-protein interaction (PPI) network. MCODE was used to seek the most important modules in PPI network, and then GO function and KEGG pathway of them were analyzed. Finally, the hub genes were calculated by the cytoHubba in Cytoscape software. The Cancer Genome Atlas (TCGA) data were analyzed using UALCAN and GEPIA to validate the hub genes and analyze the prognosis of patients. Results. 134, 317 and 147 DEGs were identified between N, PM and MM in pair, through GO functions and KEGG pathways the upregulated DEGs mainly concentrated in cell division, spindle microtubule, protein kinase activity and the pathway of transcriptional misregulation in cancer. The downregulated DEGs mainly occurred in epidermis development, extracellular exosome, structural molecule activity</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Cutaneous melanoma (CM) is the most dangerous type of skin cancer. It accounts for approximately 232,100 new cases of CM around the world each year, including 55,500 deaths <ns0:ref type='bibr' target='#b0'>[1]</ns0:ref> , and it ranks 15th among the most common cancers in the world <ns0:ref type='bibr' target='#b1'>[2]</ns0:ref> . CM is one of the most aggressive and metastatic human cancers, and compared with other cancer types, it can spread from a small primary tumor to multiple sites throughout the body <ns0:ref type='bibr' target='#b2'>[3]</ns0:ref> . Although primary cutaneous melanoma can be removed and cured through the operation, when a few millimeters thick skin lesion is found, it represents an advanced stage, and there is a high chance of distant visceral metastasis <ns0:ref type='bibr' target='#b3'>[4]</ns0:ref> . Once metastatic foci are established in distant organs, the 5-year overall survival rate of melanoma patients drops sharply to less than 10% <ns0:ref type='bibr' target='#b4'>[5]</ns0:ref> . Therefore, it is urgent to identify the mechanisms that drive the occurrence and metastasis of CM, and to develop effective therapeutic strategies. Studies had classified the somatic mutations and expression profiles of metastatic melanoma <ns0:ref type='bibr' target='#b5'>[6]</ns0:ref> , but the mechanisms of CM evolution and metastasis have not been fully understood <ns0:ref type='bibr' target='#b6'>[7]</ns0:ref> . Understanding the gene expression changes during the development of CM will help to develop new biomarkers and therapeutic targets for the diagnosis and treatment of patients.</ns0:p><ns0:p>Gene expression microarray technology can be used to understand the biology associated with cancers, gene mutations and abnormal biological pathways, as well as to predict the diagnosis, treatment, prognosis or metastasis of patients <ns0:ref type='bibr' target='#b8'>[8]</ns0:ref> . The results of microarray technology provide a wealth of information, thus, the data stored in public databases can be reintegrated and bioinformatics analyzed to search for new clues about the pathological mechanisms of cancers through computers rather than laboratories <ns0:ref type='bibr' target='#b9'>[9]</ns0:ref> . In recent years, a large number of studies have predicted the key genes, signaling pathways and protein functions <ns0:ref type='bibr' target='#b11'>[10]</ns0:ref> of many cancers by analyzing the patients' genetic profiles. For example, the pathogenesis and metastasis mechanism of colorectal cancer <ns0:ref type='bibr' target='#b12'>[11]</ns0:ref> , prostate cancer <ns0:ref type='bibr' target='#b13'>[12]</ns0:ref> , breast cancer <ns0:ref type='bibr' target='#b14'>[13]</ns0:ref> and other cancers had been explored. A number of studies have done bioinformatics analysis of CM. Chen et al. <ns0:ref type='bibr' target='#b15'>[14]</ns0:ref> compared the DEGs between normal skin and melanoma, then used bioinformatics methods to analyze and identify the pathogenesis of CM. Wang et al. <ns0:ref type='bibr' target='#b16'>[15]</ns0:ref> compared the expression of CD38 in the tissues of healthy people and melanoma patients in the TCGA database, and analyzed the occurrence of subtypes and promoter methylation, so as to conclude that CD38 may be a potential biomarker for CM. Some studies obtained differentially expressed non-coding RNAs by analyzing the microRNA and lncRNA of melanoma, which proposed more possibilities for its occurrence and development mechanism <ns0:ref type='bibr' target='#b17'>[16]</ns0:ref> . Meanwhile, some articles have reported the metastasis of CM. For example, Chen et al. <ns0:ref type='bibr' target='#b18'>[17]</ns0:ref> analyzed the gene expression of primary and metastatic melanoma in a database and obtained some candidate genes for metastasis. Wang et al. <ns0:ref type='bibr' target='#b19'>[18]</ns0:ref> comprehensively analyzed the gene expression of PM and MM in TCGA and constructed a competitive endogenous RNA (ceRNA) network, then proposed a new idea that non-coding RNA and mRNA may act together on the metastasis of melanoma.</ns0:p><ns0:p>However, previous studies have mainly focused on the analysis of PM and N samples. Several studies have also explored the metastasis of CM, but the entire progression of melanoma has not been analyzed from the perspective of occurrence and development, nor has it been compared by combining multiple data sets. In this study, we downloaded three gene expression profiles (GSE7553, GSE15605, and GSE46517) from the GEO, which all included N, PM and MM samples. DEGs among N, PM and MM were determined by gene expression profiling. Subsequently, GO functions, KEGG pathways and PPI network analyses were performed on DEGs. Finally, verification and survival analysis were performed on identified hub genes, which may be potential biomarkers and therapeutic targets in the occurrence and transfer of CM. The flow chart is shown in Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>GEO gene expression data</ns0:head><ns0:p>Three gene expression datasets (GSE7553 <ns0:ref type='bibr' target='#b20'>[19]</ns0:ref> , GSE15605 <ns0:ref type='bibr' target='#b21'>[20]</ns0:ref> , and GSE46517 <ns0:ref type='bibr' target='#b22'>[21]</ns0:ref> ) were obtained from the GEO database (http://www.ncbi.nlm.nih.gov/geo). The file type of the original gene expression data set was CEL, and the platform file contained probe ID, gene marker and entrez gene ID. GSE7553 and GSE15605 were based on the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) and GSE46517 was based on the GPL96 platform (Affymetrix Human Genome U133A Array). There were a total of 225 tissue samples in the three data sets, including 28 normal skin samples, 93 primary melanoma samples and 104 metastatic melanoma samples.</ns0:p></ns0:div> <ns0:div><ns0:head>Data processing and DEGs filtering</ns0:head><ns0:p>The raw CEL files were background-adjusted and standardized by the R software <ns0:ref type='bibr' target='#b23'>[22]</ns0:ref> . According to the annotation file, the probe ID was replaced with the corresponding gene symbol. If there were multiple probes for the same gene, the R language was used to calculate the average value for further analysis. Then the limma R package was used to screen the genes of each data set, when the p-value &lt; 0.05 and |log 2 fold change (FC)| &gt;1 were considered DEGs <ns0:ref type='bibr' target='#b24'>[23]</ns0:ref> . The upregulated or downregulated DEGs lists were overlapped by Venn diagram (http://bioinformatics.psb.ugent.be/webtools/Venn/), for subsequent function analysis.</ns0:p><ns0:p>Using DAVID 6.8 database (https://david.ncifcrf.gov/home.jsp) to analyze the GO functions and KEGG pathways of integrated DEGs <ns0:ref type='bibr' target='#b25'>[24]</ns0:ref> . The GO terms and the KEGG pathways with p&lt;0.05 were selected to be the enriched functions. GO functions analyses covered three domains: Biological Process, Cellular Component and Molecular Function.</ns0:p></ns0:div> <ns0:div><ns0:head>PPI network and the most important module analysis</ns0:head><ns0:p>The PPI network was constructed by the STRING (https://string-db.org/) platform, an online tool used for revealing protein interactions and functional analysis <ns0:ref type='bibr' target='#b26'>[25]</ns0:ref> . In PPI network, each node represents a protein and each edge represents the action between proteins <ns0:ref type='bibr' target='#b27'>[26]</ns0:ref> . Then, the PPI network was visualized by Cytoscape software.</ns0:p><ns0:p>The most important module in PPI network was identified by means of the plug-in Molecular Complex Detection (MCODE) <ns0:ref type='bibr' target='#b28'>[27]</ns0:ref> . The criteria for selection were as follows: degree cut-off=2, node score cut-off=0.2, Max depth=100, and k-score=2. Subsequently, the GO functions and KEGG pathways analyses for genes in these modules were performed by DAVID, and p&lt;0.05 was considered statistically significant.</ns0:p></ns0:div> <ns0:div><ns0:head>Hub genes selection and analysis</ns0:head><ns0:p>Through 12 topological analysis methods, the cytoHubba of R software was used to sort the nodes in the PPI network. The hub genes consists of the overlapping results, which were obtained by the top 10 nodes of the Maximal Clique Centrality (MCC) analysis method and the degree of gene &#8805;10 <ns0:ref type='bibr' target='#b29'>[28]</ns0:ref> . Subsequently, Pathway Commons Network Visualizer (PCViz), an open platform for exploring multidimensional cancer genome data, was used to analyze the association between hub genes and their co-expressed genes. The biological process analysis of hub genes was visualized by the Biological Networks Gene Oncology tool (BiNGO) plugin of Cytoscape <ns0:ref type='bibr' target='#b30'>[29]</ns0:ref> .</ns0:p></ns0:div> <ns0:div><ns0:head>Validation of hub genes and survival curve analysis</ns0:head><ns0:p>The UALCAN website (http://ualcan.path.uab.edu/) was used to analyze the TCGA gene expression data, in order to compare the expression of hub genes in normal skin, primary melanoma and metastatic melanoma samples <ns0:ref type='bibr' target='#b31'>[30]</ns0:ref> . Then, the overall survival curve of each hub genes were analyzed by Gene Expression Profiling interactive analysis (GEPIA) (http://gepia.cancer-pku.cn/), and p&lt;0.05 was considered as a statistically significant difference <ns0:ref type='bibr' target='#b33'>[31]</ns0:ref> .</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Identification of DEGs</ns0:head><ns0:p>R software was used to compare the gene expression of samples from GSE7553, GSE15605 and GSE46517 data sets, and the DEGs of N, PM and MM were obtained in each data sets (table 1, table s1-9, available at https://doi.org/10.6084/m9.figshare.12893420.v1). Then, the overlaps of 134, 317, and 147 DEGs between PM and N, MM and N, and MM and PM are obtained from the three data sets, which were shown by Venn disgram (Fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). Among them, there were 12 upregulated genes and 122 downregulated genes in the PM compared to N (table s10, available at https://doi.org/10.6084/m9.figshare.12893420.v1), 153 upregulated genes and 164 downregulated genes between MM with N (table s11, available at https://doi.org/10.6084/m9.figshare.12893420.v1), and MM had 79 upregulated genes and 68 downregulated genes compared with PM (table s12, available at https://doi.org/10.6084/m9.figshare.12893420.v1). GO functions and KEGG pathways enrichment analyses of DEGs DAVID was used for GO functions and KEGG pathways enrichment analysis (Fig. <ns0:ref type='figure'>3-5</ns0:ref>, table s13-15, available at https://doi.org/10.6084/m9.figshare.12893420.v1). GO functions analysis results showed that compared with N samples, upregulated genes of PM were enriched in the collagen catabolic process (BP), while downregulated genes were enriched in transcription from RNA polymerase II promoter (BP), plasma membrane (CC) and structural molecule activity (MF). The upregulated genes between MM and N samples were enriched in negative regulation of neuron apoptotic process (BP), spindle microtubule (CC) and protein kinase activity (MF), and the downregulated genes were enriched in epidermal development (BP), extracellular exosome (CC) and structural molecule activity (MF). In MM and PM samples, the upregulated genes mainly included cell division (BP), cytoplasm (CC), and protein binding (MF), and the downregulated genes mainly included epidermis development (BP), extracellular exosomes (CC), and structural molecule activity (MF).</ns0:p><ns0:p>The KEGG pathways of the overlapped DEGs were analyzed, the upregulated genes between PM and N were significantly enriched in the transcriptional misregulation in cancer, while the downregulated genes were enriched in the metabolic pathways. In MM and N, the upregulated DEGs enriched in the pathway in cancer and the transcriptional misregulation in cancer, and the downregulated DEGs enriched in the arachidonic acid metabolism and steroid biosynthesis. Complement and coagulation cascades was the top enriched term for upregulation genes of MM and PM, while the p53 signaling pathway was the top enriched term for downregulation genes.</ns0:p></ns0:div> <ns0:div><ns0:head>PPI network construction and the most meaningful module analysis</ns0:head><ns0:p>The PPI network of DEGs was constructed using the STRING (Fig. <ns0:ref type='figure'>6</ns0:ref>) and the most important modules were obtained by Cytoscape (Fig. <ns0:ref type='figure'>7</ns0:ref>). The GO functions and KEGG pathways enrichment analysis showed that the important modules of PM and N were enriched in the cholesterol biosynthetic process, mitochondrion, oxidoreductase activity and metabolic pathway (Fig. <ns0:ref type='figure'>8A</ns0:ref>, table s16, available at https://doi.org/10.6084/m9.figshare.12893420.v1). The module genes between MM and N were mainly enriched in cell division, extracellular exosomes, protein binding and oocyte meiosis pathway (Fig. <ns0:ref type='figure'>8B</ns0:ref>, table s17, available at https://doi.org/10.6084/m9.figshare.12893420.v1). In the MM and PM, the module genes were enriched in keratinocyte differentiation, cytoplasm, structural molecule activity, protein binding and ismatch repair (Fig. <ns0:ref type='figure'>8C</ns0:ref>, table s18, available at https://doi.org/10.6084/m9.figshare.12893420.v1).</ns0:p></ns0:div> <ns0:div><ns0:head>Hub gene selection and analysis</ns0:head><ns0:p>According to the above criteria, 14, 18 and 18 genes among N, PM and MM were selected as the hub genes in PPI network, and the details are shown in Table <ns0:ref type='table'>2</ns0:ref>. PCViz online platform is used to construct the hub genes and their co-expressed genes network (Fig. <ns0:ref type='figure'>9</ns0:ref>). The biological process analysis of hub genes is shown in Fig. <ns0:ref type='figure' target='#fig_1'>10</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Validation of hub genes and survival curve analysis</ns0:head><ns0:p>The transcription expression data of hub genes from 473 TCGA samples were analyzed using UALCAN. Among them, 1 case was normal sample, 104 cases were PM samples, and 368 cases were MM samples. We found that the expression of those hub genes in MM samples decreased significantly compared with PM samples (Fig. <ns0:ref type='figure' target='#fig_1'>11</ns0:ref>). Therefore, the results of the candidate hub genes identified by us are reliable.</ns0:p><ns0:p>We utilized the GEPIA online tool to analyze the samples data from TCGA and obtain the overall survival curve of these hub genes in skin melanoma patients, so as to further study the relationship between hub genes and patient survival and prognosis. As shown in figure <ns0:ref type='figure' target='#fig_2'>12</ns0:ref>, the changes of IVL, FLG, SPRR1B, DSG3, KRT5, DSG1, KRT16, PKP1, KRT14 and DSC3 in melanoma patients were associated with shortened overall survival, which suggested that these hub genes expression differences may be related to the progression and prognosis of cutaneous melanoma, thus can be used for predicting the deterioration and improvement of CM.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Recently, many studies had carried out gene expression profiling and bioinformatics analysis on the molecular mechanism of CM occurrence, but the biological mechanism of its development and metastasis were still unclear. In this study, we downloaded three gene expression data sets from GEO and used a comprehensive bioinformatics method to directly compare the gene expression differences among N, PM and MM samples. 134, 317 and 147 DEGs, as well as 14, 18, and 18 hub genes were identified between PM and N, MM and N, MM and PM, respectively. Then, we used the online analysis website to verify the hub genes expression in TCGA samples and performed survival analysis on CM patients.</ns0:p><ns0:p>Through GO functions and KEGG pathways analyses of DEGs, we found that biological processes of upregulated genes mainly concentrated in cell division, spindle microtubule, protein kinase activity and the pathway of transcriptional misregulation in cancer. The downregulated gene mainly occurred in epidermis development, extracellular exosome, structural molecule activity and p53 signaling pathway. Studies have shown that the occurrence and metastasis of melanoma need to be realized through the promotion of cell mitosis and the growth of anti-aging and anti-apoptosis <ns0:ref type='bibr' target='#b34'>[32]</ns0:ref> . In addition, spindle microtubules can accelerate the proliferation and transfer of cells, and the regulation of metabolic pathways such as protein synthesis and transcriptional disorders can promote cell division <ns0:ref type='bibr' target='#b35'>[33]</ns0:ref> . The results showed that downregulated genes were associated with skin epidermal development, melanoma cells were produced in the basal layer of the epidermis and hair follicles, and epidermal keratinization could control the homeostasis of melanocytes <ns0:ref type='bibr' target='#b36'>[34]</ns0:ref> . Studies have found that most exosomes mediate the tumor process in the progression of melanoma <ns0:ref type='bibr' target='#b37'>[35]</ns0:ref> . The inactivation of p53 has an influence on the occurrence of melanoma <ns0:ref type='bibr' target='#b38'>[36]</ns0:ref> , and the defective p53 pathway also has an anti-apoptotic effect <ns0:ref type='bibr' target='#b39'>[37]</ns0:ref> . Therefore, previous studies had confirmed our results.</ns0:p><ns0:p>In the 14 hub genes between PM and N, it had been found that matrix metalloproteinases (MMP) can participate in the skin matrix remodeling through degrading and rebuilding the matrix components, and affect the proliferation, survival, vascularization, protease expression and migration of melanoma cells <ns0:ref type='bibr' target='#b40'>[38]</ns0:ref> . MMP-9 knockdown can reduce the migration and invasion of melanoma cells and inhibit epithelial-mesenchymal transformation (EMT), thus being considered as a promising molecule for the CM treatment <ns0:ref type='bibr' target='#b41'>[39]</ns0:ref> . Meanwhile, bone morphogenetic protein (BMPs) is involved in the regulation of MMPs and is an inevitable factor in the migration and invasion of melanoma cells <ns0:ref type='bibr' target='#b42'>[40]</ns0:ref> . Fibroblast growth factor receptor 3 (FGFR3) may promote melanoma growth, metastasis, and EMT behavior by influencing the phosphorylation levels of ERK, AKT, and EGFR <ns0:ref type='bibr' target='#b43'>[41]</ns0:ref> . The loss of EphB6 may have deleterious immunological effects in cancer progression, while Hafner et al. <ns0:ref type='bibr' target='#b44'>[42]</ns0:ref> found that its expression decreased gradually in N, PM and MM. These previous studies had suggested that these hub genes may have a potential role in the development of CM.</ns0:p><ns0:p>In MM and PM, we found 18 hub genes through PPI network, all of which were downregulated genes. Several were associated with keratinocyte differentiation and epidermal development, such as loricrin (LOR), involucrin (IVL), filaggrin (FLG), small proline-rich protein1 (SPRR1)&#65292;keratin (KRT) and plakophilin (PKP1), which may result in loss of epidermal function. Among them, some hub genes had been found to be related to the production and metastasis of melanoma, such as SPRR1 <ns0:ref type='bibr' target='#b46'>[43]</ns0:ref> and PKP1 <ns0:ref type='bibr' target='#b47'>[44]</ns0:ref> . However, other genes had not been proven to be related to CM, such as LOR dysregulation was considered as an early indicator of potential malignant diseases, including oral submucosal fibrosis and leucoplasis <ns0:ref type='bibr' target='#b48'>[45]</ns0:ref> . IVL was a specific and sensitive marker of cell differentiation, the expression of IVL in head and neck squamous cell carcinoma patients with or without lymph node metastasis was significantly different <ns0:ref type='bibr' target='#b49'>[46]</ns0:ref> . Loss-of-function mutations in FLG can lead to a decrease in epidermal filaggrin and its degradation products, and increase the sensitivity of CM <ns0:ref type='bibr' target='#b50'>[47]</ns0:ref> . In MM and PM, the downregulated amplitude of FLG (log 2 FC = -5.404) was less than the amplitude in MM and N (log 2 FC = -8.586), while there was no significant difference between PM and N. It showed that FLG may be related to CM transfer, and this association needs to be verified by subsequent experiments. Studies had shown that KRT5 and KRT14 were involved in HNSCC differentiation and apoptosis as the epithelial proliferative markers <ns0:ref type='bibr' target='#b51'>[48]</ns0:ref> . Meanwhile, immunohistochemical staining of KRT14 and KRT16 in PM and MM were mostly negative, and the positive distribution contributed to the diagnosis of poorly differentiated squamous cell carcinoma <ns0:ref type='bibr' target='#b52'>[49]</ns0:ref> . CDSN was expressed in hair follicles and keratinized epithelial cells, played an important role in intercellular adhesion, and was related to skin barrier function and epidermal defense pathway <ns0:ref type='bibr' target='#b53'>[50]</ns0:ref> . Studies had found that mutations in the CDSN gene could cause excessive keratosis of the skin, and lead to peeling skin disease and hypotrichosis simplex of the scalp <ns0:ref type='bibr' target='#b54'>[51]</ns0:ref> , therefore, down-regulation of CDSN may accelerate the development of CM by slowing down epidermal development.</ns0:p><ns0:p>In MM and PM, there were some hub genes associated with EMT. EMT was normally associated with embryogenesis and wound healing, but in tumor cells, it promoted tumor Manuscript to be reviewed metastasis by enabling cells to leave the epithelium and acquire mesenchymal specificity <ns0:ref type='bibr' target='#b55'>[52]</ns0:ref> . This process increased the aggressiveness of the tumor by the loss of the epithelial phenotype (Ecadherin, desmosin, laminin-1) and the acquisition of the mesenchymal marker (N-cadherin) <ns0:ref type='bibr' target='#b57'>[53]</ns0:ref> . Hub gene desmoglein1(DSG1) could control the role of keratinocytes, and contribute to the page-like behavior in the development of melanoma <ns0:ref type='bibr' target='#b58'>[54]</ns0:ref> . Furthermore, desmocollin1(DSC1) and desmocollin3(DSC3) are members of the E-cadherin superfamily, involved in cell-cell adhesion and cell-extracellular matrix interaction. Benign melanocytes expressed high levels of Ecadherin, and during the transition to melanoma cells, E-cadherin was down-regulated and Ncadherin was up-regulated <ns0:ref type='bibr' target='#b59'>[55]</ns0:ref> . Studies had shown that desmoplakin (DSP) was a desmosomal protein involved in cell-cell adhesion. Desmosome formation was characteristic of cell differentiation and intercellular adhesion, and the loss of desmosome might accelerate the occurrence and early migration of tumor cells <ns0:ref type='bibr' target='#b60'>[56]</ns0:ref> .</ns0:p><ns0:p>There are also some hub genes between MM and PM had been found to be related to CM, for example, the down-regulation of cystatin A (CSTA) expression has become an important feature to distinguish N, PM and MM <ns0:ref type='bibr' target='#b61'>[57]</ns0:ref> . Several S100 family genes had been found to be highly expressed in PM, but low level in MM <ns0:ref type='bibr' target='#b62'>[58]</ns0:ref> . In particular, the loss of S100A7 is highly correlated with the metastasis progression score <ns0:ref type='bibr' target='#b63'>[59]</ns0:ref> . Lentin et al. <ns0:ref type='bibr' target='#b64'>[60]</ns0:ref> observed that the anti-invasion effect of transglutaminase(TGM) might lead to the post-translational modification of some components of the cell basal membrane, thereby interfering with the metastasis of melanoma cells. The activity of TGM2 had a protective effect on the progression of melanoma in vivo <ns0:ref type='bibr' target='#b65'>[61]</ns0:ref> , but no studies had been conducted to prove the relationship between TGM1 and CM, so TGM1 may be a new potential marker.</ns0:p><ns0:p>We found that most of the above hub genes had been reported to be closely related to the generation and metastasis of CM. Moreover, through prognostic analysis, most hub gene expression differences in CM patients were connected with overall survival, which proved the reliability of our study. There are still a few genes that had not been reported or experimentally confirmed to be associated with CM, but some of them are related to the occurrence and development of other cancers. So they might be potential biomarkers of CM, and a large number of experiments are needed to confirm. Most hub genes, such as LOR, IVL, FLG, DSG3, TGM1, KRT16, SPRR1A, KRT14, DSP and CSTA, showed no difference in the expression of PM and N, but significantly decreased in MM and PM, suggesting that these genes might be potential predictors of CM metastasis. The expression of some genes, such as CDSN, DSG1, DSC3, DSC1 and DSP, was downregulated in all three groups, which might be relate with the occurrence and progression of CM. It is worth noting that three genes, SPRR1B, PKP1 and S100A7, were upregulated in PM and N, but downregulated in MM and PM, which were likely to be used as novel markers to distinguish whether CM was metastatic or not. These assumptions need to be tested experimentally.</ns0:p><ns0:p>Compared with previous studies, we used more samples, and compared N, PM and MM in pairs, then took the intersection, so as to make the experimental results more reliable. Besides using GEO data sets, we also used TCGA data for verification, which increased the sample size and accuracy. However, the limitation of this study is the lack of experimental verification of hub genes. Therefore, to understand whether the hub genes are really closely related to the generation and metastasis of CM, a large number of subsequent experiments are needed to explore.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In conclusion, through bioinformatics analysis, we obtained some potential key genes and biological pathways related to the occurrence and metastasis of CM, providing directions for future research. In addition to the genes that have been reported and demonstrated, other identified key genes may be potential prognostic markers and therapeutic targets for CM occurrence and metastasis. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 3</ns0:note><ns0:p>GO functions and KEGG pathways enrichment analysis of the upregulated and downregulated genes between primary cutaneous melanoma and normal skin.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:49579:1:1:NEW 5 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 4</ns0:note><ns0:p>GO functions and KEGG pathways enrichment analysis of the upregulated and downregulated genes between metastatic cutaneous melanoma and normal skin.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:49579:1:1:NEW 5 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 5</ns0:note><ns0:p>GO functions and KEGG pathways enrichment analysis of the upregulated and downregulated genes between metastatic cutaneous melanoma and primary cutaneous melanoma.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:49579:1:1:NEW 5 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 6</ns0:note><ns0:p>The PPI network of DEGs was constructed by using Cytoscape. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49579:1:1:NEW 5 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 Experimental</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 Venn</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>A) PPI network of DEGs between PM and N of the three data sets. (B) PPI network of DEGs between MM and N of the three data sets. (C) PPI network of DEGs between MM and PM of the three data sets.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='24,42.52,199.12,525.00,327.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,199.12,525.00,342.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='26,42.52,219.37,525.00,420.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='30,42.52,199.12,525.00,364.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='32,42.52,70.87,525.00,448.50' type='bitmap' /></ns0:figure> </ns0:body> "

"Central South University NO.172 Tongzipo Road Yuelu District, Changsha, Hunan, China http://www.csu.edu [email protected] August 16th, 2020 Dear Editors First of all, I would like to thank the reviewers for their generous comments on my manuscript. We have revised the manuscript, and replied to the questions of reviewers and editors in the following part. We believe and hope that this manuscript is now suitable for publication in PeerJ. Hanying Dai Department of Laboratory Medicine, the Third Xiangya Hospital On behalf of all authors. Reviewer 1 (Xin Zhang) Basic reporting (1) The language in this manuscript is ambiguous, and the conclusion is exaggerated. Please see Major Q1. Major concerns 1. “Validity of the findings” The title of this manuscript is that “Comprehensive analysis and identification of key genes and signaling pathways in cutaneous melanoma metastasis”. However, from the analysis results and conclusions of the manuscript, the author did not identify convincing analysis, but only found a bunch of differentially expressed genes, analyzed the potential functions and pathways, and found a dozen genes related to prognosis. The correlation analysis used in this study can only indicate the possibility of an important role and should not be exaggerated. The author had to make a careful revision of the language. We appreciate your comments very much. We have carefully modified the language and made more acceptable changes to the purpose, conclusion and discussion of our research. Please refer to the abstract and discussion of this paper for details. (2) Picture quality is basically no problem. Thank you very much for your approval and had uploaded the clearer images. (3) No raw data is provided. We are very sorry that you did not find the original data of this study. We have submitted the original data to the Shared database. ( supplementary file: Dai, Hanying (2020): Supplemental files.zip. figshare. Online resource. https://doi.org/10.6084/m9.figshare.12893420.v1) (4) Literature well referenced. Thank you for your approval. Experimental design (1) The experimental method has some problems and needs to be redesigned. Please see Major Q2 and Q3. Major concerns 2. “Validity of the findings” The authors used multiple databases to analyze differentially expressed genes between primary melanoma and metastatic melanoma and identified these genes as the key genes associated with melanoma metastasis. However, the process of metastasis is complex, and the genes specifically expressed in the metastasis foci may be a passive process for the cancer cells to adapt to the microenvironment of the metastasis foci, rather than 'drivers'. Therefore, there is a big deviation between the subject design idea and the research objective in this paper, and the results and conclusions cannot support each other. I would suggest that the authors reformulate the purpose of the study and redesign the analysis process according to the purpose. The key is not to make the purpose too large, but to focus on a specific clinical problem or tumor biology problem. We agree with you and have made changes in the research objectives, conclusions and discussions. In fact, we reviewed the literature and previous experiments to respectively discuss the hub genes that we identifie. Some of these genes had been found to be closely related to the occurrence and metastasis of cutaneous melanoma or other cancers through experiments and functional analysis, and these studies had also confirmed the reliability of our results. Of course, there were also some hub genes which had no experimental proof of their role in the occurrence and metastasis of cutaneous melanoma, so we can only guess that these key genes may be potential markers of cutaneous melanoma. Therefore, we adopted a more rigorous expression in the research purpose and conclusion. 3. “Results – Validation of hub genes and survival curve analysis” Line 201-208. When using TCGA database for verification, the author firstly verified the expression differences of selected genes in primary foci (n = 104) and metastatic foci (n = 368), and then analyzed the relationship between related genes and survival prognosis of patients, proving the importance of related genes. However, as can be seen from the survival curve in Figure 8, the author did not simply analyze the relationship between the expression of relevant genes in the primary site and the survival prognosis of patients, but included all the data of the primary site and the metastatic site into the analysis (n = 250+), which was obviously a logical problem. The prognosis of patients with metastatic foci is certainly worse than that of patients with primary foci alone. The analyzed genes have been found to be abnormally expressed in metastatic foci. If the samples of all patients are integrated and analyzed, the correlation between these genes and prognosis is inevitable and has no real diagnostic value. Therefore, the authors analyzed the survival or prognosis of related genes in patients with primary and metastatic foci respectively. Thank you for your advice. I am very sorry that I did not specify the sample source and composition of the prognostic analysis in the article. GEPIA in this paper was used to analyze overall survival of all cutaneous melanoma patients who had high or low expression of hub genes. Therefore, in figure 8, we can clearly see that the down-regulation of hub genes leads to a significant decrease in the total survival of patients, so these key genes may be a potential factor to reduce the total survival. In the discussion section of the article, we give a corresponding more detailed explanation. (2) There is no problem with the statistical method in this manuscript. Thank you for your approval. Validity of the findings (1) The findings of this study need further experiments. Please see Major Q1 to Q3. Thank you very much for your advice. Our paper aims to provide new directions for future research through the re-use of previously public data. We strongly agree that the accurate hub genes cannot be obtained in this study. Therefore, we modify the research purpose and conclusions in this paper to make them more consistent with the results of this study. We also hope that the conjecture raised in this study can be verified through more experimental and clinical investigations in the future. Comments for the Author Melanoma is a malignant tumor of melanocytes, and the incidence has increased faster than any other cancer over the past half century. Most primary cutaneous melanoma can be cured by local excision, but metastatic cutaneous melanoma has a poor prognosis. Therefore, the research on the mechanism of cutaneous melanoma metastasis will be beneficial to diagnose the metastatic melanoma early, improve the treatment, and prolong the survival of patients. In this study, Dai Hangying and colleagues identified the key genes and molecular pathways involved in the occurrence and metastasis of cutaneous melanoma. The study provides the conclusion, which showed that some DEGs were found from normal skin, primary melanoma and metastatic melanoma samples. These hub genes may play an important role in the generation, invasion, recurrence or death of CM, providing new ideas and targets for the diagnosis and treatment of metastatic cutaneous melanoma. There are some problems in this study, which require the author to revise the research design, and there are some major concerns that need to be addressed. Thank you for your comments. We agree with you very much and had made changes accordingly. We believe that with those changes, this article will be greatly changed and will be more suitable for publication on PeerJ. Reviewer 2 (Olga Papadodima) Basic reporting The authors provide a detailed bioinformatics analysis of the mechanisms involved in cutaneous melanoma progression. I believe that some aspects of their analyses are over-represented, while some other ones are not. I would focus mainly on the comparison between PM and MM. I beleive that the English language should be improved. Please check that the correct tense for all verbs is used . Thank you very much for your comment. We have modified the research purpose, discussion and conclusion of this paper. Since we compared the differences among the three groups of normal skin, primary melanoma and metastatic melanoma, the hub genes obtained in this study may play a certain role in the occurrence and metastasis of cutaneous melanoma. Secondly, we are very sorry for the writing errors in the article, and we have carefully corrected and revised it. We believe that the revised English level has been improved to some extent. Experimental design My major concern regarding the experimental design is whether the comparison between melanoma (primary or not) and normal skin, in order to identify Differentially Expressed Genes, is valid. I mean that the comparison between cancer and normal melanocytes could be much more meaningful.Could the authors check also this comparison at least at the datasets that contain samples of normal melanocytes or nevi? We agree with you. Through searching the data, we found that melanoma is a highly invasive malignant skin tumor originated from melanocytes. And melanocytes are the cells derived from nerve C and mainly exist in basal epidermis and hair follicles. About 33 percent of primary melanomas come from moles, and chronic sun exposure to cutaneous melanomas are usually not caused by pre-existing moles ( Leonardi GC et al. 2018. Cutaneous melanoma: From pathogenesis to therapy ). Moreover, the normal skin samples in the data set we selected were from normal skin adjacent to melanoma, so the differences in gene expression were more comparable. I would suggest that the authors include a table describing the datasets that they have analysed, presenting details concerning the number of normal skin, primary or metastatic samples per analysis. The number of differentiated genes could also be indicated. Thank you very much for your suggestion. I had added a table to describe the detailed information of the number of normal skin, primary and metastatic samples, and the number of differential genes listed in Table 1. Validity of the findings I believe that the presented bioinformatics analyses are robust and statistically sound. In my opinion there are many tables concerning the GO and Kegg-based analyses. I would suggest to keep those concerning the PM versus MM DEGs and present the others as supplementary files. Thank you for your approval and suggestion. Since this study compared gene expression differences between samples of normal skin, primary and or metastatic melanoma, we adjusted the purpose of the study to look for hub genes in the occurrence and metastasis of cutaneous melanoma.We simplified the tables for GO functions and KEGG pathways enrichment analysis into more visualized figures (Fig. 3-5, Fig. 8), and listed the detailed tables in the supplementary document (table s13-18). ( supplementary file: Dai, Hanying (2020): Supplemental files.zip. figshare. Online resource. https://doi.org/10.6084/m9.figshare.12893420.v1) Regarding figure 7 I couldn’t understand why the y axis is indicated in Transcripts per million and why the category normal is presented with n=1. The y axis is the value of Transcript per million (TPM), which is the transcripts per kilobase of exon model per million mapped reads. TPM is the normalization of gene length followed by the normalization of columns, so that the sum of TPM in each sample is the same. Counts, counted using the TPM method, is the number of read alignments for a given genomic reference region, also known as raw Count. TPM method converts count matrix into relative value, removing the influence of technical deviation, making subsequent difference analysis statistically significant, and reducing the inaccuracy of quantification across samples. Second, since UALCAN is an online software, it is based on the data analysis of TCGA, TCGA is a database that includes relevant information of cancer patients, so it only contains 1 melanoma patients specimens of normal information. Using the data, we can well verify the differences in the expression of hub genes between primary and metastatic melanoma. Comments for the Author Please correct lines 271-272 Thank you for your correction. We have made changes to it. Reviewer 3 (Anonymous) Basic reporting - The use of English is verbose and not clear. There also contains grammatical errors and typos. The authors should re-check and revise carefully. We are very sorry for this. We had modified and corrected the sentences in the article. We hope that the revised article will give you a better reading experience and be more correct. - Literature reviews are weak. The authors should add more literature references about some related works. We quite agree with your opinion. We had added the previous review and discussion of similar experiments in our article. Please refer to line 69-90 of the introduction section for details. - Some abbreviations need to be defined at the first use. Thank you for your suggestions. We had corrected them in the article. Experimental design - Research design is a big concern. Why did the authors perform the analysis among three groups? If the problem aims to address cutaneous melanoma metastasis, why did the authors not compare between metastasis and non-metastasis only? Or if the authors compared three groups, why did the authors separate into three binary problems? Is it possible if the authors perform the analysis on all three groups together? We agree with your suggestion and had thought deeply about it. We adjusted the objectives and conclusions of this study to identify and analyze key genes that may be involved in the development and metastasis of cutaneous melanoma. Due to the occurrence and metastasis of melanoma is a dynamic process, so we want to compare the normal skin VS primary melanoma, normal skin VS metastatic melanoma, primary VS metastatic melanoma respectively, thus to explore the dynamic process of differentially expressed genes between different period. If the three groups were analyzed together, only the common differences between the three groups could be found. It was also impossible to define whether the difference was due to primary or metastatic disease, and some key genes might have been screened out. At the same time, in the discussion section, we analyzed the overlapping key genes in pair comparison, trying to find their roles in the process of occurrence and metastasis. - Methods have not been explained well and it is not easy to replicate. Also, it is important that the authors could release source codes for analysis. We are very sorry that we did not explain our method clearly. We had made changes in the article. The source code had also been uploaded to the supplementary file. - GO database and analysis has been used in previous works related to biomedical such as PMID: 31277574 and PMID: 31921391. Therefore, the authors should provide some references in this description. We strongly agree with your suggestion. We had added a review and discussion of relevant articles in the article , so as to make this research more persuasive. In addition, the article you proposed was cited and summarized, as shown in line 75 of the introduction section. Validity of the findings - The choice of p-value and cut-off value is a question. Why did sometimes the authors select significant level of 0.01, 0.02, or 0.05 etc? At least, these values must be consistent. We quite agree with your suggestion. We had unified the significance level in the article and changed the results to get more reliable results, as shown in Figure 7 and Figure 10. - There are many works that have addressed the same question such as PMID: 31173190, PMID: 31937175, or PMID: 32547879. Thus what are differences between this study and the others? The authors should discuss and compare with some related works. We appreciate your advice very much. Compared with previous studies, we used more samples and took the intersection through pair comparison among normal skin, primary melanoma and metastatic melanoma to make the experimental results more reliable, which have not been done before. At the same time, we had added the review and comparison of previous relevant articles in our article, and proposed the differences and design significance between our study and other works. Please refer to the introduction and discussion section for details. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. Melanoma is a malignant tumor of melanocytes, and the incidence has increased faster than any other cancer over the past half century. Most primary melanoma can be cured by local excision, but metastatic melanoma has a poor prognosis. Cutaneous melanoma(CM) is prone to metastasis, so the research on the mechanism of melanoma occurrence and metastasis will be beneficial to diagnose early, improve treatment, and prolong life survival. In this study, we compared the gene expression of normal skin (N), primary cutaneous melanoma (PM) and metastatic cutaneous melanoma (MM) in the Gene Expression Omnibus (GEO) database. Then we identified the key genes and molecular pathways that may be involved in the development and metastasis of cutaneous melanoma, thus to discover potential markers or therapeutic targets. Methods. Three gene expression profiles (GSE7553, GSE15605 and GSE46517) were downloaded from the GEO database, which contained 225 tissue samples. R software identified the differentially expressed genes (DEGs) between pairs of N, PM and MM samples in the three sets of data. Subsequently, we analyzed the gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of the DEGs, and constructed a protein-protein interaction (PPI) network. MCODE was used to seek the most important modules in PPI network, and then GO function and KEGG pathway of them were analyzed. Finally, the hub genes were calculated by the cytoHubba in Cytoscape software. The Cancer Genome Atlas (TCGA) data were analyzed using UALCAN and GEPIA to validate the hub genes and analyze the prognosis of patients. Results. 134, 317 and 147 DEGs were identified between N, PM and MM in pair. GO functions and KEGG pathways analysis results showed that the upregulated DEGs mainly concentrated in cell division, spindle microtubule, protein kinase activity and the pathway of transcriptional misregulation in cancer. The downregulated DEGs occurred in epidermis development, extracellular exosome,</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Cutaneous melanoma (CM) is the most dangerous type of skin cancer. It accounts for approximately 232,100 new cases of CM around the world each year, including 55,500 deaths <ns0:ref type='bibr' target='#b0'>[1]</ns0:ref> , and it ranks 15th among the most common cancers in the world <ns0:ref type='bibr' target='#b1'>[2]</ns0:ref> . CM is one of the most aggressive and metastatic human cancers, and compared with other cancer types, it can spread from a small primary tumor to multiple sites throughout the body <ns0:ref type='bibr' target='#b2'>[3]</ns0:ref> . Although primary cutaneous melanoma can be removed and cured through the operation, when a few millimeters thick skin lesion is found, it represents an advanced stage, and there is a high chance of distant visceral metastasis <ns0:ref type='bibr' target='#b3'>[4]</ns0:ref> . Once metastatic foci are established in distant organs, the 5-year overall survival rate of melanoma patients drops sharply to less than 10% <ns0:ref type='bibr' target='#b4'>[5]</ns0:ref> . Therefore, it is urgent to identify the mechanisms that drive the occurrence and metastasis of CM, and to develop effective therapeutic strategies. Studies had classified the somatic mutations and expression profiles of metastatic melanoma <ns0:ref type='bibr' target='#b5'>[6]</ns0:ref> , but the mechanisms of CM evolution and metastasis have not been fully understood <ns0:ref type='bibr' target='#b6'>[7]</ns0:ref> . Understanding the gene expression changes during the development of CM will help to develop new biomarkers and therapeutic targets for the diagnosis and treatment of patients.</ns0:p><ns0:p>Gene expression microarray technology can be used to understand the biology associated with cancers, gene mutations and abnormal biological pathways, as well as to predict the diagnosis, treatment, prognosis or metastasis of patients <ns0:ref type='bibr' target='#b8'>[8]</ns0:ref> . The results of microarray technology provide a wealth of information, thus, the data stored in public databases can be reintegrated and bioinformatics analyzed to search for new clues about the pathological mechanisms of cancers through computers rather than laboratories <ns0:ref type='bibr' target='#b9'>[9]</ns0:ref> . In recent years, a large number of studies have predicted the key genes, signaling pathways and protein functions <ns0:ref type='bibr' target='#b11'>[10]</ns0:ref> of many cancers by analyzing the patients' genetic profiles. For example, the pathogenesis and metastasis mechanism of colorectal cancer <ns0:ref type='bibr' target='#b12'>[11]</ns0:ref> , prostate cancer <ns0:ref type='bibr' target='#b13'>[12]</ns0:ref> , breast cancer <ns0:ref type='bibr' target='#b14'>[13]</ns0:ref> and other cancers had been explored. A number of studies have done bioinformatics analysis of CM. Chen et al. <ns0:ref type='bibr' target='#b15'>[14]</ns0:ref> compared the DEGs between normal skin and melanoma, then used bioinformatics methods to analyze and identify the pathogenesis of CM. Wang et al. <ns0:ref type='bibr' target='#b16'>[15]</ns0:ref> compared the expression of CD38 in the tissues of healthy people and melanoma patients in the TCGA database, and analyzed the occurrence of subtypes and promoter methylation, so as to conclude that CD38 may be a potential biomarker for CM. Some studies obtained differentially expressed non-coding RNAs by analyzing the microRNA and lncRNA of melanoma, which proposed more possibilities for its occurrence and development mechanism <ns0:ref type='bibr' target='#b17'>[16]</ns0:ref> . Meanwhile, some articles have reported the metastasis of CM. For example, Chen et al. <ns0:ref type='bibr' target='#b18'>[17]</ns0:ref> analyzed the gene expression of primary and metastatic melanoma in a database and obtained some candidate genes for metastasis. Wang et al. <ns0:ref type='bibr' target='#b19'>[18]</ns0:ref> comprehensively analyzed the gene expression of PM and MM in TCGA and constructed a competitive endogenous RNA (ceRNA) network, then proposed a new idea that non-coding RNA and mRNA may act together on the metastasis of melanoma.</ns0:p><ns0:p>However, previous studies have mainly focused on the analysis of PM and N samples. Several studies have also explored the metastasis of CM, but the entire progression of melanoma has not been analyzed from the perspective of occurrence and development, nor has it been compared by combining multiple data sets. In this study, we downloaded three gene expression profiles (GSE7553, GSE15605, and GSE46517) from the GEO, which all included N, PM and MM samples. DEGs among N, PM and MM were determined by gene expression profiling. Subsequently, GO functions, KEGG pathways and PPI network analyses were performed on DEGs. Finally, verification and survival analysis were performed on identified hub genes, which may be potential biomarkers and therapeutic targets in the occurrence and transfer of CM. The flow chart is shown in Figure <ns0:ref type='figure' target='#fig_1'>1</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>GEO gene expression data</ns0:head><ns0:p>Three gene expression datasets (GSE7553 <ns0:ref type='bibr' target='#b20'>[19]</ns0:ref> , GSE15605 <ns0:ref type='bibr' target='#b21'>[20]</ns0:ref> , and GSE46517 <ns0:ref type='bibr' target='#b22'>[21]</ns0:ref> ) were obtained from the GEO database (http://www.ncbi.nlm.nih.gov/geo). The file type of the original gene expression data set was CEL, and the platform file contained probe ID, gene marker and entrez gene ID. GSE7553 and GSE15605 were based on the GPL570 platform (Affymetrix Human Genome U133 Plus 2.0 Array) and GSE46517 was based on the GPL96 platform (Affymetrix Human Genome U133A Array). There were a total of 225 tissue samples in the three data sets, including 28 normal skin samples, 93 primary melanoma samples and 104 metastatic melanoma samples.</ns0:p></ns0:div> <ns0:div><ns0:head>Data processing and DEGs filtering</ns0:head><ns0:p>The raw CEL files were background-adjusted and standardized by the R software <ns0:ref type='bibr' target='#b23'>[22]</ns0:ref> . According to the annotation file, the probe ID was replaced with the corresponding gene symbol. If there were multiple probes for the same gene, the R language was used to calculate the average value for further analysis. Then the limma R package was used to screen the genes of each data set, when the p-value &lt; 0.05 and |log 2 fold change (FC)| &gt;1 were considered DEGs <ns0:ref type='bibr' target='#b24'>[23]</ns0:ref> . The upregulated or downregulated DEGs lists were overlapped by Venn diagram (http://bioinformatics.psb.ugent.be/webtools/Venn/), for subsequent function analysis.</ns0:p><ns0:p>Using DAVID 6.8 database (https://david.ncifcrf.gov/home.jsp) to analyze the GO functions and KEGG pathways of integrated DEGs <ns0:ref type='bibr' target='#b25'>[24]</ns0:ref> . The GO terms and the KEGG pathways with p&lt;0.05 were selected to be the enriched functions. GO functions analyses covered three domains: Biological Process, Cellular Component and Molecular Function.</ns0:p></ns0:div> <ns0:div><ns0:head>PPI network and the most important module analysis</ns0:head><ns0:p>The PPI network was constructed by the STRING (https://string-db.org/) platform, an online tool used for revealing protein interactions and functional analysis <ns0:ref type='bibr' target='#b26'>[25]</ns0:ref> . In PPI network, each node represents a protein and each edge represents the action between proteins <ns0:ref type='bibr' target='#b27'>[26]</ns0:ref> . Then, the PPI network was visualized by Cytoscape software.</ns0:p><ns0:p>The most important module in PPI network was identified by means of the plug-in Molecular Complex Detection (MCODE) <ns0:ref type='bibr' target='#b28'>[27]</ns0:ref> . The criteria for selection were as follows: degree cut-off=2, node score cut-off=0.2, Max depth=100, and k-score=2. Subsequently, the GO functions and KEGG pathways analyses for genes in these modules were performed by DAVID, and p&lt;0.05 was considered statistically significant.</ns0:p></ns0:div> <ns0:div><ns0:head>Hub genes selection and analysis</ns0:head><ns0:p>Through 12 topological analysis methods, the cytoHubba of R software was used to sort the nodes in the PPI network. The hub genes consists of the overlapping results, which were obtained by the top 10 nodes of the Maximal Clique Centrality (MCC) analysis method and the degree of gene &#8805;10 <ns0:ref type='bibr' target='#b29'>[28]</ns0:ref> . Subsequently, Pathway Commons Network Visualizer (PCViz), an open platform for exploring multidimensional cancer genome data, was used to analyze the association between hub genes and their co-expressed genes. The biological process analysis of hub genes was visualized by the Biological Networks Gene Oncology tool (BiNGO) plugin of Cytoscape <ns0:ref type='bibr' target='#b30'>[29]</ns0:ref> .</ns0:p></ns0:div> <ns0:div><ns0:head>Validation of hub genes and survival curve analysis</ns0:head><ns0:p>The UALCAN website (http://ualcan.path.uab.edu/) was used to analyze the TCGA gene expression data, in order to compare the expression of hub genes in normal skin, primary melanoma and metastatic melanoma samples <ns0:ref type='bibr' target='#b31'>[30]</ns0:ref> . Then, the overall survival curve of each hub genes were analyzed by Gene Expression Profiling interactive analysis (GEPIA) (http://gepia.cancer-pku.cn/), and p&lt;0.05 was considered as a statistically significant difference <ns0:ref type='bibr' target='#b33'>[31]</ns0:ref> .</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Identification of DEGs</ns0:head><ns0:p>R software was used to compare the gene expression of samples from GSE7553, GSE15605 and GSE46517 data sets, and the DEGs of N, PM and MM were obtained in each data sets (table 1, table s1-9, available at https://doi.org/10.6084/m9.figshare.13019600.v1). Then, the overlaps of 134, 317, and 147 DEGs between PM and N, MM and N, and MM and PM are obtained from the three data sets, which were shown by Venn disgram (Fig. <ns0:ref type='figure' target='#fig_2'>2</ns0:ref>). Among them, there were 12 upregulated genes and 122 downregulated genes in the PM compared to N (table s10, available at https://doi.org/10.6084/m9.figshare.13019600.v1), 153 upregulated genes and 164 downregulated genes between MM with N (table s11, available at https://doi.org/10.6084/m9.figshare.13019600.v1), and MM had 79 upregulated genes and 68 downregulated genes compared with PM (table s12, available at https://doi.org/10.6084/m9.figshare.13019600.v1). GO functions and KEGG pathways enrichment analyses of DEGs DAVID was used for GO functions and KEGG pathways enrichment analysis (Fig. <ns0:ref type='figure'>3-5</ns0:ref>, table s13-15, available at https://doi.org/10.6084/m9.figshare.13019600.v1). GO functions analysis results showed that compared with N samples, upregulated genes of PM were enriched in the collagen catabolic process (BP), while downregulated genes were enriched in transcription from RNA polymerase II promoter (BP), plasma membrane (CC) and structural molecule activity (MF). The upregulated genes between MM and N samples were enriched in negative regulation of neuron apoptotic process (BP), spindle microtubule (CC) and protein kinase activity (MF), and the downregulated genes were enriched in epidermal development (BP), extracellular exosome (CC) and structural molecule activity (MF). In MM and PM samples, the upregulated genes mainly included cell division (BP), cytoplasm (CC), and protein binding (MF), and the downregulated genes mainly included epidermis development (BP), extracellular exosomes (CC), and structural molecule activity (MF).</ns0:p><ns0:p>The KEGG pathways of the overlapped DEGs were analyzed, the upregulated genes between PM and N were significantly enriched in the transcriptional misregulation in cancer, while the downregulated genes were enriched in the metabolic pathways. In MM and N, the upregulated DEGs enriched in the pathway in cancer and the transcriptional misregulation in cancer, and the downregulated DEGs enriched in the arachidonic acid metabolism and steroid biosynthesis. Complement and coagulation cascades was the top enriched term for upregulation genes of MM and PM, while the p53 signaling pathway was the top enriched term for downregulation genes.</ns0:p></ns0:div> <ns0:div><ns0:head>PPI network construction and the most meaningful module analysis</ns0:head><ns0:p>The PPI network of DEGs was constructed using the STRING (Fig. <ns0:ref type='figure'>6</ns0:ref>) and the most important modules were obtained by Cytoscape (Fig. <ns0:ref type='figure'>7</ns0:ref>). The GO functions and KEGG pathways enrichment analysis showed that the important modules of PM and N were enriched in the cholesterol biosynthetic process, mitochondrion, oxidoreductase activity and metabolic pathway (Fig. <ns0:ref type='figure'>8A</ns0:ref>, table s16, available at https://doi.org/10.6084/m9.figshare.13019600.v1). The module genes between MM and N were mainly enriched in cell division, extracellular exosomes, protein binding and oocyte meiosis pathway (Fig. <ns0:ref type='figure'>8B</ns0:ref>, table s17, available at https://doi.org/10.6084/m9.figshare.13019600.v1). In the MM and PM, the module genes were enriched in keratinocyte differentiation, cytoplasm, structural molecule activity, protein binding and ismatch repair (Fig. <ns0:ref type='figure'>8C</ns0:ref>, table s18, available at https://doi.org/10.6084/m9.figshare.13019600.v1).</ns0:p></ns0:div> <ns0:div><ns0:head>Hub gene selection and analysis</ns0:head><ns0:p>According to the above criteria, 14, 18 and 18 genes among N, PM and MM were selected as the hub genes in PPI network, and the details are shown in Table <ns0:ref type='table'>2</ns0:ref>. PCViz online platform is used to construct the hub genes and their co-expressed genes network (Fig. <ns0:ref type='figure' target='#fig_1'>s1</ns0:ref>, available at https://doi.org/10.6084/m9.figshare.13019600.v1). The biological process analysis of hub genes is shown in figure <ns0:ref type='figure' target='#fig_2'>s2</ns0:ref> (available at https://doi.org/10.6084/m9.figshare.13019600.v1).</ns0:p></ns0:div> <ns0:div><ns0:head>Validation of hub genes and survival curve analysis</ns0:head><ns0:p>The transcription expression data of hub genes from 473 TCGA samples were analyzed using UALCAN. Among them, 1 case was normal sample, 104 cases were PM samples, and 368 cases were MM samples. We found that the expression of those hub genes in MM samples decreased significantly compared with PM samples (Fig. <ns0:ref type='figure'>9</ns0:ref>). Therefore, the results of the candidate hub genes identified by us are reliable.</ns0:p><ns0:p>We utilized the GEPIA online tool to analyze the samples data from TCGA and obtain the overall survival curve of these hub genes in skin melanoma patients, so as to further study the relationship between hub genes and patient survival and prognosis. As shown in figure <ns0:ref type='figure' target='#fig_1'>10</ns0:ref>, the changes of IVL, FLG, SPRR1B, DSG3, KRT5, DSG1, KRT16, PKP1, KRT14 and DSC3 in melanoma patients were associated with shortened overall survival, which suggested that these hub genes expression differences may be related to the progression and prognosis of cutaneous melanoma, thus can be used for predicting the deterioration and improvement of CM.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Recently, many studies had carried out gene expression profiling and bioinformatics analysis on the molecular mechanism of CM occurrence, but the biological mechanism of its development and metastasis were still unclear. In this study, we downloaded three gene expression data sets from GEO and used a comprehensive bioinformatics method to directly compare the gene expression differences among N, PM and MM samples. 134, 317 and 147 DEGs, as well as 14, 18, and 18 hub genes were identified between PM and N, MM and N, MM and PM, respectively. Then, we used the online analysis website to verify the hub genes expression in TCGA samples and performed survival analysis on CM patients.</ns0:p><ns0:p>Through GO functions and KEGG pathways analyses of DEGs, we found that biological processes of upregulated genes mainly concentrated in cell division, spindle microtubule, protein kinase activity and the pathway of transcriptional misregulation in cancer. The downregulated gene mainly occurred in epidermis development, extracellular exosome, structural molecule activity, metabolic pathways and p53 signaling pathway. Studies have shown that the occurrence and metastasis of melanoma need to be realized through the promotion of cell mitosis and the growth of anti-aging and anti-apoptosis <ns0:ref type='bibr' target='#b34'>[32]</ns0:ref> . In addition, spindle microtubules can accelerate the proliferation and transfer of cells, and the regulation of metabolic pathways such as protein synthesis and transcriptional disorders can promote cell division <ns0:ref type='bibr' target='#b35'>[33]</ns0:ref> . The results showed that downregulated genes were associated with skin epidermal development, melanoma cells were produced in the basal layer of the epidermis and hair follicles, and epidermal keratinization could control the homeostasis of melanocytes <ns0:ref type='bibr' target='#b36'>[34]</ns0:ref> . Studies have found that most exosomes mediate the tumor process in the progression of melanoma <ns0:ref type='bibr' target='#b37'>[35]</ns0:ref> . Therefore, previous studies had confirmed our results.</ns0:p><ns0:p>In the 14 hub genes between PM and N, it had been found that matrix metalloproteinases (MMP) can participate in the skin matrix remodeling through degrading and rebuilding the matrix components, and affect the proliferation, survival, vascularization, protease expression and migration of melanoma cells <ns0:ref type='bibr' target='#b38'>[36]</ns0:ref> . MMP-9 knockdown can reduce the migration and invasion of melanoma cells and inhibit epithelial-mesenchymal transformation (EMT), thus being considered as a promising molecule for the CM treatment <ns0:ref type='bibr' target='#b39'>[37]</ns0:ref> . Meanwhile, bone morphogenetic protein (BMPs) is involved in the regulation of MMPs and is an inevitable factor in the migration and invasion of melanoma cells <ns0:ref type='bibr' target='#b40'>[38]</ns0:ref> . Fibroblast growth factor receptor 3 (FGFR3) may promote melanoma growth, metastasis, and EMT behavior by influencing the phosphorylation levels of ERK, AKT, and EGFR <ns0:ref type='bibr' target='#b41'>[39]</ns0:ref> . The loss of EphB6 may have deleterious immunological effects in cancer progression, while Hafner et al. <ns0:ref type='bibr' target='#b42'>[40]</ns0:ref> found that its expression decreased gradually in N, PM and MM. These previous studies had suggested that these hub genes may have a potential role in the development of CM.</ns0:p><ns0:p>In MM and PM, we found 18 hub genes through PPI network, all of which were downregulated genes. Several were associated with keratinocyte differentiation and epidermal development, such as loricrin (LOR), involucrin (IVL), filaggrin (FLG), small proline-rich protein1 (SPRR1)&#65292;keratin (KRT) and plakophilin (PKP1), which may result in loss of epidermal function. Among them, some hub genes had been found to be related to the production and metastasis of melanoma, such as SPRR1 <ns0:ref type='bibr' target='#b43'>[41]</ns0:ref> and PKP1 <ns0:ref type='bibr' target='#b44'>[42]</ns0:ref> . However, other genes had not been proven to be related to CM, such as LOR dysregulation was considered as an early indicator of potential malignant diseases, including oral submucosal fibrosis and leucoplasis <ns0:ref type='bibr' target='#b45'>[43]</ns0:ref> . IVL was a specific and sensitive marker of cell differentiation, the expression of IVL in head and neck squamous cell carcinoma patients with or without lymph node metastasis was significantly different <ns0:ref type='bibr' target='#b46'>[44]</ns0:ref> . Loss-of-function mutations in FLG can lead to a decrease in epidermal filaggrin and its degradation products, and increase the sensitivity of CM <ns0:ref type='bibr' target='#b47'>[45]</ns0:ref> . In MM and PM, the downregulated amplitude of FLG (log 2 FC = -5.404) was less than the amplitude in MM and N (log 2 FC = -8.586), while there was no significant difference between PM and N. It showed that FLG may be related to CM transfer, and this association needs to be verified by subsequent experiments. Studies had shown that KRT5 and KRT14 were involved in HNSCC differentiation and apoptosis as the epithelial proliferative markers <ns0:ref type='bibr' target='#b48'>[46]</ns0:ref> . Meanwhile, immunohistochemical staining of KRT14 and KRT16 in PM and MM were mostly negative, and the positive distribution contributed to the diagnosis of poorly differentiated squamous cell carcinoma <ns0:ref type='bibr' target='#b49'>[47]</ns0:ref> . CDSN was expressed in hair follicles and keratinized epithelial cells, played an important role in intercellular adhesion, and was related to skin barrier function and epidermal defense pathway <ns0:ref type='bibr' target='#b50'>[48]</ns0:ref> . Studies had found that mutations in the CDSN gene could cause excessive keratosis of the skin, and lead to peeling skin disease and hypotrichosis simplex of the scalp <ns0:ref type='bibr' target='#b51'>[49]</ns0:ref> , therefore, down-regulation of CDSN may accelerate the development of CM by slowing down epidermal development.</ns0:p><ns0:p>In MM and PM, there were some hub genes associated with EMT. EMT was normally associated with embryogenesis and wound healing, but in tumor cells, it promoted tumor Manuscript to be reviewed metastasis by enabling cells to leave the epithelium and acquire mesenchymal specificity <ns0:ref type='bibr' target='#b52'>[50]</ns0:ref> . This process increased the aggressiveness of the tumor by the loss of the epithelial phenotype (Ecadherin, desmosin, laminin-1) and the acquisition of the mesenchymal marker (N-cadherin) <ns0:ref type='bibr' target='#b54'>[51]</ns0:ref> . Hub gene desmoglein1(DSG1) could control the role of keratinocytes, and contribute to the page-like behavior in the development of melanoma <ns0:ref type='bibr' target='#b55'>[52]</ns0:ref> . Furthermore, desmocollin1(DSC1) and desmocollin3(DSC3) are members of the E-cadherin superfamily, involved in cell-cell adhesion and cell-extracellular matrix interaction. Benign melanocytes expressed high levels of Ecadherin, and during the transition to melanoma cells, E-cadherin was down-regulated and Ncadherin was up-regulated <ns0:ref type='bibr' target='#b56'>[53]</ns0:ref> . Studies had shown that desmoplakin (DSP) was a desmosomal protein involved in cell-cell adhesion. Desmosome formation was characteristic of cell differentiation and intercellular adhesion, and the loss of desmosome might accelerate the occurrence and early migration of tumor cells <ns0:ref type='bibr' target='#b57'>[54]</ns0:ref> .</ns0:p><ns0:p>There are also some hub genes between MM and PM had been found to be related to CM, for example, the down-regulation of cystatin A (CSTA) expression has become an important feature to distinguish N, PM and MM <ns0:ref type='bibr' target='#b59'>[55]</ns0:ref> . Several S100 family genes had been found to be highly expressed in PM, but low level in MM <ns0:ref type='bibr' target='#b60'>[56]</ns0:ref> . In particular, the loss of S100A7 is highly correlated with the metastasis progression score <ns0:ref type='bibr' target='#b61'>[57]</ns0:ref> . Lentin et al. <ns0:ref type='bibr' target='#b62'>[58]</ns0:ref> observed that the anti-invasion effect of transglutaminase(TGM) might lead to the post-translational modification of some components of the cell basal membrane, thereby interfering with the metastasis of melanoma cells. The activity of TGM2 had a protective effect on the progression of melanoma in vivo <ns0:ref type='bibr' target='#b63'>[59]</ns0:ref> , but no studies had been conducted to prove the relationship between TGM1 and CM, so TGM1 may be a new potential marker.</ns0:p><ns0:p>We found that most of the above hub genes had been reported to be closely related to the generation and metastasis of CM. Moreover, through prognostic analysis, most hub gene expression differences in CM patients were connected with overall survival, which proved the reliability of our study. There are still a few genes that had not been reported or experimentally confirmed to be associated with CM, but some of them are related to the occurrence and development of other cancers. So they might be potential biomarkers of CM, and a large number of experiments are needed to confirm. Most hub genes, such as LOR, IVL, FLG, DSG3, TGM1, KRT16, SPRR1A, KRT14, DSP and CSTA, showed no difference in the expression of PM and N, but significantly decreased in MM and PM, suggesting that these genes might be potential predictors of CM metastasis. The expression of some genes, such as CDSN, DSG1, DSC3, DSC1 and DSP, was downregulated in all three groups, which might be relate with the occurrence and progression of CM. It is worth noting that three genes, SPRR1B, PKP1 and S100A7, were upregulated in PM and N, but downregulated in MM and PM, which were likely to be used as novel markers to distinguish whether CM was metastatic or not. These assumptions need to be tested experimentally.</ns0:p><ns0:p>Compared with previous studies, we used more samples, and compared N, PM and MM in pairs, then took the intersection, so as to make the experimental results more reliable. Besides using GEO data sets, we also used TCGA data for verification, which increased the sample size and accuracy. However, the limitation of this study is the lack of experimental verification of hub genes. Therefore, to understand whether the hub genes are really closely related to the generation and metastasis of CM, a large number of subsequent experiments are needed to explore.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In conclusion, through bioinformatics analysis, we obtained some potential key genes and biological pathways related to the occurrence and metastasis of CM, providing directions for future research. In addition to the genes that have been reported and demonstrated, other identified key genes may be potential prognostic markers and therapeutic targets for CM occurrence and metastasis. Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 3</ns0:note><ns0:p>GO functions and KEGG pathways enrichment analysis of the upregulated and downregulated genes between primary cutaneous melanoma and normal skin.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:49579:2:0:NEW 29 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 4</ns0:note><ns0:p>GO functions and KEGG pathways enrichment analysis of the upregulated and downregulated genes between metastatic cutaneous melanoma and normal skin.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:49579:2:0:NEW 29 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 5</ns0:note><ns0:p>GO functions and KEGG pathways enrichment analysis of the upregulated and downregulated genes between metastatic cutaneous melanoma and primary cutaneous melanoma.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:06:49579:2:0:NEW 29 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 6</ns0:note><ns0:p>The PPI network of DEGs was constructed by using Cytoscape. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:06:49579:2:0:NEW 29 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 1 Experimental</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 2 Venn</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>A) PPI network of DEGs between PM and N of the three data sets. (B) PPI network of DEGs between MM and N of the three data sets. (C) PPI network of DEGs between MM and PM of the three data sets.</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='24,42.52,199.12,525.00,327.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='25,42.52,199.12,525.00,342.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='26,42.52,219.37,525.00,420.75' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='30,42.52,199.12,525.00,364.50' type='bitmap' /></ns0:figure> </ns0:body> "

"Central South University NO.172 Tongzipo Road Yuelu District, Changsha, Hunan, China http://www.csu.edu [email protected] August 16th, 2020 Dear Editors First of all, I would like to thank the editors and reviewers for their generous comments on my manuscript. We have revised and edited the article, and replied to all the questions of reviewers and editors in the following part. We believe and hope that this manuscript is now suitable for publication in PeerJ. Hanying Dai Department of Laboratory Medicine, the Third Xiangya Hospital On behalf of all authors. Editor comments (Paula Soares) - In the abstract please include more precise information about the pathways deregulated in primary Melanoma vs NT vs Metastatic lesions. We quite agree with your opinion. We have added more precise information about the pathway deregulated between NT, primary and metastatic melanoma, as shown in the result part of the abstract. - In line 202 please confirm the number of cases in the sentence 'Among them, 1 case was normal sample, 104 cases were PM samples, and 368 cases were MM samples. We found that the expression of those hub genes in MM samples decreased significantly compared with PM samples (Fig. 11).' The series only includes a single normal sample and 104 primary melanomas? Thank you for your suggestion. In the article, we used UALCAN and respectively to verify and analyze the expression and overall survival of hub genes. Among them, UALCAN was used to compare gene expression of different sample types in the TCGA database, which contained information of 1, 104 and 368 cases of normal skin, primary and metastatic melanoma. Therefore, UALCAN was used to verify the differences in the expression of key genes between primary and metastatic melanoma (Fig. 9). GEPIA was used to analyze the overall survival of all skin melanoma patients with high or low expression of hub genes (Fig. 10). In this regard, we had given a more detailed explanation in this paper, provided a clearer figure, and marked whether the expression difference was statistically significant in the figure (Fig. 9). - In line 235 please delete the sentence 'The inactivation of p53 has an influence on the occurrence of melanoma[36], and the defective p53 pathway also has an anti-apoptotic effect[37].'. It is incorrect! Thank you for your correction, it had been deleted. - As noted by the reviewer, the manuscript has an excessive number of Figures. Please reduce the number of Figures or transfer some to Supplementary data. Thank you for your advice. We had deleted the figure 9 and figure 10 from the article and moved them into supplementary data (Fig. s1, Fig. s2). Reviewer 1 (Xin Zhang) Basic reporting No comment. Experimental design No comment. Validity of the findings No comment. Comments for the Author Melanoma is a malignant tumor of melanocytes, and the incidence has increased faster than any other cancer over the past half century. Most primary cutaneous melanoma can be cured by local excision, but metastatic cutaneous melanoma has a poor prognosis. Therefore, the research on the mechanism of cutaneous melanoma metastasis will be beneficial to diagnose the metastatic melanoma early, improve the treatment, and prolong the survival of patients. In this study, Dai Hangying and colleagues identified the key genes and molecular pathways involved in the occurrence and metastasis of cutaneous melanoma. The study provides the conclusion, which showed that some DEGs were found from normal skin, primary melanoma and metastatic melanoma samples. These hub genes may play an important role in the generation, invasion, recurrence or death of CM, providing new ideas and targets for the diagnosis and treatment of metastatic cutaneous melanoma. The paper is improved and most concerned raised by the reviewer have been addressed. But there are still questions to be answered. Thank you for your approval. Major concerns: 1. Too many pictures need to be deleted, too many network pictures, lack of presentation meaning. Thank you very much for your advice. We had deleted the figure 9 and figure 10 from the article and moved it into supplementary data (Fig. s1, Fig. s2). 2. Make sure the text is clearly visible in the figures. Thank you for your advice. We had changed the clarity of the figures and enlarged the text in the figures. Minor concerns: 1. Figure 11. Please convert the data logarithmically. Thank you for your advice. Since UALCAN is an online software, it can classify statistics and analyze the data in TCGA. We had tried to log-convert the Y-axis data in figure 9, but since the software only provided median, maximum, minimum, Q1 and Q3 without the original data, we cannot convert the TPM value on the Y-axis to log2(TPM + 1). However, we marked whether the expression difference between different groups in figure 9 was statistically significant and provided a clearer figure. We are very grateful to the editors and reviewers for their approval and advice of my article. We hope and believe that after the modification, my article will be more suitable for publication on PeerJ. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Background. Dye wastewater increases cancer risk in humans. For the treatment of dyestuffs, biodegradation has the advantages of economy, high efficiency, and environmental protection compared with traditional physical and chemical methods.</ns0:p><ns0:p>Laccase is the best candidate for dye degradation because of its multiple substrates and pollution-free products. Methods. Here, we modified the laccase gene of Bacillus licheniformis by error-prone PCR and site-directed mutagenesis and expressed in E. coli. The protein was purified by His-tagged protein purification kit. We tested the enzymatic properties of wild type and mutant laccase by single factor test, and further evaluated the decolorization ability of laccase to acid violet, alphazurine A, and methyl orange by spectrophotometry. Results. Mutant laccase Lac ep69 and D500G were superior to wild type laccase in enzyme activity, stability, and decolorization ability. Moreover, the laccase D500G obtained by site-directed mutagenesis had higher enzyme activity in both, and the specific activity of the purified enzyme was as high as 426.13 U/mg. Also, D500G has a higher optimum temperature of 70&#8451; and temperature stability, while it has a more neutral pH 4.5 and pH stability. D500G had the maximum enzyme activity at a copper ion concentration of 12 mM. The results of decolorization experiments showed that D500G had a strong overall decolorization ability, with a lower decolorization rate of 18% for methyl orange and a higher decolorization rate of 78% for acid violet. Conclusion. Compared with the wild type laccase, the enzyme activity of D500G was significantly increased. At the same time, it has obvious advantages in the decolorization effect of different dyes. Also, the advantages of temperature and pH stability increase its tolerance to the environment of dye wastewater.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>INTRODUCTION</ns0:head><ns0:p>Laccases (phenol-oxygen oxidoreductase; EC 1.10.3.2), a copper-containing polyphenol oxidase, belong to the superfamily of blue poly copper oxidases (MCOs) <ns0:ref type='bibr'>(Morozova et al., 2007;</ns0:ref><ns0:ref type='bibr'>Hakulinen &amp; Rouvinen, 2015)</ns0:ref>. Laccase was first discovered in the permeate of Rhus vernicifera <ns0:ref type='bibr'>(Legrand &amp; Martin, 1958)</ns0:ref>. Thereafter, they were also found in plants, fungi, bacteria, and insects <ns0:ref type='bibr' target='#b5'>(Chakroun et al., 2010;</ns0:ref><ns0:ref type='bibr'>Forootanfar et al., 2011;</ns0:ref><ns0:ref type='bibr'>Halaburgi et al., 2011)</ns0:ref>. There are many studies on fungal laccase and bacterial laccase. White rot fungi of the basidiomycete family are mostly studied in laccase-producing fungi. At present, it has been found that bacterial laccase mainly comes from Bacillus sp. <ns0:ref type='bibr'>(Mollania et al., 2011;</ns0:ref><ns0:ref type='bibr'>Chen et al., 2017)</ns0:ref>, <ns0:ref type='bibr'>Streptomyces (Freeman et al., 1993)</ns0:ref>, and Pseudomonas <ns0:ref type='bibr'>(Francis &amp; Tebo, 2001)</ns0:ref>. Laccases can catalyze phenols, polyphenols <ns0:ref type='bibr'>(Koschorreck et al., 2008;</ns0:ref><ns0:ref type='bibr'>Zeng et al., 2011;</ns0:ref><ns0:ref type='bibr'>Revanth, Niranjan &amp; Sarma, 2020)</ns0:ref>, polycyclic aromatic hydrocarbons, certain inorganic substances, and more. As a result, they are widely used for the decolorization of synthetic dyes <ns0:ref type='bibr'>(Pereira et al., 2009;</ns0:ref><ns0:ref type='bibr'>Mendes et al., 2011)</ns0:ref>, synthesis of organic substances, food processing, biosensor <ns0:ref type='bibr'>(Zhang et al., 2019)</ns0:ref>, and other fields. The molecular structure of laccase contains four copper ions. There are three types based on magnetic and spectral properties: Type 1 (T1), Type 2 (T2), and type 3 (T3) copper ions. T1 Cu 2+ , located at the substrate-binding site, is responsible for transferring substrate electrons <ns0:ref type='bibr'>(Martins et al., 2015)</ns0:ref>. T2 Cu 2+ and T3 Cu 2+ are located at the oxygen molecule binding site, where oxygen molecules combine with electrons to generate water <ns0:ref type='bibr'>(Sakurai &amp; Kataoka, 2007</ns0:ref><ns0:ref type='bibr' target='#b5'>, 2010)</ns0:ref>.</ns0:p><ns0:p>Dye wastewater has become one of the main hazardous industrial sewage due to a large number of dyes and intermediates. According to chemical properties, dyes are divided into reactive dyes, acid dyes, basic dyes, disperse dyes, vat dyes, sulfur dyes, mordants, direct dyes, naphthol dyes, solvent dyes, and organic pigments <ns0:ref type='bibr' target='#b2'>(Bhatia et al., 2017)</ns0:ref>. Synthetic dyes with strong carcinogenic polycyclic aromatic hydrocarbons as raw materials have become more commonly used dyes in the printing and dyeing industry because of their stable physical and chemical properties and low cost. Wastewater from the printing and dyeing industry is discharged into freshwater without treatment, which seriously affects the growth of aquatic organisms and microorganisms <ns0:ref type='bibr'>(Mishra &amp; Maiti, 2018)</ns0:ref>, and destroys the self-purification of water bodies <ns0:ref type='bibr'>(Tkaczyk et al., 2020;</ns0:ref><ns0:ref type='bibr'>Gowri et al., 2014)</ns0:ref>. At the same time, azo and anthraquinone dyes will produce a variety of carcinogenic aromatic amines during specific decomposition, which can cause</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed cancer, mutagenesis, and reproductive toxicity <ns0:ref type='bibr' target='#b0'>(Ali et al., 2019)</ns0:ref>. The objects of this study are both azo (methyl orange, alphazurine A) and anthraquinone (acid violet) dyes that are acid.</ns0:p><ns0:p>In terms of dye degradation, white rot fungal laccase has many problems, such as a long culture period and high cost. Therefore, researchers turned their attention to bacterial laccase.</ns0:p><ns0:p>( <ns0:ref type='bibr'>Michniewicz et al., 2008;</ns0:ref><ns0:ref type='bibr'>Hadibarata et al., 2012;</ns0:ref><ns0:ref type='bibr'>Tian et al., 2014;</ns0:ref><ns0:ref type='bibr'>Zheng et al., 2017;</ns0:ref><ns0:ref type='bibr'>Legersk&#225;, Chmelov&#225; &amp; Ondrejovi&#269;, 2018)</ns0:ref>. In 1993, Givaudan first detected laccase activity in Awspirillum lipoferum <ns0:ref type='bibr'>(Givaudan et al., 1993)</ns0:ref>. Numerous studies have shown that certain bacterial laccases, such as CotA laccases from Bacillus capsid protein, are more tolerant than fungal laccase in neutral or alkaline environments. <ns0:ref type='bibr'>(Zhang et al. 2012;</ns0:ref><ns0:ref type='bibr'>Lu et al., 2012;</ns0:ref><ns0:ref type='bibr'>Guan et al., 2014;</ns0:ref><ns0:ref type='bibr'>Martins et al., 2015;</ns0:ref><ns0:ref type='bibr'>Wang et al., 2016)</ns0:ref>. This bacterial laccase is more suitable for the environment of dye wastewater and exhibits higher enzyme activity. However, the enzyme activity of a crude enzyme solution of wild bacterial laccase is often lower. Direct modification of proteins is an effective way to improve enzyme activity and stability <ns0:ref type='bibr'>(Chen et al., 2017)</ns0:ref>. This technology mainly includes two strategies: rational design and directed evolution. Rational designs are usually based on computeraided structural modeling of enzyme proteins, using site-directed mutation techniques, knockout, and insertions of protein sequences to alter the properties and functions of the target protein.</ns0:p><ns0:p>Finally, target protein properties were analyzed by measuring enzyme activity. Directed evolution aims to construct a set of random gene transformations in vitro by mimicking natural evolution, and then select target proteins through library construction and high-throughput screening. It can be achieved by error-prone PCR and DNA recombination techniques <ns0:ref type='bibr' target='#b3'>(Bornscheuer &amp; Pohl, 2001;</ns0:ref><ns0:ref type='bibr' target='#b1'>Berman, 2008)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Here, we used a laboratory-constructed plasmid containing laccase constructed by Bacillus licheniformis as a template, modified target genes by error-prone PCR and site-directed mutation, screened mutants with higher enzyme activity, and further evaluated the decolorization ability of wild-type and mutant laccase to dyes. </ns0:p></ns0:div> <ns0:div><ns0:head>MATERIALS AND METHODS</ns0:head></ns0:div> <ns0:div><ns0:head n='2.2'>Enzyme activity assay</ns0:head><ns0:p>Laccase oxidation reaction was carried out at 50&#176;C in vitro, using ABTS as a substrate. In a solution containing 50 mM tartaric acid buffer (pH 3.0), 1 mM ABTS and 1 mM CuCl 2 300 &#956;L of enzyme solution was added to 3 mL of reaction system. After 5 minutes of reaction, the absorbance at 420 nm was measured. Under the above conditions, the amount of enzyme required to oxidize 1 &#956;mol of ABTS per minute is defined as one unit of enzyme activity (U). The assay was performed in quadruplicate. According to the study of Lu et al., some modifications were made to the enzyme activity determination method <ns0:ref type='bibr'>(Lu et al., 2012)</ns0:ref>.</ns0:p><ns0:p>The formula for calculating enzyme activity is shown in Eq. ( <ns0:ref type='formula'>1</ns0:ref>).</ns0:p><ns0:p>(1)</ns0:p><ns0:formula xml:id='formula_0'>U(U/mL) = &#8710;A &#120576;&#119887;&#119905; &#215; &#119881; 1 &#119881; 2 &#215; &#119899; &#215; 10 6</ns0:formula><ns0:p>Where &#916;A represents absorbance change value in time (t), b is the thickness of cuvette (cm), and t is the reaction time (min). V 1 and V 2 represent the volume of the reaction system (L) and a crude enzyme solution (L), respectively. n is a dilution ratio. ABTS: &#949; 420 =36 000 &#956; -1 &#8226;cm -1 .</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Error-Prone PCR</ns0:head><ns0:p>The laccase gene of B. licheniformis was randomly mutated by using the constructed recombinant plasmid pET-Lac containing the Lac gene as the template and adding the specific primers containing the enzyme cutting site (Table <ns0:ref type='table'>2</ns0:ref>). (Note: The error-prone PCR kit is only suitable for reactions with a gene length of less than 1,000 bp, but the Lac gene is 1,542 bp, so segmented PCR is performed). The mutant laccase gene was ligated with the linearized vector pET-30b (+) to form the recombinant plasmid pET-Lac ep , then transformed into E. coli BL21 competent cells, and then the positive transformants were screened with LB medium containing ampicillin. Using ABTS as a substrate, a 96-well plate method was used to screen mutants with laccase activity. Positive clones were sequentially added to 96-well plates for overnight culture, in which 200 &#956;L of resistance medium was added to the wells beforehand. The 10 &#956;L culture was added to a new 96-well plate in turn and incubated for 4 h using IPTG induction. After the culture, the bacteria were precipitated at -80&#8451; and repeatedly frozen and thawed three times. The bacteria were resuspended with Tri-HCl and lysed with lysozyme, and the lysate was centrifuged to obtain the supernatant. Enzyme activity of the supernatant was determined and mutants with higher enzyme activity were screened. Manuscript to be reviewed enzyme can digest methylated templates. After treatment with Dpn I enzyme, it was then transformed into FDM competent cells. All mutants were screened and further confirmed by DNA sequencing. Plasmids containing the desired mutations were then transformed into E. coli BL21 (DE3) for protein expression.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>Site-directed mutagenesis</ns0:head></ns0:div> <ns0:div><ns0:head n='2.5'>Expression and Purification of laccases</ns0:head><ns0:p>E. coli BL21 (DE3) containing WT laccases gene (Lac) and mutant laccase genes (Lac ep69 and D500G) were cultured overnight in 10 mL LB medium containing ampicillin (100 mg/mL) at 37&#176;C</ns0:p><ns0:p>with shaking (180 rpm). Afterward, the overnight pre-culture was inoculated into a fresh 50 mL culture medium (1% inoculation) containing ampicillin (100 mg/mL) and incubated at 37&#176;C with shaking (180 rpm) until an optical density at 600 nm (OD 600 ) of 0.6 was reached. Then, isopropyl&#946;-D-1-thiogalactopyranoside (IPTG) was added to the culture medium to a final concentration of 0.1 mM, and the culture was induced at 16&#176;C, 100 rpm. Samples were taken every two hours and 12% SDS-PAGE was used to detect the expression of target proteins <ns0:ref type='bibr'>(Laemmli, 1970)</ns0:ref>. Meanwhile, E. coli BL21 cells containing empty vector pET-30b (+) were used as control. Centrifuge (10 min, 8,000 &#215;g, 4&#176;C) to collect induced bacterial cells. Cells were crushed on ice and centrifuged (20 min, 8,000 &#215;g, 4&#176;C) to remove cell debris. Then, the supernatant was treated at 70&#176;C for 15 min, and the denatured protein was removed by centrifugation (10 min, 10,000 &#215;g, 4&#176;C) <ns0:ref type='bibr'>(Koschorreck, Schmid &amp; Urlacher, 2009;</ns0:ref><ns0:ref type='bibr'>Nasoohi et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Based on the histidine tag carried on the vector pET-30b (+), we purified the recombinant laccase using the His-tagged protein purification kit. Then, according to the SDS-PAGE results, the pure enzyme solution was desalted by Amicon ultrafiltration (membrane retention value: 10 kDa; Millipore, Billerica, Ma, USA). According to Bradford's method, bovine serum albumin was used to make the protein standard curve, and the protein content of purified laccase was determined <ns0:ref type='bibr' target='#b4'>(Bradford, 1976)</ns0:ref>.</ns0:p><ns0:p>2.6 Characterization of laccases 2.6.1 Optimum temperature and thermal stability Optimum temperature and temperature stability of purified laccase activity were assessed by relative enzyme activity measured at different temperatures. The enzyme activity of laccase at different temperatures was measured after incubation at 50, 55, <ns0:ref type='bibr'>60, 65, 70, 75, 80, 85, 90, 95, and 100&#8451;</ns0:ref> for 1 hour under standard conditions, and the enzyme activity measured at 4&#8451; was defined as 100%.</ns0:p><ns0:p>2.6.2 Optimum pH and pH stability Optimum pH and pH stability of purified laccase activity were assessed by relative enzyme activity measured at pH 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5 under standard conditions, respectively. The pH of the enzyme reaction system was adjusted by 0.05 M citric acid-Na 2 HPO 4 buffer to 2.0, 2.5, 3.0, 3.5, 4.0, 4.5, 5.0, 5.5, 6.0, 6.5, and incubated at 4&#176;C overnight to measure the enzyme activity at different pH. The enzyme activity measured under pH 4 was defined as 100%, and the relative enzyme activity was calculated.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.6.3'>Copper ion concentration</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>To detect the effect of copper ion concentration on laccase activity, CuCl 2 solution with a final concentration of 0, 0.2, 0.4, 0.6, 0.8, 1.0, 1.2, 1.4, 1.6, 1.8, 2.0 mM was added to the reaction system, and laccase activity was determined under the optimum reaction conditions. The relative enzyme activity was calculated by taking the laccase enzyme activity measured under the same reaction system without adding CuCl 2 solution was determined to be 100%. The data were processed and analyzed using Origin 8.0 software. The decolorization rate calculation formula is shown in Eq. ( <ns0:ref type='formula'>2</ns0:ref>).</ns0:p><ns0:p>(2)</ns0:p><ns0:formula xml:id='formula_1'>D = A 0 -A 1 A 0 &#215; 100%</ns0:formula><ns0:p>Where D represents the decolorization rate (%), A 0 is the initial absorbance of the dye solution at the maximum absorption wavelength, A 1 results from the initial absorbance of the dye solution at the maximum absorption wavelength after the reaction.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>Dye decolorization</ns0:head><ns0:p>The decolorization ability of Lac, Lac ep69 , and D500G was tested with three dyes of acid violet (&#955; max =600 nm), alphazurine A (&#955; max =637 nm), and methyl orange (&#955; max =470 nm). Add 100 mg/mL purified enzyme protein, dye (40 mg/L acid violet, 20 mg/L alphazurine A, 20 mg/L methyl orange) and 1 mM CuCl 2 to tartaric acid buffer (0.1 M, pH 4.0) for decolorization reaction.</ns0:p><ns0:p>Samples were taken and centrifuged regularly (12,000 rpm, 2 min), and the decolorization effect was determined by spectrophotometry. All reactions are performed in quadruplicate.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.8'>Bioinformatics analysis</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed the cells were sonicated and purified. SDS-PAGE electrophoresis results of the purified product, intracellular supernatant, and cell debris are shown in Fig. <ns0:ref type='figure'>2</ns0:ref>. We found that under low temperature and low concentration inducer conditions, the recombinant Lac was mainly expressed in a soluble state but has a low content in the precipitate. And after purification, a single band can be obtained (Lane 1). Using ABTS as the substrate, the specific activity of the purified Lac was 121.75 U/mg.</ns0:p></ns0:div> <ns0:div><ns0:head>RESULTS</ns0:head></ns0:div> <ns0:div><ns0:head n='3.1'>Expression</ns0:head><ns0:p>Here, we used a 96-well plate method to screen a mutant strain Lac ep69 with higher enzyme activity than Lac, from the mutated Lac gene library generated by error-prone PCR. The mutant strain Lac ep69 's specific activity is 51.24 U/mg, which was 1.35 times higher than that of the wild strain 37.84 U/mg. After the alignment of multiple laccase gene sequences, we found a conserved aspartic acid at position 500 of the laccase, replacing aspartic acid with glycine to carry out the targeted modification of laccase (The data isn't displayed). The specific activity of Lac ep69 was 170.45 U/mg, and D500G was 426.13 U/mg.</ns0:p><ns0:p>3.2 Characterization of the purified wild-type and mutated laccases</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2.1'>Optimal pH and pH stability</ns0:head><ns0:p>The optimized pH and pH stability results of Lac, Lac ep69 , D500G after purification are shown in Fig. <ns0:ref type='figure'>3A, 3B</ns0:ref>. Lac ep69 and Lac have the same optimal pH of 4.0, while D500G is more neutral than Lac, with a pH increase of 0.5. Fig. <ns0:ref type='figure'>3B</ns0:ref> shows that at a pH of 4.0-5.5, the relative enzyme activity of Lac ep69 after 1 hour of incubation is stable above 75%, while the relative enzyme activity of D500G after 1 hour of incubation at 4.5-6.5 is stable above 80%. In contrast, D500G has higher enzyme activity and stability in a neutral environment.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed 3.2.2 Optimum temperature and temperature stability Tested the optimal temperature and temperature stability of Lac, Lac ep69 , D500G results as shown in Fig. <ns0:ref type='figure'>3C</ns0:ref>, 3D. The optimum temperature for both Lac ep69 and D500G was higher than Lac, which was 80 and 70&#176;C respectively. Their temperature stability is high. After incubating at 50-80&#176;C for 1 hour, Lac ep69 enzyme activity remained above 80%, while D500G enzyme activity remained above 85%. It indicated that mutants were more tolerant of temperature than the wild type, had higher enzyme activity in higher temperature environments, and were more suitable for enzyme industrialization. Besides, when the temperature increased to 85&#176;C the enzyme activity of Lac, Lac ep69 , and D500G showed a rapid decline trend, indicating that excessive temperature denatured the enzyme and inactivated it.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2.3'>Copper ion concentration</ns0:head><ns0:p>Tested the effect of different concentrations of copper ions on enzyme activity. As shown in Fig. <ns0:ref type='figure'>4</ns0:ref>, when the concentration of copper ions in the reaction system was 12 mM, the activity of wild-type laccase reached its peak. However, the mutant strains Lac ep69 and D500G only need 10 mM copper ion concentration to achieve maximum enzyme activity. This indicated that the mutant was more sensitive to copper ions than the wild type Lac.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.2.4'>Km value determination</ns0:head><ns0:p>Km represents the magnitude of the affinity of the enzyme to the substrate. The larger the Km, the smaller the affinity of the enzyme and the substrate, the lower the enzyme activity. We used</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Origin8.0 software to predict the km of Lac, Lac ep69 , and D500G after purification. The Km value of engineered bacteria Lac, mutant strains Lac ep69 and D500G was 21.69 mM, 19.54 mM, and 10.50 mM respectively, the trends were consistent with the previous experimental of the enzyme protein activity determination, which showed that the increase in affinity leads to the increase in enzyme activity.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.3'>Dye decolorization assays by laccase</ns0:head><ns0:p>Fig. <ns0:ref type='figure'>5A</ns0:ref>, 5B, and 5C show the decolorization of dyes by within 6 h. First, the rapid reaction phases of Lac, Lac ep69 , and D500G were all 0-1 h. Secondly, the degradation rates of the two mutant enzymes were significantly better than those of the wild type. And D500G has the best decolorization ability. The decolorization rate of Lac to three dyes: methyl orange 15%, alphazurine A 30%, and acid violet 40%. The decolorization rate of D500G for three dyes: methyl orange 18%, alphazurine A 70%, and acid violet 78%.</ns0:p><ns0:p>As shown in Fig. <ns0:ref type='figure'>5A-C</ns0:ref>, the enzymatic reaction within 0-1 hour belongs to the rapid reaction period, and the enzyme activity is relatively less affected at this time. Therefore, we compared the decolorization of the three dyes by the wild type and the mutant within 1 hour. The result is shown in Fig. <ns0:ref type='figure'>5D</ns0:ref>. There are differences in the decolorization rates of different dyes by laccase. Lac, Lac ep69 , and D500G all have lower degradation rates for methyl orange, but higher degradation rates for alphazurine A and acid violet. For the three dyes, the degradation efficiency of the mutant is always better than that of the wild type. Especially D500G shows a significantly enhanced degradation rate for all three dyes. From the perspective of enzyme activity, the higher enzyme</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed activity of D500G provides the possibility for dye degradation.</ns0:p></ns0:div> <ns0:div><ns0:head n='3.4'>Analysis of laccase protein structure</ns0:head><ns0:p>The results of the primary structure show that compared with the original Lac, the mutant strain Lac ep69 has six pairs of base changes (T811C, A944G, T998C, T1303C, A1389C, and T1440A) in the sequence. Correspondingly, the six pairs of amino acids (Cys271Arg, Lys315Arg, Ile333Thr, Phe435Leu, Lys463Asn, Phe480Leu) in Lac ep69 have also changed.</ns0:p><ns0:p>The results of Prote-Param analysis of Lac, Lac ep69 , and D500G are shown in Table <ns0:ref type='table' target='#tab_2'>3</ns0:ref>. First, D500G and Lac ep69 are stable proteins. According to the stability coefficient data, Lac (40.03)&gt; Lac ep69 (39.57)&gt; D500G (39.40). It is noteworthy that D500G has the highest stability. The change of the protein's primary structure will affect its spatial structure, which will affect the intermolecular forces and steric hindrance to varying degrees, thereby changing the stability of the protein. Also, the increase in stability provides theoretical support for the increase in the enzyme activity of D500G. Secondly, wild-type and mutant laccase proteins have similar molecular weights and are both hydrophilic proteins, although the hydrophilicity of Lac ep69 and D500G is slightly decreased. Amino acid changes, before and after mutation, led to hydrophilic amino acids were replaced by hydrophobic amino acids, hydrophobic R groups to a certain extent weakened the hydrophilicity of enzyme proteins. The difference marks are highlighted in circles in Manuscript to be reviewed 61.4% random coils, 8.19% &#945;-helix, 5.26% &#946;-turns, and 25.15% extended chains. Lac ep69 has 60.62% random curl, 9.36% &#945;-helix, 4.29% &#946;-turn, and 25.73% extended chain. D500G has 59.45% random curl, 8.58% &#945;-helix, 5.85% &#946;-turn, and 26.12% extended chain. Due to the change of amino acids, the proportion of &#945;-helix increases, the random curl decreases, and other structural changes are small. Lac, Lac ep69 , and D500G tertiary structure prediction, Swiss-Model analysis results are shown in Fig. <ns0:ref type='figure' target='#fig_6'>8</ns0:ref>. The alpha-helical of the mutant laccase Lac ep69 is reduced by one, except that the amino acid at position 463 appears on the random curl, and the others are in the &#946;-turn. The tertiary structure of Lac ep69 is similar to Lac. However, the &#945;-helix and &#946;-turn angles of D500G are reduced, and the structure shows a loose transition state, in which the amino acid at position 500 appears on the &#946;-turn angle. The mutated base is located near the active center of the enzyme, which may increase the activity of the enzyme. Lac, Lac ep69 , and D500G mutation sites are shown in Fig. <ns0:ref type='figure'>9</ns0:ref>.</ns0:p><ns0:p>Overall, the number of Lac ep69 hydrogen bonds didn't change. Changes in amino acids affect the distribution of the atomic electron cloud around the atom. Changes in the electron cloud and hydrogen bonds may be one of the reasons affecting the enzyme activity of laccase.</ns0:p></ns0:div> <ns0:div><ns0:head>DISCUSSION</ns0:head><ns0:p>The crude laccase enzyme activity of the original B. licheniformis in this study was only 11.99 U/mg, which is because the endogenous expression level of most bacterial laccases is relatively low <ns0:ref type='bibr'>(Chen et al., 2015)</ns0:ref>. While heterologous expression of laccase is one of the effective ways to solve this poser. The low expression level of wild-type laccase is the key to the low activity of the PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed crude enzyme solution of B. licheniformis. Also, laccase belongs to intracellular localization, E.</ns0:p><ns0:p>coli expression system is a better choice <ns0:ref type='bibr'>(Wu et al., 2010)</ns0:ref>. So, we obtained a 1.37-fold increase in the expression of recombinant laccase Lac by heterologous expression in E. coli, but its enzyme activity was still lower. The intracellular enzyme may greatly reduce its original enzyme activity during the process of isolation and purification due to physical damage, inducer, and improper operation. Through directed evolution, two mutant laccases Lac ep69 and D500G with improved enzyme activity were obtained. Among them, obtained by site-directed mutation has higher enzyme activity, stability, and catalytic efficiency. This result is similar to that of some Bacillus spp. <ns0:ref type='bibr'>(Wang, Lu &amp; Feng, 2017;</ns0:ref><ns0:ref type='bibr'>Liu et al., 2011)</ns0:ref>.</ns0:p><ns0:p>Whether it is random mutagenesis or site-directed mutation, changes in amino acid will affect the spatial structure of the protein, which in turn affects the nature and function of the protein.</ns0:p><ns0:p>Studies have shown that factors such as the proportion of certain amino acids, protein accumulation, hydrophobicity, increased helical fold content, internal hydrogen bonding and density of salt bridges, and the distribution of charged residues on the surface are important factors that affect protein thermal stability <ns0:ref type='bibr'>(Kumar &amp; Nussinov, 2001;</ns0:ref><ns0:ref type='bibr'>Sterner &amp; Liebl, 2001)</ns0:ref>. Lac ep69 mutated 6 amino acid positions, and cysteine at position 271 was mutated to basic arginine, which may affect the optimal pH of the enzyme. The mutation of its non-polar isoleucine at position 333 to polar threonine may affect the hydrophobicity of the protein. The change in hydrophobicity, in turn, affects the stability of the protein.</ns0:p><ns0:p>Besides, the stability of protein structure is closely related to hydrogen bonds, because 1 mol of hydrogen bonds can provide 0.6 calories of energy to maintain the stability of protein structure.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>The improvement of hydrogen bond introduced by the amino acid mutation at position 271 of Lac ep69 is one of the important roles of enzyme protein stability <ns0:ref type='bibr'>(Mabrouk et al., 2011)</ns0:ref>. The cysteine at position 271 and the lysine at position 315 of Lac ep69 are both mutated to arginine.</ns0:p><ns0:p>Arginine can participate in a variety of non-covalent bond interactions, and its side chain can provide more space for charge interactions. These factors further improve the stability of the enzyme <ns0:ref type='bibr'>(KnoChel et al., 1996)</ns0:ref>. D500G's acidic amino acid, aspartic acid, becomes glycine, and the change in the optimal pH may be related to the change in the polarity of the amino acid. The side chain of aspartic acid is '-CH 2 COOH' and the side chain of glycine is hydrogen atom '-H'.</ns0:p><ns0:p>After the laccase mutation, the flexibility of the N-C and C-C framework changes, the binding force between the enzyme and the substrate becomes stronger, and the enzyme activity improves.</ns0:p><ns0:p>Changes in properties caused by the 500 amino acid change have also been found in other bacterial laccases <ns0:ref type='bibr'>(Koschorreck, Schmid &amp; Urlacher, 2009;</ns0:ref><ns0:ref type='bibr'>Nasoohi et al., 2013)</ns0:ref>.</ns0:p><ns0:p>The secondary and tertiary structure predictions show that Lac, Lac ep69 , and D500G are similar in structure, with little difference in physical and chemical properties. In general, the mutants only form certain secondary bonds in the structure, and the distribution of the electron cloud is slightly changed, but the sites that play a key role in the function of the enzyme are not changed. It is noteworthy that D500G differs greatly from Lac in secondary structure, which may be one of the reasons for its higher thermal stability and higher enzyme activity. Because the type and number of intramolecular forces usually affect the thermal stability and catalytic activity of enzyme molecules <ns0:ref type='bibr'>(Xie et al., 2014)</ns0:ref>.</ns0:p><ns0:p>After analyzing the degradation of different kinds of dyes, it is found that wild-type and mutant</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed laccases generally have lower degradation rates for methyl orange and higher degradation rates for acid violet. From the analysis of enzyme specificity, laccase has different specificities for dye molecules of different structures, and the degree of specific binding between the enzyme and the substrate determines the degradation effect of the substrate. The anthraquinone structure of acid violet belongs to the substrate dye of bacterial laccase laccase in this study, but has a low specificity with azo methyl orange <ns0:ref type='bibr'>(Yaropolov et al., 1994;</ns0:ref><ns0:ref type='bibr'>Galai, Youssoufi &amp; Marzouki, 2014)</ns0:ref>. From the perspective of mutants, D500G has the highest degradation rate for the three dyes among the three enzymes. The reasons for this result come from three aspects. First, from the molecular level, the mutation site of D500G structurally enhances its stability, which in turn affects its enzyme activity;</ns0:p><ns0:p>second, the structural change affects the affinity between the enzyme and the substrate, and Km value is powerful evidence. According to the enzyme kinetic theory, the Km value is negatively correlated with the substrate affinity, and among the three, the Km value of D500G is the smallest, which is 10.50&#177;0.32mM.</ns0:p><ns0:p>From the temperature analysis, the optimal temperature of the mutant is significantly improved, and high-temperature tolerance is also significantly increased. D500G still preserves more than 85% of the enzyme activity after being stored at a high temperature of 50-80&#8451; for one hour, which provides strong evidence for the improvement of the stability of the mutant. From the perspective of pH analysis, the optimum pH of D500G becomes larger, and at the same time, it still retains more than 80% of the enzyme activity after being stored at 4.0-5.5 for one hour. The improvement of temperature and pH tolerance increased the tolerance of D500G in dyes, and at the same time reducing the impact of the environment on enzyme activity, thereby increasing the mutant's </ns0:p></ns0:div> <ns0:div><ns0:head>CONCLUSION</ns0:head><ns0:p>In this study, we successfully screened a mutant laccase D500G with significantly improved decolorization of dyes by site-directed mutagenesis. Compared with wild-type laccase, D500G has significantly improved temperature and pH stability, which further enhances the tolerance of laccase in the dye wastewater environment and is more suitable for practical industrial production.</ns0:p></ns0:div> <ns0:div><ns0:head>ADDITIONAL INFORMATION AND DECLARATIONS</ns0:head></ns0:div> <ns0:div><ns0:head>Conflicts of Interest</ns0:head><ns0:p>The authors declare no conflicts of interest. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Forward and reverse mutation primers Lac-D-F and Lac-D-R were designed using the fast sitedirected mutagenesis kit. Using plasmid pET-Lac containing Lac as a template amplified mutant Lac. PCR products were digested using 1 &#956;L Dpn I enzyme (20 U/&#956;L) at 37&#176;C for 1 h. The Dpn I PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>and purification of wild-type and mutant laccases Nucleotide sequencing of the plasmid extracted from the positive transformant confirmed that Lac's ORF contains 1,542 bp that theoretically encode 513 amino acids with a molecular weight of about 60 kDa. (S1) The protein sequence has a 99% identity to the Lac gene of B. licheniformis (MK427697.1). The results of SDS-PAGE showed that the enzyme expression reached the highest level, after 10 hours of IPTG induction. Because the expression level increases from 2 to10 hours, 10 to 12 hours tends to remain unchanged. The results were shown in Fig. 1. After 10 hours of induction, PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Fig. 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>SOPMA results show that Lac, Lac ep69 , and D500G have similar secondary structures, and they are mainly composed of random coils. The results are shown in Fig.7. Compared with the wild type, the proportion of &#945;-helix in the mutant is increased and the random coil is decreased. Lac has PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:50780:1:1:NEW 4 Oct 2020)Manuscript to be reviewed degradation rate of dyes. The results of Fig.5A-C also proved that the mutant has a higher degradation rate in the first hour of the dye degradation process, and tends to end after 1 hour. It is speculated that the enzyme activity of the laccase in 1 hour is due to various reasons. The reduction ultimately leads to a decrease in its degradation rate.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>Figure 7</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 8</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>Figure 9</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='31,42.52,229.87,525.00,215.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='33,42.52,204.37,525.00,373.50' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='35,42.52,242.62,525.00,378.00' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 3 :</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Physicochemical properties of Lac, Lac ep69 and D500G</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Strain</ns0:cell><ns0:cell>molecular weight (Da)</ns0:cell><ns0:cell>isoelectric point</ns0:cell><ns0:cell>positively charged residues</ns0:cell><ns0:cell>negatively charged residues</ns0:cell><ns0:cell>instability coefficient</ns0:cell></ns0:row><ns0:row><ns0:cell>Lac</ns0:cell><ns0:cell>59074.20</ns0:cell><ns0:cell>6.25</ns0:cell><ns0:cell>60(Arg+Lys)</ns0:cell><ns0:cell>70 (Asp+Glu)</ns0:cell><ns0:cell>40.03</ns0:cell></ns0:row><ns0:row><ns0:cell>Lac ep69</ns0:cell><ns0:cell>59061.11</ns0:cell><ns0:cell>6.25</ns0:cell><ns0:cell>60(Arg+Lys)</ns0:cell><ns0:cell>70 (Asp+Glu)</ns0:cell><ns0:cell>39.57</ns0:cell></ns0:row><ns0:row><ns0:cell>D500G</ns0:cell><ns0:cell>59016.17</ns0:cell><ns0:cell>6.31</ns0:cell><ns0:cell>60(Arg+Lys)</ns0:cell><ns0:cell>70 (Asp+Glu)</ns0:cell><ns0:cell>39.40</ns0:cell></ns0:row></ns0:table></ns0:figure> </ns0:body> "

"List of reviewer comments and revisions of the manuscript Dear Editors and Reviewers, At first, many thanks for your letter and invaluable comments on our manuscript entitled “Improving decolorization of dyes by laccase from Bacillus licheniformis by random and site-directed mutagenesis. (Manuscript ID: PeerJ-50780)”. We have revised the paper according to your and other reviewers’ comments as follows: To Reviewer 1: Thank you very much indeed for your excellent comments on our manuscript. We are very glad to revise our paper according to your comments. The changes are highlighted in RED in the revised manuscript. Basic reporting Point 1: In the abstract section, I suggest giving information about the origin of the enzyme, at least mentioning the organism. Response 1: Thank you for your comments. According to your suggestion, we have supplemented the source of laccase in this experiment in the method section of the abstract, which is from Bacillus licheniformis. Please see the revision in lines 17-18, page 1。 Point 2: Line 27. It is not necessary to write that it has been repeatedly verified. Response 2: Thank you for your comments. Following your suggestion, we have rewritten the content of the conclusion in the abstract and deleted the results of repeated verification. Please see the revision in lines 33-36, page 2。 Point 3: In the introduction section. I suggest a bit more information on the origin of the enzyme, there is very little mention of the organism from which the enzyme comes from and although it is not the objective of the investigation, I consider it important to add information so that the audience knows the organism that produces said enzyme. Response 3: Thank you for your comments. Based on your suggestions, we have added more information about the origin of laccase in the introduction section. Please see the revision in lines 48-52, page 3。 We added references: Francis CA, Tebo BM. 2001. cumA multicopper oxidase genes from diverse Mn (II)-oxidizing and non-Mn (II)-oxidizing Pseudomonas strains. Applied & Environmental Microbiology 67:4272–4278. DOI: 10.1128/aem.67.9.4272-4278.2001. Freeman JC, Nayar PG, Begley TP, Villafranca JJ. 1993. Stoichiometry and spectroscopic identity of copper centers in phenoxazinone synthase: A new addition to the blue copper oxidase family. Biochemistry 32:4826–30. DOI: 10.1021/bi00069a018. Mollania N, Khajeh K, Ranjbar B, Hosseinkhani S. 2011. Enhancement of a bacterial laccase thermostability through directed mutagenesis of a surface loop. Enzyme and Microbial Technology 49:446–452. DOI: 10.1016/j.enzmictec.2011.08.001. Point 4: Line 66. The organism has not been mentioned before, write the full name. Response 4: Thank you for your comments. We apologize for our negligence. I have written the full name of the strain，Please see the revision in lines 102, page 5 Point 5: I consider that line 10 of the abstract can be developed a little more in the introduction section; This will give the study more impact. Response 5: Thank you for your comments. Under your suggestions, we have added more information about the hazards of dyes to the environment and humans in the introduction section. Please see the revision in lines 63-77, page 3-4 We added references: Ali I, Peng C, Naz I, Lin D, Saroj DP, Ali M. 2019. Development and application of novel bio-magnetic membrane capsules for the removal of the cationic dye malachite green in wastewater treatment. RSC Advances. DOI: 10.1039/C8RA09275C. Bhatia D, Sharma NR, Singh J, Kanwar RS. 2017. Biological methods for textile dye removal from wastewater: A review. Critical Reviews in Environmental Science & Technology. DOI: 10.1080/10643389.2017.1393263. Mishra S, Maiti A. 2018. The efficacy of bacterial species to decolourise reactive azo, anthroquinone and triphenylmethane dyes from wastewater: a review. Environmental Science and Pollution Research 25:8286–8314. DOI: 10.1007/s11356-018-1273-2. Tkaczyk A, Mitrowska K, Posyniak A. 2020. Synthetic organic dyes as contaminants of the aquatic environment and their implications for ecosystems: A review. Science of The Total Environment 717:137222. DOI: 10.1016/j.scitotenv.2020.137222. Experimental design Point 6: Line 77: acid, acid?? Response 6: Thank you for your comments. Sorry for our mistake. Following your suggestion, I have revised the terms here to the correct spelling format. Please see the revision in lines 113, page 6。 Point 7: Line 79: Eco RI Response 6: Thank you for your comments. Sorry for our mistake. I have changed the font format of the terms here to italics. Please see the revision in lines 114, page 6. Point 8: Line 93-98: Method reference. Response 7: Thank you for your reminding，The enzyme activity determination method in this article is the method in the reference and then modified according to your experiment. According to your suggestion, we have added the reference for this method at the end of section 2.2. Please see the revision in lines 135-136, page 7. We added references: Lu L, Zhao M, Wang T, Zhao L, Du M, Li T, Li D. 2012. Characterization and dye decolorization ability of an alkaline resistant and organic solvents tolerant laccase from Bacillus licheniformis LS04. Bioresource Technology 115:35-40. DOI: 10.1016/j.biortech.2011.07.111. Point 9: Line 112-113: Method reference or if it is from this study, I suggest describing it a bit more, for reproducibility. Response 9: Thank you for your comments. Sorry for our mistake. By your suggestions, we have added more detailed operating methods here to improve the repeatability of the experiment. Please see the revision in lines 153-160, page 8. Point 10: You can save the full name of the IPTG (it was already described above in the text). Response 10: Thank you for your reminding. According to your suggestion, we save the full name of the IPTG. Please see the revision in lines 118, page 6. Validity of the findings Point 11: Figure 1, I suggest placing it in the supplementary material. Response 11: Thank you for your reminding. According to your suggestion, we uploaded the data in S1 to the supplementary materials. Please see the revision in Fig.S1 Point 12: Figs 12 and 13. Mention in the legend of the figure, the development method (coomassie or silver). Response 12: Thank you for your reminding, and we apologize for our negligence. We have updated Fig.12. 13 and added the Coomassie Brilliant Blue R250 staining method in the legend part. Please see the revision in Fig.1. 2. Point 13: Lines 231 and 232: Here are the repeated data, I suggest removing them, as they are the same from the previous lines. Response 13: Thank you for your reminding. According to your suggestion, we have deleted duplicate data and re-modified this part. Please see the revision in lines 294-295, page 15. Point 14: The legend in figure 6 is confusing. I suggest Reorder the indications to observe and analyze the figure. Response 14: Thank you for your reminding, and we apologize for our negligence. According to your suggestion, we updated Fig. 6 and re-labeled the new legend. Please see the revision in Fig. 5. Point 15: Line: 254. There are no results in this table, instead are the primers for the PCR. Please, check this part. Response 15: Thank you for your reminding, and we apologize for our negligence. We have updated the corresponding result data table of this part of the content to Table 3, and re-uploaded Table 3. Please see the revision in Table 3. Point 16: In Figure 8. Specifically D500G, you know the location of the amino acids, so it would be helpful if in this figure you could point them out, at least with a box, and observe that possible changes; shown in fig 9. Response 16: Thank you for your reminding. According to your suggestion, we have updated Fig. 8 to use a red box to circle the label of the mutated amino acid position to better observe the position of the amino acid. Please see the revision in Fig. 7 . Point 17: Line: 285. Bacillus licheniformis B. licheniformis. Response 17: Thank you for your reminding, and we apologize for our negligence. According to your suggestion, we have revised this to the abbreviated form “B. licheniformis”. Please see the revision in lines 394, page 20. Point 18: In the supplementary material (specifically: optimum copper ion concentration) you should switch to the English language. Response 18: Thank you for your reminding, and we apologize for our negligence. We have switched the optimal copper ion concentration in the supplementary material to the English input format and re-uploaded the supplementary material Raw data (3). Please see the revision in Raw data (3). Point 19: In the conclusion section. I suggest not to expand too much and not to put data that was previously shown and discussed in the text. Response 19: Thank you for your reminding. According to your suggestion, we re-revised the conclusion section and removed too many extensions. Please see the revision in “CONCLUSION”. Comments for the author Point 20: Only if you have images of the dyes with the respective enzymes, wild type, and mutant; They would be of great help in observing the improvement in discoloration and the laccase activities. It is just a suggestion and if you have the pictures you could include them in the supplementary material. Response 20: Thank you for your reminding. First of all, we think your suggestions are of great significance to the completeness of our research. If possible, I hope to add this part of the data to increase the intuitiveness of the degradation effect. At the same time, we will use your opinion in the follow-up research and keep the relevant picture materials of the color change of the dye. However, considering that the relevant images of dye decolorization were not saved in time during the previous experiments, this part of the data is temporarily lacking. To Reviewer 2: Thank you for your inestimable comments on our manuscript. We are very glad to revise our paper according to your suggestions. The changes are highlighted in RED in the revised manuscript. Comments for the author Thank you very much for your affirmation of our research content, which is extremely important and encouraging to us. Experimental design Point 1: A lack of a discussion of magnetic and spectral properties of these true or laccase-like multi-copper oxidases compared to other bacterial laccases. Response 1: Thank you for your reminding. Your suggestions are essential for our study, especially for the depth of the discussion section of this study, and the analysis of the magnetic and optical properties of proteins provides more effective persuasion in terms of site-directed mutation improving enzyme activity and improving enzyme stability. We would be willing to include this aspect in later studies. However, it may take some time to complete this result in terms of current laboratory equipment and technology. Point 2: A lack of zymograpgy data revealing enzyme activity and dye decolorization potential. Response 2: Thank you for your reminding. And we apologize for our negligence. We have added enzyme activity and enzymatic data on dye degradation in the supplementary material. Please see the revision in Raw data (3). Point 3: A lack of statistical optimization approach using experimental designs for the dye decolourization process. Response 3: Thank you for your reminding. We apologize for our negligence. We have supplemented the statistical optimization of the dye decolorization process. Please see the revision in “Raw data (3)”. Point 4: The authors should give proper and more justification for their claim that the mutant enzyme has a high degradation capacity for the dyestuffs. For this, in-silico, in-vitro, or in-vivo toxicity tests of dye degradation products should be given. Response 4: Thank you for your comments. First of all, I think your proposal is of vital importance to the integrity of our research content. Based on your suggestion, we have added a more detailed explanation to the discussion part about mutants with high degradability in terms of dyes, so we have rewritten this paragraph. Please see the revision in lines 444-473, page 22-23. Regardin3-g toxicity analysis tests for degradation products, we have been conducting these tests recently. However, due to problems such as experimental conditions and equipment, it may take some time to obtain valid data. Point 5: The activity of the mutant enzyme at acidic pHs could limit its application in dye wastewater treatment particularly in the textile industry. Response 5: Thank you for your reminding. First of all, we believe that your suggestion is of great significance to the completeness of our research, because it is also one of the important contents that we will study next. Secondly, we apologize for the lack of comprehensiveness in the narrative of the research content. Then we have made a more detailed supplement on the background of dyes in the preface. Please see the revision in lines 63-77, page 3-4. And we will give a reasonable explanation for this problem. The textile industry wastewater contains a large number of synthetic dyes. Among them, synthetic dyes are used more for their stable physical and chemical properties and low prices. According to their chemical properties, dyes are divided into reactive dyes, acid dyes, basic dyes, disperse dyes, vat dyes, sulfur dyes, mordants, direct dyes, naphthol dyes, solvent dyes, and organic pigments (Bhatia et al., 2017). The objects of this study are both azo (methyl orange, subspecies green) and anthraquinone (acid violet) dyes that are acid. In our research, the laccase obtained by site-directed mutagenesis has a significant increase in enzyme activity and stability and a wider pH adaptation range. Compared with fungal laccase, tolerance has been significantly improved. For acid dyes, the degradation effect of D500G is significant, although it may not perform well in alkaline environments. The research on the degradation of basic dyes by the bacterial laccase will continue in our laboratory's follow-up research. References: Bhatia D, Sharma NR, Singh J, Kanwar RS. 2017. Biological methods for textile dye removal from wastewater: A review. Critical Reviews in Environmental Science & Technology. DOI: 10.1080/10643389.2017.1393263. Point 6: many typos and grammar check-up are also needed (lines 52, 293, 306, ..) Response 6: Thank you for your comments. And we apologize for our mistakes. Basing on your suggestions, we have updated the literature and revised the mistyping and grammar issues. Please see the revision in lines 83, 403, 416-420 "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Background:</ns0:head><ns0:p>The mutualistic symbiosis between the gut microbial communities (microbiota) and their host animals has attracted much attention. Many factors potentially affect the gut microbiota, which also varies among host animals. The native Chinese three-keeled pond turtle (Chinemys reevesii) and the invasive red-eared slider turtle (Trachemys scripta elegans) are two common farm-raised species in China, with the latter generally considered a more successful species. However, supporting evidence from the gut microbiota has yet to be collected.</ns0:p></ns0:div> <ns0:div><ns0:head>Methods:</ns0:head><ns0:p>We collected feces samples from these two turtle species raised in a farm under identical conditions, and analyzed the composition and relative abundance of the gut microbes using bacterial 16S rRNA sequencing on the Roach/454 platform.</ns0:p></ns0:div> <ns0:div><ns0:head>Results:</ns0:head><ns0:p>The gut microbiota was mainly composed of Bacteroidetes and Firmicutes at the phylum level, and Porphyromonadaceae, Bacteroidaceae and Lachnospiraceae at the family level in both species. The relative abundance of the microbes and gene functions in the gut microbiota differed between the two species, whereas alpha or beta diversity did not. Microbes of the families Bacteroidaceae, Clostridiaceae and Lachnospiraceae were comparatively more abundant in C. reevesii, whereas those of the families Porphyromonadaceae and Fusobacteriaceae were comparatively more abundant in T. s. elegans. In both species the gut microbiota had functional roles in enhancing metabolism, genetic information processing and environmental information processing according to the Kyoto Encyclopedia of Genes and Genomes database. The potential to gain mass is greater in T. s. elegans than in C. reevesii, as revealed by the fact that the Firmicutes/Bacteroidetes ratio was lower in the former species. The percentage of human disease-related functional genes was lower in T. s. elegans than in C. reevesii, presumably suggesting an enhanced potential to colonize new habitats in the former species.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>INTRODUCTION</ns0:head><ns0:p>The past few years have witnessed much attention paid to the gut microbiota of aquatic animals including invertebrates <ns0:ref type='bibr' target='#b39'>(Meziti, Mente &amp; Kormas, 2012;</ns0:ref><ns0:ref type='bibr' target='#b67'>Wang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b19'>Gao et al., 2020)</ns0:ref>, fish <ns0:ref type='bibr' target='#b10'>(Divya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b71'>Xing et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b14'>Egerton et al., 2018)</ns0:ref>, reptiles <ns0:ref type='bibr' target='#b1'>(Ahasan et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b76'>Zhang et al., 2019;</ns0:ref><ns0:ref type='bibr' target='#b54'>Scheelings et al., 2020)</ns0:ref> and mammals <ns0:ref type='bibr' target='#b41'>(Nelson et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b9'>Delport et al., 2016)</ns0:ref>. The gut microbes have a mutually-beneficial relationship with their hosts. Numerous studies have confirmed that the gut microbes encode 10 to 100-fold more distinct genes than their host genome <ns0:ref type='bibr' target='#b63'>(Turnbaugh et al., 2006;</ns0:ref><ns0:ref type='bibr' target='#b47'>Qin et al., 2010)</ns0:ref>, and that they are involved in a large number of host biological processes related to nutrient absorption <ns0:ref type='bibr' target='#b24'>(Kartzinel et al., 2019)</ns0:ref>, gut homeostasis maintenance <ns0:ref type='bibr' target='#b4'>(Buchon, Broderick &amp; Lemaitre, 2013)</ns0:ref>, growth <ns0:ref type='bibr' target='#b66'>(Videvall et al., 2019)</ns0:ref> and even behavioral expression <ns0:ref type='bibr' target='#b72'>(Ye et al., 2014)</ns0:ref>. Therefore, it is of great significance to study the coevolutionary relationship between the gut microbes and their hosts.</ns0:p><ns0:p>The community structure and relative abundance of gut microbes vary among hosts. In aquatic animals, for example, the dominant families are Proteobacteria, Bacteroidetes, Tenericutes and Firmicutes in crabs <ns0:ref type='bibr' target='#b22'>(Hong et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b70'>Wei et al., 2019</ns0:ref><ns0:ref type='bibr' target='#b69'>Wei et al., , 2020))</ns0:ref>, Bacteroidetes, Firmicutes and Proteobacteria in shrimps <ns0:ref type='bibr' target='#b53'>(Rungrassamee et al., 2014)</ns0:ref>, fish <ns0:ref type='bibr' target='#b14'>(Egerton et al., 2018)</ns0:ref>, sea turtles <ns0:ref type='bibr' target='#b6'>(Campos et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b35'>McDermid et al., 2020)</ns0:ref> and sea lions <ns0:ref type='bibr' target='#b9'>(Delport et al., 2016)</ns0:ref>, and Proteobacteria and Firmicutes in sharks <ns0:ref type='bibr' target='#b20'>(Givens et al., 2015)</ns0:ref>. Each gut microbial phylum may have unique functional roles. For example, PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed members of the phylum Proteobacteria contribute to the breakdown and ferment of the complex sugars and are related to the biosynthesis of vitamins for their hosts <ns0:ref type='bibr' target='#b8'>(Colston &amp; Jackson, 2016)</ns0:ref>, microbes of the phylum Bacteroidetes improve the digestive efficiency in both herbivorous and carnivorous species by degrading the complex macromolecular matter <ns0:ref type='bibr' target='#b8'>(Colston &amp; Jackson, 2016)</ns0:ref>, members of the phylum Firmicutes contribute to the production of enzymes involved in fermenting vegetative material and have the potential to fabricate vitamin B <ns0:ref type='bibr' target='#b51'>(Rowland et al., 2018)</ns0:ref>, and microbes of the phylum Tenericutes are involved in the nutrient processing of their hosts <ns0:ref type='bibr' target='#b8'>(Colston &amp; Jackson, 2016)</ns0:ref>. Taken together, gut microbes play a vital role in maintaining the normal life of the host.</ns0:p><ns0:p>Gut microbes are affected by many factors, including the host's genetic background, food habit <ns0:ref type='bibr' target='#b26'>(Kohl et al., 2017)</ns0:ref>, ontogenetic stage <ns0:ref type='bibr' target='#b66'>(Videvall et al., 2019)</ns0:ref>, gender <ns0:ref type='bibr' target='#b40'>(Mueller et al., 2006)</ns0:ref> and health status <ns0:ref type='bibr' target='#b33'>(Lin et al., 2019)</ns0:ref>, and vary seasonally <ns0:ref type='bibr' target='#b26'>(Kohl et al. 2017;</ns0:ref><ns0:ref type='bibr' target='#b24'>Kartzinel et al., 2019)</ns0:ref>. The phylogenetic dependence of the gut microbial communities has been documented in fish <ns0:ref type='bibr' target='#b20'>(Givens et al., 2015)</ns0:ref>, reptiles <ns0:ref type='bibr' target='#b21'>(Hong et al., 2011)</ns0:ref>, birds <ns0:ref type='bibr' target='#b7'>(Capunitan et al., 2020)</ns0:ref> and mammals <ns0:ref type='bibr' target='#b24'>(Kartzinel et al., 2019)</ns0:ref>. In mammals, for example, the gut microbial diversity is higher in herbivorous species than in carnivorous species <ns0:ref type='bibr' target='#b24'>(Kartzinel et al., 2019)</ns0:ref>. In humans, microbes of the phylum Firmicutes are positively correlated with latitude and obesity, whereas members of the phylum Bacteroidetes show opposite correlations <ns0:ref type='bibr' target='#b30'>(Ley et al., 2005;</ns0:ref><ns0:ref type='bibr' target='#b61'>Suzuki &amp; Worobey, 2014)</ns0:ref>. Moreover, the gut microbial profiles at the different life stages are complicated by the natural dynamics and complex interactions between intrinsic and extrinsic factors. For example, early growth, household location, and antibiotic experiences during pregnancy are correlated with the early gut microbial composition in humans <ns0:ref type='bibr' target='#b65'>(Vatanen et al., 2019)</ns0:ref>.</ns0:p><ns0:p>Seasonal variation in diets may lead to changes in the gut microbiota <ns0:ref type='bibr' target='#b24'>(Kartzinel et al., 2019)</ns0:ref>, and exposure of host animals to artificial environments (e.g., animals in captivity) may lead to an increase in the abundance of human disease-related functional genes in the gut microbes <ns0:ref type='bibr' target='#b62'>(Tang et al., 2020;</ns0:ref><ns0:ref type='bibr' target='#b78'>Zhou et al., 2020)</ns0:ref>. Taken together, the gut microbial community is affected by the host's genetic background, diets and individual status and, in turn, affects the physiological, behavioral and even evolutionary processes of the host.</ns0:p><ns0:p>In the present study, we compared gut microbes between the native Chinese threekeeled pond turtle (Chinemys reevesii) and the invasive red-eared slider turtle (Trachemys scripta elegans) using bacterial 16S rRNA sequencing on the Roach/454 platform. Both are well studied species and among common turtle species farm-raised in China as food, pets and traditional medicine, with T. s. elegans well known as a very successful invasive species in many places around the world <ns0:ref type='bibr' target='#b5'>(Cadi et al., 2004)</ns0:ref>. The red-eared slider turtle is believed to be introduced to mainland China through Hong Kong as a pet and source of food in the 1980s and has become established in many parts of China <ns0:ref type='bibr' target='#b34'>(Ma &amp; Shi, 2017)</ns0:ref>. The turtle is generally considered to be more successful than native freshwater turtles such as the Chinese three-keeled pond turtle and has be listed by the PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed World Environmental Protection Organization as one of the 100 most harmful invasive species <ns0:ref type='bibr' target='#b34'>(Ma &amp; Shi, 2017)</ns0:ref>. However, supporting evidence from the gut microbiota has yet to be collected.</ns0:p></ns0:div> <ns0:div><ns0:head>MATERIALS AND METHODS</ns0:head></ns0:div> <ns0:div><ns0:head>Sample collection</ns0:head><ns0:p>This study was performed in accordance with the current laws on animal welfare and research in China, and was approved by the Animal Research Ethics Committee of Nanjing Normal University (IACUC-200422).</ns0:p><ns0:p>We obtained three juvenile C. reevesii and three juvenile T. s. elegans in March 2013 from a turtle farm in Hangzhou, Zhejiang, East China, and brought them to our laboratory in Nanjing, where they were and individually housed in 340 &#61620; 230 &#61620; 200 mm (length &#61620; width &#61620; height) aquariums placed in a room for six months. Water temperatures varied from 26&#61485;30 &#61616;C (with a mean of 28 &#61616;C), and photoperiod inside the room was on a cycle of 12 h light and 12 h dark. Turtles were fed with commercially sold food (10% water, 60% proteins, 5% lipids, 5% carbohydrates and 20% minerals; <ns0:ref type='bibr' target='#b32'>Li et al., 2013)</ns0:ref> at an average ration of 1.5% body mass daily. At the end of the experiment, body masses varied from 56&#61485;70 g (with a mean of 64 g) in C. reevesii, and from 118&#61485;136 g (with a mean of 125 g) in T. s. elegans. We collected fecal samples from each turtle on 25 th September 2013 and stored them at &#61485;80 &#61616;C until later DNA extraction.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Sample sequencing</ns0:head><ns0:p>Genomic DNA was extracted using the Qiagen TM QIAamp DNA Stool Mini Kit (Hilden, Germany) following the manufacturer's instructions. The V1&#61485;V3 region of the 16S rRNA gene was chosen for the amplification and subsequent pyrosequencing of the PCR products. The following 16S rRNA primers were used for the PCR reaction: 8F (5'-AGAGTTTGATCCTGGCTCAG -3') and 533R (5'-TTACCGCGGCTGCTGGCAC-3') for the V1&#727;V3 regions. Each primer included 'barcode' sequences to facilitate the sequencing of products in the Roche/454 GS FLX+ system (454 Life Sciences, USA). The fusion primer sequences were 5'-454adapter-mid-CCTACGGGAGGCAGCAG-3' (forward) and 5'-454adapter-mid-CCGTCAATTCMTTTRAGT-3' (reverse). DNA (20 ng) from each sample was used for amplification in 25 &#956;l reactions that contained 2.5 &#956;l 10fold reaction buffer, 40 ng of fecal DNA, 10 &#956;M each primer, 0.625 U Pyrobest polymerase (Takara), and 5000 &#956;M concentration of each of four deoxynucleoside triphosphates. PCR reactions were started by an initial denaturation at 94 &#176;C for 5 min followed by 27 amplification cycles (94 &#176;C for 30 s, 45 s at annealing temperature, 72 &#176;C for 1 min) and a final extension step for 7 min at 72 &#176;C. Subsequently, PCR products were examined for size and yield using agarose gel in TAE buffer (20 mM Tris-HCl, 10 mM sodium acetate, 0.5 mM Na 2 EDTA, pH 8.0). Quantification of the PCR products was performed by using the PicoGreen dsDNA BR assay kit as recommended by the manufacturer. Then, the V1&#61485;V3 region of 16S rRNA was sequenced on a Roche GS-FLX PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed 454 platform (Roche, Shanghai, China) according to 454 protocols.</ns0:p></ns0:div> <ns0:div><ns0:head>Quality control and data standardization</ns0:head><ns0:p>The pyrosequencing data were optimized by control standards according to the following criteria: (1) the raw reads must perfectly match the primers we used; (2) the barcode sequences with quality average were at least 25%; (3) the range of read length was between 320 to 800 bp nucleotides except for barcodes and primers; (5) consecutively identical bases did not exceed six and excluding undetermined bases. A total of 52,469 high-quality reads with an average length of 480 bp nucleotides were obtained. These sequences were then submitted to the National Center for Biotechnology Information (NCBI) Bioproject database (SRA accession number PRJNA645767).</ns0:p><ns0:p>We used Usearch 7.0 to conduct analysis of the operational taxonomic units (OTUs) <ns0:ref type='bibr' target='#b13'>(Edgar, 2010)</ns0:ref>. We first extracted nonrepeative sequences from high-quality data to reduce redundant calculations in the analysis and removed the singletons. Then, these available sequences were clustered into OTUs according to the similarity criteria of 97%, and chimeras were removed in the clustering process to obtain the representative sequences of OTUs. Finally, map all available sequences for each sample to representative sequences of OTUs to obtain OTU tables for further analysis. Moreover, RDP Classifier 2.2 <ns0:ref type='bibr' target='#b48'>(Quast et al., 2012)</ns0:ref> <ns0:ref type='table'>2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:ref> Manuscript to be reviewed threshold of 70% to obtain the taxonomic information corresponding to each OTU. To avoid large partial sample deviations, we retained OTUs with the number of OTU greater than 5 in at least 2 samples for further analysis</ns0:p><ns0:p>The alpha diversity index under different random sampling was calculated by using mothur 1.30.2 <ns0:ref type='bibr' target='#b55'>(Schloss et al., 2009)</ns0:ref> and visualized using the R 4.0.1 (R Development Core Team, 2020) to assess the adequacy of sequencing data. We standardize the OTUs abundance information according to the sample with the least sequence number for further analysis.</ns0:p></ns0:div> <ns0:div><ns0:head>Alpha and beta diversity estimation</ns0:head><ns0:p>The alpha-diversity indexes including the community richness (ACE index), diversity (Shannon diversity), evenness (Shannoneven index), and coverage (the Good's coverage index) were calculated using mothur software for each sample. These estimators were presented visually in the form of pictures using the R software platform. Bartlett test was used to test whether the data is of equal variance and the equal-variance t-test or the heteroscedasticity t-test was conducted to compare between species according to the Bartlett test results.</ns0:p><ns0:p>The principal component analysis (PCoA) and non-metric multidimensional scaling (NMDS) were conducted to test the differences in the relative abundance of OTUs of gut microbiome between the two species. The analysis of similarity test between the two species was conducted using ANOSIM based on the bray_curtis PeerJ reviewing <ns0:ref type='table'>PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:ref> Manuscript to be reviewed distance with 999 permutations. The PCoA and NMDS analyses were performed using the package vegan in R <ns0:ref type='bibr' target='#b43'>(Oksanen et al., 2013)</ns0:ref>. Moreover, the linear discriminant analysis effect size (LEfSe) <ns0:ref type='bibr' target='#b58'>(Segata et al., 2011)</ns0:ref> was conducted to test the differences in the bacterial abundances from phylum to family between the two species. Also, the linear discriminatory analysis (LDA) was conducted to estimate the effect size for each selected classification. In this study, only the bacterial taxa with a log LDA score &gt; 4 (over 4 orders of magnitude) were used. LEfSe and LDA analyses were performed using the Galaxy online tools <ns0:ref type='bibr' target='#b0'>(Afgan et al., 2018)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Gene function prediction</ns0:head><ns0:p>We used PICRUSt to search the GreenGene ID of the corresponding OTU based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database <ns0:ref type='bibr' target='#b23'>(Kanehisa, 2019)</ns0:ref> and to predict gene functions. Further, these function genes were classified and assigned to the relevant KEGG pathways <ns0:ref type='bibr'>(Langille et al., 2013)</ns0:ref>. We calculated the numbers of functional genes in each pathway to compare the functional enrichment in gut microbiota between the two species. The Circos diagram was plotted to show the relative abundance and distribution status of KOs genes between the two species. We performed the LEfSe to compare the abundances of function genes from KOs gene-level 1 to level 3 between the two species, thereby determining their differences in gene functions. Moreover, LDA analysis was used to assess the effect size for each three KO gene levels. In this study, only gene functions with a log LDA score &gt; 2 were used.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed Student's t-test was used to compare the relative abundance of the KOs gene at different levels. All values were presented as mean &#61617; SE, and all statistical analyses were conducted at the significance level of &#945; = 0.05.</ns0:p></ns0:div> <ns0:div><ns0:head>RESULTS</ns0:head></ns0:div> <ns0:div><ns0:head>Gut microbial profile</ns0:head><ns0:p>We obtained 31,402 raw reads from C. reevesii and 31,193 raw reads from T. s. elegans.</ns0:p><ns0:p>After quality control and filtration, we harvested 27,945 and 24,519 high-quality sequences from C. reevesii and T. s. elegans, respectively. The average read was 8,745&#61617;399 (ranging from 7605-10751 reads per sample) with a sequence length of 480&#61617;4 bp (ranging from 326-635 bp) for each sample (Fig. <ns0:ref type='figure' target='#fig_2'>S1</ns0:ref>). Further, an average of 9,317&#61617;601 high-quality reads (ranging from 8,308-10,751 reads per sample) and 8,173&#61617;242 highquality reads (ranging from 7,605-8,603 reads per sample) were obtained from C. reevesii and T. s. elegans, respectively. The rarefaction curves based on the Shannon index for all samples showed that sufficient sequence numbers could be obtained for further analysis at the current sequencing depth (Fig. <ns0:ref type='figure' target='#fig_7'>S2</ns0:ref>). Furthermore, the minimum values of the Good's coverage were more than 99.8%, which meant that the vast majority of gut bacteria could be retrieved from these samples. deviation. Among them, the average OTUs were 29&#61617;1.7 (ranging from 25-32) and 33&#61617;2.9 (ranging from 29-40) per sample for C. reevesii and T. s. elegans, respectively (Table <ns0:ref type='table'>S1</ns0:ref>).</ns0:p><ns0:p>Fifty-four OTUs were shared by the two species, three were unique to T. s. elegans, and 23 were unique to C. reevesii. These OTUs were clustered into five phyla, seven classes, seven orders, 17 families and 28 genera based on phylogenetic classification for the six fecal samples (Table <ns0:ref type='table'>S1</ns0:ref>). More specifically, species in the gut microbiota belonged to four families, five classes, six orders, 10 families and 10 genera in C. reevesii, and to five phyla, seven classes, seven orders, 17 families and 28 genera in T. s. elegans (Table <ns0:ref type='table'>S1</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Interspecific differences in the gut microbiota</ns0:head><ns0:p>As the unidentified OTUs accounted for up to 15.1% at the family level and 41.6% at the genus, we analyzed the composition and relative abundance of gut bacterial community excluding data at the genus level. Figure <ns0:ref type='figure' target='#fig_2'>1</ns0:ref> shows the relative abundances of the gut microbiota across taxonomic levels from family to phylum. Considering all six samples as a whole, we found that the fecal microbiota was dominated by species of the phyla Bacteroidetes (78.02&#61617;8.00%), Firmicutes (20.21&#61617;7.94%), Proteobacteria (1.46&#61617;0.98%) and Fusobacteria (0.31&#61617;0.14%), the classes Bacteroidia (78.02&#61617;8.00%), Clostridia (19.73&#61617;7.85%), Gammaproteobacteria (1.46&#61617;0.98%), Erysipelotrichi (0.48&#61617;0.13%) and Fusobacteriia (0.31&#61617;0.14%), the orders Bacteroidales (78.02&#61617;8.00%), Clostridiales (19.73&#61617;7.85%), Erysipelotrichales (1.87&#61617;1.01%), Fusobacteriales (0.31&#61617;0.14%) and Aeromonadales (0.07&#61617;0.03%), and the families Porphyromonadaceae (43.88&#61617;8.83%), PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed Bacteroidaceae (20.01&#61617;4.85%), Lachnospiraceae (13.89&#61617;5.53%), Clostridiaceae (2.41&#61617;0.91%), S24-7 (1.77&#61617;1.15%), Enterobacteriaceae (1.39&#61617;0.99%), Ruminococcaceae (0.66&#61617;0.09%), Erysipelotrichaceae (0.46&#61617;0.13%), Fusobacteriaceae (0.31&#61617;0.14%) and Aeromonadaceae (0.07&#61617;0.03%).</ns0:p><ns0:p>The composition and relative abundance of the gut microbiota at different taxonomic levels showed differences between the two species. For the sake of convenience, the bacteria with a relative abundance &gt; 2% were defined as the dominant taxa. The dominant phyla were Bacteroidetes (63.45&#61617;10.38%), Firmicutes (34.12&#61617;10.75%) and Proteobacteria (2.40&#61617;1.80%) in C. reevesii, and Bacteroidetes (92.59&#61617;2.63%) and Firmicutes (6.30&#61617;2.77%) in T. s. elegans (Fig. <ns0:ref type='figure' target='#fig_2'>1A</ns0:ref>). The dominant classes were Bacteroidia (63.45&#61617;10.38%), Clostridia (33.60&#61617;10.55%) and Gammaproteobacteria (2.40&#61617;1.80%) in C. reevesii, and Bacteroidia (92.59&#61617;2.63%) and Clostridia (5.87&#61617;2.69%) in T. s. elegans (Fig. <ns0:ref type='figure' target='#fig_2'>1B</ns0:ref>). The dominant orders were Bacteroidales (63.45&#61617;10.38%), Clostridiales (33.60&#61617;10.55%) and Erysipelotrichales (2.82&#61617;1.84%) in C. reevesii, and Bacteroidales (92.59&#61617;2.63%) and Clostridiales (5.87&#61617;2.69%) in T. s. elegans (Fig. <ns0:ref type='figure' target='#fig_2'>1C</ns0:ref>). The dominant families were Bacteroidaceae (30.74&#61617;2.95%), Porphyromonadaceae (26.77&#61617;10.33%), Lachnospiraceae (3.81&#61617;1.92%), Clostridiaceae (3.87&#61617;1.27%), S24-7 (3.22&#61617;1.98%) and Enterobacteriaceae (2.29&#61617;1.84%) in C. reevesii, and Porphyromonadaceae (60.99&#61617;3.11%), Bacteroidaceae (9.28&#61617;2.97%) and Lachnospiraceae (3.81&#61617;1.92%) in T. s. elegans (Fig. <ns0:ref type='figure' target='#fig_2'>1D</ns0:ref>).</ns0:p><ns0:p>Microbes of the phylum Firmicutes, the class Clostridia, the order Clostridiales and PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed the families Bacteroidaceae, Clostridiaceae and Lachnospiraceae were more abundant in C. reevesii (Table <ns0:ref type='table'>S3</ns0:ref>; Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>). Microbes of the phyla Bacteroidetes and Fusobacteria, the classes Bacteroidia and Fusobacteriia, the orders Fusobacteriales and Bacteroidales and the families Porphyromonadaceae and Fusobacteriaceae were more abundant in T. s. elegans (Table <ns0:ref type='table'>S3</ns0:ref>; Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>).</ns0:p><ns0:p>Table <ns0:ref type='table'>S2</ns0:ref> shows the alpha-diversity indexes for each sample including the community richness (ACE index), diversity (Shannon diversity), evenness (Shannoneven index), and coverage (the Good's coverage index). Student's t test showed that none of these indexes differed between the two species (all P &gt; 0.09). PCoA and NMSD analyses showed no significant differences in bacterial relative abundance between the two species (Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>; anosim: R = 0.44, P = 0.10).</ns0:p></ns0:div> <ns0:div><ns0:head>The predicted metagenomes</ns0:head><ns0:p>PICRUSt analysis was performed to predict the gene functions in the two turtle species based on the 16S RNA of six fecal samples. These gene functions were predicted into three levels of KEGG functional categories. Among them, metabolism-related genes had an overwhelming proportional advantage, with a relative abundance of up to 45.34&#61617;1.38% at the first level (Fig. <ns0:ref type='figure' target='#fig_5'>4A</ns0:ref>). Furthermore, the gene functions at the first level also included environmental information processing (17.12&#61617;1.43%), genetic information processing (16.21&#61617;0.45%), human diseases (15.80&#61617;0.43%), cellular processes (4.03&#61617;0.33%), organismal systems (0.59&#61617;0.06%) and unclassified genes (15.80&#61617;0.43%) (Fig. <ns0:ref type='figure' target='#fig_5'>4A</ns0:ref>). There PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed were 18 major gene functions at the second level ( Fig. <ns0:ref type='figure' target='#fig_5'>4B</ns0:ref>), among which, the most abundant gene functions were composed of membrane transport (14.64&#61617;1.30%), carbohydrate metabolism (10.96&#61617;0.37%), amino acid metabolism (8.80&#61617;0.19%), replication and repair (6.94&#61617;0.23%), energy metabolism (5.00&#61617;0.20%), translation (4.02&#61617;0.18%), metabolism of cofactors and vitamins (3.79&#61617;0.05%), cell motility (3.37&#61617;0.42%), nucleotide metabolism (3.26&#61617;0.13%) and transcription (3.06&#61617;0.08%) (Fig. <ns0:ref type='figure' target='#fig_5'>4B</ns0:ref>). Also, at the third level, the gene functions with the highest relative abundance were transporters (7.18&#61617;0.56%), ABC transporters (3.77&#61617;0.40%), DNA repair and recombination proteins (2.25&#61617;0.05%), transcription factors (2.21&#61617;0.16%) and twocomponent system (2.19&#61617;0.19%) (Figs. <ns0:ref type='figure' target='#fig_5'>4C and S3</ns0:ref>).</ns0:p><ns0:p>As a whole, 240 known KOs and 27 unknown gene functions were identified from the six samples. The distribution of KOs in different species with their relative abundance of &gt; 1% was displayed on the Circos diagram (Fig. <ns0:ref type='figure' target='#fig_4'>S3</ns0:ref>). The gene functions at the first level that accounted for the highest abundance included metabolism (46.76&#61617;2.45%), genetic information processing (16.84&#61617;0.60%) and environmental information processing (15.48&#61617;2.51%) in C. reevesii, and metabolism (43.91&#61617;0.54%), environmental information processing (18.76&#61617;0.30%) and genetic information processing (15.59&#61617;0.44%) in T. s. elegans (Figs. <ns0:ref type='figure' target='#fig_5'>4A and S3</ns0:ref>). The relative abundance of gene functions at the second level accounted more than 5% were membrane transport (13.13&#61617;2.27%), replication and repair (7.32&#61617;0.29%), amino acid metabolism (8.93&#61617;0.31%), PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed carbohydrate metabolism (11.41&#61617;0.58%), and energy metabolism (5.26&#61617;0.33%) in C. reevesii, and those in T. s. elegans were membrane transport (16.15&#61617;0.16%), replication and repair (6.56&#61617;0.18%), amino acid metabolism (8.67&#61617;0.17%) and carbohydrate metabolism (10.51&#61617;0.27%) (Figs. <ns0:ref type='figure' target='#fig_5'>4B and S3</ns0:ref>). Furthermore, transporters (6.66&#61617;0.13% in C. reevesii, and 7.69&#61617;0.15% in T. s. elegans) and ABC transporters (3.28&#61617;0.68% in C. reevesii, and 4.27&#61617;0.15% in T. s. elegans) at the third level accounted more than 3% in both species (Figs. <ns0:ref type='figure' target='#fig_5'>4C and S3</ns0:ref>).</ns0:p><ns0:p>LEfSe analysis based on the KOs revealed obvious differences in gene functions between the two species. At the third level, LDA discriminant analysis showed that there was a greater proportion of human disease-related functions (e.g. valine, leucine, and isoleucine biosynthesis, and Influenza A, both P = 0.046) and metabolism-related functions (e.g. bisphenol degradation, linoleic acid metabolism, nitrogen metabolism and colorectal cancer, all P = 0.050) in C. reevesii, as well as tyrosine metabolism (LDA = 2.79562, P = 0.050) in T. s. elegans.</ns0:p></ns0:div> <ns0:div><ns0:head>DISCUSSION</ns0:head><ns0:p>From this study where the gut microbiota was compared between two species of turtles raised under the identical conditions for six months we knew the following. First, neither alpha diversity nor beta diversity differed significantly between the two species (Table <ns0:ref type='table'>S2</ns0:ref>; Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>). Second, the relative abundance of gut microbes differed significantly PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed between the two species across the taxonomic levels from family to phylum (Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>).</ns0:p><ns0:p>Third, the relative abundance of metabolism-related functional genes in the gut microbiota differed significantly between the two species, and so did the relative abundance of human disease-related functional genes (Fig. <ns0:ref type='figure' target='#fig_5'>4</ns0:ref>).</ns0:p><ns0:p>The influence of the host's genetic background on the gut microbiota has been detected in most vertebrates studied thus far, including fish, reptiles, birds and mammals. For instance, phylogenetic relationships shape the gut microbial profile in phylogenetically closely related mammals that are similar in body shape, craniofacial anatomy and the gut structure <ns0:ref type='bibr' target='#b31'>(Ley et al., 2008;</ns0:ref><ns0:ref type='bibr' target='#b24'>Kartzinel et al., 2019</ns0:ref>. The taxonomic or phylogenetic correlates of the gut microbiota has also been reported for birds in Equatorial Guinea <ns0:ref type='bibr' target='#b7'>(Capunitan et al., 2020)</ns0:ref>. In Gal&#225;pagos iguanas, differences in the fecal microbial communities are primarily related to the host species and ecotype, and subsequently to population origin <ns0:ref type='bibr' target='#b29'>(Lankau et al., 2012)</ns0:ref>. Significant differences in the gut microbiota also exist between the bony fish and sharks <ns0:ref type='bibr' target='#b20'>(Givens et al., 2015)</ns0:ref>. From these results we know that the influences of phylogeny on the gut microbiota are universal in vertebrates. This is probably the main reason for why we could still distinguish differences in the gut microbiota between two species of turtles even though they had been maintained under identical conditions for six months. the gopher tortoise Gopherus polyphemus <ns0:ref type='bibr' target='#b73'>(Yuan et al., 2015)</ns0:ref>, the green sea turtle Chelonia mydas <ns0:ref type='bibr' target='#b6'>(Campos et al., 2018;</ns0:ref><ns0:ref type='bibr' target='#b35'>McDermid et al., 2020)</ns0:ref>, and the loggerhead sea turtle Caretta caretta <ns0:ref type='bibr' target='#b3'>(Arizza et al., 2019)</ns0:ref>, and the painted turtle Chrysemys picta <ns0:ref type='bibr'>(Fugate et al., 2020)</ns0:ref>. Gut microbes of the families Bacteroidaceae, Clostridiaceae and Lachnospiraceae were comparatively more abundant in C. reevesii than in T. s. elegans (Fig. <ns0:ref type='figure' target='#fig_2'>1</ns0:ref>). Of these three families, Bacteroidaceae belongs to the phylum Bacteroidetes, and Clostridiaceae and Lachnospiraceae both belong to the order Clostridiales, the class Clostridia and the phylum Firmicutes. Furthermore, gut microbes of the families Porphyromonadaceae and Fusobacteriaceae were more abundant in T. s. elegans than in C. reevesii (Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>). Porphyromonadaceae belongs to the order Bacteroidales, the class Bacteroidia and the phylum Bacteroidetes, and Fusobacteriaceae belongs to the order Fusobacteriales, the class Fusobacteriia and the phylum Fusobacteria (Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>). Microbes of the families Bacteroidaceae and Porphyromonadaceae were the main components of the phylum Bacteroidetes (Fig. <ns0:ref type='figure' target='#fig_3'>2</ns0:ref>). Bacteroidetes species in the gut play an important role in degrading carbohydrates and proteins, thus being essential for their hosts in the absorption and utilization of nutrients <ns0:ref type='bibr' target='#b15'>(Fernando et al., 2010;</ns0:ref><ns0:ref type='bibr' target='#b42'>Nuriel-Ohayon, Neuman &amp; Koren, 2016)</ns0:ref>. Firmicutes species are universal representatives in mammalian gut microbiota and play important functional roles in digestion and host metabolism <ns0:ref type='bibr' target='#b31'>(Ley et al., 2008)</ns0:ref>. Fusobacteria is usually rare in the gut microbiota of reptiles, but can be obtained from the infected animals and are the dominant phylum in the gut microbiota PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed in scavengers like the American alligator Alligator mississippiensis <ns0:ref type='bibr' target='#b25'>(Keenan, Engel &amp; Elsey, 2013)</ns0:ref>, the black vulture Coragyps atratus and the turkey vulture Cathartes aura <ns0:ref type='bibr' target='#b38'>(Mendoza et al., 2018)</ns0:ref>. The Firmicutes/Bacteroidetes ratio was 0.54 in C. reevesii and 0.07 in T. s. elegans. It is worth noting that the Firmicutes/Bacteroidetes ratio is negatively correlated with mass gain <ns0:ref type='bibr' target='#b15'>(Fernando et al., 2010)</ns0:ref>. Thus, a lower Firmicutes/Bacteroidetes ratio in T. s. elegans suggests a greater potential to gain mass in the species.</ns0:p><ns0:p>Numerous studies on aquatic animals have shown that the gut microbiota is influenced by food ingested, environment, and their age, gender and health status. For example, colony location and captivity influence the gut microbial community composition of the Australian sea lion Neophoca cinerea <ns0:ref type='bibr' target='#b9'>(Delport et al., 2016)</ns0:ref>. The gut microbial diversity in green turtles are influenced by their age and population origin <ns0:ref type='bibr' target='#b6'>(Campos et al., 2018)</ns0:ref>. Likewise, the gut microbiota of fish is affected by life stage, tropic level, diet, season, habitat, sex, captivity and phylogeny <ns0:ref type='bibr' target='#b14'>(Egerton et al., 2018)</ns0:ref>. Our experiment design allowed us to exclude the effects of external factors on the gut microbiota because turtles we used were raised under the same conditions for a half year.</ns0:p><ns0:p>Neither alpha diversity nor beta diversity differed between the two species (Table <ns0:ref type='table'>S2</ns0:ref>, Fig. <ns0:ref type='figure' target='#fig_4'>3</ns0:ref>). This might be related to small sample sizes in both species. Data from one C. reevesii sample deviated from those from other samples, suggesting that future work Manuscript to be reviewed could usefully examine the impact of long-term homogeneous culture conditions on the gut microbes in animals. The composition of gut microbes in the two species was relatively simple, presumably because turtles were raised under identical conditions for a long time period (six months). Similar results have been reported in an earlier study of T. s. elegans where gut microbes in fecal samples from three adult turtles are mainly composed of Firmicutes and Bacteroidetes <ns0:ref type='bibr' target='#b12'>(Du, Zhang &amp; Shi, 2013)</ns0:ref>. In that study, Bacteroides account for 98.82% of the Bacteroidetes, and Clostridium accounts for 95.81% of the Firmicutes <ns0:ref type='bibr' target='#b12'>(Du, Zhang &amp; Shi, 2013)</ns0:ref>. In another study of T. s. elegans the gut microbiota in young turtles is mainly composed of Firmicutes, Bacteroidetes and Proteobacteria <ns0:ref type='bibr' target='#b45'>(Peng et al., 2020)</ns0:ref>.</ns0:p><ns0:p>Our data showed that in both species the most functionally distinct categories were focused on metabolism, genetic information processing and environmental information processing at the first function level, followed by gene functions associated with membrane transport, replication and repair, amino acid metabolism and carbohydrate metabolism at the second level, and transporters and ABC transporters at the third level.</ns0:p><ns0:p>In reptiles, that the gene functions of the gut microbes are associated with metabolism has been reported for the timber rattlesnake Crotalus horridus <ns0:ref type='bibr' target='#b36'>(McLaughlin et al., 2015)</ns0:ref>, the crocodile lizard Shinisaurus crocodilurus <ns0:ref type='bibr' target='#b62'>(Tang et al., 2020)</ns0:ref>, and the northern grass lizard Takydromus septentrionalis <ns0:ref type='bibr' target='#b78'>(Zhou et al., 2020)</ns0:ref>. Similar results have also been reported for birds <ns0:ref type='bibr' target='#b68'>(Wang et al., 2018)</ns0:ref> and mammals <ns0:ref type='bibr' target='#b77'>(Zhao et al., 2018)</ns0:ref>. Previous studies PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed generally support the idea that the most functionally distinct categories of gut microbes play an important role in host energy metabolism.</ns0:p><ns0:p>Comparing gene functions between C. reevesii and T. s. elegans, we found that they differed in human diseases and metabolic-related functions. Captive animals had an ample opportunity to come into contact with human keepers for transmission of microbiota from host-associated sources, which could colonize the animals. In this study, we found that gut microbes of the families Bacteroidaceae, Clostridiaceae, and Lachnospiraceae were more abundant in C. reevesii. Clostridiaceae and Lachnospiraceae (Firmicutes; Clostridia; Clostridiales) are more abundant in the gut microbiota for the time periods of disease progression <ns0:ref type='bibr' target='#b75'>(Zhang et al., 2014)</ns0:ref>. The relative abundance of Bacteroidaceae (Bacteroidetes; Bacteroidia; Bacteroidales) increases at one or two months old in humans and is negatively correlated with depression <ns0:ref type='bibr' target='#b59'>(Songjinda et al., 2007;</ns0:ref><ns0:ref type='bibr' target='#b60'>Strandwitz et al., 2019)</ns0:ref>. Gut microbes of the families Porphyromonadaceae and Fusobacteriaceae were comparatively more abundant in T. s. elegans.</ns0:p><ns0:p>Porphyromonadaceae (Bacteroidetes; Bacteroidia; Bacteroidales) is negatively associated with cognitive decline, affective disorders and anxiety-like behavior in aged mice <ns0:ref type='bibr' target='#b56'>(Scott et al. 2017</ns0:ref>). Fusobacteriaceae (Fusobacteria; Fusobacteriia; Fusobacteriales) is involved in the fermentative progress of a variety of carbohydrates, amino acids and peptides <ns0:ref type='bibr' target='#b37'>(Zoqratt et al., 2018)</ns0:ref>. Therefore, we hypothesized that the difference in gene function between C. reevesii and T. scripta elegans may be related to their absorption and PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:p><ns0:p>Manuscript to be reviewed utilization of food resources. Comparative studies have found that C. reevesii is at greater risk of colonizing human gut microbes than T. s. elegans, so it is recommended that actions be taken to minimize direct contact between human managers and native turtles.</ns0:p></ns0:div> <ns0:div><ns0:head>CONCLUSION</ns0:head><ns0:p>Our data showed that red-eared slider turtles and Chinese three-keeled pond turtles raised under identical conditions for a long time period (six months) differed in the relative abundance of the microbes and gene functions in the gut microbiota, thus adding evidence for the phylogenetic (genetic) dependence of the gut microbial communities in reptiles. The potential to gain mass was greater in T. s. elegans than in C. reevesii, as revealed by the fact that the Firmicutes/Bacteroidetes ratio was lower in the former species. The percentage of human disease-related functional genes was lower in T. s. elegans than in C. reevesii, presumably suggesting an enhanced potential to colonize new habitats in the former species. Taken together, our data allow the conclusion that the invasive red-eared slider turtle is more successful than the native Chinese threekeeled pond turtle. Manuscript to be reviewed Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head>Figure legends</ns0:head><ns0:note type='other'>Figure 2</ns0:note></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>performed a taxonomic analysis of the OTU representative sequences against the Greengenes 135/16S Database at the confidence PeerJ reviewing PDF | (</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51573:1:1:NEW 2 Oct 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1 Relative abundances of the gut microbiota at the phylum (A), class (B), order</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 The differences in relative abundance of gut microbiota between Chinemys</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3 Fecal microbial diversity in the two turtle species. Results of principal</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 4</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4 Gene functional categories based on 16S RNA in the gut microbiota at top</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 1 Figure 1</ns0:head><ns0:label>11</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 The differences in relative abundance of gut microbiota between Chinemys reevesii and Trachemys scripta as shown by linear discriminatory analysis (LDA) scores.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 3 Figure 3</ns0:head><ns0:label>33</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 4 Figure 4</ns0:head><ns0:label>44</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> </ns0:body> "

" Nanjing Normal University College of Life Sciences 1 Wenyuan Road, Nanjing 210023, China Dr and Professor Xiang Ji Email: [email protected] Telephone: +86 25 85891597 Fax: +86 25 85891526 Dr. Jianjun Wang Academic Editor, PeerJ Nanjing, September 23, 2020 The invasive red-eared slider turtle is more successful than the native Chinese three-keeled pond turtle: evidence from the gut microbiota (#2020:07:51573:0:1:REVIEW) Dear Dr. Wang, Thank you very much for your decision letter on September 2, 2020, which allows us to submit a substantially revised manuscript to PeerJ. We found the editor and reviewer comments constructive in preparing a revised manuscript that we think is now much improved. We have considered all of the comments carefully, and responded by making substantive revisions/additions in the manuscript that we believe address the comments thoroughly. We answered the questions using a blue colour in the comments. Hope the revised manuscript is more readable and easier to follow. Below you will find the original decision letter including all editor and reviewer comments. We have indicated our responses and changes in a blue colour following each comment. Please find attached a Word document of the revised manuscript and all supplemental files. We are waiting for further comments from you, and would greatly appreciate it if the manuscript can be improved at the editorial stage. Thank you once again for considering our manuscript. Sincerely yours, Xiang Ji Professor in Ecology & Zoology Dear Dr. Ji, Thank you for your submission to PeerJ. It is my opinion as the Academic Editor for your article - The invasive red-eared slider turtle is more successful than the native Chinese three-keeled pond turtle: evidence from the gut microbiota - that it requires a number of Major Revisions. My suggested changes and reviewer comments are shown below and on your article ‘Overview’ screen. Please address these changes and resubmit. Although not a hard deadline please try to submit your revision within the next 55 days. With kind regards, Jianjun Wang Academic Editor, PeerJ Editor comments (Jianjun Wang) Major Revisions I obtained comments from three experts in this field and they all found merit in this study. However, they also raised critical comments to improve the quality and clarity. I will be happy to consider a revised manuscript upon these comments being carefully considered. >> Thank you for your considering our manuscript further once the concerns of reviewers are well addressed [# PeerJ Staff Note: It is PeerJ policy that additional references suggested during the peer-review process should only be included if the authors are in agreement that they are relevant and useful #] >> Informed. Thanks [# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. t is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #] >> Informed. Thanks Reviewer 1 (Anonymous) Basic reporting This is a very interesting study which I feel should be published. There are very few studies which examine the microbiota of reptiles, such as turtles. However, I do have some questions about your Experimental Design and Validity of Findings. >> Thanks for your positive comments. We have considered all of your comments carefully, particularly those on the experimental design and validity of findings. We have responded by making substantive revisions/additions in the manuscript that we believe address the comments thoroughly Experimental design According to the Materials and Methods one fecal sample/turtle was collected after 6 months in your laboratory. Why collect only one sample/turtle at the 6 months’ period of time? Fecal samples could have been collected starting at time =0, 1 month, 2 months, 3 months, 4 months, 5 months and 6 months. You could have determined how the bacterial diversity changed over time and if the gut microbiota determined in Figure 1 is stable. >> We did not use a repeated measures experimental design to determine temporal variation in the gut microbiota (e.g., changes in the gut microbiota over six months by sampling every month), but instead compared the gut microbiota between two turtle species using juvenile individuals acclimated under the identical conditions for six months, thereby highlighting the genetically determined inter-specific differences Validity of the findings Unfortunately, I do not think it is valid of say (Line 48 and 49) “The invasive species is more successful than the native species, as revealed by two lines of evidence.” In your study you only have 3 samples/ turtle species and one time point (6 months). I think you need to say “The invasive species could be more successful than the native species as documented in this preliminary study.” Parts of your manuscript, beginning with the title of the manuscript, should be rewritten to reflect this change. Follow up studies are going to be needed, including fecal samples from both turtle species living in the wild, to make a more definitive conclusion. I see this current study as a first step. >> We do not agree with you on that our claim ‘the invasive species is more successful than the native species because of two lines of evidence’ is invalid. We did not focus on temporal variation but on inter-specific differences in the gut microbiota. To highlight the genetically determined inter-specific differences in the gut microbiota, we acclimated juveniles of the two species under the identical conditions for six months, thereby minimizing the confounding effect resulting from proximate factors Comments for the Author 1. Under Keywords add “turtle” since this is a study about turtles. >> Done. Thanks 2. In the Introduction there is nothing mentioned about turtles. I would begin by describing the Chinese three-keeled pond turtle and the red-eared slider turtle. You state the red-eared slider turtle is invasive. Where did the turtle originally come from? Is it causing harm? >> Done. The sentences have been changed to ‘The red-eared slider turtle is believed to be introduced to mainland China through Hong Kong as a pet and food in the 1980s and has become established in many parts of China (Ma & Shi, 2017). The turtle is generally considered to be more successful than native turtles including the Chinese three-keeled pond turtle and has be listed by the World Environmental Protection Organization as one of the 100 most harmful invasive species 3. Line 110 “Roach 454 platform” should be changed to “roche 454 platform” >> Thanks but, perhaps, ‘Roach/454 platform’ is better 4. Line 131 Sample Sequencing. Was there any library preparation/adapters used? This needs to be mentioned. >> We have provided the missing information in the manuscript. Thanks 5. Lines 238 and 239 The authors write “On the whole, the fecal microbiota was dominated by species of the phyla Bacteroidetes (78.02±8.00%)…” Are you averaging the abundance of Bacteroidetes from all six samples to get 78.02%? >> We calculated descriptive statistics for Bacteroidetes and others using data from all six samples. We changed the sentence into ‘Considering all six samples as a whole, we found that the fecal microbiota was dominated by species of the phyla Bacteroidetes …’ 6. Line 294 The authors wrote “In the whole” This should be changed to “As a whole” >> Corrected. Thanks 7. Lines 341 Since there are relatively few turtle species which have been studied you should discuss the results of the study by Fugate et al. Curr Microbiol 2020 on the painted turtle. >> The study by Fugate et al. (2020) has been cited in the revised manuscript. Thanks 8. Line 367 The study by McLaughlin et al. Mol Biol Rep (2015) examined the gut microbiota of a Timber rattlesnake using a metagenomics approach. Functional categories are discussed in their paper. >> The study by McLaughlin et al. (2015) has been cited in the revised manuscript. Thanks 9. Line 711 The correct citation is Md Zoqratt MZH, Eng WWH, Thai BT, Austin CM, Gan HM. Microbiome analysis of Pacific white shrimp gut and rearing water from Malaysia and Vietnam: implications for aquaculture research and management. >> Corrected. Thanks Reviewer 2 (Anonymous) Basic reporting The authors assessed the gut microbiome of native Chinese three-keeled pond turtle and the invasive red-eared slider turtle by 16S rRNA sequencing approach, and discovered that the gut microbial diversity and richness of the gut microbiomes were different in two species. >> More importantly, the observed inter-specific differences in the gut microbiota allow the conclusion that the invasive species is more successful than the native species because of its enhanced potentials to gain mass and to colonize new habitats Experimental design The most important for this work is that the sample size is too small >> Yes, future work could usefully use more individuals to increase the powerfulness of statistical analyses Validity of the findings No comments Comments for the Author The authors assessed the gut microbiome of native Chinese three-keeled pond turtle and the invasive red-eared slider turtle by 16S rRNA sequencing approach, and discovered that the gut microbial diversity and richness of the gut microbiomes were different in two species. I have some concerns as listed below. I suggest the authors to carefully revise their manuscript before further process. >> We found your comments constructive in preparing a revised manuscript. Thanks. We have considered all of your comments carefully, and responded by making substantive revisions/additions in the manuscript Major concerns: 1. The most important for this work is that the sample size is too small, and Especially, In figure 3, there is individual in CR is different with the other two in the same group, which can affect the results. >> Yes, future work could usefully use more individuals to increase the powerfulness of statistical analyses 2. In the abstract, the authors said that the percentage of human disease-related functional genes was lower in T. s. elegans than in C. reevesii, suggesting a greater potential to colonize new habitats in the former species. Are you sure you can get this conclusion? as we know, turtles have lower defence mechanisms to protect them from disease compared with Human, and why compared with human? >> We toned down the conclusion by changing the sentence to ‘The percentage of human disease-related functional genes was lower in T. s. elegans than in C. reevesii, presumably suggesting an enhanced potential to colonize new habitats in the former species’ 3. Gut microbiology may indicate species differences in diet, physiology, and other internal and external factors, and significantly more variation in faecal microbiome composition may enable them to adapt quicker to new environments, so I suggest that the authors compare and find the main OTU or bacteria species in turtles, which is helpful for turtles conservation and farm. >> Gut bacterial composition and abundance have been studied only in the green turtle (Chelonia mydas; Price et al., 2017, Campos et al., 2018) and the painted turtle (Chrysemys picta; Fugate et al., 2020). We have cited studies on these two species in the revised manuscript. However, available data are not enough to allow for in-depth discussion Reference: Shanmuganandam S, Hu Y, Strive T, Schwessinger B, Hall RN. 2020. Uncovering the microbiome of invasive sympatric European brown hares and European rabbits in Australia. PeerJ 8:e9564 https://doi.org/10.7717/peerj.9564 Reviewer 3 (Anonymous) Basic reporting This manuscript studied the invasive red-eared slider turtle is more successful than the native Chinese three-keeled pond turtle from the gut microbiota angle. It is clear and interesting. >> Thanks for your positive comments Experimental design The experimental design is appropriate. The data supports their conclusions. >> Thanks for your positive comments Validity of the findings The findings is effective. The invasive species harbors more microbes associated with gain mass. In addition, the percentage of human disease-related functional genes was less in the invasive species. >> The aforementioned findings are of great interest because they provide an inference that the invasive turtle is more successful than the native turtle Comments for the Author This study mainly compared the microbes and gene functions in the invasive and native turtle. They found that the invasive animal harbors more microbes associated with gain mass. In addition, the percentage of human disease-related functional genes was less in the invasive species. The experimental procedures are very detailed. And the experimental design is reasonable. In addition, the subjects of research are novel. However, there are still some problems in this paper. >> Thanks for your positive comments 1. The distance of one letter in front of each paragraph rather than two Chinese characters >> Corrected. Thanks 2. Whether to record the altitude, longitude and latitude of the sampling site and the temperature at the time of sampling >> Population origin and thus information on the altitude, longitude and latitude of turtles used in this study were unfortunately unknown because they were obtained from a turtle farm in Hangzhou. The current situation of turtles such as Chinemys reevesii in China is that they are farmed but endangered: rarely can we find a turtle in the field ever since wild stocks of nearly all species of freshwater turtles in China became depleted in 1970’s 3. Why are the LDA scores distinct in difference of gene function and difference of bacterial abundances >> LDA can represent the axes that maximize the separation between multiple classes. In this study, both gene function and bacterial taxon have a multi-class classification and, as such, we used the LDA scores to analyse the differences in gene function and bacterial abundance 4. Please give a clear definition of the ‘dominant microbes’ in this study. >> In the present study, we arbitrarily defined a taxon to be dominant if it had a relative abundance > 2%. This definition has been added in the revised manuscript 5. It is suggested to supplement the composition of gut microbiota at genus level. >> Thanks for your suggestion. But we tried to annotate OTUs with different databases. Greengene is believed to be the best database. However, as the annotation rate of genera was very low (~41.6%), we did not discuss the classification of genera 6. How to define ‘more successful’ in this study. >> More successful species grow (gain mass) more rapidly and survive better in the field. We believe that the invasive turtle (T. s. elegans) is more successful than the native turtle (C. reevesii) because the former species harbors gut microbes that allow it to grow (gains mass) more rapidly and colonize new habitats more easily than the native species 7. What statistical software and drawing software were used in this study？ >> We used R to analyse data and make graphs. We added software information on pcoa, NMDS and LEfSe analyses in the revised manuscript 8. The abbreviation, such as T. s. elegans, should be stated in the previous article firstly, and can‘t be directly exported. >> Corrected. Thanks 9. Latin names should be marked When a noun appears firstly. >> Done. Thanks 10. From Line 294 to Line 316, the description of the results was not clear enough. It is suggested to reorganize the language. >> Great efforts have been made to make these sentences more readable and easier to follow. Thanks "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Most orchid species exhibit an extreme case of hermaphroditism, owing to the fusion of male and female organs into a gynostemium. E xceptions to this rule have only been reported from the subtribes Catasetinae and Satyriinae. Here, I report an additional example of a Japanese orchid species whose flowers are not always hermaphroditic. In Japan, some flowers of the mycoheterotrophic orchid Eulophia zollingeri (Rchb.f.) J.J.Sm possess both the stigma and anther (i.e., anther cap and pollinaria), whereas others possess only the stigma . Therefore, pollination experiments, an investigation of floral morphology and observation of floral visitors were conducted to understand the reproductive biology of E. zollingeri in Miyazaki Prefecture, Japan. It was confirmed that E. zollingeri pos sesses a gynomonoecious reproductive system, a sexual system in which a single plant has both female flowers and hermaphroditic flowers. In addition, hermaphroditic flowers often p ossessed an effective self-pollination system while female flowers could avoid autogamy but suffered from severe pollinator limitation, due to a lack of agamospermy and low insect-mediated pollination. The present study represents the first documented example of gynomonoecy within Orchidaceae. Gynomonoecy in E. zollingeri may be maintained by the tradeoff between female flowers (with low fruit set but potential outcrossing benefits) and hermaphroditic flowers (with high fruit set but inbreeding depression in selfed offspring). This mixed mating is probably important in a fully mycoheterotrophic E. zollingeri because it occurs in shaded forest understorey with a paucity of pollinators.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The Orchidaceae are one of the largest and most morphologically diverse families of land plants, and include more than 28,000 species classified into ~760 genera <ns0:ref type='bibr' target='#b7'>(Christenhusz &amp; Byng, 2016)</ns0:ref>.</ns0:p><ns0:p>Variation in its floral characteristics, and the effect of this variation on reproductive success, has long intrigued botanists since the time of Darwin <ns0:ref type='bibr' target='#b15'>(Inoue, 1986;</ns0:ref><ns0:ref type='bibr' target='#b27'>Nilsson, 1988;</ns0:ref><ns0:ref type='bibr' target='#b34'>Sletvold &amp; Gren, 2011)</ns0:ref>. However, it is noteworthy that while the vast majority of orchid species produce only hermaphroditic flowers (i.e., flowers that possess both male and female reproductive organs; <ns0:ref type='bibr' target='#b29'>Pannell, 2009)</ns0:ref>, a variety of sexual polymorphisms (the co-occurrence of morphologically distinct sex phenotypes within the same species) can be found in flowering plants as a whole <ns0:ref type='bibr' target='#b0'>(Barrett, 2010)</ns0:ref>.</ns0:p><ns0:p>In fact, almost all orchid species exhibit an extreme case of hermaphroditism, owing to the fusion of male and female organs into a gynostemium <ns0:ref type='bibr' target='#b33'>(Rudall &amp; Bateman, 2002)</ns0:ref>. Exceptions to this rule have only been reported from the subtribes, Catasetinae and Satyriinae <ns0:ref type='bibr' target='#b29'>(Pannell, 2009;</ns0:ref><ns0:ref type='bibr' target='#b32'>Romero &amp; Nelson, 1986;</ns0:ref><ns0:ref type='bibr' target='#b14'>Huang et al., 2009)</ns0:ref>. More specifically, within Catasetinae, the members of Catasetum Rich. ex Kunth and Cycnoches Lindl. typically exhibit dioecy (i.e., unisexual individuals). In dioecious Catasetum, male flowers forcibly attach a large pollinarium onto euglossine bees, and the bees subsequently avoid flowers with the same appearance <ns0:ref type='bibr' target='#b32'>(Romero &amp; Nelson, 1986)</ns0:ref>. Therefore, Catasetum populations are sexually dimorphic, and the agitated pollinators bearing their pollinia move away from the male flowers to the morphologically different female flowers <ns0:ref type='bibr' target='#b32'>(Romero &amp; Nelson, 1986)</ns0:ref>. In addition, within Satyriinae, Satyrium ciliatum Lindl. has been reported to produce both hermaphroditic and female individuals (i.e., gynodioecy; <ns0:ref type='bibr' target='#b14'>Huang et al., 2009)</ns0:ref>. Female individuals of S. ciliatum can PeerJ reviewing PDF | (2020:07:51078:1:0:NEW 2 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed avoid pollen limitation for seed production and can be maintained in populations that experience high levels of pollen limitation, because females, via facultative parthenogenesis, can produce more seeds than hermaphrodites <ns0:ref type='bibr' target='#b14'>(Huang et al., 2009)</ns0:ref>. These examples helped elucidate the unusual maintenance of gender dimorphism in orchids <ns0:ref type='bibr' target='#b29'>(Pannell, 2009)</ns0:ref>.</ns0:p><ns0:p>Here I describe an additional example of an orchid species whose flowers are not always hermaphroditic. In Japan, some flowers of the mycoheterotrophic orchid Eulophia zollingeri (Rchb.f.) J.J.Sm possess both the stigma and anther (i.e., anther cap and pollinaria), whereas others possess only the stigma (Fig. <ns0:ref type='figure'>1</ns0:ref>). It is unlikely that the absence of anther cap and pollinaria is the result of removal by floral visitors, because careful dissection revealed that they were already absent before anthesis. Such a sexual system, in which plants have both female and hermaphroditic flowers co-occurring within the same plants, is called gynomonoecy. Compared with andromonoecy (male and hermaphroditic flowers within one plant) and monoecy (separate male and female flowers on the same plant), gynomonoecy remains a poorly studied sexual system, even though it occurs in 2.8-4.7% of flowering plants in at least 15 plant families <ns0:ref type='bibr' target='#b23'>(Lu &amp; Huang, 2006;</ns0:ref><ns0:ref type='bibr' target='#b45'>Yampolsky &amp; Yampolsky, 1922)</ns0:ref>.</ns0:p><ns0:p>In fact, while several hypotheses have been proposed, the adaptive significance of gynomonoecy remains largely unknown. First, the presence of the two flower types may permit flexible allocation of resources to female and male reproductive functions in response to environmental conditions <ns0:ref type='bibr' target='#b6'>(Charnov &amp; Bull, 1977;</ns0:ref><ns0:ref type='bibr' target='#b22'>Lloyd, 1979)</ns0:ref>. Second, female flowers may promote outcrossing more than hermaphroditic flowers <ns0:ref type='bibr' target='#b26'>(Marshall &amp; Abbott, 1984)</ns0:ref>. Third, due to the lack of evidence for the above two hypotheses, it has been proposed that female flowers may boost attractiveness to pollinators <ns0:ref type='bibr' target='#b2'>(Bertin &amp; Kerwin, 1998)</ns0:ref>. Finally, female flowers would be favored if hermaphroditic flowers were more susceptible to florivory <ns0:ref type='bibr' target='#b1'>(Bertin, Connors &amp; Kleinman, 2010;</ns0:ref><ns0:ref type='bibr' target='#b46'>Zhang, Xie &amp; Du, 2012)</ns0:ref>. Meanwhile, current understanding of the adaptive advantages of gynomonoecy is largely limited to the Asteraceae and a few species that have been investigated in other families <ns0:ref type='bibr' target='#b9'>(Davis &amp; Delph, 2005;</ns0:ref><ns0:ref type='bibr' target='#b25'>Mamut et al., 2014)</ns0:ref>. Manuscript to be reviewed of pollinators <ns0:ref type='bibr' target='#b21'>(Leake, 1994;</ns0:ref><ns0:ref type='bibr' target='#b48'>Zhou et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b36'>Suetsugu, 2013</ns0:ref><ns0:ref type='bibr' target='#b37'>Suetsugu, , 2015))</ns0:ref>. However, the Red Queen hypothesis suggests that sexual reproduction is important in a coevolutionary arms race between a parasite and host <ns0:ref type='bibr' target='#b20'>(Ladle, 1992)</ns0:ref>, such as between mycoheterotrophic plants and fungal hosts.</ns0:p><ns0:p>Intriguingly, Chinese E. zollingeri flowers are self-compatible but dependent on pollinators for fruit set; these nectarless flowers are exclusively pollinated by Nomia viridicinctula Cockerell through food deception <ns0:ref type='bibr' target='#b47'>(Zhang et al., 2014)</ns0:ref>. Consequently, the Chinese E. zollingeri population experienced strong pollinator limitation in its native habitat <ns0:ref type='bibr' target='#b47'>(Zhang et al., 2014)</ns0:ref>. In contrast, my preliminary investigation revealed that Japanese E. zollingeri populations consistently showed high fruit set. Therefore, it is possible that the Japanese hermaphroditic flowers are capable of autonomous selfing, providing reproductive assurance, while female flowers enhance outcrossing However, it should be also noted that the 'female' E. zollingeri flowers can be sterile without not only the male but also the female reproductive function. In fact, in Catasetum species that produce male and female flowers, intermediate flowers, which are sterile, have also been found <ns0:ref type='bibr' target='#b30'>(Romero, 1992)</ns0:ref>. Therefore, I first investigated whether the 'female' flowers of E. zollingeri possess female reproductive functions. After that, I conducted additional pollination experiments, investigations of floral morphology, and observations of floral visitors to determine the potential for reproductive assurance provided by autonomous selfing in female flowers and outcrossing via pollinator visitation in both hermaphroditic and female flowers.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head><ns0:p>Eulophia zollingeri is a mycoheterotrophic orchid distributed from India and Southeast Asia to New Guinea and Australia <ns0:ref type='bibr' target='#b28'>(Ogura-Tsujita &amp; Yukawa, 2008;</ns0:ref><ns0:ref type='bibr' target='#b38'>Suetsugu &amp; Mita, 2019;</ns0:ref><ns0:ref type='bibr' target='#b39'>Suetsugu, Matsubayashi &amp; Tayasu, 2020)</ns0:ref>. The behavior of floral visitors in Miyazaki City, Miyazaki Prefecture, Japan, was monitored during the peak flowering period (early to mid-July), in 2016 and 2017. Direct observations were made for ca. 30 h in total, during the peak of diurnal insect activity (09:00-17:00). The behavior of potential visitors was observed by walking around the study site, sitting next to flower patches, or hiding in the vegetation near flower clusters (within 1-2 m). In addition, artificial cross-pollination was performed in the same population in July 2016, by transferring pollinaria from different individuals to the stigmas of female flowers (five inflorescences, 10 flowers). <ns0:ref type='table' target='#tab_0'>2020:07:51078:1:0:NEW 2 Sep 2020)</ns0:ref> Manuscript to be reviewed Three to four months after manual pollination, all the mature but non-dehisced fruits capsules were collected. After the fruits were silica-dried, I weighed the total mass of dry seeds freed from each capsule to the nearest 0.1 mg. All the seeds from each plant were then mixed, and 100 randomly selected seeds from each plant were examined under a dissecting microscope to determine presence of an embryo. The effects of pollination treatment on fruit set were tested using Fisher's exact test. In addition, after confirming that the datasets were normally distributed using Levene's test, the effects of pollination treatment on the seed mass, and the proportion of seeds with an embryo were tested using ANOVA, followed by Fisher's multiple comparisons test.</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing PDF | (</ns0:head></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Despite conducting ca. 30 h of field observations, few insects were observed visiting the E. zollingeri flowers. Several dipteran visitors, such as the agromyzid fly Japanagromyza tokunagai, occasionally landed on the flowers. However, none of these visitors were observed to Manuscript to be reviewed remove or deposit pollinaria. The length of the dorsal sepal, lateral sepal, lateral petal, and lip were not significantly different between female and hermaphroditic flowers (Table <ns0:ref type='table'>1</ns0:ref>). In addition, there are marginally significant differences in the number of female flowers between the distal half (1.2 &#177; 1.1; mean &#177; SD) and the proximal half (3.3 &#177; 3.4; P = 0.06) of the inflorescence.</ns0:p><ns0:p>More than half (6/10) of the female flowers subsequently developed fruit capsules that contained seeds with an embryo through artificial cross-pollination in 2016, thereby demonstrating their female function and confirming the gynomonoecy of the species. The results are stable at least in the investigated site, because similar results were obtained in 2017 (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>).</ns0:p><ns0:p>The detailed pollination experiments showed that the begged female flowers failed to develop fruits autonomously, excluding the possibility of agamospermy, while comparable fruit set ratio was also obtained in open, bagged, manual geitonogamous and allogamous hermaphroditic flowers. Therefore, the hermaphroditic flowers are capable of outbreeding, but self-compatible and not pollinator-limited for fruit set under natural condition (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>). The seed mass did not vary significantly with pollination treatment (ANOVA F 6, 37 = 1.17, P = 0.34), while the proportion of seeds with an embryo differ significantly among pollination treatment (ANOVA F 6, 37 = 2.43, P = 0.04). In general, the pollination experiments indicated that outcrossing tended to increase both seed mass and the number of seeds with embryo, suggesting a negative impact of self-pollination, while the differences were not always significant (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref> The observation of floral morphology confirmed that most of the hermaphroditic flowers possessed an effective self-pollination system, in which the rostellum was poorly developed and lost the ability to physically separate the stigma and pollinaria, allowing contact between them (Fig. <ns0:ref type='figure' target='#fig_5'>2B</ns0:ref>), whereas the others had functional rostella and were therefore unlikely autogamous (Fig. <ns0:ref type='figure' target='#fig_5'>2D</ns0:ref>). The female flowers had column with neither a rostellum nor anther cap and pollinaria (Fig. <ns0:ref type='figure' target='#fig_5'>2F</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Most orchid species exhibit an extreme case of hermaphroditism, owing to the fusion of male and female organs into a gynostemium. Here we showed that Eulophia zollingeri develops both female and hermaphroditic flowers co-occurring within the same inflorescence (i.e., gynomonoecy), while Catasetum and Cycnoches typically produces unisexual individuals (i.e., PeerJ reviewing PDF | (2020:07:51078:1:0:NEW 2 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed dioecy, <ns0:ref type='bibr' target='#b32'>Romero &amp; Nelson, 1986)</ns0:ref>, and Satyrium ciliatum produces both hermaphroditic and female individuals (i.e., gynodioecy; <ns0:ref type='bibr' target='#b14'>Huang et al., 2009)</ns0:ref>. Therefore, the present study represents the first example of gynomonoecy within the Orchidaceae. In addition, hermaphroditic flowers of E. zollingeri often possess an effective self-pollination system, while the female flowers without agamospermy can improve the probability of outcrossing (but selfing may still occur via geitonogamous pollinations). While female flowers are generally smaller than hermaphroditic flowers in other gynomonoecious species (reviewed by <ns0:ref type='bibr' target='#b25'>Mamut et al., 2014)</ns0:ref>, the size of floral parts did not differ significantly between female and hermaphroditic flowers of E. zollingeri. In addition, female flowers tend to be on the lower part of the inflorescence, suggesting that production of female flowers is not a result of resource competition. In summary, the system observed in E. zollingeri is consistent with the outcrossing-benefit hypothesis for gynomonoecy <ns0:ref type='bibr' target='#b25'>(Mamut et al., 2014)</ns0:ref>.</ns0:p><ns0:p>Many models predict that plants evolve toward either complete self-fertilization or complete outcrossing <ns0:ref type='bibr' target='#b5'>(Charlesworth &amp; Charlesworth, 1990</ns0:ref>). However, it seems that mixedmating systems are more common in nature <ns0:ref type='bibr' target='#b43'>(Vogler &amp; Kalisz, 2001;</ns0:ref><ns0:ref type='bibr' target='#b44'>Whitehead et al., 2018)</ns0:ref>, possibly because mixed mating can reduce the probability of inbreeding depression via outcrossing, while still providing reproductive assurance via selfing <ns0:ref type='bibr' target='#b12'>(Goodwillie &amp; Weber, 2018)</ns0:ref>. As such, mixed mating systems are often referred to as 'best-of-both-worlds' mating systems <ns0:ref type='bibr' target='#b9'>(Davis &amp; Delph, 2005;</ns0:ref><ns0:ref type='bibr' target='#b12'>Goodwillie &amp; Weber, 2018)</ns0:ref>. Mixed mating can be accomplished by delayed selfing (selfing that occurs after all opportunities for outcrossing are past), because it provides reproductive assurance without limiting outcrossing opportunities. In addition, mixed mating can also occur in species that produce two flower types within the same plant.</ns0:p><ns0:p>Gynomonoecy is such a system involving two flower types that allows for mixed mating. Indeed, in the E. zollingeri populations investigated here, hermaphroditic flowers conferred reproductive assurance under pollinator-limited conditions, whereas female flowers, despite their susceptibility to pollen limitation, can facilitate outcrossing, because of the lack of autonomous selfing (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>).</ns0:p><ns0:p>It is possible that geitonogamy reduces the possibility of outcrossing in female flowers. In E. zollingeri, though, the level of geitonogamy will be low, because only a few flowers on each plant are open at one time. In particular, the risk of geitonogamy is probably negligible in necterless E. zollingeri, given that pollinators are likely to quickly leave inflorescences in food-PeerJ reviewing PDF | (2020:07:51078:1:0:NEW 2 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed deceptive plants <ns0:ref type='bibr' target='#b47'>(Zhang et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b40'>Suetsugu et al., 2015)</ns0:ref>. Indeed, the avoidance of geitonogamy has been hypothesized as a driving force for the evolution of food deceptive pollination in plants <ns0:ref type='bibr' target='#b17'>(Johnson, Peter &amp; &#197;gren, 2004)</ns0:ref>. Moreover, it is noteworthy that female flowers tended to be on the lower part of the inflorescence, given that E. zollingeri were exclusively pollinated by the halictid bee Nomia viridicinctula <ns0:ref type='bibr' target='#b47'>(Zhang et al., 2014)</ns0:ref> and that bees usually visit bottom flowers first and move upwards within an inflorescence (e.g. <ns0:ref type='bibr' target='#b16'>Iwata et al., 2012)</ns0:ref>. In fact, several studies have shown that pollinator behaviors lead to directional pollen flow within inflorescences and influence floral sex allocation <ns0:ref type='bibr' target='#b4'>(Brunet &amp; Charlesworth, 1995)</ns0:ref>.</ns0:p><ns0:p>The first flowers visited will receive more pollen grains from other plants, while the last flowers visited before pollinators leave the inflorescence tend to receive geitonogamous pollination but successfully export pollen grains to other plants <ns0:ref type='bibr' target='#b19'>(Kudo, Maeda &amp; Narita, 2001)</ns0:ref>. Therefore, it has been predicted that female-biased allocation to lower flowers and male-biased allocation to those in upper positions occurs in bee-pollinated plants <ns0:ref type='bibr' target='#b19'>(Kudo, Maeda &amp; Narita, 2001)</ns0:ref>. The variations in floral sex allocation within E. zollingeri are consistent with the theory and are probably effective for lowering the risk of geitonogamy.</ns0:p><ns0:p>The advantages of outcrossing and, consequently, producing female flowers can be somewhat influenced by the degree of inbreeding depression and pollinator availability <ns0:ref type='bibr' target='#b35'>(Smithson, 2006)</ns0:ref>. In E. zollingeri, pollinator-mediated fruit set was arguably low, at least in the investigated population, given that (i) direct pollinator observation was unsuccessful and (ii) pollination experiments showed that natural pollination in female flowers was recorded only in one flower. Nonetheless, a small degree of outcrossing can result in a rapid decline in linkage disequilibrium across the genome and can be sufficient to overcome negative effects such as the accumulation of deleterious mutations and the slowdown in adaptation rate <ns0:ref type='bibr' target='#b8'>(Culley &amp; Klooster, 2007)</ns0:ref>. In addition, although the differences were not obvious <ns0:ref type='bibr' target='#b42'>(Tremblay et al. 2005)</ns0:ref>, both artificial allogamous pollination and natural pollination in a female flower tended to increase seed mass and the proportion of seed with an embryo in E. zollingeri (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>), probably providing some support for the negative effect of autonomous selfing. It should be noted that, while seed mass and presence of an embryo was measured as the indicator of inbreeding depression, it can even under-estimate the level of inbreeding depression. Inbreeding depression might be more prominent during later stages such as seed germination or seedling growth <ns0:ref type='bibr' target='#b35'>(Smithson, 2006)</ns0:ref>. This possibility warrants further investigation.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:07:51078:1:0:NEW 2 Sep 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The outcrossing opportunity might be particularly important in mycoheterotrophic plants exploiting their mycorrhizal partners <ns0:ref type='bibr' target='#b41'>(Suetsugu et al., 2017)</ns0:ref>, given that the Red Queen hypothesis argues that outcrossing is maintained by antagonistic interactions between a host and parasite <ns0:ref type='bibr' target='#b20'>(Ladle, 1992;</ns0:ref><ns0:ref type='bibr' target='#b11'>Gibson &amp; Fuentes, 2015)</ns0:ref>. In fact, although most studies highlighted the importance of autonomous self-pollination in mycoheterotrophic plants <ns0:ref type='bibr' target='#b21'>(Leake, 1994;</ns0:ref><ns0:ref type='bibr' target='#b48'>Zhou et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b36'>Suetsugu, 2013</ns0:ref><ns0:ref type='bibr' target='#b37'>Suetsugu, , 2015))</ns0:ref>, several recent studies have shown that mixed mating system (outcrossing pollinators with delayed self-pollination) occurs in mycoheterotrophic species belonging to Ericaceae and Gentianaceae which have independently evolved mycoheterotrophy from E. zollingeri <ns0:ref type='bibr' target='#b18'>(Klooster and Culley, 2009;</ns0:ref><ns0:ref type='bibr' target='#b13'>Hentrich et al., 2010)</ns0:ref>. Given that mycoheterotrophic plants face similar selective constraints such as limited access to carbon sources and/or shaded understorey habitats with a paucity of pollinators <ns0:ref type='bibr' target='#b18'>(Klooster &amp; Culley, 2009;</ns0:ref><ns0:ref type='bibr' target='#b13'>Hentrich, Kaiser &amp; Gottsberger, 2010;</ns0:ref><ns0:ref type='bibr' target='#b36'>Suetsugu, 2013</ns0:ref><ns0:ref type='bibr' target='#b37'>Suetsugu, , 2015))</ns0:ref>, a mixed mating system, including gynomonoecy, can be more common and important in mycoheterotrophic plants than previously thought.</ns0:p><ns0:p>Overall, it can be concluded that E. zollingeri preserve reproductive assurance by producing autonomously selfing hermaphroditic flowers and still maintain the potential benefit of producing outcrossed offspring by developing female flowers. Current understanding of the adaptive advantages of gynomonoecy is largely limited to the Asteraceae <ns0:ref type='bibr' target='#b26'>(Marshall &amp; Abbott, 1984;</ns0:ref><ns0:ref type='bibr' target='#b2'>Bertin &amp; Kerwin, 1998;</ns0:ref><ns0:ref type='bibr' target='#b1'>Bertin, Connors &amp; Kleinman, 2010;</ns0:ref><ns0:ref type='bibr' target='#b46'>Zhang, Xie &amp; Du, 2012)</ns0:ref>. The outcrossing hypothesis of gynomonoecy has been questioned in many asteraceous taxa, given that most Asteraceae species are self-incompatible <ns0:ref type='bibr' target='#b2'>(Bertin &amp; Kerwin, 1998)</ns0:ref>. However, it has been shown that hermaphroditic flowers promote seed quantity in that they are more attractive to pollinators and/or are capable of autonomous selfing, while female flowers compensate for loss of male function through outcrossing in non-asteraceous taxa [i.e., Silene noctiflora (Caryophyllaceae) and Eremurus anisopterus (Xanthorrhoeaceae)] ( <ns0:ref type='bibr' target='#b9'>Davis &amp; Delph, 2005;</ns0:ref><ns0:ref type='bibr' target='#b25'>Mamut et al., 2014)</ns0:ref>. Taken together with these recent finding, I suggested that the ability of female flowers to reduce geitonogamy and enhance outcrossing may be widespread in gynomonoecious plants. However, it is noteworthy that although many orchids are (at least partially) parasitic on their mycorrhizal fungi and exhibit strong pollinator-limitation <ns0:ref type='bibr' target='#b21'>(Leake, 1994)</ns0:ref>, gynomonoecy is not prevalent within the orchid family as a whole. Given that (i) hypotheses regarding the adaptive significance of gynomonoecy are not mutually exclusive and (ii) the seed-feeding fly Japanagromyza tokunagai have probably substantial negative impact on Manuscript to be reviewed the reproduction of E. zollingeri <ns0:ref type='bibr' target='#b38'>(Suetsugu &amp; Mita, 2019)</ns0:ref>, benefits other than outcrossing, such as herbivory reduction, could also have contributed to the evolution of gynomonoecy. Therefore, further investigation is needed to elucidate the potentially diverse adaptive significance, disadvantages, and developmental constraints of gynomonoecy. Different superscript letters indicate significant differences (P &lt; 0.05) between treatment groups. Both seed mass and seeds with an embryo are expressed by mean &#177; SD, whenever the sample size is more than &gt; 1.</ns0:p><ns0:p>1</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Therefore, I investigated the reproductive biology of E. zollingeri, which potentially represents the first documentation of gynomonoecy within Orchidaceae, to understand the ecological significance of the different reproductive strategies of the two floral morphs within one individual. Autonomous self-pollination has been suggested to be favorable for mycoheterotrophic plants, as they are restricted to dark shaded forest understorey with a paucity PeerJ reviewing PDF | (2020:07:51078:1:0:NEW 2 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>After confirming with the cross-pollination experiment that both hermaphroditic and female flowers produce fruits, additional pollination experiments were conducted in early July 2017.Flowers were either (i) manually cross-pollinated by transferring pollinaria to the stigmas of different individuals (five inflorescences, 10 each of female and hermaphroditic flowers); (ii) manually geitonogamous-pollinated by transferring pollinaria to the stigmas of the different flowers within the same individuals for female flowers and of the same flowers for hermaphroditic flowers (five inflorescences, 10 each of female and hermaphroditic flowers); (iii) enclosed in mesh bags to exclude floral visitors and test for autonomous self-pollination (five inflorescences, 10 hermaphroditic flowers); or (iv) left unmanipulated, in order to monitor fruit set under natural conditions (seven inflorescences, 19 female flowers and 21 hermaphroditic flowers). In addition, the relative position of female and hermaphroditic flowers on the racemes was determined in 12 inflorescences. Furthermore, to compare flower size between female and hermaphroditic flowers in gynomonoecious individuals, we measured the length of the dorsal sepal, lateral sepal, lateral petal, and lip of 10 plants using digital calipers to 0.1 mm in early July 2017. Finally, the distribution of female flowers was checked in 12 inflorescences in early July 2017. After dividing each inflorescence into distal and proximal halves, the data were tested using the Mann-Whitney U-test to investigate whether female flowers tended to be in the distal or basal part of the inflorescence.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51078:1:0:NEW 2 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51078:1:0:NEW 2 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure legends Figure 1</ns0:head><ns0:label>legends1</ns0:label><ns0:figDesc>Figure legends</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 Column morphology of Eulophia zollingeri flowers. (A, B) Column with a degenerate rostellum, which facilitates autogamy. (C, D) Column with a well-developed rostellum, which prevents autogamy. (E, F) Column with neither a rostellum nor anther cap and pollinaria. AC, anther cap; RS, rostellum; PO, pollinaria, ST, stigma.</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Effect of pollination treatment on fruit set, seed mass, and proportion of seeds with an embryo in Eulophia zollingeri.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Flower type</ns0:cell><ns0:cell>Treatment</ns0:cell><ns0:cell>Manual allogamy</ns0:cell><ns0:cell>Manual geitonogamy</ns0:cell><ns0:cell>Autonomous autogamy</ns0:cell><ns0:cell>Open</ns0:cell></ns0:row><ns0:row><ns0:cell>Hermaphroditic</ns0:cell><ns0:cell>Fruit set (%)</ns0:cell><ns0:cell>70.0 a</ns0:cell><ns0:cell>70.0 a</ns0:cell><ns0:cell>50.0 a</ns0:cell><ns0:cell>57.1 a</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Seed mass</ns0:cell><ns0:cell>31.6 &#177; 11.6</ns0:cell><ns0:cell>24.1 &#177; 11.4</ns0:cell><ns0:cell>20.8 &#177; 9.3</ns0:cell><ns0:cell>24.9 &#177; 8.6</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Seeds with embryo</ns0:cell><ns0:cell>82.4 &#177; 4.2 ac</ns0:cell><ns0:cell>79.0 &#177; 4.2 abc</ns0:cell><ns0:cell>77.2 &#177; 2.9 bc</ns0:cell><ns0:cell>79.2 &#177; 3.6 c</ns0:cell></ns0:row><ns0:row><ns0:cell>Female</ns0:cell><ns0:cell>Fruit set (%)</ns0:cell><ns0:cell>60.0 a</ns0:cell><ns0:cell>60.0 a</ns0:cell><ns0:cell>0.0</ns0:cell><ns0:cell>5.3 b</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Seed mass</ns0:cell><ns0:cell>30.2 &#177; 14.7</ns0:cell><ns0:cell>25.7 &#177; 11.0</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>44.9</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Seeds with embryo</ns0:cell><ns0:cell>83.3 &#177; 4.4 a</ns0:cell><ns0:cell>77.3 &#177; 2.9 bc</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>82.0 abc</ns0:cell></ns0:row></ns0:table></ns0:figure> </ns0:body> "

"Department of Biology, Graduate School of Science, Kobe University 1-1 Rokkodai, Nada-ku, Kobe, 657-8501, Japan Dear Dr. David Roberts, Editor, PeerJ Thank you for your positive comments on our submission entitled 'Gynomonoecy in a mycoheterotrophic orchid Eulophia zollingeri with autonomous selfing hermaphroditic flowers and putatively outcrossing female flowers'. I am grateful to the three reviewers for their insights and constructive comments on the earlier version of our manuscript. These comments have been helpful in improving our manuscript. I greatly appreciate your time and effort to carefully review our manuscript and being given the opportunity to revise it. Please find below my detailed responses to the reviewers’ comments. I feel these revisions have strengthened the resulting paper. I hope that the revised version addresses all of the concerns raised. I would, of course, be willing to make additional revisions to make the manuscript acceptable for publication. Sincerely yours, Kenji Suetsugu Kenji Suetsugu (Ph.D.) Associate Professor Contact Address: Department of Biology, Graduate School of Science, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe, 657-8501, Japan Email: [email protected] Tel: +81-78-803-5713 HP: https://sites.google.com/site/suetsuguen/ I am grateful to the reviewers for the constructive comments on the previous version of the manuscript. All the reviewers noticed several typographical errors and suggested the rewording of some sentences, all of which I have amended in the revised document. Below, I have provided the details of the other changes made. The responses (in regular font) are given directly below the reviewers’ comments (in italic font). The changes made in the revised manuscript are highlighted by colored text. Replies to Dr. David Roberts, Editor Many thanks for submitting your manuscript to PeerJ. As you can see all the reviewers, as well as myself, find your paper to be an intriguing study that is worthy of publication. However, the reviewers found potential issues with the interpretation of the results that need careful consideration and potentially further support. I have therefore recommended major revisions and look forward to seeing your revised manuscript and rebuttal in due course. -Thank you for the encouragements (all the reviewers, as well as myself, find your paper to be an intriguing study that is worthy of publication). The manuscript has carefully been rechecked and the necessary changes have been made in accordance with reviewers’ suggestions. The manuscript has benefited from these insightful suggestions. I hope that the revised version of the manuscript will be found suitable for publication. I would, of course, be willing to make additional revisions, if needed, to make the manuscript acceptable for publication. Replies to Reviewer 1 (Dr. Florian Schiestl) This is an interesting article documenting the presence of single sex flowers in a orchid. As most orchids are hermaphroditic, this is a worthwhile contribution to our knowledge of mating systems in orchids. I have seen a few problems that need fixing before the paper can be published. -I appreciate your positive comments and constructive criticism. I also sincerely appreciate your helpful comments, which have enabled me to significantly improve the manuscript. Table 1 needs to indicate statistical values -As already noted in the main text, the length of all the floral parts (dorsal sepal, lateral sepal, lateral petal, and lip) were not significantly different between female and hermaphroditic flowers. Therefore, I did not include different superscript letters. Figure 2 needs labelling of the different organs -Thank you for the suggestion. I have added the label of the different organs in Figure 2. L122, Table 2: pollinations between different flowers of the same plant are called geitonogamy, not autogamy (i.e., an only-female flower is not capable of autogamy) -I have changed autogamy with geitonogamy, as suggested. Abstract: it is mentioned that female flowers increase chance of outcrossing. If this was the case, they should be more attractive than hermaphroditic flowers, to increase the income of pollen. I guess what is really meant here is that female flowers avoid autogamy, which is semantically not the same. -As suggested, I have rephrased the pointed parts with avoid autogamy. L97: sentence starting with “however” makes no sense; reformulate. -As suggested, I have rewritten the pointed sentence. Replies to Reviewer 2 (Dr. James Ackerman) This manuscript is well written with only a few minor grammatical issues. The literature review is not exhaustive but is intelligently selective to get the breadth of issues to the forefront. The figures and tables are well-done and the raw data are available in the supplemental files. -I appreciate your positive comments and constructive criticism. I also sincerely appreciate your helpful comments, which have enabled me to significantly improve the manuscript. L162-163: The way the sentence reads, severe pollinator limitation improves chances for outcrossing. Pollinator limitation is not directly related to outcrossing probabilities. Being a female flower without agamospermy is what improves the probability of outcrossing (selfing may still occur via geitonogamous pollinations). -I am sorry for the confusing expression. I have rephrased the pointed parts with “female flowers without agamospermy can improve the probability of outcrossing (but selfing may still occur via geitonogamous pollinations)”, as suggested. L119-127 It is not clear how the averages were calculated. As flowers on an inflorescence are not independent of one another (they receive resources from the same plant; pollinator attraction may be at the inflorescence level, not the flower level; etc.), the sample size for each treatment is 5, not 10. Furthermore, from an evolutionary perspective, fitness is at the plant level, not the flower. ANOVAs were calculated to compare treatments for fruit and seed set. The author should state whether the data meet the assumptions of the test, and also mention which test(s) they used to determine that. Furthermore, at a minimum, F statistics and degrees of freedom must be shown, not just the P-value. This would also help the reader understand the statistical analysis. -I have simply averaged all the values. In this respect, I agreed with you that flowers on an inflorescence are not independent of one another, and the sample size for each treatment is, therefore, not 10 but 5. I should apologize for the small number of plants used in the artificial pollination experiments. In order to minimize the impact on the study plant populations, I limited the numbers of plants used. However, I believe that, in spite of the low sample size, the present study clearly indicated there were no fruits developing by apomixis in female flowers, while there was a relatively high proportion of fruit developed by both pollinator exclusion and controlled self- and cross-pollination in hermaphroditic flowers. Therefore, I believe that the small sample size does not substantially reduce the value of the present study. In addition, as suggested, I have noted that the data meet the assumptions of the test, and we have also added the F statistics and degrees of freedom in the revised manuscript. L167: It is difficult to imagine that resource constraints would be the reason for the production of female flowers at the top (distal end) of an inflorescence because fruit production is far more expensive than male flowers. Hermaphroditic flowers may be more expensive because of pollen production, but one may argue that the female flowers would generally have genetically superior seeds and that there would be selection (if genetically based variation existed) for a favored place on the inflorescence. -Thank you for the opinion. I have agreed with you that resource constraints is not likely to be main reason to produce female flowers at the top of an inflorescence. However, since female flowers tended to be on the lower part of the inflorescence in E. zollingeri., this is not so relevant to our paper. Therefore, I have shortly introduced pervious hypothesis and have decided not to add additional discussion on this topic Under resource constraints, one might expect andromonoecy to be advantageous, with male flowers produced in the upper parts of the inflorescence because they are cheap to make. Using the raw data on flower position, I divided each inflorescence into two equal halves, distal and proximal halves. Female flowers averaged 1.17 flowers in the distal half, and 3.33 flowers in the proximal half. I did not test for differences (non-parametric method would likely be appropriate) but it looks like it would be significant. So, if that is true, then there is a tendency for female flowers to be on the lower part of the inflorescence. I suggest you do this analysis or something like it. -Thank you very much for pointing out important fact. While I did not notice the fact, I have now found that there was a tendency for female flowers to be on the lower part of the inflorescence, based on the suggested analysis. I have considered this is very reasonable, given that bees tend to move upwards on inflorescences. That is to say, because bees tend to move upward on inflorescences, they probably import pollinia from different plants into flowers on the lower part of inflorescences (that are more likely to be females). After that, they will export pollinia from hermaphroditic flowers on the higher part of inflorescences to other plants. The variations in floral sex allocation within inflorescences are probably effective for lowering the risk of geitonogamy. I have added short discussion on the topic. It is not clear whether seed set is different between self and cross pollinations. The averages are very close. Usually, if there is a difference, it is much more obvious (see table 6 in Tremblay et al. 2005, Biol J Linn Soc 84: 1-54). -I have also agreed with you that inbreeding depression is rather week. However, as noted in Reviewer 3, the present method can under-estimate the level of inbreeding depression. I have added the short discussion on this topic Invoking the Red Queen hypothesis is an interesting angle and worthy of further exploration. Nonetheless, I have doubts that it could explain gynomonoecy with the parasitic orchid-fungus interaction being the underlying driver. If the Red Queen is dealing cards with orchids via their host-parasite interactions, then it should be most obvious with mycoheterotrophic species. However, it is this reviewer’s perception that most of them are autogamous – more so than the rate in which we see in autotrophic species, which if true would run contrary to expectations. You might dig into this a little more. -Thank you for sharing me your detailed thought. I have also considered that further studies are needed to elucidate the potentially diverse ecological functions, disadvantages and developmental constraints of gynomonoecy. Overall, I have considered that relationship between gynomonoecy and maintenance of antagonistic interactions is not a demonstration but one of the hypotheses (are not mutually exclusive). In addition, it should be noted that, while most studies have highlighted the importance of that autonomous self-pollination in mycoheterotrophic plants, several recent studies have also pointed out a mixed mating system can be more common in mycoheterotrophic plants than previously thought. Since this manuscript represents a first step in understanding a rare example of gynomonoecy in the Orchidaceae, I believe it is worth mentioning future research direction. Therefore, I have amended the concluding remarks, by noting that “However, it is noteworthy that although many orchids are (at least partially) parasitic on their mycorrhizal fungi and exhibit strong pollinator limitation (Leake, 1994), gynomonoecy is not prevalent within the orchid family as a whole. Since hypotheses regarding the adaptive significance of gynomonoecy are not mutually exclusive, benefits other than outcrossing, such as herbivory reduction, could also have contributed to the evolution of gynomonoecy. Hence, further investigation is needed to elucidate the potentially diverse adaptive significance, disadvantages, and developmental constraints of gynomonoecy.” Replies to Reviewer 3 An intriguing study that is basically well conceived and carefully undertaken, but it does tend to over-interpret the data and make unnecessarily grand claims. -I appreciate your positive comments and constructive criticism. I also sincerely appreciate your helpful comments, which have enabled me to significantly improve the manuscript. Essentially fine to explore the ecological subject described, although the inferences are a little over-interpreted in an evolutionary context in the Discussion. A very intriguing subject matter and clearly a rare example of gynomonoecy in the Orchidaceae. However, the Discussion tends to over-interpret the data, making rather grand conclusions from a limited – albeit intriguing – sample set. I think a more guarded approach should be adopted, particularly with using embryo presence to infer seed viability, since the two are not necessarily correlated, and in deriving support for the hypothesis that the observed mixed mating strategy is important for maintaining the species’ symbiotic (“antagonistic”) interactions. If the latter is to be viewed as a solid interpretation for the data at hand, I feel the author should consider why this reproductive strategy is not more generally prevalent within the orchid family as a whole, since many of its species are obligately mycorrhizal, many occur in pollinator-poor habitats and many exhibit pollinator-limitation -I have totally agreed with you that presence of an embryo probably does not always lead to seed viability. Therefore, I have revised throughout the manuscript not to use seed viability. In addition, I have agreed with you that this manuscript represents an initial step in understanding of a rare example of gynomonoecy in the Orchidaceae. In fact, I have also considered that further studies is needed to elucidate the potentially diverse ecological functions, disadvantages and developmental constraints of gynomonoecy. While I attempted to explain our notion in the previous version of the manuscript, the misconception was entirely my fault, because it was not stated clearly enough. Based on comments of you and Reviewer 2 (Dr. James Ackerman), the additional statement on the importance of mixed mating in mycoheterotrophic plants have now been included but I've softened the related argument throughout the manuscript. Line 29. Insert “documented” before “example”. Why do you claim this to be the first documented example if, as you state in the Introduction, the same phenomenon has been reported previously in Satyrium ciliatum? -As already noted in previous manuscript, while Satyrium ciliatum has been reported to produce both hermaphroditic and female individuals (i.e., gynodioecy), Eulophia zollingeri has both female and hermaphroditic flowers co-occurring within the same plants (i.e., gynomonoecy). This is the clear difference between Satyrium ciliatum and Eulophia zollingeri. Line 35. I don’t understand the meaning of “such as mycoheterotrophic plants and its fungal victims”. Change to “such as those with fungal associates”. -I have deleted the sentence form the abstract, since it is still a hypothesis. Line 60. Change “The females of” to “Female flowers of”. -As noted in previous comments, “Female flowers” is not appropriate. Therefore, I have changed “The females” with “Female individuals”. Line 81. Why would female flowers be more attractive to pollinators? Please explain. -In the absence of clear evidence in Asteraceae in support of the above two hypotheses concerning gynomonoecy, Bertin & Kerwin (1998) proposed the hypothesis that the advantage of the pistillate flowers in aster heads lies in their attractiveness to pollinators. I have explained it in the revised manuscript. Line 98. It is not clear what you mean here. Why do you refer to “female” flowers having male function? -I am sorry for confusing expression. I have rewritten the pointed sentence. Lines 87–105. In this discussion of the mating system of Eulophia zollingeri, I am surprised you do not refer to the study of Zhang et al. (Guihaia 34: 541–547. 2014), who report data for crossing experiments and observations of pollinators in this species in China. -Thank you for providing this important information regarding the literature on the subject. I have added the short discussion on the study of Zhang et al. (Guihaia 34: 541–547. 2014), as suggested. Line 136. By what method or measure was seed viability assessed? Since there are different assumptions involved in the different methods available (presence of an embryo, TTC-staining, in vitro germinability testing, in situ seed-baiting, etc.), you need to be more precise in describing your approach. Simple presence of an embryo should not be misconstrued as viability. -As you suspected, I have only examined the presence of an embryo. I have revised throughout the manuscript not to use seed viability. Line 148. The presence of an embryo alone should not be misconstrued as viability, which would require germination experiments to verify. -As mentioned before, Therefore, I have revised throughout the manuscript not to use seed viability. Line 147. And to which experiment are you referring here? Is this as a result of artificial self- or cross-pollination or through open pollination? -I have clarified that the statement is based on artificial cross-pollination in 2016. Lines 147–156. Please refer to Table 2 earlier in this paragraph so it obvious from what raw data you are basing these inferences. -I have referred to Table 2 earlier in this paragraph, as suggested. Line 150. Where are the data showing the results of the crossing experiments? -I am sorry for lack of detailed explanation on the pollination experiments. I have now explained the results in not only Table 2 but also maintext. Line 159. To avoid confusion with the description of separate female and hermaphroditic flowers in Satyrium ciliatum that you provide in the Introduction, I think it would good to emphasise the distinguishing features of the breeding system identified here. -As suggested, I have emphasized the distinguishing features of the breeding system identified here. Line 162. Perhaps better to restructure this sentence. -As also requested by suggested by Reviewer 2 (Dr. James Ackerman), I have rephrased the pointed parts with “female flowers without agamospermy can improve the probability of outcrossing (but selfing may still occur via geitonogamous pollinations)”. Lines 170–187. How does this discussion gel with the findings of Zhang et al. (Guihaia 34: 541–547. 2014), who claim E. zollingeri is food-deceptive? -As suggested, we have added short discussion on the findings of Zhang et al. (2014). Lines 202–205. But you have not measured actual viability in terms of germinability. -I have added short discussion on the possibility that our method under-estimate the level of inbreeding depression. Lines 206–208. If this is the case, why is this strategy not more widely prevalent throughout the Orchidaceae, given that the vast majority of its species are obligately mycorrhizal, and that many occur in pollinator-poor habitats and exhibit pollinator-limitation? I suspect there are other factors other than those you mention here. This interpretation is a little simplistic. -Thank you for the important suggestion. I have agreed with you that my results should be carefully interpreted, given that most orchidaceous species are obligately mycorrhizal, and that many occur in pollinator-poor habitats and exhibit pollinator-limitation. In fact, I have totally with you that other factors (both adaptive significances, disadvantages and developmental constraints) deserve future study. Consequently, I have now noted “Since hypotheses regarding the adaptive significance of gynomonoecy are not mutually exclusive, benefits other than outcrossing, such as herbivory reduction, could also have contributed to the evolution of gynomonoecy. Hence, further investigation is needed to elucidate the potentially diverse adaptive significance, disadvantages, and developmental constraints of gynomonoecy.” in the revised manuscript. In addition, I have adopted more conservative phrasing on Red Queen hypothesis, as suggested by both you and Reviewer 2 (Dr. James Ackerman). "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Most orchid species exhibit an extreme case of hermaphroditism, owing to the fusion of male and female organs into a gynostemium. E xceptions to this rule have only been reported from the subtribes Catasetinae and Satyriinae. Here, I report an additional orchidaceous example whose flowers are not always hermaphroditic. In Japanese populations of Eulophia zollingeri (Rchb.f.) J.J.Sm, a widespread Asian and Oceanian orchid, some flowers possess both the anther (i.e., anther cap and pollinaria) and stigma, whereas others possess only the stigma . Therefore, pollination experiments, an investigation of floral morphology and observations of floral visitors were conducted to understand the reproductive biology of E. zollingeri in Miyazaki Prefecture, Japan. It was confirmed that E. zollingeri studied here pos sesses a gynomonoecious reproductive system, a sexual system in which a single plant has both female flowers and hermaphroditic flowers. In addition, hermaphroditic flowers often p ossessed an effective self-pollination system while female flowers could avoid autogamy but suffered from severe pollinator limitation, due to a lack of agamospermy and low insect-mediated pollination. The present study represents the first documented example of gynomonoecy within Orchidaceae. Gynomonoecy in E. zollingeri may be maintained by the tradeoff in reproductive traits between female flowers (with low fruit set but potential outcrossing benefits) and hermaphroditic flowers (with high fruit set but inbreeding depression in selfed offspring). This mixed mating is probably important in mycoheterotrophic E. zollingeri because it occurs in shaded forest understorey with a paucity of pollinators.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>The Orchidaceae are one of the largest and most morphologically diverse families of land plants, and include more than 28,000 species classified into ~760 genera <ns0:ref type='bibr' target='#b7'>(Christenhusz &amp; Byng, 2016)</ns0:ref>.</ns0:p><ns0:p>Variations in its floral characteristics and their effects on reproductive success have long intrigued botanists since the time of Darwin <ns0:ref type='bibr' target='#b15'>(Inoue, 1986;</ns0:ref><ns0:ref type='bibr' target='#b26'>Nilsson, 1988;</ns0:ref><ns0:ref type='bibr' target='#b34'>Sletvold &amp; Gren, 2011)</ns0:ref>. However, it is noteworthy that while the vast majority of orchid species produce only hermaphroditic flowers (i.e., flowers that possess both male and female reproductive organs; <ns0:ref type='bibr' target='#b28'>Pannell, 2009)</ns0:ref>, a variety of sexual polymorphisms (the co-occurrence of morphologically distinct sex phenotypes within the same species) can be found in flowering plants as a whole <ns0:ref type='bibr' target='#b0'>(Barrett, 2010)</ns0:ref>.</ns0:p><ns0:p>In fact, almost all orchid species exhibit an extreme case of hermaphroditism, owing to the fusion of male and female organs into a gynostemium <ns0:ref type='bibr' target='#b32'>(Rudall &amp; Bateman, 2002)</ns0:ref>. Exceptions to this rule have only been reported from the subtribes, Catasetinae and Satyriinae <ns0:ref type='bibr' target='#b28'>(Pannell, 2009;</ns0:ref><ns0:ref type='bibr' target='#b31'>Romero &amp; Nelson, 1986;</ns0:ref><ns0:ref type='bibr' target='#b14'>Huang et al., 2009)</ns0:ref>. More specifically, within Catasetinae, the members of Catasetum Rich. ex Kunth and Cycnoches Lindl. typically exhibit dioecy (i.e., unisexual individuals). In the dioecious Catasetum, male flowers forcibly attach a large pollinarium onto euglossine bees, and the bees subsequently avoid flowers with the same appearance <ns0:ref type='bibr' target='#b31'>(Romero &amp; Nelson, 1986)</ns0:ref>. Therefore, Catasetum populations are sexually dimorphic, and the agitated pollinators bearing their pollinia move away from the male flowers to the morphologically different female flowers <ns0:ref type='bibr' target='#b31'>(Romero &amp; Nelson, 1986)</ns0:ref>. In addition, within Satyriinae, Satyrium ciliatum Lindl. has been reported to produce both hermaphroditic and PeerJ reviewing PDF | (2020:07:51078:2:1:NEW 26 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed female individuals (i.e., gynodioecy; <ns0:ref type='bibr' target='#b14'>Huang et al., 2009)</ns0:ref>. Female individuals of S. ciliatum can avoid pollen limitation for seed production and can be maintained in populations that experience high levels of pollen limitation, because females, via facultative parthenogenesis, can produce more seeds than do hermaphrodites <ns0:ref type='bibr' target='#b14'>(Huang et al., 2009)</ns0:ref>. These observations helped elucidate the unusual maintenance of gender dimorphism in orchids <ns0:ref type='bibr' target='#b28'>(Pannell, 2009)</ns0:ref>.</ns0:p><ns0:p>Here, I report an additional orchidaceous example whose flowers are not always hermaphroditic. In a Japanese population of Eulophia zollingeri (Rchb.f.) J.J.Sm, a widespread Asian and Oceanian orchid, some flowers possess both the anther (i.e., anther cap and pollinaria) and stigma, whereas others possess only the stigma (Fig. <ns0:ref type='figure'>1</ns0:ref>). It is unlikely that the absence of anther cap and pollinaria is the result of removal by floral visitors, because careful dissection revealed that they were already absent before anthesis. Such a sexual system, in which plants have both female and hermaphroditic flowers co-occurring within the same plants, is called gynomonoecy. Compared with andromonoecy (male and hermaphroditic flowers within one plant) and monoecy (separate male and female flowers on the same plant), gynomonoecy remains a poorly studied sexual system, even though it occurs in 2.8-4.7% of flowering plants in at least 15 plant families <ns0:ref type='bibr' target='#b23'>(Lu &amp; Huang, 2006;</ns0:ref><ns0:ref type='bibr' target='#b46'>Yampolsky &amp; Yampolsky, 1922)</ns0:ref>.</ns0:p><ns0:p>In fact, while several hypotheses have been proposed, the adaptive significance of gynomonoecy remains largely unknown. First, the presence of the two flower types may permit flexible allocation of resources to female and male reproductive functions in response to environmental conditions <ns0:ref type='bibr' target='#b6'>(Charnov &amp; Bull, 1977;</ns0:ref><ns0:ref type='bibr' target='#b22'>Lloyd, 1979)</ns0:ref>. Second, female flowers may promote outcrossing more than hermaphroditic flowers <ns0:ref type='bibr' target='#b25'>(Marshall &amp; Abbott, 1984)</ns0:ref>. Third, due to the lack of evidence for the above two hypotheses, it has been proposed that female flowers may boost attractiveness to pollinators <ns0:ref type='bibr' target='#b2'>(Bertin &amp; Kerwin, 1998)</ns0:ref>. Finally, female flowers may be favored because hermaphroditic flowers, which are more attractive in gynomonoecious plants, are more susceptible to florivory <ns0:ref type='bibr' target='#b1'>(Bertin, Connors &amp; Kleinman, 2010;</ns0:ref><ns0:ref type='bibr' target='#b47'>Zhang, Xie &amp; Du, 2012)</ns0:ref>.</ns0:p><ns0:p>Meanwhile, current understanding of the adaptive advantages of gynomonoecy is largely limited to the Asteraceae and to a few species that have been investigated in other families <ns0:ref type='bibr' target='#b9'>(Davis &amp; Delph, 2005;</ns0:ref><ns0:ref type='bibr' target='#b24'>Mamut et al., 2014)</ns0:ref>. Manuscript to be reviewed morphs within one individual. Autonomous self-pollination has been suggested to be favorable for mycoheterotrophic plants, as they are restricted to dark shaded forest understorey with a paucity of pollinators <ns0:ref type='bibr' target='#b21'>(Leake, 1994;</ns0:ref><ns0:ref type='bibr' target='#b50'>Zhou et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b36'>Suetsugu, 2013a</ns0:ref><ns0:ref type='bibr' target='#b38'>Suetsugu, , 2015))</ns0:ref>. However, the Red Queen hypothesis suggests that sexual reproduction is important in a coevolutionary arms race between a parasite and host <ns0:ref type='bibr' target='#b20'>(Ladle, 1992)</ns0:ref>, such as between mycoheterotrophic plants and fungal hosts. Intriguingly, <ns0:ref type='bibr' target='#b48'>Zhang et al. (2014)</ns0:ref> revealed Chinese populations of E. zollingeri to be hermaphroditic, non-rewarding, self-compatible, and dependent on the halictid bee Nomia viridicinctula Cockerell for pollination through food deception. Although those Chinese populations consequently experienced strong pollinator limitation, especially in forest understorey populations <ns0:ref type='bibr' target='#b48'>(Zhang et al., 2014)</ns0:ref>, my preliminary investigation revealed that Japanese populations consistently exhibit high fruit set even under the shaded forest understorey. Therefore, it is possible that the Japanese hermaphroditic flowers are capable of autonomous selfing, providing reproductive assurance, while female flowers enhance outcrossing However, it should also be noted that the 'female' E. zollingeri flowers can be sterile without not only the male but also the female reproductive function. In fact, in Catasetum species that produce male and female flowers, intermediate flowers, which are sterile, have also been found <ns0:ref type='bibr' target='#b29'>(Romero, 1992)</ns0:ref>. Therefore, I first investigated whether the 'female' flowers of E. zollingeri possess female reproductive functions. After that, I conducted additional pollination experiments, investigations of floral morphology, and observations of floral visitors to determine the potential for reproductive assurance provided by autonomous selfing in female flowers and outcrossing via pollinator visitation in both hermaphroditic and female flowers.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head><ns0:p>Eulophia zollingeri is a mycoheterotrophic orchid distributed from India and Southeast Asia to New Guinea and Australia <ns0:ref type='bibr' target='#b27'>(Ogura-Tsujita &amp; Yukawa, 2008;</ns0:ref><ns0:ref type='bibr' target='#b39'>Suetsugu &amp; Mita, 2019;</ns0:ref><ns0:ref type='bibr' target='#b40'>Suetsugu, Matsubayashi &amp; Tayasu, 2020)</ns0:ref>. The behavior of floral visitors in Miyazaki City, Miyazaki Prefecture, Japan, was monitored during the peak flowering period (early to mid-July), in 2016 and 2017. Direct observations were made for ca. 30 h in total, during the peak of diurnal insect activity (09:00-17:00). The behavior of potential visitors was observed by walking around the study site, sitting next to flower patches, or hiding in the vegetation near flower clusters (within 1-2 m). In addition, artificial cross-pollination was performed in the same population in July 2016, <ns0:ref type='table' target='#tab_0'>PeerJ reviewing PDF | (2020:07:51078:2:1:NEW 26 Sep 2020)</ns0:ref> Manuscript to be reviewed Three to four months after manual pollination, all the mature but non-dehisced fruits capsules were collected. After the fruits were silica-dried, I weighed the total mass of dry seeds freed from each capsule to the nearest 0.1 mg. All the seeds from each plant were then mixed, and 100 randomly selected seeds from each plant were examined under a dissecting microscope to determine presence of an embryo. The effects of pollination treatment on fruit set were tested using Fisher's exact test. In addition, after confirming that the datasets were normally distributed using Levene's test, the effects of pollination treatment on the seed mass, and the proportion of seeds with an embryo were tested using ANOVA, followed by Fisher's multiple comparisons test.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:07:51078:2:1:NEW 26 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Despite conducting ca. 30 h of field observations, few insects were observed visiting the E. zollingeri flowers. Several dipteran visitors, such as the agromyzid fly Japanagromyza tokunagai, occasionally landed on the flowers. However, none of these visitors were observed to remove or deposit pollinaria. The length of the dorsal sepal, lateral sepal, lateral petal, and lip were not significantly different between female and hermaphroditic flowers (Table <ns0:ref type='table'>1</ns0:ref>). In addition, there are marginally significant differences in the number of female flowers between the distal half (1.2 &#177; 1.1; mean &#177; SD) and the proximal half (3.3 &#177; 3.4; P = 0.06) of the inflorescence.</ns0:p><ns0:p>More than half (6/10) of the female flowers subsequently developed fruit capsules that contained seeds with an embryo through artificial cross-pollination in 2016, thereby demonstrating their female function and confirming the gynomonoecy of the species. The results are stable at least in the investigated site, because similar results were obtained in 2017 (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>).</ns0:p><ns0:p>The detailed pollination experiments showed that the bagged female flowers failed to develop fruits autonomously, excluding the possibility of agamospermy, while comparable fruit set ratio was also obtained in open, bagged, manual geitonogamous and allogamous hermaphroditic flowers. Therefore, the hermaphroditic flowers are capable of outbreeding, but self-compatible and not pollinator-limited for fruit set under natural condition (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>). The seed mass did not vary significantly with pollination treatment (ANOVA F 6, 37 = 1.17, P = 0.34), while the proportion of seeds with an embryo differed significantly among pollination treatment (ANOVA F 6, 37 = 2.43, P = 0.04). In general, the pollination experiments indicated that outcrossing tended to increase both seed mass and the number of seeds with embryo, suggesting a negative impact of self-pollination, although the differences were not always significant (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>).</ns0:p><ns0:p>The observation of floral morphology confirmed that most of the hermaphroditic flowers possessed an effective self-pollination system, in which the rostellum was poorly developed, allowing contact between the stigma and pollinaria (Fig. <ns0:ref type='figure' target='#fig_8'>2B</ns0:ref>), whereas the others had functional rostella and were therefore unlikely to be autogamous (Fig. <ns0:ref type='figure' target='#fig_8'>2D</ns0:ref>). The female flowers had a column with neither a rostellum nor anther cap and pollinaria (Fig. <ns0:ref type='figure' target='#fig_8'>2F</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Most orchid species exhibit an extreme case of hermaphroditism, owing to the fusion of male and female organs into a gynostemium. Here I showed that a Japanese population of Eulophia Manuscript to be reviewed zollingeri develops both female and hermaphroditic flowers co-occurring within the same inflorescence (i.e., gynomonoecy), while Catasetum and Cycnoches typically produces unisexual individuals (i.e., dioecy, <ns0:ref type='bibr' target='#b31'>Romero &amp; Nelson, 1986)</ns0:ref>, and Satyrium ciliatum produces both hermaphroditic and female individuals (i.e., gynodioecy; <ns0:ref type='bibr' target='#b14'>Huang et al., 2009)</ns0:ref>. Therefore, the present study represents the first example of gynomonoecy within the Orchidaceae. However, it should be noted that gynomonoecy must not be considered a universal strategy within the species as a whole, since it was not reported in the Chinese study <ns0:ref type='bibr' target='#b48'>(Zhang et al. 2014)</ns0:ref>. In this sense, it differs from the fixed systems in Catasetum, Cycnoches, and Satyrium. The hermaphroditic flowers of a Japanese E. zollingeri population often possess an effective self-pollination system, while the female flowers without agamospermy can improve the probability of outcrossing (but selfing may still occur via geitonogamous pollinations). While female flowers are generally smaller than hermaphroditic flowers in other gynomonoecious species (reviewed by <ns0:ref type='bibr' target='#b24'>Mamut et al., 2014)</ns0:ref>, the size of floral parts did not differ significantly between female and hermaphroditic flowers of E. zollingeri. In addition, female flowers tend to be on the lower part of the inflorescence, suggesting that production of female flowers is not a result of resource competition. In summary, the system observed in E. zollingeri is consistent with the outcrossingbenefit hypothesis for gynomonoecy <ns0:ref type='bibr' target='#b24'>(Mamut et al., 2014)</ns0:ref>.</ns0:p><ns0:p>Many models predict that plants evolve toward either complete self-fertilization or complete outcrossing <ns0:ref type='bibr' target='#b5'>(Charlesworth &amp; Charlesworth, 1990</ns0:ref>). However, it seems that mixedmating systems are more common in nature <ns0:ref type='bibr' target='#b44'>(Vogler &amp; Kalisz, 2001;</ns0:ref><ns0:ref type='bibr' target='#b45'>Whitehead et al., 2018)</ns0:ref>, possibly because mixed mating can reduce the probability of inbreeding depression via outcrossing, while still providing reproductive assurance via selfing <ns0:ref type='bibr' target='#b11'>(Goodwillie &amp; Weber, 2018)</ns0:ref>. As such, mixed mating systems are often referred to as 'best-of-both-worlds' mating systems <ns0:ref type='bibr' target='#b9'>(Davis &amp; Delph, 2005;</ns0:ref><ns0:ref type='bibr' target='#b11'>Goodwillie &amp; Weber, 2018)</ns0:ref>. Mixed mating can be accomplished by delayed selfing, occurring after all other opportunities for outcrossing have been missed, because it provides reproductive assurance without limiting outcrossing opportunities. In addition, mixed mating can also occur in species that produce two flower types within the same plant. Gynomonoecy is one of the systems involving two flower types that allows for mixed mating. Indeed, in the E. zollingeri populations investigated here, hermaphroditic flowers conferred reproductive assurance under pollinator-limited conditions, whereas female flowers, Manuscript to be reviewed despite their susceptibility to pollen limitation, can facilitate outcrossing, because of the lack of autonomous selfing (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>).</ns0:p><ns0:p>It is possible that geitonogamy reduces the possibility of outcrossing in female flowers. In E. zollingeri, though, the level of geitonogamy will be low, because only a few flowers on each plant are open at one time. In particular, the risk of geitonogamy is probably negligible in nectarless E. zollingeri, given that pollinators are likely to quickly leave inflorescences in fooddeceptive plants <ns0:ref type='bibr' target='#b48'>(Zhang et al., 2014</ns0:ref><ns0:ref type='bibr' target='#b49'>(Zhang et al., , 2019;;</ns0:ref><ns0:ref type='bibr' target='#b41'>Suetsugu et al., 2015)</ns0:ref>. Indeed, the avoidance of geitonogamy has been hypothesized as a driving force for the evolution of food deceptive pollination in plants <ns0:ref type='bibr' target='#b17'>(Johnson, Peter &amp; &#197;gren, 2004)</ns0:ref>. Moreover, it is noteworthy that female flowers tended to be on the lower part of the inflorescence, given that E. zollingeri were exclusively pollinated by the halictid bee Nomia viridicinctula in China <ns0:ref type='bibr' target='#b48'>(Zhang et al., 2014)</ns0:ref> and that bees usually visit bottom flowers first and move upwards within an inflorescence (e.g. <ns0:ref type='bibr' target='#b16'>Iwata et al., 2012)</ns0:ref>. In fact, several studies have shown that pollinator behaviors lead to directional pollen flow within inflorescences and influence floral sex allocation <ns0:ref type='bibr' target='#b4'>(Brunet &amp; Charlesworth, 1995)</ns0:ref>. The first flowers visited will receive more pollen grains from other plants, while the last flowers visited before pollinators leave the inflorescence tend to receive geitonogamous pollination but successfully export pollen grains to other plants <ns0:ref type='bibr' target='#b19'>(Kudo, Maeda &amp; Narita, 2001)</ns0:ref>.</ns0:p><ns0:p>Therefore, it has been predicted that female-biased allocation to lower flowers and male-biased allocation to those in upper positions occurs in bee-pollinated plants <ns0:ref type='bibr' target='#b19'>(Kudo, Maeda &amp; Narita, 2001)</ns0:ref>. The variations in floral sex allocation within E. zollingeri are consistent with the theory and are probably effective for lowering the risk of geitonogamy.</ns0:p><ns0:p>The advantages of outcrossing and, consequently, producing female flowers can be somewhat influenced by the degree of inbreeding depression and pollinator availability <ns0:ref type='bibr' target='#b35'>(Smithson, 2006)</ns0:ref>. In E. zollingeri, pollinator-mediated fruit set was arguably low, at least in the investigated population, given that (i) direct pollinator observation was unsuccessful and (ii) pollination experiments showed that natural pollination in female flowers was recorded only in one flower. Nonetheless, a small degree of outcrossing can result in a rapid decline in linkage disequilibrium across the genome and can be sufficient to overcome negative effects such as the accumulation of deleterious mutations and the slowdown in adaptation rate <ns0:ref type='bibr' target='#b8'>(Culley &amp; Klooster, 2007)</ns0:ref>. In addition, although the differences were not obvious <ns0:ref type='bibr' target='#b43'>(Tremblay et al. 2005)</ns0:ref> Manuscript to be reviewed seed mass and the proportion of seed with an embryo in E. zollingeri (Table <ns0:ref type='table' target='#tab_0'>2</ns0:ref>), probably providing some support for the negative effect of autonomous selfing. It should be noted that, while seed mass and presence of an embryo was measured as the indicator of inbreeding depression, it can even under-estimate the level of inbreeding depression. Inbreeding depression might be more prominent during later stages such as seed germination or seedling growth <ns0:ref type='bibr' target='#b35'>(Smithson, 2006)</ns0:ref>. This possibility warrants further investigation.</ns0:p><ns0:p>The outcrossing opportunity might be particularly important in mycoheterotrophic plants exploiting their mycorrhizal partners <ns0:ref type='bibr' target='#b42'>(Suetsugu et al., 2017)</ns0:ref>, given that they usually occur in shaded understorey habitats with a paucity of pollinators, and that the Red Queen hypothesis argues that outcrossing is maintained by antagonistic interactions between a host and a parasite <ns0:ref type='bibr' target='#b20'>(Ladle, 1992;</ns0:ref><ns0:ref type='bibr' target='#b10'>Gibson &amp; Fuentes, 2015)</ns0:ref>. Because mycoheterotrophic plants occur mainly in pollinator-hostile shaded understorey habitats, they tend to experience strong pollinator limitation, unless they possess autonomous selfing ability <ns0:ref type='bibr' target='#b18'>(Klooster &amp; Culley, 2009;</ns0:ref><ns0:ref type='bibr' target='#b12'>Hentrich, Kaiser &amp; Gottsberger, 2010;</ns0:ref><ns0:ref type='bibr' target='#b36'>Suetsugu, 2013a</ns0:ref><ns0:ref type='bibr' target='#b38'>Suetsugu, , 2015))</ns0:ref>. In fact, the Chinese populations without autogamous ability exhibited a significant difference in fruit-set between forest edge and forest populations <ns0:ref type='bibr' target='#b48'>(Zhang et al., 2014)</ns0:ref>. Therefore, pollination limitation due to its mycoheterotrophic habit could be a driving force in the autonomous self-pollination in E. zollingeri. Consequently, most studies highlighted the importance of autonomous self-pollination in mycoheterotrophic plants <ns0:ref type='bibr' target='#b21'>(Leake, 1994;</ns0:ref><ns0:ref type='bibr' target='#b50'>Zhou et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b36'>Suetsugu, 2013a</ns0:ref><ns0:ref type='bibr' target='#b38'>Suetsugu, , 2015))</ns0:ref>. However, several recent studies have shown that mixed mating systems such as outcrossing pollinators with delayed self-pollination occur in mycoheterotrophic species belonging to Ericaceae and Gentianaceae, which evolved mycoheterotrophy independently from E. zollingeri <ns0:ref type='bibr' target='#b18'>(Klooster and Culley, 2009;</ns0:ref><ns0:ref type='bibr' target='#b12'>Hentrich et al., 2010)</ns0:ref>. The mixed mating systems, including gynomonoecy, might be more common and important in mycoheterotrophic plants than previously thought.</ns0:p><ns0:p>Overall, it can be concluded that the Japanese population of E. zollingeri studied here preserve reproductive assurance by producing autonomously selfing hermaphroditic flowers and still maintain the potential benefit of producing outcrossed offspring by developing female flowers. In addition, while I did not conduct the pollination experiments, several other Japanese populations such as Okinawa ones exhibit very similar floral morphology (Fig. <ns0:ref type='figure'>S1</ns0:ref>), suggesting that the strategy might be widespread at least in Japan. However, intriguingly, the Chinese populations appear to develop hermaphroditic flowers that are completely dependent on bee Manuscript to be reviewed pollinators <ns0:ref type='bibr' target='#b48'>(Zhang et al., 2014)</ns0:ref>. In fact, it is well-known that plant mating systems often vary widely among populations <ns0:ref type='bibr'>(Suetsugu, 2013b;</ns0:ref><ns0:ref type='bibr' target='#b45'>Whitehead et al., 2018)</ns0:ref>. Variations in mating systems between populations usually reflect the influence of ecological factors such as the availability and abundance of suitable pollinator <ns0:ref type='bibr'>(Suetsugu, 2013b;</ns0:ref><ns0:ref type='bibr' target='#b33'>Schouppe et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b45'>Whitehead et al., 2018)</ns0:ref>. Therefore, it is worth clarifying how common gynomonoecy with autonomous selfing hermaphroditic flowers and putatively outcrossing female flowers, is across the distribution range and whether the strategy is be more prevalent where its effective pollinator is less abundant.</ns0:p><ns0:p>It is also notable that current understanding of the adaptive advantages of gynomonoecy is largely limited to the Asteraceae <ns0:ref type='bibr' target='#b25'>(Marshall &amp; Abbott, 1984;</ns0:ref><ns0:ref type='bibr' target='#b2'>Bertin &amp; Kerwin, 1998;</ns0:ref><ns0:ref type='bibr' target='#b1'>Bertin, Connors &amp; Kleinman, 2010;</ns0:ref><ns0:ref type='bibr' target='#b47'>Zhang, Xie &amp; Du, 2012)</ns0:ref>. The outcrossing hypothesis of gynomonoecy has been questioned in many asteraceous taxa, given that most Asteraceae species are self-incompatible <ns0:ref type='bibr' target='#b2'>(Bertin &amp; Kerwin, 1998)</ns0:ref>. However, it has been shown that hermaphroditic flowers promote seed quantity in that they are more attractive to pollinators and/or are capable of autonomous selfing, while female flowers compensate for loss of male function through outcrossing in non-asteraceous taxa [i.e., Silene noctiflora (Caryophyllaceae) and Eremurus anisopterus (Xanthorrhoeaceae)] ( <ns0:ref type='bibr' target='#b9'>Davis &amp; Delph, 2005;</ns0:ref><ns0:ref type='bibr' target='#b24'>Mamut et al., 2014)</ns0:ref>. Taken together with these recent finding, I suggest that the ability of female flowers to reduce geitonogamy and enhance outcrossing may be widespread in gynomonoecious plants. However, it should be noted that although many orchids are (at least partially) parasitic on their mycorrhizal fungi and exhibit strong pollinator-limitation <ns0:ref type='bibr' target='#b21'>(Leake, 1994)</ns0:ref>, gynomonoecy is not prevalent within the orchid family as a whole. Given that (i) hypotheses regarding the adaptive significance of gynomonoecy are not mutually exclusive and (ii) the seed-feeding fly Japanagromyza tokunagai have probably substantial negative impact on the reproduction of E. zollingeri <ns0:ref type='bibr' target='#b39'>(Suetsugu &amp; Mita, 2019)</ns0:ref>, benefits other than outcrossing, such as herbivory reduction, could also have contributed to the evolution of gynomonoecy. Therefore, further investigation is needed to elucidate the potentially diverse adaptive significance, disadvantages, and developmental constraints of gynomonoecy. Different superscript letters indicate significant differences (P &lt; 0.05) between treatment groups. Both seed mass and seeds with an embryo are expressed by mean &#177; SD, whenever the sample size is more than &gt; 1.</ns0:p><ns0:p>1</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Therefore, I investigated the reproductive biology of a Japanese E. zollingeri population, which potentially represents the first documentation of gynomonoecy within Orchidaceae, to understand the ecological significance of the different reproductive strategies of the two floral PeerJ reviewing PDF | (2020:07:51078:2:1:NEW 26 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>by transferring pollinaria from different individuals to the stigmas of female flowers (five inflorescences, 10 flowers).After confirming with the cross-pollination experiment that both hermaphroditic and female flowers produce fruits, additional pollination experiments were conducted in early July 2017.Flowers were either (i) manually cross-pollinated by transferring pollinaria to the stigmas of different individuals (five inflorescences, 10 each of female and hermaphroditic flowers); (ii) manually geitonogamous-pollinated by transferring pollinaria to the stigmas of the different flowers within the same individuals for female flowers and of the same flowers for hermaphroditic flowers (five inflorescences, 10 each of female and hermaphroditic flowers); (iii) enclosed in mesh bags to exclude floral visitors and test for autonomous self-pollination (five inflorescences, 10 hermaphroditic flowers); or (iv) left unmanipulated, in order to monitor fruit set under natural conditions (seven inflorescences, 19 female flowers and 21 hermaphroditic flowers). In addition, the relative position of female and hermaphroditic flowers on the racemes was determined in 12 inflorescences. Furthermore, to compare flower size between female and hermaphroditic flowers in gynomonoecious individuals, we measured the length of the dorsal sepal, lateral sepal, lateral petal, and lip of 10 plants using digital calipers to 0.1 mm in early July 2017. Finally, the distribution of female flowers was checked in 12 inflorescences in early July 2017. After dividing each inflorescence into distal and proximal halves, the data were tested using the Mann-Whitney U-test to investigate whether female flowers tended to be in the distal or basal part of the inflorescence.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51078:2:1:NEW 26 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51078:2:1:NEW 26 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>, both artificial allogamous pollination and natural pollination in a female flower tended to increase PeerJ reviewing PDF | (2020:07:51078:2:1:NEW 26 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:07:51078:2:1:NEW 26 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure legends Figure 1</ns0:head><ns0:label>legends1</ns0:label><ns0:figDesc>Figure legends</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2 Column morphology of Eulophia zollingeri flowers. (A, B) Column with a degenerate rostellum, which facilitates autogamy. (C, D) Column with a well-developed rostellum, which prevents autogamy. (E, F) Column with neither a rostellum nor anther cap and pollinaria. AC, anther cap; RS, rostellum; PO, pollinaria; ST, stigma.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Effect of pollination treatment on fruit set, seed mass, and proportion of seeds with an embryo in Eulophia zollingeri.</ns0:figDesc><ns0:table><ns0:row><ns0:cell>Flower type</ns0:cell><ns0:cell>Treatment</ns0:cell><ns0:cell>Manual allogamy</ns0:cell><ns0:cell>Manual geitonogamy</ns0:cell><ns0:cell>Autonomous autogamy</ns0:cell><ns0:cell>Open</ns0:cell></ns0:row><ns0:row><ns0:cell>Hermaphroditic</ns0:cell><ns0:cell>Fruit set (%)</ns0:cell><ns0:cell>70.0 a</ns0:cell><ns0:cell>70.0 a</ns0:cell><ns0:cell>50.0 a</ns0:cell><ns0:cell>57.1 a</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Seed mass</ns0:cell><ns0:cell>31.6 &#177; 11.6</ns0:cell><ns0:cell>24.1 &#177; 11.4</ns0:cell><ns0:cell>20.8 &#177; 9.3</ns0:cell><ns0:cell>24.9 &#177; 8.6</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Seeds with embryo</ns0:cell><ns0:cell>82.4 &#177; 4.2 ac</ns0:cell><ns0:cell>79.0 &#177; 4.2 abc</ns0:cell><ns0:cell>77.2 &#177; 2.9 bc</ns0:cell><ns0:cell>79.2 &#177; 3.6 c</ns0:cell></ns0:row><ns0:row><ns0:cell>Female</ns0:cell><ns0:cell>Fruit set (%)</ns0:cell><ns0:cell>60.0 a</ns0:cell><ns0:cell>60.0 a</ns0:cell><ns0:cell>0.0</ns0:cell><ns0:cell>5.3 b</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Seed mass</ns0:cell><ns0:cell>30.2 &#177; 14.7</ns0:cell><ns0:cell>25.7 &#177; 11.0</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>44.9</ns0:cell></ns0:row><ns0:row><ns0:cell /><ns0:cell>Seeds with embryo</ns0:cell><ns0:cell>83.3 &#177; 4.4 a</ns0:cell><ns0:cell>77.3 &#177; 2.9 bc</ns0:cell><ns0:cell>-</ns0:cell><ns0:cell>82.0 abc</ns0:cell></ns0:row></ns0:table></ns0:figure> </ns0:body> "

"Department of Biology, Graduate School of Science, Kobe University 1-1 Rokkodai, Nada-ku, Kobe, 657-8501, Japan Dear Dr. David Roberts, Editor, PeerJ Thank you for your positive comments on our submission entitled 'Gynomonoecy in a mycoheterotrophic orchid Eulophia zollingeri with autonomous selfing hermaphroditic flowers and putatively outcrossing female flowers'. I am grateful to an anonymous reviewer for the insights and constructive comments on the earlier version of our manuscript. These comments have been helpful in improving our manuscript. Please find below my detailed responses to the reviewers’ comments. I feel these revisions have strengthened the resulting paper. I hope that the revised version addresses all of the concerns raised. I would, of course, be willing to make additional revisions to make the manuscript acceptable for publication. Sincerely yours, Kenji Suetsugu Kenji Suetsugu (Ph.D.) Associate Professor Contact Address: Department of Biology, Graduate School of Science, Kobe University, 1-1 Rokkodai, Nada-ku, Kobe, 657-8501, Japan Email: [email protected] Tel: +81-78-803-5713 HP: https://sites.google.com/site/suetsuguen/ I am grateful to an anonymous reviewer for the insights and constructive comments on the earlier version of our manuscript. These comments have been helpful in improving our manuscript. The reviewer noticed several typographical errors and suggested the rewording of some sentences, all of which I have amended in the revised document. Below, I have provided the details of the other changes made. The responses (in regular font) are given directly below the reviewers’ comments (in italic font). The changes made in the revised manuscript are highlighted by colored text. Replies to Dr. David Roberts, Editor Many thanks for taking on many of the reviewers' comments in the revision. Like the reviewer suggest you need to be clear that you are reporting on study populations in Japan and that the results may not be the case for the species elsewhere (e.g. Zhang et al. 2014). -The manuscript has carefully been rechecked and the necessary changes have been made in accordance with the suggestions. In particular, I have carefully revised the manuscript to make the reader understand what occurs in a Japanese Eulophia zollingeri population may not reflect the situation in other parts. Replies to Reviewer 3 I appreciate your positive comments and constructive criticism. I also sincerely appreciate your helpful comments, which have enabled me to significantly improve the manuscript. I feel the author should underscore the fact that what he reports for his study populations of E. zollingeri in Japan may not (in fact appears not to) be the case for the species elsewhere in its range, as evidenced by the findings of Zhang et al. (2014). -Thank you for the important suggestion. I have clearly noted that the results may not be the case in other locations. The title is a bit of a mouthful. Can it be simplified? -It is difficult to simplify the title incorporating all the results. Therefore, I did not change the title. Lines 19–20: Eulophia zollingeri is actually very widespread in Asia and Australasia, not purely a Japanese species as this line suggests. This is an important point, because the reader should be informed that the data presented here concern only a tiny fraction of the global population, and what occurs in these few Japanese populations may not reflect the situation in other parts of the species’ range. -As suggested, I have changed the sentence to make the reader understand what occurs in the Japanese population may not reflect the situation in other parts. In addition, I have also carefully conducted the similar revision in the other parts including the parts you did not mention. Line 33: Although I neglected to mention this in my first review of this paper, I am reticent to consider this species “fully mycoheterotrophic” – as your photos in Fig. 1 show, many populations I’ve seen of this species in Asia have green stems which probably permit a degree of nutrient gain via photosynthesis, albeit probably rather limited. -Thank you for the useful opinion. While E. zollingeri is often categorized as fully mycoheterotrophic (e.g. Yagame et al. 2018), I have agreed with you that the green stems probably permit a degree of nutrient gain via photosynthesis. Since it is not a main topic whether E. zollingeri is fully or nearly fully mycoheterotrophic, I have simply deleted the term “fully” in the revised manuscript. Yagame, T., Funabiki, E., Yukawa, T., & Nagasawa, E. (2018). Identification of mycobionts in an achlorophyllous orchid, Cremastra aphylla (Orchidaceae), based on molecular analysis and basidioma morphology. Mycoscience, 59(1), 18-23. Lines 95–97: It is interesting to note that the Chinese study populations exhibited a significant difference in fruit-set between forest edge and forest populations (perhaps something to consider in your Discussion – e.g. were your study populations in deep forest or at the forest edge?). -As suggested, I have added the short discussion on this topic. Please see lines 258-260 in the revised manuscript. Line 182: I think it is important to underscore that what you report in these Japanese populations of E. zollingeri is clearly not a universal strategy within the species as a whole, since it was not reported in the Chinese study (Zhang et al. 2014). -I have clearly noted that gynomonoecy must not be a universal strategy within E. zollingeri, as suggested. Lines 279–281: I would also add that it would be interesting to clarify how common this strategy is in different E. zollingeri populations across its range – could it be more prevalent where its effective pollinator is less abundant or absent? -Thank you for the important suggestion. I have agreed with you that my results should be carefully interpreted, given that the investigated population is near the northern limit of E. zollingeri distribution, and mating system in plants often vary greatly among locations. Since I have also considered that the geographic mosaic warrants further investigation, I have added the discussion on this topic, as suggested. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Effects of substrate and water depth on the physiological status of a submerged macrophyte, Vallisneria natans (Lour.) H.Hara, were determined by measuring biomarkers in leaves and roots, to understand factors limiting the re-establishment of V. natans in urban eutrophic ponds. Ramets of V. natans were grown in the laboratory using aquaria containing water and bottom mud from a eutrophic pond and maintained under sufficient light in an incubator. The growth and chlorophyll-a (Chl-a) content of leaves were greater in aquaria with mud than in those with sand, which was used as the reference substrate.</ns0:p><ns0:p>The contents of a peroxidation product [malondialdehyde (MDA)] and three antioxidant enzymes [superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD)] in leaves and roots, used as stress biomarkers, changed during the experiment, although differences in these contents between mud and sand were not consistent across the experimental days. To control water depth in the field, ramets of V. natans were grown in cages with different substrates (mud and sand) installed at different depths (0.5, 1.2, and 2.0 m) in the pond. The mean light quantum during the experiment decreased with increasing depth, from 79.3 &#956;mol/m 2 s at 0.5 m to 7.9 &#956;mol/m 2 s at 2.0 m. The Chl-a content in leaves decreased, whereas the MDA content in both leaves and roots increased with increasing water depth. All enzyme activities increased at the beginning and then decreased to the end of the experiment at 2.0 m depth, suggesting deterioration of enzyme activities due to depth-related stress. The MDA content and CAT activity were higher for sand than for mud, whereas the difference in the growth and the leaf Chl-a content between substrates remained unclear in the pond. On comparing the laboratory and field experiments, the leaf Chl-a content was found to be lower and the MDA content and enzyme activities exhibited sharp increase for ramets grown in the pond, even at 0.5 m depth, when compared with those grown in the aquaria. Our results suggest that the bottom mud of the pond is not the major limiting factor in the re-establishment of V.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Urban ponds often suffer from eutrophication <ns0:ref type='bibr' target='#b13'>(Harper 1992</ns0:ref><ns0:ref type='bibr' target='#b10'>, Grimm et al. 2008</ns0:ref><ns0:ref type='bibr' target='#b29'>, Smith and Schindler 2009)</ns0:ref>. In closed aquatic ecosystems with less renewal of water, excessive nutrient input immediately leads to the overgrowth of phytoplankton. Oxygen depletion is particularly severe at the bottom of such aquatic ecosystems because of respiration by overabundant phytoplankton, decomposition of accumulated organic matter, and limited benthic photosynthesis due to reduced light transparency. Such hypoxic conditions result in the exclusion of animals, such as fish and other aerobic organisms, from the bottom. Submerged plants are often used to improve the ecological status of eutrophic aquatic environments because of their ability to absorb nutrients <ns0:ref type='bibr' target='#b25'>(Qiu et al. 2001</ns0:ref><ns0:ref type='bibr' target='#b15'>, Hilt et al. 2006</ns0:ref><ns0:ref type='bibr' target='#b27'>, Sayer et al. 2010)</ns0:ref>. Vallisneria natans (Lour.) H.Hara is a submerged rooted plant, which is widely distributed in freshwater habitats across the Asia and Australia <ns0:ref type='bibr' target='#b22'>(Lowden 1982)</ns0:ref>. Owing to its adaptability to a wide range of temperatures and substrates <ns0:ref type='bibr' target='#b41'>(Xiong and Li 2000</ns0:ref><ns0:ref type='bibr' target='#b38'>, Xie et al. 2005</ns0:ref><ns0:ref type='bibr' target='#b17'>, Ke and Li 2006)</ns0:ref>, ability to absorb significant amounts of nutrients <ns0:ref type='bibr' target='#b33'>(Wang et al. 2017</ns0:ref><ns0:ref type='bibr' target='#b39'>, Xing et al. 2018)</ns0:ref>, and allelopathic effects on phytoplankton <ns0:ref type='bibr' target='#b36'>(Xian et al. 2006</ns0:ref>), V. natans has been used to restore many urban ponds <ns0:ref type='bibr' target='#b44'>(Yan et al. 1997</ns0:ref><ns0:ref type='bibr' target='#b25'>, Qiu et al., 2001)</ns0:ref>.</ns0:p><ns0:p>Despite their potential to improve degraded aquatic ecosystems, submerged plants, including V. natans, have been declining in many freshwater bodies due to habitat degradation <ns0:ref type='bibr' target='#b15'>(Hilt et al. 2006</ns0:ref><ns0:ref type='bibr' target='#b6'>, Cao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b24'>, Qin et al. 2013)</ns0:ref>. Restoration works in urban ponds often fail to re-establish stands of submerged plants because of the low survival rate of transplants. High concentrations of nutrients, such as NH 4 + , inhibit and impairs the growth of V. natans <ns0:ref type='bibr' target='#b6'>(Cao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b32'>, Wang et al. 2008)</ns0:ref>. Light availability, which is regulated by water depth and transparency, is the principal factor restricting the growth of V. natans in eutrophic aquatic environments <ns0:ref type='bibr' target='#b37'>(Xiao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b2'>, Bai et al. 2015)</ns0:ref>. Substrate quality in terms of texture and chemistry has also been shown to affect V. natans <ns0:ref type='bibr' target='#b38'>(Xie et al. 2005</ns0:ref><ns0:ref type='bibr' target='#b21'>, Li et al. 2012</ns0:ref><ns0:ref type='bibr' target='#b2'>, Bai et al. 2015)</ns0:ref>. In addition, organicrich mud under anaerobic conditions, which is typical at the bottom of eutrophic ponds, can inhibit the survival of submerged plants <ns0:ref type='bibr' target='#b3'>(Barko and Smart 1986</ns0:ref><ns0:ref type='bibr' target='#b35'>, Wu et al. 2009</ns0:ref><ns0:ref type='bibr'>, Silveila and Thomaz 2015)</ns0:ref>. Physical disturbances, such as waves and currents in lakes and large water habitats <ns0:ref type='bibr' target='#b23'>(Madsen et al. 2001</ns0:ref><ns0:ref type='bibr' target='#b8'>, Ellawala et al. 2013</ns0:ref><ns0:ref type='bibr' target='#b43'>, Xu et al. 2016)</ns0:ref>, can also be a key on the survival of submerged plants. Elucidating the factors limiting the survival of submerged plants is required for effective restoration of urban ponds.</ns0:p><ns0:p>Plants under stress exhibit physiological changes in their cells and organs. Chlorophyll (Chl) is a pigment that absorbs solar energy and accelerates photosynthesis, and its content in leaf tissues is often used as an indicator of photosynthetic ability and plant health. Chl-a absorbs light in the blue and red regions and is the primary photosynthetic pigment, whereas Chl-b absorbs light in slightly different regions and is an accessory pigment supporting Chl-a. Stressful conditions increase the accumulation of reactive oxygen species (ROS), such as superoxide radicals (O 2 -), hydroxyl radicals (OH -), and hydrogen peroxide (H 2 O 2 ), which can damage cell organelles. Products of lipid peroxidation induced by ROS, such as malondialdehyde (MDA), are also harmful to cell organelles. ROS accumulation can be controlled by antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD). Although the activities of such enzymes increase with ROS, excessive accumulation of ROS and oxidative compounds in cells can reduce their activities, ultimately leading to apoptosis. These peroxidation products and enzyme activities have been used as indicators of stress caused by toxic chemicals or low nutrient availability in V. natans <ns0:ref type='bibr' target='#b32'>(Wang et al. 2008</ns0:ref><ns0:ref type='bibr' target='#b12'>, Hao et al. 2011</ns0:ref><ns0:ref type='bibr'>, Wang et al. 2012</ns0:ref><ns0:ref type='bibr' target='#b30'>, Song et al. 2015)</ns0:ref>.</ns0:p><ns0:p>To promote ecosystem restoration of urban ponds by introducing V. natans, we examined the water quality of an urban pond in Wenzhou City, China, and the effects of water, bottom mud, and pond depth on the physiological status of V. natans by in vitro and in situ experiments. We measured the Chl-a and Chl-b contents of leaves as indicators of plant health and of MDA, SOD, CAT, and POD in leaves and roots as indicators of stress.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Study site</ns0:head><ns0:p>The study was conducted at Zhong Shan Park, approximately 1 km south of the Ou River, central Wenzhou City, China (Fig. <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). The study pond was approximately 300 m long in the north-south direction, 20 m wide in the east-west direction, and 2 m deep. Field surveys and experiments were approved by the Wenzhou Science and Technology Bureau (Water Pollution Control and Treatment Technology Innovation Project under Wenzhou Science and Technology Plan Project: W20170002).</ns0:p><ns0:p>The pond has been restored repeatedly using V. natans, which was originally abundant in this area, since 2011. Although the water quality improved after planting V. natans, aquatic plants, including V. natans, died and disappeared after a few years. Subsequently, an aeration device was installed at the bottom of the pond. Despite an improvement in dissolved oxygen (DO), the introduction of V. natans failed again in recent years. The bottom mud, which was organic-rich and anaerobic state, has been assumed as a cause of the failure because roots of the dead V. natans were dwarf and black-colored.</ns0:p><ns0:p>Our preliminary measurements of the pond water showed that the pH was 7.8-8.3, DO was 6-10 mg/L, water transparency was 0.2-0.3 m, turbidity was 40-80 nephelometric turbidity units (NTU), electric conductivity (EC) was 430-465 &#956;s/cm, total nitrogen (TN) and total phosphorus (TP) were 6.59-8.59 mg/L and 0.41-0.50 mg/L, respectively, and the Chl-a concentration was 30-65 &#956;g/L. The collected bottom mud was black and emitted anaerobic odors, exhibited a chemical oxygen demand (COD) of 4.56 mg, and contained 1.01 mg of TN and 0.18 mg of TP per unit dry weight g of mud. The aeration device was located at the southern part of the pond (Fig. <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>), where we surveyed the water quality and conducted the field experiment.</ns0:p></ns0:div> <ns0:div><ns0:head>Laboratory experiment</ns0:head><ns0:p>The responses of V. natans to the mud and water of the pond were examined in the laboratory. The mud and water were collected from the pond a few days before the experiment. We used quartz sand (SiO 2 : &gt;95%, particle size: 1-2 mm), free of organic matter and nutrients (hereafter we called sand), as the control substrate. Intact and fresh ramets of V. natans collected from a rural wetland were used. Five ramets were planted in a 500-mL beaker with a 5-cm layer of the substrate (either mud or sand) at the bottom. Three beakers with ramets were placed in an aquarium (30&#215;30&#215;50 cm 3 , 45 L) containing 30 L of pond water such that the entire propagule was submerged. Three aquaria containing a total of nine beakers and 45 ramets were used for each substrate type.</ns0:p><ns0:p>The aquaria were placed in an incubator maintained at a constant temperature of 25&#176;C, under a light intensity of 5000 lux, and light:dark photoperiod of 12 h:12 h for 50 d. For physiological measurements, leaves and roots were sampled from a ramet in each aquarium (i.e., n = 3 for each substrate) every 10 d, and then frozen and preserved at -20&#176;C. A previously unsampled ramet was collected from each aquarium at the end of the experiment for measuring leaf length and number (n = 3 for each substrate). Water quality parameters, including temperature, pH, and DO, were measured using a multiparameter water quality meter (Hydrolab DS5X, OTT Hydromet GmbH, Kempten, Germany), and water was sampled for N and P analyses from each aquarium (n = 3 for each substrate) at the end of the experiment.</ns0:p></ns0:div> <ns0:div><ns0:head>Field experiment</ns0:head><ns0:p>The responses of V. natans to different water depths (0.5, 1.2, and 2.0 m) were surveyed in the southern part of the pond. The mud of the pond and river coarse sand (particle size: 1-2 mm), which was washed to remove organic matter, were used as substrates. The ramets of V. natans were planted uniformly in a mesh plastic cage (40.0&#215;48.5&#215;67.5 cm 3 ) containing three rectangular trays (10&#215;25&#215;38 cm 3 ) with a 7-cm layer of the substrate (either mud or sand) (Fig. <ns0:ref type='figure'>2</ns0:ref>). A tiered structure was constructed in the pond using steel pipes, and three cages for each substrate type were placed at three different depths (0.5, 1.2, and 2.0 m; Fig. <ns0:ref type='figure'>2</ns0:ref>).</ns0:p><ns0:p>The experiment commenced on May 11, 2019. The water quality of the pond was evaluated and the ramets of V. natans were sampled on 5, 10, 20, and 30 d of the experiment. The vertical profile (0.1 m intervals) of water quality, including temperature, pH, and DO, was measured near the experimental site using the water quality meter. In addition, water samples (500 mL) were taken from each experimental depth (0.5, 1.2, and 2.0 m) for N and P analyses. The light quantum at each experimental depth was monitored continuously by installing a pocket-size photosynthetically-active radiation logger (DEFI2-L, JFE Advantech Co., Ltd., Nishinomiya, Japan). Water transparency was measured using a Secchi disk. For physiological measurements, leaves and roots were sampled from a ramet in each tray (i.e., n = 3 for each depth and substrate combination). A previously unsampled ramet was collected from each tray at the end of the experiment for measuring the leaf length and number (n = 3 for each depth and substrate combination).</ns0:p><ns0:p>Water chemistry and biochemical measurements Concentrations (mg/L) of N and P were determined according to the Surface Water Environment Quality Standard <ns0:ref type='bibr'>(GB 3838-2002</ns0:ref><ns0:ref type='bibr'>) (State Environmental Protection Administration 2002)</ns0:ref>. TN and TP were determined by ultraviolet spectrophotometry and the molybdenum blue method, respectively, after digestion of sampled water. Inorganic N (NH 4 + -N, NO 3 -N, NO 2 --N) was determined by Nessler's reagent spectrophotometry and ultraviolet spectrophotometry. The COD was determined using the potassium dichromate method.</ns0:p><ns0:p>Collected leaves and roots were cut, the surface water was removed using a paper, and the samples were then weighed to obtain the fresh weight. Approximately 2 g of samples were used for evaluating plant health and stress parameters. The Chl content was measured following <ns0:ref type='bibr' target='#b1'>Arnon (1949)</ns0:ref>. Leaf samples were ground and homogenized with 80% acetone, CaCO 3 , and quartz sand and then centrifuged at 12 000 &#215; g for 10 min. The supernatant was collected, and its absorbance was measured at 645 and 663 nm. The concentrations of Chl-a and Chl-b were calculated using the following equations: Chl-a = 12.7A 663 -2.69A 645 Chl-b = 22.9A 645 -4.68A 663 The concentrations were then converted to mg per unit g of leaf fresh weight.</ns0:p><ns0:p>The MDA content was measured following <ns0:ref type='bibr' target='#b14'>Heath and Packer (1968)</ns0:ref>. Leaf or root samples were ground and homogenized with 5% trichloroacetic acid and quartz sand and then centrifuged at 12 000 &#215; g at 4&#176;C for 10 min. Thiobarbituric acid (2%) was added to the resulting supernatant and the solution was then heated in boiling water for 15 min. After cooling to 20&#176;C, the solution was again centrifuged at 15 000 &#215; g for 10 min. The supernatant was collected and its absorbance was measured at 450, 532, and 600 nm. The concentration of MDA was calculated using the following equation: MDA = 6.45(A 532 -A 600 ) -0.56A 450 The concentrations were then converted to nmol per unit g of tissue fresh weight.</ns0:p><ns0:p>Prior to the measurement of enzyme activities (SOD, CAT, and POD), the leaf or root samples were ground and homogenized with 50 mM sodium phosphate buffer solution (pH 7.0) and quartz sand and centrifuged at 12 000 &#215; g at 4&#176;C for 20 min. The supernatant was collected immediately for enzyme activity measurements.</ns0:p><ns0:p>The SOD activity was assayed following <ns0:ref type='bibr' target='#b4'>Beauchamp and Fridovich (1971)</ns0:ref> and <ns0:ref type='bibr' target='#b20'>Li et al. (2002)</ns0:ref>. The reaction solution was prepared by adding 0.1 mL each of 8 mM hydroxylammonium chloride, 3.0 mM EDTA-2Na, 0.15% (w/v) bovine serum albumin (BSA), 8 mM xanthene, and the enzyme extract to 1 mL phosphate buffer (50 mM, pH 7.8). After adding 0.1 mL of xanthine oxidase, the reaction solution was heated for 40 min at 30&#176;C. One milliliter each of l mL of 20 mM sulfanilic acid and l0 mM N-(1-naphthyl)ethylenediamine dihydrochloride were added to the resulting solution, which was then incubated at 25&#176;C for 20 min, and the absorbance was measured at 545 nm. One unit of SOD activity was defined as the amount of enzyme required for 50% inhibition of absorbance reduction.</ns0:p><ns0:p>The CAT activity was assayed following <ns0:ref type='bibr' target='#b9'>Greenfield and Price (1954)</ns0:ref>. The production of O 2 from a reaction solution containing 2 mL of 50 mM phosphate buffer (pH 7. 0), 1 mL of the enzyme extract, and 2 mL of 3% H 2 O 2 was measured by volumetry at normal pressure and 24&#176;C for 1 min. A unit of CAT activity was calculated by assuming 1 cm 3 of O 2 as equivalent to 0.041 mmol.</ns0:p><ns0:p>The POD activity was measured following <ns0:ref type='bibr' target='#b18'>Kochba et al. (1977)</ns0:ref>. A 3 mL of a mixture of 50 mM phosphate buffer (pH 7. 0) and 20 mM guaiacol was added to 0.5 mL of the enzyme extract to prepare the reaction solution. After adding 0.2 mL of 8 mM H 2 O 2 , the absorbance was measured at 470 nm for 1 min.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical tests</ns0:head><ns0:p>In the laboratory experiment, a split-plot analysis of variance (ANOVA) was performed for leaf Chl-a and Chl-b contents, with substrate (mud, sand) and experiment time <ns0:ref type='bibr'>(10, 20, 30, 40, 50 d)</ns0:ref> as fixed factors and aquarium (n = 3 for each substrate) as a random factor. The contents of MDA, SOD, CAT, and POD in leaves and roots were analyzed by adding sampled organ (leaf, root) as a fixed factor in the ANOVA. Welch's two-sample t-test was used to assess differences in the length and number of leaves between mud and sand collected at the end of the experiment (n = 3 for each substrate).</ns0:p><ns0:p>In the field experiment, a split-plot ANOVA was performed for leaf Chl-a and Chl-b contents with depth (0.5, 1.2, 2.0 m), substrate (mud, sand), and experiment time <ns0:ref type='bibr'>(5, 10, 20, 30 d)</ns0:ref> as fixed factors and tray (n = 3 for each depth and substrate combination) as a random factor. The contents of MDA, SOD, CAT, and POD were analyzed by adding sampled organ (leaf, root) as a fixed factor in the ANOVA. We focused mainly on the effects of substrate and depth, and their interaction with other factors to determine if the effects of substrate or depth varied according to other factors. A two-way ANOVA was done for the length and number of leaves with depth and substrate as fixed factors (n = 3 for each depth and substrate combination). Spatio-temporal variation in water quality was also analyzed as a background condition of the experiment. A two-way ANOVA with depth (0.5, 1.2, 2.0 m) and experiment time (5, 10, 20, 30 d) as factors and without replication was performed for variables measured by the water quality meter (temperature, pH, DO, oxidation-reduction potential: ORP, EC, turbidity, and Chl-a concentration), light quantum, nutrients (TN, TP, NH 4 + -N, NO 3 --N, and NO 2 --N), and COD of the water samples. For variables measured by the water quality meter, data of the nearest five depths were averaged for each depth (0.5, 1.2, 2.0 m) on each experimental day. For all tests, an &#945; value of 0.05 was used to determine the significance of effects. All statistical analyses were performed in R (version 3.6.3; R Development Core Team, Vienna, Austria), with 'lme4' and 'lmerTest' packages.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Laboratory experiment A temporal change was detected in the leaf Chl-a content (mg/g), and the effect of the experiment time was significant (Fig. <ns0:ref type='figure'>3</ns0:ref>, Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). The Chl-a content increased slightly from 0 to 10-20 d and then decreased. The decrease from 10-20 d to the end of the experiment was greater in aquaria with sand than mud, and the effects of substrate and time&#215;substrate interaction were significant. Consequently, the Chl-a content at 50 d was 19% increase from its 0 d for the mud, and it was 9% decrease from its 0 d for the sand.</ns0:p><ns0:p>Temporal change in the Chl-b content were relatively small when compared to those in the Chl-a content. However, some patterns were similar to those observed for the Chl-a content, such as significantly higher for mud than for sand, and a significant effect of time&#215;substrate interaction (Fig. <ns0:ref type='figure'>3</ns0:ref>, Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>).</ns0:p><ns0:p>The MDA content (nmol/g) of both leaves and roots increased at the beginning of the experiment and then decreased, and it was significantly higher in leaves than in roots (Fig. <ns0:ref type='figure'>4</ns0:ref>, Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). The MDA content decreased visibly after 30 d for leaves, while it decreased steadily after 10 d for roots, and the effect of time&#215;organ interaction was significant. The MDA content of leaves was higher in aquaria with mud than sand, whereas an opposite pattern was observed for roots, and the effect of organ&#215;substrate interaction was significant. The decline in MDA content from 30 to 50 d was steeper for mud than for sand. Consequently, the MDA content at 50 d was 17% (leaves) or 5% (roots) decrease from its 0 d for the mud, and it was 8% (leaves) or 52% (roots) increase from its 0 d for the sand.</ns0:p><ns0:p>The SOD activity (unit/g) increased after 10 d in leaves, whereas it changed less throughout the experiment in roots, and the effect of time&#215;organ interaction was significant (Fig. <ns0:ref type='figure'>4</ns0:ref>, Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). As a consequence, the SOD activity in leaves exceeded that in roots from 20 d onwards. The SOD activity in leaves changed less after 30 d. No significant difference was detected in the SOD activity between the two substrates.</ns0:p><ns0:p>The CAT activity (H 2 O 2 nmol/g/min) of both leaves and roots increased at the beginning of the experiment and then gradually decreased, and the effect of time was significant (Fig. <ns0:ref type='figure'>4</ns0:ref>, Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). The CAT activity was significantly higher in leaves than in roots throughout the experiment. No significant difference was detected in the CAT activity between the two substrates. The CAT activity at 50 d was 27-54% increase from its 0 d in leaves, and it was 5-10% decrease from its 0 d in roots.</ns0:p><ns0:p>The POD activity (A 470 /g/min) of both leaves and roots increased at the beginning of the experiment and then gradually decreased, and the effect of time was significant (Fig. <ns0:ref type='figure'>4</ns0:ref>, Table <ns0:ref type='table' target='#tab_0'>1</ns0:ref>). The POD activity was significantly higher in roots than in leaves throughout the experiment. The POD activity in roots was higher for sand than for mud throughout the experiment, whereas the difference between the two substrates remained unclear in leaves, and the effect of organ&#215;substrate was significant. The POD activity at 50 d was 28-55% decrease from its 0 d in leaves, while it was 120-125% increase from its 0 d in roots.</ns0:p><ns0:p>Ramets grew well in aquaria with water and mud from the pond (Fig. <ns0:ref type='figure'>5</ns0:ref>). The leaf length (cm) increased from 27.8 cm (&#177;2.0 SD, n = 3) before the experiment to 47.4 cm (&#177;2.9 SD) and 38.8 cm (&#177;3.6 SD) in aquaria with mud and sand, respectively, at the end of the experiment (Welch's two-sample t-test, t = -2.720, df = 3.224, p = 0.067). The leaf number per ramet increased from 13.3 (&#177;1.2 SD, n = 3) before the experiment to 45.0 (&#177;2.4 SD, n = 3) and 35.7 (&#177;4.2 SD, n = 3) in aquaria with mud and sand, respectively, at the end of the experiment (Welch's two-sample t-test, t = -2.521, df = 3.124, p = 0.083). Thus, the growth of V. natans was greater for mud than for sand.</ns0:p><ns0:p>The water quality of aquaria also changed during the experiment. For example, pH increased from 8.3 before the experiment to 9.2 and 9.4, and DO (mg/L) increased from 2.04 to 9.11 and 10.02 in aquaria with mud and sand, respectively, at the end of experiment. Such an increase was expected as a result of plant photosynthesis, which involves consumption of CO 2 and production of O 2 . On the other hand, the concentrations of N and P had decreased after the experiment. For example, TN (mg/L) decreased from 8.59 to 2.34 (&#177;0.65 SD) and 1.83 (&#177;0.52 SD), and TP (mg/L) decreased from 0.11 to 0.078 (&#177;0.017 SD) and 0.071 (&#177;0.010 SD) for mud and sand, respectively. The reduction of N and P in the water seems to be associated with nutrient uptake by V. natans. TN and TP were slightly higher for mud, which originally contained nutrients, than for sand.</ns0:p></ns0:div> <ns0:div><ns0:head>Field experiment</ns0:head><ns0:p>The water quality of the pond varied among the sampling days (Table <ns0:ref type='table' target='#tab_0'>S1</ns0:ref>). For example, at 0.5 m depth, the water temperature, pH, DO, Chl-a concentration, and turbidity varied from 21.7 to 25.0&#176;C, 7.9 to 8.3, 6.4 to 10.0 mg/L, 28.1 to 62.9 mg/L, and 34.8 to 75.8 NTU, respectively. In contrast, the water quality exhibited less variation among 0.5 m, 1.2 m, and 2.0 m depths at each day. For example, at 0 d, the water temperature and pH at all depths were 21.7&#176;C and 8.2, respectively, DO, Chl-a concentration, and turbidity varied from 9.9 to 10.0 mg/L, 62.9 to 70.4 mg/L, and 44.9 to 48.6 NTU, respectively. Similarly, the COD (range: 24-77 mg/L), TN (5.63-9.65 mg/L), TP (0.36-0.64 mg/L) varied among days, but they exhibited less variation among the three depths at each day.</ns0:p><ns0:p>The light quantum (&#956;mol/m 2 s) at each depth also exhibited temporal variation (Fig. <ns0:ref type='figure'>6</ns0:ref>). In addition, it decreased with increasing depth every day, declining to almost half and less than onetenth from the depth of 0.5 m (mean: 79.3 &#956;mol/m 2 s) to 1.2 m (38.3 &#956;mol/m 2 s) and 2.0 m (6.7&#956;mol/m 2 s), respectively. Water transparency gradually increased from 0.25 to 0.30 m during the experiment (Table <ns0:ref type='table' target='#tab_0'>S1</ns0:ref>). Rainy days were more frequent in the latter half of the experiment, with a maximum daily rainfall of 42.2 mm and total rainfall of 208 mm during the experiment (Fig. <ns0:ref type='figure' target='#fig_0'>S1</ns0:ref>).</ns0:p><ns0:p>The leaf Chl-a content (mg/g) declined sharply at the beginning of the experiment, particularly at the depths of 1.2 and 2.0 m (Fig. <ns0:ref type='figure'>7</ns0:ref>). The change in Chl-a content after 10 d differed depending on the water depth, and the effects of time and time&#215;depth interaction were significant (Fig. <ns0:ref type='figure'>7</ns0:ref>, Table <ns0:ref type='table' target='#tab_2'>2</ns0:ref>). After 10 d, the Chl-a content increased slightly at the depth of 0.5 m, whereas it declined steadily at 1.2 and 2.0 m. The Chl-a content decreased with increasing depth, and the effect of depth was significant. However, no clear difference was observed between mud and sand. The Chl-b content also decreased with increasing depth, and the difference between mud and sand remained unclear (Fig. <ns0:ref type='figure'>7</ns0:ref>, Table <ns0:ref type='table' target='#tab_2'>2</ns0:ref>).</ns0:p><ns0:p>The MDA content (nmol/g) of leaves increased 2-to 3-fold during the experiment, whereas the content of roots changed less, and the effects of time and time&#215;organ interaction were significant. The MDA content was significantly higher in leaves than in roots throughout the experiment (Fig. <ns0:ref type='figure'>8</ns0:ref>, Table <ns0:ref type='table' target='#tab_2'>2</ns0:ref>). The MDA content was also significantly higher in deeper positions, and significantly higher for sand than for mud. Consequently, the MDA content of leaves and roots at 30 d was the lowest for mud at 0.5 m.</ns0:p><ns0:p>The SOD activity (unit/g) of leaves and roots increased at the beginning of the experiment at all depths. However, the change of the SOD activity in the latter half of the experiment differed depending on the depth (Fig. <ns0:ref type='figure'>8, Table 2</ns0:ref>); during this period the SOD activity at 0.5 and 1.2 m increased continuously but slowly, whereas that at 2.0 m decreased, and the effects of time and time&#215;depth interaction were significant. At 0.5 and 1.2 m, the SOD activity increased 3-to 4-fold and 2-to 3-fold during the experiment in leaves and in roots, respectively, and the effects of organ, time&#215;organ interaction, and organ&#215;depth interaction were significant. In addition, the SOD activity was significantly higher for mud than for sand, particularly in roots at 0.5 and 1.2 m depths, and the effects of substrate and time&#215;substrate, organ&#215;substrate, and depth&#215;substrate interactions were significant.</ns0:p><ns0:p>The CAT activity (H 2 O 2 nmol/g/min) of leaves and roots increased at the beginning of the experiment at all depths. However, the change of the SOD activity in the latter half of the experiment differed depending on the depth (Fig. <ns0:ref type='figure'>8</ns0:ref>, Table <ns0:ref type='table' target='#tab_2'>2</ns0:ref>); during this period, the CAT activity at 0.5 and 1.2 m increased continuously but slowly, whereas that at 2.0 m decreased. This pattern was similar to that of the SOD activity. The difference in the CAT activity between leaves and roots remained unclear. The CAT activity was significantly higher for sand than for mud.</ns0:p><ns0:p>The POD activity (A 470 /g/min) of leaves and roots increased slightly at 0.5 and 1.2 m during the experiment, whereas it increased sharply at the beginning of the experiment and then decreased at 2.0 m depth, and the effects of time and time&#215;depth interaction were significant (Fig. <ns0:ref type='figure'>8</ns0:ref>, Table <ns0:ref type='table' target='#tab_2'>2</ns0:ref>). The POD activity was significantly higher in leaves than in roots, whereas no significant difference was observed between mud and sand.</ns0:p><ns0:p>The ramets of V. natans did not exhibit an apparent increase in the length and number of leaves during the experiment (Fig. <ns0:ref type='figure' target='#fig_1'>9</ns0:ref>); they rather decreased at 1.2 m and 2.0 m depths. The length and number of leaves tended to decrease with increasing water depth, and were less for sand than for mud, but due to a variation among trays a significant effect was detected only for depth and depth&#215;substrate interaction on leaf number (depth: df = 2, F = 24.4, p &lt; 0.001; substrate: df = 1, F = 3.56, p = 0.071; depth&#215;substrate: df = 2, F = 5.06, p = 0.015). The leaves of ramets at 0.5 m were completely green, but some leaf apices were flat (i.e., not acute like before the experiment), resembling being cut by animals in the pond (e.g., fish, birds). The leaves of ramets at 1.2 m were only partially green, and the leaves at 2.0 m were light brown, indicating senescence.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>In the present study, we examined the growth and physiological status of V. natans under the water and mud conditions of an urban pond using laboratory and field experiments. Plant physiological status was assessed using photosynthetic pigments, Chl-a and Chl-b, as plant health indicators, and a lipid peroxidation product, i.e., MDA, and antioxidant enzymes, including SOD, CAT, and POD, as stress indicators. Ramets grew well in the laboratory and physiological status differed less between 0 and 50 d of the experiment in both mud and sand. Thus, the water of the pond, which is more or less polluted due to urban human activities, is unlikely to directly or adversely affect V. natans. High N and P concentrations can have toxic effects on V. natans <ns0:ref type='bibr' target='#b6'>(Cao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b32'>, Wang et al. 2008</ns0:ref>). However, N and P concentrations in water decreased during our laboratory experiment, which is likely to be associated with nutrient uptake and growth of V. natans. We also revealed that the growth and physiological status of V. natans were better with mud than with sand as a substrate. Thus, although the mud of the pond was rich in organics, an adverse effect of such mud on submerged plants <ns0:ref type='bibr' target='#b3'>(Barko and Smart 1986</ns0:ref><ns0:ref type='bibr' target='#b35'>, Wu et al. 2009</ns0:ref><ns0:ref type='bibr'>, Silveila and Thomaz 2015)</ns0:ref> was not evident in this study. We used sand, which was free of organic matter, as the control substrate. Substrate type and nutrient contents are considered to be important for the nutrient acquisition by the roots of V. natans <ns0:ref type='bibr' target='#b38'>(Xie et al. 2005</ns0:ref><ns0:ref type='bibr' target='#b37'>, Xiao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b2'>, Bai et al. 2015)</ns0:ref>. Although high N and P concentrations in water possibly compensate for a low nutrient content in substrate, sand may be less suitable than natural mud or clay for roots to adjust and acquire nutrients. Further studies using different substrates, such as mud in oligotrophic lakes, are required to examine the suitability of the mud from eutrophic ponds for transplanting V. natans.</ns0:p><ns0:p>The adverse effects of water depth and reduced light availability on V. natans were evident in the field experiment. The leaf number of ramets decreased with increasing depth at the end of the experiment. Moreover, the Chl-a and Chl-b contents of leaves decreased, and the MDA content of leaves and roots increased with increasing water depth. Interestingly, the activities of antioxidant enzymes, SOD, CAT, and POD, increased at the beginning of the experiment and then decreased at 2.0 m depth. This was likely due to the oxidative damage caused by excessive production of ROS under low-light conditions at this depth. Such a deterioration of enzyme activity has been reported for V. natans exposed to lead <ns0:ref type='bibr' target='#b45'>(Yan et al. 2006</ns0:ref><ns0:ref type='bibr'>, Wang et al. 2012)</ns0:ref>. Light availability is the important factor that varies vertically in the study pond. A sharp decline in light availability with increasing depth was detected in this study; the light quantum was reduced by 50% and 90% from 0.5 m to 1.2 and 2.0 m, respectively. <ns0:ref type='bibr' target='#b2'>Bai et al. (2015)</ns0:ref> also reported a 62% and 99% reduction in the light quantum from the surface to 0.6 and 1.8 m in an experimental pond, respectively. Such a sharp attenuation in light availability is typical of eutrophic ponds and lakes <ns0:ref type='bibr' target='#b16'>(Hodoki and</ns0:ref><ns0:ref type='bibr'>Watanabe 1998, De Lange 2000)</ns0:ref>. On the other hand, only small differences were detected in the vertical profile of water quality, including temperature, DO, and N and P concentrations, in this pond. These results suggest that V. natans experiences strong stress at greater depths in this pond due to light depletion, which impedes photosynthesis. Most area inside the study pond was near or greater than 2.0 m deep, at which the growth of V. natans is likely to be inhibited.</ns0:p><ns0:p>Light availability, which is regulated by water depth and transparency, has been identified as the main factor limiting the distribution of submerged plants including V. natans <ns0:ref type='bibr' target='#b31'>(Voesenek et al. 2006</ns0:ref><ns0:ref type='bibr' target='#b2'>, Bai et al. 2015</ns0:ref><ns0:ref type='bibr'>, Dong et al. 2014</ns0:ref><ns0:ref type='bibr' target='#b11'>, Han and Cui 2016)</ns0:ref>. The optimal water depth for the growth of V. natans has been reported as 100-160 cm in an oligotrophic lake <ns0:ref type='bibr'>(Xiao et al. 2017)</ns0:ref>, in which water transparency and light availability were high. However, a steep light attenuation with increasing depth in eutrophic lakes and ponds is likely to limit the distribution of V. natans to shallow areas. <ns0:ref type='bibr' target='#b11'>Han and Cui (2016)</ns0:ref> used the ratio of transparency to water depth as an indicator of eutrophication pressure on macrophyte communities. They suggested that the ratio should be no less than 0.52 to restore submerged species in eutrophic ponds. Based on this criterion, and because the maximum transparency in our study pond was 0.3 m, shallow area less than 0.58 m deep are required to restore submerged plants. Although a deterioration of enzyme activity was not observed at 0.5 and 1.2 m in this study, V. natans is unlikely to be able to tolerate low light stress for a long period. Less growth, reduced Chl contents, and increased level of stress indicators of V. natans even at 0.5 m in this study may suggest that 0.5 m or shallower areas are required for the growth of this plant in this pond. However, too shallow area may be unsuitable for V. natans to grow vertically well in the water column.</ns0:p><ns0:p>The strong effect of depth on V. natans might have obscured the differences between mud and sand in the field experiment. Differences in growth and leaf Chl-a and Chl-b contents between mud and sand, which were observed in the laboratory experiment, were not detected in the field experiment. The MDA content and CAT activity of leaves and roots were higher for sand than for mud in the field, which were not detected in the laboratory experiment. Although there are different results between the experiments, the results of field study suggest that the mud of the pond is unlikely to be a limiting factor in the establishment of V. natans.</ns0:p><ns0:p>Sufficient light and low nutrient concentrations in water were more advantageous to the ramets in the laboratory than to those in the field. The growth and physiological status of leaves and roots were obviously better in the laboratory than in the field, evident from the increase in length and number of leaves, lesser decrease in the Chl-a and Chl-b contents, and lesser increase in the MDA content and antioxidant enzyme activities. The MDA content and activities of antioxidant enzymes, except SOD, declined after a small increase in the early stages of the laboratory experiment. The decline of these indices to the initial or even smaller values at the end of the experiment may indicate ramets acclimatization to the aquaria environment. The mean light quantum at 0.5 m depth (79.3 &#956;mol/m 2 s) was similar to the intensity of light in the incubator (70-80 &#956;mol/m 2 s). However, the light quantum would be smaller inside the meshed cages used to grow ramets in the field. Although the nutrient concentration was initially similar between the aquaria and pond, nutrient uptake by ramets substantially reduced the nutrient concentration in the aquaria at the end of the experiment. High nutrient concentrations can adversely affect V. natans, both directly and indirectly, by promoting epiphytic algal growth on V. natans <ns0:ref type='bibr' target='#b30'>(Song et al. 2015)</ns0:ref>. Ramets in the field were also at a risk of grazing by animals such as birds and fish. Some leaf apices of V. natans were flat, likely to have been eaten partially by pond animals. This was supported by a chance observation of a fish feeding on V. natans collected in a bucket (personal observation). The better growth and physiological status of ramets in the laboratory than in the field may be partially associated with the absence of predator and hydrologic disturbance in the former.</ns0:p><ns0:p>Previous studies have shown increased MDA content in V. natans growing under salinity, lead, and ammonia stress <ns0:ref type='bibr' target='#b32'>(Wang et al. 2008</ns0:ref><ns0:ref type='bibr' target='#b12'>, Hao et al. 2011</ns0:ref><ns0:ref type='bibr' target='#b19'>, Li et al. 2011</ns0:ref><ns0:ref type='bibr' target='#b30'>, Song et al. 2015)</ns0:ref>. In our study, the MDA content was higher with increasing depth. The accumulation of MDA eventually inactivates the enzymes associated with photosynthesis, respiration, and other metabolic processes in plant cells <ns0:ref type='bibr' target='#b30'>(Song et al. 2015)</ns0:ref>. Of the three enzymes analyzed in this study, SOD showed the strongest response, in terms of the magnitude of changes in both laboratory and field experiments. SOD converts O 2into O 2 and H 2 O 2 in the first step of ROS removal <ns0:ref type='bibr' target='#b0'>(Apel and</ns0:ref><ns0:ref type='bibr'>Hirt 2004, Rahnama and</ns0:ref><ns0:ref type='bibr' target='#b26'>Ebrahimzadeh 2005)</ns0:ref>. On the other hand, POD exhibited the fastest response (i.e., stopped increasing the earliest) among the enzymes in both laboratory and field experiments. Both POD and CAT convert H 2 O 2 into H 2 O and O 2 <ns0:ref type='bibr' target='#b5'>(Bowler et al. 1992</ns0:ref>). Responses of these enzymes varied depending on the study <ns0:ref type='bibr' target='#b45'>(Yan et al. 2006</ns0:ref><ns0:ref type='bibr' target='#b12'>, Hao et al. 2011</ns0:ref><ns0:ref type='bibr' target='#b19'>, Li et al. 2011</ns0:ref><ns0:ref type='bibr'>, Wang et al. 2012)</ns0:ref>, and further studies are required to generalize the response of each enzyme.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>We demonstrated important factors on the growth and physiological status of V. natans in eutrophic urban ponds using laboratory and field experiments. Sufficient light availability is required for better physiological status of the species. Owing to the sharp attenuation of light with increasing depth, shallow areas less than 1 m deep and improved water transparency are fundamental requirements for successful re-introduction of V. natans in eutrophic ponds. Despite the anaerobic conditions prevailing in the mud at the pond bottom, no adverse effects were detected on V. natans in the present study. Thus, it is suggested that the current status of the bottom mud does not directly inhibit the growth of submerged species. However, it can indirectly affect growth by releasing nutrients in the water column, which, in turn, can induce algal blooms. Efforts to reduce the nutrient load are also important to limit the phytoplankton overgrowth, and thus, to maintain transparency and ensure light availability to submerged plants. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 9</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Figure 9</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>Results of split-plot-design analysis of variance (ANOVA) showing the effect of each factor on the physiological indices in the laboratory experiment Significance of effects are shown by asterisks ( . Organ and interaction of organ and other factors were not included in the ANOVA for Chl-a and Chl-b PeerJ reviewing PDF | (2020:04:48470:1:1:NEW 31 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>Results of the split-plot-design analysis of variance (ANOVA) that show the effect of each factor on the physiological indices in the field experiment Significance of effects are shown by asterisks ( results of the interaction among three or more variables were omitted). Organ and interaction of organ and other factors were not included in the ANOVA for Chl-a and Chl-b PeerJ reviewing PDF | (2020:04:48470:1:1:NEW 31 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='20,42.52,199.12,525.00,178.50' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:04:48470:1:1:NEW 31 Jul 2020)Manuscript to be reviewed</ns0:note> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:04:48470:1:1:NEW 31 Jul 2020)</ns0:note> </ns0:body> "

"Dear Prof. Jörg Oehlmann, Academic Editor, PeerJ Thank you very much for handling our manuscript. We also thank the two reviewers for their critical and productive comments on our manuscript. We improved our manuscript following each of their comments. We hope the changes in manuscript and our responses are sufficient for the requirements given by the reviewers. Sincerely, Sohei Kobayashi On behalf of all authors. Reviewer 1 (Mohsen Tootoonchi) Thank you very much for your valuable comments. We understood what are unclear and missing in our previous manuscript by your comments. Basic reporting Please see the attachment. Experimental design Please see the attachment. Validity of the findings Please see the attachment. Comments for the Author In the manuscript entitled: Effects of substrate and water depth of a eutrophic pond on the physiological status of Vallisneria natans, a useful aquatic plant for water environment restoration in urban areas” authors explore the limiting factor for the growth of V. natans in eutrophic urban ponds. They measure various compounds in root and shoot to assess the stress level of V. natans when grown under different depth/light conditions and substrates. General comments 1- The title can be more concise. Try removing the second part: a useful aquatic plant… We removed the second part and changed as “Effects of substrate and water depth of a eutrophic pond on the physiological status of a submerged plant, Vallisneria natans” 2- The study is conducted using a small laboratory experiment and then in the field using a eutrophic urban pond. But results and discussion on these two parts of the study are not well organized. The text needs to be reworked and reorganized to clarify what authors have found from each experiment separately and then what the pilot study (lab exp) contributed to the field study. We changed the structure of Discussion by separating paragraphs for laboratory and field experiments at the begginning of Discussion (First paragraph for the laboratory, second one for field, third and later paragraphs for common patterns and comparisons between the 2 experiments). 3- Tables and figures are not consistent. They are not clear and lack the information necessary for the assessment of research findings. Most importantly, statistical analysis needs to be incorporated into the figures or shown to clearly demonstrate the differences across depths and substrates. We worry about redundancy and too much information in figures by adding statistical results in figures. However, readers may feel bothering by go and back between tables and figures, so we showed statistical results in figures (Fig. 3,4,7,8) as well as in tables. 4- Statistical analysis is not explained properly. With two experiments (lab and field) and different experimental designs, authors need to provide a complete explanation of how and why they decided to run the stats with the current method. We changed and separated the explanation for lab and field experiment, and explained much detail for each analysis. 5- Several compounds are measured and discussed in the text based on leaf analysis and the majority of the results and discussion are focused on these compounds without a word of how the plants actually performed at different treatments/depths. only plant assessment for lab exp was shown which seems unrealistic. The data are perhaps rounded up and somehow all stnd dev are 5! In addition, there is no description of how the authors assessed these data (height, fresh weight, etc.) We focused on physiological status to examine the healthiness of V. natans, and we made less effort on measuring size or growth. This is because our study was originally motivated by a fact that many transplanted V. natans suddenly died and floated on surface (with roots and leaves being black, roots being dwarf) even they appeared to have grew well. However, we agree that both growth and physiological status are important to know what is happening. We checked the data and corrected the mean and variation values. We deleted the result of fresh weight (the whole weight of ramet), because we couldn't find the original data that were used to calculate mean value. We also showed the results of leaf length and number in the field experiment. 6- Substrate is a big component of this study and it is even in the title. But there is no information on substrate texture and chemistry. Measurements of mud characteristics were planned after we detect some adverse effects of the mud (but we didn’t detect so far). After the comments by both reviewers, we measured COD, TN, TP contents in the mud, which we can measure now. We added information of mud and sand in Methods. This manuscript can be significantly improved by English editing and requires careful attention to the disclosed comments. We wish our English is readable this time. Both the first and second manuscripts were edited by an English editing service Abstract 20 it is better to define “physiological status” or be more specific. Please state what physiological traits you have measured. We changed here by adding “measuring biomarkers in leaves and roots” 22 “water environmental conditions” sounds odd. Throughout the text. We intended to include not only water quality but also bottom and living organisms in the meaning of water environment. But according to the comments, we changed and used water quality, or habitat instead of water environment throughout the text. 26 “different physiological status” is vague. You could change the sentence to” MDA, SOD, CAT and POD content differed in leaves and roots when plants were grown in different substrates…”. We changed and used the name of actual compounds instead of physiological status as much as possible throughout the text. 35 due to environmental stress. This is too general. If your treatments are depths, just make statements about the depth to avoid generalization. We changed and avoid to use environmental stress throughout the text. 34-38 needs reorganizing to make it clear what is compared to aquaria or sand. Try to separate the findings between the laboratory and field experiment to avoid confusion. Structure of Abstract and Discussion is changed to show results of each of the laboratory and field experiments first, and then compared between the laboratory and field experiments. 40 bottom mud has adverse effect?! Why is that expected? Please explain. We added an explanation that organic-rich mud can inhibit survival of submerged plants and cite references, in Introduction and Discussion. 42 this study talks about water depth and ties that with light attenuation. But there is no mention to light intensity at different depths in the abstract. We added a statement “Mean light quantum (μmol/m2s) during the experiment decreased with depth, from 79.3 at 0.5 m to 7.9 at 2.0 m.” in abstract. 53 please avoid using the word “purify”. Plants do not purify the water. We deleted the word “purify” throughout the text. 63 “because of less survival of planted individuals” sounds odd. Maybe change to ‘ because of low survival rate of transplants or introduced plants” Changed as suggested. 64 inhibits Changed as suggested. 69 shorten the sentences, here: . but it is not clear whether… We totally changed this sentence “In addition, organic-rich mud under anaerobic conditions, which is typical at the bottom of eutrophic ponds, can inhibit the survival of submerged plants (Barko and Smart 1986, Wu et al. 2009, Silveila and Thomaz 2015)”. 70-72 I do not understand the connection between hydraulic forces of waves in large water bodies and lakes to this study on small urban ponds. I suggest removing this statement. We changed here as “Physical disturbances, such as waves and currents in lakes and large water habitats (Madsen et al. 2001, Ellawala et al. 2013, Xu et al. 2016), can also be a key on the survival of submerged plants.”. 75-76 you measured both Chl a and b. explain their difference here and what different levels of each means. 77 isnt it better to say photosynthetic ability?! We added sentence as suggested. “Chlorophyll (Chl) is a pigment that absorbs solar energy and accelerates photosynthesis, and its content in leaf tissue is often used as an indicator of photosynthetic ability and plant health. Chl-a absorbs light with blue and red region and is the primary photosynthetic pigment, while Chl-b absorbs light with slightly different region and is the accessory pigment supporting Chl-a.” 79 you should state that ROS induce lipid peroxidation. Otherwise there is no connection between the two sentences. We changed as “Products of lipid peroxidation induced by ROS, such as malondialdehyde (MDA), are also harmful to cell organs”. 80 please explain why under stress conditions, production of SOD, CAT and POD is increased but their activity (line 83) is reduced. We didn’t mean to separate production and activity of enzymes. We changed as “Although the activities of such enzymes increase with ROS, excessive accumulation of ROS and oxidative compounds in cells can reduce their activities,”. 97 remove “ of the park”. The pond is approximately 300 m long… Changed as suggested. 99-101 I recommend moving these statements about permits to the acknowledgement sections. This is required in the author guideline.. 105-106 “… leaves on the water surface have shown an obvious black color in recent years.” I do not understand what the authors are trying to convey here. 108 remove “a location in”. 102-110 in this paragraph, authors could simply say that, in the study site/pond the restoration of V. natans has failed repeatedly despite… list all the failed trials including aerator installation. According to these comments, we changed as “The pond has been restored repeatedly using V. natans, which was originally abundant in this area, since 2011. Although the water quality improved after planting V. natans, aquatic plants, including V. natans, died and disappeared after a few years. Subsequently, an aeration device was installed at the bottom of the pond. Despite an improvement in dissolved oxygen (DO), the introduction of V. natans failed again in recent years. The bottom mud, which was organic-rich and anaerobic state, has been assumed as a cause of the failure because roots of the dead V. natans were dwarf and black-colored.”. 111-117 how were these measured? Using what device/probes? We would like to just show water quality as a background condition of the pond here, and explain detail of these devices in the latter paragraph of experiment design. 118 black color and anaerobic odor? Is this all we know about the collected sediment/mud? After the comments by the reviewers, we measured the COD, TN, TP contents of the mud and showed as mud characteristics. 136-138 The two substrates are being called different things throughout the text. Here is the longest name used have in the text: Bottom mud of the pond and River coarse sand. I suggest calling them simply mud and sand, and at first mention describe how you collected the mud (from the bottom of the pond) and sand. Also provide the chemical and physical properties of both substrates. We made definitions and used mud and sand throughout the text. We used different sand in the laboratory and field experiments, but to make simple we used sand for both cases after we defined and showed properties. 141 replace “allayed” with placed. Changed as suggested. 142 three different depths… what are the depths. Although 3 depths are mentioned in the early this paragraph, we showed again. 145-148 do you need all these (Temperature, pH, DO, ORP, EC, Turbidity, Chl a (what about Chl b?)) parameters? If you do not discuss them, you should remove them from the text. We changed and removed the variables we don’t discuss so much. We also deleted some statements in the results, and deleted Tables of water quality. 153 remove “during the experiment” Changed as suggested. 153-155 other researchers do not need to know about the permitting agency. Move these to the acknowledgement section. We deleted this statement here. 159-164 rephrase all these sentences. Do not start explaining each method with”By…”. For example, digested water samples were analyzed for TP using molybdenum… We changed as “TN and TP were determined by ultraviolet spectrophotometry and the molybdenum blue method, respectively, after digestion of sampled water. Inorganic N (NH4+-N, NO3—N, NO2--N) was determined by Nessler’s reagent spectrophotometry and ultraviolet spectrophotometry. The COD was determined using the potassium dichromate method.”. 172 “converted to mg g-1 of fresh leaf.” Also how did you measure the fresh weight? Did you ensure that there is no water on the plant tissue when weighting them? How did you deal with the clonal growth? Did you remove them? Are new clonal growth a part of the fresh weight measurement? We changed and mentioned “Collected leaf and root were soon cut and weighed as fresh weight after removing surface water by paper.”. We measured growth for ramets we left unsampled. 193-194 please expand on this statement. We didn’t get the point of this comment. We explained measurement methods following previous studies.. 205 statistical analysis I suggest separating the statistical analysis into two sections and explain the design for lab and field experiments separately. In the result section, you explain the split plot design first but in the stats section, you described it in the latter section. These need to be consistent. We changed and separated explanation for lab and field experiments, and also made consistent between Methods and Results. 216 was there a depth factor in the aquaria design? I am getting confused. No depth factor in the laboratory experiment. We changed and separated explanation for lab and field. 224 are these reported numbers for both substrates? We changed and showed sample n for each substrate. 227 report nitrate conc at the beginning and at the end. The change in nitrate was shown in Table previously, but we delete the table and showed result of only TN and TP in the text, following reviewer 2. 229 nutrients? Or are you still talking about nitrate? Also, reduction in nutrient may indicate nutrient uptake but not plant growth. Please remove the statement about growth. We were talking about nutrient previously. We removed the statement as suggested. 232 heterotrophic microbes… please provide supporting literature. We removed the sentence about heterotrophic microbes and changed as “TN and TP was slightly higher for mud, which originally contained nutrients, than for sand.”. 235 change to… was almost double than the growth in sand… We deleted Table 2 following reviewer 2, and showed growth values for each substrate in the text. 237 is there a statistical analysis done on this part to detect significant differences between the growth of V. natans in the two different substrates? We added statistical analysis for the difference in growth between substrates. 238-242 start this section by stating that there was a temporal difference between Chl a… content of the leaves and then point at the increased levels by reporting the concentration at the specific days into the experiment. We changed and stated about overall temporal pattern first, and then stated detail pattern. 242 if statistical analysis was done on these measurements, why they are not incorporated in the figures? We added result of statistical test in figures, as mentioned previously. 246 if both Chl a and b had the same trend, you could revise this paragraph to reflect this observation. That would bes much more effective than making the reader go through them one by one. The trends of Chl-a and Chl-b are not completely the same, so we separated the paragraph. 248 MDA increased by 5 or 10 d in both leaves and roots. What does this mean? We changed here as “The MDA content (nmol/g) of both leaves and roots increased at the beginning of the experiment and then decreased,”. 258 the difference was small? Table 3 shows that there is No difference! Table showed the significance of the difference, and it doesn’t show about no difference. We changed and wrote as “no significant difference was detected or the difference was unclear”. 266 how much was the decline? 10%? 50%? Is this a statistically significant decline? We would like to show here an overall temporal pattern. We changed as “The POD activity (A470/g/min) of both leaves and roots increased at the beginning of the experiment and then gradually decreased, and the effect of time was significant (Fig. 4, Table 1).”. 271-274 why are these important? Did temperature and rain both had a significant effect on the experiment? Daily rain and temperature have equal effect (if any) on the treatments. If this is the case, then reporting them does not add to this manuscript and I suggest removing all the statements and fig/tables related to temp and rain. 275 all the water equality parameters changed by day? Did this fluctuation have a sig effect on the treatments? What do you mean by …turbidity were recorded at 0 or 5 d. ? does it mean that they were recorded on 5-day intervals? We would like to show about environmental variables that can affect water transparency, and indirectly affect plants. We deleted most of the statements about water variables, which are not directly associated with plants, and deleted Figure and Table (changed to supplemental Figure and Table). But we left some of the statements of water variables as background conditions of the field experiment. 335 as mentioned before, the statistical analysis was not shown and it needs to be incorporated in figures or authors provide a table to show there was a statistically significant different between Chl level in leaves in mud than sand. We wonder whether the reviewer recognized that we used tables to show results of statistical tests. What was found in the laboratory experiment? We changed and used 1st paragraph of Discussion for the result of laboratory experiment. 345 what is the hypothesis behind the mud having an adverse effect on the growth of v. natans? We added known effects of mud in Introduction “In addition, organic-rich mud under anaerobic conditions, which is typical at the bottom of eutrophic ponds, can inhibit the survival of submerged plants (Barko and Smart 1986, Wu et al. 2009, Silveila and Thomaz 2015).”. 350 I suggest saying that the light quantum or light penetration was reduced by 50% and 90% at depths… Changed as suggested. 355 sharply increased by 10 d? please mention the fig number. I do not understand what authors are trying to convey here. We changed as “, the activities of antioxidant enzymes, SOD, CAT, and POD, increased at the beginning of the experiment and then decreased at 2.0 m depth.”. 359 please cite literature that also reported similar observation under low light conditions instead of chemical exposure. Also what does severe chemical conditions mean? We changed here as “This was likely due to the oxidative damage caused by excessive production of ROS under low-light conditions at this depth. Such a deterioration of enzyme activity has been reported for V. natans exposed to lead (Yan et al. 2006, Wang et al. 2012).”. We couldn’t find so far studies showing deterioration of enzyme activities other than toxic stress. 389 what is the day of peak activity? Please explain? We intended to show when the maximum stress value occurred. But we changed and simply mentioned as “, POD exhibited the fastest response (i.e., stopped increasing the earliest) among the enzymes in both laboratory and field experiments.”. 401-404 this is interesting but should move to the discussion section where you can cite the paper by Han and Cui and discuss their finding. Also this needs to be further discussed since you had a treatment at 0.5 m depth so explain how your treatment performed under this condition. We moved this statement to Discussion, and discussed more about the suitable depth for V. natans. 408 I do not recall where in the text you showed a correlation between rainfall and nutrient concentration! This needs to be removed. In the previous manuscript, we briefly showed a relation between rainfall and TN and TP in the pond in Results, but it was not so strong relationship, we deleted this sentence. Fig1 mud of pond bottom. Please change to “collected mud”. Changed as suggested. Fig2 if these cages were used. Im afraid they might have blocked quite a lot of sunlight themselves! We referred this possibility in the paragraph that compared between laboratory and field experiments in Discussion. Fig 3 what is d? please specify how many observation/data point is shown by each circle. D represents day. We added sample n in the caption. Table 1 the table and its caption does not indicate what each column represents. For example, what are the two “after”? also state the duration of the experiment. Table 2 how are these measurements done? The numbers seem too clean and all appear to be rounded up. This table is for the lab experiment. What about the field experiment? Did the plants survive 30 day in that depth? How was the growth and other growth components? Table 1 and 2 were deleted. Table 3 why was beaker/tray number the random factor and was not considered a replication? You have df for chl a/b in plant organs? This was not measured and there is no statistical analysis on it. Please leave it blank. It is a kind of replication, but we sampled from the same trays every time, so samples of different times are not completely independent from each other. We left it blank for F and p values, which indicates no test for this factor. Table 4 is confusing. You have different parameters measured on 5-day interval, but at what depth? Then you have different depths that numbers do not differ by much! Should you replace them with a range to simplify the table? The significant difference for depth at the last column, is comparing the three depths (0.5,1.2 and 2 m)? We tested mean values of each day across all depths, and mean values of each depth across all experiment days. We think it is reasonable to show these mean values because these are the values tested by ANOVA. We changed old Table 4 to Table S1 in the present manuscript. Why transparency is not measured at different depths? Secchi disk readings could be the most important measurement in this study since you are focusing only on water depth in the field experiment. We think transparency is usually measured at water surface, not at different depths of water. Other variable, such as light, turbidity, Chl-a concentration, which have a relationship with transparency, supports patterns of vertical difference. What is the + for the TP p value? We added explanation of +, which indicates marginal significance (p < 0.1). All the water quality parameters, those reported in mg/l are not different across depths. why report them for different depths? We would like to show what variables vary vertically and what variables don’t. Annotated manuscript The reviewer has also provided an annotated manuscript as part of their review: Download Annotated Manuscript We downloaded the file, and we found that all the comments were already given in the decision letter. We also asked the editorial staffs if the file is correct or not. Reviewer 2 (Anonymous) Basic reporting The manuscript investigated the effects of substrate type and water depth on the growth and physiological responses of submerged plant Vallisneria natans (Lour.) H.Hara by laboratory and field experiments. The experimental design is quite straightforward. Hence, the study and its results are very easily followed. Thank you very much for your valuable comments. We understood what are unclear and missing in our previous manuscript by your comments. Experimental design In this study, the authors compared the physiological responses of V. natans between bottom mud of the pond and quartz sand. The collected bottom mud was black and emitted anaerobic odors as mentioned by the authors, which may be stressful to V. natans. However, quartz sand may be also bad to the growth of V. natans because of its extremely low nutrition, which means quartz sand may be also stressful to V. natans. Thus, quartz sand may not be suitable as a reference substrate, and using quartz sand as a reference substrate can not achieve the purpose of the study. The authors should notice the limitation and should be more cautious when discussing the results. If I did this experiment, I would choose another suitable substrate as a reference which lets V. natans growth well in the natural habitats (such as a mixture of sand and soil, please see the Xiao et al., 2007 in Hydrobiologia, the authors also cited in the text). We assumed that organic-rich state of the mud is stressful for V. natans, and used sand, which is free of organic, as the control substrate. Because nutrient concentrations were high in the water, we didn’t think much about the low nutrient concentration in substrates. We added statements why we used sand for the control substrate in Methods, and also limitations of our study in Discussion. Validity of the findings The authors investigated the physiological status of V. natans in response to substrate type and water depth in the field experiment, but they only compared the physiological responses of V. natans between two substrate types in laboratory experiment. The missed data about the response of V. natans to water depth may hinder the comprehensive understanding of the physiological status V. natans in response to substrate type and water depth. We focused on physiological status to examine the healthiness of V. natans, we made less effort on measuring size or growth. This is based on an observation in a previous restoration work that many of transplanted V. natans were suddenly dead (root and leaf color changed black and then soon died) even they appeared to have grew well. However, we agree that both growth and physiological status are important to know what is happening. We checked the data and added figures about the length and number of leaves at before and the end of the experiment. Number of ramets were unchanged during the experiment. Comments for the Author The manuscript investigated the effects of substrate type and water depth on the growth and physiological responses of submerged plant Vallisneria natans (Lour.) H.Hara by laboratory and field experiments. The experimental design is quite straightforward. Hence, the study and its results are very easily followed. However, I still have some concerns that the authors need to deal with: 1. In this study, the authors compared the physiological responses of V. natans between bottom mud of the pond and quartz sand. The collected bottom mud was black and emitted anaerobic odors as mentioned by the authors, which may be stressful to V. natans. However, quartz sand may be also bad to the growth of V. natans because of its extremely low nutrition, which means quartz sand may be also stressful to V. natans. Thus, quartz sand may not be suitable as a reference substrate, and using quartz sand as a reference substrate can not achieve the purpose of the study. The authors should notice the limitation and should be more cautious when discussing the results. If I did this experiment, I would choose another suitable substrate as a reference which lets V. natans growth well in the natural habitats (such as a mixture of sand and soil, please see the Xiao et al., 2007 in Hydrobiologia, the authors also cited in the text). 2. The authors investigated the physiological status of V. natans in response to substrate type and water depth in the field experiment, but they only compared the physiological responses of V. natans between two substrate types in laboratory experiment. The missed data about the response of V. natans to water depth may hinder the comprehensive understanding of the physiological status V. natans in response to substrate type and water depth. These are the same with the previous comments. 3. Specific comments： Long tile, I suggest delete ‘a useful aquatic plant for water environment restoration in urban areas’ We deleted this part. Line124-125. Please clarify how many repetitions in laboratory experiment? A replication for each beaker, or each aquarium? We changed and showed sample n every time. Line132. 500 L of water was sampled from each aquarium??? Or 500 mL? Our mistake. We changed to 500 mL. Lin136-142. Again, how many repetitions in field experiment? Please clarify it. We changed and showed sample n every time. Line 208. How could the experimental time be treated as a fixed factor? Experimental time should be a repeated factor, and thus a two-way repeated ANOVA should be conducted to investigate the effects of experiment time and depth on the variables measured by the water quality meter (i.e., temperature, pH, DO, ORP, EC, turbidity, and Chl-a). We conducted two-way ANOVA without replication. We recognize that this is identical to repeated measures ANOVA but the concept is different (the factor is sequence number or categorical). Line 234. If the plant biomass included the biomass sampled for physiological measurements? Please clarify. We added the sentence. “A previously unsampled ramet was collected from each aquarium at the end of the experiment for measuring leaf length and number”. We deleted biomass data because we were unable to confirm the original data. For the Results, there are too many tables and figures, I strongly suggest the authors do some consolidation and streamlining. We deleted 3 of 5 Tables (old Table 3 was changed to Table S1). We deleted old Fig. 3, but added 3 new Figs, which are about the length and number of leaves in the laboratory and field experiments, and light quantum. For the Discussion, the authors mainly listed the results but did not explain why these results occurred, and what is the ecological significance of the obtained results. Moreover, the authors discussed the effects of substrate type and water depth separately, but not mentioned their interactive effects which may be most interesting results! We tried to explain mechanisms of our finding and compare with previous studies in Discussion. We think our findings (e.g., effect of depth) are ecologically meaningful, but not a new topic in a basic ecology. We initially expected to find some different responses of roots and leaves to substrate and depth, but the differences were not clear and consistent. It is interesting if we could revealed that not a single factor but a combination of depth and substrate is important. Our impression is that the effect of substrate was weaker and that of depth was stronger than we initially expected, and the effect of substrate was obscured by depth. The language is in general easy to understand, but there are minor problems throughout the text (according to my view, but I am not a native English speaker). The authors need to check the text carefully, and ideally also ask a native speaker to have a quick check. We used English editing service to improve out writing this time as well as for the previous manuscript. We hope our writing is improved this time. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Effects of substrate and water depth on the physiological status of a submerged macrophyte, Vallisneria natans (Lour.) H.Hara, were determined by measuring biomarkers in leaves and roots, to understand factors limiting the re-establishment of V. natans in urban eutrophic ponds. Ramets of V. natans were grown in the laboratory using aquaria containing water and bottom mud from a eutrophic pond and maintained under sufficient light in an incubator. The growth and chlorophyll-a (Chl-a) content of leaves were greater in aquaria with mud than in those with sand, which was used as the reference substrate.</ns0:p><ns0:p>The contents of a peroxidation product [malondialdehyde (MDA)] and three antioxidant enzymes [superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD)] in leaves and roots, used as stress biomarkers, changed during the experiment, although differences in these contents between mud and sand were not consistent across the experimental days. To control water depth in the field, ramets of V. natans were grown in cages with different substrates (mud and sand) installed at different depths (0.5, 1.2, and 2.0 m) in the pond. The mean light quantum during the experiment decreased with increasing depth, from 79.3 &#956;mol/m 2 s at 0.5 m to 7.9 &#956;mol/m 2 s at 2.0 m. The Chl-a content in leaves decreased, whereas the MDA content in both leaves and roots increased with increasing water depth. All enzyme activities increased at the beginning and then decreased to the end of the experiment at 2.0 m depth, suggesting deterioration of enzyme activities due to depth-related stress. The MDA content and CAT activity were higher for sand than for mud, whereas the difference in the growth and the leaf Chl-a content between substrates remained unclear in the pond. On comparing the laboratory and field experiments, the leaf Chl-a content was found to be lower and the MDA content and enzyme activities exhibited sharp increase for ramets grown in the pond, even at 0.5 m depth, when compared with those grown in the aquaria. Our results suggest that the bottom mud of the pond is not the major limiting factor in the re-establishment of V.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Urban ponds often suffer from eutrophication <ns0:ref type='bibr' target='#b13'>(Harper 1992</ns0:ref><ns0:ref type='bibr' target='#b10'>, Grimm et al. 2008</ns0:ref><ns0:ref type='bibr' target='#b31'>, Smith and Schindler 2009)</ns0:ref>. In closed aquatic ecosystems with less renewal of water, excessive nutrient input immediately leads to the overgrowth of phytoplankton. Oxygen depletion is particularly severe at the bottom of such aquatic ecosystems because of respiration by overabundant phytoplankton, decomposition of accumulated organic matter, and limited benthic photosynthesis due to reduced light transparency. Such hypoxic conditions result in the exclusion of animals, such as fish and other aerobic organisms, from the bottom. Submerged plants are often used to improve the ecological status of eutrophic aquatic environments because of their ability to absorb nutrients <ns0:ref type='bibr' target='#b27'>(Qiu et al. 2001</ns0:ref><ns0:ref type='bibr' target='#b15'>, Hilt et al. 2006</ns0:ref><ns0:ref type='bibr' target='#b29'>, Sayer et al. 2010)</ns0:ref>. Vallisneria natans (Lour.) H.Hara is a submerged rooted plant, which is widely distributed in freshwater habitats across the Asia and Australia <ns0:ref type='bibr' target='#b23'>(Lowden 1982)</ns0:ref>. Owing to its adaptability to a wide range of temperatures and substrates <ns0:ref type='bibr' target='#b43'>(Xiong and Li 2000</ns0:ref><ns0:ref type='bibr' target='#b41'>, Xie et al. 2005</ns0:ref><ns0:ref type='bibr' target='#b17'>, Ke and Li 2006)</ns0:ref>, ability to absorb significant amounts of nutrients <ns0:ref type='bibr' target='#b35'>(Wang et al. 2017</ns0:ref><ns0:ref type='bibr' target='#b42'>, Xing et al. 2018)</ns0:ref>, and allelopathic effects on phytoplankton <ns0:ref type='bibr' target='#b38'>(Xian et al. 2006</ns0:ref>), V. natans has been used to restore many urban ponds <ns0:ref type='bibr' target='#b46'>(Yan et al. 1997</ns0:ref><ns0:ref type='bibr' target='#b27'>, Qiu et al., 2001)</ns0:ref>.</ns0:p><ns0:p>Despite their potential to improve degraded aquatic ecosystems, submerged plants, including V. natans, have been declining in many freshwater bodies due to habitat degradation <ns0:ref type='bibr' target='#b15'>(Hilt et al. 2006</ns0:ref><ns0:ref type='bibr' target='#b6'>, Cao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b25'>, Qin et al. 2013)</ns0:ref>. Restoration works in urban ponds often fail to re-establish stands of submerged plants because of the low survival rate of transplants. High concentrations of nutrients, such as NH 4 + , inhibit and impairs the growth of V. natans <ns0:ref type='bibr' target='#b6'>(Cao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b34'>, Wang et al. 2008)</ns0:ref>. Light availability, which is regulated by water depth and transparency, is the principal factor restricting the growth of V. natans in eutrophic aquatic environments <ns0:ref type='bibr' target='#b39'>(Xiao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b2'>, Bai et al. 2015)</ns0:ref>. Substrate quality in terms of texture and chemistry has also been shown to affect V. natans <ns0:ref type='bibr' target='#b41'>(Xie et al. 2005</ns0:ref><ns0:ref type='bibr' target='#b22'>, Li et al. 2012</ns0:ref><ns0:ref type='bibr' target='#b2'>, Bai et al. 2015)</ns0:ref>. In addition, organicrich mud under anaerobic conditions, which is typical at the bottom of eutrophic ponds, can inhibit the survival of submerged plants <ns0:ref type='bibr' target='#b3'>(Barko and Smart 1986</ns0:ref><ns0:ref type='bibr' target='#b37'>, Wu et al. 2009</ns0:ref><ns0:ref type='bibr'>, Silveila and Thomaz 2015)</ns0:ref>. Physical disturbances, such as waves and currents in lakes and large water habitats <ns0:ref type='bibr' target='#b24'>(Madsen et al. 2001</ns0:ref><ns0:ref type='bibr' target='#b8'>, Ellawala et al. 2013</ns0:ref><ns0:ref type='bibr' target='#b45'>, Xu et al. 2016)</ns0:ref>, can also be a key on the survival of submerged plants. Elucidating the factors limiting the survival of submerged plants is required for effective restoration of urban ponds.</ns0:p><ns0:p>Plants under stress exhibit physiological changes in their cells and organs. Chlorophyll (Chl) is a pigment that absorbs solar energy and accelerates photosynthesis, and its content in leaf tissues is often used as an indicator of photosynthetic ability and plant health. Chl-a absorbs light in the blue and red regions and is the primary photosynthetic pigment, whereas Chl-b absorbs light in slightly different regions and is an accessory pigment supporting Chl-a. Stressful conditions increase the accumulation of reactive oxygen species (ROS), such as superoxide radicals (O 2 -), hydroxyl radicals (OH -), and hydrogen peroxide (H 2 O 2 ), which can damage cell organelles. Products of lipid peroxidation induced by ROS, such as malondialdehyde (MDA), are also harmful to cell organelles. ROS accumulation can be controlled by antioxidant enzymes such as superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD). Although the activities of such enzymes increase with ROS, excessive accumulation of ROS and oxidative compounds in cells can reduce their activities, ultimately leading to apoptosis. These peroxidation products and enzyme activities have been used as indicators of stress caused by toxic chemicals or low nutrient availability in V. natans <ns0:ref type='bibr' target='#b34'>(Wang et al. 2008</ns0:ref><ns0:ref type='bibr' target='#b12'>, Hao et al. 2011</ns0:ref><ns0:ref type='bibr'>, Wang et al. 2012</ns0:ref><ns0:ref type='bibr' target='#b32'>, Song et al. 2015)</ns0:ref>.</ns0:p><ns0:p>To promote ecosystem restoration of urban ponds by introducing V. natans, we examined the water quality of an urban pond in Wenzhou City, China, and the effects of water, bottom mud, and pond depth on the physiological status of V. natans by in vitro and in situ experiments. We measured the Chl-a and Chl-b contents of leaves as indicators of plant health and of MDA, SOD, CAT, and POD in leaves and roots as indicators of stress.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Study site</ns0:head><ns0:p>The study was conducted at Zhong Shan Park, approximately 1 km south of the Ou River, central Wenzhou City, China (Fig. <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>). The study pond was approximately 300 m long in the north-south direction, 20 m wide in the east-west direction, and 2 m deep. Authorization of field surveys and experiments were given by the Wenzhou Science and Technology Bureau (Water Pollution Control and Treatment Technology Innovation Project under Wenzhou Science and Technology Plan Project: W20170002).</ns0:p><ns0:p>The pond has been restored repeatedly using V. natans, which was originally abundant in this area, since 2011. Although the water quality improved after planting V. natans, aquatic plants, including V. natans, died and disappeared after a few years. Subsequently, an aeration device was installed at the surface of the pond. Despite an improvement in dissolved oxygen (DO), the introduction of V. natans failed again in recent years. The bottom mud, which was organic-rich and anaerobic state, has been assumed as a cause of the failure because roots of the dead V. natans were dwarf and black-colored.</ns0:p><ns0:p>Our preliminary measurements of the pond water showed that the pH was 7.8-8.3, DO was 6-10 mg/L, water transparency was 0.2-0.3 m, turbidity was 40-80 nephelometric turbidity units (NTU), electric conductivity (EC) was 430-465 &#956;s/cm, total nitrogen (TN) and total phosphorus (TP) were 6.59-8.59 mg/L and 0.41-0.50 mg/L, respectively, and the Chl-a concentration was 30-65 &#956;g/L. The collected bottom mud was black and emitted anaerobic odors, exhibited a total organic carbon (TOC) of 15.4-17.1%, and contained 6.0-7.6 mg of TN and 2.2-3.4 mg of TP per unit dry weight g of mud. The aeration device was located at the southern part of the pond (Fig. <ns0:ref type='figure' target='#fig_0'>1</ns0:ref>), where we surveyed the water quality and conducted the field experiment.</ns0:p></ns0:div> <ns0:div><ns0:head>Laboratory experiment</ns0:head><ns0:p>The responses of V. natans to the mud and water of the pond were examined in the laboratory. The mud and water were collected from the pond a few days before the experiment. We used quartz sand (SiO 2 : &gt;95%, particle size: 1-2 mm), free of organic matter and nutrients (hereafter we called sand), as the control substrate. Intact and fresh ramets of V. natans collected from a rural wetland were used. Five ramets were planted in a 500-mL beaker with a 5-cm layer of the substrate (either mud or sand) at the bottom. Three beakers with ramets were placed in an aquarium (30&#215;30&#215;50 cm 3 , 45 L) containing 30 L of pond water such that the entire propagule was submerged. Three aquaria containing a total of nine beakers and 45 ramets were used for each substrate type.</ns0:p><ns0:p>The aquaria were placed in an incubator maintained at a constant temperature of 25&#176;C, under a light intensity of 5000 lux, and light:dark photoperiod of 12 h:12 h for 50 d. For physiological measurements, leaves and roots were sampled from a ramet in each aquarium (i.e., n = 3 for each substrate) every 10 d, and then frozen and preserved at -20&#176;C. A previously unsampled ramet was collected from each aquarium at the end of the experiment for measuring leaf length and number (n = 3 for each substrate). Water quality parameters, including temperature, pH, and DO, were measured using a multiparameter water quality meter (Hydrolab DS5X, OTT Hydromet GmbH, Kempten, Germany), and water was sampled for N and P analyses from each aquarium (n = 3 for each substrate) at the end of the experiment.</ns0:p></ns0:div> <ns0:div><ns0:head>Field experiment</ns0:head><ns0:p>The responses of V. natans to different water depths (0.5, 1.2, and 2.0 m) were surveyed in the southern part of the pond. The mud of the pond and river coarse sand (particle size: 1-2 mm), which was washed to remove organic matter, were used as substrates. The ramets of V. natans were planted uniformly in a mesh plastic cage (40.0&#215;48.5&#215;67.5 cm 3 ) containing three rectangular trays (10&#215;25&#215;38 cm 3 ) with a 7-cm layer of the substrate (either mud or sand) (Fig. <ns0:ref type='figure'>2</ns0:ref>). A tiered structure was constructed in the pond using steel pipes, and three cages for each substrate type were placed at three different depths (0.5, 1.2, and 2.0 m; Fig. <ns0:ref type='figure'>2</ns0:ref>).</ns0:p><ns0:p>The experiment commenced on May 11, 2019. The water quality of the pond was evaluated and the ramets of V. natans were sampled on 5, 10, 20, and 30 d of the experiment. The vertical profile (0.1 m intervals) of water quality, including temperature, pH, and DO, was measured near the experimental site using the water quality meter. In addition, water samples (500 mL) were taken from each experimental depth (0.5, 1.2, and 2.0 m) for N and P analyses. The light quantum at each experimental depth was monitored continuously by installing a pocket-size photosynthetically-active radiation logger (DEFI2-L, JFE Advantech Co., Ltd., Nishinomiya, Japan). Water transparency was measured using a Secchi disk. For physiological measurements, leaves and roots were sampled from a ramet in each tray (i.e., n = 3 for each depth and substrate combination). A previously unsampled ramet was collected from each tray at the end of the experiment for measuring the leaf length and number (n = 3 for each depth and substrate combination).</ns0:p><ns0:p>Water chemistry and biochemical measurements Concentrations (mg/L) of N and P were determined according to the Surface Water Environment Quality Standard <ns0:ref type='bibr'>(GB 3838-2002</ns0:ref><ns0:ref type='bibr'>) (State Environmental Protection Administration 2002)</ns0:ref>. TN and TP were determined by ultraviolet spectrophotometry and the molybdenum blue method, respectively, after digestion of sampled water. Inorganic N (NH 4 + -N, NO 3 -N, NO 2 --N) was determined by Nessler's reagent spectrophotometry and ultraviolet spectrophotometry. Chemical oxygen demand (COD) was determined using the potassium dichromate method.</ns0:p><ns0:p>Collected leaves and roots were cut, the surface water was removed using a paper, and the samples were then weighed to obtain the fresh weight. Approximately 2 g of samples were used for evaluating plant health and stress parameters. The Chl content was measured following <ns0:ref type='bibr' target='#b1'>Arnon (1949)</ns0:ref>. Leaf samples were ground and homogenized with 80% acetone, CaCO 3 , and quartz sand and then centrifuged at 12 000 &#215; g for 10 min. The supernatant was collected, and its absorbance was measured at 645 and 663 nm. The concentrations of Chl-a and Chl-b were calculated using the following equations: Chl-a = 12.7A 663 -2.69A 645 Chl-b = 22.9A 645 -4.68A 663 The concentrations were then converted to mg per unit g of leaf fresh weight.</ns0:p><ns0:p>The MDA content was measured following <ns0:ref type='bibr' target='#b14'>Heath and Packer (1968)</ns0:ref>. Leaf or root samples were ground and homogenized with 5% trichloroacetic acid and quartz sand and then centrifuged at 12 000 &#215; g at 4&#176;C for 10 min. Thiobarbituric acid (2%) was added to the resulting supernatant and the solution was then heated in boiling water for 15 min. After cooling to 20&#176;C, the solution was again centrifuged at 15 000 &#215; g for 10 min. The supernatant was collected and its absorbance was measured at 450, 532, and 600 nm. The concentration of MDA was calculated using the following equation: MDA = 6.45(A 532 -A 600 ) -0.56A 450 The concentrations were then converted to nmol per unit g of tissue fresh weight.</ns0:p><ns0:p>Prior to the measurement of enzyme activities (SOD, CAT, and POD), the leaf or root samples were ground and homogenized with 50 mM sodium phosphate buffer solution (pH 7.0) and quartz sand and centrifuged at 12 000 &#215; g at 4&#176;C for 20 min. The supernatant was collected immediately for enzyme activity measurements.</ns0:p><ns0:p>The SOD activity was assayed following <ns0:ref type='bibr' target='#b4'>Beauchamp and Fridovich (1971)</ns0:ref> and <ns0:ref type='bibr' target='#b21'>Li et al. (2002)</ns0:ref>. The reaction solution was prepared by adding 0.1 mL each of 8 mM hydroxylammonium chloride, 3.0 mM EDTA-2Na, 0.15% (w/v) bovine serum albumin (BSA), 8 mM xanthene, and the enzyme extract to 1 mL phosphate buffer (50 mM, pH 7.8). After adding 0.1 mL of xanthine oxidase, the reaction solution was heated for 40 min at 30&#176;C. One milliliter each of l mL of 20 mM sulfanilic acid and l0 mM N-(1-naphthyl)ethylenediamine dihydrochloride were added to the resulting solution, which was then incubated at 25&#176;C for 20 min, and the absorbance was measured at 545 nm. One unit of SOD activity was defined as the amount of enzyme required for 50% inhibition of absorbance reduction.</ns0:p><ns0:p>The CAT activity was assayed following <ns0:ref type='bibr' target='#b9'>Greenfield and Price (1954)</ns0:ref>. The production of O 2 from a reaction solution containing 2 mL of 50 mM phosphate buffer (pH 7. 0), 1 mL of the enzyme extract, and 2 mL of 3% H 2 O 2 was measured by volumetry at normal pressure and 24&#176;C for 1 min. A unit of CAT activity was calculated by assuming 1 cm 3 of O 2 as equivalent to 0.041 mmol.</ns0:p><ns0:p>The POD activity was measured following <ns0:ref type='bibr' target='#b18'>Kochba et al. (1977)</ns0:ref>. A 3 mL of a mixture of 50 mM phosphate buffer (pH 7. 0) and 20 mM guaiacol was added to 0.5 mL of the enzyme extract to prepare the reaction solution. After adding 0.2 mL of 8 mM H 2 O 2 , the absorbance was measured at 470 nm for 1 min.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical tests</ns0:head><ns0:p>In the laboratory experiment, a split-plot analysis of variance (ANOVA) was performed for leaf Chl-a and Chl-b contents, with substrate (mud, sand) and experiment time <ns0:ref type='bibr'>(10, 20, 30, 40, 50 d)</ns0:ref> as fixed factors and aquarium (n = 3 for each substrate) as a random factor. The contents of MDA, SOD, CAT, and POD in leaves and roots were analyzed by adding sampled organ (leaf, root) as a fixed factor in the ANOVA. Welch's two-sample t-test was used to assess differences in the length and number of leaves between mud and sand collected at the end of the experiment (n = 3 for each substrate).</ns0:p><ns0:p>In the field experiment, a split-plot ANOVA was performed for leaf Chl-a and Chl-b contents with depth (0.5, 1.2, 2.0 m), substrate (mud, sand), and experiment time <ns0:ref type='bibr'>(5, 10, 20, 30 d)</ns0:ref> as fixed factors and tray (n = 3 for each depth and substrate combination) as a random factor. The contents of MDA, SOD, CAT, and POD were analyzed by adding sampled organ (leaf, root) as a fixed factor in the ANOVA. We focused mainly on the effects of substrate and depth, and their interaction with other factors to determine if the effects of substrate or depth varied according to other factors. A two-way ANOVA was done for the length and number of leaves with depth and substrate as fixed factors (n = 3 for each depth and substrate combination). Spatio-temporal variation in water quality was also analyzed as a background condition of the experiment. A two-way ANOVA with depth (0.5, 1.2, 2.0 m) and experiment time (5, 10, 20, 30 d) as factors and without replication was performed for variables measured by the water quality meter (temperature, pH, DO, oxidation-reduction potential: ORP, EC, turbidity, and Chl-a concentration), light quantum, nutrients (TN, TP, NH 4 + -N, NO 3 --N, and NO 2 --N), and COD of the water samples. For variables measured by the water quality meter, data of the nearest five depths were averaged for each depth (0.5, 1.2, 2.0 m) on each experimental day. For all tests, an &#945; value of 0.05 was used to determine the significance of effects. All statistical analyses were performed in R (version 3.6.3; R Development Core Team, Vienna, Austria), with 'lme4' and 'lmerTest' packages.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head><ns0:p>Laboratory experiment A temporal change was detected in the leaf Chl-a content (mg/g), and the effect of the experiment time was significant (Fig. <ns0:ref type='figure'>3</ns0:ref>, Table <ns0:ref type='table'>1</ns0:ref>). The Chl-a content increased slightly from 0 to 10-20 d and then decreased. The decrease from 10-20 d to the end of the experiment was greater in aquaria with sand than mud, and the effects of substrate and time&#215;substrate interaction were significant. Consequently, the Chl-a content at 50 d was 19% increase from its 0 d for the mud, and it was 9% decrease from its 0 d for the sand.</ns0:p><ns0:p>Temporal changes in the Chl-b content were relatively small when compared to those in the Chl-a content. However, some patterns were similar to those observed for the Chl-a content, such as significantly higher for mud than for sand, and a significant effect of time&#215;substrate interaction (Fig. <ns0:ref type='figure'>3</ns0:ref>, Table <ns0:ref type='table'>1</ns0:ref>).</ns0:p><ns0:p>The MDA content (nmol/g) of both leaves and roots increased at the beginning of the experiment and then decreased, and it was significantly higher in leaves than in roots (Fig. <ns0:ref type='figure'>4</ns0:ref>, Table <ns0:ref type='table'>1</ns0:ref>). The MDA content decreased visibly after 30 d for leaves, while it decreased steadily after 10 d for roots, and the effect of time&#215;organ interaction was significant. The MDA content of leaves was higher in aquaria with mud than sand, whereas an opposite pattern was observed for roots, and the effect of organ&#215;substrate interaction was significant. The decline in MDA content from 30 to 50 d was steeper for mud than for sand. Consequently, the MDA content at 50 d was 17% (leaves) or 5% (roots) decrease from its 0 d for the mud, and it was 8% (leaves) or 52% (roots) increase from its 0 d for the sand.</ns0:p><ns0:p>The SOD activity (unit/g) increased after 10 d in leaves, whereas it changed less throughout the experiment in roots, and the effect of time&#215;organ interaction was significant (Fig. <ns0:ref type='figure'>4</ns0:ref>, Table <ns0:ref type='table'>1</ns0:ref>). As a consequence, the SOD activity in leaves exceeded that in roots from 20 d onwards. The SOD activity in leaves changed less after 30 d. No significant difference was detected in the SOD activity between the two substrates.</ns0:p><ns0:p>The CAT activity (H 2 O 2 nmol/g/min) of both leaves and roots increased at the beginning of the experiment and then gradually decreased, and the effect of time was significant (Fig. <ns0:ref type='figure'>4</ns0:ref>, Table <ns0:ref type='table'>1</ns0:ref>). The CAT activity was significantly higher in leaves than in roots throughout the experiment. No significant difference was detected in the CAT activity between the two substrates. The CAT activity at 50 d was 27-54% increase from its 0 d in leaves, and it was 5-10% decrease from its 0 d in roots.</ns0:p><ns0:p>The POD activity (A 470 /g/min) of both leaves and roots increased at the beginning of the experiment and then gradually decreased, and the effect of time was significant (Fig. <ns0:ref type='figure'>4</ns0:ref>, Table <ns0:ref type='table'>1</ns0:ref>). The POD activity was significantly higher in roots than in leaves throughout the experiment. The POD activity in roots was higher for sand than for mud throughout the experiment, whereas the difference between the two substrates remained unclear in leaves, and the effect of organ&#215;substrate was significant. The POD activity at 50 d was 28-55% decrease from its 0 d in leaves, while it was 120-125% increase from its 0 d in roots.</ns0:p><ns0:p>Ramets grew well in aquaria with water and mud from the pond (Fig. <ns0:ref type='figure'>5</ns0:ref>). The leaf length (cm) increased from 27.8 cm (&#177;2.0 SD, n = 3) before the experiment to 47.4 cm (&#177;2.9 SD) and 38.8 cm (&#177;3.6 SD) in aquaria with mud and sand, respectively, at the end of the experiment (Welch's two-sample t-test, t = -2.720, df = 3.224, p = 0.067). The leaf number per ramet increased from 13.3 (&#177;1.2 SD, n = 3) before the experiment to 45.0 (&#177;2.4 SD, n = 3) and 35.7 (&#177;4.2 SD, n = 3) in aquaria with mud and sand, respectively, at the end of the experiment (Welch's two-sample t-test, t = -2.521, df = 3.124, p = 0.083). Thus, the growth of V. natans was greater for mud than for sand.</ns0:p><ns0:p>The water quality of aquaria also changed during the experiment. For example, pH increased from 8.3 before the experiment to 9.2 and 9.4, and DO (mg/L) increased from 2.04 to 9.11 and 10.02 in aquaria with mud and sand, respectively, at the end of experiment. Such an increase was expected as a result of plant photosynthesis, which involves consumption of CO 2 and production of O 2 . On the other hand, the concentrations of N and P had decreased after the experiment. For example, TN (mg/L) decreased from 8.59 to 2.34 (&#177;0.65 SD) and 1.83 (&#177;0.52 SD), and TP (mg/L) decreased from 0.11 to 0.078 (&#177;0.017 SD) and 0.071 (&#177;0.010 SD) for mud and sand, respectively. The reduction of N and P in the water seems to be associated with nutrient uptake by V. natans. TN and TP were slightly higher for mud, which originally contained nutrients, than for sand.</ns0:p></ns0:div> <ns0:div><ns0:head>Field experiment</ns0:head><ns0:p>The water quality of the pond varied among the sampling days (Table <ns0:ref type='table'>S1</ns0:ref>). For example, at 0.5 m depth, the water temperature, pH, DO, Chl-a concentration, and turbidity varied from 21.7 to 25.0&#176;C, 7.9 to 8.3, 6.4 to 10.0 mg/L, 28.1 to 62.9 mg/L, and 34.8 to 75.8 NTU, respectively. In contrast, the water quality exhibited less variation among 0.5 m, 1.2 m, and 2.0 m depths at each day. For example, at 0 d, the water temperature and pH at all depths were 21.7&#176;C and 8.2, respectively, DO, Chl-a concentration, and turbidity varied from 9.9 to 10.0 mg/L, 62.9 to 70.4 mg/L, and 44.9 to 48.6 NTU, respectively. Similarly, the COD (range: 24-77 mg/L), TN (5.63-9.65 mg/L), TP (0.36-0.64 mg/L) varied among days, but they exhibited less variation among the three depths at each day.</ns0:p><ns0:p>The light quantum (&#956;mol/m 2 s) at each depth also exhibited temporal variation (Fig. <ns0:ref type='figure'>6</ns0:ref>). In addition, it decreased with increasing depth every day, declining to almost half and less than onetenth from the depth of 0.5 m (mean: 79.3 &#956;mol/m 2 s) to 1.2 m (38.3 &#956;mol/m 2 s) and 2.0 m (6.7&#956;mol/m 2 s), respectively. Water transparency gradually increased from 0.25 to 0.30 m during the experiment (Table <ns0:ref type='table'>S1</ns0:ref>). Rainy days were more frequent in the latter half of the experiment, with a maximum daily rainfall of 42.2 mm and total rainfall of 208 mm during the experiment (Fig. <ns0:ref type='figure' target='#fig_0'>S1</ns0:ref>).</ns0:p><ns0:p>The leaf Chl-a content (mg/g) declined sharply at the beginning of the experiment, particularly at the depths of 1.2 and 2.0 m (Fig. <ns0:ref type='figure'>7</ns0:ref>). The change in Chl-a content after 10 d differed depending on the water depth, and the effects of time and time&#215;depth interaction were significant (Fig. <ns0:ref type='figure'>7</ns0:ref>, Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). After 10 d, the Chl-a content increased slightly at the depth of 0.5 m, whereas it declined steadily at 1.2 and 2.0 m. The Chl-a content decreased with increasing depth, and the effect of depth was significant. However, no clear difference was observed between mud and sand. The Chl-b content also decreased with increasing depth, and the difference between mud and sand remained unclear (Fig. <ns0:ref type='figure'>7</ns0:ref>, Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>).</ns0:p><ns0:p>The MDA content (nmol/g) of leaves increased 2-to 3-fold during the experiment, whereas the content of roots changed less, and the effects of time and time&#215;organ interaction were significant. The MDA content was significantly higher in leaves than in roots throughout the experiment (Fig. <ns0:ref type='figure'>8</ns0:ref>, Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). The MDA content was also significantly higher in deeper positions, and significantly higher for sand than for mud. Consequently, the MDA content of leaves and roots at 30 d was the lowest for mud at 0.5 m.</ns0:p><ns0:p>The SOD activity (unit/g) of leaves and roots increased at the beginning of the experiment at all depths. However, the change of the SOD activity in the latter half of the experiment differed depending on the depth (Fig. <ns0:ref type='figure'>8, Table 2</ns0:ref>); during this period the SOD activity at 0.5 and 1.2 m increased continuously but slowly, whereas that at 2.0 m decreased, and the effects of time and time&#215;depth interaction were significant. At 0.5 and 1.2 m, the SOD activity increased 3-to 4-fold and 2-to 3-fold during the experiment in leaves and in roots, respectively, and the effects of organ, time&#215;organ interaction, and organ&#215;depth interaction were significant. In addition, the SOD activity was significantly higher for mud than for sand, particularly in roots at 0.5 and 1.2 m depths, and the effects of substrate and time&#215;substrate, organ&#215;substrate, and depth&#215;substrate interactions were significant.</ns0:p><ns0:p>The CAT activity (H 2 O 2 nmol/g/min) of leaves and roots increased at the beginning of the experiment at all depths. However, the change of the SOD activity in the latter half of the experiment differed depending on the depth (Fig. <ns0:ref type='figure'>8</ns0:ref>, Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>); during this period, the CAT activity at 0.5 and 1.2 m increased continuously but slowly, whereas that at 2.0 m decreased. This pattern was similar to that of the SOD activity. The difference in the CAT activity between leaves and roots remained unclear. The CAT activity was significantly higher for sand than for mud.</ns0:p><ns0:p>The POD activity (A 470 /g/min) of leaves and roots increased slightly at 0.5 and 1.2 m during the experiment, whereas it increased sharply at the beginning of the experiment and then decreased at 2.0 m depth, and the effects of time and time&#215;depth interaction were significant (Fig. <ns0:ref type='figure'>8</ns0:ref>, Table <ns0:ref type='table' target='#tab_1'>2</ns0:ref>). The POD activity was significantly higher in leaves than in roots, whereas no significant difference was observed between mud and sand.</ns0:p><ns0:p>The ramets of V. natans did not exhibit an apparent increase in the length and number of leaves during the experiment (Fig. <ns0:ref type='figure'>9</ns0:ref>); they rather decreased at 1.2 m and 2.0 m depths. The length and number of leaves tended to decrease with increasing water depth, and were less for sand than for mud, but due to a variation among trays a significant effect was detected only for depth and depth&#215;substrate interaction on leaf number (depth: df = 2, F = 24.4, p &lt; 0.001; substrate: df = 1, F = 3.56, p = 0.071; depth&#215;substrate: df = 2, F = 5.06, p = 0.015). The leaves of ramets at 0.5 m were completely green, but some leaf apices were flat (i.e., not acute like before the experiment), resembling being cut by animals in the pond (e.g., fish, birds). The leaves of ramets at 1.2 m were only partially green, and the leaves at 2.0 m were light brown, indicating senescence.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>In the present study, we examined the growth and physiological status of V. natans under the water and mud conditions of an urban pond using laboratory and field experiments. Plant physiological status was assessed using photosynthetic pigments, Chl-a and Chl-b, as plant health indicators, and a lipid peroxidation product, i.e., MDA, and antioxidant enzymes, including SOD, CAT, and POD, as stress indicators. Ramets grew well in the laboratory and physiological status differed less between 0 and 50 d of the experiment in both mud and sand. Thus, the water of the pond, which is more or less polluted due to urban human activities, is unlikely to directly or adversely affect V. natans. High N and P concentrations can have toxic effects on V. natans <ns0:ref type='bibr' target='#b6'>(Cao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b34'>, Wang et al. 2008</ns0:ref>). However, N and P concentrations in water decreased during our laboratory experiment, which is likely to be associated with nutrient uptake and growth of V. natans. We also revealed that the growth and physiological status of V. natans were better with mud than with sand as a substrate. Thus, although the mud of the pond was rich in organics, an adverse effect of such mud on submerged plants <ns0:ref type='bibr' target='#b3'>(Barko and Smart 1986</ns0:ref><ns0:ref type='bibr' target='#b37'>, Wu et al. 2009</ns0:ref><ns0:ref type='bibr'>, Silveila and Thomaz 2015)</ns0:ref> was not evident in this study. We used sand, which was free of organic matter, as the control substrate. Substrate type and nutrient contents are considered to be important for the nutrient acquisition by the roots of V. natans <ns0:ref type='bibr' target='#b41'>(Xie et al. 2005</ns0:ref><ns0:ref type='bibr' target='#b39'>, Xiao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b2'>, Bai et al. 2015)</ns0:ref>. Although high N and P concentrations in water possibly compensate for a low nutrient content in substrate, sand may be less suitable than natural mud or clay for roots to adjust and acquire nutrients. Further studies using different substrates, such as mud in oligotrophic lakes, are required to examine the suitability of the mud from eutrophic ponds for transplanting V. natans.</ns0:p><ns0:p>The adverse effects of water depth and reduced light availability on V. natans were evident in the field experiment. The leaf number of ramets decreased with increasing depth at the end of the experiment. Moreover, the Chl-a and Chl-b contents of leaves decreased, and the MDA content of leaves and roots increased with increasing water depth. Interestingly, the activities of antioxidant enzymes, SOD, CAT, and POD, increased at the beginning of the experiment and then decreased at 2.0 m depth. This was likely due to the oxidative damage caused by excessive production of ROS under low-light conditions at this depth. Such a deterioration of enzyme activity has been reported for V. natans exposed to lead <ns0:ref type='bibr' target='#b47'>(Yan et al. 2006</ns0:ref><ns0:ref type='bibr'>, Wang et al. 2012)</ns0:ref>. Light availability is the important factor that varies vertically in the study pond. A sharp decline in light availability with increasing depth was detected in this study; the light quantum was reduced by 50% and 90% from 0.5 m to 1.2 and 2.0 m, respectively. <ns0:ref type='bibr' target='#b2'>Bai et al. (2015)</ns0:ref> also reported a 62% and 99% reduction in the light quantum from the surface to 0.6 and 1.8 m in an experimental pond, respectively. Such a sharp attenuation in light availability is typical of eutrophic ponds and lakes <ns0:ref type='bibr' target='#b16'>(Hodoki and</ns0:ref><ns0:ref type='bibr'>Watanabe 1998, De Lange 2000)</ns0:ref>. On the other hand, only small differences were detected in the vertical profile of water quality, including temperature, DO, and N and P concentrations, in this pond. These results suggest that V. natans experiences strong stress at greater depths in this pond due to light depletion, which impedes photosynthesis. Most area inside the study pond was near or greater than 2.0 m deep, at which the growth of V. natans is likely to be inhibited.</ns0:p><ns0:p>Light availability, which is regulated by water depth and transparency, has been identified as the main factor limiting the distribution of submerged plants including V. natans <ns0:ref type='bibr' target='#b33'>(Voesenek et al. 2006</ns0:ref><ns0:ref type='bibr' target='#b2'>, Bai et al. 2015</ns0:ref><ns0:ref type='bibr'>, Dong et al. 2014</ns0:ref><ns0:ref type='bibr' target='#b11'>, Han and Cui 2016)</ns0:ref>. The optimal water depth for the growth of V. natans has been reported as 100-160 cm in an oligotrophic lake <ns0:ref type='bibr'>(Xiao et al. 2017)</ns0:ref>, in which water transparency and light availability were high. However, a steep light attenuation with increasing depth in eutrophic lakes and ponds is likely to limit the distribution of V. natans to shallow areas. <ns0:ref type='bibr' target='#b11'>Han and Cui (2016)</ns0:ref> used the ratio of transparency to water depth as an indicator of eutrophication pressure on macrophyte communities. They suggested that the ratio should be no less than 0.52 to restore submerged species in eutrophic ponds. Based on this criterion, and because the maximum transparency in our study pond was 0.3 m, shallow area less than 0.58 m deep are required to restore submerged plants. Although a deterioration of enzyme activity was not observed at 0.5 and 1.2 m in this study, V. natans is unlikely to be able to tolerate low light stress for a long period. Less growth, reduced Chl contents, and increased level of stress indicators of V. natans even at 0.5 m in this study may suggest that 0.5 m or shallower areas are required for the growth of this plant in this pond. However, too shallow area may be unsuitable for V. natans, which is originally adapted to habitats deeper than 1 m <ns0:ref type='bibr' target='#b39'>(Xiao et al. 2007</ns0:ref><ns0:ref type='bibr' target='#b20'>, Li et al. 2020)</ns0:ref>, to grow vertically well in the water column. Because we examined limited depths deeper than 0.5 m in the field, further studies are needed to clarify the suitability of such shallow areas for the growth and survival of V. natans in eutrophic ponds.</ns0:p><ns0:p>The strong effect of depth on V. natans might have obscured the differences between mud and sand in the field experiment. Differences in growth and leaf Chl-a and Chl-b contents between mud and sand, which were observed in the laboratory experiment, were not detected in the field experiment. The MDA content and CAT activity of leaves and roots were higher for sand than for mud in the field, which were not detected in the laboratory experiment. Although there are different results between the experiments, the results of field study suggest that the mud of the pond is unlikely to be a limiting factor in the establishment of V. natans.</ns0:p><ns0:p>Sufficient light and low nutrient concentrations in water were more advantageous to the ramets in the laboratory than to those in the field. The growth and physiological status of leaves and roots were obviously better in the laboratory than in the field, evident from the increase in length and number of leaves, lesser decrease in the Chl-a and Chl-b contents, and lesser increase in the MDA content and antioxidant enzyme activities. The MDA content and activities of antioxidant enzymes, except SOD, declined after a small increase in the early stages of the laboratory experiment. The decline of these indices to the initial or even smaller values at the end of the experiment may indicate ramets acclimatization to the aquaria environment. The mean light quantum at 0.5 m depth (79.3 &#956;mol/m 2 s) was similar to the intensity of light in the incubator (70-80 &#956;mol/m 2 s). However, the light quantum would be smaller inside the meshed cages used to grow ramets in the field. Although the nutrient concentration was initially similar between the aquaria and pond, nutrient uptake by ramets substantially reduced the nutrient concentration in the aquaria at the end of the experiment. High nutrient concentrations can adversely affect V. natans, both directly and indirectly, by promoting epiphytic algal growth on V. natans <ns0:ref type='bibr' target='#b32'>(Song et al. 2015)</ns0:ref>. Ramets in the field were also at a risk of grazing by animals such as birds and fish. Some leaf apices of V. natans were flat, likely to have been eaten partially by pond animals. This was supported by a chance observation of a fish feeding on V. natans collected in a bucket (personal observation). The better growth and physiological status of ramets in the laboratory than in the field may be partially associated with the absence of predator and hydrologic disturbance in the former. Present study is inadequate to show the importance of water depth and light on V. natans across different seasons and life stages, and how physical disturbances can modify the depth related responses of V. natans.</ns0:p><ns0:p>Previous studies have shown increased MDA content in V. natans growing under salinity, lead, and ammonia stress <ns0:ref type='bibr' target='#b34'>(Wang et al. 2008</ns0:ref><ns0:ref type='bibr' target='#b12'>, Hao et al. 2011</ns0:ref><ns0:ref type='bibr' target='#b19'>, Li et al. 2011</ns0:ref><ns0:ref type='bibr' target='#b32'>, Song et al. 2015)</ns0:ref>. In our study, the MDA content was higher with increasing depth. The accumulation of MDA eventually inactivates the enzymes associated with photosynthesis, respiration, and other metabolic processes in plant cells <ns0:ref type='bibr' target='#b32'>(Song et al. 2015)</ns0:ref>. Of the three enzymes analyzed in this study, SOD showed the strongest response, in terms of the magnitude of changes in both laboratory and field experiments. SOD converts O 2into O 2 and H 2 O 2 in the first step of ROS removal <ns0:ref type='bibr' target='#b0'>(Apel and</ns0:ref><ns0:ref type='bibr'>Hirt 2004, Rahnama and</ns0:ref><ns0:ref type='bibr' target='#b28'>Ebrahimzadeh 2005)</ns0:ref>. On the other hand, POD exhibited the fastest response (i.e., stopped increasing the earliest) among the enzymes in both laboratory and field experiments. Both POD and CAT convert H 2 O 2 into H 2 O and O 2 <ns0:ref type='bibr' target='#b5'>(Bowler et al. 1992</ns0:ref>). Responses of these enzymes varied depending on the study <ns0:ref type='bibr' target='#b47'>(Yan et al. 2006</ns0:ref><ns0:ref type='bibr' target='#b12'>, Hao et al. 2011</ns0:ref><ns0:ref type='bibr' target='#b19'>, Li et al. 2011</ns0:ref><ns0:ref type='bibr'>, Wang et al. 2012)</ns0:ref>, and further studies are required to generalize the response of each enzyme.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>We demonstrated important factors on the growth and physiological status of V. natans in eutrophic urban ponds using laboratory and field experiments. Sufficient light availability is required for better physiological status of the species. Owing to the sharp attenuation of light with increasing depth, shallow areas less than 1 m deep and improved water transparency are fundamental requirements for successful re-introduction of V. natans in eutrophic ponds. Despite the anaerobic conditions prevailing in the mud at the pond bottom, no adverse effects were detected on V. natans in the present study. Thus, it is suggested that the current status of the bottom mud does not directly inhibit the growth of submerged species. However, it can indirectly affect growth by releasing nutrients in the water column, which, in turn, can induce algal blooms. Efforts to reduce the nutrient load are also important to limit the phytoplankton overgrowth, and thus, to maintain transparency and ensure light availability to submerged plants. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>Results of the split-plot-design analysis of variance (ANOVA) that show the effect of each factor on the physiological indices in the field experiment Significance of effects are shown by asterisks ( results of the interaction among three or more variables were omitted). Organ and interaction of organ and other factors were not included in the ANOVA for Chl-a and Chl-b PeerJ reviewing PDF | (2020:04:48470:2:0:NEW 23 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='20,42.52,199.12,525.00,178.50' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:04:48470:2:0:NEW 23 Sep 2020)</ns0:note> <ns0:note place='foot' n='2'>PeerJ reviewing PDF | (2020:04:48470:2:0:NEW 23 Sep 2020)</ns0:note> </ns0:body> "

"Dear Prof. Jörg Oehlmann, Academic Editor, PeerJ Thank you very much for handling our manuscript and for the grateful decision. We also thank the reviewer for reading through our manuscript again and for giving suggestions. We improved our manuscript following the suggestion. We hope the changes in manuscript and our responses are sufficient for the requirements given by the reviewer. Sincerely, Sohei Kobayashi On behalf of all authors. Reviewer 2 (Anonymous) Comments for the Author The authors have made substantial changes according to my comments and addressed all my questions. I am generally satisfied with the revised version. The only question is that authors investigated the physiological status of V. natans in response to substrate type and water depth (two factors) in the field experiment, but they only compared the physiological responses of V. natans between two substrate types (one factor) in laboratory experiment. The two experiments can not be well matched and complement each other. The authors should notice the limitation. Thank you very much for reading many times and for your suggestion. Because we initially focused more on effects of eutrophic mud on V. natans, our study has limitation that the effect of depth was confirmed only in a single field experiment, as mentioned by the reviewer. We tried to organize Discussion so that the laboratory and field experiment complement each other. After the comments of the previous review, we separated paragraphs for laboratory and field experiments at the beginning of Discussion, and then compared between them and explained some of the differences between the experiments. Study limitation about effects of substrate was mentioned after comments by the previous review. After the comment this time, we added study limitations about effects of light in Discussion as “Because we examined limited depths deeper than 0.5 m in the field, further studies are needed to clarify the suitability of such shallow areas for the growth and survival of V. natans in eutrophic ponds.” (Line 419-), and “Present study is inadequate to show the importance of water depth and light on V. natans across different seasons and life stages, and how physical disturbances can modify the depth related responses of V. natans.” (Line 448-). We also made changes in site description about chemical properties of mud (Line 118-119), because we noticed that the previous values (that we measured after the previous comments by the reviewer) were too low for this site, and we analyzed again with a help of a professional analytical person this time to obtain correct values. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>A dwarf, multi-pistil and male sterile dms mutant was previously reported by us. However, the genetic changes in this dms are unclear. To examine the genetic changes, single nucleotide polymorphism (SNP) association, chromosome counting, and high-resolution chromosome fluorescence in situ hybridization (FISH) techniques were employed. By comparing tall plants (T) with dwarf plants (D) in the offspring of dms mutant plants, SNP association analysis indicated that most SNPs were on chromosome 2A. There were 3 types in offspring of dms plants, with 42, 41 and 40 respectively. High-resolution chromosome painting analysis demonstrated that T plants had all 42 wheat chromosomes; the medium plants (M) had 41 chromosomes, lacking one chromosome 2A; while D plants had 40 wheat chromosomes, and lacked both 2A chromosomes. These data demonstrated that dms resulted from a loss of chromosome 2A. We identified 23 genes on chromosome 2A which might be involved in the development of stamens or pollen grains. These results lay a solid foundation for further analysis of the molecular mechanisms of wheat male sterility. Because D plants can be used as a female parent to cross with other wheat genotypes, dms is a unique germplasm for any functional study of chromosome 2A and wheat breeding specifically targeting genes on 2A.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Allohexaploid wheat (Triticum aestivum L., 2n = 6x = 42, genomic constitution AABBDD) has a genome from three diploid species: Triticum urartu Thum. (the source of the A genome), Aegilops speltoides (Tausch) Gren. or a closely related species (the source of the B genome), and Aegilops tauschii Coss. (the source of the D genome) <ns0:ref type='bibr' target='#b29'>(Huang et al., 2002)</ns0:ref>. Because allohexaploid wheat has high level of functional redundancy, it can host a range of diverse whole-chromosome aneuploids <ns0:ref type='bibr' target='#b78'>(Zhang et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b76'>Zhang et al., 2017)</ns0:ref>. There are various types aneuploid variations available in wheat, such as nulli-tetrasomic lines, nullisomic lines, monosomic lines, ditelosomic lines, as well as chromosome fragmental deletion lines <ns0:ref type='bibr' target='#b13'>(Endo &amp; Gill, 1996;</ns0:ref><ns0:ref type='bibr' target='#b53'>Qi et al., 2003)</ns0:ref>. The aneuploid stocks are useful in wheat gene mapping, and especially, genes can be located to a small segment using a series of chromosome fragmental deletion lines <ns0:ref type='bibr' target='#b13'>(Endo &amp; Gill, 1996;</ns0:ref><ns0:ref type='bibr' target='#b53'>Qi et al., 2003)</ns0:ref>. A set of homozygous chromosome deletion lines were obtained in cv. Chinese Spring <ns0:ref type='bibr' target='#b13'>(Endo &amp; Gill, 1996)</ns0:ref>. Most of the homozygous chromosome 2A short arm deletion lines are sterile; genes involved in male development are located on the chromosome 2A short arm <ns0:ref type='bibr' target='#b13'>(Endo &amp; Gill, 1996)</ns0:ref>.</ns0:p><ns0:p>Presently, at least five stable genic male sterility (GMS) genes are known in bread wheat. They are ms1 on 4BS <ns0:ref type='bibr' target='#b68'>(Wang et al., 2017)</ns0:ref>, Ms2 on 4DS <ns0:ref type='bibr' target='#b72'>(Xia et al., 2017)</ns0:ref>, Ms3 on 5AS <ns0:ref type='bibr' target='#b44'>(Maan et al., 1987)</ns0:ref>, Ms4 on 4DS <ns0:ref type='bibr' target='#b45'>(Maan &amp; Kianian, 2001</ns0:ref>) and ms5 on 3AL <ns0:ref type='bibr'>(Pallotta et al., 2019)</ns0:ref>, but the molecular regulation mechanisms of the male sterility lines are largely unknown.</ns0:p><ns0:p>Anther and pollen developments are complex biological processes, determining wheat male fertility. Pollen development starts from a single cell layer, which undergoes a series of cell divisions and differentiation to form the innermost meiocytes encased within four somatic anther cell layers; from inner to outer these are the tapetum, middle layer, endothecium and epidermis <ns0:ref type='bibr' target='#b77'>(Zhang &amp; Yang, 2014)</ns0:ref>. The tapetum serves as a nutritive tissue, providing metabolites, nutrients, and cell wall precursors for the development of pollen grains <ns0:ref type='bibr' target='#b20'>(Goldberg, Beals &amp; Sanders, 1993)</ns0:ref>. The regulatory genes involved in pollen exine patterning are known in Arabidopsis and rice <ns0:ref type='bibr' target='#b50'>(Pearce et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b41'>Lin et al., 2017)</ns0:ref>. For example, AtMS1 (Male Sterility 1) <ns0:ref type='bibr' target='#b70'>(Wilson et al., 2001)</ns0:ref>, AtDRL1 (Dihydroflavonol 4-Reductase-Like 1) <ns0:ref type='bibr' target='#b62'>(Tang et al., 2009)</ns0:ref>, AtLAP3 (Less Adherent Pollen 3) <ns0:ref type='bibr' target='#b10'>(Dobritsa et al., 2009)</ns0:ref>, AtLAP5 (Less Adherent Pollen 5) <ns0:ref type='bibr' target='#b9'>(Dobritsa et al., 2010)</ns0:ref> in Arabidopsis, and OsGAMYB (GA, gibberellin; MYB, v-myb avian myeloblastosis viral oncogene homolog) <ns0:ref type='bibr' target='#b0'>(Aya et al., 2009)</ns0:ref>, OsNP1 (No Pollen 1) <ns0:ref type='bibr' target='#b42'>(Liu et al., 2017)</ns0:ref>, OsDPW2 (Defective Pollen Wall 2) <ns0:ref type='bibr' target='#b73'>(Xu et al., 2017)</ns0:ref> in rice are involved in the biosynthesis of sporopollenin, which is a major constituent of exine in the outer pollen wall. However, pollen developmental studies in wheat have lagged behind these plants.</ns0:p><ns0:p>Previously, we reported a mutant of dwarf, multi-pistil and male sterile dms in wheat <ns0:ref type='bibr' target='#b12'>(Duan et al., 2015;</ns0:ref><ns0:ref type='bibr' target='#b82'>Zhu et al., 2016)</ns0:ref>. Pollen vigor and hybridization tests demonstrated that dms mutant was male sterile. Male sterility and male fertility followed a segregation ratio of 1:3 [D:(T+M)=1:3] (Duan et al., 2015). However, the genetic basis of this mutant is unknown. The present study is to discover the genetic basis at the cytological and molecular levels. We also identified a set of genes playing potential key roles accounting for male sterility on chromosome 2A.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Plant materials</ns0:head><ns0:p>Mutant dms used in this study was obtained as previously described by us <ns0:ref type='bibr' target='#b12'>(Duan et al., 2015)</ns0:ref>. All plant materials were planted in our experimental field at Houwang Village, Xingyang City, Henan, P. R. China (34&#176;51&#180;N, 113&#176;35&#180;E, 49 m above sea level). We have got permission prior to accessing the field site by Henan Seed Company, and the administrator's name is Haolong Yang.</ns0:p></ns0:div> <ns0:div><ns0:head>Morphological and histochemical observations</ns0:head><ns0:p>Phenotype of plants, young spikes and stamens of dms were observed at different developmental stages <ns0:ref type='bibr' target='#b75'>(Zadoks et al., 1974)</ns0:ref>. Developmental stages of the young spike primordia were referenced as previously described <ns0:ref type='bibr' target='#b63'>(Vahamidis et al., 2014)</ns0:ref>. The florets with anthers and pistils at different developmental stages were dissected from spikes using an anatomical needle. Anthers were observed using scanning electron microscope (SEM) (SU8010, Hitachi, Tokyo, Japan) as previously described <ns0:ref type='bibr' target='#b32'>(Jiao et al., 2019)</ns0:ref>. Structural and histochemical observation on the anthers of T and D plants were carried out using a method previously described by Geng et al. (2018).</ns0:p></ns0:div> <ns0:div><ns0:head>RNA Extraction and mRNA Sequencing</ns0:head><ns0:p>Young spikes of T, M and D plants at floret primordium visible stage (stage 7) <ns0:ref type='bibr' target='#b63'>(Vahamidis et al., 2014)</ns0:ref> and anthers of T and D plants at 3-nucleate pollen stage (stage 12) <ns0:ref type='bibr' target='#b3'>(Browne et al., 2018)</ns0:ref> were sampled for RNA extraction. All the five samples for mRNA sequencing had 3 biological replicates. Total RNAs of fifteen samples were extracted respectively with TRIzol &#174; reagent <ns0:ref type='bibr'>(TransGen Biotech, Beijing, China)</ns0:ref>. RNA sequencing and basic analysis were carried out in BioMarker Company (Beijing, China).</ns0:p></ns0:div> <ns0:div><ns0:head>mRNA Data Analysis</ns0:head><ns0:p>The mRNA reads of the fifteen samples were aligned to the draft assembly (IWGSC v1.0) of the wheat genome survey sequence (http://www.wheatgenome.org/) using Tophat2 tool software <ns0:ref type='bibr' target='#b33'>(Kim et al., 2013)</ns0:ref>. Reads distribution on 21 wheat chromosomes of T, M and D plants were analyzed and drawn using Circos tool software (http://mkweb.bcgsc.ca/tableviewer/). Gene functional annotation was carried out as previously described by us <ns0:ref type='bibr' target='#b25'>(He et al., 2018)</ns0:ref>. Gene expression levels were estimated by fragments per kilobase of transcript per million fragments mapped (FPKM) <ns0:ref type='bibr' target='#b15'>(Florea, Song &amp; Salzberg, 2013)</ns0:ref>. Differentially expressed genes (DEGs) between two sample groups were analyzed using DESeq R package <ns0:ref type='bibr' target='#b66'>(Wang et al., 2010)</ns0:ref>. The FDR &lt; 0.01 (false discovery rate) and FC &#8805; 2 were set as the thresholds for significantly DEGs.</ns0:p><ns0:p>Principal components were calculated using the FPKM values <ns0:ref type='bibr' target='#b57'>(Schulze et al., 2012)</ns0:ref>. For the single gene, heat maps were drawn using software Hem&#8544;v 1.0.3.7 according to the FPKM values. Tissue specific expression patterns of wheat genes were analyzed using k-means cluster on the BMKCloud platform (https://www.biocloud.net/). Clustering was performed in R using the k-means function, where k = 8 within the cluster package by Euclidean distance. Wheat tissue type, expression profile data sources and sample description in origin article <ns0:ref type='bibr' target='#b17'>(Garcia-Seco et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b14'>Feng et al., 2017;</ns0:ref><ns0:ref type='bibr' target='#b39'>Li et al., 2019)</ns0:ref> were listed in Table <ns0:ref type='table'>S1</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Single nucleotide polymorphism (SNP) association analysis</ns0:head><ns0:p>Clean reads data of the two bulks (young spikes of T and D plants) were selected for SNPs identification. After the reads were aligned to the Chinese Spring genome, the SNPs were called using module <ns0:ref type='bibr'>'HaplotypeCaller' software GATK v3.6 (McKenna et al., 2010)</ns0:ref>. Euclidean distance (ED) algorithm was used to calculate the grade of different SNPs between T and D plants <ns0:ref type='bibr' target='#b26'>(Hill et al., 2013)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Simple sequence repeat (SSR) analysis</ns0:head><ns0:p>Genomic DNAs of T, M and D plants were extracted from young leaves using cetyltrimethyl ammonium bromid (CTAB)-method <ns0:ref type='bibr' target='#b7'>(Clarke, 2009)</ns0:ref>. DNA concentration was measured with a DU800 Nucleic Acid Protein Analyzer (Beckman coulter, Fullerton, California, USA). SSR markers distributed on wheat chromosome 2A were used to analyze the genetic polymorphisms among T, M and D plants. SSR primers employed in this study included those of GWM <ns0:ref type='bibr' target='#b56'>(R&#246;der et al., 1998)</ns0:ref>, WMC <ns0:ref type='bibr' target='#b58'>(Somers, Isaac &amp; Edwards, 2004)</ns0:ref>, BARC <ns0:ref type='bibr' target='#b59'>(Song et al., 2005)</ns0:ref> and GPW <ns0:ref type='bibr' target='#b24'>(Gupta et al., 2002)</ns0:ref>. PCR amplification reactions were performed using a method previously described by Zhu et al. ( <ns0:ref type='formula'>2019</ns0:ref>). PCR products were separated on an 8% PAGE gel with a standard DNA molecular weight marker in the first lane of the gel. The products were run at 60 W for about 1.0 h. Then the gel was removed from the apparatus and stained using the silver staining method <ns0:ref type='bibr' target='#b40'>(Li et al., 2018b)</ns0:ref>. Primers used for SSR analysis are list in Table <ns0:ref type='table'>S2</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Cytological analysis</ns0:head><ns0:p>Chromosome configurations and high-resolution chromosome painting analysis of plants derived from M plants at metaphase of mitosis. Chromosome samples were prepared as previously described <ns0:ref type='bibr' target='#b11'>(Du et al., 2017)</ns0:ref>. For chromosome painting, eight single strand oligonucleotides were used to form a modified multiplex probes for karyotype analysis in wheat, which included TAMRA (6-carboxytetramethylrhodamine)-modified oligonucleotides pAs1-1, pAs1-3, pAs1-4, pAs1-6, AFA-3 and AFA-4, and two FAM (6-carboxyfluorescein)-modified oligonucleotides pSc119.2-1 and (GAA) 10 . Oligonucleotide probes used for FISH are list in Table <ns0:ref type='table'>S3</ns0:ref>. The FISH procedure was tested as previously described <ns0:ref type='bibr' target='#b11'>(Du et al., 2017)</ns0:ref>. Chromosomes were visualized with microscope Olympus BX51 and pictures were captured with SPOT CCD (SPOT Cooled Color Digital Camera). Image analysis was conducted using Photoshop v6.0.</ns0:p></ns0:div> <ns0:div><ns0:head>qRT-PCR for mRNAs</ns0:head><ns0:p>Anthers of T and D plants at 3-nucleate pollen stage were prepared for real-time PCR. The experimental samples were consistent with the samples of RNA-seq. The qRT-PCR was performed as previously described by us <ns0:ref type='bibr' target='#b25'>(He et al., 2018)</ns0:ref>. Reverse transcription was performed with 1 &#956;g RNA using Hifair &#174; &#8545; 1st Strand cDNA Synthesis SuperMix (11123ES60, Yeasen, Shanghai, China). Real-time PCRs of mRNAs were performed using Hieff &#174; qPCR SYBR Green Master Mix (1201ES08, Yeasen, Shanghai, China) and a CFX ConnectTM Real-Time System (Bio-Rad, Hercules, CA, USA) following the production instructions. The wheat actin gene was used as an internal control. All primer sequences are listed in Table <ns0:ref type='table'>S4</ns0:ref>. The gene expression levels were calculated according to the 2 &#8722;&#916;&#916;Ct method <ns0:ref type='bibr' target='#b43'>(Livak &amp; Schmittgen, 2001)</ns0:ref>. The SPSS version 17.0 software (SPSS Inc., Chicago, IL, USA) was applied for statistical analysis for the qRT-PCR.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Male abortion in D plants of dms</ns0:head><ns0:p>There were three typical phenotypes in the progeny of dms, tall (T), semi-dwarf (M) and dwarf (D) plants (Fig. <ns0:ref type='figure'>S1</ns0:ref>). D plants were male sterile according to the result of I 2 -KI staining <ns0:ref type='bibr' target='#b12'>(Duan et al., 2015)</ns0:ref>. To discover the morphological causes of the male abortion in D, scanning electron microscope was employed to observe the anther ultrastructure (Fig. <ns0:ref type='figure'>1</ns0:ref>). Unlike the fertile T plants, the anthers of D plants were not dehiscent at the trinucleate stage, and no mature pollen grains were released (Fig. <ns0:ref type='figure'>1A and 1B</ns0:ref>). The outer anther epidermal cells of T plants were arranged neatly, whereas these of D plants were irregular (Fig. <ns0:ref type='figure'>1C and 1D</ns0:ref>). Moreover, compared with the anthers of the T plants, the inner epidermal of D plants showed aberrant sized Ubisch bodies, which suggested a structural abnormality (Fig. <ns0:ref type='figure'>1E-1H</ns0:ref>). The pollen grains of T plants were plump and rounded; by contrast, the pollen grains of D plants were extremely shriveled and atrophied (Fig. <ns0:ref type='figure'>1I-1L</ns0:ref>). Furthermore, we performed a histological analysis of the anthers in the dms mutant and the wild type. In the initial stages of pollen development (Figure <ns0:ref type='figure'>S2A and S2B</ns0:ref>), there were no differences between the wild type and dms mutant. The young microspores were normal (Figure <ns0:ref type='figure'>S2C and S2D</ns0:ref>). However, compared with the wild type, degenerated pollen grains were observed in the dms mutant at 3-nucleate pollen stage (Figure <ns0:ref type='figure'>S2E and S2F</ns0:ref>).</ns0:p><ns0:p>The female organs in flowers of D plants developed unwell, most of the pistils were normal, a few were multi-pistils (Fig. <ns0:ref type='figure'>S3</ns0:ref>). D plants were male sterile but female fertile, it can be used as a female parent to cross with other wheat genotypes. We got F 1 seeds from dwarf plants (as female parent) crossed with Guomai 301 (as pollen parent) (Fig. <ns0:ref type='figure'>S4</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>The most SNPs were on chromosome 2A</ns0:head><ns0:p>In order to clarify the genetic changes in dms, SNP association analysis was carried out. A total of 176.73 Gb data were obtained from the five super bulked samples of dms by mRNA Sequencing: young spikes of T plants (T-YS; T1a, T1b, T1c) (Fig. <ns0:ref type='figure' target='#fig_1'>S5A</ns0:ref>), young spikes of M plants (M-YS; T2a, T2b, T2c) (Fig. <ns0:ref type='figure' target='#fig_1'>S5B</ns0:ref>), young spikes of D plants (D-YS; T3a, T3b, T3c) (Fig. <ns0:ref type='figure' target='#fig_1'>S5C</ns0:ref>), stamens of T plants (T-ST; T4a, T4b, T4c) (Fig. <ns0:ref type='figure' target='#fig_1'>S5D</ns0:ref>), stamens of D plants (D-ST; T5a, T5b, T5c) (Fig. <ns0:ref type='figure' target='#fig_1'>S5E</ns0:ref>). SNP association analysis indicated that the most SNPs between T and D plants were on chromosome 2A (Fig. <ns0:ref type='figure'>2</ns0:ref>). Total 523 SNPs were significantly different between T-ST and D-ST, ED&gt;0.33, in them, 230 were on chromosome 2A, which occupied 44% of the total SNPs (Fig. <ns0:ref type='figure' target='#fig_2'>S6</ns0:ref>; Table <ns0:ref type='table'>S5</ns0:ref>). The result implied that the mutation occurred on chromosome 2A. The results were consistent with the sequencing reads distribution on chromosome 2A of young spikes in T, M and D plants (Fig. <ns0:ref type='figure'>3</ns0:ref>). About 5.24% of the total reads was identified on chromosome 2A in T plants, which was about twice that of M plants (2.86%) (Table <ns0:ref type='table'>S6</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>SSR markers on chromosome 2A were polymorphic among tall, semidwarf and dwarf plants</ns0:head><ns0:p>In order to further verify that the genetic variation of dms occurred on chromosome 2A, eleven plants including three typical phenotypes of tall, semi-dwarf and dwarf were randomly selected for SSR genotyping. SSR markers evenly distributed across wheat A, B and D genomes were used to detect the polymorphism between tall and dwarf plants of dms. The result showed that all the primers specifically amplifying fragments on chromosomes 2A (Xgwm312, Xgpw2229, Xgwm95, Xgwm445, Xwmc794, Xgwm328, Xgwm425, Xbarc212 and Xbarc122) couldn't amplify the expected products in the dwarf plants of dms (Fig. <ns0:ref type='figure'>4</ns0:ref>; lane 4, 7, 9, 11), which implied that wheat chromosome 2A was missing in the dwarf plants.</ns0:p><ns0:p>The SSR markers were used to quantitatively amplify the DNA templates of tall, semi-dwarf and dwarf plants. The amounts of the amplified products of the tall plants (Fig. <ns0:ref type='figure'>4</ns0:ref>; lane 1, 3, 5, 8) were about double that of the semi-dwarf plants (Fig. <ns0:ref type='figure'>4</ns0:ref>; lane 2, 6, 10), and dwarf plants without PCR products (Fig. <ns0:ref type='figure'>4</ns0:ref>). In another word, the SSR primers specifically amplifying fragments on chromosomes 2A could be used to distinguish the T, M and D plants in the progeny of dms.</ns0:p></ns0:div> <ns0:div><ns0:head>Chromosome 2A was absent in D plants</ns0:head><ns0:p>To explore the chromosome number of dms, 42 plants derived from M plants were investigated. Among them, 17 plants had 42 chromosomes, 21 had 41 chromosomes and 4 had 40 chromosomes (Table <ns0:ref type='table'>1</ns0:ref>). After chromosome analysis, the seedlings were planted in field. The 17 plants with 42 chromosomes showed regular plant height, pistil and fertility, the 21 plants with 41 chromosomes showed medium plant height and regular pistil and fertility, while all the 4 plants with 40 chromosomes showed dwarf status, multi-pistil and complete male sterility (Fig. <ns0:ref type='figure' target='#fig_3'>S7</ns0:ref>).</ns0:p><ns0:p>To validate and identify the chromosome constitution of dms, high-resolution chromosome painting was applied using eight single strand oligonucelotide probes. The result showed that all 21 wheat homoeologous chromosome pairs can be reliably discriminated. Total 45 plants derived from M plants were clearly characterized, among them, 18 plants had 42 chromosomes and regular karyotypes (Fig. <ns0:ref type='figure' target='#fig_1'>5A and 5B</ns0:ref>), 20 plants had 41 chromosomes and lacked one chromosome 2A (Fig. <ns0:ref type='figure' target='#fig_1'>5C and 5D</ns0:ref>), while the remaining 7 plants had 40 chromosomes and lacked a pair of chromosomes 2A (Fig. <ns0:ref type='figure' target='#fig_1'>5E and 5F</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Chromosome 2A carries key genes determining fertility</ns0:head><ns0:p>We assessed the effects of several different chromosome 2As by making six crosses (Table <ns0:ref type='table'>2</ns0:ref>). At F 1 generation, all six crosses segregated into two phenotypes, tall plants (T) and Semi-dwarf plants (M). Combined with the data above, we knew that the genotypes of the cross Zhoumai 18 &#215; M at F 1 generation were 2A zhoumai18 2A dms and 2A zhoumai18 , the corresponding phenotypes were T and M plants. This demonstrated that the transmitting frequency of null-2A pollens was about half of the 2A pollens (Table <ns0:ref type='table'>2</ns0:ref>). All the T plants of the six crosses at F 1 generation didn't segregate at F 2 generation, but all M plants at F 1 generation segregated into T, M and D plants at F 2 generation. All M plants at F 2 also segregated into T, M and D plants at F 3 (Table <ns0:ref type='table'>2</ns0:ref>). The 2As played key roles during whole plant development in all the monosomic lines of 2As from Taishan 4429, Jing 08-426, Yangmai 11, Yuyou 1 and Guomai 301. These data demonstrated that the six different origin chromosomes 2As had the similar function as the chromosome 2A in dms. In addition, the heterozygous genetic backgrounds of the six crosses, including chromosomes 2Ds and 2Bs couldn't complement the effects of chromosome 2A. D plants were used as a female parent to cross with other wheat genotypes, so as to construct inter-cultivar chromosome 2A substitution lines (Fig. <ns0:ref type='figure'>S8</ns0:ref>). At F 1 generation, all the lines had one chromosome 2A, they were male fertile, which indicated chromosome 2A carries key genes determining male fertility.</ns0:p></ns0:div> <ns0:div><ns0:head>Stamen-specifically expressed genes on chromosome 2A</ns0:head><ns0:p>To identify the key genes determining fertility in wheat, 5939 genes located on chromosome 2A (TraesCS2A01G000100 -TraesCS2A01G593900) were analyzed. Total 4613 genes on chromosome 2A were identified and found to be homeologous to genes on other chromosomes (Table <ns0:ref type='table'>S7</ns0:ref>). Deletion of these genes on chromosome 2A might not affect the phenotype of D plants because of gene redundancy. Total 1326 2A-specific genes were identified (Table <ns0:ref type='table'>S8</ns0:ref>). Tissue specific expression analysis showed that 188 genes on chromosome 2A were stamen specifically expressed genes (Fig. <ns0:ref type='figure' target='#fig_2'>6A</ns0:ref>; Table <ns0:ref type='table'>S9</ns0:ref>). Venn diagram analysis showed that 23 genes were chromosome 2A specific and stamen specifically expressed genes (Fig. <ns0:ref type='figure' target='#fig_2'>6B</ns0:ref>; Table <ns0:ref type='table'>S9</ns0:ref>). Among them 6 genes were reported to be involved in pollen development related biological processes (Table <ns0:ref type='table'>3</ns0:ref>), they may be the key genes determining male fertility.</ns0:p></ns0:div> <ns0:div><ns0:head>DEGs involved in pollen development related signal transduction in dms</ns0:head><ns0:p>A total of 5199 genes were significantly differentially expressed (FC &#8805; 4) between stamens of T and D plants. Among them 4761 DEGs expressed less, only 438 DEGs expressed highly in D-ST (Table <ns0:ref type='table'>S10</ns0:ref>). Obviously, the expressions of most DEGs in D plants of dms were lower because lacking of the chromosome 2A. We identified 229 putative TF DEGs between T-ST and D-ST. They belonged to 47 TF families. The top three with the most number of DEGs were MYB, C2H2 zinc finger protein (C2H2) and APETALA 2/ethylene-responsive element binding factor (AP2/ERF) transcription factor families and most of them expressed less in D-ST (Table <ns0:ref type='table'>S11</ns0:ref>).</ns0:p><ns0:p>Totally 45 DEGs were associated with auxin homeostasis, such as biosynthesis, response, signaling and metabolism (Fig. <ns0:ref type='figure'>S9</ns0:ref>). Among auxin signal transduction-related genes, homologs of auxin response factor (ARF) genes and several auxin biosynthesis-related genes expressed less in D-ST. Reduced expression of auxin biosynthesis and signal transduction related genes were closely related to male sterility <ns0:ref type='bibr' target='#b61'>(Su et al., 2019)</ns0:ref>. Abnormality of auxin homeostasis might be a major factor leading to the phenotype of dms.</ns0:p></ns0:div> <ns0:div><ns0:head>DEGs involved in pollen development related metabolism in dms</ns0:head><ns0:p>Enrichment analysis of the DEGs between T-ST and D-ST revealed that most of them were involved in pollen development related metabolism such as the GO terms of 'lipid metabolism', 'cell wall biogenesis' and 'pollen development' (Fig. <ns0:ref type='figure' target='#fig_3'>7</ns0:ref>). Among lipid metabolism related genes, fatty acid biosynthetic related genes expressed less and lipid catabolic process related genes expressed highly in D-ST. Among cell wall biogenesis related genes, cell wall modification related genes expressed less and cellulose biosynthetic process related genes expressed highly in D-ST (Fig. <ns0:ref type='figure' target='#fig_3'>7</ns0:ref>). This indicated that fatty acid metabolic and cell wall assembly disorder might be the critical factors causing male sterility in dms.</ns0:p></ns0:div> <ns0:div><ns0:head>DEGs involved in abnormal pollen development of dms</ns0:head><ns0:p>The DEGs associated with various aspects of pollen development, such as pollen tube growth, pollen germination, megagametogenesis, anther dehiscence and anther wall tapetum formation, expressed less in D-ST (Fig. <ns0:ref type='figure' target='#fig_3'>7</ns0:ref>). A series of pollen development related genes were identified (Table <ns0:ref type='table'>4</ns0:ref>). The homologs of AtSAC1B and OsGAMYB involved in exine formation and AtAGC1.5, OsSUT1, AtRopGEF8, AtAGC1.7, AtFIM5 and etc. involved in pollen germination and pollen tube growth expressed less in D-ST (Table <ns0:ref type='table'>4</ns0:ref>). The qRT-PCR results showed that the expression patterns of the representative genes were well consistent with that of the sequencing results (Fig. <ns0:ref type='figure'>8</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>A hypothesis of the molecular regulatory network in dms wheat lines</ns0:head><ns0:p>In summary, we put forward a hypothesis on the molecular regulatory network in dms (Fig. <ns0:ref type='figure'>9</ns0:ref>). Several evidences support this hypothesis: (1) Chromosome 2A is absent in D plants (Fig. <ns0:ref type='figure'>4</ns0:ref>); (2) key genes involved in pollen development are identified on chromosome 2A in dms (Table <ns0:ref type='table'>3</ns0:ref>); and (3) fatty acid biosynthetic related genes expressed less and catabolic related genes expressed highly in dms (Fig. <ns0:ref type='figure' target='#fig_3'>7</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>Aneuploids are large scale mutations greatly affect cellular physiology and have significant phenotypic consequences <ns0:ref type='bibr' target='#b76'>(Zhang et al., 2017)</ns0:ref>. The typical phenotype of dms was significantly different from its parent Zhoumai 18 at three traits, plant height, pistil number and male fertility. Preliminary, this mutant was considered as a SNP mutation. Till the SNP association analysis showed that a large amount of SNPs between T and D plants, we thought their chromosomes should be clarified. High resolution chromosome painting is a new and efficient method for distinguishing chromosomes, which has many advantages including high sensitivity and resolution <ns0:ref type='bibr' target='#b11'>(Du et al., 2017)</ns0:ref>. Using this method, we successfully distinguished the karyotypes of D, M and T plants derived from M plants of mutant dms, and their phenotypes were corresponded with their chromosome constitutions. Now it was clear that the mutant dms was resulted from the absence of chromosome 2A. Our data showed that there were 23 2A-specific genes were highly expressed in stamen. However, it can't exclude other genes on 2A involved in pollen development also. In the case of wheat Ms1 gene on 4BS, it has homoeologs on 4A and 4D. Mutant ms1 is responsible for male sterile phenotype due to that homoeologous Ms1 on 4A and 4D were not expressed (due to methylation) <ns0:ref type='bibr' target='#b68'>(Wang et al., 2017)</ns0:ref>. Some genes in the list of 23 2A-specific genes could be candidates of key genes responsible for the male sterility, but not exclude other possibilities. The molecular regulatory network can be elucidated well till the key gene/genes have been investigated.</ns0:p><ns0:p>Endo and Gill reported a set of nullisomic, monosomic, trisomic and tetrasomic lines from Chinese Spring (CS) <ns0:ref type='bibr' target='#b13'>(Endo &amp; Gill, 1996)</ns0:ref>. Among them, the 2A nullisomic line could not be maintained for they were sterile in both sexes. However, a stable self-fertile 2A nullisomic line was obtained from common wheat 'Abbondanza'. Although the pistils and stamens of the 2A nullisomic line were fertile, its female flower organ developed unwell <ns0:ref type='bibr' target='#b74'>(Xue et al., 1991)</ns0:ref>. Different genetic backgrounds lead to nullisomic lines of 'Abbondanza' are greater vigor and fertility than those of Chinese spring <ns0:ref type='bibr' target='#b31'>(Ji, Xue &amp; Wang, 1992)</ns0:ref>. Our 2A nullisomic line dms is multi-pistil and male sterile, that is different from the other 2A nullisomic lines from 'Abbondanza' and CS <ns0:ref type='bibr' target='#b13'>(Endo &amp; Gill, 1996)</ns0:ref>. A set of chromosome deletion stocks from CS are reported, five out of the nine chromosome 2AS deletion lines have irregular meioses with many univalents at metaphase I, and they are highly sterile in both sexes, the seed settings of the four chromosome 2AL deletion lines are reduced after selfing. In our study, the meiosis of the pollen development is normal in dms mutant, which is different from the 2A nullisomic lines from CS <ns0:ref type='bibr' target='#b13'>(Endo &amp; Gill, 1996)</ns0:ref>.</ns0:p><ns0:p>MYB TFs play pivotal roles in plant development and stress response <ns0:ref type='bibr' target='#b65'>(Verma, 2019;</ns0:ref><ns0:ref type='bibr' target='#b81'>Zheng et al., 2018)</ns0:ref>. Many MYB TFs have been functionally characterized in pollen development of Arabidopsis and rice, such as AtMYB32 <ns0:ref type='bibr' target='#b51'>(Preston et al., 2004)</ns0:ref>, OsGAMYB <ns0:ref type='bibr' target='#b0'>(Aya et al., 2009)</ns0:ref> and OsTDF1 <ns0:ref type='bibr' target='#b4'>(Cai et al., 2015)</ns0:ref>. In dms, three homologs of OsGAMYB, TraesCS7A01G458700, TraesCS7B01G357900 and TraesCS7D01G446700, expressed less. In rice, GAMYB is essential for pollen development, and it directly binds to promoter of &#946;-KETOACYL REDUCTASE (KAR), a key enzyme essential for fatty acid synthesis. GAMYB activates the expression of KAR and other genes involved in the synthesis of sporopollenin, and are involved in the formation of exine and Ubisch bodies <ns0:ref type='bibr' target='#b0'>(Aya et al., 2009)</ns0:ref>. Reduced expression of GAMYB might lead to the shriveled and atrophied pollen grains of D plants. Change in the levels of AtMYB32 expression influence pollen development by affecting the composition of the pollen wall in Arabidopsis <ns0:ref type='bibr' target='#b51'>(Preston et al., 2004)</ns0:ref>. Knocking out OsTDF1 impaired tapetum development, leading to male sterility in rice <ns0:ref type='bibr' target='#b4'>(Cai et al., 2015)</ns0:ref>. Similarly, some MYB TF genes expressed less in dms, their functions involved in exine formation in wheat needs further research.</ns0:p><ns0:p>Pollen germination is critical for double fertilization in angiosperms <ns0:ref type='bibr' target='#b79'>(Zhang, He &amp; McCormick, 2009)</ns0:ref>. The polarity of tip-growing pollen tubes is maintained through dynamic association of active Rho GTPases in plants (ROP-GTP) <ns0:ref type='bibr' target='#b37'>(Li et al., 2018a)</ns0:ref>. Guanine nucleotide exchange factors for ROPs (RopGEFs) catalyze the activation of ROPs and thereby affect spatiotemporal ROP signaling <ns0:ref type='bibr' target='#b22'>(Gu et al., 2006)</ns0:ref>. Deletion RopGEF mutant has the defects in pollen tube polar growth <ns0:ref type='bibr' target='#b22'>(Gu et al., 2006)</ns0:ref>. AGC1.5 and AGC1.7 kinases phosphorylate RopGEFs to control pollen tube growth. Loss functions of AGC1.5 and AGC1.7 in pollen tubes results in meandering and depolarized growth morphology <ns0:ref type='bibr' target='#b79'>(Zhang et al., 2009)</ns0:ref>. In summary, the AGC1.5/1.7-RopGEFs-ROPs signaling pathway is involved in pollen germination and tip growth in Arabodopsis <ns0:ref type='bibr' target='#b37'>(Li et al., 2018a;</ns0:ref><ns0:ref type='bibr' target='#b28'>Huang et al., 2019)</ns0:ref>. In our research, the homologs of AtAGC1.5, AtAGC1.7 and AtRopGEF8 involved in ROP signaling expressed less in dms. Similarly, all the DEGs associated with various aspects of pollen germination related biological processes, such as pollen tube growth, regulation of pollen tube growth, pollen tube development and pollination, expressed less in dms. These data demonstrated that pollen germination and pollen tube growth might be suppressed in dms. Further experiments should be carried out to test the hypothesis.</ns0:p><ns0:p>In our study, all the six chromosome 2As from different cultivars and the genetic backgrounds of the six heterozygotes of the crosses had similar functions. These indicated that the interactions among 2A, 2B and 2D were similar to that in dms. Wheat chromosome 2A has many important agronomy trait genes such as powdery mildew resistance gene PmLK906 <ns0:ref type='bibr' target='#b47'>(Niu et al., 2008)</ns0:ref>, photoperiod response locus Ppd-A1 <ns0:ref type='bibr' target='#b1'>(Beales et al., 2007)</ns0:ref>, reduced height (Rht) genes Rht7 <ns0:ref type='bibr' target='#b71'>(Worland, Law &amp; Shakoor, 1980)</ns0:ref>. Some quantitative trait loci (QTL) for thousand grain weight <ns0:ref type='bibr' target='#b54'>(Quan, Sean &amp; Sparkes, 2015)</ns0:ref>, floret primordia development <ns0:ref type='bibr' target='#b23'>(Guo et al., 2017)</ns0:ref> and grain protein-content <ns0:ref type='bibr' target='#b21'>(Groos et al., 2003)</ns0:ref> are also mapped on chromosome 2A. Because the 2A nullisomic line dms derived from Zhoumai 18 is male sterile but female fertile, it can be used as a female parent to cross with other wheat genotypes, so as to construct inter-cultivar chromosome 2A substitution lines. Backcross to dms can construct series lines with highly similar genetic backgrounds but different 2As (Fig. <ns0:ref type='figure'>10</ns0:ref>), which can be used to evaluate the functions of different 2As and wheat design breeding targeting 2As.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>We characterized a dwarf, multi-pistil and male sterile mutant dms derived from a widely-grown wheat cultivar Zhoumai 18. Cytological and molecular analyses demonstrated that mutant dms was a novel wheat 2A nullisomic line. Twenty-three stamen and pollen development related genes are identified specifically on chromosome 2A. We put forward a hypothesis on the molecular regulatory network of the sterility trait in dms. dms is a unique germplasm for gene functional study about chromosome 2A and wheat design breeding targeting 2A.</ns0:p></ns0:div> <ns0:div><ns0:head>Figure 1</ns0:head><ns0:p>The scanning electron micrographs of the anthers, anther epidermis, anther inner surface, and pollen grains in the T and D plants of dms at the trinucleate stage. <ns0:ref type='table'>3</ns0:ref> The key genes determining male fertility in wheat on chromosome 2A. Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head>ID</ns0:head></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>Uby: Ubisch bodies. Scale bars represent 1 mm in anthers, 500 &#956;m in pollen, 50 &#956;m on the epidermis surface and 10 &#956;m on the inner surface.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>Figure 6 Chromosome</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 7 The</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 10 ATable 1</ns0:head><ns0:label>101</ns0:label><ns0:figDesc>Figure 10</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>Key genes involved in abnormal pollen development of dms.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>4</ns0:head><ns0:label /><ns0:figDesc>indicate the genes verified by real-time qRT-PCR. 3 PeerJ reviewing PDF | (2020:06:49928:1:2:CHECK 5 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='21,42.52,280.87,525.00,321.00' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='24,42.52,255.37,525.00,263.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='28,42.52,250.12,525.00,334.50' type='bitmap' /></ns0:figure> <ns0:note place='foot'>PeerJ reviewing PDF | (2020:06:49928:1:2:CHECK 5 Sep 2020)</ns0:note> </ns0:body> "

"Dear Editor, Thanks a lot for the reviewers’ comments and their kind suggestions of our manuscript entitled “Cytological and molecular characterizations of a novel 2A nullisomic line derived from a widely-grown wheat cultivar Zhoumai 18 conferring male sterility” (Manuscript ID: peerj-49928). We provide this cover letter to explain our revised manuscript and our responses to the reviewers’ comments, point by point, as follows. We hope the revised manuscript would satisfy you and the reviewers. We are looking forward to hearing from you soon. Kind Regards, Zhixin Jiao Reviewer 1 (Anonymous) Basic reporting The article is well written in unambiguous professional English. Sufficient background along with references are provided. The article is well presented in terms of article structure etc. With relevant results and hypothesis. Experimental design The research in the manuscript is original and within the aims and scope of this journal. The research question is well defined with relevance to wheat genetic research. And although similar in aims to other studies, it adds to those studies and shows different unique outcomes. The investigation is thorough and technically sound and methods are described in sufficient detail. Validity of the findings All the relevant data has been provided and are robust and sound. Conclusions are well stated and linked to the research question. Some modifications to the conclusions are suggested below. Comments for the Author The manuscript titled 'Cytological and molecular characterizations of a novel 2A nullisomic line derived from a widely-grown wheat cultivar Zhoumai 18 conferring male sterility' details the characterization of a novel wheat line deficient in chromosome 2A. Although, 2A nullisomics have been previously reported for wheat (Xue et al., 1991 and 1992), the current manuscripts divulges some previously unknown functions of chromosome 2A. The line characterized in this manuscript was previously identified by the same authors as a mutant that displayed three pleiotropic phenotypes - male sterility, multiple pistils and reduced plant height. In this manuscript the authors present further data that shows the absence of chromosome 2A (nullisomic 2A) as the main cause for the phenotypes observed. The authors have generated molecular and cytological data including, SNP association, SSR markers and chromosome painting towards the characterization of this mutant. This suggests that original mutant isolated was a spontaneous monosomic line for chromosome 2A. Further, the authors have made an effort to dissect the molecular basis of male sterility through identification of anther-specific genes on chromosome 2A. Twenty-three genes were identified as candidates controlling anther and pollen development. The manuscript advances the knowledge of wheat genomics and genetics and shows the various developmental aspects of wheat that chromosome 2A is involved in. Identification of 2A located anther-specific genes furthers the understanding of 2A genes involved in male fertility in wheat. therefore this manuscript is suitable for publication in PeerJ. However, several revisions are required before the manuscript can be accepted. Thank you very much for your positive comments. 1) As the authors mention in the discussion, several chromosome 2AS internal deletions in CS genotype show male sterility including due to meiosis defects, more information is needed on the developmental defects in the 2A nullisomic. Fig S2 should be expanded to include earlier stages of meiosis. Thank you very much. According to your comment, we have added two earlier stages in Fig. S2. (A) and (D) Central callose stage; (B) and (E) Young microspore stage. 2) In the proposed model, two points should be clarified i) Is GAMYB homolog (TraesCS7B01G357900) anther-specific in wheat? If it is anther-specific a QPCR panel in figure 8 should be included. If it is not anther-specific then the emphasis in model (fig 9) should be de-emphasized. Thank you very much. According to your comment, we have rechecked the expression pattern of GAMYB homolog gene (TraesCS7B01G357900), it was not a anther-specific gene. So we have modified the model (fig 9) and de-emphasized this gene. ii) Figure 8 includes expression of pollen germination-related genes, however, since pollen germination stages were not analyzed and since pollen are shown to be aborted at microspore stage in D mutants (Fig S2), pollen germination genes should not be expressed at the stages investigated particularly in D mutants. Therefore, the DEGs observed for pollen germination could be homologous genes but not involved in pollen germination. This should be further looked into and clarified in the revised manuscript. The hypothetical model should be accordingly adjusted. Thank you very much. I agree with you that the DEGs observed for pollen germination could be homologous genes but not involved in pollen germination. According to your comment, we have modified the model (fig 9) and deleted pollen germination related hypothetical model. 3) In line 289-291, the statement 'Tissue specific expression analysis showed that 188 genes on chromosome 2A were stamen specifically expressed genes (Fig. 6A)' should be rechecked in the text and figure. Thank you very much. According to your comment, we have rechecked the tissue specific expression pattern of the genes on chromosome 2A, 188 genes were identified as stamen specifically expressed genes using the k-means analysis. The expression pattern of the 188 genes have been list in Table S9 (Sheet 1). Other minor comments: 1) It appears that the term 'proprietary' in line 50 is not appropriate and should be changed to 'novel'. if any intellectual property has been issued or applied for these genes then it should be mentioned. Agreed. I have revised it. 2) Also consider changing the term 'wizened' to other suitable words such as 'shriveled' Agreed. I have replaced 'wizened' with 'shriveled'. 3) Abbreviation 'TF' has been used at several places but it not described in the manuscript Agreed. I have revised it. 4) In figure S5 all the figures should be arranged in a developmental order youngest to oldest (for anthers as well). Agreed. I have revised it. 5) In table 2 check the description under F1 (Phenotype and observed lines at F2 (number)) I have deleted the words 'at F2 '. Reviewer 2 (Anonymous) Basic reporting In this study, authors described characterization of a 2A nullisomic line derived from Zhoumai 18 which is male sterile. The language is clear and professional; the methods used to address the hypothesis are appropriate, although some experiments were not necessary, for example, the SSR marker analysis. It seems authors did the cytology analysis last; other analysis was done before the cytology analysis. It is reasonable to include all the experimental data to support the hypothesis. The figures were relevant and raw data were supplied. Thank you very much for your positive comments. However, two conclusions drawn from the study were a bit arbitrary; there is not enough evidence to support them. The first, the less expression of MYB transcription factor in D plant might lead to the wizened pollen grains (male sterility) of D plants. This hypothesis was drawn in Figure 9. It seems they excluded other TEs involvement. The results didn’t show how much less expression and how significant it was for MYB. Table_S11 showed differentially expressed TFs. Could authors explain why MYB but not others involved in male sterility/fertility? A few literatures demonstrated that some MYB involved in pollen development. Some other TFs listed in Table_S11 could also be involved in pollen development or plant cuticle biosynthesis, such as C2H2, bHLH, and AP2/ERF (indeed, in Table 3, C2H2 and bHLH were listed). Thank you very much. I agree with your opinions that some other TFs such as C2H2, bHLH, and AP2/ERF could also be involved in pollen development or plant cuticle biosynthesis, so the hypothesis have been modified the Figure 9. We have also removed the conclusion that MYB involved in male sterility/fertility in the text. Second, “there were 23 chromosome 2A proprietary genes were involved in stamen and pollen developments” (copied from the abstract). This sentence was not quite appropriate, although data showed that there were 23 2A-specific genes were highly expressed in stamen. It can’t exclude other genes on 2A might be also involved in pollen development. In the case of wheat Ms1 gene on 4BS, it has homoeologs on 4A and 4D. Mutant ms1 is responsible for male sterile phenotype due to that homoeologous Ms1 on 4A and 4D were not expressed (due to methylation). Overall, the discussion part could be improved. Some genes in the list of 23 2A-specific genes could be candidates of key genes responsible for the male sterility, but not exclude other possibilities. Until the key gene/genes are identified, the molecular regulatory network will be elucidated. Thank you very much. I agree with your opinions that some genes in the list of 23 2A-specific genes could be candidates of key genes responsible for the male sterility, but not exclude other possibilities. We have added this comment to the discussion. We also have replaced 'there were 23 chromosome 2A proprietary genes were involved in stamen and pollen developments' with 'we identified 23 genes on chromosome 2A which might be involved in stamen and pollen developments.' in the abstract. Below is the list for minor revisions. Line 137, “the fifteen bulks” should be “the fifteen samples”. Agreed. I have revised it. Line 161, “Clarke, 2013” should be Clarke, 2009”. Agreed. I have revised it. Line 227-228, “between stamens of T and D plants” should be “between T and D plants”. Agreed. I have revised it. Line 248, “In a word” should be “In another word”. Agreed. I have revised it. Line 299, if you use “TF” first time, it should be “transcription factor (TF)”. Agreed. I have revised it. Line 335, “gravely” should be “greatly” or “seriously”? Agreed. I have revised it. Line 348, “they all were male fertile but female sterile”. It is not correct. In Endo and Gill (1996)’s paper, 2A nullisomic and some deletion lines were described as they were sterile in both sexes. Agreed. I have revised it. Line 361, “Verma, 1996” should be “Verma, 2019”. Agreed. I have revised it. Line 391, “both the six chromosome 2As….” Should be “all the six ….”. Agreed. I have revised it. Line 396, “Same” should be “Some”. Agreed. I have revised it. Table 3, reference “Fu et al. 2018” was not in the reference list. Agreed. I have revised it. Table 4, two references “Li et al. 2018”, they should be 2018a, 2018b? Agreed. I have revised it. They should be “Li et al., 2018a” Please check the format of references cited in the text; they were not constant, sometime as “Li et al. 2018”, sometime “Li et al., 2018”. Please check the Journal’s guidance. Agreed. I have revised them. Fig. S5, samples should be described more clearly. Agreed. I have revised them. Experimental design Experimental design to address the hypothesis is appropriate. Validity of the findings Some conclusions need to be revised. See basic reporting. Thank you very much. According to your comment, we have revised them. Comments for the Author no comment. Reviewer 3 (Peter Sharp) Basic reporting This paper is fine in these aspects, except for English expression. I have attached a version of the Abstract and Introduction of the paper where I have corrected/made suggestion in word with track-changes and saved as a pdf. This will give the authors the ideas of what should be done in the rest of the paper. We have revised the manuscript carefully and tried to avoid any grammar or syntax error. In addition, we have asked several colleagues who are skilled authors of English language papers to check the English. We believe that the language is now acceptable for the review process. Experimental design Once again, this papers is fine in these technical aspects. Validity of the findings Also fine. Comments for the Author This paper is fine in all technical aspects, and very interesting, the researchers have done a nice job. English expression needs some work. I have attached a version of the Abstract and Introduction of the paper where I have corrected/made suggestion in word with track-changes and saved as a pdf. This will give the authors the ideas of what should be done in the rest of the paper. Thank you very much. According to your comment, we have revised them. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The enzyme L-asparaginase from Escherichia coli is a therapeutic enzyme that has been a cornerstone in the clinical treatment of acute lymphoblastic leukemia for the last decades.</ns0:p><ns0:p>However, treatment effectiveness is limited by the highly immunogenic nature of the protein and its cross-reactivity towards L-glutamine. In this work, a bioinformatic approach was used to identify, select and characterize L-asparaginases from Streptomyces through sequence-based screening analyses, immunoinformatics, homology modeling, and molecular docking studies. Based on its predicted low immunogenicity and excellent enzymatic activity, we selected a previously uncharacterized L-asparaginase from Streptomyces scabrisporus. Furthermore, two putative asparaginase binding sites were identified and a 3D model is proposed. These promising features allow us to propose Lasparaginase from S. scabrisporus as an alternative for the treatment of acute lymphocytic leukemia.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Acute lymphocytic leukemia (ALL) is a hematological disorder of the bone marrow and is characterized by abnormal proliferation of immature lymphoid line cells, blocked at an early stage of cell differentiation, that accumulate and replace healthy hematopoietic cells in the bone marrow <ns0:ref type='bibr' target='#b46'>(Pui, Relling &amp; Downing, 2004;</ns0:ref><ns0:ref type='bibr' target='#b43'>Onciu, 2009)</ns0:ref>. ALL occurs predominantly in children of 1-4 years of age and represents approximately 25% of childhood cancers and about 80% of leukemias <ns0:ref type='bibr' target='#b33'>(Katz et al., 2015)</ns0:ref>.</ns0:p><ns0:p>Although in most cases the risk factors and pathogenicity associated with ALL have not been clearly identified, the etiology of the disease has been mainly associated with a variety of conditions; cytogenetic alterations, mutations to key genes that regulate cellular proliferation, PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed differentiation and death; presence of oncogenic viruses, immunodeficiency, exposure to pesticides, solvents, and ionizing radiation <ns0:ref type='bibr' target='#b46'>(Pui, Relling &amp; Downing, 2004;</ns0:ref><ns0:ref type='bibr' target='#b4'>Bassan, Maino &amp; Cortelazzo, 2016)</ns0:ref>.</ns0:p><ns0:p>Treatment for ALL patients involve steroid drugs, prednisone, vincristine, and the enzyme Lasparaginase (ASNase) <ns0:ref type='bibr' target='#b2'>(Avramis, 2012;</ns0:ref><ns0:ref type='bibr' target='#b54'>Schwab &amp; Harrison, 2018)</ns0:ref>. ASNase has been essential in the treatment of ALL since the 1970s, with demonstrated effectiveness as an individual drug with remission rates of up to 68% <ns0:ref type='bibr' target='#b49'>(Salzer et al., 2017)</ns0:ref>. The combination of ASNase with other anticancer drugs has led to remission rates of up to 90% (Lanvers-Kaminsky, 2017).</ns0:p><ns0:p>Currently, there are four ASNase formulations available for the ALL treatment: two native forms of the enzyme, obtained from Escherichia coli (EcAII) and Erwinia chrysanthemi (ErAII), and pegylated E. coli ASNase (EcAII-PEG), as well as pegylated E. chrysanthemi ASNase (EcAI-PEG). Of these, EcAII-PEG has become the first-line treatments for ALL in the US, with EcAII the most widely used formulation. ErAII is administered to patients who have developed hypersensitivity to the above formulations <ns0:ref type='bibr' target='#b45'>(Pieters et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abribat, 2016;</ns0:ref><ns0:ref type='bibr' target='#b3'>Barba et al., 2017)</ns0:ref>.</ns0:p><ns0:p>In recent years, evidence has been accumulating of its usefulness as an important component in the treatment of other hematological malignancies, such as acute myeloid leukemia, myelosarcoma, lymphosarcoma, Hodgkin's disease, and chronic lymphocytic leukemia <ns0:ref type='bibr' target='#b14'>(Emadi, Zokaee &amp; Sausville, 2014;</ns0:ref><ns0:ref type='bibr' target='#b36'>Lopes et al., 2015)</ns0:ref>. Despite their high antileukemic potential, the use of ASNases in the treatment of ALL is limited by their toxicity. Among the adverse effects that have been reported are leukopenia, immune suppression, acute pancreatitis, liver dysfunction, hyperglycemia, abnormalities in hemostasis, and hemorrhages of the central nervous system <ns0:ref type='bibr' target='#b53'>(Schein et al., 1969;</ns0:ref><ns0:ref type='bibr' target='#b47'>Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b10'>Chan et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b1'>Ali et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b28'>Hijiya &amp; van der Sluis, 2016;</ns0:ref><ns0:ref type='bibr' target='#b31'>Kamal et al., 2019)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The generation of immune responses during treatment with ASNase is a common condition that has been reported in up to 75% of patients. These reactions depend on the formulation used, the mode of administration (intravenous or intramuscular), and the treatment protocol <ns0:ref type='bibr' target='#b27'>(Hijiya &amp; van der Sluis, 2015)</ns0:ref>. For example, between 30 and 75% of patients that receive the native form of the E. coli enzyme experience hypersensitivity reactions, and about 70% develop anti-EcAII antibodies after drug administration <ns0:ref type='bibr' target='#b5'>(Battistel et al., 2020)</ns0:ref>; these antibodies lead to rapid inactivation of the enzyme <ns0:ref type='bibr' target='#b60'>(Walenciak et al., 2019)</ns0:ref>. Allergic reactions to ASNase, which are associated with its bacterial origin, range from mild urticaria to life-threatening anaphylactic shock. Irritation, fever, vomiting, gastrointestinal edema, and breathing difficulties are symptoms frequently reported (Lanvers-Kaminsky, 2017). On the other hand, adverse effects have been reported due to the toxicity produced by glutaminase cross activity, such as leukopenia, immune suppression, acute pancreatitis, hyperglycemia, thrombosis, neurotoxicity, and liver failure, among others <ns0:ref type='bibr' target='#b47'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b10'>Chan et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b1'>Ali et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Different strategies to reduce the toxicity of ASNase have been reported, including modifications in the structure of the protein by mutagenesis, design of mutants with diminished ability to hydrolyze L-glutamine, chemical modifications in specific amino acids, and modifications to drug formulations <ns0:ref type='bibr' target='#b47'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b41'>Nguyen, Su &amp; Lavie, 2016;</ns0:ref><ns0:ref type='bibr' target='#b42'>Nguyen et al., 2018)</ns0:ref>. Covalent conjugation of the enzyme with polyethylene glycol, known as PEGylation, reduces the incidence of hyperglycemia, pancreatitis, and anaphylaxis. This specific modification increase the half-life of the enzyme and reduces the frequency of drug administration <ns0:ref type='bibr' target='#b59'>(Thomas &amp; Le Jeune, 2016)</ns0:ref>.</ns0:p><ns0:p>On the other hand, the exploration of new sources of ASNases offers the possibility of finding versions of the enzyme with different pharmacological characteristics, potentially useful for the</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Identification and selection of homologous L-Asparaginases</ns0:head><ns0:p>Putative ASNases from Streptomyces were identified through a BLASTp search against the NR database of the NCBI using as seeds the amino acid sequences of EcAII (ID P00805) and Streptomyces coelicolor type II ASNase (ScAII; ID Q9K4F5). The search was restricted to the Streptomyces taxon (Taxid 1883), and an E-value less than 1e-06 was considered significant.</ns0:p><ns0:p>Partial proteins and those from unidentified Streptomyces strains were excluded. In a posterior step, the set of protein sequences was filtered at 60% identity as cutoff to avoid redundancy, using the CD-Hit program (http://weizhongli-lab.org/cdhit_suite/cgi-bin/index.cgi) <ns0:ref type='bibr' target='#b29'>(Huang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>Each cluster was analyzed using the HMMER program on the PFAM server (http://pfam.xfam.org/) to determine the protein family to which they belonged <ns0:ref type='bibr' target='#b19'>(Finn, Clements &amp; Eddy, 2011;</ns0:ref><ns0:ref type='bibr' target='#b20'>Finn et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.2'>Phylogenetic analysis</ns0:head><ns0:p>ASNases amino acid sequence alignments were performed using Clustal Omega <ns0:ref type='bibr' target='#b55'>(Sievers et al., 2011)</ns0:ref> with default parameters. The quality of the alignments was improved using the model PF06089.11 or PF00710.11 of ASNase, as required. Multiple sequence alignment statistics were computed with AliStat (http://www.csb.yale.edu/userguides/seq/hmmer/docs/node27.html).</ns0:p><ns0:p>Phylogenetic analyses were carried out using the maximum-likelihood method with the program Mega 7. The WAG model was chosen as substitution model, and 1000 replicates were performed.</ns0:p><ns0:p>The best tree was calculated using the majority rule. Additionally, E. coli type I ASNase <ns0:ref type='bibr'>(EcAI)</ns0:ref> was included in the phylogenetic analysis of the PF00710.11 cluster. EcAI is closely related to PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed EcA but it does not have therapeutic potential. For the PF06089.11 cluster, Rhizobium etli type II ASNase (ReAII) was included in the analysis.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.3'>Antigenicity prediction</ns0:head><ns0:p>The prediction of the probability of antigenicity of each ASNase was calculated with the server ANTIGENpro (http://scratch.proteomics.ics.uci.edu/) <ns0:ref type='bibr' target='#b37'>(Magnan et al., 2010)</ns0:ref>. ANTIGENpro is a sequence-based, alignment-free, protein antigenicity predictor with an estimated accuracy of 82%.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.4'>HLA class II binding prediction</ns0:head><ns0:p>The amino acid sequence of each candidate ASNase was screened for T-cells epitopes with the MHC II Analysis Resource at the Immune Epitope Data Base (IEDB) server and HLA-DRB1*15:01. The IEDB-recommended method uses the consensus approach, combining <ns0:ref type='bibr'>NN-align, SMM-align, CombLib, Sturniolo, and NetMHCIIpan (Wang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>For each peptide, a percentile rank is generated by comparing the peptide's score against the scores of five million random 15-mer selected from SWISSPROT database, and the median percentile rank is used to calculate a consensus percentile rank (CPR). Peptides with a CPR &lt; 2 were defined as high-affinity binders and thus selected for epitope density (ED) calculation. Multiple 9-mer cores were identified in overlapped 15-mer peptides. To reduce overestimation of predicted peptides, only the 9-mer cores, predicted by using the Sturniolo method <ns0:ref type='bibr' target='#b57'>(Sturniolo et al., 1999)</ns0:ref> PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed and with a CPR &lt; 1, were considered for the analysis. Finally, epitope density (ED) was calculated using the follow equation, modified from <ns0:ref type='bibr' target='#b52'>(Santos et al., 2013)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_0'>&#119864;&#119863; = &#119875;&#119903;&#119890;&#119889;&#119894;&#119888;&#119905;&#119890;&#119889; &#119890;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; * (2 -&#119860;&#119891;&#119891;&#119894;&#119899;&#119894;&#119905;&#119910; &#119886;&#119907;&#119890;&#119903;&#119886;&#119892;&#119890; ( &#119888;&#119901;&#119903; ) ) &#119875;&#119903;&#119900;&#119905;&#119890;&#119894;&#119899; &#119897;&#119890;&#119899;&#119892;&#119905;&#8462; &#119904;&#119894;&#119911;&#119890; -&#119864;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; &#119904;&#119894;&#119911;&#119890; + 1</ns0:formula><ns0:p>Where Predicted epitope is the number of epitopes with a CPR &lt; 1.</ns0:p><ns0:p>Epitope coverage was calculated as the number of alleles covered by the epitope consensus, according to the following assumption: when a small number of alleles is covered, a lower percentage of the population will develop sensitivity to ASNase.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.5'>Protein structure prediction, refinement and quality assessment</ns0:head><ns0:p>The three-dimensional structures of the selected ASNases was modeled by homology using the I-Tasser server (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) <ns0:ref type='bibr' target='#b65'>(Zhang, 2008)</ns0:ref>. In brief, starting from an amino acid sequence, I-Tasser generates three-dimensional atomic models from multiple threading alignments and iterative structural assembly simulations. A C-score, provided as an estimate of the accuracy of the models generated, typically ranges between -5 to +2, with a higher value indicating higher confidence, and vice versa <ns0:ref type='bibr' target='#b48'>(Roy, Kucukural &amp; Zhang, 2010)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the model with the higher C-score was selected and then refined using the ModRefiner server (https://zhanglab.ccmb.med.umich.edu/ModRefiner/). ModRefiner improves the physical quality and structural accuracy of three-dimensional protein structures by a two-step, atomic-level energy minimization <ns0:ref type='bibr' target='#b64'>(Xu &amp; Zhang, 2011)</ns0:ref>. Finally, the quality of the models was evaluated by RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php), Qmean (https://swissmodel.expasy.org/qmean/), and Verify3D (http:/servicesn.mbi.ucla.edu/Verify3D). <ns0:ref type='table'>2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing PDF | (</ns0:head></ns0:div> <ns0:div><ns0:head n='1.6'>Molecular docking</ns0:head><ns0:p>The molecular coupling was carried out using Autodock Tools software <ns0:ref type='bibr' target='#b51'>(Sanner, 1999;</ns0:ref><ns0:ref type='bibr' target='#b39'>Morris et al., 2009)</ns0:ref>. EcAII (PDB ID: 3ECA) was recovered from the PDB protein database (http://www.rcsb.org/) <ns0:ref type='bibr' target='#b58'>(Swain et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b6'>Berman et al., 2000)</ns0:ref>. Once refined, selected ASNase structures were prepared using Dock prep at UCSF Chimera and refined using the Gasteiger method <ns0:ref type='bibr' target='#b22'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>The three-dimensional structures of the asparagine and glutamine ligands were obtained from the DrugBank repository (https://www.drugbank.ca/; accession numbers DB00174 and DB00130, respectively) <ns0:ref type='bibr'>(Wishart et al., 2018)</ns0:ref>. The preparation of the ligands was carried out by the Gasteiger method and, finally, the allocation of the rotation centers was determined <ns0:ref type='bibr' target='#b22'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the search box was focused on previously proposed active sites. The box size was defined to cover all residues of the ligand binding site, using a grid size of 0.375 &#197;.</ns0:p><ns0:p>Blind molecular docking was performed with Autodock 4.2 software, using the Lamarckian genetic algorithm, with 1000 runs, for a population size equal to 150, with 2.5 x 10^6 evaluations, a mutation rate equal to 0.02 in 27,000 generations.</ns0:p><ns0:p>In addition, the active site location was predicted by AutoLigand <ns0:ref type='bibr' target='#b26'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Briefly, AutoLigand identifies sites of maximum affinity from maps generated by AutoGrid, finding regions with better energy and a lower volume.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>L-Asparaginases from Streptomyces cluster into two type families according to its protein architecture</ns0:head><ns0:p>The Blast search against the Streptomyces taxon revealed 296 putative ASNases homologous to EcAII and 703 homologous to ScAII with a significant score. After manual examination of both groups, 136 and 311 complete sequences were kept for EcAII and ScAII groups, respectively. Protein domain analysis using PFAM server showed that 136 sequences are related to the PF00710.11 family of N-terminal ASNases. For sequences homologous to ScAII, PFAM analysis revealed that they belong to the PF06089.11 family of ASNases, a group of enzymes related to ReAII, a thermolabile enzyme induced by L-asparagine and repressed by the carbon source <ns0:ref type='bibr' target='#b38'>(Moreno-Enriquez et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b30'>Huerta-Saquero et al., 2013)</ns0:ref>. Representative clusters for PF00710.11 and PF06089.11 families obtained using the CD-Hit suite program were generated at a 60% identity cutoff, with 19 and 7 putative ASNases, respectively (Table <ns0:ref type='table'>1</ns0:ref>). ASNases sequences showed similar lengths in both clusters, ranging from 320 to 420 amino acids. Manuscript to be reviewed lower affinity than L-asparaginases from both E. coli and E. chrysanthemi <ns0:ref type='bibr' target='#b38'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Furthermore, ReAII is the only ASNase characterized from the PF06089.11 family</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Phylogenetic analysis of ASNases</ns0:head><ns0:p>For the PF00710.11 family, EcAI was added to the multiple sequence alignment in order to know the relationship between this ASNase and the candidate ASNases. EcAI belongs to the same family of proteins as EcAII, but it does not represent a therapeutic option for ALL treatment. It is noteworthy that asparaginases can also be classified according to subcellular localization, a) periplasmic asparaginases containing secretion signal peptide and, b) asparaginases with intracellular localization. The former generally have a higher affinity for asparagine. However, according to their architecture, both types of proteins can be found in the PF00710.11 or PF06089.11 families. This is the case of E. coli asparaginases I and II, both belonging to the PF00710.11 family (https://pfam.xfam.org/family/PF00710#tabview=tab1). We found that the ASNase with accession number WP_059134811.1 of Streptomyces alboniger is grouped in the same clade as EcAI, and so it was excluded from subsequent analyses (Figure <ns0:ref type='figure' target='#fig_14'>1A</ns0:ref>).</ns0:p><ns0:p>The phylogenetic reconstruction showed three well-defined clades (Figure <ns0:ref type='figure' target='#fig_14'>1A</ns0:ref>). On the other hand, for the ASNases of PF06089.11, phylogenetic analysis included both the ASNase sequence of R. etli and S. coelicolor (ReAII and ScAII, respectively) (Figure <ns0:ref type='figure' target='#fig_14'>1B</ns0:ref>). The tree defines two clades. In the first one, where the ScAII was included, we also considered ARZ68596.1 from S. albireticuli, SOD64826.1 from S. zhaozhouensis, WP_078645645 from S. varsoviensis, CDR15801.1 from S. iranensis, and WP_020554088 from S. scabrisporus.</ns0:p><ns0:p>In the second clade were included the following proteins: WP_044373749 from S. ahygroscopicus and WP_078980718.1 from S. scabrisporus. Bootstrap values are indicated.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Antigenicity predictions</ns0:head><ns0:p>The results for antigenicity showed a likelihood of being antigenic for all ASNases in both sets that was lower than that of EcAII (Figure <ns0:ref type='figure' target='#fig_5'>2</ns0:ref>). Nevertheless, among selected Streptomyces ASNases, the candidates from S. purpurogeneiscleroticus (WP_053609500.1) and S. phaeochromogenes </ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>T-cell epitope analysis</ns0:head><ns0:p>After antigenicity prediction, the ED, the total number of high-affinity epitopes, the affinity epitopes, and the number of HLA alleles covered by each ASNase were calculated. The results showed that the ASNases with accession numbers WP_053609500.1, WP_053610569.1, EFL23513.1, WP_095730579.1, WP_078513220.1, and WP_052425051.1 have higher EDs than the reference (P00805_EcAII; ED=0.01114; 5 covered alleles) (Figure <ns0:ref type='figure' target='#fig_6'>3</ns0:ref>).</ns0:p><ns0:p>On the other hand, the ASNase with the lowest predicted ED was WP_044373749.1, with an ED of 0.0027 and a coverage of 4 alleles, following by WP_095730579.1 (2 alleles), ELP65653.1 (3 alleles), and Q9K4F5 (3 alleles) (Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p><ns0:p>Additionally, the distribution of epitopes was mapped into the sequences of the ASNases (Figure <ns0:ref type='figure' target='#fig_6'>3</ns0:ref>). ASNases of the PF06089.11 family tended to have a lower ED (Table <ns0:ref type='table'>3</ns0:ref>) as well as lower allele coverage than those of the PF00710.11 family (Figure <ns0:ref type='figure' target='#fig_6'>3</ns0:ref>).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed Next, ASNases with lower allele coverage, lower ED, and lower probability of antigenicity were selected for further analysis. S. coelicolor (Q9K4F5), S. scabrisporus (WP_078980718.1), and S. albireticuli (ARZ68596.1) were selected as promising enzymes.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>Protein structure predictions</ns0:head><ns0:p>From selected ASNases, homology-based models were generated (I-Tasser). For the subsequent analysis, the S. scabrisporus asparaginase II model, which had the highest C-value, was chosen (WP_078980718.1 SsAII-2) (Figure <ns0:ref type='figure' target='#fig_7'>4</ns0:ref>). The stereochemical quality of the models was evaluated using Ramachandran plots. In order to improve the quality of the models, these were structurally refined with ModRefiner and reassessed with RAMPAGE. In addition, the Verify3D server was used to determine the compatibility of the three-dimensional model with the amino acid sequence.</ns0:p><ns0:p>Based on the predicted structure, ASNase WP_0789718.1 (PF06089.11 family) is related in terms of folding to the beta-lactamase family. Beta-lactamases (SCOP data base, entry 56600) consist of a cluster of alpha-helices and an alpha/beta sandwich. This folding is also found in transpeptidases, esterases, penicillin receptors, D-aminopeptidases, and glutaminases (InterPro IPR012338). </ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>Active site prediction</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>In order to identify the active site residues of the S. scabrisporus ASNase (WP_0789718.1), three approaches were used: genomic comparison, blind molecular coupling simulation, and search for high-affinity binding pockets with AutoLigand (active site). To our knowledge, there is no information regarding the active site of the family PF06089.11 ASNases, so genomic comparison was not possible. Using AutoLigand, two possible high affinity binding sites for L-asparagine were identified (Figure <ns0:ref type='figure' target='#fig_8'>5A</ns0:ref>). The first (site A) had a volume of 121 &#197; 3 and an energy per volume equal to -0.2149 kcal/mol &#197; 3 ; the second (site B) had a volume of 101 &#197; 3 and an energy per volume equal to -0. 2136 kcal/mol &#197; 3 . Site A is located between an alpha-helix in the amino terminal containing the 57 PRSx(2)KPxQ 65 motif, and a loop in the central region of the enzyme, containing the 141 NCSGKHxAML 150 motif (Table <ns0:ref type='table'>3</ns0:ref>). Site B is located in a pocket formed by a set of alphahelices in the amino terminal of the protein, marked by the presence of the 87 SHTGQxHFV 95 motif.</ns0:p><ns0:p>On the other hand, by performing AutoDock 4.2 whole-protein molecular coupling simulations, we found that the best ligand-enzyme interaction (L-asparagine-ASNase), with a binding free energy of -4.17 kcal/mol, targeted residues corresponding to the 141 NCSGKHxAML 150 motif, which correspond to the site A (Figure <ns0:ref type='figure' target='#fig_8'>5B</ns0:ref>). Additionally, in order to validate AutoLigand analysis searching active sites in the S. scabrisporus ASNases, a search for binding sites in EcAII was performed. To do this, the monomeric, dimeric, and tetrameric forms of the enzyme (the latter is the catalytically active form) were analyzed using PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed the same conditions used for SsAII-2. It was found that AutoLigand successfully identified the binding site of L-Asn, consisting of Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, and Lys 162 and also Asn 248 and Glu 283 (Figure <ns0:ref type='figure' target='#fig_9'>6</ns0:ref>), the latter two only for dimeric and tetrameric forms. The sites found (red squares curves) had energies by volume equal to -0.2119, -0.2242, and -0.2366 kcal/mol &#197; 3 and a volume of 136, 122, and 102 &#197; 3 for the monomer, dimer, and tetramer, respectively (Figure <ns0:ref type='figure' target='#fig_10'>7</ns0:ref>). It is relevant that for both the dimeric and the tetramer forms, AutoLigand successfully identified L-Asn binding pockets in EcAII: the pocket formed between the aminoterminal end of subunit A and the carboxy terminal of the subunit C, as well as equivalent pockets for dimer BD. In addition, several other solutions found by AutoLigand (curve with blue or green squares), using up to 90 filling points, converge in the different joint pockets formed by dimers. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>Molecular docking</ns0:head><ns0:p>Molecular docking simulations were performed at the putative sites found (Table <ns0:ref type='table'>4</ns0:ref>). For EcAII, as the reference ASNase, Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, Asn 248, and Glu 283 were established as flexible residues; meanwhile, molecular docking for S. scabrisporus ASNase were performed using only the rigid structure of the protein, without defining flexible side chains for L-asparagine binding.</ns0:p><ns0:p>Our results showed a higher affinity for L-asparagine of the S. scabrisporus ASNase site A than site B; however, the affinity was lower than that for EcAII. For S. scabrisporus ASNase site A, the L-asparagine interacts with residues Ser 59, Lys 62, Asn 141, Ser 143, Lys 145, His 146, Gly 237, Lys 255, and Gly 256 (Figure <ns0:ref type='figure' target='#fig_12'>8A</ns0:ref>); for site B, the residues that interact with L-asparagine are Ala 84, Gly 78, Ser 87, Tyr 163, Leu 164, and Asp165 (Figure <ns0:ref type='figure' target='#fig_12'>8B</ns0:ref>). Interestingly, from site A, Lys </ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>In this work, a set of bioinformatics tools were used to identify, select, and characterize ASNases from the Streptomyces genus. ASNase identification was carried out by searching sequences homologous to EcAII and ScAII. EcAII is the best-characterized and most widely used ASNase for ALL treatment, while ScAII is a homologous ASNase related to ReAII, an atypical ASNase PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed with no glutaminase activity and with a different immunogenic profile than EcAII <ns0:ref type='bibr' target='#b30'>(Huerta-Saquero et al., 2013)</ns0:ref>. The search for homologous sequences resulted in two sets of sequences with a high probability of being ASNases (E value &lt;1e-06). These sequence sets, in turn, were classified into two different protein families based on their homology, using HMMer: PF00710.11 and PF06089.11, according to the classification of the PFAM database. So far, most of the reported ASNases belong to the PF00710.11 family and have been extensively studied. EcAII and the E.</ns0:p><ns0:p>chrysanthemi ASNase belong to this family. On the other hand, the PF06089.11 family represents a group of atypical ASNases that remain poorly characterized. Some representative reports about these ASNases include the R. etli ASNase <ns0:ref type='bibr' target='#b44'>(Ortu&#241;o-Olea &amp; Dur&#225;n-Vargas, 2000;</ns0:ref><ns0:ref type='bibr' target='#b38'>Moreno-Enriquez et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b30'>Huerta-Saquero et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Interestingly, the BLAST results showed a greater abundance of PF06089.11 family sequences compared to the PF00710.11 family in Streptomyces. In addition, we found that about 20% of species have ASNase isoforms. In that sense, many Gram-negative bacteria have at least two isozymes of the family PF00710.11 <ns0:ref type='bibr' target='#b18'>(Fern&#225;ndez &amp; Z&#250;&#241;iga, 2006)</ns0:ref> and, in E. coli, the existence of a third isoenzyme has been recently reported <ns0:ref type='bibr' target='#b11'>(Correia da Silva et al., 2018)</ns0:ref>. Historically, the genus Streptomyces has been attractive due to the wide repertoire of bioactive molecules produced.</ns0:p><ns0:p>However, searching for ASNases of pharmacological interest has been done only rarely.</ns0:p><ns0:p>After the identification of two sets of ASNases, we chose T-cell ED as the immunogenicity indicator, according to <ns0:ref type='bibr'>Cantor et al. (2004</ns0:ref><ns0:ref type='bibr'>), Fern&#225;ndez et al. (2012</ns0:ref><ns0:ref type='bibr' target='#b21'>), and Galindo-Rodr&#237;guez et al. (2017)</ns0:ref>, who proposed that HLA class II molecules play a critical role in the development of specific anti-ASNase antibodies and in hypersensitivity to the enzyme <ns0:ref type='bibr' target='#b9'>(Cantor et al., 2011;</ns0:ref><ns0:ref type='bibr'>Fernandez et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b21'>Galindo-Rodr&#237;guez et al., 2017)</ns0:ref>. Additionally, it has been shown that proteins that are highly immunogenic generally contain a greater amount of T-cell epitopes, or PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed clusters thereof <ns0:ref type='bibr' target='#b56'>(Singh et al., 2012)</ns0:ref>. In addition, the measurement and prediction of ED have generated interest as useful tools for comparisons between therapeutic proteins, allowing selection of the best candidate in terms of probable immunogenicity <ns0:ref type='bibr' target='#b25'>(De Groot &amp; Martin, 2009)</ns0:ref>. In this sense, our results showed that ASNases of the PF06089.11 family contain lower EDs than enzymes of the PF00710.11 family, as well as fewer epitope clusters throughout the sequence. In addition, the allele coverage, which is related to the percentage of the population that develops a significant immune response, showed Streptomyces ASNases to be potential pharmacological options. In For the PF06089.11 family of ASNases, the lack of information of the active site precludes direct comparison, as was used in the approach for the ASNase WP_078979039.1. However, the use of computational tools based on structure inspection and on the evaluation of affinity maps has proven highly effective in identifying probable binding sites in uncharacterized proteins <ns0:ref type='bibr' target='#b26'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Based on the use of computational tools, it was possible to identify two putative binding sites in SsAII-2 (WP_078980718.1). Interestingly, in both sites the motifs NCSGKHxAM, PRSx(2)KPxQ, and SHSGEx(2)H were identified, and these motifs are highly conserved in the PF06089.11 family <ns0:ref type='bibr' target='#b38'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Of these, <ns0:ref type='bibr' target='#b7'>Borek et al. (2001)</ns0:ref> proposed that some of the residues of the NCSGKHxAM motif could be involved in the hydrolytic PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:p><ns0:p>Manuscript to be reviewed deamidation of L-asparagine <ns0:ref type='bibr' target='#b7'>(Borek &amp; Jask&#243;lski, 2001)</ns0:ref>. Although site A showed higher affinity for L-asparagine binding, additional studies are needed to confirm the best site for ligand binding.</ns0:p><ns0:p>Additionally, molecular dynamics simulations can provide more evidence of the characteristics of the binding site and, together with in vitro studies, will be useful for understanding the mechanism of enzymatic reaction <ns0:ref type='bibr' target='#b32'>(Karplus &amp; Kuriyan, 2005)</ns0:ref>. Although our results predicted that SsAII-2 has a lower affinity than EcAII, its different folding and immunogenic characteristics place it as a good candidate. Identifying catalytic site residues will allow us to perform site-directed modifications to increase its affinity.</ns0:p><ns0:p>The strategy developed here can be applied to the search for asparaginases in other clades of microorganisms, and even in eukaryotes, specifically mammalian asparaginases, whose evolutionary proximity to humans predicts less immunogenicity.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In summary, the search for ASNases in phylogenetically distant microorganisms and the application of bioinformatic tools to assess their toxicity and affinity for L-asparagine are viable approaches to obtain new ASNases with therapeutic potential. Based on its low immunogenicity and excellent enzymatic activity predicted, we have identified the S. scabrisporus ASNase as a potential alternative for the treatment of ALL. The subsequent enzymatic and immunogenic characterization of the S. scabrisporus ASNase is necessary for the validation of this bioinformatic approach. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>ASNase</ns0:head><ns0:note type='other'>Figure 7</ns0:note><ns0:p>AutoLigand results for EcAII.</ns0:p><ns0:p>The minima observed in the total energy graphs per unit volume represent putative binding sites in the structures analyzed, for the monomer, dimer, and tetramer conformation. As more filling points are used, the binding sites, cavities, or grooves are filled and the affinity decreases. The best sites are the ones with the lowest energy and the lowest volume.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>http://tools.iedb.org/mhcii/). MHC II Analysis Resource parses sequences into 15-mer and assesses the binding potential of each 15-mer to MHC class II molecules of one or more HLA alleles. The IEDB recommended method was used for predictions for a set of 8 HLA alleles that collectively represent &gt;%95 world population: HLA-DRB1*01:01, HLA-DRB1*03:01, HLA-DRB1*04:01, HLA-DRB1*07:01, HLA-DRB1*08:01, HLA-DRB1*11:01, HLA-DRB1*13:01</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>The sequences belonging to the PF00710.11 family have conserved residues located at the ligand binding site necessary for L-asparagine hydrolysis: Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp90, and Lys 162 for subunit A; Asn 248 and Glu 283 for subunit C. In this regard, Thr 12-Lys 162-Asp 90 and Thr 12-Tyr 2-Glu 283 are the catalytic triads involved in L-asparagine hydrolysis, where Thr 12 and Thr 89 are involved in the nucleophilic attack of the substrate (Gesto et al., 2013; Sanches, Kraunchenko &amp; Polikarpov, 2016). Concerning the PF06089.11 family, we identified an N-terminal conserved motif, with sequences NCSGKHxAM, DGCGAPL, SHSGEx(2)H, and PRSx(2)KPxQ probably involved in asparagine hydrolysis. ReAII hydrolyzes L-asparagine at similar levels to Erwinia chrysanthemi, but with PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>The first clade includes ASNases from Streptomyces species S. aureocirculatus (WP_078965752.1), S. cattleya (WP_014151616.1), S. thermoautotrophicus (KWW98572.1), S. himastatinicu (EFL23513.1), S. turgidiscabies (ELP65653.1), S. nanshensis (WP_070201703.1), and S. griseus (WP_030748190.1). The second clade includes ASNases from S. albidoflavus (WP_095730579.1), S. kebangsaanensis (WP_073950513.1), S. fradiae (WP_078649241.1), S. himastatinicus (WP_009718687.1), S. purpureus (WP_078513220.1), and S. paucisporeus (WP_079189481.1). Finally, the third clade PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)Manuscript to be reviewed contains proteins from S.purpurogeneiscleroticus (WP_053609500.1), S. purpurogeneiscleroticus (WP_053610569.1), S. phaeochromogenes (WP_055617501.1), and S. lavenduligriseus (WP_051815467.1) where EcAII was included, suggesting that proteins clustered in this clade share similar properties to EcAII. In addition, two proteins, WP_053609500.1 and WP_055617501.1, exhibited the largest proportion of antigenic regions, with almost the same probability regions as the EcAII protein.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Phylogenetic tree of PF00710.11 (A) and PF06089.11 (B) families. Blue dots highlight</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:1:1:NEW 18 Jun 2020)Manuscript to be reviewed (WP_055617501.1) showed a higher probability of being antigenic, whereas the rest of the ASNases showed very low antigenicity values in comparison with an E. coli ASNase (P00805_EcAII).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. ASNase antigenicity predictions. The antigenicity scores for PF00710.11 family (A) and</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. Epitope mapping of ASNases of the PF familes evaluated, PF00710.11 and PF06089.11.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. 3D protein structure prediction of S. scabrisporus asparaginase II (WP_078980718.1;</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5. SsAII-2 putative binding sites. A) Site A (orange) contains the NCSGKHxAML</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6. EcAII dimer AutoLigand analysis. Cyan EcAII subunit C is shown in cyan and subunit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 7 .</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7. AutoLigand results for EcAII. The minima observed in the total energy graphs per unit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head /><ns0:label /><ns0:figDesc>62, Asn 141, Ser 143, Lys 145, and His 146 are highly conserved in ASNases of the PF06089.11 family.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 8 .</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8. Interaction maps for sites A and B from S. scabrisporus ASNase. The black spheres</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head /><ns0:label /><ns0:figDesc>other words, due to their low content of T-cell epitopes, low antigenicity profile, and low allele coverage, Streptomyces ASNases represent, in terms of immunogenicity, a pharmacological alternative for ALL treatment. In this sense, the Streptomyces brollosae NEAE-115 ASNase has better cytotoxicity and immunogenicity profiles for use in ALL treatment, based on evaluation in a murine model, compared with EcAII (El-naggar et al., 2018). Previously, anticancer activity of the Streptomyces fradiae NEAE-82 ASNase in colon cancer cell cultures was reported (El-Naggar et al., 2016).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure 2 ASNase</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_17'><ns0:head>Figure 4 3D</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_18'><ns0:head>Figure 5 SsAII- 2</ns0:head><ns0:label>52</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_19'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='49,42.52,255.37,525.00,324.75' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>ID Epitope number CPR value Allele number ED</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>P00805_EcAII</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6383</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0114</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053609500.1</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>0.5174</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0171</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053610569.1</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>0.5381</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0196</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_055617501.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4532</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.0112</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_051815467.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.6673</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0060</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078649241.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4554</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0111</ns0:cell></ns0:row><ns0:row><ns0:cell>EFL23513.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6054</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_014151616.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4024</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_095730579.1</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.5346</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078965752.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4987</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0045</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078513220.1</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>0.4551</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0119</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_009718687.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6480</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0052</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_079189481.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.5217</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0051</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_052425051.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.4369</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0170</ns0:cell></ns0:row><ns0:row><ns0:cell>ELP65653.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6717</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0047</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_070201703.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6637</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0069</ns0:cell></ns0:row><ns0:row><ns0:cell>KWW98572.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.7254</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0034</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_073950513.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7424</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0048</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_030748190.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.5125</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0046</ns0:cell></ns0:row><ns0:row><ns0:cell>Q9K4F5_ScAII</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4167</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0053</ns0:cell></ns0:row><ns0:row><ns0:cell>ARZ68596.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6283</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0044</ns0:cell></ns0:row><ns0:row><ns0:cell>SOD64826.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5046</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0080</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078645645.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6404</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0074</ns0:cell></ns0:row><ns0:row><ns0:cell>CDR15801.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5510</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0059</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078980718.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7003</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_044373749.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.7114</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0027</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot' n='1'>Table 2. High-affinity epitope prediction. Epitope number, CPR value, allele coverage,</ns0:note> </ns0:body> "

"Selection of L-asparaginases from Streptomyces strains with competitive activity and immunogenic profiles. A bioinformatic approach Iván González-Torres, Ernesto Pérez-Rueda, Zahaed Evangelista-Martínez, Andrés Zárate-Romero, Alejandro Huerta-Saquero. Rebuttal letter. Dear editor and reviewers, We are very grateful for your opinions and your interest in improving our work. Here we present an answer to the suggested changes and questions. Thank you for your professionalism and constructive criticism. Editor comments (Joseph Gillespie) MAJOR REVISIONS Dear Dr. González-Torres and colleagues: Thanks for submitting your manuscript to PeerJ. I have now received three independent reviews of your work, and as you will see, two of the reviewers raised some concerns about the research (and manuscript). Despite this, these reviewers are optimistic about your work and the potential impact it will have on research studying applied clinical aspects of L-asparaginases. Thus, I encourage you to revise your manuscript, accordingly, taking into account all of the concerns raised by all three reviewers. Please address the robustness issues raised by the reviewers; your literature searches seemed limited and you stand to do well from considering a wider range of organisms. I am less concerned about conducting laboratory work, but a detailed plan about how such work will (or should by others) be carried out. As pointed out by Reviewer 2, your bioinformatic approach would benefit from being able to distinguish between a low Km (clinically relevant) and a high Km (clinically irrelevant) ASNase. Please focus on this in your revision. Therefore, I am recommending that you revise your manuscript, accordingly, taking into account all of the issues raised by the reviewers. Good luck with your revision, -joe Reviewer 1 (Anonymous) Basic reporting Good Experimental design Good Validity of the findings Good Comments for the Author Further genetic engineering studies on L-aspa is highly appreciable! RESPONSE: Thanks for the suggestion. We are working on the cloning of S. scabrisporus asparaginase to validate our bioinformatics approach, in addition to selecting those residues that could be modified to increase its affinity, if required. Reviewer 2 (Arnon Lavie) Basic reporting The manuscript by Gonzales-Torres et al addresses an important need, namely, that of identifying a new asparaginase (ASNase) that would have clinical advantages over the currently approved ASNases (which are anti-leukemic biologic drugs). However, the work has major deficiencies that detract from its impact. This same group proposed in 2012 that an ASNase from Rhizobium etli (ReAII) has ‘therapeutic potential’ (Lines 84-88). This assertion is perplexing since according to the 2012 paper, ReAII has a Km value 600-fold higher than that of EcAII (Table 2 of the 2012 paper) – see point #4 below of ‘Major Issues’ section. In line 214 the authors write that ‘ReAII hydrolyzes L-asparagine as similar levels to EcAII, but with lower activity’ (and site the 2012 paper). This statement gives this reviewer pause, since it demonstrates a total misunderstanding of what type of activity is required for clinical efficacy. We need to care less about the rate of Asn hydrolysis when [Asn] is in the millimolar range. The only relevant number is the rate of Asn hydrolysis at physiological [Asn], which is 50 micromolar. RESPONSE: Thank you very much for the correction. The text should say 'with less affinity'; moreover, the comparison should be done with Erwinia chrysanthemi asparaginase. We agree that an essential characteristic of asparaginases is having a high affinity for their substrate, which, as the reviewer well comments, R. etli's asparaginase does not possess. For this reason, we are looking for alternatives in other microorganisms, taking into account this parameter and its probable antigenicity as its main characteristics. The text was corrected as follows: “ReAII hydrolyzes L-asparagine at similar levels to Erwinia chrysanthemi, but with lower affinity than L-asparaginases from both E. coli and E. chrysantemi”. On the other hand, in the active site prediction section and molecular docking, we focus on characterizing the affinity of S. scabrisporus asparaginase by bioinformatic approaches, since to our knowledge, there is no information regarding the active site of the family PF06089.11 asparaginases, and we know the importance of affinity for a competitive enzyme for the ALL treatment. To do this, we used Autoligand (searching for high-affinity binding pockets) and molecular docking simulations with asparagine as a substrate. Major issues 1. The authors fail to be explicit about what properties would make an asparaginase a suitable anti-cancer drug. They note, correctly, the importance of identifying new ASNases that are ‘less toxic and less immunogenic’ (line 90). However, the authors throughout the manuscript fail the mention the concept of ‘Km value’ and that it is imperative for the ASNase to have a Km value in the low micromolar range. RESPONSE: To clarify more about this topic, we added on introduction section the next sentence: “In this sense, besides searching for less immunogenic asparaginases, it is essential to find those with high affinity for L-asparagine (in the micromolar range) in order to have the potential for therapeutic use”. On the other hand, enzymes for industrial and therapeutic uses require the best kinetic parameters, high affinity (Km), and high catalytic capacity. A simple strategy to improve the catalytic efficiency could be implemented by site-directed mutagenesis as some papers refer. E.g the design of mutants with diminished ability to hydrolyze L-glutamine from Erwinia chrysanthemi L-asparaginase (ErA) (Nguyen and Lavie 2016. The Journal of Biological Chemistry 291, 17664-17676; Nguyen et al 2018. Cancer Res (78) (6) 1549-1560; DOI: 10.1158/0008-5472.CAN-17-2106). With the bioinformatics’ advances exposed in the present paper, we propose tools for the identification of target amino acids for design and substitution as an appealing alternative for conventional experimental mutagenesis methods, which would drastically decrease the required time and expenses. In this sense, we have the possibility to improve the affinity (Km) of the Streptomyces asparaginase in future works. Additional to the above, is clear that for many years the ASNase has been used to treat ALL in children; however, in recent years, there has been an increased interest in using the ASNase to treat ALL in adults. (“Potential” is also referred to this use). In this sense, despite its high anti-leukemic efficacy in childhood, this drug has been used less frequently in adult ALL, because of its specific toxic effects increasing in older people, possibly related to its immunogenicity or by its glutaminase activity (Larson et al 1998. Leukemia. 1998; 12:660–5; Stock et al 2011. Leuk Lymphoma. 52:2237–53). 2. When searching for less immunogenic ASNases, it is puzzling that the authors do not discuss searching mammalian genomes. What is the rationale for focusing on yet another bacterium, when the current ASNases are bacterial and are highly immunogenic? Why not include mammalian ASNases in the search, since, one can make the assumption, that a more human-like ASNase would likely be less immunogenic than a more distant ASNase. RESPONSE: We agree. There are currently reports of human or humanized asparaginase production, which are proposed as a therapeutic alternative for ALL. However, our proposal is different and equally valid, based on the different composition and three-dimensional conformation of the phylogenetically distant asparaginases, which consequently will generate different immune responses. Our approach can expand to other enzymes or other organisms. In this regard, we added on discussion section as follows: “The strategy developed here can be applied to the search for asparaginases in other clades of microorganisms, and even in eukaryotes, specifically mammalian asparaginases, whose evolutionary proximity to humans predicts less immunogenicity”. 3. E. coli has several ASNases. The clinically used one, EcAII is structurally very similar to EcAI. However, whereas EcAII has the required low Asn Km value, EcAI does not. Therefore, any bioinformatic search for a new ASNase must be able to distinguish between a low Km (clinically relevant) and a high Km (clinically irrelevant) ASNase. RESPONSE: We agree. However, Km value is not the only desired characteristic. L-Asparaginase (ASNase) as a vital component of the first-line treatment of acute lymphoblastic leukemia (ALL), and more recently, with potential for preventing metastasis from solid tumors, have a plethora of potential side effects, ranging from immune reactions to severe toxicity. The ASNase from Erwinia carotovora offer an alternative as a second line treatment for patients developing hypersensitivity, even though its affinity is in the millimolar range, like R. etli's asparaginase. An important feature of this last enzyme is that does not share antigenic cross-reactivity with the E. coli enzyme. These conditions (reduced immunogenicity and cross-reaction) attracted scientists for discovering new enzymes in many other organisms. In fact, continuous investigations for L-asparaginase obtained from alternative sources as therapeutic agents for the management of ALL and other related malignancies have been done. (Shrivastava et al. 2016). Recent developments in L-asparaginase discovery and its potential as an anticancer agent. Critical Reviews in Oncology/Hematology, 100, 1–10; Brumano et al. (2019). Development of L-Asparaginase. Biobetters: Current Research Status and Review of the Desirable Quality Profiles. Front. Bioeng. Biotechnol. 6:212.). The authors need to include a section on how the bioinformatic tools that they use make this differentiation (if they do). If the tools do NOT make this differentiation, that this work is largely not helpful since it misses the top criterium for an efficient ASNase. RESPONSE: As mentioned previously, the active site prediction and molecular docking sections are directed at that purpose, determining with these bioinformatic tools, the possibility of selecting those asparaginases with the best enzyme-substrate coupling values, which suggests a higher affinity. To further clarify this point, we add the following text: “In this work, we develop a strategy based on bioinformatics tools to analyze and select ASNases from Streptomyces for ALL treatment, taking advantage of its phylogenetic distance from E. coli, looking for those candidates that meet the two fundamental criteria: asparaginases with high affinity for asparagine (using active site prediction tools and molecular docking), and that have lower immunogenicity (using antigenicity and protein structure prediction tools).” If the authors believe that by adding EcAI to the phylogenetic analysis this was actually done, they are asked to be more explicit about it. Also, please discuss the presence of a periplasmic secretion sequence in EcAII but not in EcAI, and whether this can act as a differentiator between Type I and Type II ASNases (and as such, predict ASNases with low Km value). The authors hint at this (Line 198), but if so, it needs more explicit discussion. RESPONSE: Agree. We expand this topic adding the following text on phylogenetic analysis of ASNases section: “. It is noteworthy that asparaginases can also be classified according to subcellular localization, a) periplasmic asparaginases containing secretion signal peptide and, b) asparaginases with intracellular localization. The former generally have a higher affinity for asparagine. However, according to their architecture, both types of proteins can be found in the PF00710.11 or PF06089.11 families. This is the case of E. coli asparaginases I and II, both belonging to the PF00710.11 family (https://pfam.xfam.org/family/PF00710#tabview=tab1)”. 4. As discussed above, Km is the most important parameter for clinical relevance. It is unclear why the authors include ReAII in their analysis since it has a Km that is way too high. RESPONSE: To emphasize this important observation, we add the following text: “The main characteristics to select asparaginases with therapeutic potential are the high affinity for L-asparagine (in the micromolar range), null or low glutaminase cross-activity, as well as a different three-dimensional folding from the E. coli asparaginase, which suggests different immunogenicity. In this work, we develop a strategy based on bioinformatics tools to analyze and select ASNases from Streptomyces for ALL treatment, taking advantage of its phylogenetic distance from E. coli, looking for those candidates that meet the two fundamental criteria: asparaginases with high affinity for asparagine (using active site prediction tools and molecular docking), and that have lower immunogenicity (using antigenicity and protein structure prediction tools)”. 5. The authors write that ASNases with sequences homologous to that of ScAII (S. coelicolor type II) are in the same family as that of ReAII. In other words, those ASNases in family PF06089.11 are, to my understanding, not suitable for clinical use based on a predicted high Asn Km value. So why are these even considered in this work? RESPONSE: According to our knowledge, the classification of asparaginases in the PF00710 and PF06089 families is based on the active site position within the amino acid sequence of the protein and not necessarily due to their affinity characteristics for its substrate. As an example, E. coli asparaginases I and II, which have different kinetic properties, -one has signal peptide and the other does not, so one is periplasmic and the other cytoplasmic-, and yet they belong to the same family, according to its architecture. We used R. etli asparaginase because it belongs to the PF06089 family, with a different architecture from that of E. coli. 6. The authors find that the ReAII family (PF06089.11) is predicted to be less immunogenic than the EcAII family (PF00710.11). Assuming this is correct, it does not suggest that PF06089.11 family members be tested since they would be predicted to have a high Km, and hence, clinically, irrelevant. RESPONSE: As discussed, the classification of families depends on their architecture and not on their kinetic parameters. Our initial search criteria were the structural one, but followed by the analysis of the prediction of active site and affinity for its substrate, in order to select asparaginase with therapeutic potential. 7. This reviewer sees no value in the protein structure predictions. Can these predictions say something about the Km value? I think not. If the authors disagree, please explain how these data would inform the selection of an ASNase to test. RESPONSE: Structural predictions do not give a direct Km value, but they do provide important data on the affinity of a particular region (predicted active site) and its substrate. For this purpose, searches of the active site were carried out using Autoligand, and blind molecular docking with Autodock 4.2. These software predict maximum affinity interaction sites from regions with lower free energy binding and lower volume of interaction with the substrate. The results of these analyzes were complemented and can be seen in Tables 3 and 4. 8. At the end of the day, the proof of the pudding is in the eating. In other words, the authors need to pick the ‘best’ ASNase based on the predictions of all of the programs that they ran, express it, and confirm that it has the required low Km value. Without such confirmatory work, the value of this report is deemed low. RESPONSE: Partially agree. We are working on the cloning of S. scabrisporus asparaginase to validate our bioinformatics approach, in addition to selecting those residues that could be modified to increase its affinity, if required. However, these bioinformatics tools and the proposed strategy represent, by themselves, an important contribution. Minor issues 1. Line 51: there are actually 4, not 3 ASNase formulations currently available. A new PEGylated EcA formulation, which is different to Oncaspar by only having a different linker between enzyme and PEG, has been recently approved. RESPONSE: The new formulation was added to the text. 2. Line 53: In the US, Elspar (EcAII) is not used anymore, and Oncaspar (EcAII-PEG) has become the first line treatment. RESPONSE: Corrected properly. 3. Line 61: please look into liver toxicity as well. RESPONSE: Corrected properly. 4. Line 71: please explain why you connect the glutaminase co-activity with allergic reactions. I can understand why the bacterial origin would cause an allergic reaction, but why do you include the glutaminase activity. Of course, the glutaminase activity is likely to be behind many of the other toxicities seen with asparaginases (but not immunogenicity). RESPONSE: We agree. The paragraph was corrected properly. “Allergic reactions to ASNase, which are associated with its bacterial origin, range from mild urticaria to life-threatening anaphylactic shock. Irritation, fever, vomiting, gastrointestinal edema, and breathing difficulties are symptoms frequently reported (Lanvers-Kaminsky, 2017).” Grammar/English suggestions 1. The word ‘Selection’ in the title is misleading since it implies some sort of an experimental selection assay. A more appropriate word would be ‘Identification’. RESPONSE: We agree. The title paper was changed accordingly. 2. Line 27; move ‘predicted’ to the front; i.e. ‘Based on it predicted low immunogenicity…..’ RESPONSE: Corrected properly. 3. Line 69; these ‘enzymes’ should be these ‘antibodies’ RESPONSE: Corrected properly. 4. Line 84; typo; ASNasa  ASNase RESPONSE: Corrected properly. 5. Line 138; DRB1*11:01 is listed twice. RESPONSE: Corrected properly. Experimental design Included above Validity of the findings Included above Reviewer 3 (Anonymous) Basic reporting The authors use appropriate concise language and provide a relevant introduction discussion that describes the current state of the field and limitations to current asparaginase therapy during the treatment of leukemias. The figure legends and labels are appropriate and clear. Experimental design The authors use sophisticated methods for their research objective aiming to identify a new asparaginase source that can be less immunogenic relative to currently used preparations. However, there are a few areas of opportunity to clarify their approach using the Immune Epitope Database (IEDB). In particular, with regards to the following: 1. For epitope density (ED) estimation, the equation used includes a parameter “Predicted epitope” which is not clear. Is this the CPR of the predicted epitope? If so, it should be clarified. RESPONSE: Thank you very much for the observation. “Predicted epitope is the number of epitopes with a CPR < 1.” It was corrected properly. 2. For Table 2: a. The authors should clarify whether “epitope number” refers to the number of epitopes with CPR < 1. b. For HLA “Allele number” on table 2, the authors should clarify whether this refers to the # of HLA alleles (out of 8) where that particular epitope has a CPR < 1. RESPONSE: Thank you. We added a footnote clarifying both concepts. We added next information: “Epitope number refers to the number of epitopes with CPR < 1. Allele number is the number of allele coverage for high affinity epitopes (with a CPR < 1).” Generally, the antigenicity/HLA binding data is used clearly to compare to E. coli asparaginase (EcAII). The manuscript would benefit by including the same analysis for Erwnia asparaginase (ErAII), as both preparations are used clinically. Furthermore, demonstrating that epitopes of EcAII and ErAII don’t cross-react with asparaginase from Streptomyces scabrisporus is key for recommending it as a therapeutic option after immune responses to both agents (not clear from Fig. 3). RESPONSE: The Erwinia chrysanthemi asparaginase belongs to the same family of E. coli asparaginase (PF00710 family), conserving similar architecture, so we do not consider a comparison necessary, as a similar result is assumed. The different architecture of the PF006089 family of asparaginase motivated the comparative analysis, so the best known and asparaginase used in the treatment against ALL was used as an example. Validity of the findings The authors’ conclusions are supported by their results. However, an important limitation of the study is that the stability of asparaginase from Streptomyces scabrisporus in plasma or serum was not assessed or estimated. The authors should acknowledge importance of PK properties/clearance for identifying a suitable alternative asparaginase preparation that can be used clinically. Note that an asparaginase with high clearance will have low immunogenicity due to decreased immune cell presentation. RESPONSE: Thank you. Nowadays, we are working on the cloning of S. scabrisporus asparaginase to validate our bioinformatics approach, and as the reviewer points out, we will determine the stability of asparaginase, in serum, cell cultures and animal models. Comments for the Author The manuscript by Gonzales -Torres et al. presents a computational approach for identifying less immunogenic forms of the chemotherapeutic agent asparaginase. The authors use a novel approach that screens candidates for antigenicity and binding to MHC class II alleles, which is an important consideration for therapeutic asparaginases. Based on their search and approach, they identify a previously uncharacterized L-asparaginase from Streptomyces scabrisporus as a promising therapeutic candidate that can be used after human immune responses to PEGylated E. coli asparaginase and/or Erwinia asparaginase. The authors focus on an important research question related to asparaginase therapy, which is an essential component of pediatric leukemia treatment protocols worldwide. Their approach using bioinformatic tools to assess whether a particular asparaginase would have a high probability of a human immune response is novel and provides a new tool or strategy for screening potential therapeutic enzymes. The strength of the manuscript is the approach used for identifying their proposed asparaginase. The most important issue is providing a more detailed discussion and conclusion on whether Streptomyces scabrisporus asparaginase would cross-react after E. coli or Erwinia asparaginase. RESPONSE: We agree. We hope that with the modifications suggested by all the reviewers, this point has become much clearer in the new version of our manuscript. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The enzyme L-asparaginase from Escherichia coli is a therapeutic enzyme that has been a cornerstone in the clinical treatment of acute lymphoblastic leukemia for the last decades.</ns0:p><ns0:p>However, treatment effectiveness is limited by the highly immunogenic nature of the protein and its cross-reactivity towards L-glutamine. In this work, a bioinformatic approach was used to identify, select and computationally characterize L-asparaginases from Streptomyces through sequence-based screening analyses, immunoinformatics, homology modeling, and molecular docking studies. Based on its predicted low immunogenicity and excellent enzymatic activity, we selected a previously uncharacterized L-asparaginase from Streptomyces scabrisporus. Furthermore, two putative asparaginase binding sites were identified and a 3D model is proposed. These promising features allow us to propose L-asparaginase from S. scabrisporus as an alternative for the treatment of acute lymphocytic leukemia.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Acute lymphocytic leukemia (ALL) is a hematological disorder of the bone marrow and is characterized by abnormal proliferation of immature lymphoid line cells, blocked at an early stage of cell differentiation, that accumulate and replace healthy hematopoietic cells in the bone marrow <ns0:ref type='bibr' target='#b45'>(Pui, Relling &amp; Downing, 2004;</ns0:ref><ns0:ref type='bibr' target='#b42'>Onciu, 2009)</ns0:ref>. ALL occurs predominantly in children of 1-4 years of age and represents approximately 25% of childhood cancers and about 80% of leukemias <ns0:ref type='bibr' target='#b32'>(Katz et al., 2015)</ns0:ref>.</ns0:p><ns0:p>Although in most cases the risk factors and pathogenicity associated with ALL have not been clearly identified, the etiology of the disease has been mainly associated with a variety of conditions; cytogenetic alterations, mutations to key genes that regulate cellular proliferation, PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed differentiation and death; presence of oncogenic viruses, immunodeficiency, exposure to pesticides, solvents, and ionizing radiation <ns0:ref type='bibr' target='#b45'>(Pui, Relling &amp; Downing, 2004;</ns0:ref><ns0:ref type='bibr' target='#b4'>Bassan, Maino &amp; Cortelazzo, 2016)</ns0:ref>.</ns0:p><ns0:p>Treatment for ALL patients involve steroid drugs, prednisone, vincristine, and the enzyme Lasparaginase (ASNase) <ns0:ref type='bibr' target='#b2'>(Avramis, 2012;</ns0:ref><ns0:ref type='bibr' target='#b54'>Schwab &amp; Harrison, 2018)</ns0:ref>. ASNase has been essential in the treatment of ALL since the 1970s, with demonstrated effectiveness as an individual drug with remission rates of up to 68% <ns0:ref type='bibr' target='#b48'>(Salzer et al., 2017)</ns0:ref>. The combination of ASNase with other anticancer drugs has led to remission rates of up to 90% (Lanvers-Kaminsky, 2017).</ns0:p><ns0:p>Currently, there are four ASNase formulations available for the ALL treatment: two native forms of the enzyme, obtained from Escherichia coli (EcAII) and Erwinia chrysanthemi (ErAII), and pegylated E. coli ASNase (EcAII-PEG), as well as pegylated E. chrysanthemi ASNase (ErAII-PEG). Of these, EcAII-PEG has become the first-line treatments for ALL in the US, with EcAII the most widely used formulation. ErAII is administered to patients who have developed hypersensitivity to the above formulations <ns0:ref type='bibr' target='#b44'>(Pieters et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abribat, 2016;</ns0:ref><ns0:ref type='bibr' target='#b3'>Barba et al., 2017)</ns0:ref>.</ns0:p><ns0:p>In recent years, evidence has been accumulating of its usefulness as an important component in the treatment of other hematological malignancies, such as acute myeloid leukemia, myelosarcoma, lymphosarcoma, Hodgkin's disease, and chronic lymphocytic leukemia <ns0:ref type='bibr' target='#b13'>(Emadi, Zokaee &amp; Sausville, 2014;</ns0:ref><ns0:ref type='bibr'>Lopes et al., 2015)</ns0:ref>. Despite their high antileukemic potential, the use of ASNases in the treatment of ALL is limited by their toxicity. Among the adverse effects that have been reported are leukopenia, immune suppression, acute pancreatitis, liver dysfunction, hyperglycemia, abnormalities in hemostasis, and hemorrhages of the central nervous system <ns0:ref type='bibr' target='#b53'>(Schein et al., 1969;</ns0:ref><ns0:ref type='bibr' target='#b46'>Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b9'>Chan et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b1'>Ali et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b25'>Hijiya &amp; van der Sluis, 2016;</ns0:ref><ns0:ref type='bibr' target='#b30'>Kamal et al., 2019)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The generation of immune responses during treatment with ASNase is a common condition that has been reported in up to 75% of patients. These reactions depend on the formulation used, the mode of administration (intravenous or intramuscular), and the treatment protocol <ns0:ref type='bibr' target='#b24'>(Hijiya &amp; van der Sluis, 2015)</ns0:ref>. For example, between 30 and 75% of patients that receive the native form of the E. coli enzyme experience hypersensitivity reactions, and about 70% develop anti-EcAII antibodies after drug administration <ns0:ref type='bibr' target='#b5'>(Battistel et al., 2020)</ns0:ref>; these antibodies lead to rapid inactivation of the enzyme <ns0:ref type='bibr' target='#b60'>(Walenciak et al., 2019)</ns0:ref>. Allergic reactions to ASNase, which are associated with its bacterial origin, range from mild urticaria to life-threatening anaphylactic shock. Irritation, fever, vomiting, gastrointestinal edema, and breathing difficulties are symptoms frequently reported (Lanvers-Kaminsky, 2017). On the other hand, adverse effects have been reported due to the toxicity produced by glutaminase cross activity, such as leukopenia, immune suppression, acute pancreatitis, hyperglycemia, thrombosis, neurotoxicity, and liver failure, among others <ns0:ref type='bibr' target='#b46'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b9'>Chan et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b1'>Ali et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Different strategies to reduce the toxicity of ASNase have been reported, including modifications in the structure of the protein by mutagenesis, design of mutants with diminished ability to hydrolyze L-glutamine, chemical modifications in specific amino acids, and modifications to drug formulations <ns0:ref type='bibr' target='#b46'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b40'>Nguyen, Su &amp; Lavie, 2016;</ns0:ref><ns0:ref type='bibr' target='#b41'>Nguyen et al., 2018)</ns0:ref>. Covalent conjugation of the enzyme with polyethylene glycol, known as PEGylation, reduces the incidence of hyperglycemia, pancreatitis, and anaphylaxis. This specific modification increase the half-life of the enzyme and reduces the frequency of drug administration <ns0:ref type='bibr' target='#b59'>(Thomas &amp; Le Jeune, 2016)</ns0:ref>.</ns0:p><ns0:p>On the other hand, the exploration of new sources of ASNases offers the possibility of finding versions of the enzyme with different pharmacological characteristics, potentially useful for the</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Identification and selection of homologous L-Asparaginases</ns0:head><ns0:p>Putative ASNases from Streptomyces were identified through a BLASTp search against the NR database of the NCBI using as seeds the amino acid sequences of EcAII (ID P00805) and Streptomyces coelicolor type II ASNase (ScAII; ID Q9K4F5). The search was restricted to the Streptomyces taxon (Taxid 1883), and an E-value less than 1e-06 was considered significant.</ns0:p><ns0:p>Partial proteins and those from unidentified Streptomyces strains were excluded. In a posterior step, the set of protein sequences was filtered at 60% identity as cutoff to avoid redundancy, using the CD-Hit program (http://weizhongli-lab.org/cdhit_suite/cgi-bin/index.cgi) <ns0:ref type='bibr' target='#b26'>(Huang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>Each cluster was analyzed using the HMMER program on the PFAM server (http://pfam.xfam.org/) to determine the protein family to which they belonged <ns0:ref type='bibr' target='#b17'>(Finn, Clements &amp; Eddy, 2011;</ns0:ref><ns0:ref type='bibr' target='#b18'>Finn et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.2'>Phylogenetic analysis</ns0:head><ns0:p>ASNases amino acid sequence alignments were performed using Clustal Omega <ns0:ref type='bibr' target='#b55'>(Sievers et al., 2011)</ns0:ref> with default parameters. The quality of the alignments was improved using the model PF06089.11 or PF00710.11 of ASNase, as required. Multiple sequence alignment statistics were computed with AliStat (http://www.csb.yale.edu/userguides/seq/hmmer/docs/node27.html).</ns0:p><ns0:p>Phylogenetic analyses were carried out using the maximum-likelihood method with the program Mega 7. The WAG model was chosen as substitution model, and 1000 replicates were performed.</ns0:p><ns0:p>The best tree was calculated using the majority rule. Additionally, E. coli type I ASNase <ns0:ref type='bibr'>(EcAI)</ns0:ref> was included in the phylogenetic analysis of the PF00710.11 cluster. EcAI is closely related to PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed EcA but it does not have therapeutic potential. For the PF06089.11 cluster, Rhizobium etli type II ASNase (ReAII) was included in the analysis.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.3'>Antigenicity prediction</ns0:head><ns0:p>The prediction of the probability of antigenicity of each ASNase was calculated with the server ANTIGENpro (http://scratch.proteomics.ics.uci.edu/) <ns0:ref type='bibr' target='#b37'>(Magnan et al., 2010)</ns0:ref>. ANTIGENpro is a sequence-based, alignment-free, protein antigenicity predictor with an estimated accuracy of 82%.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.4'>HLA class II binding prediction</ns0:head><ns0:p>The amino acid sequence of each candidate ASNase was screened for T-cells epitopes with the MHC II Analysis Resource at the Immune Epitope Data Base (IEDB) server and HLA-DRB1*15:01. The IEDB-recommended method uses the consensus approach, combining <ns0:ref type='bibr'>NN-align, SMM-align, CombLib, Sturniolo, and NetMHCIIpan (Wang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>For each peptide, a percentile rank is generated by comparing the peptide's score against the scores of five million random 15-mer selected from SWISSPROT database, and the median percentile rank is used to calculate a consensus percentile rank (CPR). Peptides with a CPR &lt; 2 were defined as high-affinity binders and thus selected for epitope density (ED) calculation. Multiple 9-mer cores were identified in overlapped 15-mer peptides. To reduce overestimation of predicted peptides, only the 9-mer cores, predicted by using the Sturniolo method <ns0:ref type='bibr' target='#b57'>(Sturniolo et al., 1999)</ns0:ref> PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed and with a CPR &lt; 1, were considered for the analysis. Finally, epitope density (ED) was calculated using the follow equation, modified from <ns0:ref type='bibr' target='#b52'>(Santos et al., 2013)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_0'>&#119864;&#119863; = &#119875;&#119903;&#119890;&#119889;&#119894;&#119888;&#119905;&#119890;&#119889; &#119890;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; * (2 -&#119860;&#119891;&#119891;&#119894;&#119899;&#119894;&#119905;&#119910; &#119886;&#119907;&#119890;&#119903;&#119886;&#119892;&#119890; ( &#119888;&#119901;&#119903; ) ) &#119875;&#119903;&#119900;&#119905;&#119890;&#119894;&#119899; &#119897;&#119890;&#119899;&#119892;&#119905;&#8462; &#119904;&#119894;&#119911;&#119890; -&#119864;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; &#119904;&#119894;&#119911;&#119890; + 1</ns0:formula><ns0:p>Where Predicted epitope is the number of epitopes with a CPR &lt; 1.</ns0:p><ns0:p>Epitope coverage was calculated as the number of alleles covered by the epitope consensus, according to the following assumption: when a small number of alleles is covered, a lower percentage of the population will develop sensitivity to ASNase.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.5'>Protein structure prediction, refinement and quality assessment</ns0:head><ns0:p>The three-dimensional structures of the selected ASNases was modeled by homology using the I-Tasser server (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) <ns0:ref type='bibr'>(Zhang, 2008)</ns0:ref>. In brief, starting from an amino acid sequence, I-Tasser generates three-dimensional atomic models from multiple threading alignments and iterative structural assembly simulations. A C-score, provided as an estimate of the accuracy of the models generated, typically ranges between -5 to +2, with a higher value indicating higher confidence, and vice versa <ns0:ref type='bibr' target='#b47'>(Roy, Kucukural &amp; Zhang, 2010)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the model with the higher C-score was selected and then refined using the ModRefiner server (https://zhanglab.ccmb.med.umich.edu/ModRefiner/). ModRefiner improves the physical quality and structural accuracy of three-dimensional protein structures by a two-step, atomic-level energy minimization <ns0:ref type='bibr' target='#b63'>(Xu &amp; Zhang, 2011)</ns0:ref>. Finally, the quality of the models was evaluated by RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php), Qmean (https://swissmodel.expasy.org/qmean/), and Verify3D (http:/servicesn.mbi.ucla.edu/Verify3D).</ns0:p></ns0:div> <ns0:div><ns0:head n='1.6'>Molecular docking</ns0:head><ns0:p>The molecular coupling was carried out using Autodock Tools software <ns0:ref type='bibr' target='#b51'>(Sanner, 1999;</ns0:ref><ns0:ref type='bibr' target='#b39'>Morris et al., 2009)</ns0:ref>. EcAII (PDB ID: 3ECA) was recovered from the PDB protein database (http://www.rcsb.org/) <ns0:ref type='bibr' target='#b58'>(Swain et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b6'>Berman et al., 2000)</ns0:ref>. Once refined, selected ASNase structures were prepared using Dock prep at UCSF Chimera and refined using the Gasteiger method <ns0:ref type='bibr' target='#b20'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>The three-dimensional structures of the asparagine and glutamine ligands were obtained from the DrugBank repository (https://www.drugbank.ca/; accession numbers DB00174 and DB00130, respectively) <ns0:ref type='bibr' target='#b62'>(Wishart et al., 2018)</ns0:ref>. The preparation of the ligands was carried out by the Gasteiger method and, finally, the allocation of the rotation centers was determined <ns0:ref type='bibr' target='#b20'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the search box was focused on previously proposed active sites. The box size was defined to cover all residues of the ligand binding site, using a grid size of 0.375 &#197;.</ns0:p><ns0:p>Blind molecular docking was performed with Autodock 4.2 software, using the Lamarckian genetic algorithm, with 1000 runs, for a population size equal to 150, with 2.5 x 10^6 evaluations, a mutation rate equal to 0.02 in 27,000 generations.</ns0:p><ns0:p>In addition, the active site location was predicted by AutoLigand <ns0:ref type='bibr' target='#b23'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Briefly, AutoLigand identifies sites of maximum affinity from maps generated by AutoGrid, finding regions with better energy and a lower volume. <ns0:ref type='table'>PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>L-Asparaginases from Streptomyces cluster into two type families according to its protein architecture</ns0:head><ns0:p>The Blast search against the Streptomyces taxon revealed 296 putative ASNases homologous to EcAII and 703 homologous to ScAII with a significant score. After manual examination of both groups, 136 and 311 complete sequences were kept for EcAII and ScAII groups, respectively. Protein domain analysis using PFAM server showed that 136 sequences are related to the PF00710.11 family of N-terminal ASNases. For sequences homologous to ScAII, PFAM analysis revealed that they belong to the PF06089.11 family of ASNases, a group of enzymes related to ReAII, a thermolabile enzyme induced by L-asparagine and repressed by the carbon source <ns0:ref type='bibr' target='#b38'>(Moreno-Enriquez et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b27'>Huerta-Saquero et al., 2013)</ns0:ref>. Representative clusters for PF00710.11 and PF06089.11 families obtained using the CD-Hit suite program were generated at a 60% identity cutoff, with 19 and 7 putative ASNases, respectively (Table <ns0:ref type='table'>1</ns0:ref>). ASNases sequences showed similar lengths in both clusters, ranging from 320 to 420 amino acids. Manuscript to be reviewed lower affinity than L-asparaginases from both E. coli and E. chrysanthemi <ns0:ref type='bibr' target='#b38'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Furthermore, ReAII is the only ASNase characterized from the PF06089.11 family</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Phylogenetic analysis of ASNases</ns0:head><ns0:p>For the PF00710.11 family, EcAI was added to the multiple sequence alignment in order to know the relationship between this ASNase and the candidate ASNases. EcAI belongs to the same family of proteins as EcAII, but it does not represent a therapeutic option for ALL treatment. It is noteworthy that asparaginases can also be classified according to subcellular localization, a) periplasmic asparaginases containing secretion signal peptide and, b) asparaginases with intracellular localization. The former generally have a higher affinity for asparagine. However, according to their architecture, both types of proteins can be found in the PF00710.11 or PF06089.11 families. This is the case of E. coli asparaginases I and II, both belonging to the PF00710.11 family (https://pfam.xfam.org/family/PF00710#tabview=tab1). We found that the ASNase with accession number WP_059134811.1 of Streptomyces alboniger is grouped in the same clade as EcAI, and so it was excluded from subsequent analyses (Figure <ns0:ref type='figure' target='#fig_15'>1A</ns0:ref>).</ns0:p><ns0:p>The phylogenetic reconstruction showed three well-defined clades (Figure <ns0:ref type='figure' target='#fig_15'>1A</ns0:ref>). On the other hand, for the ASNases of PF06089.11, phylogenetic analysis included both the ASNase sequence of R. etli and S. coelicolor (ReAII and ScAII, respectively) (Figure <ns0:ref type='figure' target='#fig_15'>1B</ns0:ref>). The tree defines two clades. In the first one, where the ScAII was included, we also considered ARZ68596.1 from S. albireticuli, SOD64826.1 from S. zhaozhouensis, WP_078645645 from S. varsoviensis, CDR15801.1 from S. iranensis, and WP_020554088 from S. scabrisporus.</ns0:p><ns0:p>In the second clade were included the following proteins: WP_044373749 from S. ahygroscopicus and WP_078980718.1 from S. scabrisporus. </ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Antigenicity predictions</ns0:head><ns0:p>The results for antigenicity showed a likelihood of being antigenic for all ASNases in both sets that was lower than that of EcAII (Figure <ns0:ref type='figure' target='#fig_5'>2</ns0:ref>). Nevertheless, among selected Streptomyces ASNases, the candidates from S. purpurogeneiscleroticus (WP_053609500.1) and S. phaeochromogenes </ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>T-cell epitope analysis</ns0:head><ns0:p>After antigenicity prediction, the ED, the total number of high-affinity epitopes, the affinity epitopes, and the number of HLA alleles covered by each ASNase were calculated. The results showed that the ASNases with accession numbers WP_053609500.1, WP_053610569.1, EFL23513.1, WP_095730579.1, WP_078513220.1, and WP_052425051.1 have higher EDs than the reference (P00805_EcAII; ED=0.01114; 5 covered alleles) (Figure <ns0:ref type='figure' target='#fig_7'>3</ns0:ref>).</ns0:p><ns0:p>On the other hand, the ASNase with the lowest predicted ED was WP_044373749.1, with an ED of 0.0027 and a coverage of 4 alleles, following by WP_095730579.1 (2 alleles), ELP65653.1 (3 alleles), and Q9K4F5 (3 alleles) (Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p><ns0:p>Additionally, the distribution of epitopes was mapped into the sequences of the ASNases (Figure <ns0:ref type='figure' target='#fig_7'>3</ns0:ref>). ASNases of the PF06089.11 family tended to have a lower ED (Table <ns0:ref type='table'>3</ns0:ref>) as well as lower allele coverage than those of the PF00710.11 family (Figure <ns0:ref type='figure' target='#fig_7'>3</ns0:ref>). Manuscript to be reviewed Next, ASNases with lower allele coverage, lower ED, and lower probability of antigenicity were selected for further analysis. S. coelicolor (Q9K4F5), S. scabrisporus (WP_078980718.1), and S. albireticuli (ARZ68596.1) were selected as promising enzymes.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>Protein structure predictions</ns0:head><ns0:p>From selected ASNases, homology-based models were generated (I-Tasser). For the subsequent analysis, the S. scabrisporus asparaginase II model, which had the highest C-value, was chosen (WP_078980718.1 SsAII-2) (Figure <ns0:ref type='figure' target='#fig_8'>4</ns0:ref>). The stereochemical quality of the models was evaluated using Ramachandran plots. In order to improve the quality of the models, these were structurally refined with ModRefiner and reassessed with RAMPAGE. In addition, the Verify3D server was used to determine the compatibility of the three-dimensional model with the amino acid sequence.</ns0:p><ns0:p>Based on the predicted structure, ASNase WP_0789718.1 (PF06089.11 family) is related in terms of folding to the beta-lactamase family. Beta-lactamases (SCOP data base, entry 56600) consist of a cluster of alpha-helices and an alpha/beta sandwich. This folding is also found in transpeptidases, esterases, penicillin receptors, D-aminopeptidases, and glutaminases (InterPro IPR012338). </ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>Active site prediction</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>In order to identify the active site residues of the S. scabrisporus ASNase (WP_0789718.1), three approaches were used: genomic comparison, blind molecular coupling simulation, and search for high-affinity binding pockets with AutoLigand (active site). To our knowledge, there is no information regarding the active site of the family PF06089.11 ASNases, so genomic comparison was not possible. Using AutoLigand, two possible high affinity binding sites for L-asparagine were identified (Figure <ns0:ref type='figure' target='#fig_9'>5A</ns0:ref>). The first (site A) had a volume of 121 &#197; 3 and an energy per volume equal to -0.2149 kcal/mol &#197; 3 ; the second (site B) had a volume of 101 &#197; 3 and an energy per volume equal to -0. 2136 kcal/mol &#197; 3 . Site A is located between an alpha-helix in the amino terminal containing the 57 PRSx(2)KPxQ 65 motif, and a loop in the central region of the enzyme, containing the 141 NCSGKHxAML 150 motif (Table <ns0:ref type='table'>3</ns0:ref>). Site B is located in a pocket formed by a set of alphahelices in the amino terminal of the protein, marked by the presence of the 87 SHTGQxHFV 95 motif.</ns0:p><ns0:p>On the other hand, by performing AutoDock 4.2 whole-protein molecular coupling simulations, we found that the best ligand-enzyme interaction (L-asparagine-ASNase), with a binding free energy of -4.17 kcal/mol, targeted residues corresponding to the 141 NCSGKHxAML 150 motif, which correspond to the site A (Figure <ns0:ref type='figure' target='#fig_9'>5B</ns0:ref>). Additionally, in order to validate AutoLigand analysis searching active sites in the S. scabrisporus ASNases, a search for binding sites in EcAII was performed. To do this, the monomeric, dimeric, and tetrameric forms of the enzyme (the latter is the catalytically active form) were analyzed using PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed the same conditions used for SsAII-2. It was found that AutoLigand successfully identified the binding site of L-Asn, consisting of Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, and Lys 162 and also Asn 248 and Glu 283 (Figure <ns0:ref type='figure' target='#fig_10'>6</ns0:ref>), the latter two only for dimeric and tetrameric forms. The sites found (red squares curves) had energies by volume equal to -0.2119, -0.2242, and -0.2366 kcal/mol &#197; 3 and a volume of 136, 122, and 102 &#197; 3 for the monomer, dimer, and tetramer, respectively (Figure <ns0:ref type='figure' target='#fig_11'>7</ns0:ref>). It is relevant that for both the dimeric and the tetramer forms, AutoLigand successfully identified L-Asn binding pockets in EcAII: the pocket formed between the aminoterminal end of subunit A and the carboxy terminal of the subunit C, as well as equivalent pockets for dimer BD. In addition, several other solutions found by AutoLigand (curve with blue or green squares), using up to 90 filling points, converge in the different joint pockets formed by dimers. Manuscript to be reviewed 2.7 Molecular docking Molecular docking simulations were performed at the putative sites found (Table <ns0:ref type='table'>4</ns0:ref>). For EcAII, as the reference ASNase, Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, Asn 248, and Glu 283 were established as flexible residues; meanwhile, molecular docking for S. scabrisporus ASNase were performed using only the rigid structure of the protein, without defining flexible side chains for L-asparagine binding.</ns0:p><ns0:p>Our results showed a higher affinity for L-asparagine of the S. scabrisporus ASNase site A than site B; however, the affinity was lower than that for EcAII. For S. scabrisporus ASNase site A, the L-asparagine interacts with residues Ser 59, Lys 62, Asn 141, Ser 143, Lys 145, His 146, Gly 237, Lys 255, and Gly 256 (Figure <ns0:ref type='figure' target='#fig_13'>8A</ns0:ref>); for site B, the residues that interact with L-asparagine are Ala 84, Gly 78, Ser 87, Tyr 163, Leu 164, and Asp165 (Figure <ns0:ref type='figure' target='#fig_13'>8B</ns0:ref>). Interestingly, from site A, Lys Manuscript to be reviewed with no glutaminase activity and with a different immunogenic profile than EcAII <ns0:ref type='bibr' target='#b27'>(Huerta-Saquero et al., 2013)</ns0:ref>. The search for homologous sequences resulted in two sets of sequences with a high probability of being ASNases (E value &lt;1e-06). These sequence sets, in turn, were classified into two different protein families based on their homology, using HMMer: PF00710.11 and PF06089.11, according to the classification of the PFAM database. So far, most of the reported ASNases belong to the PF00710.11 family and have been extensively studied. EcAII and the E.</ns0:p><ns0:p>chrysanthemi ASNase belong to this family. On the other hand, the PF06089.11 family represents a group of atypical ASNases that remain poorly characterized. Some representative reports about these ASNases include the R. etli ASNase <ns0:ref type='bibr' target='#b43'>(Ortu&#241;o-Olea &amp; Dur&#225;n-Vargas, 2000;</ns0:ref><ns0:ref type='bibr' target='#b38'>Moreno-Enriquez et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b27'>Huerta-Saquero et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Interestingly, the BLAST results showed a greater abundance of PF06089.11 family sequences compared to the PF00710.11 family in Streptomyces. In addition, we found that about 20% of species have ASNase isoforms. In that sense, many Gram-negative bacteria have at least two isozymes of the family PF00710.11 <ns0:ref type='bibr' target='#b16'>(Fern&#225;ndez &amp; Z&#250;&#241;iga, 2006)</ns0:ref> and, in E. coli, the existence of a third isoenzyme has been recently reported <ns0:ref type='bibr' target='#b10'>(Correia da Silva et al., 2018)</ns0:ref>. Historically, the genus Streptomyces has been attractive due to the wide repertoire of bioactive molecules produced.</ns0:p><ns0:p>However, searching for ASNases of pharmacological interest has been done only rarely.</ns0:p><ns0:p>After the identification of two sets of ASNases, we chose T-cell ED as the immunogenicity indicator, according to <ns0:ref type='bibr'>Cantor et al. (2004</ns0:ref><ns0:ref type='bibr'>), Fern&#225;ndez et al. (2012</ns0:ref><ns0:ref type='bibr' target='#b19'>), and Galindo-Rodr&#237;guez et al. (2017)</ns0:ref>, who proposed that HLA class II molecules play a critical role in the development of specific anti-ASNase antibodies and in hypersensitivity to the enzyme <ns0:ref type='bibr' target='#b8'>(Cantor et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b14'>Fernandez et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b19'>Galindo-Rodr&#237;guez et al., 2017)</ns0:ref>. Additionally, it has been shown that proteins that are highly immunogenic generally contain a greater amount of T-cell epitopes, or PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed clusters thereof <ns0:ref type='bibr' target='#b56'>(Singh et al., 2012)</ns0:ref>. In addition, the measurement and prediction of ED have generated interest as useful tools for comparisons between therapeutic proteins, allowing selection of the best candidate in terms of probable immunogenicity <ns0:ref type='bibr' target='#b22'>(De Groot &amp; Martin, 2009)</ns0:ref>. In this sense, our results showed that ASNases of the PF06089.11 family contain lower EDs than enzymes of the PF00710.11 family, as well as fewer epitope clusters throughout the sequence. In addition, the allele coverage, which is related to the percentage of the population that develops a significant immune response, showed Streptomyces ASNases to be potential pharmacological options. In For the PF06089.11 family of ASNases, the lack of information of the active site precludes direct comparison, as was used in the approach for the ASNase WP_078979039.1. However, the use of computational tools based on structure inspection and on the evaluation of affinity maps has proven highly effective in identifying probable binding sites in uncharacterized proteins <ns0:ref type='bibr' target='#b23'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Based on the use of computational tools, it was possible to identify two putative binding sites in SsAII-2 (WP_078980718.1). Interestingly, in both sites the motifs NCSGKHxAM, PRSx(2)KPxQ, and SHTGQx(2)H were identified, and these motifs are highly conserved in the PF06089.11 family <ns0:ref type='bibr' target='#b38'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Of these., <ns0:ref type='bibr' target='#b7'>Borek et al. (2001)</ns0:ref> PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed proposed that some of the residues of the NCSGKHxAM motif could be involved in the hydrolytic deamidation of L-asparagine <ns0:ref type='bibr' target='#b7'>(Borek &amp; Jask&#243;lski, 2001)</ns0:ref>.</ns0:p><ns0:p>On the other hand, the residues we found conserved in this family of asparaginases resemble those of the active site of the Ntn amidotransferases, in which, among the important residues for glutamine deamidation are found Cys, Asn, and Gly, and the deamidation mechanism proceeds with an oxyanion formation with the substrate. Although this mechanism is described for glutamine amidohydrolases, it may be a mechanism similar to that of this family of asparaginases, whose active site is different from those of the PF00710.11 family <ns0:ref type='bibr' target='#b29'>(Isupov et al., 1996)</ns0:ref>.</ns0:p><ns0:p>Although site A showed higher affinity for L-asparagine binding, additional studies are needed to confirm the best site for ligand binding. Additionally, molecular dynamics simulations can provide more evidence of the characteristics of the binding site and, together with in vitro studies, will be useful for understanding the mechanism of enzymatic reaction <ns0:ref type='bibr' target='#b31'>(Karplus &amp; Kuriyan, 2005)</ns0:ref>.</ns0:p><ns0:p>Although our results predicted that SsAII-2 has a lower affinity than EcAII, its different folding and immunogenic characteristics place it as a good candidate. Identifying catalytic site residues will allow us to perform site-directed modifications to increase its affinity.</ns0:p><ns0:p>The strategy developed here can be applied to the search for asparaginases in other clades of microorganisms, and even in eukaryotes, specifically mammalian asparaginases, whose evolutionary proximity to humans predicts less immunogenicity.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In summary, the search for ASNases in phylogenetically distant microorganisms and the application of bioinformatic tools to assess their toxicity and affinity for L-asparagine are viable approaches to obtain new ASNases with therapeutic potential. Based on its low immunogenicity and excellent enzymatic activity predicted, we have identified the S. scabrisporus ASNase as a PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed potential alternative for the treatment of ALL. The subsequent enzymatic and immunogenic characterization of the S. scabrisporus ASNase is necessary for the validation of this bioinformatic approach. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>ASNase</ns0:head><ns0:note type='other'>Figure 7</ns0:note><ns0:p>AutoLigand results for EcAII.</ns0:p><ns0:p>The minima observed in the total energy graphs per unit volume represent putative binding sites in the structures analyzed, for the monomer, dimer, and tetramer conformation. As more filling points are used, the binding sites, cavities, or grooves are filled and the affinity decreases. The best sites are the ones with the lowest energy and the lowest volume.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>http://tools.iedb.org/mhcii/). MHC II Analysis Resource parses sequences into 15-mer and assesses the binding potential of each 15-mer to MHC class II molecules of one or more HLA alleles. The IEDB recommended method was used for predictions for a set of 8 HLA alleles that collectively represent &gt;%95 world population: HLA-DRB1*01:01, HLA-DRB1*03:01, HLA-DRB1*04:01, HLA-DRB1*07:01, HLA-DRB1*08:01, HLA-DRB1*11:01, HLA-DRB1*13:01</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>The sequences belonging to the PF00710.11 family have conserved residues located at the ligand binding site necessary for L-asparagine hydrolysis: Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, and Lys 162 for subunit A; Asn 248 and Glu 283 for subunit C. In this regard, Thr 12-Lys 162-Asp 90 and Thr 12-Tyr 2-Glu 283 are the catalytic triads involved in L-asparagine hydrolysis, where Thr 12 and Thr 89 are involved in the nucleophilic attack of the substrate<ns0:ref type='bibr' target='#b21'>(Gesto et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b49'>Sanches, Kraunchenko &amp; Polikarpov, 2016)</ns0:ref>.Concerning the PF06089.11 family, we identified an N-terminal conserved motif, with sequences NCSGKHxAM, DGCGAPL, SHSGEx(2)H, and PRSx(2)KPxQ probably involved in asparagine hydrolysis. ReAII hydrolyzes L-asparagine at similar levels to Erwinia chrysanthemi, but with PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>The first clade includes ASNases from Streptomyces species S. aureocirculatus (WP_078965752.1), S. cattleya (WP_014151616.1), S. thermoautotrophicus (KWW98572.1), S. himastatinicu (EFL23513.1), S. turgidiscabies (ELP65653.1), S. nanshensis (WP_070201703.1), and S. griseus (WP_030748190.1). The second clade includes ASNases from S. albidoflavus (WP_095730579.1), S. kebangsaanensis (WP_073950513.1), S. fradiae (WP_078649241.1), S. himastatinicus (WP_009718687.1), S. purpureus (WP_078513220.1), and S. paucisporeus (WP_079189481.1). Finally, the third clade PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)Manuscript to be reviewed contains proteins from S.purpurogeneiscleroticus (WP_053609500.1), S. purpurogeneiscleroticus (WP_053610569.1), S. phaeochromogenes (WP_055617501.1), and S. lavenduligriseus (WP_051815467.1) where EcAII was included, suggesting that proteins clustered in this clade share similar properties to EcAII. In addition, two proteins, WP_053609500.1 and WP_055617501.1, exhibited the largest proportion of antigenic regions, with almost the same probability regions as the EcAII protein.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Phylogenetic tree of PF00710.11 (A) and PF06089.11 (B) families. Blue dots highlight</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)Manuscript to be reviewed (WP_055617501.1) showed a higher probability of being antigenic, whereas the rest of the ASNases showed very low antigenicity values in comparison with an E. coli ASNase (P00805_EcAII).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. ASNase antigenicity predictions. The antigenicity scores for PF00710.11 family (A) and</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:2:0:NEW 13 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. Epitope mapping of ASNases of the PF familes evaluated, PF00710.11 and PF06089.11.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. 3D protein structure prediction of S. scabrisporus asparaginase II (WP_078980718.1;</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5. SsAII-2 putative binding sites. A) Site A (orange) contains the NCSGKHxAML</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6. EcAII dimer AutoLigand analysis. Cyan EcAII subunit C is shown in cyan and subunit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 7 .</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7. AutoLigand results for EcAII. The minima observed in the total energy graphs per unit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head /><ns0:label /><ns0:figDesc>62, Asn 141, Ser 143, Lys 145, and His 146 are highly conserved in ASNases of the PF06089.11 family.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 8 .</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8. Interaction maps for sites A and B from S. scabrisporus ASNase. The black spheres</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head /><ns0:label /><ns0:figDesc>other words, due to their low content of T-cell epitopes, low antigenicity profile, and low allele coverage, Streptomyces ASNases represent, in terms of immunogenicity, a pharmacological alternative for ALL treatment. In this sense, the Streptomyces brollosae NEAE-115 ASNase has better cytotoxicity and immunogenicity profiles for use in ALL treatment, based on evaluation in a murine model, compared with EcAII (El-naggar et al., 2018). Previously, anticancer activity of the Streptomyces fradiae NEAE-82 ASNase in colon cancer cell cultures was reported (El-Naggar et al., 2016).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_17'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_18'><ns0:head>Figure 4 3D</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_19'><ns0:head /><ns0:label /><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_20'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='49,42.52,255.37,525.00,324.75' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>ID Epitope number CPR value Allele number ED</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>P00805_EcAII</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6383</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0114</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053609500.1</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>0.5174</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0171</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053610569.1</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>0.5381</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0196</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_055617501.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4532</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.0112</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_051815467.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.6673</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0060</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078649241.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4554</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0111</ns0:cell></ns0:row><ns0:row><ns0:cell>EFL23513.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6054</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_014151616.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4024</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_095730579.1</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.5346</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078965752.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4987</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0045</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078513220.1</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>0.4551</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0119</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_009718687.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6480</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0052</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_079189481.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.5217</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0051</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_052425051.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.4369</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0170</ns0:cell></ns0:row><ns0:row><ns0:cell>ELP65653.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6717</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0047</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_070201703.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6637</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0069</ns0:cell></ns0:row><ns0:row><ns0:cell>KWW98572.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.7254</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0034</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_073950513.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7424</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0048</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_030748190.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.5125</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0046</ns0:cell></ns0:row><ns0:row><ns0:cell>Q9K4F5_ScAII</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4167</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0053</ns0:cell></ns0:row><ns0:row><ns0:cell>ARZ68596.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6283</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0044</ns0:cell></ns0:row><ns0:row><ns0:cell>SOD64826.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5046</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0080</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078645645.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6404</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0074</ns0:cell></ns0:row><ns0:row><ns0:cell>CDR15801.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5510</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0059</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078980718.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7003</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_044373749.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.7114</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0027</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot' n='1'>Table 2. High-affinity epitope prediction. Epitope number, CPR value, allele coverage,</ns0:note> </ns0:body> "

"Identification of L-asparaginases from Streptomyces strains with competitive activity and immunogenic profiles: a bioinformatic approach Iván González-Torres, Ernesto Pérez-Rueda, Zahaed Evangelista-Martínez, Andrés Zárate-Romero, Alejandro Huerta-Saquero. Rebuttal letter second review. Dear editor and reviewers, We are very grateful again for your opinions and your interest in improving our work. Here we present an answer to the suggested changes and questions. Editor comments (Joseph Gillespie) MINOR REVISIONS Dear Dr. González-Torres and colleagues: Thanks for revising your manuscript. The reviewers are very satisfied with your revision (as am I). Great! However, there are a few minor edits to make. Please address these ASAP so we may move towards acceptance of your work. Best, -joe Reviewer 2 (Arnon Lavie) Basic reporting The author’s revised manuscript is definitely improved over the original submission. Yet, some issues that need attention remain. Major required change: Section 2.7. Here the authors discuss the molecular docking results for S. scabrisporus ASNase (SsAII), with the goal of identifying the active site. The result is shown in Figure 8. From this figure, it is not clear how this enzyme would catalyze the hydrolysis of asparagine. Specifically, for the predicted Site A, the amide group of the asparagine side chain is predicted to be close to Gly237; the carbonyl to Asn141; neither of these amino acids are likely to participate in catalysis. The predicted binding to Site B also fails to show the type of amino acids that could catalyze the hydrolysis reaction. For example, for the EcA ASNase, conserved threonine residues, a tyrosine, and a lysine participate in catalysis. The authors need to re-examine the predicted binding of asparagine to SsAII to see if it is consistent with being near to residues that can catalyze the reaction. And are the identified putative catalytic residues conserved in this family of ASNases? If not, then this prediction is likely to be false. RESPONSE: We address this question on discussion section as follows: “For the PF06089.11 family of ASNases, the lack of information of the active site precludes direct comparison, as was used in the approach for the ASNase WP_078979039.1. However, the use of computational tools based on structure inspection and on the evaluation of affinity maps has proven highly effective in identifying probable binding sites in uncharacterized proteins (Harris, Olson & Goodsell, 2008). Based on the use of computational tools, it was possible to identify two putative binding sites in SsAII-2 (WP_078980718.1). Interestingly, in both sites the motifs NCSGKHxAM, PRSx(2)KPxQ, and SHTGQx(2)H were identified, and these motifs are highly conserved in the PF06089.11 family (Moreno-Enriquez et al., 2012). Of these, Borek et al. (2001) proposed that some of the residues of the NCSGKHxAM motif could be involved in the hydrolytic deamidation of L-asparagine (Borek & Jaskólski, 2001).” The putative catalytic sites identified are highly conserved in the PF06089.11 family of asparaginases. To further clarify this point, we add the following information: “On the other hand, the residues we found conserved in this family of asparaginases resemble those of the active site of the Ntn amidotransferases, in which, among the important residues for glutamine deamidation are found Cys, Asn, and Gly, and the deamidation mechanism proceeds with an oxyanion formation with the substrate. Although this mechanism is described for glutamine amidohydrolases, it may be a mechanism similar to that of this family of asparaginases, whose active site is different from those of the PF00710.11 family (Isupov, et al., 1996)”. Minor required changes: Title: Identification of L-asparaginases from Streptomyces strains with competitive activity and immunogenic profiles: a bioinformatic approach 􏰀 Identification of L- asparaginases from Streptomyces strains with a predicted competitive activity and immunogenic profiles: a bioinformatic approach RESPONSE: Adding “predicted” word to the title seems to us unnecessary since the last part of the sentence “a bioinformatic approach” includes the subject intrinsically. Abstract: In this work, a bioinformatic approach was used to identify, select and characterize L-asparaginases from Streptomyces through sequence....􏰀 In this work, a bioinformatic approach was used to identify, select and computationally characterize L-asparaginases from Streptomyces through sequence.... RESPONSE: Corrected. Page 3:...as well as pegylated E. chrysanthemi ASNase (EcAI-PEG). 􏰀 as well as pegylated E. chrysanthemi ASNase (ErAI-PEG). RESPONSE: Corrected. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The enzyme L-asparaginase from Escherichia coli is a therapeutic enzyme that has been a cornerstone in the clinical treatment of acute lymphoblastic leukemia for the last decades.</ns0:p><ns0:p>However, treatment effectiveness is limited by the highly immunogenic nature of the protein and its cross-reactivity towards L-glutamine. In this work, a bioinformatic approach was used to identify, select and computationally characterize L-asparaginases from Streptomyces through sequence-based screening analyses, immunoinformatics, homology modeling, and molecular docking studies. Based on its predicted low immunogenicity and excellent enzymatic activity, we selected a previously uncharacterized L-asparaginase from Streptomyces scabrisporus. Furthermore, two putative asparaginase binding sites were identified and a 3D model is proposed. These promising features allow us to propose L-asparaginase from S. scabrisporus as an alternative for the treatment of acute lymphocytic leukemia.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Acute lymphocytic leukemia (ALL) is a hematological disorder of the bone marrow and is characterized by abnormal proliferation of immature lymphoid line cells, blocked at an early stage of cell differentiation, that accumulate and replace healthy hematopoietic cells in the bone marrow <ns0:ref type='bibr' target='#b48'>(Pui, Relling &amp; Downing, 2004;</ns0:ref><ns0:ref type='bibr' target='#b45'>Onciu, 2009)</ns0:ref>. ALL occurs predominantly in children of 1-4 years of age and represents approximately 25% of childhood cancers and about 80% of leukemias <ns0:ref type='bibr' target='#b33'>(Katz et al., 2015)</ns0:ref>.</ns0:p><ns0:p>Although in most cases the risk factors and pathogenicity associated with ALL have not been clearly identified, the etiology of the disease has been mainly associated with a variety of conditions; cytogenetic alterations, mutations to key genes that regulate cellular proliferation, The generation of immune responses during treatment with ASNase is a common condition that has been reported in up to 75% of patients. These reactions depend on the formulation used, the mode of administration (intravenous or intramuscular), and the treatment protocol <ns0:ref type='bibr' target='#b26'>(Hijiya &amp; van der Sluis, 2015)</ns0:ref>. For example, between 30 and 75% of patients that receive the native form of the E. coli enzyme experience hypersensitivity reactions, and about 70% develop anti-EcAII antibodies after drug administration <ns0:ref type='bibr' target='#b6'>(Battistel et al., 2020)</ns0:ref>; these antibodies lead to rapid inactivation of the enzyme <ns0:ref type='bibr' target='#b62'>(Walenciak et al., 2019)</ns0:ref>. Allergic reactions to ASNase, which are associated with its bacterial origin, range from mild urticaria to life-threatening anaphylactic shock. Irritation, fever, vomiting, gastrointestinal edema, and breathing difficulties are symptoms frequently reported <ns0:ref type='bibr' target='#b35'>(Lanvers-Kaminsky, 2017)</ns0:ref>. On the other hand, adverse effects have been reported due to the toxicity produced by glutaminase cross activity, such as leukopenia, immune suppression, acute pancreatitis, hyperglycemia, thrombosis, neurotoxicity, and liver failure, among others <ns0:ref type='bibr' target='#b49'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b10'>Chan et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b1'>Ali et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Different strategies to reduce the toxicity of ASNase have been reported, including modifications in the structure of the protein by mutagenesis, design of mutants with diminished ability to hydrolyze L-glutamine, chemical modifications in specific amino acids, and modifications to drug formulations <ns0:ref type='bibr' target='#b49'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b41'>Nguyen, Su &amp; Lavie, 2016;</ns0:ref><ns0:ref type='bibr'>Nguyen et al., 2018)</ns0:ref>. Covalent conjugation of the enzyme with polyethylene glycol, known as PEGylation, reduces the incidence of hyperglycemia, pancreatitis, and anaphylaxis. This specific modification increase the half-life of the enzyme and reduces the frequency of drug administration <ns0:ref type='bibr' target='#b61'>(Thomas &amp; Le Jeune, 2016)</ns0:ref>.</ns0:p><ns0:p>On the other hand, the exploration of new sources of ASNases offers the possibility of finding versions of the enzyme with different pharmacological characteristics, potentially useful for the</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Identification and selection of homologous L-Asparaginases</ns0:head><ns0:p>Putative ASNases from Streptomyces were identified through a BLASTp search against the NR database of the NCBI using as seeds the amino acid sequences of EcAII (ID P00805) and Streptomyces coelicolor type II ASNase (ScAII; ID Q9K4F5). The search was restricted to the Streptomyces taxon (Taxid 1883), and an E-value less than 1e-06 was considered significant.</ns0:p><ns0:p>Partial proteins and those from unidentified Streptomyces strains were excluded. In a posterior step, the set of protein sequences was filtered at 60% identity as cutoff to avoid redundancy, using the CD-Hit program (http://weizhongli-lab.org/cdhit_suite/cgi-bin/index.cgi) <ns0:ref type='bibr' target='#b28'>(Huang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>Each cluster was analyzed using the HMMER program on the PFAM server (http://pfam.xfam.org/) to determine the protein family to which they belonged <ns0:ref type='bibr' target='#b19'>(Finn, Clements &amp; Eddy, 2011;</ns0:ref><ns0:ref type='bibr' target='#b20'>Finn et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.2'>Phylogenetic analysis</ns0:head><ns0:p>ASNases amino acid sequence alignments were performed using Clustal Omega <ns0:ref type='bibr' target='#b57'>(Sievers et al., 2011)</ns0:ref> with default parameters. The quality of the alignments was improved using the model PF06089.11 or PF00710.11 of ASNase, as required. Multiple sequence alignment statistics were computed with AliStat (http://www.csb.yale.edu/userguides/seq/hmmer/docs/node27.html).</ns0:p><ns0:p>Phylogenetic analyses were carried out using the maximum-likelihood method with the program Mega 7. The WAG model was chosen as substitution model, and 1000 replicates were performed.</ns0:p><ns0:p>The best tree was calculated using the majority rule. Additionally, E. coli type I ASNase <ns0:ref type='bibr'>(EcAI)</ns0:ref> was included in the phylogenetic analysis of the PF00710.11 cluster. EcAI is closely related to Manuscript to be reviewed EcA but it does not have therapeutic potential. For the PF06089.11 cluster, Rhizobium etli type II ASNase (ReAII) was included in the analysis.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.3'>Antigenicity prediction</ns0:head><ns0:p>The prediction of the probability of antigenicity of each ASNase was calculated with the server ANTIGENpro (http://scratch.proteomics.ics.uci.edu/) <ns0:ref type='bibr' target='#b38'>(Magnan et al., 2010)</ns0:ref>. ANTIGENpro is a sequence-based, alignment-free, protein antigenicity predictor with an estimated accuracy of 82%.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.4'>HLA class II binding prediction</ns0:head><ns0:p>The amino acid sequence of each candidate ASNase was screened for T-cells epitopes with the MHC II Analysis Resource at the Immune Epitope Data Base (IEDB) server and HLA-DRB1*15:01. The IEDB-recommended method uses the consensus approach, combining <ns0:ref type='bibr'>NN-align, SMM-align, CombLib, Sturniolo, and NetMHCIIpan (Wang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>For each peptide, a percentile rank is generated by comparing the peptide's score against the scores of five million random 15-mer selected from SWISSPROT database, and the median percentile rank is used to calculate a consensus percentile rank (CPR). Peptides with a CPR &lt; 2 were defined as high-affinity binders and thus selected for epitope density (ED) calculation. Multiple 9-mer cores were identified in overlapped 15-mer peptides. To reduce overestimation of predicted peptides, only the 9-mer cores, predicted by using the Sturniolo method <ns0:ref type='bibr' target='#b59'>(Sturniolo et al., 1999)</ns0:ref> PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed and with a CPR &lt; 1, were considered for the analysis. Finally, epitope density (ED) was calculated using the follow equation, modified from <ns0:ref type='bibr' target='#b54'>(Santos et al., 2013)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_0'>&#119864;&#119863; = &#119875;&#119903;&#119890;&#119889;&#119894;&#119888;&#119905;&#119890;&#119889; &#119890;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; * (2 -&#119860;&#119891;&#119891;&#119894;&#119899;&#119894;&#119905;&#119910; &#119886;&#119907;&#119890;&#119903;&#119886;&#119892;&#119890; ( &#119888;&#119901;&#119903; ) ) &#119875;&#119903;&#119900;&#119905;&#119890;&#119894;&#119899; &#119897;&#119890;&#119899;&#119892;&#119905;&#8462; &#119904;&#119894;&#119911;&#119890; -&#119864;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; &#119904;&#119894;&#119911;&#119890; + 1</ns0:formula><ns0:p>Where Predicted epitope is the number of epitopes with a CPR &lt; 1.</ns0:p><ns0:p>Epitope coverage was calculated as the number of alleles covered by the epitope consensus, according to the following assumption: when a small number of alleles is covered, a lower percentage of the population will develop sensitivity to ASNase.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.5'>Protein structure prediction, refinement and quality assessment</ns0:head><ns0:p>The three-dimensional structures of the selected ASNases was modeled by homology using the I-Tasser server (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) <ns0:ref type='bibr' target='#b66'>(Zhang, 2008)</ns0:ref>. In brief, starting from an amino acid sequence, I-Tasser generates three-dimensional atomic models from multiple threading alignments and iterative structural assembly simulations. A C-score, provided as an estimate of the accuracy of the models generated, typically ranges between -5 to +2, with a higher value indicating higher confidence, and vice versa <ns0:ref type='bibr' target='#b50'>(Roy, Kucukural &amp; Zhang, 2010)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the model with the higher C-score was selected and then refined using the ModRefiner server (https://zhanglab.ccmb.med.umich.edu/ModRefiner/). ModRefiner improves the physical quality and structural accuracy of three-dimensional protein structures by a two-step, atomic-level energy minimization <ns0:ref type='bibr' target='#b65'>(Xu &amp; Zhang, 2011)</ns0:ref>. Finally, the quality of the models was evaluated by RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php), Qmean (https://swissmodel.expasy.org/qmean/), and Verify3D (http:/servicesn.mbi.ucla.edu/Verify3D).</ns0:p></ns0:div> <ns0:div><ns0:head n='1.6'>Molecular docking</ns0:head><ns0:p>The molecular coupling was carried out using Autodock Tools software <ns0:ref type='bibr' target='#b53'>(Sanner, 1999;</ns0:ref><ns0:ref type='bibr' target='#b40'>Morris et al., 2009)</ns0:ref>. EcAII (PDB ID: 3ECA) was recovered from the PDB protein database (http://www.rcsb.org/) <ns0:ref type='bibr' target='#b60'>(Swain et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b7'>Berman et al., 2000)</ns0:ref>. Once refined, selected ASNase structures were prepared using Dock prep at UCSF Chimera and refined using the Gasteiger method <ns0:ref type='bibr' target='#b22'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>The three-dimensional structures of the asparagine and glutamine ligands were obtained from the DrugBank repository (https://www.drugbank.ca/; accession numbers DB00174 and DB00130, respectively) <ns0:ref type='bibr' target='#b64'>(Wishart et al., 2018)</ns0:ref>. The preparation of the ligands was carried out by the Gasteiger method and, finally, the allocation of the rotation centers was determined <ns0:ref type='bibr' target='#b22'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the search box was focused on previously proposed active sites. The box size was defined to cover all residues of the ligand binding site, using a grid size of 0.375 &#197;.</ns0:p><ns0:p>Blind molecular docking was performed with Autodock 4.2 software, using the Lamarckian genetic algorithm, with 1000 runs, for a population size equal to 150, with 2.5 x 10^6 evaluations, a mutation rate equal to 0.02 in 27,000 generations.</ns0:p><ns0:p>In addition, the active site location was predicted by AutoLigand <ns0:ref type='bibr' target='#b25'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Briefly, AutoLigand identifies sites of maximum affinity from maps generated by AutoGrid, finding regions with better energy and a lower volume. <ns0:ref type='table'>PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>L-Asparaginases from Streptomyces cluster into two type families according to its protein architecture</ns0:head><ns0:p>The Blast search against the Streptomyces taxon revealed 296 putative ASNases homologous to EcAII and 703 homologous to ScAII with a significant score. After manual examination of both groups, 136 and 311 complete sequences were kept for EcAII and ScAII groups, respectively. Protein domain analysis using PFAM server showed that 136 sequences are related to the PF00710.11 family of N-terminal ASNases. For sequences homologous to ScAII, PFAM analysis revealed that they belong to the PF06089.11 family of ASNases, a group of enzymes related to ReAII, a thermolabile enzyme induced by L-asparagine and repressed by the carbon source <ns0:ref type='bibr' target='#b39'>(Moreno-Enriquez et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b29'>Huerta-Saquero et al., 2013)</ns0:ref>. Representative clusters for PF00710.11 and PF06089.11 families obtained using the CD-Hit suite program were generated at a 60% identity cutoff, with 19 and 7 putative ASNases, respectively (Table <ns0:ref type='table'>1</ns0:ref>). ASNases sequences showed similar lengths in both clusters, ranging from 320 to 420 amino acids.</ns0:p><ns0:p>The sequences belonging to the PF00710.11 family have conserved residues located at the ligand binding site necessary for L-asparagine hydrolysis: Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, and Lys 162 for subunit A; Asn 248 and Glu 283 for subunit C. In this regard, Thr 12-Lys 162-Asp 90 and Thr 12-Tyr 2-Glu 283 are the catalytic triads involved in L-asparagine hydrolysis, where Thr 12 and Thr 89 are involved in the nucleophilic attack of the substrate <ns0:ref type='bibr' target='#b23'>(Gesto et al., 2013;</ns0:ref><ns0:ref type='bibr' target='#b52'>Sanches, Kraunchenko &amp; Polikarpov, 2016)</ns0:ref>.</ns0:p><ns0:p>Concerning the PF06089.11 family, we identified an N-terminal conserved motif, with sequences NCSGKHxAM, DGCGAPL, SHSGEx(2)H, and PRSx(2)KPxQ probably involved in asparagine hydrolysis. ReAII hydrolyzes L-asparagine at similar levels to Erwinia chrysanthemi, but with PeerJ reviewing <ns0:ref type='table'>PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:ref> Manuscript to be reviewed lower affinity than L-asparaginases from both E. coli and E. chrysanthemi <ns0:ref type='bibr' target='#b39'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Furthermore, ReAII is the only ASNase characterized from the PF06089.11 family</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Phylogenetic analysis of ASNases</ns0:head><ns0:p>For the PF00710.11 family, EcAI was added to the multiple sequence alignment in order to know the relationship between this ASNase and the candidate ASNases. EcAI belongs to the same family of proteins as EcAII, but it does not represent a therapeutic option for ALL treatment. It is noteworthy that asparaginases can also be classified according to subcellular localization, a) periplasmic asparaginases containing secretion signal peptide and, b) asparaginases with intracellular localization. The former generally have a higher affinity for asparagine. However, according to their architecture, both types of proteins can be found in the PF00710.11 or PF06089.11 families. This is the case of E. coli asparaginases I and II, both belonging to the PF00710.11 family (https://pfam.xfam.org/family/PF00710#tabview=tab1). We found that the ASNase with accession number WP_059134811.1 of Streptomyces alboniger is grouped in the same clade as EcAI, and so it was excluded from subsequent analyses (Figure <ns0:ref type='figure' target='#fig_21'>1A</ns0:ref>).</ns0:p><ns0:p>The phylogenetic reconstruction showed three well-defined clades (Figure <ns0:ref type='figure' target='#fig_21'>1A</ns0:ref>). The first clade includes ASNases from Streptomyces species S. aureocirculatus (WP_078965752.1), S. cattleya Manuscript to be reviewed contains proteins from S.purpurogeneiscleroticus (WP_053609500.1), S. purpurogeneiscleroticus (WP_053610569.1), S. phaeochromogenes (WP_055617501.1), and S. lavenduligriseus (WP_051815467.1) where EcAII was included, suggesting that proteins clustered in this clade share similar properties to EcAII. In addition, two proteins, WP_053609500.1 and WP_055617501.1, exhibited the largest proportion of antigenic regions, with almost the same probability regions as the EcAII protein.</ns0:p><ns0:p>On the other hand, for the ASNases of PF06089.11, phylogenetic analysis included both the ASNase sequence of R. etli and S. coelicolor (ReAII and ScAII, respectively) (Figure <ns0:ref type='figure' target='#fig_21'>1B</ns0:ref>). The tree defines two clades. In the first one, where the ScAII was included, we also considered ARZ68596.1 from S. albireticuli, SOD64826.1 from S. zhaozhouensis, WP_078645645 from S. varsoviensis, CDR15801.1 from S. iranensis, and WP_020554088 from S. scabrisporus.</ns0:p><ns0:p>In the second clade were included the following proteins: WP_044373749 from S. ahygroscopicus and WP_078980718.1 from S. scabrisporus. </ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Antigenicity predictions</ns0:head><ns0:p>The results for antigenicity showed a likelihood of being antigenic for all ASNases in both sets that was lower than that of EcAII (Figure <ns0:ref type='figure' target='#fig_5'>2</ns0:ref>). Nevertheless, among selected Streptomyces ASNases, the candidates from S. purpurogeneiscleroticus (WP_053609500.1) and S. phaeochromogenes </ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>T-cell epitope analysis</ns0:head><ns0:p>After antigenicity prediction, the ED, the total number of high-affinity epitopes, the affinity epitopes, and the number of HLA alleles covered by each ASNase were calculated. The results showed that the ASNases with accession numbers WP_053609500.1, WP_053610569.1, EFL23513.1, WP_095730579.1, WP_078513220.1, and WP_052425051.1 have higher EDs than the reference (P00805_EcAII; ED=0.01114; 5 covered alleles) (Figure <ns0:ref type='figure' target='#fig_7'>3</ns0:ref>).</ns0:p><ns0:p>On the other hand, the ASNase with the lowest predicted ED was WP_044373749.1, with an ED of 0.0027 and a coverage of 4 alleles, following by WP_095730579.1 (2 alleles), ELP65653.1 (3 alleles), and Q9K4F5 (3 alleles) (Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p><ns0:p>Additionally, the distribution of epitopes was mapped into the sequences of the ASNases (Figure <ns0:ref type='figure' target='#fig_7'>3</ns0:ref>). ASNases of the PF06089.11 family tended to have a lower ED (Table <ns0:ref type='table'>3</ns0:ref>) as well as lower allele coverage than those of the PF00710.11 family (Figure <ns0:ref type='figure' target='#fig_7'>3</ns0:ref>). Manuscript to be reviewed Next, ASNases with lower allele coverage, lower ED, and lower probability of antigenicity were selected for further analysis. S. coelicolor (Q9K4F5), S. scabrisporus (WP_078980718.1), and S. albireticuli (ARZ68596.1) were selected as promising enzymes.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>Protein structure predictions</ns0:head><ns0:p>From selected ASNases, homology-based models were generated (I-Tasser). For the subsequent analysis, the S. scabrisporus asparaginase II model, which had the highest C-value, was chosen (WP_078980718.1 SsAII-2) (Figure <ns0:ref type='figure' target='#fig_8'>4</ns0:ref>). The stereochemical quality of the models was evaluated using Ramachandran plots. In order to improve the quality of the models, these were structurally refined with ModRefiner and reassessed with RAMPAGE. In addition, the Verify3D server was used to determine the compatibility of the three-dimensional model with the amino acid sequence.</ns0:p><ns0:p>Based on the predicted structure, ASNase WP_0789718.1 (PF06089.11 family) is related in terms of folding to the beta-lactamase family. Beta-lactamases (SCOP data base, entry 56600) consist of a cluster of alpha-helices and an alpha/beta sandwich. This folding is also found in transpeptidases, esterases, penicillin receptors, D-aminopeptidases, and glutaminases (InterPro IPR012338). </ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>Active site prediction</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>In order to identify the active site residues of the S. scabrisporus ASNase (WP_0789718.1), three approaches were used: genomic comparison, blind molecular coupling simulation, and search for high-affinity binding pockets with AutoLigand (active site). To our knowledge, there is no information regarding the active site of the family PF06089.11 ASNases, so genomic comparison was not possible. Using AutoLigand, two possible high affinity binding sites for L-asparagine were identified (Figure <ns0:ref type='figure' target='#fig_9'>5A</ns0:ref>). The first (site A) had a volume of 121 &#197; 3 and an energy per volume equal to -0.2149 kcal/mol &#197; 3 ; the second (site B) had a volume of 101 &#197; 3 and an energy per volume equal to -0. 2136 kcal/mol &#197; 3 . Site A is located between an alpha-helix in the amino terminal containing the 57 PRSx(2)KPxQ 65 motif, and a loop in the central region of the enzyme, containing the 141 NCSGKHxAML 150 motif (Table <ns0:ref type='table'>3</ns0:ref>). Site B is located in a pocket formed by a set of alphahelices in the amino terminal of the protein, marked by the presence of the 87 SHTGQxHFV 95 motif.</ns0:p><ns0:p>On the other hand, by performing AutoDock 4.2 whole-protein molecular coupling simulations, we found that the best ligand-enzyme interaction (L-asparagine-ASNase), with a binding free energy of -4.17 kcal/mol, targeted residues corresponding to the 141 NCSGKHxAML 150 motif, which correspond to the site A (Figure <ns0:ref type='figure' target='#fig_9'>5B</ns0:ref>). Additionally, in order to validate AutoLigand analysis searching active sites in the S. scabrisporus ASNases, a search for binding sites in EcAII was performed. To do this, the monomeric, dimeric, and tetrameric forms of the enzyme (the latter is the catalytically active form) were analyzed using Manuscript to be reviewed the same conditions used for SsAII-2. It was found that AutoLigand successfully identified the binding site of L-Asn, consisting of Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, and Lys 162 and also Asn 248 and Glu 283 (Figure <ns0:ref type='figure' target='#fig_11'>6</ns0:ref>), the latter two only for dimeric and tetrameric forms. The sites found (red squares curves) had energies by volume equal to -0.2119, -0.2242, and -0.2366 kcal/mol &#197; 3 and a volume of 136, 122, and 102 &#197; 3 for the monomer, dimer, and tetramer, respectively (Figure <ns0:ref type='figure' target='#fig_12'>7</ns0:ref>). It is relevant that for both the dimeric and the tetramer forms, AutoLigand successfully identified L-Asn binding pockets in EcAII: the pocket formed between the aminoterminal end of subunit A and the carboxy terminal of the subunit C, as well as equivalent pockets for dimer BD. In addition, several other solutions found by AutoLigand (curve with blue or green squares), using up to 90 filling points, converge in the different joint pockets formed by dimers. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>Molecular docking</ns0:head><ns0:p>Molecular docking simulations were performed at the putative sites found (Table <ns0:ref type='table'>4</ns0:ref>). For EcAII, as the reference ASNase, Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, Asn 248, and Glu 283 were established as flexible residues; meanwhile, molecular docking for S. scabrisporus ASNase were performed using only the rigid structure of the protein, without defining flexible side chains for L-asparagine binding.</ns0:p><ns0:p>Our results showed a higher affinity for L-asparagine of the S. scabrisporus ASNase site A than site B; however, the affinity was lower than that for EcAII. For S. scabrisporus ASNase site A, the L-asparagine interacts with residues Ser 59, Lys 62, Asn 141, Ser 143, Lys 145, His 146, Gly 237, Lys 255, and Gly 256 (Figure <ns0:ref type='figure' target='#fig_14'>8A</ns0:ref>); for site B, the residues that interact with L-asparagine are Ala 84, Gly 78, Ser 87, Tyr 163, Leu 164, and Asp165 (Figure <ns0:ref type='figure' target='#fig_14'>8B</ns0:ref>). Interestingly, from site A, Lys </ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>In this work, a set of bioinformatics tools were used to identify, select, and characterize ASNases Manuscript to be reviewed with no glutaminase activity and with a different immunogenic profile than EcAII <ns0:ref type='bibr' target='#b29'>(Huerta-Saquero et al., 2013)</ns0:ref>. The search for homologous sequences resulted in two sets of sequences with a high probability of being ASNases (E value &lt;1e-06). These sequence sets, in turn, were classified into two different protein families based on their homology, using HMMer: PF00710.11 and PF06089.11, according to the classification of the PFAM database. So far, most of the reported ASNases belong to the PF00710.11 family and have been extensively studied. EcAII and the E.</ns0:p><ns0:p>chrysanthemi ASNase belong to this family. On the other hand, the PF06089.11 family represents a group of atypical ASNases that remain poorly characterized. Some representative reports about these ASNases include the R. etli ASNase <ns0:ref type='bibr' target='#b46'>(Ortu&#241;o-Olea &amp; Dur&#225;n-Vargas, 2000;</ns0:ref><ns0:ref type='bibr' target='#b39'>Moreno-Enriquez et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b29'>Huerta-Saquero et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Interestingly, the BLAST results showed a greater abundance of PF06089.11 family sequences compared to the PF00710.11 family in Streptomyces. In addition, we found that about 20% of species have ASNase isoforms. In that sense, many Gram-negative bacteria have at least two isozymes of the family PF00710.11 <ns0:ref type='bibr' target='#b18'>(Fern&#225;ndez &amp; Z&#250;&#241;iga, 2006)</ns0:ref> and, in E. coli, the existence of a third isoenzyme has been recently reported <ns0:ref type='bibr' target='#b11'>(Correia da Silva et al., 2018)</ns0:ref>. Historically, the genus Streptomyces has been attractive due to the wide repertoire of bioactive molecules produced. However, searching for ASNases of pharmacological interest has been done only rarely.</ns0:p><ns0:p>After the identification of two sets of ASNases, we chose T-cell ED as the immunogenicity indicator, according to <ns0:ref type='bibr'>Cantor et al. (2004</ns0:ref><ns0:ref type='bibr'>), Fern&#225;ndez et al. (2012</ns0:ref><ns0:ref type='bibr' target='#b21'>), and Galindo-Rodr&#237;guez et al. (2017)</ns0:ref>, who proposed that HLA class II molecules play a critical role in the development of specific anti-ASNase antibodies and in hypersensitivity to the enzyme <ns0:ref type='bibr' target='#b9'>(Cantor et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b16'>Fernandez et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b21'>Galindo-Rodr&#237;guez et al., 2017)</ns0:ref>. Additionally, it has been shown that proteins that are highly immunogenic generally contain a greater amount of T-cell epitopes, or Manuscript to be reviewed clusters thereof <ns0:ref type='bibr' target='#b58'>(Singh et al., 2012)</ns0:ref>. In addition, the measurement and prediction of ED have generated interest as useful tools for comparisons between therapeutic proteins, allowing selection of the best candidate in terms of probable immunogenicity <ns0:ref type='bibr' target='#b24'>(De Groot &amp; Martin, 2009)</ns0:ref>. In this sense, our results showed that ASNases of the PF06089.11 family contain lower EDs than enzymes of the PF00710.11 family, as well as fewer epitope clusters throughout the sequence. In addition, the allele coverage, which is related to the percentage of the population that develops a significant immune response, showed Streptomyces ASNases to be potential pharmacological options. In For the PF06089.11 family of ASNases, the lack of information of the active site precludes direct comparison, as was used in the approach for the ASNase WP_078979039.1. However, the use of computational tools based on structure inspection and on the evaluation of affinity maps has proven highly effective in identifying probable binding sites in uncharacterized proteins <ns0:ref type='bibr' target='#b25'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Based on the use of computational tools, it was possible to identify two putative binding sites in SsAII-2 (WP_078980718.1). Interestingly, in both sites the motifs NCSGKHxAM, PRSx(2)KPxQ, and SHTGQx(2)H were identified, and these motifs are highly conserved in the PF06089.11 family <ns0:ref type='bibr' target='#b39'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Of these., <ns0:ref type='bibr' target='#b8'>Borek et al. (2001)</ns0:ref> PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed proposed that some of the residues of the NCSGKHxAM motif could be involved in the hydrolytic deamidation of L-asparagine <ns0:ref type='bibr' target='#b8'>(Borek &amp; Jask&#243;lski, 2001)</ns0:ref>.</ns0:p><ns0:p>On the other hand, the residues we found conserved in this family of asparaginases resemble those of the active site of the Ntn amidotransferases, in which, among the important residues for glutamine deamidation are found Cys, Asn, and Gly, and the deamidation mechanism proceeds with an oxyanion formation with the substrate. Although this mechanism is described for glutamine amidohydrolases, it may be a mechanism similar to that of this family of asparaginases, whose active site is different from those of the PF00710.11 family <ns0:ref type='bibr' target='#b30'>(Isupov et al., 1996)</ns0:ref>. In that sense, the E. coli GLMS protein (1xfg) several catalytic residues have been identified, among which Cys1 is the catalytic nucleophile, and the nucleophilic character of its thiol group appears to be increased through general base activation by its own alpha-amino group. The authors propose that when a nitrogen acceptor is present Cys1 is kept in the active conformation, explaining the phenomenon of substrate-induced activation of the enzyme and that Arg26 is central in this coupling <ns0:ref type='bibr' target='#b30'>(Isupov et al., 1996)</ns0:ref>. To determine if the catalytic residues reported in GLMS overlap with the WP_078980718 protein, we performed a structural alignment using a flexible structure alignment approach, POSA (Partial order structure alignment (http://posa.godziklab.org/) <ns0:ref type='bibr' target='#b36'>(Li et al., 2014)</ns0:ref> between the structure 1xfg (Glutaminase domain of glucosamine 6-phosphate synthase of E. coli) and our three-dimensional model from WP_078980718. The alignment showed an overlap with an RMSD of 6.55 &#197; with 121 equivalent positions and a p-value of 3.46e-01, which suggests that the alignment can be considered non-significant at global scale (random structural similarity), therefore the two proteins are not homologous (as we expected). However, at local overlapping, the residues in this region strongly suggest that the catalytic mechanism could be similar (Figure <ns0:ref type='figure' target='#fig_19'>9</ns0:ref>). The R26 residue of 1xfga which participates in substrate coupling, overlaps Manuscript to be reviewed with the site identified in WP_07898071 (NCSGKHxAM), and the other residues are equivalent in both proteins, reinforcing the notion that at the NCSGKHxAM site, the substrate can be coupled, and thus be the catalytic site. Although site A showed higher affinity for L-asparagine binding, additional studies are needed to confirm the best site for ligand binding. Additionally, molecular dynamics simulations can provide more evidence of the characteristics of the binding site and, together with in vitro studies, will be useful for understanding the mechanism of enzymatic reaction <ns0:ref type='bibr' target='#b32'>(Karplus &amp; Kuriyan, 2005)</ns0:ref>.</ns0:p><ns0:p>Although our results predicted that SsAII-2 has a lower affinity than EcAII, its different folding and immunogenic characteristics place it as a good candidate. Identifying catalytic site residues will allow us to perform site-directed modifications to increase its affinity.</ns0:p><ns0:p>The strategy developed here can be applied to the search for asparaginases in other clades of microorganisms, and even in eukaryotes, specifically mammalian asparaginases, whose evolutionary proximity to humans predicts less immunogenicity.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In summary, the search for ASNases in phylogenetically distant microorganisms and the application of bioinformatic tools to assess their toxicity and affinity for L-asparagine are viable approaches to obtain new ASNases with therapeutic potential. Based on its low immunogenicity Manuscript to be reviewed and excellent enzymatic activity predicted, we have identified the S. scabrisporus ASNase as a potential alternative for the treatment of ALL. The subsequent enzymatic and immunogenic characterization of the S. scabrisporus ASNase is necessary for the validation of this bioinformatic approach. Manuscript to be reviewed Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>ASNase</ns0:head><ns0:note type='other'>Figure 7</ns0:note><ns0:p>AutoLigand results for EcAII.</ns0:p><ns0:p>The minima observed in the total energy graphs per unit volume represent putative binding sites in the structures analyzed, for the monomer, dimer, and tetramer conformation. As more filling points are used, the binding sites, cavities, or grooves are filled and the affinity decreases. The best sites are the ones with the lowest energy and the lowest volume. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>http://tools.iedb.org/mhcii/). MHC II Analysis Resource parses sequences into 15-mer and assesses the binding potential of each 15-mer to MHC class II molecules of one or more HLA alleles. The IEDB recommended method was used for predictions for a set of 8 HLA alleles that collectively represent &gt;%95 world population: HLA-DRB1*01:01, HLA-DRB1*03:01, HLA-DRB1*04:01, HLA-DRB1*07:01, HLA-DRB1*08:01, HLA-DRB1*11:01, HLA-DRB1*13:01</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>WP_014151616.1), S. thermoautotrophicus (KWW98572.1), S. himastatinicu (EFL23513.1), S. turgidiscabies (ELP65653.1), S. nanshensis (WP_070201703.1), and S. griseus (WP_030748190.1). The second clade includes ASNases from S. albidoflavus (WP_095730579.1), S. kebangsaanensis (WP_073950513.1), S. fradiae (WP_078649241.1), S. himastatinicus (WP_009718687.1), S. purpureus (WP_078513220.1), and S. paucisporeus (WP_079189481.1). Finally, the third clade PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Phylogenetic tree of PF00710.11 (A) and PF06089.11 (B) families. Blue dots highlight</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)Manuscript to be reviewed (WP_055617501.1) showed a higher probability of being antigenic, whereas the rest of the ASNases showed very low antigenicity values in comparison with an E. coli ASNase (P00805_EcAII).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. ASNase antigenicity predictions. The antigenicity scores for PF00710.11 family (A) and</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. Epitope mapping of ASNases of the PF familes evaluated, PF00710.11 and PF06089.11.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. 3D protein structure prediction of S. scabrisporus asparaginase II (WP_078980718.1;</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5. SsAII-2 putative binding sites. A) Site A (orange) contains the NCSGKHxAML</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6. EcAII dimer AutoLigand analysis. Cyan EcAII subunit C is shown in cyan and subunit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 7 .</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7. AutoLigand results for EcAII. The minima observed in the total energy graphs per unit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head /><ns0:label /><ns0:figDesc>62, Asn 141, Ser 143, Lys 145, and His 146 are highly conserved in ASNases of the PF06089.11 family.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Figure 8 .</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8. Interaction maps for sites A and B from S. scabrisporus ASNase. The black spheres</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head /><ns0:label /><ns0:figDesc>from the Streptomyces genus. ASNase identification was carried out by searching sequences homologous to EcAII and ScAII. EcAII is the best-characterized and most widely used ASNase for ALL treatment, while ScAII is a homologous ASNase related to ReAII, an atypical ASNase PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_17'><ns0:head /><ns0:label /><ns0:figDesc>other words, due to their low content of T-cell epitopes, low antigenicity profile, and low allele coverage, Streptomyces ASNases represent, in terms of immunogenicity, a pharmacological alternative for ALL treatment. In this sense, the Streptomyces brollosae NEAE-115 ASNase has better cytotoxicity and immunogenicity profiles for use in ALL treatment, based on evaluation in a murine model, compared with EcAII (El-naggar et al., 2018). Previously, anticancer activity of the Streptomyces fradiae NEAE-82 ASNase in colon cancer cell cultures was reported (El-Naggar et al., 2016).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_18'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_19'><ns0:head>Figure 9 .</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Figure 9. Structural alignment of S. scabrisporus asparaginase II (WP_07898071) and E. coli</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_20'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:3:0:NEW 27 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_21'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_22'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_23'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_24'><ns0:head>Figure 9 Figure 9 .</ns0:head><ns0:label>99</ns0:label><ns0:figDesc>Figure 9</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='48,42.52,255.37,525.00,212.25' type='bitmap' /></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='52,42.52,255.37,525.00,324.75' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>ID Epitope number CPR value Allele number ED</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>P00805_EcAII</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6383</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0114</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053609500.1</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>0.5174</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0171</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053610569.1</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>0.5381</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0196</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_055617501.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4532</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.0112</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_051815467.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.6673</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0060</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078649241.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4554</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0111</ns0:cell></ns0:row><ns0:row><ns0:cell>EFL23513.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6054</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_014151616.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4024</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_095730579.1</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.5346</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078965752.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4987</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0045</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078513220.1</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>0.4551</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0119</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_009718687.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6480</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0052</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_079189481.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.5217</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0051</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_052425051.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.4369</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0170</ns0:cell></ns0:row><ns0:row><ns0:cell>ELP65653.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6717</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0047</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_070201703.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6637</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0069</ns0:cell></ns0:row><ns0:row><ns0:cell>KWW98572.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.7254</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0034</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_073950513.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7424</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0048</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_030748190.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.5125</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0046</ns0:cell></ns0:row><ns0:row><ns0:cell>Q9K4F5_ScAII</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4167</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0053</ns0:cell></ns0:row><ns0:row><ns0:cell>ARZ68596.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6283</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0044</ns0:cell></ns0:row><ns0:row><ns0:cell>SOD64826.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5046</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0080</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078645645.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6404</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0074</ns0:cell></ns0:row><ns0:row><ns0:cell>CDR15801.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5510</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0059</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078980718.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7003</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_044373749.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.7114</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0027</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot' n='1'>Table 2. High-affinity epitope prediction. Epitope number, CPR value, allele coverage,</ns0:note> </ns0:body> "

"Identification of L-asparaginases from Streptomyces strains with competitive activity and immunogenic profiles: a bioinformatic approach Iván González-Torres, Ernesto Pérez-Rueda, Zahaed Evangelista-Martínez, Andrés Zárate-Romero, Alejandro Huerta-Saquero. Rebuttal letter third review. Dear editor and reviewers, We are very grateful for your opinions and your interest in improving our work. Here we present an answer to the suggested changes. EDITOR COMMENTS (Joseph Gillespie) ==================================================== Dear Drs. Gutiérrez-Fonseca and Ramírez: Thanks for revising your manuscript.  It mostly looks great except for one concern.  In looking over your rebuttal, it is not clear to me that you addressed a specific issue raised by Reviewer 2.  Ideally, your claims regarding similarity between their active sites and those of Ntn amiditransferases should be supported by comparison with the 1XFG crystal structure.  Please address this so we can move forward with accepting your work for publication. Best, -joe RESPONSE: We added next information in discussion section: “In that sense, the E. coli GLMS protein (1xfg) several catalytic residues have been identified, among which Cys1 is the catalytic nucleophile, and the nucleophilic character of its thiol group appears to be increased through general base activation by its own alpha-amino group. The authors propose that when a nitrogen acceptor is present Cys1 is kept in the active conformation, explaining the phenomenon of substrate-induced activation of the enzyme and that Arg26 is central in this coupling (Isupov et al., 1996). To determine if the catalytic residues reported in GLMS overlap with the WP_078980718 protein, we performed a structural alignment using a flexible structure alignment approach, POSA (Partial order structure alignment (http://posa.godziklab.org/) (Li et al., 2014) between the structure 1xfg (Glutaminase domain of glucosamine 6-phosphate synthase of E. coli) and our three-dimensional model from WP_078980718. The alignment showed an overlap with an RMSD of 6.55 Å with 121 equivalent positions and a p-value of 3.46e-01, which suggests that the alignment can be considered non-significant at global scale (random structural similarity), therefore the two proteins are not homologous (as we expected). However, at local overlapping, the residues in this region strongly suggest that the catalytic mechanism could be similar (Figure 9). The R26 residue of 1xfga which participates in substrate coupling, overlaps with the site identified in WP_07898071 (NCSGKHxAM), and the other residues are equivalent in both proteins, reinforcing the notion that at the NCSGKHxAM site, the substrate can be coupled, and thus be the catalytic site. 118 -----RPEDEDTYQEMIARGeenTRERMNCSGKHAAML- 1 CgivgAIAQRDVAEILLEGL---RRLEYRGYDSAGLAVVDAE Figure 9. Structural alignment of S. scabrisporus asparaginase II (WP_07898071) and E. coli GLMS protein sequences. The residues involved in catalytic activity are shown in bold. Capital letters indicate equivalent residues according to POSA program.” Reference Z Li, P Natarajan, Y Ye, T Hrabe, A Godzik. 2014. POSA: a user-driven, interactive multiple protein structure alignment server. Nucl. Acids Res. 42(1): W240–W245. doi: 10.1093/nar/gku394 "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The enzyme L-asparaginase from Escherichia coli is a therapeutic enzyme that has been a cornerstone in the clinical treatment of acute lymphoblastic leukemia for the last decades.</ns0:p><ns0:p>However, treatment effectiveness is limited by the highly immunogenic nature of the protein and its cross-reactivity towards L-glutamine. In this work, a bioinformatic approach was used to identify, select and computationally characterize L-asparaginases from Streptomyces through sequence-based screening analyses, immunoinformatics, homology modeling, and molecular docking studies. Based on its predicted low immunogenicity and excellent enzymatic activity, we selected a previously uncharacterized L-asparaginase from Streptomyces scabrisporus. Furthermore, two putative asparaginase binding sites were identified and a 3D model is proposed. These promising features allow us to propose L-asparaginase from S. scabrisporus as an alternative for the treatment of acute lymphocytic leukemia.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Acute lymphocytic leukemia (ALL) is a hematological disorder of the bone marrow and is characterized by abnormal proliferation of immature lymphoid line cells, blocked at an early stage of cell differentiation, that accumulate and replace healthy hematopoietic cells in the bone marrow <ns0:ref type='bibr' target='#b46'>(Pui, Relling &amp; Downing, 2004;</ns0:ref><ns0:ref type='bibr' target='#b43'>Onciu, 2009)</ns0:ref>. ALL occurs predominantly in children of 1-4 years of age and represents approximately 25% of childhood cancers and about 80% of leukemias <ns0:ref type='bibr' target='#b32'>(Katz et al., 2015)</ns0:ref>.</ns0:p><ns0:p>Although in most cases the risk factors and pathogenicity associated with ALL have not been clearly identified, the etiology of the disease has been mainly associated with a variety of conditions; cytogenetic alterations, mutations to key genes that regulate cellular proliferation, Manuscript to be reviewed differentiation and death; presence of oncogenic viruses, immunodeficiency, exposure to pesticides, solvents, and ionizing radiation <ns0:ref type='bibr' target='#b46'>(Pui, Relling &amp; Downing, 2004;</ns0:ref><ns0:ref type='bibr' target='#b5'>Bassan, Maino &amp; Cortelazzo, 2016)</ns0:ref>.</ns0:p><ns0:p>Treatment for ALL patients involve steroid drugs, prednisone, vincristine, and the enzyme Lasparaginase (ASNase) <ns0:ref type='bibr' target='#b3'>(Avramis, 2012;</ns0:ref><ns0:ref type='bibr' target='#b55'>Schwab &amp; Harrison, 2018)</ns0:ref>. ASNase has been essential in the treatment of ALL since the 1970s, with demonstrated effectiveness as an individual drug with remission rates of up to 68% <ns0:ref type='bibr' target='#b50'>(Salzer et al., 2017)</ns0:ref>. The combination of ASNase with other anticancer drugs has led to remission rates of up to 90% (Lanvers-Kaminsky, 2017).</ns0:p><ns0:p>Currently, there are four ASNase formulations available for the ALL treatment: two native forms of the enzyme, obtained from Escherichia coli (EcAII) and Erwinia chrysanthemi (ErAII), and pegylated E. coli ASNase (EcAII-PEG), as well as pegylated E. chrysanthemi ASNase (ErAII-PEG). Of these, EcAII-PEG has become the first-line treatments for ALL in the US, with EcAII the most widely used formulation. ErAII is administered to patients who have developed hypersensitivity to the above formulations <ns0:ref type='bibr' target='#b45'>(Pieters et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abribat, 2016;</ns0:ref><ns0:ref type='bibr' target='#b4'>Barba et al., 2017)</ns0:ref>.</ns0:p><ns0:p>In recent years, evidence has been accumulating of its usefulness as an important component in the treatment of other hematological malignancies, such as acute myeloid leukemia, myelosarcoma, lymphosarcoma, Hodgkin's disease, and chronic lymphocytic leukemia <ns0:ref type='bibr' target='#b14'>(Emadi, Zokaee &amp; Sausville, 2014;</ns0:ref><ns0:ref type='bibr' target='#b36'>Lopes et al., 2015)</ns0:ref>. Despite their high antileukemic potential, the use of ASNases in the treatment of ALL is limited by their toxicity. Among the adverse effects that have been reported are leukopenia, immune suppression, acute pancreatitis, liver dysfunction, hyperglycemia, abnormalities in hemostasis, and hemorrhages of the central nervous system <ns0:ref type='bibr' target='#b54'>(Schein et al., 1969;</ns0:ref><ns0:ref type='bibr' target='#b48'>Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b10'>Chan et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b1'>Ali et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b26'>Hijiya &amp; van der Sluis, 2016;</ns0:ref><ns0:ref type='bibr' target='#b30'>Kamal et al., 2019)</ns0:ref>. </ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The generation of immune responses during treatment with ASNase is a common condition that has been reported in up to 75% of patients. These reactions depend on the formulation used, the mode of administration (intravenous or intramuscular), and the treatment protocol <ns0:ref type='bibr' target='#b25'>(Hijiya &amp; van der Sluis, 2015)</ns0:ref>. For example, between 30 and 75% of patients that receive the native form of the E. coli enzyme experience hypersensitivity reactions, and about 70% develop anti-EcAII antibodies after drug administration <ns0:ref type='bibr' target='#b6'>(Battistel et al., 2020)</ns0:ref>; these antibodies lead to rapid inactivation of the enzyme <ns0:ref type='bibr' target='#b62'>(Walenciak et al., 2019)</ns0:ref>. Allergic reactions to ASNase, which are associated with its bacterial origin, range from mild urticaria to life-threatening anaphylactic shock. Irritation, fever, vomiting, gastrointestinal edema, and breathing difficulties are symptoms frequently reported (Lanvers-Kaminsky, 2017). On the other hand, adverse effects have been reported due to the toxicity produced by glutaminase cross activity, such as leukopenia, immune suppression, acute pancreatitis, hyperglycemia, thrombosis, neurotoxicity, and liver failure, among others <ns0:ref type='bibr' target='#b48'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b10'>Chan et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b1'>Ali et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Different strategies to reduce the toxicity of ASNase have been reported, including modifications in the structure of the protein by mutagenesis, design of mutants with diminished ability to hydrolyze L-glutamine, chemical modifications in specific amino acids, and modifications to drug formulations <ns0:ref type='bibr' target='#b48'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b41'>Nguyen, Su &amp; Lavie, 2016;</ns0:ref><ns0:ref type='bibr' target='#b42'>Nguyen et al., 2018)</ns0:ref>. Covalent conjugation of the enzyme with polyethylene glycol, known as PEGylation, reduces the incidence of hyperglycemia, pancreatitis, and anaphylaxis. This specific modification increase the half-life of the enzyme and reduces the frequency of drug administration <ns0:ref type='bibr' target='#b61'>(Thomas &amp; Le Jeune, 2016)</ns0:ref>.</ns0:p><ns0:p>On the other hand, the exploration of new sources of ASNases offers the possibility of finding versions of the enzyme with different pharmacological characteristics, potentially useful for the</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Identification and selection of homologous L-Asparaginases</ns0:head><ns0:p>Putative ASNases from Streptomyces were identified through a BLASTp search against the NR database of the NCBI using as seeds the amino acid sequences of EcAII (ID P00805) and Streptomyces coelicolor type II ASNase (ScAII; ID Q9K4F5). The search was restricted to the Streptomyces taxon (Taxid 1883), and an E-value less than 1e-06 was considered significant.</ns0:p><ns0:p>Partial proteins and those from unidentified Streptomyces strains were excluded. In a posterior step, the set of protein sequences was filtered at 60% identity as cutoff to avoid redundancy, using the CD-Hit program (http://weizhongli-lab.org/cdhit_suite/cgi-bin/index.cgi) <ns0:ref type='bibr' target='#b27'>(Huang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>Each cluster was analyzed using the HMMER program on the PFAM server (http://pfam.xfam.org/) to determine the protein family to which they belonged <ns0:ref type='bibr' target='#b18'>(Finn, Clements &amp; Eddy, 2011;</ns0:ref><ns0:ref type='bibr' target='#b19'>Finn et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.2'>Phylogenetic analysis</ns0:head><ns0:p>ASNases amino acid sequence alignments were performed using Clustal Omega <ns0:ref type='bibr'>(Sievers et al., 2011)</ns0:ref> with default parameters. The quality of the alignments was improved using the model PF06089.11 or PF00710.11 of ASNase, as required. Multiple sequence alignment statistics were computed with AliStat (http://www.csb.yale.edu/userguides/seq/hmmer/docs/node27.html).</ns0:p><ns0:p>Phylogenetic analyses were carried out using the maximum-likelihood method with the program Mega 7. The WAG model was chosen as substitution model, and 1000 replicates were performed.</ns0:p><ns0:p>The best tree was calculated using the majority rule. Additionally, E. coli type I ASNase <ns0:ref type='bibr'>(EcAI)</ns0:ref> was included in the phylogenetic analysis of the PF00710.11 cluster. EcAI is closely related to Manuscript to be reviewed EcA but it does not have therapeutic potential. For the PF06089.11 cluster, Rhizobium etli type II ASNase (ReAII) was included in the analysis.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.3'>Antigenicity prediction</ns0:head><ns0:p>The prediction of the probability of antigenicity of each ASNase was calculated with the server ANTIGENpro (http://scratch.proteomics.ics.uci.edu/) <ns0:ref type='bibr' target='#b37'>(Magnan et al., 2010)</ns0:ref>. ANTIGENpro is a sequence-based, alignment-free, protein antigenicity predictor with an estimated accuracy of 82%.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.4'>HLA class II binding prediction</ns0:head><ns0:p>The amino acid sequence of each candidate ASNase was screened for T-cells epitopes with the MHC II Analysis Resource at the Immune Epitope Data Base (IEDB) server and HLA-DRB1*15:01. The IEDB-recommended method uses the consensus approach, combining <ns0:ref type='bibr'>NN-align, SMM-align, CombLib, Sturniolo, and NetMHCIIpan (Wang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>For each peptide, a percentile rank is generated by comparing the peptide's score against the scores of five million random 15-mer selected from SWISSPROT database, and the median percentile rank is used to calculate a consensus percentile rank (CPR). Peptides with a CPR &lt; 2 were defined as high-affinity binders and thus selected for epitope density (ED) calculation. Multiple 9-mer cores were identified in overlapped 15-mer peptides. To reduce overestimation of predicted peptides, only the 9-mer cores, predicted by using the Sturniolo method <ns0:ref type='bibr' target='#b59'>(Sturniolo et al., 1999)</ns0:ref> PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed and with a CPR &lt; 1, were considered for the analysis. Finally, epitope density (ED) was calculated using the follow equation, modified from <ns0:ref type='bibr' target='#b53'>(Santos et al., 2013)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_0'>&#119864;&#119863; = &#119875;&#119903;&#119890;&#119889;&#119894;&#119888;&#119905;&#119890;&#119889; &#119890;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; * (2 -&#119860;&#119891;&#119891;&#119894;&#119899;&#119894;&#119905;&#119910; &#119886;&#119907;&#119890;&#119903;&#119886;&#119892;&#119890; ( &#119888;&#119901;&#119903; ) ) &#119875;&#119903;&#119900;&#119905;&#119890;&#119894;&#119899; &#119897;&#119890;&#119899;&#119892;&#119905;&#8462; &#119904;&#119894;&#119911;&#119890; -&#119864;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; &#119904;&#119894;&#119911;&#119890; + 1</ns0:formula><ns0:p>Where Predicted epitope is the number of epitopes with a CPR &lt; 1.</ns0:p><ns0:p>Epitope coverage was calculated as the number of alleles covered by the epitope consensus, according to the following assumption: when a small number of alleles is covered, a lower percentage of the population will develop sensitivity to ASNase.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.5'>Protein structure prediction, refinement and quality assessment</ns0:head><ns0:p>The three-dimensional structures of the selected ASNases was modeled by homology using the I-Tasser server (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) <ns0:ref type='bibr' target='#b67'>(Zhang, 2008)</ns0:ref>. In brief, starting from an amino acid sequence, I-Tasser generates three-dimensional atomic models from multiple threading alignments and iterative structural assembly simulations. A C-score, provided as an estimate of the accuracy of the models generated, typically ranges between -5 to +2, with a higher value indicating higher confidence, and vice versa <ns0:ref type='bibr' target='#b49'>(Roy, Kucukural &amp; Zhang, 2010)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the model with the higher C-score was selected and then refined using the ModRefiner server (https://zhanglab.ccmb.med.umich.edu/ModRefiner/). ModRefiner improves the physical quality and structural accuracy of three-dimensional protein structures by a two-step, atomic-level energy minimization <ns0:ref type='bibr' target='#b66'>(Xu &amp; Zhang, 2011)</ns0:ref>. Finally, the quality of the models was evaluated by RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php), Qmean (https://swissmodel.expasy.org/qmean/), and Verify3D (http:/servicesn.mbi.ucla.edu/Verify3D). <ns0:ref type='table'>2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing PDF | (</ns0:head></ns0:div> <ns0:div><ns0:head n='1.6'>Molecular docking</ns0:head><ns0:p>The molecular coupling was carried out using Autodock Tools software <ns0:ref type='bibr' target='#b52'>(Sanner, 1999;</ns0:ref><ns0:ref type='bibr' target='#b40'>Morris et al., 2009)</ns0:ref>. EcAII (PDB ID: 3ECA) was recovered from the PDB protein database (http://www.rcsb.org/) <ns0:ref type='bibr' target='#b60'>(Swain et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b7'>Berman et al., 2000)</ns0:ref>. Once refined, selected ASNase structures were prepared using Dock prep at UCSF Chimera and refined using the Gasteiger method <ns0:ref type='bibr' target='#b21'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>The three-dimensional structures of the asparagine and glutamine ligands were obtained from the DrugBank repository (https://www.drugbank.ca/; accession numbers DB00174 and DB00130, respectively) <ns0:ref type='bibr'>(Wishart et al., 2018)</ns0:ref>. The preparation of the ligands was carried out by the Gasteiger method and, finally, the allocation of the rotation centers was determined <ns0:ref type='bibr' target='#b21'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the search box was focused on previously proposed active sites. The box size was defined to cover all residues of the ligand binding site, using a grid size of 0.375 &#197;.</ns0:p><ns0:p>Blind molecular docking was performed with Autodock 4.2 software, using the Lamarckian genetic algorithm, with 1000 runs, for a population size equal to 150, with 2.5 x 10^6 evaluations, a mutation rate equal to 0.02 in 27,000 generations.</ns0:p><ns0:p>In addition, the active site location was predicted by AutoLigand <ns0:ref type='bibr' target='#b24'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Briefly, AutoLigand identifies sites of maximum affinity from maps generated by AutoGrid, finding regions with better energy and a lower volume. <ns0:ref type='table'>PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>L-Asparaginases from Streptomyces cluster into two type families according to its protein architecture</ns0:head><ns0:p>The Blast search against the Streptomyces taxon revealed 296 putative ASNases homologous to EcAII and 703 homologous to ScAII with a significant score. After manual examination of both groups, 136 and 311 complete sequences were kept for EcAII and ScAII groups, respectively. Protein domain analysis using PFAM server showed that 136 sequences are related to the PF00710.11 family of N-terminal ASNases. For sequences homologous to ScAII, PFAM analysis revealed that they belong to the PF06089.11 family of ASNases, a group of enzymes related to ReAII, a thermolabile enzyme induced by L-asparagine and repressed by the carbon source <ns0:ref type='bibr' target='#b38'>(Moreno-Enriquez et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b28'>Huerta-Saquero et al., 2013)</ns0:ref>. Representative clusters for PF00710.11 and PF06089.11 families obtained using the CD-Hit suite program were generated at a 60% identity cutoff, with 19 and 7 putative ASNases, respectively (Table <ns0:ref type='table'>1</ns0:ref>). ASNases sequences showed similar lengths in both clusters, ranging from 320 to 420 amino acids. Manuscript to be reviewed lower affinity than L-asparaginases from both E. coli and E. chrysanthemi <ns0:ref type='bibr' target='#b38'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Furthermore, ReAII is the only ASNase characterized from the PF06089.11 family</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Phylogenetic analysis of ASNases</ns0:head><ns0:p>For the PF00710.11 family, EcAI was added to the multiple sequence alignment in order to know the relationship between this ASNase and the candidate ASNases. EcAI belongs to the same family of proteins as EcAII, but it does not represent a therapeutic option for ALL treatment. It is noteworthy that asparaginases can also be classified according to subcellular localization, a) periplasmic asparaginases containing secretion signal peptide and, b) asparaginases with intracellular localization. The former generally have a higher affinity for asparagine. However, according to their architecture, both types of proteins can be found in the PF00710.11 or PF06089.11 families. This is the case of E. coli asparaginases I and II, both belonging to the PF00710.11 family (https://pfam.xfam.org/family/PF00710#tabview=tab1). We found that the ASNase with accession number WP_059134811.1 of Streptomyces alboniger is grouped in the same clade as EcAI, and so it was excluded from subsequent analyses (Figure <ns0:ref type='figure' target='#fig_24'>1A</ns0:ref>).</ns0:p><ns0:p>The phylogenetic reconstruction showed three well-defined clades (Figure <ns0:ref type='figure' target='#fig_24'>1A</ns0:ref>). The first clade includes ASNases from Streptomyces species S. aureocirculatus (WP_078965752.1), S. cattleya Manuscript to be reviewed contains proteins from S.purpurogeneiscleroticus (WP_053609500.1), S. purpurogeneiscleroticus (WP_053610569.1), S. phaeochromogenes (WP_055617501.1), and S. lavenduligriseus (WP_051815467.1) where EcAII was included, suggesting that proteins clustered in this clade share similar properties to EcAII. In addition, two proteins, WP_053609500.1 and WP_055617501.1, exhibited the largest proportion of antigenic regions, with almost the same probability regions as the EcAII protein.</ns0:p><ns0:p>On the other hand, for the ASNases of PF06089.11, phylogenetic analysis included both the ASNase sequence of R. etli and S. coelicolor (ReAII and ScAII, respectively) (Figure <ns0:ref type='figure' target='#fig_24'>1B</ns0:ref>). The tree defines two clades. In the first one, where the ScAII was included, we also considered ARZ68596.1 from S. albireticuli, SOD64826.1 from S. zhaozhouensis, WP_078645645 from S. varsoviensis, CDR15801.1 from S. iranensis, and WP_020554088 from S. scabrisporus.</ns0:p><ns0:p>In the second clade were included the following proteins: WP_044373749 from S. ahygroscopicus and WP_078980718.1 from S. scabrisporus. </ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Antigenicity predictions</ns0:head><ns0:p>The results for antigenicity showed a likelihood of being antigenic for all ASNases in both sets that was lower than that of EcAII (Figure <ns0:ref type='figure' target='#fig_8'>2</ns0:ref>). Nevertheless, among selected Streptomyces ASNases, the candidates from S. purpurogeneiscleroticus (WP_053609500.1) and S. phaeochromogenes </ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>T-cell epitope analysis</ns0:head><ns0:p>After antigenicity prediction, the ED, the total number of high-affinity epitopes, the affinity epitopes, and the number of HLA alleles covered by each ASNase were calculated. The results showed that the ASNases with accession numbers WP_053609500.1, WP_053610569.1, EFL23513.1, WP_095730579.1, WP_078513220.1, and WP_052425051.1 have higher EDs than the reference (P00805_EcAII; ED=0.01114; 5 covered alleles) (Figure <ns0:ref type='figure' target='#fig_10'>3</ns0:ref>).</ns0:p><ns0:p>On the other hand, the ASNase with the lowest predicted ED was WP_044373749.1, with an ED of 0.0027 and a coverage of 4 alleles, following by WP_095730579.1 (2 alleles), ELP65653.1 (3 alleles), and Q9K4F5 (3 alleles) (Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p><ns0:p>Additionally, the distribution of epitopes was mapped into the sequences of the ASNases (Figure <ns0:ref type='figure' target='#fig_10'>3</ns0:ref>). ASNases of the PF06089.11 family tended to have a lower ED (Table <ns0:ref type='table'>3</ns0:ref>) as well as lower allele coverage than those of the PF00710.11 family (Figure <ns0:ref type='figure' target='#fig_10'>3</ns0:ref>). Manuscript to be reviewed Next, ASNases with lower allele coverage, lower ED, and lower probability of antigenicity were selected for further analysis. S. coelicolor (Q9K4F5), S. scabrisporus (WP_078980718.1), and S. albireticuli (ARZ68596.1) were selected as promising enzymes.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>Protein structure predictions</ns0:head><ns0:p>From selected ASNases, homology-based models were generated (I-Tasser). For the subsequent analysis, the S. scabrisporus asparaginase II model, which had the highest C-value, was chosen (WP_078980718.1 SsAII-2) (Figure <ns0:ref type='figure' target='#fig_12'>4</ns0:ref>). The structural model obtained by I-Tasser (with a C-value of -3.09) was refined with ModRefiner. In addition, the RAMPAGE program (http://mordred.bioc.cam.ac.uk/&#732;rapper) and Verify3D were used to validate the stereochemical quality of the resulting three-dimensional model. After analyzing the Ramachandran plot, 91.7% and 5.5% of the residues were located in favored and allowed regions, respectively; whereas Verify3D analysis revealed that 80.73% of the residues had an average 3D-1D score &lt; 0.2, indicating that the model is compatible with its sequence.</ns0:p><ns0:p>Based on the predicted structure, ASNase WP_0789718.1 (PF06089.11 family) is related in terms of folding to the beta-lactamase family. Beta-lactamases (SCOP data base, entry 56600) consist of a cluster of alpha-helices and an alpha/beta sandwich. This folding is also found in transpeptidases, esterases, penicillin receptors, D-aminopeptidases, and glutaminases (InterPro IPR012338). Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>Active site prediction</ns0:head><ns0:p>In order to identify the active site residues of the S. scabrisporus ASNase (WP_0789718.1), three approaches were used: genomic comparison, blind molecular coupling simulation, and search for high-affinity binding pockets with AutoLigand (active site). To our knowledge, there is no information regarding the active site of the family PF06089.11 ASNases, so genomic comparison was not possible. Using AutoLigand, two possible high affinity binding sites for L-asparagine were identified (Figure <ns0:ref type='figure' target='#fig_13'>5A</ns0:ref>). The first (site A) had a volume of 121 &#197; 3 and an energy per volume equal to -0.2149 kcal/mol &#197; 3 ; the second (site B) had a volume of 101 &#197; 3 and an energy per volume equal to -0. 2136 kcal/mol &#197; 3 . Site A is located between an alpha-helix in the amino terminal containing the 57 PRSx(2)KPxQ 65 motif, and a loop in the central region of the enzyme, containing the 141 NCSGKHxAML 150 motif (Table <ns0:ref type='table'>3</ns0:ref>). Site B is located in a pocket formed by a set of alphahelices in the amino terminal of the protein, marked by the presence of the 87 SHTGQxHFV 95 motif.</ns0:p><ns0:p>On the other hand, by performing AutoDock 4.2 whole-protein molecular coupling simulations, we found that the best ligand-enzyme interaction (L-asparagine-ASNase), with a binding free energy of -4.17 kcal/mol, targeted residues corresponding to the 141 NCSGKHxAML 150 motif, which correspond to the site A (Figure <ns0:ref type='figure' target='#fig_13'>5B</ns0:ref>). Manuscript to be reviewed Additionally, in order to validate AutoLigand analysis searching active sites in the S. scabrisporus ASNases, a search for binding sites in EcAII was performed. To do this, the monomeric, dimeric, and tetrameric forms of the enzyme (the latter is the catalytically active form) were analyzed using the same conditions used for SsAII-2. It was found that AutoLigand successfully identified the binding site of L-Asn, consisting of Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, and Lys 162 and also Asn 248 and Glu 283 (Figure <ns0:ref type='figure' target='#fig_14'>6</ns0:ref>), the latter two only for dimeric and tetrameric forms. The sites found (red squares curves) had energies by volume equal to -0.2119, -0.2242, and -0.2366 kcal/mol &#197; 3 and a volume of 136, 122, and 102 &#197; 3 for the monomer, dimer, and tetramer, respectively (Figure <ns0:ref type='figure' target='#fig_15'>7</ns0:ref>). It is relevant that for both the dimeric and the tetramer forms, AutoLigand successfully identified L-Asn binding pockets in EcAII: the pocket formed between the aminoterminal end of subunit A and the carboxy terminal of the subunit C, as well as equivalent pockets for dimer BD. In addition, several other solutions found by AutoLigand (curve with blue or green squares), using up to 90 filling points, converge in the different joint pockets formed by dimers. Manuscript to be reviewed tetramer conformation. As more filling points are used, the binding sites, cavities, or grooves are filled and the affinity decreases. The best sites are the ones with the lowest energy and the lowest volume.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>Molecular docking</ns0:head><ns0:p>Molecular docking simulations were performed at the putative sites found (Table <ns0:ref type='table'>4</ns0:ref>). For EcAII, as the reference ASNase, Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, Asn 248, and Glu 283 were established as flexible residues; meanwhile, molecular docking for S. scabrisporus ASNase were performed using only the rigid structure of the protein, without defining flexible side chains for L-asparagine binding.</ns0:p><ns0:p>Our results showed a higher affinity for L-asparagine of the S. scabrisporus ASNase site A than site B; however, the affinity was lower than that for EcAII. Interestingly, the BLAST results showed a greater abundance of PF06089.11 family sequences compared to the PF00710.11 family in Streptomyces. In addition, we found that about 20% of species have ASNase isoforms. In that sense, many Gram-negative bacteria have at least two isozymes of the family PF00710.11 <ns0:ref type='bibr' target='#b17'>(Fern&#225;ndez &amp; Z&#250;&#241;iga, 2006)</ns0:ref> and, in E. coli, the existence of a third isoenzyme has been recently reported <ns0:ref type='bibr' target='#b11'>(Correia da Silva et al., 2018)</ns0:ref>. Historically, the genus Streptomyces has been attractive due to the wide repertoire of bioactive molecules produced.</ns0:p><ns0:p>However, searching for ASNases of pharmacological interest has been done only rarely.</ns0:p><ns0:p>After the identification of two sets of ASNases, we chose T-cell ED as the immunogenicity indicator, according to <ns0:ref type='bibr'>Cantor et al. (2004</ns0:ref><ns0:ref type='bibr'>), Fern&#225;ndez et al. (2012)</ns0:ref>, and Galindo-Rodr&#237;guez et al. Manuscript to be reviewed (2017), who proposed that HLA class II molecules play a critical role in the development of specific anti-ASNase antibodies and in hypersensitivity to the enzyme <ns0:ref type='bibr' target='#b9'>(Cantor et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b15'>Fernandez et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b20'>Galindo-Rodr&#237;guez et al., 2017)</ns0:ref>. Additionally, it has been shown that proteins that are highly immunogenic generally contain a greater amount of T-cell epitopes, or clusters thereof <ns0:ref type='bibr' target='#b58'>(Singh et al., 2012)</ns0:ref>. In addition, the measurement and prediction of ED have generated interest as useful tools for comparisons between therapeutic proteins, allowing selection of the best candidate in terms of probable immunogenicity <ns0:ref type='bibr' target='#b23'>(De Groot &amp; Martin, 2009)</ns0:ref>. In this sense, our results showed that ASNases of the PF06089.11 family contain lower EDs than enzymes of the PF00710.11 family, as well as fewer epitope clusters throughout the sequence. In addition, the allele coverage, which is related to the percentage of the population that develops a significant immune response, showed Streptomyces ASNases to be potential pharmacological options. In For the PF06089.11 family of ASNases, the lack of information of the active site precludes direct comparison, as was used in the approach for the ASNase WP_078979039.1. However, the use of computational tools based on structure inspection and on the evaluation of affinity maps has proven highly effective in identifying probable binding sites in uncharacterized proteins <ns0:ref type='bibr' target='#b24'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Based on the use of computational tools, it was possible to identify two Manuscript to be reviewed putative binding sites in SsAII-2 (WP_078980718.1). Interestingly, in both sites the motifs NCSGKHxAM, PRSx(2)KPxQ, and SHTGQx(2)H were identified, and these motifs are highly conserved in the PF06089.11 family <ns0:ref type='bibr' target='#b38'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Of these., <ns0:ref type='bibr' target='#b8'>Borek et al. (2001)</ns0:ref> proposed that some of the residues of the NCSGKHxAM motif could be involved in the hydrolytic deamidation of L-asparagine <ns0:ref type='bibr' target='#b8'>(Borek &amp; Jask&#243;lski, 2001)</ns0:ref>.</ns0:p><ns0:p>On the other hand, the residues we found conserved in this family of asparaginases resemble those of the active site of the Ntn amidotransferases, in which, among the important residues for glutamine deamidation are found Cys, Asn, and Gly, and the deamidation mechanism proceeds with an oxyanion formation with the substrate. Although this mechanism is described for glutamine amidohydrolases, it may be a mechanism similar to that of this family of asparaginases, whose active site is different from those of the PF00710.11 family <ns0:ref type='bibr' target='#b29'>(Isupov et al., 1996)</ns0:ref>. In that sense, the E. coli GLMS protein (1xfg) several catalytic residues have been identified, among which Cys1 is the catalytic nucleophile, and the nucleophilic character of its thiol group appears to be increased through general base activation by its own alpha-amino group. The authors propose that when a nitrogen acceptor is present Cys1 is kept in the active conformation, explaining the phenomenon of substrate-induced activation of the enzyme and that Arg26 is central in this coupling <ns0:ref type='bibr' target='#b29'>(Isupov et al., 1996)</ns0:ref>. To determine if the catalytic residues reported in GLMS overlap with the WP_078980718 protein, we performed a structural alignment using a flexible structure alignment approach, POSA (Partial order structure alignment (http://posa.godziklab.org/) <ns0:ref type='bibr' target='#b35'>(Li et al., 2014)</ns0:ref> between the structure 1xfg (Glutaminase domain of glucosamine 6-phosphate synthase of E. coli) and our three-dimensional model from WP_078980718. The alignment showed an overlap with an RMSD of 6.55 &#197; with 121 equivalent positions and a p-value of 3.46e-01, which suggests that the alignment can be considered non-significant at global scale (random structural Manuscript to be reviewed similarity; supplementary Figure <ns0:ref type='figure' target='#fig_6'>1</ns0:ref>), therefore the two proteins are not homologous (as we expected). However, at local overlapping, the residues in this region strongly suggest that the catalytic mechanism could be similar (Figure <ns0:ref type='figure' target='#fig_22'>9</ns0:ref>). The R26 residue of 1xfga which participates in substrate coupling, overlaps with the site identified in WP_07898071 (NCSGKHxAM) (Figure <ns0:ref type='figure' target='#fig_22'>9A</ns0:ref>), and the other residues are homologous in both proteins, reinforcing the notion that at the NCSGKHxAM site, the substrate can be coupled, and thus be the catalytic site (Figure <ns0:ref type='figure' target='#fig_22'>9B</ns0:ref>). Although site A showed higher affinity for L-asparagine binding, additional studies are needed to confirm the best site for ligand binding. Additionally, molecular dynamics simulations can provide more evidence of the characteristics of the binding site and, together with in vitro studies, will be useful for understanding the mechanism of enzymatic reaction <ns0:ref type='bibr' target='#b31'>(Karplus &amp; Kuriyan, 2005)</ns0:ref>.</ns0:p><ns0:p>Although our results predicted that SsAII-2 has a lower affinity than EcAII, its different folding and immunogenic characteristics place it as a good candidate. Identifying catalytic site residues will allow us to perform site-directed modifications to increase its affinity. Manuscript to be reviewed</ns0:p><ns0:p>The strategy developed here can be applied to the search for asparaginases in other clades of microorganisms, and even in eukaryotes, specifically mammalian asparaginases, whose evolutionary proximity to humans predicts less immunogenicity.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In summary, the search for ASNases in phylogenetically distant microorganisms and the application of bioinformatic tools to assess their toxicity and affinity for L-asparagine are viable approaches to obtain new ASNases with therapeutic potential. Based on its low immunogenicity and excellent enzymatic activity predicted, we have identified the S. scabrisporus ASNase as a potential alternative for the treatment of ALL. The subsequent enzymatic and immunogenic characterization of the S. scabrisporus ASNase is necessary for the validation of this bioinformatic approach. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>ASNase</ns0:head><ns0:note type='other'>Figure 7</ns0:note><ns0:p>AutoLigand results for EcAII.</ns0:p><ns0:p>The minima observed in the total energy graphs per unit volume represent putative binding sites in the structures analyzed, for the monomer, dimer, and tetramer conformation. As more filling points are used, the binding sites, cavities, or grooves are filled and the affinity decreases. The best sites are the ones with the lowest energy and the lowest volume. </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>http://tools.iedb.org/mhcii/). MHC II Analysis Resource parses sequences into 15-mer and assesses the binding potential of each 15-mer to MHC class II molecules of one or more HLA alleles. The IEDB recommended method was used for predictions for a set of 8 HLA alleles that collectively represent &gt;%95 world population: HLA-DRB1*01:01, HLA-DRB1*03:01, HLA-DRB1*04:01, HLA-DRB1*07:01, HLA-DRB1*08:01, HLA-DRB1*11:01, HLA-DRB1*13:01</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>The sequences belonging to the PF00710.11 family have conserved residues located at the ligand binding site necessary for L-asparagine hydrolysis: Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp90, and Lys 162 for subunit A; Asn 248 and Glu 283 for subunit C. In this regard, Thr 12-Lys 162-Asp 90 and Thr 12-Tyr 2-Glu 283 are the catalytic triads involved in L-asparagine hydrolysis, where Thr 12 and Thr 89 are involved in the nucleophilic attack of the substrate (Gesto et al., 2013; Sanches, Kraunchenko &amp; Polikarpov, 2016). Concerning the PF06089.11 family, we identified an N-terminal conserved motif, with sequences NCSGKHxAM, DGCGAPL, SHSGEx(2)H, and PRSx(2)KPxQ probably involved in asparagine hydrolysis. ReAII hydrolyzes L-asparagine at similar levels to Erwinia chrysanthemi, but with PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>WP_014151616.1), S. thermoautotrophicus (KWW98572.1), S. himastatinicu (EFL23513.1), S. turgidiscabies (ELP65653.1), S. nanshensis (WP_070201703.1), and S. griseus (WP_030748190.1). The second clade includes ASNases from S. albidoflavus (WP_095730579.1), S. kebangsaanensis (WP_073950513.1), S. fradiae (WP_078649241.1), S. himastatinicus (WP_009718687.1), S. purpureus (WP_078513220.1), and S. paucisporeus (WP_079189481.1). Finally, the third clade PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Phylogenetic tree of PF00710.11 (A) and PF06089.11 (B) families. Blue dots highlight</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)Manuscript to be reviewed (WP_055617501.1) showed a higher probability of being antigenic, whereas the rest of the ASNases showed very low antigenicity values in comparison with an E. coli ASNase (P00805_EcAII).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. ASNase antigenicity predictions. The antigenicity scores for PF00710.11 family (A) and</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. Epitope mapping of ASNases of the PF familes evaluated, PF00710.11 and PF06089.11.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. 3D protein structure prediction of S. scabrisporus asparaginase II (WP_078980718.1;</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5. SsAII-2 putative binding sites. A) Site A (orange) contains the NCSGKHxAML</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>Figure 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6. EcAII dimer AutoLigand analysis. Cyan EcAII subunit C is shown in cyan and subunit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure 7 .</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7. AutoLigand results for EcAII. The minima observed in the total energy graphs per unit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head /><ns0:label /><ns0:figDesc>For S. scabrisporus ASNase site A, the L-asparagine interacts with residues Ser 59, Lys 62, Asn 141, Ser 143, Lys 145, His 146, Gly 237, Lys 255, and Gly 256 (Figure 8A); for site B, the residues that interact with L-asparagine are Ala 84, Gly 78, Ser 87, Tyr 163, Leu 164, and Asp165 (Figure 8B). Interestingly, from site A, Lys 62, Asn 141, Ser 143, Lys 145, and His 146 are highly conserved in ASNases of the PF06089.11 family.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_17'><ns0:head>Figure 8 .</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8. Interaction maps for sites A and B from S. scabrisporus ASNase. The black spheres</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_18'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_19'><ns0:head /><ns0:label /><ns0:figDesc>other words, due to their low content of T-cell epitopes, low antigenicity profile, and low allele coverage, Streptomyces ASNases represent, in terms of immunogenicity, a pharmacological alternative for ALL treatment. In this sense, the Streptomyces brollosae NEAE-115 ASNase has better cytotoxicity and immunogenicity profiles for use in ALL treatment, based on evaluation in a murine model, compared with EcAII (El-naggar et al., 2018). Previously, anticancer activity of the Streptomyces fradiae NEAE-82 ASNase in colon cancer cell cultures was reported (El-Naggar et al., 2016).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_20'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_21'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_22'><ns0:head>Figure 9 .</ns0:head><ns0:label>9</ns0:label><ns0:figDesc>Figure 9. Structural alignment of S. scabrisporus asparaginase II (WP_07898071) and E. coli</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_23'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:4:0:NEW 11 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_24'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_25'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_26'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_27'><ns0:head>Figure 4 3D</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_28'><ns0:head /><ns0:label /><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_29'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_30'><ns0:head>Figure 9 Figure 9 .</ns0:head><ns0:label>99</ns0:label><ns0:figDesc>Figure 9</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='51,42.52,255.37,525.00,324.75' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>ID Epitope number CPR value Allele number ED</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>P00805_EcAII</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6383</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0114</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053609500.1</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>0.5174</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0171</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053610569.1</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>0.5381</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0196</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_055617501.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4532</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.0112</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_051815467.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.6673</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0060</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078649241.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4554</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0111</ns0:cell></ns0:row><ns0:row><ns0:cell>EFL23513.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6054</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_014151616.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4024</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_095730579.1</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.5346</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078965752.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4987</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0045</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078513220.1</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>0.4551</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0119</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_009718687.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6480</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0052</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_079189481.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.5217</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0051</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_052425051.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.4369</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0170</ns0:cell></ns0:row><ns0:row><ns0:cell>ELP65653.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6717</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0047</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_070201703.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6637</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0069</ns0:cell></ns0:row><ns0:row><ns0:cell>KWW98572.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.7254</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0034</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_073950513.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7424</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0048</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_030748190.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.5125</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0046</ns0:cell></ns0:row><ns0:row><ns0:cell>Q9K4F5_ScAII</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4167</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0053</ns0:cell></ns0:row><ns0:row><ns0:cell>ARZ68596.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6283</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0044</ns0:cell></ns0:row><ns0:row><ns0:cell>SOD64826.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5046</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0080</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078645645.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6404</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0074</ns0:cell></ns0:row><ns0:row><ns0:cell>CDR15801.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5510</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0059</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078980718.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7003</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_044373749.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.7114</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0027</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot' n='1'>Table 2. High-affinity epitope prediction. Epitope number, CPR value, allele coverage,</ns0:note> </ns0:body> "

"Identification of L-asparaginases from Streptomyces strains with competitive activity and immunogenic profiles: a bioinformatic approach Iván González-Torres, Ernesto Pérez-Rueda, Zahaed Evangelista-Martínez, Andrés Zárate-Romero, Angélica Moreno-Enríquez, Alejandro Huerta-Saquero. Rebuttal letter third review. Dear editor professor, We are very grateful again for your opinions and your interest in improving our work. Here we present an answer to the suggested changes and questions. Dear Dr. González-Torres and colleagues: Thanks for revising your manuscript. However, your structural analysis is not convincing at all. Please (at least) provide the coordinates of your model and a figure comparing your proposed active site with that of the 1XFG crystal structure. We have also noticed that section 2.5 lacks any data regarding the actual results returned by RAMPAGE and verify3D, the C-scores of their models (and how that scores compares with the typical values for good models) etc. You cannot simultaneously claim 'resemble those of the active site of the Ntn amidotransferases, in which, among the important residues for glutamine deamidation are found Cys, Asn, and Gly, and the deamidation mechanism proceeds with an oxyanion formation with the substrate. ' and provide such a paucity of confirming data. Please address this as described above. Best, -joe RESPONSE: Thank you. We are agreed. We added next information on section 2.5: “The structural model obtained by i-Tasser (with a C-value of -3.09) was refined with ModRefiner. In addition, the RAMPAGE program (http://mordred.bioc.cam.ac.uk/˜rapper) and Verify3D were used to validate the stereochemical quality of the resulting three-dimensional model. After analyzing the Ramachandran plot, 91.7% and 5.5% of the residues were located in favored and allowed regions, respectively; whereas Verify3D analysis revealed that 80.73% of the residues had an average 3D-1D score <0.2, indicating that the model is compatible with its sequence.” Additionally, we added a comparison between our proposed active site with that of the 1xfg crystal structure (Figure 9B). Also, we added the complete sequence alignment of Ntn amidotransferase and S. scabrisporus asparaginase, as well as structural comparison of both proteins (Supplementary Figure 1, supplementary material). A 118 -----RPEDEDTYQEMIARGeenTRERMNCSGKHAAML- 1 CgivgAIAQRDVAEILLEGL---RRLEYRGYDSAGLAVVDAE B Figure 9. Structural alignment of S. scabrisporus asparaginase II (WP_07898071) and E. coli GLMS protein sequences. A) The residues involved in catalytic activity are shown in bold. Capital letters indicate equivalent residues according to POSA program. B) Overlapping of catalytic residues of both proteins (WP_07898071 in blue and GLMS in black). The GLMS catalytic residue R26 is shown in the box. Supplementary Figure 1. http://posa.godziklab.org/POSAn-cgi/displayMolPage.pl?id=15979420821926&jobname=query&sysdir=result&what=aln&view=JSmol http://posa.godziklab.org/POSAn-cgi/displayMolPage.pl?id=15979420821926&jobname=query&sysdir=result&what=aln&view=JSmol Supplementary Figure 1. Structural alignment of S. scabrisporus asparaginase II (WP_07898071, in red) and E. coli GLMS protein (1XFG, in green). Amino acids alignment is shown in the link above. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The enzyme L-asparaginase from Escherichia coli is a therapeutic enzyme that has been a cornerstone in the clinical treatment of acute lymphoblastic leukemia for the last decades.</ns0:p><ns0:p>However, treatment effectiveness is limited by the highly immunogenic nature of the protein and its cross-reactivity towards L-glutamine. In this work, a bioinformatic approach was used to identify, select and computationally characterize L-asparaginases from Streptomyces through sequence-based screening analyses, immunoinformatics, homology modeling, and molecular docking studies. Based on its predicted low immunogenicity and excellent enzymatic activity, we selected a previously uncharacterized L-asparaginase from Streptomyces scabrisporus. Furthermore, two putative asparaginase binding sites were identified and a 3D model is proposed. These promising features allow us to propose L-asparaginase from S. scabrisporus as an alternative for the treatment of acute lymphocytic leukemia.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Acute lymphocytic leukemia (ALL) is a hematological disorder of the bone marrow and is characterized by abnormal proliferation of immature lymphoid line cells, blocked at an early stage of cell differentiation, that accumulate and replace healthy hematopoietic cells in the bone marrow <ns0:ref type='bibr' target='#b47'>(Pui, Relling &amp; Downing, 2004;</ns0:ref><ns0:ref type='bibr' target='#b44'>Onciu, 2009)</ns0:ref>. ALL occurs predominantly in children of 1-4 years of age and represents approximately 25% of childhood cancers and about 80% of leukemias <ns0:ref type='bibr' target='#b34'>(Katz et al., 2015)</ns0:ref>.</ns0:p><ns0:p>Although in most cases the risk factors and pathogenicity associated with ALL have not been clearly identified, the etiology of the disease has been mainly associated with a variety of conditions; cytogenetic alterations, mutations to key genes that regulate cellular proliferation, Manuscript to be reviewed differentiation and death; presence of oncogenic viruses, immunodeficiency, exposure to pesticides, solvents, and ionizing radiation <ns0:ref type='bibr' target='#b47'>(Pui, Relling &amp; Downing, 2004;</ns0:ref><ns0:ref type='bibr' target='#b4'>Bassan, Maino &amp; Cortelazzo, 2016)</ns0:ref>.</ns0:p><ns0:p>Treatment for ALL patients involve steroid drugs, prednisone, vincristine, and the enzyme Lasparaginase (ASNase) <ns0:ref type='bibr' target='#b2'>(Avramis, 2012;</ns0:ref><ns0:ref type='bibr' target='#b56'>Schwab &amp; Harrison, 2018)</ns0:ref>. ASNase has been essential in the treatment of ALL since the 1970s, with demonstrated effectiveness as an individual drug with remission rates of up to 68% <ns0:ref type='bibr' target='#b51'>(Salzer et al., 2017)</ns0:ref>. The combination of ASNase with other anticancer drugs has led to remission rates of up to 90% (Lanvers-Kaminsky, 2017).</ns0:p><ns0:p>Currently, there are four ASNase formulations available for the ALL treatment: two native forms of the enzyme, obtained from Escherichia coli (EcAII) and Erwinia chrysanthemi (ErAII), and pegylated E. coli ASNase (EcAII-PEG), as well as pegylated E. chrysanthemi ASNase (ErAII-PEG). Of these, EcAII-PEG has become the first-line treatments for ALL in the US, with EcAII the most widely used formulation. ErAII is administered to patients who have developed hypersensitivity to the above formulations <ns0:ref type='bibr' target='#b46'>(Pieters et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b0'>Abribat, 2016;</ns0:ref><ns0:ref type='bibr' target='#b3'>Barba et al., 2017)</ns0:ref>.</ns0:p><ns0:p>In recent years, evidence has been accumulating of its usefulness as an important component in the treatment of other hematological malignancies, such as acute myeloid leukemia, myelosarcoma, lymphosarcoma, Hodgkin's disease, and chronic lymphocytic leukemia <ns0:ref type='bibr' target='#b14'>(Emadi, Zokaee &amp; Sausville, 2014;</ns0:ref><ns0:ref type='bibr' target='#b37'>Lopes et al., 2015)</ns0:ref>. Despite their high antileukemic potential, the use of ASNases in the treatment of ALL is limited by their toxicity. Among the adverse effects that have been reported are leukopenia, immune suppression, acute pancreatitis, liver dysfunction, hyperglycemia, abnormalities in hemostasis, and hemorrhages of the central nervous system <ns0:ref type='bibr' target='#b55'>(Schein et al., 1969;</ns0:ref><ns0:ref type='bibr' target='#b48'>Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b9'>Chan et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b1'>Ali et al., 2016;</ns0:ref><ns0:ref type='bibr' target='#b28'>Hijiya &amp; van der Sluis, 2016;</ns0:ref><ns0:ref type='bibr' target='#b32'>Kamal et al., 2019)</ns0:ref>.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The generation of immune responses during treatment with ASNase is a common condition that has been reported in up to 75% of patients. These reactions depend on the formulation used, the mode of administration (intravenous or intramuscular), and the treatment protocol <ns0:ref type='bibr' target='#b26'>(Hijiya &amp; van der Sluis, 2015)</ns0:ref>. For example, between 30 and 75% of patients that receive the native form of the E. coli enzyme experience hypersensitivity reactions, and about 70% develop anti-EcAII antibodies after drug administration <ns0:ref type='bibr' target='#b5'>(Battistel et al., 2020)</ns0:ref>; these antibodies lead to rapid inactivation of the enzyme <ns0:ref type='bibr' target='#b62'>(Walenciak et al., 2019)</ns0:ref>. Allergic reactions to ASNase, which are associated with its bacterial origin, range from mild urticaria to life-threatening anaphylactic shock. Irritation, fever, vomiting, gastrointestinal edema, and breathing difficulties are symptoms frequently reported (Lanvers-Kaminsky, 2017). On the other hand, adverse effects have been reported due to the toxicity produced by glutaminase cross activity, such as leukopenia, immune suppression, acute pancreatitis, hyperglycemia, thrombosis, neurotoxicity, and liver failure, among others <ns0:ref type='bibr' target='#b48'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b9'>Chan et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b1'>Ali et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Different strategies to reduce the toxicity of ASNase have been reported, including modifications in the structure of the protein by mutagenesis, design of mutants with diminished ability to hydrolyze L-glutamine, chemical modifications in specific amino acids, and modifications to drug formulations <ns0:ref type='bibr' target='#b48'>(Ramya et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b41'>Nguyen, Su &amp; Lavie, 2016;</ns0:ref><ns0:ref type='bibr' target='#b43'>Nguyen et al., 2018)</ns0:ref>. Covalent conjugation of the enzyme with polyethylene glycol, known as PEGylation, reduces the incidence of hyperglycemia, pancreatitis, and anaphylaxis. This specific modification increase the half-life of the enzyme and reduces the frequency of drug administration <ns0:ref type='bibr' target='#b61'>(Thomas &amp; Le Jeune, 2016)</ns0:ref>.</ns0:p><ns0:p>On the other hand, the exploration of new sources of ASNases offers the possibility of finding versions of the enzyme with different pharmacological characteristics, potentially useful for the</ns0:p></ns0:div> <ns0:div><ns0:head>Materials &amp; Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Identification and selection of homologous L-Asparaginases</ns0:head><ns0:p>Putative ASNases from Streptomyces were identified through a BLASTp search against the NR database of the NCBI using as seeds the amino acid sequences of EcAII (ID P00805) and Streptomyces coelicolor type II ASNase (ScAII; ID Q9K4F5). The search was restricted to the Streptomyces taxon (Taxid 1883), and an E-value less than 1e-06 was considered significant.</ns0:p><ns0:p>Partial proteins and those from unidentified Streptomyces strains were excluded. In a posterior step, the set of protein sequences was filtered at 60% identity as cutoff to avoid redundancy, using the CD-Hit program (http://weizhongli-lab.org/cdhit_suite/cgi-bin/index.cgi) <ns0:ref type='bibr' target='#b29'>(Huang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>Each cluster was analyzed using the HMMER program on the PFAM server (http://pfam.xfam.org/) to determine the protein family to which they belonged <ns0:ref type='bibr' target='#b18'>(Finn, Clements &amp; Eddy, 2011;</ns0:ref><ns0:ref type='bibr' target='#b20'>Finn et al., 2016)</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.2'>Phylogenetic analysis</ns0:head><ns0:p>ASNases amino acid sequence alignments were performed using Clustal Omega <ns0:ref type='bibr' target='#b57'>(Sievers et al., 2011)</ns0:ref> with default parameters. The quality of the alignments was improved using the model PF06089.11 or PF00710.11 of ASNase, as required. Multiple sequence alignment statistics were computed with AliStat (http://www.csb.yale.edu/userguides/seq/hmmer/docs/node27.html).</ns0:p><ns0:p>Phylogenetic analyses were carried out using the maximum-likelihood method with the program Mega 7. The WAG model was chosen as substitution model, and 1000 replicates were performed.</ns0:p><ns0:p>The best tree was calculated using the majority rule. Additionally, E. coli type I ASNase <ns0:ref type='bibr'>(EcAI)</ns0:ref> was included in the phylogenetic analysis of the PF00710.11 cluster. EcAI is closely related to Manuscript to be reviewed EcA but it does not have therapeutic potential. For the PF06089.11 cluster, Rhizobium etli type II ASNase (ReAII) was included in the analysis.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.3'>Antigenicity prediction</ns0:head><ns0:p>The prediction of the probability of antigenicity of each ASNase was calculated with the server ANTIGENpro (http://scratch.proteomics.ics.uci.edu/) <ns0:ref type='bibr' target='#b38'>(Magnan et al., 2010)</ns0:ref>. ANTIGENpro is a sequence-based, alignment-free, protein antigenicity predictor with an estimated accuracy of 82%.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.4'>HLA class II binding prediction</ns0:head><ns0:p>The amino acid sequence of each candidate ASNase was screened for T-cells epitopes with the MHC II Analysis Resource at the Immune Epitope Data Base (IEDB) server and HLA-DRB1*15:01. The IEDB-recommended method uses the consensus approach, combining <ns0:ref type='bibr'>NN-align, SMM-align, CombLib, Sturniolo, and NetMHCIIpan (Wang et al., 2010)</ns0:ref>.</ns0:p><ns0:p>For each peptide, a percentile rank is generated by comparing the peptide's score against the scores of five million random 15-mer selected from SWISSPROT database, and the median percentile rank is used to calculate a consensus percentile rank (CPR). Peptides with a CPR &lt; 2 were defined as high-affinity binders and thus selected for epitope density (ED) calculation. Multiple 9-mer cores were identified in overlapped 15-mer peptides. To reduce overestimation of predicted peptides, only the 9-mer cores, predicted by using the Sturniolo method <ns0:ref type='bibr' target='#b59'>(Sturniolo et al., 1999)</ns0:ref> PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed and with a CPR &lt; 1, were considered for the analysis. Finally, epitope density (ED) was calculated using the follow equation, modified from <ns0:ref type='bibr' target='#b54'>(Santos et al., 2013)</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_0'>&#119864;&#119863; = &#119875;&#119903;&#119890;&#119889;&#119894;&#119888;&#119905;&#119890;&#119889; &#119890;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; * (2 -&#119860;&#119891;&#119891;&#119894;&#119899;&#119894;&#119905;&#119910; &#119886;&#119907;&#119890;&#119903;&#119886;&#119892;&#119890; ( &#119888;&#119901;&#119903; ) ) &#119875;&#119903;&#119900;&#119905;&#119890;&#119894;&#119899; &#119897;&#119890;&#119899;&#119892;&#119905;&#8462; &#119904;&#119894;&#119911;&#119890; -&#119864;&#119901;&#119894;&#119905;&#119900;&#119901;&#119890; &#119904;&#119894;&#119911;&#119890; + 1</ns0:formula><ns0:p>Where Predicted epitope is the number of epitopes with a CPR &lt; 1.</ns0:p><ns0:p>Epitope coverage was calculated as the number of alleles covered by the epitope consensus, according to the following assumption: when a small number of alleles is covered, a lower percentage of the population will develop sensitivity to ASNase.</ns0:p></ns0:div> <ns0:div><ns0:head n='1.5'>Protein structure prediction, refinement and quality assessment</ns0:head><ns0:p>The three-dimensional structures of the selected ASNases was modeled by homology using the I-Tasser server (https://zhanglab.ccmb.med.umich.edu/I-TASSER/) <ns0:ref type='bibr' target='#b67'>(Zhang, 2008)</ns0:ref>. In brief, starting from an amino acid sequence, I-Tasser generates three-dimensional atomic models from multiple threading alignments and iterative structural assembly simulations. A C-score, provided as an estimate of the accuracy of the models generated, typically ranges between -5 to +2, with a higher value indicating higher confidence, and vice versa <ns0:ref type='bibr' target='#b50'>(Roy, Kucukural &amp; Zhang, 2010)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the model with the higher C-score was selected and then refined using the ModRefiner server (https://zhanglab.ccmb.med.umich.edu/ModRefiner/). ModRefiner improves the physical quality and structural accuracy of three-dimensional protein structures by a two-step, atomic-level energy minimization <ns0:ref type='bibr' target='#b66'>(Xu &amp; Zhang, 2011)</ns0:ref>. Finally, the quality of the models was evaluated by RAMPAGE (http://mordred.bioc.cam.ac.uk/~rapper/rampage.php), Qmean (https://swissmodel.expasy.org/qmean/), and Verify3D (http:/servicesn.mbi.ucla.edu/Verify3D). <ns0:ref type='table'>2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing PDF | (</ns0:head></ns0:div> <ns0:div><ns0:head n='1.6'>Molecular docking</ns0:head><ns0:p>The molecular coupling was carried out using Autodock Tools software <ns0:ref type='bibr' target='#b53'>(Sanner, 1999;</ns0:ref><ns0:ref type='bibr' target='#b40'>Morris et al., 2009)</ns0:ref>. EcAII (PDB ID: 3ECA) was recovered from the PDB protein database (http://www.rcsb.org/) <ns0:ref type='bibr' target='#b60'>(Swain et al., 1993;</ns0:ref><ns0:ref type='bibr' target='#b6'>Berman et al., 2000)</ns0:ref>. Once refined, selected ASNase structures were prepared using Dock prep at UCSF Chimera and refined using the Gasteiger method <ns0:ref type='bibr' target='#b22'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>The three-dimensional structures of the asparagine and glutamine ligands were obtained from the DrugBank repository (https://www.drugbank.ca/; accession numbers DB00174 and DB00130, respectively) <ns0:ref type='bibr' target='#b64'>(Wishart et al., 2018)</ns0:ref>. The preparation of the ligands was carried out by the Gasteiger method and, finally, the allocation of the rotation centers was determined <ns0:ref type='bibr' target='#b22'>(Gasteiger and Marsili, 1978)</ns0:ref>.</ns0:p><ns0:p>For each ASNase, the search box was focused on previously proposed active sites. The box size was defined to cover all residues of the ligand binding site, using a grid size of 0.375 &#197;.</ns0:p><ns0:p>Blind molecular docking was performed with Autodock 4.2 software, using the Lamarckian genetic algorithm, with 1000 runs, for a population size equal to 150, with 2.5 x 10^6 evaluations, a mutation rate equal to 0.02 in 27,000 generations.</ns0:p><ns0:p>In addition, the active site location was predicted by AutoLigand <ns0:ref type='bibr' target='#b25'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Briefly, AutoLigand identifies sites of maximum affinity from maps generated by AutoGrid, finding regions with better energy and a lower volume. <ns0:ref type='table'>PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:ref> Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>PeerJ reviewing</ns0:head></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head n='2.1'>L-Asparaginases from Streptomyces cluster into two type families according to its protein architecture</ns0:head><ns0:p>The Blast search against the Streptomyces taxon revealed 296 putative ASNases homologous to EcAII and 703 homologous to ScAII with a significant score. After manual examination of both groups, 136 and 311 complete sequences were kept for EcAII and ScAII groups, respectively. Protein domain analysis using PFAM server showed that 136 sequences are related to the PF00710.11 family of N-terminal ASNases. For sequences homologous to ScAII, PFAM analysis revealed that they belong to the PF06089.11 family of ASNases, a group of enzymes related to ReAII, a thermolabile enzyme induced by L-asparagine and repressed by the carbon source <ns0:ref type='bibr' target='#b39'>(Moreno-Enriquez et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b30'>Huerta-Saquero et al., 2013)</ns0:ref>. Representative clusters for PF00710.11 and PF06089.11 families obtained using the CD-Hit suite program were generated at a 60% identity cutoff, with 19 and 7 putative ASNases, respectively (Table <ns0:ref type='table'>1</ns0:ref>). ASNases sequences showed similar lengths in both clusters, ranging from 320 to 420 amino acids. Manuscript to be reviewed lower affinity than L-asparaginases from both E. coli and E. chrysanthemi <ns0:ref type='bibr' target='#b39'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Furthermore, ReAII is the only ASNase characterized from the PF06089.11 family</ns0:p></ns0:div> <ns0:div><ns0:head n='2.2'>Phylogenetic analysis of ASNases</ns0:head><ns0:p>For the PF00710.11 family, EcAI was added to the multiple sequence alignment in order to know the relationship between this ASNase and the candidate ASNases. EcAI belongs to the same family of proteins as EcAII, but it does not represent a therapeutic option for ALL treatment. It is noteworthy that asparaginases can also be classified according to subcellular localization, a) periplasmic asparaginases containing secretion signal peptide and, b) asparaginases with intracellular localization. The former generally have a higher affinity for asparagine. However, according to their architecture, both types of proteins can be found in the PF00710.11 or PF06089.11 families. This is the case of E. coli asparaginases I and II, both belonging to the PF00710.11 family (https://pfam.xfam.org/family/PF00710#tabview=tab1). We found that the ASNase with accession number WP_059134811.1 of Streptomyces alboniger is grouped in the same clade as EcAI, and so it was excluded from subsequent analyses (Figure <ns0:ref type='figure' target='#fig_20'>1A</ns0:ref>).</ns0:p><ns0:p>The phylogenetic reconstruction showed three well-defined clades (Figure <ns0:ref type='figure' target='#fig_20'>1A</ns0:ref>). On the other hand, for the ASNases of PF06089.11, phylogenetic analysis included both the ASNase sequence of R. etli and S. coelicolor (ReAII and ScAII, respectively) (Figure <ns0:ref type='figure' target='#fig_20'>1B</ns0:ref>). The tree defines two clades. In the first one, where the ScAII was included, we also considered ARZ68596.1 from S. albireticuli, SOD64826.1 from S. zhaozhouensis, WP_078645645 from S. varsoviensis, CDR15801.1 from S. iranensis, and WP_020554088 from S. scabrisporus.</ns0:p><ns0:p>In the second clade were included the following proteins: WP_044373749 from S. ahygroscopicus and WP_078980718.1 from S. scabrisporus. </ns0:p></ns0:div> <ns0:div><ns0:head n='2.3'>Antigenicity predictions</ns0:head><ns0:p>The results for antigenicity showed a likelihood of being antigenic for all ASNases in both sets that was lower than that of EcAII (Figure <ns0:ref type='figure' target='#fig_7'>2</ns0:ref>). Nevertheless, among selected Streptomyces ASNases, the candidates from S. purpurogeneiscleroticus (WP_053609500.1) and S. phaeochromogenes </ns0:p></ns0:div> <ns0:div><ns0:head n='2.4'>T-cell epitope analysis</ns0:head><ns0:p>After antigenicity prediction, the ED, the total number of high-affinity epitopes, the affinity epitopes, and the number of HLA alleles covered by each ASNase were calculated. The results showed that the ASNases with accession numbers WP_053609500.1, WP_053610569.1, EFL23513.1, WP_095730579.1, WP_078513220.1, and WP_052425051.1 have higher EDs than the reference (P00805_EcAII; ED=0.01114; 5 covered alleles) (Figure <ns0:ref type='figure' target='#fig_9'>3</ns0:ref>).</ns0:p><ns0:p>On the other hand, the ASNase with the lowest predicted ED was WP_044373749.1, with an ED of 0.0027 and a coverage of 4 alleles, following by WP_095730579.1 (2 alleles), ELP65653.1 (3 alleles), and Q9K4F5 (3 alleles) (Table <ns0:ref type='table'>2</ns0:ref>).</ns0:p><ns0:p>Additionally, the distribution of epitopes was mapped into the sequences of the ASNases (Figure <ns0:ref type='figure' target='#fig_9'>3</ns0:ref>). ASNases of the PF06089.11 family tended to have a lower ED (Table <ns0:ref type='table'>3</ns0:ref>) as well as lower allele coverage than those of the PF00710.11 family (Figure <ns0:ref type='figure' target='#fig_9'>3</ns0:ref>). Manuscript to be reviewed Next, ASNases with lower allele coverage, lower ED, and lower probability of antigenicity were selected for further analysis. S. coelicolor (Q9K4F5), S. scabrisporus (WP_078980718.1), and S. albireticuli (ARZ68596.1) were selected as promising enzymes.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.5'>Protein structure predictions</ns0:head><ns0:p>From selected ASNases, homology-based models were generated (I-Tasser). For the subsequent analysis, the S. scabrisporus asparaginase II model, which had the highest C-value, was chosen (WP_078980718.1 SsAII-2) (Figure <ns0:ref type='figure' target='#fig_10'>4</ns0:ref>). The structural model obtained by I-Tasser (with a C-value of -3.09) was refined with ModRefiner. In addition, the RAMPAGE program (http://mordred.bioc.cam.ac.uk/&#732;rapper) and Verify3D were used to validate the stereochemical quality of the resulting three-dimensional model. After analyzing the Ramachandran plot, 91.7% and 5.5% of the residues were located in favored and allowed regions, respectively; whereas Verify3D analysis revealed that 80.73% of the residues had an average 3D-1D score &lt; 0.2, indicating that the model is compatible with its sequence.</ns0:p><ns0:p>Based on the predicted structure, ASNase WP_0789718.1 (PF06089.11 family) is related in terms of folding to the beta-lactamase family. Beta-lactamases (SCOP data base, entry 56600) consist of a cluster of alpha-helices and an alpha/beta sandwich. This folding is also found in transpeptidases, esterases, penicillin receptors, D-aminopeptidases, and glutaminases (InterPro IPR012338).</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed </ns0:p></ns0:div> <ns0:div><ns0:head n='2.6'>Active site prediction</ns0:head><ns0:p>In order to identify the active site residues of the S. scabrisporus ASNase (WP_0789718.1), three approaches were used: genomic comparison, blind molecular coupling simulation, and search for high-affinity binding pockets with AutoLigand (active site). To our knowledge, there is no information regarding the active site of the family PF06089.11 ASNases, so genomic comparison was not possible. Using AutoLigand, two possible high affinity binding sites for L-asparagine were identified (Figure <ns0:ref type='figure' target='#fig_11'>5A</ns0:ref>). The first (site A) had a volume of 121 &#197; 3 and an energy per volume equal to -0.2149 kcal/mol &#197; 3 ; the second (site B) had a volume of 101 &#197; 3 and an energy per volume equal to -0. 2136 kcal/mol &#197; 3 . Site A is located between an alpha-helix in the amino terminal containing the 57 PRSx(2)KPxQ 65 motif, and a loop in the central region of the enzyme, containing the 141 NCSGKHxAML 150 motif (Table <ns0:ref type='table'>3</ns0:ref>). Site B is located in a pocket formed by a set of alphahelices in the amino terminal of the protein, marked by the presence of the 87 SHTGQxHFV 95 motif.</ns0:p><ns0:p>On the other hand, by performing AutoDock 4.2 whole-protein molecular coupling simulations, we found that the best ligand-enzyme interaction (L-asparagine-ASNase), with a binding free energy of -4.17 kcal/mol, targeted residues corresponding to the 141 NCSGKHxAML 150 motif, which correspond to the site A (Figure <ns0:ref type='figure' target='#fig_11'>5B</ns0:ref>). Manuscript to be reviewed Additionally, in order to validate AutoLigand analysis searching active sites in the S. scabrisporus ASNases, a search for binding sites in EcAII was performed. To do this, the monomeric, dimeric, and tetrameric forms of the enzyme (the latter is the catalytically active form) were analyzed using the same conditions used for SsAII-2. It was found that AutoLigand successfully identified the binding site of L-Asn, consisting of Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, and Lys 162 and also Asn 248 and Glu 283 (Figure <ns0:ref type='figure' target='#fig_12'>6</ns0:ref>), the latter two only for dimeric and tetrameric forms. The sites found (red squares curves) had energies by volume equal to -0.2119, -0.2242, and -0.2366 kcal/mol &#197; 3 and a volume of 136, 122, and 102 &#197; 3 for the monomer, dimer, and tetramer, respectively (Figure <ns0:ref type='figure' target='#fig_13'>7</ns0:ref>). It is relevant that for both the dimeric and the tetramer forms, AutoLigand successfully identified L-Asn binding pockets in EcAII: the pocket formed between the aminoterminal end of subunit A and the carboxy terminal of the subunit C, as well as equivalent pockets for dimer BD. In addition, several other solutions found by AutoLigand (curve with blue or green squares), using up to 90 filling points, converge in the different joint pockets formed by dimers. Manuscript to be reviewed tetramer conformation. As more filling points are used, the binding sites, cavities, or grooves are filled and the affinity decreases. The best sites are the ones with the lowest energy and the lowest volume.</ns0:p></ns0:div> <ns0:div><ns0:head n='2.7'>Molecular docking</ns0:head><ns0:p>Molecular docking simulations were performed at the putative sites found (Table <ns0:ref type='table'>4</ns0:ref>). For EcAII, as the reference ASNase, Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp 90, Asn 248, and Glu 283 were established as flexible residues; meanwhile, molecular docking for S. scabrisporus ASNase were performed using only the rigid structure of the protein, without defining flexible side chains for L-asparagine binding.</ns0:p><ns0:p>Our results showed a higher affinity for L-asparagine of the S. scabrisporus ASNase site A than site B; however, the affinity was lower than that for EcAII. For S. scabrisporus ASNase site A, the L-asparagine interacts with residues Ser 59, Lys 62, Asn 141, Ser 143, Lys 145, His 146, Gly 237, Lys 255, and Gly 256 (Figure <ns0:ref type='figure' target='#fig_15'>8A</ns0:ref>); for site B, the residues that interact with L-asparagine are Ala 84, Gly 78, Ser 87, Tyr 163, Leu 164, and Asp165 (Figure <ns0:ref type='figure' target='#fig_15'>8B</ns0:ref>). Interestingly, from site A, Lys </ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>In this work, a set of bioinformatics tools were used to identify, select, and characterize ASNases from the Streptomyces genus. ASNase identification was carried out by searching sequences homologous to EcAII and ScAII. EcAII is the best-characterized and most widely used ASNase for ALL treatment, while ScAII is a homologous ASNase related to ReAII, an atypical ASNase with no glutaminase activity and with a different immunogenic profile than EcAII <ns0:ref type='bibr' target='#b30'>(Huerta-Saquero et al., 2013)</ns0:ref>. The search for homologous sequences resulted in two sets of sequences with a high probability of being ASNases (E value &lt;1e-06). These sequence sets, in turn, were classified into two different protein families based on their homology, using HMMer: PF00710.11 and PF06089.11, according to the classification of the PFAM database. So far, most of the reported ASNases belong to the PF00710.11 family and have been extensively studied. EcAII and the E.</ns0:p><ns0:p>chrysanthemi ASNase belong to this family. On the other hand, the PF06089.11 family represents a group of atypical ASNases that remain poorly characterized. Some representative reports about these ASNases include the R. etli ASNase <ns0:ref type='bibr' target='#b45'>(Ortu&#241;o-Olea &amp; Dur&#225;n-Vargas, 2000;</ns0:ref><ns0:ref type='bibr' target='#b39'>Moreno-Enriquez et al., 2012;</ns0:ref><ns0:ref type='bibr' target='#b30'>Huerta-Saquero et al., 2013)</ns0:ref>.</ns0:p><ns0:p>Interestingly, the BLAST results showed a greater abundance of PF06089.11 family sequences compared to the PF00710.11 family in Streptomyces. In addition, we found that about 20% of species have ASNase isoforms. In that sense, many Gram-negative bacteria have at least two isozymes of the family PF00710.11 <ns0:ref type='bibr' target='#b17'>(Fern&#225;ndez &amp; Z&#250;&#241;iga, 2006)</ns0:ref> and, in E. coli, the existence of a third isoenzyme has been recently reported <ns0:ref type='bibr' target='#b11'>(Correia da Silva et al., 2018)</ns0:ref>. Historically, the genus Streptomyces has been attractive due to the wide repertoire of bioactive molecules produced.</ns0:p><ns0:p>However, searching for ASNases of pharmacological interest has been done only rarely.</ns0:p><ns0:p>After the identification of two sets of ASNases, we chose T-cell ED as the immunogenicity indicator, according to <ns0:ref type='bibr'>Cantor et al. (2004</ns0:ref><ns0:ref type='bibr'>), Fern&#225;ndez et al. (2012)</ns0:ref>, and Galindo-Rodr&#237;guez et al. Manuscript to be reviewed (2017), who proposed that HLA class II molecules play a critical role in the development of specific anti-ASNase antibodies and in hypersensitivity to the enzyme <ns0:ref type='bibr' target='#b8'>(Cantor et al., 2011;</ns0:ref><ns0:ref type='bibr' target='#b15'>Fernandez et al., 2014;</ns0:ref><ns0:ref type='bibr' target='#b21'>Galindo-Rodr&#237;guez et al., 2017)</ns0:ref>. Additionally, it has been shown that proteins that are highly immunogenic generally contain a greater amount of T-cell epitopes, or clusters thereof <ns0:ref type='bibr' target='#b58'>(Singh et al., 2012)</ns0:ref>. In addition, the measurement and prediction of ED have generated interest as useful tools for comparisons between therapeutic proteins, allowing selection of the best candidate in terms of probable immunogenicity <ns0:ref type='bibr' target='#b24'>(De Groot &amp; Martin, 2009)</ns0:ref>. In this sense, our results showed that ASNases of the PF06089.11 family contain lower EDs than enzymes of the PF00710.11 family, as well as fewer epitope clusters throughout the sequence. In addition, the allele coverage, which is related to the percentage of the population that develops a significant immune response, showed Streptomyces ASNases to be potential pharmacological options. In For the PF06089.11 family of ASNases, the lack of information of the active site precludes direct comparison, as was used in the approach for the ASNase WP_078979039.1. However, the use of computational tools based on structure inspection and on the evaluation of affinity maps has proven highly effective in identifying probable binding sites in uncharacterized proteins <ns0:ref type='bibr' target='#b25'>(Harris, Olson &amp; Goodsell, 2008)</ns0:ref>. Based on the use of computational tools, it was possible to identify two Manuscript to be reviewed putative binding sites in SsAII-2 (WP_078980718.1). Interestingly, in both sites the motifs NCSGKHxAM, PRSx(2)KPxQ, and SHTGQx(2)H were identified, and these motifs are highly conserved in the PF06089.11 family <ns0:ref type='bibr' target='#b39'>(Moreno-Enriquez et al., 2012)</ns0:ref>. Of these., <ns0:ref type='bibr' target='#b7'>Borek et al. (2001)</ns0:ref> proposed that some of the residues of the NCSGKHxAM motif could be involved in the hydrolytic deamidation of L-asparagine <ns0:ref type='bibr' target='#b7'>(Borek &amp; Jask&#243;lski, 2001)</ns0:ref>.</ns0:p><ns0:p>On the other hand, the residues we found conserved in this family of asparaginases resemble those of the active site of the Ntn amidotransferases, in which, among the important residues for glutamine deamidation are found Cys, Asn, and Gly, all of them present in NCSGKHxAM motif, and the deamidation mechanism proceeds with an oxyanion formation with the substrate. Although this mechanism is described for glutamine amidohydrolases, it may be a mechanism similar to that of this family of asparaginases, whose active site is different from those of the PF00710.11 family <ns0:ref type='bibr' target='#b31'>(Isupov et al., 1996)</ns0:ref>.</ns0:p><ns0:p>Although site A showed higher affinity for L-asparagine binding, additional studies are needed to confirm the best site for ligand binding. Additionally, molecular dynamics simulations can provide more evidence of the characteristics of the binding site and, together with in vitro studies, will be useful for understanding the mechanism of enzymatic reaction <ns0:ref type='bibr' target='#b33'>(Karplus &amp; Kuriyan, 2005)</ns0:ref>.</ns0:p><ns0:p>Although our results predicted that SsAII-2 has a lower affinity than EcAII, its different folding and immunogenic characteristics place it as a good candidate. Identifying catalytic site residues will allow us to perform site-directed modifications to increase its affinity.</ns0:p><ns0:p>The strategy developed here can be applied to the search for asparaginases in other clades of microorganisms, and even in eukaryotes, specifically mammalian asparaginases, whose evolutionary proximity to humans predicts less immunogenicity. Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>In summary, the search for ASNases in phylogenetically distant microorganisms and the application of bioinformatic tools to assess their toxicity and affinity for L-asparagine are viable approaches to obtain new ASNases with therapeutic potential. Based on its low immunogenicity and excellent enzymatic activity predicted, we have identified the S. scabrisporus ASNase as a potential alternative for the treatment of ALL. The subsequent enzymatic and immunogenic characterization of the S. scabrisporus ASNase is necessary for the validation of this bioinformatic approach. Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>ASNase</ns0:head><ns0:note type='other'>Figure 7</ns0:note><ns0:p>AutoLigand results for EcAII.</ns0:p><ns0:p>The minima observed in the total energy graphs per unit volume represent putative binding sites in the structures analyzed, for the monomer, dimer, and tetramer conformation. As more filling points are used, the binding sites, cavities, or grooves are filled and the affinity decreases. The best sites are the ones with the lowest energy and the lowest volume.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>http://tools.iedb.org/mhcii/). MHC II Analysis Resource parses sequences into 15-mer and assesses the binding potential of each 15-mer to MHC class II molecules of one or more HLA alleles. The IEDB recommended method was used for predictions for a set of 8 HLA alleles that collectively represent &gt;%95 world population: HLA-DRB1*01:01, HLA-DRB1*03:01, HLA-DRB1*04:01, HLA-DRB1*07:01, HLA-DRB1*08:01, HLA-DRB1*11:01, HLA-DRB1*13:01</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>The sequences belonging to the PF00710.11 family have conserved residues located at the ligand binding site necessary for L-asparagine hydrolysis: Thr 12, Tyr 25, Ser 58, Gln 59, Thr 89, Asp90, and Lys 162 for subunit A; Asn 248 and Glu 283 for subunit C. In this regard, Thr 12-Lys 162-Asp 90 and Thr 12-Tyr 2-Glu 283 are the catalytic triads involved in L-asparagine hydrolysis, where Thr 12 and Thr 89 are involved in the nucleophilic attack of the substrate (Gesto et al., 2013; Sanches, Kraunchenko &amp; Polikarpov, 2016). Concerning the PF06089.11 family, we identified an N-terminal conserved motif, with sequences NCSGKHxAM, DGCGAPL, SHSGEx(2)H, and PRSx(2)KPxQ probably involved in asparagine hydrolysis. ReAII hydrolyzes L-asparagine at similar levels to Erwinia chrysanthemi, but with PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>The first clade includes ASNases from Streptomyces species S. aureocirculatus (WP_078965752.1), S. cattleya (WP_014151616.1), S. thermoautotrophicus (KWW98572.1), S. himastatinicu (EFL23513.1), S. turgidiscabies (ELP65653.1), S. nanshensis (WP_070201703.1), and S. griseus (WP_030748190.1). The second clade includes ASNases from S. albidoflavus (WP_095730579.1), S. kebangsaanensis (WP_073950513.1), S. fradiae (WP_078649241.1), S. himastatinicus (WP_009718687.1), S. purpureus (WP_078513220.1), and S. paucisporeus (WP_079189481.1). Finally, the third clade PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)Manuscript to be reviewed contains proteins from S.purpurogeneiscleroticus (WP_053609500.1), S. purpurogeneiscleroticus (WP_053610569.1), S. phaeochromogenes (WP_055617501.1), and S. lavenduligriseus (WP_051815467.1) where EcAII was included, suggesting that proteins clustered in this clade share similar properties to EcAII. In addition, two proteins, WP_053609500.1 and WP_055617501.1, exhibited the largest proportion of antigenic regions, with almost the same probability regions as the EcAII protein.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 1 .</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1. Phylogenetic tree of PF00710.11 (A) and PF06089.11 (B) families. Blue dots highlight</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)Manuscript to be reviewed (WP_055617501.1) showed a higher probability of being antigenic, whereas the rest of the ASNases showed very low antigenicity values in comparison with an E. coli ASNase (P00805_EcAII).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2. ASNase antigenicity predictions. The antigenicity scores for PF00710.11 family (A) and</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 3 .</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3. Epitope mapping of ASNases of the PF familes evaluated, PF00710.11 and PF06089.11.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head>Figure 4 .</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4. 3D protein structure prediction of S. scabrisporus asparaginase II (WP_078980718.1;</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head>Figure 5 .</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5. SsAII-2 putative binding sites. A) Site A (orange) contains the NCSGKHxAML</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head>Figure 6 .</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6. EcAII dimer AutoLigand analysis. Cyan EcAII subunit C is shown in cyan and subunit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 7 .</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7. AutoLigand results for EcAII. The minima observed in the total energy graphs per unit</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head /><ns0:label /><ns0:figDesc>62, Asn 141, Ser 143, Lys 145, and His 146 are highly conserved in ASNases of the PF06089.11 family.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure 8 .</ns0:head><ns0:label>8</ns0:label><ns0:figDesc>Figure 8. Interaction maps for sites A and B from S. scabrisporus ASNase. The black spheres</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_17'><ns0:head /><ns0:label /><ns0:figDesc>other words, due to their low content of T-cell epitopes, low antigenicity profile, and low allele coverage, Streptomyces ASNases represent, in terms of immunogenicity, a pharmacological alternative for ALL treatment. In this sense, the Streptomyces brollosae NEAE-115 ASNase has better cytotoxicity and immunogenicity profiles for use in ALL treatment, based on evaluation in a murine model, compared with EcAII (El-naggar et al., 2018). Previously, anticancer activity of the Streptomyces fradiae NEAE-82 ASNase in colon cancer cell cultures was reported (El-Naggar et al., 2016).</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_18'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_19'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:47329:5:0:NEW 29 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_20'><ns0:head>Figure 1</ns0:head><ns0:label>1</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_21'><ns0:head>Figure 2</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_22'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_23'><ns0:head>Figure 4 3D</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_24'><ns0:head /><ns0:label /><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_25'><ns0:head>Figure 6</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='50,42.52,255.37,525.00,324.75' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_0'><ns0:head>ID Epitope number CPR value Allele number ED</ns0:head><ns0:label /><ns0:figDesc /><ns0:table><ns0:row><ns0:cell>P00805_EcAII</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6383</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0114</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053609500.1</ns0:cell><ns0:cell>12</ns0:cell><ns0:cell>0.5174</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0171</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_053610569.1</ns0:cell><ns0:cell>14</ns0:cell><ns0:cell>0.5381</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0196</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_055617501.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4532</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.0112</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_051815467.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.6673</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0060</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078649241.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.4554</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0111</ns0:cell></ns0:row><ns0:row><ns0:cell>EFL23513.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.6054</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_014151616.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4024</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_095730579.1</ns0:cell><ns0:cell>8</ns0:cell><ns0:cell>0.5346</ns0:cell><ns0:cell>2</ns0:cell><ns0:cell>0.0115</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078965752.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4987</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0045</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078513220.1</ns0:cell><ns0:cell>9</ns0:cell><ns0:cell>0.4551</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0119</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_009718687.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6480</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0052</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_079189481.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.5217</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0051</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_052425051.1</ns0:cell><ns0:cell>10</ns0:cell><ns0:cell>0.4369</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0170</ns0:cell></ns0:row><ns0:row><ns0:cell>ELP65653.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6717</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0047</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_070201703.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6637</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0069</ns0:cell></ns0:row><ns0:row><ns0:cell>KWW98572.1</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.7254</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0034</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_073950513.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7424</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0048</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_030748190.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.5125</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0046</ns0:cell></ns0:row><ns0:row><ns0:cell>Q9K4F5_ScAII</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.4167</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.0053</ns0:cell></ns0:row><ns0:row><ns0:cell>ARZ68596.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.6283</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0044</ns0:cell></ns0:row><ns0:row><ns0:cell>SOD64826.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5046</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0080</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078645645.1</ns0:cell><ns0:cell>7</ns0:cell><ns0:cell>0.6404</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0074</ns0:cell></ns0:row><ns0:row><ns0:cell>CDR15801.1</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.5510</ns0:cell><ns0:cell>5</ns0:cell><ns0:cell>0.0059</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_078980718.1</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.7003</ns0:cell><ns0:cell>6</ns0:cell><ns0:cell>0.0056</ns0:cell></ns0:row><ns0:row><ns0:cell>WP_044373749.1</ns0:cell><ns0:cell>3</ns0:cell><ns0:cell>0.7114</ns0:cell><ns0:cell>4</ns0:cell><ns0:cell>0.0027</ns0:cell></ns0:row></ns0:table></ns0:figure> <ns0:note place='foot' n='1'>Table 2. High-affinity epitope prediction. Epitope number, CPR value, allele coverage,</ns0:note> </ns0:body> "

"Identification of L-asparaginases from Streptomyces strains with competitive activity and immunogenic profiles: a bioinformatic approach Iván González-Torres, Ernesto Pérez-Rueda, Zahaed Evangelista-Martínez, Andrés Zárate-Romero, Angélica Moreno-Enríquez, Alejandro Huerta-Saquero. Rebuttal letter third review. Dear editor, Here we present an answer to the suggested changes. Editor comments (Joseph Gillespie) MINOR REVISIONS Dear Dr. González-Torres and colleagues: Thanks for revising your manuscript. However, your structural analysis is still not convincing, and it raises some doubt with your interpretations. Your 'structural alignment' in the Supporting information shows that the fold of your protein does not resemble that of the glutaminase at all. This might not be too much of a problem if the putative active site cavity were similar, the region of the putative active site in Fig, 9, (which you decided to show as ribbons instead of actual atoms) is also extremely different, but that doesn't prevent you from claiming similarity. At this time, I do not feel comfortable with accepting your work in its current form. I believe the modeling does not warrant you interpretations at all. Please considering revising your work and aborting framing your conclusions based on this comparative analysis. RESPONSE: We agree that the structural comparison that we present is not totally convincing, since there is no identity in the residues that we propose as an active site and those that form the catalytic site of the E. coli amidotransferase. However, we consider that the probable catalytic site that we propose has enough bioinformatic evidence to be considered as such. We will withdraw our analysis of the structure as suggested. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The gizzard is the only gastrointestinal organ for mechanical processing in birds. Many birds utilize grit in the gizzard to enhance mechanical processing efficiency. We conducted an experiment to test the factors that affect chicken grit use by using 68 male layer chicks of Gallus gallus domesticus, which were divided into two different groups in gizzard muscularity (muscular and less-muscular gizzard). Each muscularity group was fed two different types of diet (herbivory and non-herbivory) to test whether diet and gizzard muscularity of chicks affect grit characteristics such as amount, size, and shape (circularity, roundness, and solidity) of different stages (ingested grit, grit in gizzard, and excreted grit). Amount of ingested grit and grit in gizzard were larger in herbivorous groups, whereas the amount of excreted grit was smaller in herbivorous groups. Larger grit was selectively ingested, especially in the herbivorous groups.</ns0:p><ns0:p>Grit in gizzard was larger in herbivorous groups, while the size of excreted grit was nearly equal or smaller in herbivorous groups. Ingested grit was sharper (low circularity and solidity) than the offered grit. Grit in gizzard was much less-sharp than the offered and ingested grit, especially in the herbivorous, muscular gizzard groups. Excreted grit was less-sharp than the offered grit.</ns0:p><ns0:p>These results show that diet affects the characteristics of ingested grit, grit in gizzard, and excreted grit, whereas gizzard muscularity affects the characteristics of grit in gizzard and excreted grit. The use of large size and amount of grit in gizzard in herbivorous groups may be a response upon needs of digesting hard, coarse materials. Flexibility on grit use might reflect the omnivorous nature of Gallus gallus domesticus and may aid their smooth diet shifts. The results also show that shapes of grit in gizzard do not reflect the shapes of ingested grit, in contrast to previously published concepts, but the shape of grit in the gizzard reflects diet and gizzard muscularity of chicks.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The gizzard is the only gastrointestinal organ for mechanical processing in birds. Many birds utilize grit in the gizzard to enhance mechanical processing efficiency. We conducted an experiment to test the factors that affect chicken grit use by using 68 male layer chicks of Gallus gallus domesticus, which were divided into two different groups in gizzard muscularity (muscular and less-muscular gizzard). Each muscularity group was fed two different types of diet (herbivory and non-herbivory) to test whether diet and gizzard muscularity of chicks affect grit characteristics such as amount, size, and shape (circularity, roundness, and solidity) of different stages (ingested grit, grit in gizzard, and excreted grit). Amount of ingested grit and grit in gizzard were larger in herbivorous groups, whereas the amount of excreted grit was smaller in herbivorous groups. Larger grit was selectively ingested, especially in the herbivorous groups. Grit in gizzard was larger in herbivorous groups, while the size of excreted grit was nearly equal or smaller in herbivorous groups. Ingested grit was sharper (low circularity and solidity) than the offered grit. Grit in gizzard was much less-sharp than the offered and ingested grit, especially in the herbivorous, muscular gizzard groups. Excreted grit was less-sharp than the offered grit. These results show that diet affects the characteristics of ingested grit, grit in gizzard, and excreted grit, whereas gizzard muscularity affects the characteristics of grit in gizzard and excreted grit. The use of large size and amount of grit in gizzard in herbivorous groups may be a response upon needs of digesting hard, coarse materials. Flexibility on grit use might reflect the omnivorous nature of Gallus gallus domesticus and may aid their smooth diet shifts. The results also show that shapes of grit in gizzard do not reflect the shapes of ingested grit, in contrast to previously published concepts, but the shape of grit in the gizzard reflects diet and gizzard muscularity of chicks.</ns0:p></ns0:div> <ns0:div><ns0:head>INTRODUCTION</ns0:head><ns0:p>Digestion, or food processing, is a key phase of animal feeding <ns0:ref type='bibr' target='#b24'>(Montuelle &amp; Kane, 2019)</ns0:ref>. In order to perform efficient digestion, animals have established morphological and physiological adaptations during their evolutionary history. Multiple specialized gastrointestinal organs have been evolved in birds, including a crop for temporal storage of food <ns0:ref type='bibr'>(Proctor &amp; Lynch, 1993)</ns0:ref>, caeca for conservation of water and/or nitrogen recycling <ns0:ref type='bibr' target='#b7'>(DeGolier et al., 1999;</ns0:ref><ns0:ref type='bibr' target='#b21'>Karasawa, 1989)</ns0:ref>, and a gizzard for mechanical processing of ingesta <ns0:ref type='bibr'>(Moore, 1999)</ns0:ref>. In a gizzard, strong compressing and translational stress is put on ingesta for mechanical processing <ns0:ref type='bibr'>(Moore, 1998a)</ns0:ref>. Large food particles are selectively retained in a gizzard until these are ground to small size <ns0:ref type='bibr' target='#b18'>(Hetland et al., 2003;</ns0:ref><ns0:ref type='bibr'>Moore, 1999)</ns0:ref>. For better digestion efficiency, birds ingest and retain grit in a gizzard to break down food particles as efficiently as non-ruminant mammals do with their teeth <ns0:ref type='bibr' target='#b11'>(Fritz et al., 2011)</ns0:ref>. Some birds even travel a long distance to obtain grit in cases where there is not enough sands or gravel close by <ns0:ref type='bibr' target='#b23'>(McIlhenny, 1932)</ns0:ref>. Although multiple nondigestive functions, such as parasite destruction, relief of hunger, and ballast, have been proposed for grit use in vertebrates <ns0:ref type='bibr'>(Wings, 2007)</ns0:ref>, grit use is especially common in herbivorous and granivorous birds <ns0:ref type='bibr' target='#b15'>(Gionfriddo &amp; Best, 1999)</ns0:ref>. Benefits of grit use in domestic chickens have been investigated in field of poultry.</ns0:p><ns0:p>While grit use is not mandatory, previous works generally agree that grit improve digestion efficiency of chickens, especially of the ones that are fed coarse, less-nutritional food <ns0:ref type='bibr' target='#b12'>(Fritz, 1937;</ns0:ref><ns0:ref type='bibr' target='#b18'>Hetland et al., 2003;</ns0:ref><ns0:ref type='bibr'>Smith &amp; MacIntyre, 1959)</ns0:ref>. Other than digestive function, previous works attempted to identify the best form and size of limestone to provide as grit for maximizing egg productivity and quality by layer hens (e.g., <ns0:ref type='bibr' target='#b16'>Guinotte &amp; Nys, 1991;</ns0:ref><ns0:ref type='bibr'>Sk&#345;ivan et al., 2016)</ns0:ref>.</ns0:p><ns0:p>Multiple studies also investigated how different grit (e.g., size, amount, shape) improve nutritional/commercial efficiency in domestic chickens (e.g., <ns0:ref type='bibr' target='#b2'>Balloun &amp; Phillips, 1956;</ns0:ref><ns0:ref type='bibr' target='#b6'>Cooney,</ns0:ref> PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed 1941). On the other hand, factors that affect grit use behaviors are less understood. This is partly because previous studies are based primarily on grit collected from gizzards (e.g., <ns0:ref type='bibr' target='#b3'>Best &amp; Gionfriddo, 1991;</ns0:ref><ns0:ref type='bibr' target='#b14'>Gionfriddo &amp; Best, 1996)</ns0:ref> although grit characteristics can be strongly modified in a gizzard through abrasions <ns0:ref type='bibr' target='#b5'>(Buckner et al., 1926;</ns0:ref><ns0:ref type='bibr'>Wings &amp; Sander, 2007)</ns0:ref>.</ns0:p><ns0:p>Here we report an experiment which tests if different diet and gizzard muscularity changes amount, size, and shape of grit used, in order to understand what affect grit use behavior in domestic chickens. In addition to diet, our experiment also test effects of gizzard muscularity difference on grit use behavior. This is done because gizzard with a higher muscularity should put larger stress to ingesta therefore expected to affect chicken grit use. The factors that may affect chicken grit use are tested upon grit ingestion, retention in a gizzard, and excretion in order to understand the thorough process of chicken grit uses. This study will provide insights into how domestic chicks benefit from changing their grit use behaviors upon demands.</ns0:p></ns0:div> <ns0:div><ns0:head>MATERIALS AND METHODS</ns0:head><ns0:p>Ethics statement: An experiment in this study was approved by Hokkaido University (Permission number: 16-0023) in Sapporo, Japan, and followed the rules specified on Hokkaido University manual for implementing animal experimentation.</ns0:p></ns0:div> <ns0:div><ns0:head>Experimental design and managements</ns0:head><ns0:p>A total of 68 one-day-old male layer chicks (Gallus gallus domesticus), purchased from a local feed manufacturer, were used in this experiment. This sample size was set based on the Hokkaido University regulation, space availability, and several prior experiments conducted on domestic chickens <ns0:ref type='bibr' target='#b18'>(Hetland et al., 2003;</ns0:ref><ns0:ref type='bibr'>Van der Meulen et al., 2008)</ns0:ref>. Prior to the experiment, the chicks were raised for three weeks to produce a difference in initial gizzard muscularity</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed (evaluated as relative weight of a gizzard and the body mass of the chick). The duration was determined based on <ns0:ref type='bibr' target='#b0'>Amerah et al. (2007)</ns0:ref>, which demonstrated a significant gizzard muscularity difference in three weeks. During the three weeks, all chicks were fed commercial starter pellet (Yamaichi Shiryo Co. Ltd.). Development of a gizzard muscularity (Fig. <ns0:ref type='figure'>S1</ns0:ref>) was enhanced on half of the chicks (34 individuals) by feeding larger amount of insoluble fiber (Sacranie et al., 2012) through feeding 30 wt% of rice hull (Honda Co. Ltd.) mixed to the starter pellet. Rice hull was ground to &lt; 5 mm using food processor prior to feed. Non-herbivorous groups (nH-M and nH-lM) fed on dried fish (Engraulis japonicas), purchased from Sakamoto Corp. The chicks were fed either 100% grass or 100% fish to test effect on grit use under extreme diet difference. Grass and dried fish were ground to &lt; 5 mm using food processor and provided as meal.</ns0:p><ns0:p>During the experiment, all chicks were raised in individual cages with wire mesh floor.</ns0:p><ns0:p>Room temperature was maintained between 28 &#176;C to 30 &#176;C. Lighting was controlled as 12 hours in light and 12 hours in dark. All of the chicks were given ad libitum access to total of 24 grams of grit per chicks, which were provided separate from feed. Feces on the last day of the experiment were collected to evaluate characteristics of excreted grit. All chicks were weighed and then euthanized by cervical dislocation at the end of the experiment, following the Hokkaido University regulations. Gizzards were removed from all of the carcasses and weighed after</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed removing stomach contents.</ns0:p></ns0:div> <ns0:div><ns0:head>Terminology</ns0:head><ns0:p>Offered grit refers to the stones which were given ad libitum access to each chick (Fig. <ns0:ref type='figure'>1A</ns0:ref>). Ingested grit refers to the stones which were swallowed by the chicks out of the offered grit during the experiment. Uningested grit refers to the stones which were not ingested by the chicks out of the offered grit by the end of the experiment. Grit in gizzard refer to the stones remained in the gizzards of the chicks after euthanization. Excreted grit refers to the stones excreted with the feces on the last day of the experiment. Initial gizzard muscularity refers to the gizzard muscularity of chicks at the start of the experiment. 'Sharp' is used to describe grit with relatively low circularity, roundness, and/or solidity and 'less-sharp' is used to describe grit with relatively high shape index.</ns0:p></ns0:div> <ns0:div><ns0:head>Grit characteristics</ns0:head><ns0:p>All of the grit used in the experiment were silicastic stones. The amount, size, and shape of grit (offered grit, uningested grit, grit in gizzard, and excreted grit) were evaluated. The amount of grit was evaluated in weights (grams). Size and shape were evaluated quantitatively using the menu command Analyze &gt; Analyze particles of ImageJ <ns0:ref type='bibr'>(Schneider et al., 2012)</ns0:ref>. To obtain the images for the analyses, grit was manually separated from each other and was lighted from the background to obtain clear outlines (Fig. <ns0:ref type='figure'>1B</ns0:ref>, Fig. <ns0:ref type='figure'>S2</ns0:ref>). All images were taken manually.</ns0:p><ns0:p>A minor axis was employed as a grit size index (in millimeters). Circularity, roundness, and solidity were employed as grit shape indexes <ns0:ref type='bibr'>(Schneider et al., 2012)</ns0:ref>: circularity was calculated as four times the product of &#960; and area, divided by square of perimeter; roundness was an inverse of an aspect ratio; and solidity was calculated as an area of a grit divided by an area of convex</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed hull (Fig. <ns0:ref type='figure'>1C</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Offered grit</ns0:head><ns0:p>The amount, size, and shape of ingested grit was inferred by comparing the characteristics of offered and uningested grit. To test size preference by the chicks, the size distribution of offered grit was controlled in advance. Grit was classified into six different size classes by dry sieving using sieves of Sanpo Corp. (0.5-1.0 mm, 1.0-1.4 mm, 1.4-1.7 mm, 1.7-2.0 mm, 2.0-2.8 mm, 2.8-3.35 mm). Four grams of grit from each size classes were supplied in mixture. Prior to the experiment, minor axis, circularity, roundness, and solidity of 500 randomly chosen grit from each size classes were evaluated by ImageJ (Fig. <ns0:ref type='figure'>S3</ns0:ref>). After the experiment, uningested grit was collected and sieved into the six size classes. Five-hundred uningested grit were randomly sampled from each size classes and their size and shape indexes were evaluated (Fig. <ns0:ref type='figure'>S3</ns0:ref>). To test size preferences, amount of ingested grit in each size classes was evaluated by subtracting the weights of the uningested grit from weights of the offered grit by each size classes (4 grams each). Average values of the shape indexes of the uningested grit were compared with those of the offered grit to test if there was any shape preference on the ingested grit. The amount, size, and shape of the uningested grit was then compared among different diet and gizzard muscularity groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Grit in gizzard</ns0:head><ns0:p>Grit in gizzard was separated from other stomach contents by a floatation method (decantation), modified from <ns0:ref type='bibr' target='#b20'>Itani (2015)</ns0:ref>. Stomach contents were soaked with water in a beaker over one night. Gizzard digesta was stirred then low-density floating food particles were gently disposed. This procedure was repeated until only grit was remained in the beaker. Grit smaller</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed than 0.5 mm were collected as much as possible, but removed from the analyses. Total amount was weighed, then size and shape of all grit in gizzard were analyzed using ImageJ (Fig. <ns0:ref type='figure'>S4</ns0:ref>).</ns0:p><ns0:p>The amount, size, and shape of the gizzard grit was compared among different diet and gizzard muscularity groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Excreted grit</ns0:head><ns0:p>Excreted grit was separated from fecal particles using the same method as separating gizzard grit. Grit smaller than 0.5 mm were collected as much as possible, but removed from the analyses. Total amount is weighed and size and shape of all excreted grit were analyzed using ImageJ (Fig. <ns0:ref type='figure'>S5</ns0:ref>). The amount, size, and shape of the excreted grit was evaluated and compared with those of the gizzard grit to test selection upon excretion. Grit characteristics were also compared among different diet and gizzard muscularity groups. Since excreted grit were collected only on the last day of the experiment, and since they were collected per group instead of per individual, amount and size of excreted grit per individual are unavailable in present study.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>All statistical analyses were conducted using software R (R Core Team, 2019). Since multiple datasets do not have normal distribution, non-parametric analyses were conducted.</ns0:p><ns0:p>Ordinal logistic regressions were conducted as non-parametric equivalent of two-way ANOVA to test effects of gizzard muscularity, diet, and their interactions for body mass, gizzard mass, and grit features (size, amount, and shape), using R package MASS (Venables &amp; Ripley, 2013).</ns0:p><ns0:p>Steel-Dwass method was used for post-hoc tests. Correlations between shape indexes of grit in gizzard and gizzard muscularity at the end of the experiment are tested using Spearman's rank</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed correlation. Grit amount is corrected by chick body mass and grit size is corrected by cubic root of chick body mass upon analyses. Chicks, euthanized prior to the end of the experiment following the Hokkaido University rules, were excluded from the analyses. The data analyzed are provided as Supplemental Information (Data S1-S6).</ns0:p></ns0:div> <ns0:div><ns0:head>RESULTS</ns0:head><ns0:p>During the experiment, two chicks from non-herbivorous, muscular gizzard group (nH-M), one chick from the non-herbivorous, less-muscular gizzard group (nH-lM), five chicks from the herbivorous, muscular gizzard group (H-M), and two chicks from the herbivorous, lessmuscular gizzard group (H-lM) were euthanized due to sudden drop of body mass, following the Hokkaido University regulations before the end of the experiment. Therefore, all of the analyses were performed on total of 58 chicks.</ns0:p><ns0:p>The average body mass of the chicks at the end of the experiment were affected by both diet and initial gizzard muscularity, as well as their interaction (Table <ns0:ref type='table'>S1</ns0:ref>). Body mass were higher in the non-herbivorous groups than in the herbivorous groups (nH-M &gt; H-M, nH-lM &gt; H-lM; Fig. <ns0:ref type='figure'>2</ns0:ref>, Table <ns0:ref type='table'>1</ns0:ref>, Table <ns0:ref type='table' target='#tab_4'>S2</ns0:ref>). This difference in body mass was significant only between the groups with high initial gizzard muscularity. Average gizzard muscularity at the end of the experiment was affected by diet and initial gizzard muscularity (Table <ns0:ref type='table'>S1</ns0:ref>). The average gizzard muscularity was significantly higher in herbivorous groups than in non-herbivorous groups (H-M &gt; nH-M, H-lM &gt; nH-lM; Fig. <ns0:ref type='figure'>2B</ns0:ref>, Table <ns0:ref type='table' target='#tab_4'>S2</ns0:ref>). While the differences in initial gizzard muscularity were maintained significant in between the herbivorous groups at the end of the experiment (H-M &gt; H-lM), the differences were insignificant in between the non-herbivorous groups (nH-M and nH-lM). The result is likely to reflect a rapid change in gizzard muscularity associated with diet change.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Grit amount</ns0:head><ns0:p>The experiment demonstrated that amount of ingested grit per chick were approximately 3 g in average (1.7% of body mass), whereas the amount of grit in gizzard were approximately 1 g in average (0.5 % of body mass), suggesting more than half of the ingested stones were excreted during the experiment (Table <ns0:ref type='table'>1</ns0:ref>). Amount of the excreted grit on the last day of the experiment was 2.52 g in total (0.045 g per chick in average). Diet affected the average amount of ingested grit and grit in gizzard, both in total and relative to the body mass (Table <ns0:ref type='table'>S1</ns0:ref>). The post-hoc tests show that herbivorous groups ingested significantly more grit relative to their body mass (H-M &gt; nH-M, H-lM &gt; nH-lM; Fig. <ns0:ref type='figure'>2</ns0:ref>, Table <ns0:ref type='table' target='#tab_4'>S2</ns0:ref>). Amount of grit in gizzard relative to body mass were also greater in herbivorous groups (H-M &gt; nH-M, H-lM &gt; nH-lM; Table <ns0:ref type='table' target='#tab_4'>S2</ns0:ref>, Fig. <ns0:ref type='figure'>2</ns0:ref>). No significant difference in amount of ingested grit and grit in gizzard was detected by difference in initial gizzard muscularity. Amount of excreted grit at the last day of the experiment were larger in non-herbivorous groups than in herbivorous groups in total weights (nH-M: 0.83 g, H-M: 0.26 g, nH-lM: 1.34 g, H-lM: 0.09 g).</ns0:p></ns0:div> <ns0:div><ns0:head>Grit size</ns0:head><ns0:p>Large grit (&gt;2.8 mm) were generally ingested more than smaller grit (Fig. <ns0:ref type='figure'>3</ns0:ref>, Table <ns0:ref type='table'>S3</ns0:ref>).</ns0:p><ns0:p>The average size of grit in gizzard was about 1.84 mm and that of the excreted grit was 1.09 mm (Table <ns0:ref type='table'>1</ns0:ref>). Diet primarily affected ingestion of grit larger than 1.4 mm (Table <ns0:ref type='table'>S4</ns0:ref>). Post-hoc tests show that the difference was significant between herbivorous and non-herbivorous groups of the less-muscular groups (H-lM &gt; nH-lM; Table <ns0:ref type='table'>S5</ns0:ref>). Diet and interaction of gizzard muscularity + diet affected size of grit in gizzard relative to body mass (Table <ns0:ref type='table'>S1</ns0:ref>). The average sizes of grit in gizzard were significantly larger in herbivorous groups (H-M &gt; nH-M, H-lM &gt; nH-lM; Manuscript to be reviewed S2). Within non-herbivorous groups, the less-muscular gizzard group contained larger grit in gizzard in respect to their body mass than the muscular gizzard group (nH-lM &gt; nH-M; Table <ns0:ref type='table' target='#tab_4'>S2</ns0:ref>). Average size of excreted grit is affected by diet and interaction of diet + gizzard muscularity (Table <ns0:ref type='table'>S1</ns0:ref>). Excreted grit is larger in non-herbivorous group than in herbivorous group within less initial gizzard muscularity group (nH-lM &gt; H-lM; Table <ns0:ref type='table' target='#tab_4'>S2</ns0:ref>), as well as in non-herbivorous, less-muscular group than in non-herbivorous, muscular group (nH-lM &gt; nH-M, Table <ns0:ref type='table' target='#tab_4'>S2</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>Grit shape</ns0:head><ns0:p>Circularity, roundness, and solidity of the uningested grit were higher than those of the offered grit (Fig. <ns0:ref type='figure'>4A</ns0:ref>, Table <ns0:ref type='table' target='#tab_3'>2</ns0:ref>), suggesting that ingested grit had low circularity, roundness, and solidity. This trend is generally significant in circularity and solidity for grit larger than 1.4 mm (Table <ns0:ref type='table'>S6</ns0:ref>). Grit in gizzard have higher circularity, roundness, and solidity than those of offered and uningested grit (Table <ns0:ref type='table' target='#tab_3'>2</ns0:ref>). This trend is significant in circularity and solidity for all size classes and is generally significant in solidity for herbivorous groups (Table <ns0:ref type='table'>S7</ns0:ref>). Circularity and solidity of excreted grit was larger than those of grit in gizzard (Table <ns0:ref type='table' target='#tab_3'>2</ns0:ref>), although the trend is significant only in solidity (Table <ns0:ref type='table'>S8</ns0:ref>). The shape indexes of excreted grit was higher than those of the offered grit (significant in circularity and roundness; Table <ns0:ref type='table'>S8</ns0:ref>).</ns0:p><ns0:p>Neither diet and gizzard muscularity strongly affected shape indexes of the uningested grit (Table <ns0:ref type='table'>S9</ns0:ref>, S10). Diet and gizzard muscularity affect circularity of the grit in gizzard of nearly all size classes, while diet, gizzard muscularity, and their interaction affect solidity of grit in gizzard (Fig. <ns0:ref type='figure'>4B</ns0:ref>, Table <ns0:ref type='table'>S11</ns0:ref>). On the other hand, roundness of grit in gizzard is affected only by diet in size classes 1.0 -2.0 mm. Post-hoc tests show that grit in gizzard of herbivorous groups was significantly high in circularity and solidity for most size classes (H-M &gt; nH-M, H-lM &gt; nH-lM; Fig. <ns0:ref type='figure'>4B</ns0:ref>, Table <ns0:ref type='table' target='#tab_4'>S12</ns0:ref>). Circularity and solidity of grit in gizzard were also higher in Manuscript to be reviewed herbivorous, muscular gizzard group than in the herbivorous, less-muscular gizzard group (H-M &gt; H-lM; Table <ns0:ref type='table' target='#tab_4'>S12</ns0:ref>). Circularity, roundness, and solidity were correlated with gizzard muscularity at the end of the experiment (p &lt; 0.05). Solidity of excreted grit is inferred to be affected by diet and interaction of gizzard muscularity and diet (Table <ns0:ref type='table'>S13</ns0:ref>), although the difference was undetected in post-hoc tests (Table <ns0:ref type='table'>S14</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>DISCUSSION</ns0:head></ns0:div> <ns0:div><ns0:head>Grit amount</ns0:head><ns0:p>The larger amounts of ingested grit and grit in gizzard in herbivorous groups (H-lM &gt; nH-lM; Fig. <ns0:ref type='figure'>2</ns0:ref>, Tables <ns0:ref type='table' target='#tab_4'>S2, S3</ns0:ref>) were concordant with previous studies (comprehensive review done in <ns0:ref type='bibr' target='#b15'>Gionfriddo and Best, 1999)</ns0:ref>. The larger amounts of excreted grit in non-herbivorous groups (nH-M &gt; H-M, nH-lM &gt; H-lM) suggests that the large amounts of grit in gizzard in herbivorous groups were affected by both large amount of grit ingestions and limited grit excretions. Retaining larger amount of grit in gizzard is likely to benefit herbivorous groups to supply higher digestion ability for breaking down tough grass fibers, since larger amount of grit in gizzard improves digestive performance in domestic chickens <ns0:ref type='bibr' target='#b1'>(Bale-Therik et al., 2012)</ns0:ref> as long as the amount is not excessive <ns0:ref type='bibr'>(Moore, 1998b)</ns0:ref>.</ns0:p><ns0:p>From the amount of ingested grit and grit in gizzard, total amount of the excreted grit can be calculated as 20.99 g, 30.46 g, 17.58 g, and 53.22 g in groups nH-M, H-M, nH-lM, and H-lM, respectively. These are much more than the expected amount of grit excreted, assuming that amounts of the excreted grit were same every day as the last day of the experiment.</ns0:p><ns0:p>Reasonable explanations are that the chicks excreted much more stones on other days, and that large amounts of excreted grit were less than 0.5 mm in size therefore undetected. While both are likely, the latter suggest that up to 20.36 g, 28.64 g, 8.20 g, and 47.42 g of grit in groups nH-M, PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed H-M, nH-lM, and H-lM, respectively, were abraded to less than 0.5 mm. The larger amount of lost grit in herbivorous groups (H-M &gt; nH-M, H-lM &gt; nH-lM) may reflect rigorous grit use in the herbivorous groups, although a more specific experiment with specific records on amount of excreted grit is mandatory to make any further assumptions.</ns0:p></ns0:div> <ns0:div><ns0:head>Grit size</ns0:head><ns0:p>Since the size of grit in gizzard is unlikely to affect digestion efficiency in domestic chickens <ns0:ref type='bibr'>(Smith, 1960)</ns0:ref>, or larger grit may even have lower digestion efficiency (Moore, 1998c), selective ingestion of large grit in all groups (Table <ns0:ref type='table'>S3</ns0:ref>) may simply be due to ease to pick large grit. The smaller size of excreted grit than grit in gizzard (Table <ns0:ref type='table'>S8</ns0:ref>) in all groups suggest that size is one of the primary factors that determine which grit to be excreted in domestic chickens.</ns0:p><ns0:p>While the excretion of small grit is concordant with a trend in domestic chicken <ns0:ref type='bibr'>(Smith, 1960)</ns0:ref>, it is controversial with this trend in house sparrow <ns0:ref type='bibr' target='#b13'>(Gionfriddo &amp; Best, 1995)</ns0:ref>. Therefore, the responses in size of excreted grit may vary taxonomically. The larger sizes of ingested grit and grit in gizzard of herbivorous groups (Fig. <ns0:ref type='figure'>3</ns0:ref>, Tables <ns0:ref type='table' target='#tab_4'>1, S2</ns0:ref>, S5) were concordant with previous works <ns0:ref type='bibr' target='#b15'>(Gionfriddo &amp; Best, 1999;</ns0:ref><ns0:ref type='bibr' target='#b19'>Hoskin et al., 1970;</ns0:ref><ns0:ref type='bibr' target='#b22'>May &amp; Braun, 1973;</ns0:ref><ns0:ref type='bibr'>Norris et al., 1975;</ns0:ref><ns0:ref type='bibr'>Soler et al., 1993;</ns0:ref><ns0:ref type='bibr'>Thomas et al., 1977)</ns0:ref>. The large size of excreted grit in non-herbivorous, lessmuscular gizzard group (nH-lM &gt; H-lM, nH-lM &gt; nH-M; Table <ns0:ref type='table'>1</ns0:ref>) suggests that this group had low ability to retain grit in gizzard, which is concordant with large amount of excreted grit from the group.</ns0:p></ns0:div> <ns0:div><ns0:head>Grit shape and abrasions</ns0:head><ns0:p>Ingested grit being sharp (having higher shape indexes) than offered grit (Fig. <ns0:ref type='figure'>4A</ns0:ref>, Table <ns0:ref type='table'>S6</ns0:ref>) is consistent with previous knowledge in domestic chickens <ns0:ref type='bibr'>(Smith, 1960)</ns0:ref> as well as in Manuscript to be reviewed</ns0:p><ns0:p>House Sparrows and Northern Bobwhite <ns0:ref type='bibr' target='#b4'>(Best &amp; Gionfriddo, 1994)</ns0:ref>. Since sharp grit in gizzard function as 'blades', this selection would increase digestion efficiency <ns0:ref type='bibr'>(Moore, 1998c)</ns0:ref>. The active ingestions of sharp grit in all groups were likely to be a congenital behavior unlike the amount of ingested or excreted grit which were likely to be controlled upon demands (see above). The grit in gizzard being less-sharp than the offered grit (Table <ns0:ref type='table'>S7</ns0:ref>) contradicts with selective ingestion of sharp grit. Since the excreted grit was also less-sharp than the offered grit (Table <ns0:ref type='table'>S8</ns0:ref>), it is most likely that the grit in gizzard were severely abraded inside of the gizzards upon mechanical digestion of ingesta <ns0:ref type='bibr'>(Wings &amp; Sander, 2007)</ns0:ref>. The severe grit abrasion and associated grit size reduction is concordant with large amount of lost grit (see above). Severe grit abrasion within one week contrasts with the trend in ostrich, in which requires as much as four weeks to make severe change in grit shape <ns0:ref type='bibr'>(Wings &amp; Sander, 2007)</ns0:ref>. The difference may suggest time required for grit abrasion vary taxonomically and/or by body size. The dominance of less-sharp grit in gizzard of herbivorous groups (H-M &gt; nH-M, H-lM &gt; nH-lM; Fig. <ns0:ref type='figure'>4B</ns0:ref>, Table <ns0:ref type='table' target='#tab_4'>S12</ns0:ref>), as well as in herbivorous, muscular gizzard group (H-M &gt; H-lM), strongly suggests that diet and gizzard muscularity affect the degree of abrasions on grit in gizzard. Since dietary structures largely affect gizzard muscularity in birds including domestic chickens <ns0:ref type='bibr' target='#b9'>(Dekinga et al., 2001;</ns0:ref><ns0:ref type='bibr' target='#b18'>Hetland et al., 2003;</ns0:ref><ns0:ref type='bibr'>Sacranie et al., 2012)</ns0:ref>, gizzard muscularity may be a primary factor which determines the degree of abrasion of grit in gizzard. Correlations between gizzard muscularity and shape indexes of grit in gizzard further support this assumption.</ns0:p><ns0:p>Therefore, the shapes of grit in gizzard were unlikely to reflect grit selection patterns in domestic chickens, in contrast to previously published concepts <ns0:ref type='bibr' target='#b3'>(Best &amp; Gionfriddo, 1991;</ns0:ref><ns0:ref type='bibr' target='#b14'>Gionfriddo &amp; Best, 1996)</ns0:ref>. Instead, our experiment suggests that the differences in shapes of grit in gizzard reflect differences in diets and gizzard muscularities, although investigations in broader taxonomic sets are essential to test the assumption.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Chick grit use behaviors</ns0:head><ns0:p>This study is the first attempt to examine whether diet and gizzard muscularity affect chicken grit use behaviors throughout ingestion, retention, and excretion. This experiment strongly suggests that chick grit use behaviors were primarily affected by a diet and secondarily by a gizzard muscularity (Fig. <ns0:ref type='figure'>5</ns0:ref>, Table <ns0:ref type='table'>1</ns0:ref>, 2). The flexible grit use upon needs of digesting tuff, coarse ingesta may be reflecting omnivorous nature of Gallus gallus domesticus and might have benefited for their shifts between herbivorous and carnivorous diets. Since numerous birds are known for omnivory and seasonal diet shifts (e.g., del <ns0:ref type='bibr' target='#b10'>Hoyo et al., 2005)</ns0:ref>, flexibility in use of grit in gizzard may not be limited to domestic chickens but might had been a key importance for wide diet range of omnivorous birds, together with the gizzard phenotypic flexibility <ns0:ref type='bibr' target='#b9'>(Dekinga et al., 2001;</ns0:ref><ns0:ref type='bibr'>Starck, 1999;</ns0:ref><ns0:ref type='bibr'>van Gils et al., 2005)</ns0:ref>. Further studies on other birds are mandatory to test the hypothesis.</ns0:p></ns0:div> <ns0:div><ns0:head>CONCLUSION</ns0:head><ns0:p>This experiment on chick grit use behaviors demonstrated that chicks had a selection on size, amount, and the shape of ingested and excreted grit. It also revealed that grit in gizzard was greatly modified through abrasion; therefore, grit did not retain their original size and shapes upon ingestion. Instead, gizzard grit shapes reflected diets and gizzard muscularities of chicks.</ns0:p><ns0:p>Ingestion of sharp grit regardless of diet and gizzard muscularity is likely to be congenial to Manuscript to be reviewed Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>chicks and facilitates better digestion efficiency. On the other hand, the ingestion and retention of larger amount of grit by herbivorous groups may be behavioral adaptation to supple digestion ability upon need of digesting coarse ingesta. The grit use flexibility might be reflecting the omnivorous nature of chickens. Grit in gizzard being less-sharp than ingested grit suggests strong PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='28,42.52,229.87,525.00,134.25' type='bitmap' /></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table PeerJ</ns0:head><ns0:label>PeerJ</ns0:label><ns0:figDesc /><ns0:table /><ns0:note>reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_2'><ns0:head /><ns0:label /><ns0:figDesc>abrasion of grit inside gizzard. Herbivorous and muscular gizzard groups having sharp grit in gizzard than non-herbivorous and less-muscular gizzard further suggest that grit abrasion is enhanced by herbivory and large gizzard muscularity.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell>Chick</ns0:cell><ns0:cell /><ns0:cell cols='2'>Grit amount</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell>Grit size</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='2'>Body mass Gizzard mass</ns0:cell><ns0:cell cols='7'>Ingested Gizzard Feces Offered Remained Gizzard Feces</ns0:cell></ns0:row><ns0:row><ns0:cell>Raw values</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>H-lM</ns0:cell><ns0:cell>182.736</ns0:cell><ns0:cell>7.531</ns0:cell><ns0:cell>4.853</ns0:cell><ns0:cell cols='2'>1.305 0.09*</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>1.884</ns0:cell><ns0:cell>0.960</ns0:cell></ns0:row><ns0:row><ns0:cell>H-M</ns0:cell><ns0:cell>153.403</ns0:cell><ns0:cell>7.863</ns0:cell><ns0:cell>3.657</ns0:cell><ns0:cell cols='2'>1.118 0.26*</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>1.743</ns0:cell><ns0:cell>0.975</ns0:cell></ns0:row><ns0:row><ns0:cell>nH-lM</ns0:cell><ns0:cell>225.163</ns0:cell><ns0:cell>6.636</ns0:cell><ns0:cell>1.879</ns0:cell><ns0:cell cols='2'>0.781 1.34*</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>2.004</ns0:cell><ns0:cell>1.273</ns0:cell></ns0:row><ns0:row><ns0:cell>nH-M</ns0:cell><ns0:cell>250.977</ns0:cell><ns0:cell>8.205</ns0:cell><ns0:cell>2.318</ns0:cell><ns0:cell cols='2'>0.919 0.83*</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>1.883</ns0:cell><ns0:cell>1.138</ns0:cell></ns0:row><ns0:row><ns0:cell>Relative to body mass</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell>H-lM</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>0.041</ns0:cell><ns0:cell>0.026</ns0:cell><ns0:cell>0.007</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>0.332</ns0:cell><ns0:cell>0.169</ns0:cell></ns0:row><ns0:row><ns0:cell>H-M</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>0.051</ns0:cell><ns0:cell>0.022</ns0:cell><ns0:cell>0.007</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>0.326</ns0:cell><ns0:cell>0.182</ns0:cell></ns0:row><ns0:row><ns0:cell>nH-lM</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>0.030</ns0:cell><ns0:cell>0.009</ns0:cell><ns0:cell>0.003</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>0.329</ns0:cell><ns0:cell>0.209</ns0:cell></ns0:row><ns0:row><ns0:cell>nH-M</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>0.033</ns0:cell><ns0:cell>0.009</ns0:cell><ns0:cell>0.003</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>NA</ns0:cell><ns0:cell>0.298</ns0:cell><ns0:cell>0.180</ns0:cell></ns0:row></ns0:table><ns0:note>*Total amount excreted on the last day of the experiment 1 PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)</ns0:note></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_4'><ns0:head>Table 2 .</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Average values of shape indexes.</ns0:figDesc><ns0:table><ns0:row><ns0:cell /><ns0:cell /><ns0:cell>Circularity</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Roundness</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell>Solidity</ns0:cell><ns0:cell /><ns0:cell /></ns0:row><ns0:row><ns0:cell /><ns0:cell cols='4'>Offered Uningested Gizzard Feces</ns0:cell><ns0:cell cols='4'>Offered Uningested Gizzard Feces</ns0:cell><ns0:cell cols='4'>Offered Uningested Gizzard Feces</ns0:cell></ns0:row><ns0:row><ns0:cell>H-lM</ns0:cell><ns0:cell>0.734</ns0:cell><ns0:cell>0.749</ns0:cell><ns0:cell>0.789</ns0:cell><ns0:cell>0.773</ns0:cell><ns0:cell>0.732</ns0:cell><ns0:cell>0.742</ns0:cell><ns0:cell>0.762</ns0:cell><ns0:cell>0.760</ns0:cell><ns0:cell>0.950</ns0:cell><ns0:cell>0.954</ns0:cell><ns0:cell>0.961</ns0:cell><ns0:cell>0.947</ns0:cell></ns0:row><ns0:row><ns0:cell>H-M</ns0:cell><ns0:cell>0.734</ns0:cell><ns0:cell>0.746</ns0:cell><ns0:cell>0.798</ns0:cell><ns0:cell>0.783</ns0:cell><ns0:cell>0.732</ns0:cell><ns0:cell>0.740</ns0:cell><ns0:cell>0.764</ns0:cell><ns0:cell>0.763</ns0:cell><ns0:cell>0.950</ns0:cell><ns0:cell>0.953</ns0:cell><ns0:cell>0.964</ns0:cell><ns0:cell>0.953</ns0:cell></ns0:row><ns0:row><ns0:cell>nH-lM</ns0:cell><ns0:cell>0.734</ns0:cell><ns0:cell>0.747</ns0:cell><ns0:cell>0.776</ns0:cell><ns0:cell>0.774</ns0:cell><ns0:cell>0.732</ns0:cell><ns0:cell>0.738</ns0:cell><ns0:cell>0.745</ns0:cell><ns0:cell>0.762</ns0:cell><ns0:cell>0.950</ns0:cell><ns0:cell>0.954</ns0:cell><ns0:cell>0.959</ns0:cell><ns0:cell>0.953</ns0:cell></ns0:row><ns0:row><ns0:cell>nH-M</ns0:cell><ns0:cell>0.734</ns0:cell><ns0:cell>0.752</ns0:cell><ns0:cell>0.780</ns0:cell><ns0:cell>0.777</ns0:cell><ns0:cell>0.732</ns0:cell><ns0:cell>0.741</ns0:cell><ns0:cell>0.752</ns0:cell><ns0:cell>0.753</ns0:cell><ns0:cell>0.950</ns0:cell><ns0:cell>0.955</ns0:cell><ns0:cell>0.954</ns0:cell><ns0:cell>0.951</ns0:cell></ns0:row><ns0:row><ns0:cell>1</ns0:cell><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /><ns0:cell /></ns0:row></ns0:table><ns0:note>PeerJ reviewing PDF | (2020:03:46973:1:0:NEW 10 Jul 2020)Manuscript to be reviewed</ns0:note></ns0:figure> </ns0:body> "

"Okayama University of Science Ridaicho Kitaku Okayama 700-0005 Japan Tel: 81-80-3833-9083 [email protected] July 10, 2020 Dear Editors We thank the reviewers for their generous comments on the manuscript. We edited the manuscript to address their concerns. In particular, details of the experiments such as information of grit and feed, methods for grit collection and character evaluation, and statistical analyses are added to the manuscript. Visual presentation of data is improved by additional figures in the main article and the supplements. Summative data of the experiment is organized as tables for general comparisons and all of the statistic results are provided as supplementary tables. The language is revised throughout the manuscript. We believe that the manuscript is now suitable for publication in PeerJ. Dr. Ryuji Takasaki Postdoctoral researcher On behalf of all authors. Reviewer 1 (Oliver Wings) Basic reporting New literature on gastroliths and grit use in birds is rare and every new paper is a very welcomed addition to our yet limited understanding of this matter. The manuscript by Takasaki & Kobayashi reports a very interesting but relatively short-termed experiment with grit use in chicken, focusing on gastroliths development depended on diet and muscularity of the gizzard. I found the language of the manuscript sometimes cumbersome. For example, the presentation of results in the abstract could be shorter and written more clearly, with a focus on just the significant results. Response: Language is revised throughout the manuscript. Results of the abstract are reorganized. There are three major problems I have with the manuscript as it stands: 1) there is virtually no detailed information about the grit used in this study (except its shape) 2) these is not enough relevant literature regarding grit use in domestic chicken cited and discussed 3) the visual presentation of data is poor, it could be very much improved with more easily accessible figures and diagrams Response: We appreciate the suggestions. Grit information is added in the material section. Literatures on grit use in domestic chicken are added in the introduction and discussion. Six figures (one in the main and five as supplement) are added. If these issues are remedied, the paper would be a valuable addition to research on bird digestion, gizzards, and gastroliths. Experimental design My main issue is with the short duration of the experiment and the validity of its results. See detailed comments below. Response: We consider the duration is appropriate for this experiment. Please check response to the detailed comments below. As for the animal usage: I consider the chicken experiments necessary and ethical, the necessary approval statements have been provided. Validity of the findings See detailed comments below. Comments for the Author Here are some specific comments referring to the line of the manuscript: 14 – To my knowledge there is no plural for grit (the term always incorporates several small stones). “Grits” is a term rather used for groats. Response: Thank you for pointing out. We deleted “s” out from all “grits”. 20 – there are well-established and well-defined terms for clast shapes in the geological literature. what do you mean by solidity? hardness? Response: Circularity, roundness, and solidity of the grit are defined following software ImageJ (Schneider et al., 2012): Circularity = 4π*area/perimeter2 Roundness = 4π*area/(π*major_axis2) Solidity = area/convex_area Added its citation in the method section. 22 – larger than what? are these changes significant? Response: We meant larger than offered grit, and the changes are significant. Modified the sentence for clarification. 39/40 – after reading the complete manuscript, I am not sure you can make such a statement because your experiment with grit only lasted a week! Response: We are aware that degree of ostrich grit abrasion is small in a week, but we consider a week is enough for domestic chickens, at least under the condition this experiment was conducted. The chicks were excreting grit rigorously: while about 180g of stones are ingested in total, only about 60g in total are retained in gizzards at the end of the experiment (Data S1, S4), suggesting that two-third of the ingested grit are excreted within a week. Therefore, longer experiment duration would only increase amounts of grit ingested/excreted and is unlikely to significantly affect shapes of the grits inside gizzard. Difference in the duration required for grit abrasion between domestic chickens and ostrich are likely to be caused by taxonomic and/or body size differences. Additionally, even if a week is too short to make shape differences, that would increase risk of false negative detection and the experiment nonetheless demonstrates shape differences by diet and gizzard muscularity. Comparison with ostrich is added to the discussion section of the manuscript. 51 – perhaps mention the other relevant functions of grit (reviewed in: Wings O. A review of gastrolith function with implications for fossil vertebrates and a revised classification. Acta Palaeontologica Polonica. 2007;52(1):1-16.) Response: Added following statement at the beginning of the last sentence of the paragraph: “Although multiple non-digestive functions such as parasite destruction, relief of hunger, and ballast have been proposed for grit use in vertebrates (Wings, 2007),” 83 – I am not sure that three weeks will make such a big difference in the development of (or lack of) gizzard muscles. Please explain why you did not choose a longer period for this experiment? Anyhow, there often is a high plasticity of gizzard muscles in birds. Response: As pointed out, bird gizzard muscles have extreme phenotypic plasticity. Amerah et al. (2007) demonstrated that three weeks of diet difference would make big gizzard muscularity difference using broilers. In fact, our preliminary experiment (conducted under the same ethical permission) also suggest that even two weeks may be sufficient to make gizzard muscularity difference, although this data was not included in the manuscript since sample size is too small to conduct any statistical analysis and also the experimental condition is not exactly the same with the subsequent experiment. For clarification, the following sentence is added to the method section: “The duration was determined based on Amerah et al. (2007) which demonstrated significant gizzard muscularity difference in three weeks.” 106 – What was the lithological composition of grit used? This is perhaps the most important factor for development of grit shape changes! Was it a mixture of rock types with different hardnesses? Or was it just quartz or a similarily hard rock type? Response: We agree and appreciate for pointing this out. Yes, all of the stones are commercial silicastic grains, so they are expected to have Mohs hardness 6~7. Following sentence was added to the method section: “All of the grit used in the experiment are silicastic stones.” With hard lithologies, the changes on the grit would only have been minimal after one week (see Wings & Sander 2007). Another example: if you had some limestone pieces in your grit (often incorporated in the commercially used grit for poultry), these clasts would simply dissolve in the stomach juices… Response: As explained above, hard lithology and short experimental duration are unlikely to cause significant problems in domestic chickens. what was the shape variety in initial grit? Response: The shape (circularity, roundness, and solidity) distribution of the initial grit for each size group is illustrated in Figure 4. Additionally, histograms of shape distribution for the initial (and the remained) grits are added as Fig. S3. 112 – Ok, here you define the term solidity. Please provide references for this use in the literature. Response: Modified as suggested. 170 – What was the reason that chicks had to be euthanized prematurely? Response: The sentence is modified as: “…were euthanized due to sudden drop of body mass, following the Hokkaido University regulations before the end of the experiment.” 175 – This makes me wonder if the chicks would have chosen even larger grit particles if you would have supplied them. On what basis did you choose the upper grit size limit? Response: We agree and admit the result was out of our expectation. Size range was determined based on previous studies including: Moghaddam et al. (2016), 2.0, 3.0, 4.0 mm grit for 42 days old chicks; Borg (2016), 1.0-3.5 mm grit for 32-34 days old chicks; and Garipoglu et al. (2006), 2.0 mm grit for 42 days old chicks. General comments for the results: it would be good if you could illustrate the original shape variety of your initial grit in a diagram. you could also illustrate all other grit samples (ingested, excreted, remaining) in the same way. perhaps with area diagramms? or scatter plots? this would make your main results far easier to compare and comprehend. Response: Shape distribution of initial, remaining, gizzard, and excreted grit are illustrated in histogram and provided as supplementary figures S3-S5 as suggested. Also, it would be helpful to have photographs of the different grit samples. at least in the supplements. also, I would be interested to see photographs of a typical gizzard from each group. Response: Photographs of the grit samples are provided as Fig. S2 and representatives of muscular and less-muscular gizzards are provided as Fig. S1. 259 – what do you mean with “dull? less polished? or less sharp? be specific Response: “Dull” meant grit with low circularity, roundness, and/or solidity as defined in the terminology section. Modified to “Sharp” and “less-sharp”. 261 – of course gastroliths are heavily abraded in the gizzard. this has been documented by several studies see Wings & Sander 2007 Response: Cited Wings and Sander (2007). 269 – grit abrasion is also strongly dependent on the lithology Response: All of the grit provided are quartzite therefore have equivalent hardness, as explained above. 273 – this is very strongly dependent on the duration gastroliths remain in the gizzard Response: We agree, but one week is enough in domestic chickens, as explained above. 278 – I am not sure this really is the first attempt. There is a vast number of papers about grit use in commercial chicken out there. Here are just some from my database which could be incorporated in your discussion: Balloun, S. L., and Phillips, R. E.: Grit feeding affects growth and feed utilization of chicks and egg production of laying hens, Poult. Sci., 35, 566-569, 1956. Bgatov, V. I., Motovilov, K. Y., and Speshilova, M. A.: Фyнкции пpиpoдныx минepaлoв в oбмeнныx пpoцeccax ceльcкoxoзяйcтвeннoй птицы [Functions of natural minerals in the metabolic processes of poultry], C.-x. биoлoгия [Agricultural Biology], 7, 98-102, 1987. Buckner, G. D., and Martin, J. H.: The function of grit in the gizzard of the chicken, Poult. Sci., 1, 108-113, 1922. Combs, G. F., G.L., R., and Nicholson, J. L.: Studies on the evaluation of insoluble grit for broilers, Maryland Agr. Exp. Sta. Misc.Publ., 210, 1954. Cooney, W. T.: Influence of various grits on battery-raised broilers, Station circular / Agricultural Experiment Station / Oregon State Agricultural College, 139, 1941. Curtis, M. R.: On the ability of chickens to digest small pieces of aluminum, Ann. Rept. Maine Agric. Exper. Sta. Bull, 221, 314-318, 1913. Ferber, K. E., and Brüggemann, H.: Die Zugabe von Kalksteingrit und Flintgrit zum Futter bei der Jungmast von Hähnchen, Archiv für Geflügelkunde, 7, 363-368, 1933. Heuser, G. F., and Noms, L. C.: Calcite grit and granite grit as supplements to a chick starting ration, Poult. Sci., 25, 195-198, 1946. Kaupp, B. F., and Ivey, J. E.: Digestive coefficients of poultry feeds and the rapidity of digestion and fate of grit in the fowl, North Carolina Agr. Exp. Sta. Tech. Bul., 22, 1923. Platt, C. S., and Stephenson, A. B.: The influence of commercial limestone and mica grits upon growth, feed utilization, and gizzard measurements of chicks, New Jersey Agr. Exp. Sta. Bul., 587, 1935. Rau, G. J., and Platt, C. S.: The effect of size of limestone grit particles in poultry rations, Poult. Sci., 28, 232-235, 1949. Scott, M. L., and Heuser, G. F.: The value of grit for chickens and turkeys, Journal of Poultry Science, 36, 276-283, 1957. Tepper, A. E. R., Durgin, R. C., and Botorff, C. A.: Fine versus coarse grit as a feed ingredient for poultry, New Hampshire Agr. Exp. Sta. Circ., 56, 1939. Titus, H. W., and Fritz, J. C.: The Scientific Feeding of Chickens, 5th ed., Interstate, Danville, Ill.,, 336 pp., 1971. Response: We deeply appreciate you sharing your database. Some of the papers are incorporated to the manuscript. As far as we are aware of, however, most of the papers on grit use in commercial chicken focus on economic effects. They control grit amount, size, shape, etc. to test if differences in grit characteristics affect chicken nutritional/commercial efficiency. Our work instead tests if differences in chicken diet and gizzard muscularity affect their grit use, which in future expect to be a basis for comparison widely among neornithines. Reviewer 2 (Marcus Clauss) Basic reporting The manuscript describes a very interesting experiment that is of high biological interest in my view. The language is not acceptable, and requires extensive revision, including the involvement of a professional in avian biology/nutrition in my view. I made extremely detailed language corrections in the abstract in the attached pdf, and a lot of the detailed criticism can be transferred to the whole manuscript from there. Examples are the use of plural for grit ('grits'), the use of the word 'regulation' when a word like 'response' or 'effect' would be adequate, or 'remained grit' for leftovers. Correcting the language of the whole article is beyond the scope of work a reviewer can do. Response: We appreciate your corrections. Abstract and the manuscript are corrected as suggested. The literature references are sufficient, incl. the background. I made one comment in the attached pdf on literature use in the introduction, where – in chicken – the fermentation of fibre is not the sole function of the caeca (I think fermentation of uric acid is at least also important) and using a citation on a very different species (kiwi) appears inappropriate to me. Response: Agree. A general paper on avian caeca (DeGolier et al., 1999) and a paper specifically about chicken caeca (Karasawa, 1989) are cited instead. The article structure is professional, raw data is provided (albeit in a strange way – split across many different files – there is no reason why the data cannot be provided in a single file in my view, and I would recommend/demand that). This should include both size-specific information per individual (for grit of a certain particle size range) as well as summative information of «all grit». Response: All data compiled into a single file as Data S6. Data S1-S5 are left as they are easier to use on analyses. The manuscript is self-contained with relevant results to hypotheses. Experimental design The research is original, and primary. The question is well defined, relevant and meaningful, and the knowledge gap is evident. The ethical standard is ok, and I guess the investigation methods are ok as well, but the way that the methods are worded precludes a thorough judgement. In particular, the following method issues are relevant in my view: The diets need to be described in detail, in terms of composition, and form (pelleted? meal? grain size? etc). Response: Diets prior to the experiment were either fully starter pellet or the starter pellet + 30wt% of rice hull. Diets during the experiment were either fully grass or fully dried fish to test grit use difference under extreme diet difference. Diets during the experiments are provided in meal, grinded to < 5 mm by food processor. The details are added to the manuscript as suggested. Manufacturers of the feeds are also provided. Data that is summative for an individual, such as body weight, gizzard weight, total amount of grit ingested, total amount of grit in the gizzard, total amount of grit in the faeces, should be evaluated by statistical models (either using the raw data, or transformed/ranked data as appropriate) with diet and gizzard muscle state as cofactors, incl. their interaction. This should also be done with relative measures (grit or gizzard weights in % of body mass). Response: Summative data added as suggested at the beginning of the result section. Statistic tests on amount of grit in the feces are not available in our data. Data on mean grit particle size should be calculated (this is possible, there are methods for this, e.g. in Fritz J, Streich WJ, Schwarm A, Clauss M (2012) Condensing results of wet sieving analyses into a single data: a comparison of methods for particle size description. Journal of Animal Physiology and Animal Nutrition 96:783-797. Response: Mean grit particle sizes for grit in gizzard and grit in feces are calculated based on actual measurements and added to the size section. We chose not to estimate mean grit particle sizes of the initial and remained grit using methods of Fritz et al. (2012) since the method (dMEAN) evaluate mean values by proportion in weight, whereas mean calculation for grit in gizzard and feces are done by summing up sizes of grit particles and then dividing by sample size. These are not comparable since 4 grams of small grit and 4 grams of large grit have different counts, resulting in much larger average in dMEAN. We prefer having no mean value for initial and remained grit than showing incomparable data. ideally, one single value per animal for shape measures would be calculated (using a weighted average approach), and these would be compared between ingested grit, gizzard grit and faecal grit using repeated measures (or, individual as random factor), and diet and gizzard type as covariates. Response: We agree that it would be the best if one single value per animal could be tracked for all grit features throughout the experiment. However, we don’t think weighted average approach can calculate shapes of ingested grit based on the data we have. To make it clear, we have: ・Amount of initial grit per INDIVIDUAL ・Amount of grit not ingested per INDIVIDUAL ・Shape indexes of initial grit per GROUP ・Shape indexes of grit not ingested per GROUP As far as we know, we may be able to calculate average shape indexes of the ingested grit per group by solving an equation: Si = (Wr*Sr – Wo*So)/Wi Where Si is the average shape of ingested grit, Wi is the total weight of the ingested grit, Wr and Sr are the total weight and average shape of the remained grit, and Wo and So are the total weight and the average shape of the offered grit, all within a group. To obtain average grit shape for each individual, equation would be Si*Wi = Si1*Wi1 + Si2*Wi2 + … + Sin*Win Where n is the number of the individuals and Sin and Win are the average shape and total weight of the ingested stone within an individual. To obtain Si1 … Sin, which are the one single value per animal for shape measures, we need to solve simultaneous equations, which cannot be obtained from the data we have. Therefore, to stay consistent throughout the manuscript, we prefer comparisons among groups on grit basis instead of individual basis, in terms of grit shape. Some statistical metods and results mentioned in the discussion are never explained in methods or results (see pdf). Response: Explanations added as suggested. The methods of shape need to be explained in detail, ideally with example graphs. Later, in the discussion, «sharpness» is used to describe these measures, but that is not explained in methods. It is also not clear how the measurements in ImageJ were done – how was it achieved that particles did not lie against each other, how were measurements taken (manually, algorithm)? Response: Graphical explanation of shape evaluation is added as Fig. 1B and schematic images of shape indexes are added as Fig. 1C. Term “sharp” is defined as grit with low circularity, roundness, and/or solidity and the term “less-sharp” is defined as grit with high circularity, roundness, and/or solidity. All the grits were separated from each other manually. All images were taken manually. Size and shape of the grit are evaluated using the menu command Analyze > Analyze particles of ImageJ. The explanations are added to the manuscript. Sieving was done – and the number of samples for video analysis (n=500 individual stones) was explained for the offered grit. Sieving is not mentioned for gizzard, or faeces, but I assume it was done as well? How many stones did you use for leftover grit/gizzard grit/ faeces grit – 500 per sample as well – or did you measure all particles? How were they arranged for video analysis? Response: Actually, sieving was not done for grit in gizzard and feces. The only reason we used sieving for the initial and leftover grit are that there are way too many grit to count and measure. All of the girt in gizzard and feces are analyzed using ImageJ. The stones are separated from each other manually, put on a clear plane, and lighted from beneath to obtain clear outlines. What sieving did you use – wet or dry sieving – what machine was used? Response: We used dry sieving manually. There is a general conceptual issue that influences the methods. Evidently, grit in the gizzard is not only modified in terms of shape, but it is also REDUCED IN SIZE. Hence, even if the ingested grit is never <0.5 mm, the grit in gizzard and especially faeces will definitely contain a lot of material <0.5 mm. How do you deal with this? It seems that this fraction was ignored? That is no problem in terms of methods as long as you discuss it, and the implications. For example, you could calculate the daily ingestion of grit, the daily excretion of grit, and calculate the difference (which, due to your methods, one would have to assume to represent material <0.5 mm). How much would that be? What proportion of the ingested grit would that represent? Response: Right, grit particles < 0.5 mm are ignored here, because it is virtually impossible to collect all of the stones by floating method. Therefore, we set the cut-off at 0.5 mm. Discussion on the issue is added to the manuscript. I would expect graphical representations of body mass, relative gizzard mass, grit ingestion mass, gizzard grit mass (%BM), mean particle size of ingested/gizzard/faeces grit (e.g. as column charts), i.e. not only charts that represent each individual sieve fraction. Response: Boxplots of body mass, relative gizzard mass, grit ingestion mass, gizzard grit mass, and mean particle size of gizzard grit per chick, are added as suggested. Mean particle sizes of ingested/ excreted grit are not added since sizes of ingested grit cannot be evaluated (as explained below) and sizes of excreted grit cannot be evaluated per chick from the data we have. Comparisons should not be made between gizzard/faeces and initial grit, but with ingested grit. Response: We agree it is the best to compare with ingested grit. However, size and shape of ingested grit cannot be directly evaluated since once the grit are ingested, they get abraded/excreted during the experiment. Average size/shape of ingested grit per chick cannot be calculated since remained grits are evaluated by group instead of individuals. Therefore, we compared initial and remained grit to make logical assumption on general trend of grit selection and then compared initial and gizzard/feces. Specific procedures, such as correcting for body mass or using cube root of body mass for relationship with particle size should be stated in the methods. Response: Modified as suggested. Validity of the findings The results are given without selective reporting in my view. Underlying data have been provided. In conclusions, particle size reduction in the gizzard is not mentioned. Most other conclusions are sound, but some are illogical (see pdf). Comments for the Author This is a fascinating study! Annotated manuscript Comments and responses from the annotated manuscript Abstract- no line breaks in abstracts Response: Modified as suggested. Abstract- no line break in abstract Response: Modified as suggested. Abstract- the red part does not match the results that say that grit in the gizzard is larger, not smaller, in less-muscular gizzard groups Response: We appreciate you pointing out and modified the sentence. Abstract- the word 'regulation' is a legal term that is not commonly used in biology Response: Modified to words such as “affect” and “response”. 12- generally, thelanguage should be adapted according to the corrections made on the abstract above: 'grit' should not be used in plural ('grits' is not a good word; use 'grit' or 'grit stones'). Also, the location should be expressed as 'ingested grit', 'grit in the gizzard' and 'grit excreted in the faeces', or maybe 'excreted grit', but not as 'gizzard grit' in my view - this sounds as if different organs might have different grit types, which is not the case. Response: The language adapted to the corrections on the abstract. Grit locations are now expressed as: “initial grit”, “uningested grit”, “ingested grit”, “grit in gizzard”, and “excreted grit”, as suggested. 43- this is a very general introduction. I think for a study in chicken, chicken literature should be used preferentially. Response: We re-organized and added a few statements to the first two paragraphs of introduction. Since PeerJ is a journal that widely covers biological sciences, the general explanation of avian physiology is left as the first paragraph. The second paragraph introduces previous works on chicken grit uses. Fermentation in the caeca may or may not be mainly for fibre (consider uric acid fermentation, which is also very important!). A citation on kiwi (Potter) should not be part of a chicken introduction in my view. Response: Agree. Modified as explained above. 43- The manuscript requires extensive language editing. I hate such a comment if I get it as an author, but I think in this case, it is justified. Response: We appreciate your comment, and the language is modified. Examples in this abstract: 'feeding' is the process of ingestion, and ingestion is not part of digestion, but PRECEDES digestion. Hence, digestion cannot be a part or a 'phase' of feeding. Response: In terms of “feeding” and “phase”, we follow the definition in a recently published book Feeding in Vertebrates Evolution, Morphology, Behavior, Biomechanics. Eds. Vincent Bels, Ian Q. Whishaw. 2019. https://doi.org/10.1007/978-3-030-13739-7. Chapter 4 of the book (Montuelle and Kane, 2019. Food capture in vertebrates: a complex integrative performance of the cranial and postcranial systems. DOI: 10.1007/978-3-030-13739-7_4) defines five phases of “feeding”: searching, approaching, capturing, processing, and assimilating (digestion). You do not 'experience' adaptations, you evolve or develop adaptations. I thin you do not 'acquire' an organ but 'evolve' an organ. I would not personalize 'ingesta' as something that can 'experience' something. to grind, ground, ground - not to grind, grinded, grinded Response: Modified as suggested. 50- I do not make comprehesnive comments on language from here on but trust that there will be a thorough language check before resubmission. I just mark some spots haphazardly. Please do not think that absence of marks means the language is ok. Response: Thorough language check was done as suggested. 55- I suggest to remain consistent in the word choice of 'mechanical breakdown' vs. 'mechanical digestion'. I personally do not like 'mechanical digestion' even if that might have been used in the literature, I would use 'mechanical breakdown' or 'mechanical processing'. Response: Changed to mechanical processing. 59- see comment in abstract - 'regulatory' is not a biological term in my view. Response: Modified to words such as “affect” and “response”. 65- repetition from above Response: The sentence reorganized. 68- I do not understand the logic. Without grits, it does not matter how much muscles a gizzard has - it will never achieve particle breakdown. Or is there evidence (then it should be cited) that a muscular structure without grit can actually achieve breakdown? Response: Grit is not mandatory for mechanical processing, although the efficiency is considered to decrease without grit (e.g., Fritz, 1937; Hetland et al., 2003). The sentence reworded. 85- did you check 'muscularity' by later? And was the concept confirmed? Response: Gizzard muscularity should have significant difference at the beginning of the experiment (as explained above) and the differences are maintained at the end of the experiment, especially in between the herbivorous group. The relationship between the non-herbivorous group is not significant, but the result is likely to reflect rapid change in gizzard muscularity associated with diet change, known widely in modern birds. This is now explained in the beginning of the result section and shown in Fig. 2. 91- This sentence is superfluous because it is self-evident from the previous sentence. Response: The sentence re-organized. 94- please describe already here how the diets were prepared and provided. In pelleted form (then some indication of the particle size would be good)? As whole pieces (then the size of the pieces would be good)? As 'meals' (ground how)? Response: The information added as suggested. 97- does 'separated' mean 'individual'? Response: Yes. Modified as suggested. 107- later, you say you used sieving - that should be already mentioned here in my view Response: Since sieving was done only for the offered and uningested grit, we prefer mentioning sieving in that section. Method section reorganized for clarification (“Offered grit”, “Grit in gizzard”, and “Excreted grit” sections are now subsections of “Grit characteristics” section). 109- please describe in more detail, I do not understand. Please explain how you separated the grit from the gizzard digesta and from faeces (sieving?), and how the grit was prepared for image analysis? Response: The grit was separated from the gizzard digesta and feces by referring to the method described in Itani (2015): gizzard content (feces) was soaked in a beaker, stirred, then floating low-density materials are gently disposed. This was repeated until only grit was remained in the beaker. Cited Itani (2015). 109-How did you achieve segregation of individual stones? How did you sample the material (or did you always analyse the whole sample)? Did you use ImageJ manually, or did you use algorithms? Please provide schematic pictures of high and low circularity, solidity, roundness. Response: Individual grit were segregated manually. Whole sample was analyzed for grit in gizzard and excreted grit. Analyses on ImageJ was done manually. Schematic pictures of shape indexes are provided in Fig. 1C. 124- repetition Response: Deleted the sentence. 135- did you use a wet sieving or a dry sieving procedure? are the sizes given here the linear dimensions of sieve pores? Response: Dry sieving was used. The sizes represent sizes of sieve pores. 135- did this classification correspond to measurements of 'size' using the image analysis? Response: May not match perfectly, but they do correspond to each other. 136- did you apply these sieves to the gizzard and faeces as well? Response: We applied the sieves to the offered and the uningested grit only. How did you deal with finely ground material smaller than 0.5 mm? In theory, we would expect grit to be ground to dust before leaving the gizzard ... would your method catch those grit particles, or not? Response: Our method collected grit much smaller than 0.5 mm, but the weights of the excreted grit we collected suggest this is only a part of the grit actually excreted. Therefore, we chose to ignore all grit smaller than 0.5 mm. The issue is now shortly discussed in the manuscript. 139- 'remained grit' should be replaced throughout by 'leftover' grit or 'grit not ingested' or similar. Response: Changed to “uningested grit” throughout the manuscript. 139- after how many days? Response: Sieving was done right after the experiment was finished. 141- for grit offered, you tested 500 stones of each size class. How did you do this with the leftover stones? How many per size class? Response: The same was done for the uningested grit: 500 stones of each size class. 151- no sieving? how many stones per animal? Response: No sieving. All grit was analyzed. 157- how many stones per bird? no sieving? Response: No sieving. All grit was analyzed. 161- I am not really familiar with this procedure. I would expect first a test for normality (or, later, for normality of residuals). Then, I would expect models with the dependent variable (size, shape etc.) and as cofactors gizzard status and diet and an interaction term, with post-hoc tests. Response: We largely changed statistical method. We now use non-parametric methods for all analyses therefore data does not need test for normality. Ordinal logistic regression is used as a non-parametric equivalent of two-way ANOVA, and then Steel-Dwass test as post-hoc test. The results changed slightly so the manuscript was modified accordingly. It would be easier if the procedure included 'particle size' as a single data, which could be done using e.g. the procedure of discrete means (dMEAN) from Fritz J, Streich WJ, Schwarm A, Clauss M (2012) Condensing results of wet sieving analyses into a single data: a comparison of methods for particle size description. Journal of Animal Physiology and Animal Nutrition 96:783-797 and if an average roundness, average circularity etc. per group could be calculated, so that one would not depend on the very large number of individual comparisons given as supplemental tables Response: In fact, dMean calculated by proportion in weight and mean calculated by proportion in count are not comparable as explained above. Average circularity, roundness, solidity were calculated per size classes in order to test if grit use differ by grit size. Therefore, we prefer not simplifying them. 169- what was the reason for euthanasia? Response: The sentence is modified as: “…were euthanized due to sudden drop of body mass, following the Hokkaido University regulations before the end of the experiment.” 172- first, describe body mass differences between the groups. Next, differences in absolute and relative gizzard mass. (which group was heavier, and had the relatively heavier gizzards) - the non-H groups grew distinctively faster, but the H groups had larger gizzards. Differences in relative gizzard mass were clear in both nH and H, but were more evident in H. Next, differences in absolute and relative total grit ingestion mass, grit gizzard mass, and grit excretion mass. Which group ingested more total grit, had more total grit in gizzard, and excreted more total grit? Then, in my view, it would make sense to address each of the grit aspects separately: size - how did size differ between ingested, in gizzard, excreted? ... because the readers fors the story in her/his head: a large stone becomes smaller in gizzard an is then excreted. then same for circularity, for solidity, for roundness. One always wants to first hear: how did a factor change from ingestion to gizzard to faeces, and THEN how were the different groups. Response: Result section re-organized as suggested. 176- Table S1 does not give a significant p-value for group H-lM for the last two comparisons. Response: Added “generally” as suggested. 176- I would expect, first, to get a result on the total amount of grit (in g), and only later a result split up by different size categories. Response: Modified as suggested 184- Table S1 and S2 do not give shape information Response: Result section re-organized and modified appropriately. 186- how was the size of gizzard grit compared to ingested grit of the same animals? Response: Exact size of the ingested grit cannot be evaluated as explained above. 188- this is the first time that you mention 'relative to body mass'. This needs to be mentioned in the method section. Also, The body masses of the 4 groups should be given as one of the first results. Response: Explanation added to the method section as suggested. Body masses are provided in result section as suggested. 193- this is really interesting: - first, you say that the leftover grit has higher circularity and solidity than initial grit - in other words, the ingested grit must have lower circularity and solidity tha the initial grit - here you say that the gizzard grit also has higher circularity and solidity than initial grit - which sounds as if the shape of the stones changes in the gizzard so that it resembles more the grit leftovers. This should be stated somewhere. Response: Shapes of grit are actually even less-sharp than the offered grit. Following statement is added in the result section: “Grit in gizzard have higher circularity, roundness, and solidity than those of offered and uningested grit”. A table comparing average values of shape indexes in each stage (Offered, Uningested, Gizzard, Feces) is added. 204- this is the first time you mention average size. how did you calculate it? why don't you give results for average size of ingested, gizzard, faeces? Response: Average sizes are calculated as minor axis averaged by number of grit. Average size of gizzard grit is added. Average size of ingested grit cannot be evaluated and dMEAN is not comparable to average by count (explained above) therefore we chose not to use the method. 205- how did you calculate average solidity? Response: Averages are calculated by taking average of solidity by grit number. 208- I do not see why this comparison is interesting. I would be interested to know how it compares to the INGESTED grit, but not to the initial grit. Response: As explained above, features of ingested grit cannot be evaluated therefore the best we can do is to compare with offered grit. 223- you have data on grit intake (for 7 days? I am not sure for how many days) and grit excretion (for a single day). If animals retain grit longer, then there must be some compensation at some stage: they need to excrete the same amount that they ingest, or they will burst. Now, a reasonable explanation is that grit is ground, in the gizzard, to very fine particles that you did not retain on your sieves. It would be good to state this, and speculate on how many fine material you have in faeces. Because you do not explain how you measured size in faeces (after sieving? the smallest stone size in your data is for 0.5-1 mm, which is quite large - does this mean you did not consider stones smaller than 0.5 mm? Response: Yes, we ignored grit smaller than 0.5 mm as explained above. Discussion on the issue is added. 230- the evident fact that size changes in the gizzard over time (grit is ground to smaller pieces) is somehow missing from this discussion Response: Discussion added as suggested. 240- this blue sentence contradicts the blue sentence below. which ones have the larger gizzard grit - the herbivore or the non-herbivore group? Response: Sentence modified for clarification. 243- no - this means that the herbivores have more ability to retain the LARGE grit, not the small grit Response: Sentence is deleted. 253- the fact that the shape measures are a measure for 'shaprness' should be mentioned in the methods Response: Sentence and method sections are modified. 260- why is there no comparison of ingested and gizzard grit for sharpness Response: Shapes of ingested grit cannot be evaluated as explained above. 261- yes. And this must mean that they also change in size! Response: Grit size change is also shortly discussed now. 269- these correlations should be given in the results, and explained in the methods Response: Modified as suggested. 292- the same should apply for size! grit in the gizzard will surely be reduced in size! Response: Grit size change is also shortly discussed now. Amerah, A.M., Lentle, R.G., Ravindran, V., 2007. Influence of Feed Form on Gizzard Morphology and Particle Size Spectra of Duodenal Digesta in Broiler Chickens. The Journal of Poultry Science 44, 175-181. Borg, K., 2016. The effect of gritstone supplementation on performance and digestion in broiler chickens. Norwegian University of Life Sciences, Ås. DeGolier, T.F., Mahoney, S.A., Duke, G.E., 1999. Relationships of Avian Cecal Lengths to Food Habits, Taxonomic Position, and Intestinal Lengths. The Condor 101, 622-634. Fritz, J.C., 1937. The Effect of Feeding Grit on Digestibility in the Domestic Fowl. Poult. Sci. 16, 75-79. Garipoglu, A.V., Erener, G., Ocak, N., 2006. Voluntary Intake of Insoluble Granite-grit Offered in Free Choice by Broilers: Its Effect on Their Digestive Tract Traits and Performances. Asian-Australas J Anim Sci 19, 549-553. Hetland, H., Svihus, B., Krogdahl, A., 2003. Effects of oat hulls and wood shavings on digestion in broilers and layers fed diets based on whole or ground wheat. Br. Poult. Sci. 44, 275-282. Itani, K., 2015. Eating Patterns of Broiler Chickens Fed Insoluble Grit and its Effect on Intake Variation, Retention Time, Performance and Gizzard Development, Animal and Aquacultual Sciences. Norwegian University of Life Sciences. Karasawa, Y., 1989. Ammonia production from uric acid, urea, and amino acids and its absorption from the ceca of the cockerel. J Exp Zool Suppl 3, 75-80. Moghaddam, A.A.R., Ebrahimnezhad, Y., Teli, A.-A.S., 2016. The effects of different sizes of insoluble grit on growth performance and carcass traits in broiler chickens. Journal of BioScience & Biotechnology 5, 87-91. Wings, O., 2007. A review of gastrolith function with implications for fossil vertebrates and a revised classification. Acta Palaeontol. Pol. 52. "

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"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>The gizzard is the only gastrointestinal organ for mechanical processing in birds. Many birds use grit in the gizzard to enhance mechanical processing efficiency. We conducted an experiment to test the factors that affect chicken grit use in 68 male layer chicks of Gallus gallus domesticus, which were divided into two different groups in gizzard muscularity (high and low). Within each muscularity group, two different diets were provided (herbivory and non-herbivory) to test whether diet and gizzard muscularity affect grit characteristics including amount, size, and shape (circularity, roundness, and solidity) at different stages of digestion (ingested grit, grit in gizzard, and excreted grit). All animals ingested more grit than they excreted, possibly because excreted grit was below the detection size limit of 0.5 mm of the present study. The amounts of grit ingested and remained in the gizzard were larger in herbivorous groups, but these groups excreted less grit. Larger, rougher grit was selectively ingested by all chicks, but size preferences were especially pronounced in the herbivorous groups. Grit in the gizzard tended to be larger in herbivorous groups, but the grit in excreta was smaller, whereas the size of excreted grit was larger in groups with less muscular gizzards. Grit in the gizzard was much smoother than the offered and ingested grit, especially in the herbivorous, muscular gizzard groups. Excreted grit in all groups was smoother than the offered grit. These results show that diet affects the characteristics of ingested grit, grit in the gizzard, and excreted grit, whereas gizzard muscularity affects the characteristics of grit in the gizzard and excreted grit. The use of larger sizes and amounts of grit by herbivorous groups may be a response to the needs of digesting hard, coarse materials. The recovered behavioral flexibility of grit use might reflect the omnivorous nature of Gallus gallus domesticus and may aid smooth dietary shifts. The results also show that the shape of grit remaining in the gizzard does not reflect the initial shape of ingested grit, in contrast to previously published ideas. Instead, the shape of grit in the gizzard more closely reflects the diet and gizzard muscularity of chicks.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>INTRODUCTION</ns0:head><ns0:p>Digestion, or food processing, is a key phase of animal feeding <ns0:ref type='bibr'>(Montuelle &amp; Kane, 2019)</ns0:ref>. In response to the challenges of digestion, many animal lineages have evolved complex morphological and physiological adaptations during their evolutionary history. This is particularly true of birds, which have multiple specialized gastrointestinal organs, including a crop for temporal storage of food <ns0:ref type='bibr'>(Proctor &amp; Lynch, 1993)</ns0:ref>, caeca for the conservation of water and/or nitrogen recycling <ns0:ref type='bibr'>(DeGolier et al., 1999;</ns0:ref><ns0:ref type='bibr'>Karasawa, 1989)</ns0:ref>, and a muscular gizzard for mechanical processing of ingesta <ns0:ref type='bibr'>(Moore, 1999)</ns0:ref>. In the gizzard, strong compression and translational stress mechanically processes ingesta <ns0:ref type='bibr'>(Moore, 1998a)</ns0:ref>. Large food particles are selectively retained in the gizzard until these are ground to a small size <ns0:ref type='bibr'>(Hetland et al., 2003;</ns0:ref><ns0:ref type='bibr'>Moore, 1999)</ns0:ref>. To improve the efficiency of digestion, many birds ingest and retain grit in the gizzard to break down food particles, similar to the use of teeth by non-ruminant mammals <ns0:ref type='bibr'>(Fritz et al., 2011)</ns0:ref>. Some birds even travel long distances to obtain suitable grit in cases where there are insufficient sands or gravels nearby <ns0:ref type='bibr'>(McIlhenny, 1932)</ns0:ref>. Although multiple non-digestive functions such as parasite destruction, relief of hunger, and ballast, have also been proposed for grit use in vertebrates <ns0:ref type='bibr'>(Wings, 2007)</ns0:ref>, grit use is especially common in herbivorous and granivorous birds <ns0:ref type='bibr'>(Gionfriddo &amp; Best, 1999)</ns0:ref>.</ns0:p><ns0:p>The benefits of grit use in domestic chickens have been investigated in poultry science.</ns0:p><ns0:p>While grit use is not necessary for survival, previous works generally agree that grit improve digestion efficiency of chickens, especially those fed coarse, less-nutritional food <ns0:ref type='bibr'>(Fritz, 1937;</ns0:ref><ns0:ref type='bibr'>Hetland et al., 2003;</ns0:ref><ns0:ref type='bibr'>Smith &amp; MacIntyre, 1959)</ns0:ref>. Additionally, previous works have attempted to identify the best forms and sizes of limestone grit for maximizing egg productivity and quality in layer hens (e.g., <ns0:ref type='bibr'>Guinotte &amp; Nys, 1991;</ns0:ref><ns0:ref type='bibr'>Sk&#345;ivan et al., 2016)</ns0:ref>. Multiple studies have also investigated how different grit characteristics (e.g., size, amount, shape) improve Manuscript to be reviewed nutritional/commercial efficiency in domestic chickens (e.g., <ns0:ref type='bibr' target='#b2'>Balloun &amp; Phillips, 1956;</ns0:ref><ns0:ref type='bibr'>Cooney, 1941)</ns0:ref>. On the other hand, factors that affect grit use behavior are less well understood. This is partly because previous studies are based primarily on grit collected from gizzards (e.g., <ns0:ref type='bibr' target='#b3'>Best &amp; Gionfriddo, 1991;</ns0:ref><ns0:ref type='bibr'>Gionfriddo &amp; Best, 1996)</ns0:ref>, even though initial grit characteristics can be heavily modified through abrasion in the gizzard <ns0:ref type='bibr' target='#b5'>(Buckner et al., 1926;</ns0:ref><ns0:ref type='bibr'>Wings &amp; Sander, 2007)</ns0:ref>.</ns0:p><ns0:p>Here we test whether differences in diet and gizzard muscularity affect the amount, size, and shape of grit at various stages of digestion. This provides insights into how domestic chicks change grit use behaviour in response to dietary demands.</ns0:p></ns0:div> <ns0:div><ns0:head>MATERIALS AND METHODS</ns0:head></ns0:div> <ns0:div><ns0:head>Ethics statement:</ns0:head><ns0:p>The experiment in this study was approved by Hokkaido University (Permission number: 16-0023) in Sapporo, Japan, and followed the rules specified in the Hokkaido University manual for implementing animal experimentation.</ns0:p></ns0:div> <ns0:div><ns0:head>Experimental design and managements</ns0:head><ns0:p>A total of 68 one-day-old male layer chicks (Gallus gallus domesticus), purchased from a local feed manufacturer, were used in this experiment. This sample size was set based on Hokkaido University regulations, space availability, and several prior experiments conducted on domestic chickens <ns0:ref type='bibr'>(Hetland et al., 2003;</ns0:ref><ns0:ref type='bibr'>Van der Meulen et al., 2008)</ns0:ref>. Prior to the experiment, the chicks were raised for three weeks to produce two groups of differing gizzard muscularity (evaluated as the relative weight of a gizzard to the body mass of the chick). This interval was determined based on the study of <ns0:ref type='bibr' target='#b0'>Amerah et al. (2007)</ns0:ref>, which demonstrated a significant difference in gizzard muscularity at three weeks. For three weeks, all chicks were fed a commercial starter pellet (Yamaichi Shiryo Co. Ltd.). Muscular development of the gizzard (Fig. Manuscript to be reviewed fed either 100% grass or 100% fish to test the effect of diet on grit use under extreme dietary differences. Grass and dried fish were ground to &lt; 5 mm and provided as meal.</ns0:p><ns0:p>During the experiment, all chicks were raised in individual cages with a wire mesh floor. Room temperature was maintained between 28-30 &#176;C. Lighting was controlled to provide a 12-hour light/dark cycle. All of the chicks were given ad libitum access to a total of 24 grams of grit per chick, which was provided separately from the feed. Feces were collected on the last day of the experiment to evaluate the characteristics of excreted grit. All chicks were weighed and then euthanized by cervical dislocation at the end of the experiment, following Hokkaido University regulations. The gizzard was removed from each of the carcasses and weighed after removing stomach contents.</ns0:p></ns0:div> <ns0:div><ns0:head>Terminology</ns0:head><ns0:p>We use the term offered grit to refer to all of the stones which were given with ad Manuscript to be reviewed libitum access to the chicks (Fig. <ns0:ref type='figure'>1A</ns0:ref>). Uningested grit refers to the grains that were not ingested by the chicks from the offered grit by the end of the experiment (i.e. the remainder of the offered grit). Ingested grit refers to the grains that were selected and swallowed by the chicks from the offered grit during the experiment; this was measured as the difference between the offered and the uningested grit fractions. Grit in the gizzard refers to the particles remaining in the gizzards of the chicks after euthanasia. Excreted grit refers to the particles excreted with the feces on the last day of the experiment. Initial gizzard muscularity refers to the gizzard muscularity of chicks at the start of the experiment. 'Rough' is used to describe grit with relatively low circularity, roundness, and/or solidity, and 'smooth' is used to describe grit with relatively high shape index.</ns0:p></ns0:div> <ns0:div><ns0:head>Grit characteristics</ns0:head><ns0:p>All of the grit grains used in the experiment were commercial quartzite stones. The amount, size, and shape of grit at different stages of digestion (i.e. offered grit, uningested grit, grit in the gizzard, and excreted grit) were evaluated. The amount of grit was weighed in grams.</ns0:p><ns0:p>Size and shape were evaluated quantitatively in ImageJ using the menu command Analyze &gt; Analyze Particles <ns0:ref type='bibr'>(Schneider et al., 2012)</ns0:ref>. To obtain the images for these analyses, grains were manually separated and backlit to obtain clear outlines (Fig. <ns0:ref type='figure'>1B</ns0:ref>, Fig. <ns0:ref type='figure'>2</ns0:ref>). All images were taken manually. The minor axis of a particle was used to measure grit size (in millimeters), and the minimum size threshold for collection was 0.5 mm (i.e., grit particles &lt; 0.5 mm were not retrieved). Circularity, roundness, and solidity were employed as grit shape indices <ns0:ref type='bibr'>(Schneider et al., 2012)</ns0:ref>. Circularity was calculated as four times the product of &#960; and area, divided by the square of the perimeter. Roundness was taken from the inverse of the aspect ratio. Solidity was calculated as the area of a grain divided by the area of the convex hull (Fig. <ns0:ref type='figure'>1C</ns0:ref>). The quantitative grit shape evaluation methods used here are not direct equivalents of the qualitative grit shape Manuscript to be reviewed evaluation proposed by <ns0:ref type='bibr' target='#b3'>Best &amp; Gionfriddo (1991)</ns0:ref>. For example, the quantitative methods are less powerful in detecting corner sharpness, whereas the qualitative methods do not take aspect ratio into account. Despite the differences, both methods adequately evaluate grit shape and this study adopts the quantitative method for scientific objectivity.</ns0:p></ns0:div> <ns0:div><ns0:head>Offered grit</ns0:head><ns0:p>The amount, size, and shape of ingested grit were inferred by comparing the characteristics of offered and uningested grit. These measurements were performed on a groupby-group basis. To test grit size preference of the chicks, the size distribution of offered grit was controlled in advance. Grit was classified into six different size classes by dry sieving using mesh sieves (Sanpo Corp.; 0.5-1.0 mm, 1.0-1.4 mm, 1.4-1.7 mm, 1.7-2.0 mm, 2.0-2.8 mm, 2.8-3.35 mm). Four grams of grit from each size class were supplied in the mixture. Before the experiment, minor axis, circularity, roundness, and solidity of 500 randomly chosen grit from each grit size class were evaluated using ImageJ (Fig. <ns0:ref type='figure'>S2</ns0:ref>). After the experiment, uningested grit was collected and sieved again into the six size classes. Five-hundred uningested grit were randomly sampled from each size classes and their size and shape indices were evaluated (Fig. <ns0:ref type='figure'>S2</ns0:ref>). Because the weight of the 500 randomly-selected grit of each size category was not determined, the total number of grit per size class could not be reconstructed, and therefore the average particle size of offered and uningested grit is unavailable. To test size preferences, the amount of ingested grit in each size class was measured as the difference between the weights of the uningested grit and the weights of the offered grit, by size class (4 grams each). Average shape indices of the uningested grit were compared to those of the offered grit to test if there was any shape preference in the ingested grit. The amounts, sizes, and shapes of the uningested grit were then compared among different dietary and gizzard muscularity groups.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p></ns0:div> <ns0:div><ns0:head>Grit in the gizzard</ns0:head><ns0:p>Grit in the gizzard was separated from other stomach contents using a flotation method (decantation) modified from Itani (2015). Stomach contents were soaked in water in a beaker overnight. Gizzard digesta was stirred and then low-density floating food particles were gently discarded. This procedure was repeated until only grit remained in the beaker. Grit smaller than 0.5 mm were collected if possible, but were removed from the analyses. The total amount of grit was weighed, and then the size and shape of all grit particles in the gizzard were analyzed using ImageJ (Fig. <ns0:ref type='figure'>S2</ns0:ref>). The amounts, sizes, and shapes of the gizzard grit were compared among different dietary and gizzard muscularity groups.</ns0:p></ns0:div> <ns0:div><ns0:head>Excreted grit</ns0:head><ns0:p>Excreted grit was collected and evaluated on a group basis. Grit particles were separated from fecal particles using the same decantation method as for separating gizzard grit. Grit smaller than 0.5 mm were collected if possible, but were removed from the analyses. The total amount of grit was weighed and the sizes and shapes of all excreted grit were analyzed using ImageJ (Fig. <ns0:ref type='figure'>S2</ns0:ref>). The amounts, sizes, and shapes of the excreted grit were evaluated and compared with those of the gizzard grit. Grit characteristics were also compared among different diet and gizzard muscularity groups. Because excreted grit was only collected on the last day of the experiment, and because it was collected per group instead of per individual, the amount and size of excreted grit per individual is unavailable in the present study.</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analyses</ns0:head><ns0:p>All statistical analyses were conducted using R software package (R Core Team, 2019). Manuscript to be reviewed</ns0:p><ns0:p>Because some of the datasets did not have a normal distribution, non-parametric analyses were conducted throughout. Ordinal logistic regressions were conducted as a non-parametric equivalent of two-way ANOVA to test the effects of gizzard muscularity, diet, and their interactions for body mass, gizzard mass, and grit features (size, amount, and shape), using the R package MASS <ns0:ref type='bibr'>(Venables &amp; Ripley, 2013)</ns0:ref>. The Steel-Dwass method was used for post-hoc tests. Correlations between shape indices of gizzard grit and gizzard muscularity at the end of the experiment were tested using Spearman's rank correlation. Grit amount was corrected using chick body mass and grit size was corrected using the cubic root of chick body mass in the analyses. Average chick body mass and grit amount were compared on an individual basis (the average of individuals per group), whereas average grit size, circularity, roundness, and solidity were compared on grit basis (the average of the grits in each group). Chicks that were euthanized before the end of the experiment following Hokkaido University regulations were excluded from the analyses. The data analyzed are provided as Supplemental Information (Data S1-S6).</ns0:p></ns0:div> <ns0:div><ns0:head>RESULTS</ns0:head><ns0:p>During the experiment, two chicks from the non-herbivorous, muscular gizzard group (nH-M), one chick from the non-herbivorous, less-muscular gizzard group (nH-lM), five chicks from the herbivorous, muscular gizzard group (H-M), and two chicks from the herbivorous, lessmuscular gizzard group (H-lM) were euthanized before the end of the experiment due to a sudden drop in body mass, following Hokkaido University regulations. Therefore, the analyses were performed on a total of 58 chicks.</ns0:p><ns0:p>The average body mass of the chicks at the end of the experiment was affected by both diet and initial gizzard muscularity, as well as the interaction of these factors (Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>). Body Manuscript to be reviewed masses were higher in the non-herbivorous groups than in the herbivorous groups (nH-M &gt; H-M, nH-lM &gt; H-lM; Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>, Table <ns0:ref type='table' target='#tab_3'>S2</ns0:ref>). This difference in body mass was significant only between the groups with high initial gizzard muscularity. Average gizzard muscularity at the end of the experiment was affected by diet and initial gizzard muscularity (Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>). The average gizzard muscularity was significantly higher in herbivorous groups than in non-herbivorous groups (H-M &gt; nH-M, H-lM &gt; nH-lM; Table <ns0:ref type='table' target='#tab_3'>S2</ns0:ref>). While the differences in initial gizzard muscularity remained significant between the herbivorous groups at the end of the experiment (H-M &gt; H-lM), the differences were insignificant between the non-herbivorous groups. This result is likely to reflect a rapid change in gizzard muscularity associated with diet change.</ns0:p></ns0:div> <ns0:div><ns0:head>Grit amount</ns0:head><ns0:p>The experiment demonstrated that amount of ingested grit per chick was approximately 3 g in average (1.7% of body mass), whereas the amount of grit in the gizzard was approximately 1 g in average (0.5 % of body mass), suggesting that about two-thirds of the ingested stones were excreted during the experiment (Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>). The amount of excreted grit on the last day of the experiment was 0.045 g per chick, on average. Diet affected the average amount of ingested grit and grit in the gizzard, both in total and relative to body mass (Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>). The post-hoc tests showed that herbivorous groups ingested significantly more grit relative to their body mass (H-M &gt; nH-M, H-lM &gt; nH-lM; Table <ns0:ref type='table' target='#tab_3'>S2</ns0:ref>). The amount of grit in the gizzard relative to body mass was also greater in herbivorous groups (H-M &gt; nH-M, H-lM &gt; nH-lM; Table <ns0:ref type='table' target='#tab_3'>S2</ns0:ref>). No significant difference in the amount of ingested grit and grit in the gizzard was detected between groups with differing initial gizzard muscularity. The amount of excreted grit on the last day of the experiment was larger in non-herbivorous groups than in herbivorous groups in total weights (nH-M: 0.83 g, H-M: 0.26 g, nH-lM: 1.34 g, H-lM: 0.09 g), although no statistical test is Manuscript to be reviewed available to test its significance (n = 1 per group).</ns0:p></ns0:div> <ns0:div><ns0:head>Grit size</ns0:head><ns0:p>Large grit (&gt;2.8 mm) were generally ingested more than smaller grit (Fig. <ns0:ref type='figure' target='#fig_13'>3</ns0:ref>, Table <ns0:ref type='table'>S3</ns0:ref>).</ns0:p><ns0:p>The average size of grit in the gizzard was about 1.84 mm and that of the excreted grit was 1.09 mm (Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>). Diet affected the ingestion of grit larger than 1.4 mm (Table <ns0:ref type='table'>S4</ns0:ref>). Post-hoc tests show that this difference was significant between herbivorous and non-herbivorous groups of the less-muscular gizzard group (H-lM &gt; nH-lM; Table <ns0:ref type='table'>S5</ns0:ref>). Diet and the interaction of gizzard muscularity with diet affected the average size of grit in gizzard relative to body mass (Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>). While the average absolute sizes of the grit in the gizzard were larger in non-herbivorous groups, the average sizes of grit in the gizzard relative to body mass were significantly larger in herbivorous groups (Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>, Table <ns0:ref type='table' target='#tab_3'>S2</ns0:ref>). Within non-herbivorous groups, the less-muscular gizzard group contained significantly larger grit in the gizzard relative to their body mass than the muscular gizzard group (nH-lM &gt; nH-M; Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>, Table <ns0:ref type='table' target='#tab_3'>S2</ns0:ref>). The average size of excreted grit was affected by diet and the interaction of diet and gizzard muscularity (Table <ns0:ref type='table' target='#tab_1'>S1</ns0:ref>). Within the less-muscular gizzard group, excreted grit was larger in the non-herbivorous chicks than in the herbivorous chicks (nH-lM &gt; H-lM; Table <ns0:ref type='table' target='#tab_3'>S2</ns0:ref>). Furthermore, excreted grit was larger in the non-herbivorous, less-muscular group compared to the non-herbivorous, muscular group (nH-lM &gt; nH-M, Table <ns0:ref type='table' target='#tab_3'>S2</ns0:ref>), both in absolute and corrected values.</ns0:p></ns0:div> <ns0:div><ns0:head>Grit shape</ns0:head><ns0:p>Circularity, roundness, and solidity of the uningested grit was higher than that of the offered grit (Fig. <ns0:ref type='figure'>4A</ns0:ref>, Table <ns0:ref type='table' target='#tab_3'>2</ns0:ref>), suggesting that ingested grit had low circularity, roundness, and solidity. This trend in circularity and solidity is generally significant for grit larger than 1.4 mm Manuscript to be reviewed (Table <ns0:ref type='table'>S6</ns0:ref>). Grit in the gizzard had higher circularity, roundness, and solidity than both the offered and uningested grit (Table <ns0:ref type='table' target='#tab_3'>2</ns0:ref>). This trend in circularity and solidity was significant for all size classes and the trend in roundness was generally significant for herbivorous groups (Table <ns0:ref type='table'>S7</ns0:ref>). The circularity and solidity of excreted grit were higher than those of grit in the gizzard (Table <ns0:ref type='table' target='#tab_3'>2</ns0:ref>), although this trend is only significant for solidity (Table <ns0:ref type='table'>S8</ns0:ref>). The shape indices of excreted grit were higher than those of the offered grit (generally significant for circularity and roundness; Table <ns0:ref type='table'>S8</ns0:ref>).</ns0:p><ns0:p>Neither diet nor gizzard muscularity strongly affected shape indices of the uningested grit (Table <ns0:ref type='table'>S9</ns0:ref>, S10). Diet and gizzard muscularity did affect the circularity of the grit in the gizzard of nearly all grit size classes, while diet, gizzard muscularity, and their interaction affected the solidity of grit in gizzard (Fig. <ns0:ref type='figure'>4B</ns0:ref>, Table <ns0:ref type='table' target='#tab_1'>S11</ns0:ref>). On the other hand, the roundness of grit in the gizzard was affected only by diet in size classes 1.0 -2.0 mm. Post-hoc tests show that grit in the gizzard of herbivorous groups was significantly higher in circularity and solidity for most size classes (H-M &gt; nH-M, H-lM &gt; nH-lM; Fig. <ns0:ref type='figure'>4B</ns0:ref>, Table <ns0:ref type='table' target='#tab_3'>S12</ns0:ref>). Circularity and solidity of the grit in the gizzard were also higher in the herbivorous, muscular gizzard group than in the herbivorous, less-muscular gizzard group (H-M &gt; H-lM; Table <ns0:ref type='table' target='#tab_3'>S12</ns0:ref>). Circularity, roundness, and solidity were correlated with gizzard muscularity (p &lt; 0.05). The solidity of excreted grit is inferred to be affected by diet and the interaction of gizzard muscularity and diet (Table <ns0:ref type='table' target='#tab_1'>S13</ns0:ref>), although the difference was undetected in post-hoc tests (Table <ns0:ref type='table' target='#tab_1'>S14</ns0:ref>).</ns0:p></ns0:div> <ns0:div><ns0:head>DISCUSSION</ns0:head></ns0:div> <ns0:div><ns0:head>Grit amount</ns0:head><ns0:p>The larger amounts of ingested grit and grit in the gizzard in herbivorous groups (H-lM &gt; nH-lM; Tables <ns0:ref type='table' target='#tab_3'>S2, S3</ns0:ref>) are concordant with previous studies (see a comprehensive review by Manuscript to be reviewed Gionfriddo and <ns0:ref type='bibr'>Best, 1999)</ns0:ref>. The larger amount of excreted grit in the non-herbivorous groups (nH-M &gt; H-M, nH-lM &gt; H-lM) might suggest that the large amount of grit in the gizzard in herbivorous groups was driven by higher ingestion rates of grit in combination with limited grit excretions. Retaining a larger amount of grit in the gizzard is likely to benefit herbivorous groups by helping to break down tough grass fibers, because a larger amount of grit in the gizzard improves digestive performance in domestic chickens <ns0:ref type='bibr' target='#b1'>(Bale-Therik et al., 2012)</ns0:ref>, as long as the amount is not excessive <ns0:ref type='bibr'>(Moore, 1998b)</ns0:ref>.</ns0:p><ns0:p>Assuming equivalent intake and excretion of grit, the total weight of grit theoretically excreted throughout the experiment would be 20.99 g, 30.46 g, 17.58 g, and 53.22 g in groups nH-M, H-M, nH-lM, and H-lM, respectively. However, these values are higher than the measured amounts of grit excreted. Reasonable explanations for this are that the chicks excreted more grit on days prior to fecal collection, or that a high proportion of the excreted grains were less than 0.5 mm in size and were therefore undetected. While both are likely, the latter explanation suggests that up to 20.36 g, 28.64 g, 8.20 g, and 47.42 g of grit in groups nH-M, H-M, nH-lM, and H-lM, respectively, were abraded to less than 0.5 mm. The larger amount of lost grit in herbivorous groups (H-M &gt; nH-M, H-lM &gt; nH-lM) might indicate a more thorough particle size reduction of grit due to more extensive use in the herbivorous groups. This would result in a larger fraction of the grit being excreted at sizes below the detection limit of the present study. The fact that, on average, larger grains were excreted by the non-herbivorous group with less muscular gizzards supports this latter interpretation. However, a more specific experiment with specific daily records on the amount of excreted grit would be required to make any further conclusions.</ns0:p></ns0:div> <ns0:div><ns0:head>Grit size</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>Because the size of grit in the gizzard is unlikely to affect digestion efficiency in domestic chickens <ns0:ref type='bibr'>(Smith, 1960)</ns0:ref>, and larger grit may even be associated with lower digestion efficiency (Moore, 1998c), selective ingestion of larger grit in all groups (Table <ns0:ref type='table'>S3</ns0:ref>) may simply reflect the ease of picking larger grains. The smaller size of the excreted grit than the grit in the gizzard (Table <ns0:ref type='table'>S8</ns0:ref>) in all groups suggests that size is one of the primary factors that determines which grains are to be excreted in domestic chickens. While the excretion of small grit is concordant with a trend in domestic chickens <ns0:ref type='bibr'>(Smith, 1960)</ns0:ref>, it contrasts with a trend reported in House Sparrows Passer domesticus <ns0:ref type='bibr'>(Gionfriddo &amp; Best, 1995)</ns0:ref>. Therefore, the responses in the size of excreted grit may vary taxonomically. The larger sizes of ingested grit and grit in the gizzard (relative to body mass) in herbivorous groups (Fig. <ns0:ref type='figure' target='#fig_13'>3</ns0:ref>, Tables <ns0:ref type='table' target='#tab_3'>1, S2</ns0:ref>, S5) agree with previous works (Gionfriddo <ns0:ref type='bibr'>&amp; Best, 1999;</ns0:ref><ns0:ref type='bibr'>Hoskin et al., 1970;</ns0:ref><ns0:ref type='bibr'>May &amp; Braun, 1973;</ns0:ref><ns0:ref type='bibr'>Norris et al., 1975;</ns0:ref><ns0:ref type='bibr'>Soler et al., 1993;</ns0:ref><ns0:ref type='bibr'>Thomas et al., 1977)</ns0:ref>. The large size of excreted grit in the nonherbivorous, less-muscular gizzard group (Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>) suggests that this group either could not retain grit in the gizzard or did not use the grit as extensively, thus failing to reduce its size. Both possibilities are consistent with the large amount of excreted grit measuring greater than 0.5 mm in this group.</ns0:p></ns0:div> <ns0:div><ns0:head>Grit shape and abrasions</ns0:head><ns0:p>The higher average roughness of the ingested grit (having higher shape indexes) than the offered grit (Fig. <ns0:ref type='figure'>4A</ns0:ref>, Table <ns0:ref type='table'>S6</ns0:ref>) is consistent with previous knowledge in domestic chickens <ns0:ref type='bibr'>(Smith, 1960)</ns0:ref> as well as in House Sparrows Passer domesticus and the Northern Bobwhite</ns0:p><ns0:p>Colinus virginianus <ns0:ref type='bibr' target='#b4'>(Best &amp; Gionfriddo, 1994)</ns0:ref>. <ns0:ref type='bibr'>Moore (1998c)</ns0:ref> showed that rough grit may increase comminution efficiency. Therefore, in each group, actively ingesting rough grit may reflect a congenital behavior for better digestion efficiency, although further investigation into Manuscript to be reviewed the impacts of grit shape on comminution efficiency is necessary. That the grit in the gizzard is smoother on average than the offered grit (Table <ns0:ref type='table'>S7</ns0:ref>) contrasts the selective ingestion of rougher grit. Because the excreted grit was also smoother than the offered grit (Table <ns0:ref type='table'>S8</ns0:ref>), it is most likely that the grit in the gizzard was severely abraded inside the gizzard <ns0:ref type='bibr'>(Wings &amp; Sander, 2007)</ns0:ref>. Severe grit abrasion and the associated grain size reduction are both concordant with a large amount of lost grit (see above).</ns0:p><ns0:p>The dominance of smooth grit in the gizzard of herbivorous groups, as well as in the more muscular gizzard groups (H-M &gt; nH-M, H-lM &gt; nH-lM, H-M &gt; H-lM; Fig. <ns0:ref type='figure'>4B</ns0:ref>, Table <ns0:ref type='table' target='#tab_3'>S12</ns0:ref>), strongly suggests that diet and gizzard muscularity affect the degree of abrasion of grit in the gizzard. Because dietary structures significantly affect gizzard muscularity in birds, including domestic chickens <ns0:ref type='bibr'>(Dekinga et al., 2001;</ns0:ref><ns0:ref type='bibr'>Hetland et al., 2003;</ns0:ref><ns0:ref type='bibr'>Sacranie et al., 2012)</ns0:ref>, gizzard muscularity may be a primary factor in determining the degree of abrasion of grit in the gizzard.</ns0:p><ns0:p>Correlations between gizzard muscularity and shape indices of grit in the gizzard are also consistent with this interpretation. Therefore, the shapes of particles in the gizzard are unlikely to fully reflect grit selection patterns in domestic chickens, in contrast to previously published concepts <ns0:ref type='bibr' target='#b3'>(Best &amp; Gionfriddo, 1991;</ns0:ref><ns0:ref type='bibr'>Gionfriddo &amp; Best, 1996)</ns0:ref>. Instead, our experiment suggests that the differences in the shapes of grains in the gizzard more strongly reflect differences in diets and gizzard muscularity. At the same time, however, it should be noted that in cases where birds can only access smoother stones for use as grit in natural conditions, grit might be expected to be less abraded in the gizzard and may thus more strongly reflect the original shape.</ns0:p><ns0:p>Investigations using broader taxonomic datasets based on wild birds would be expected to provide further insights.</ns0:p></ns0:div> <ns0:div><ns0:head>Chick grit use behaviors</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed</ns0:p><ns0:p>This study is the first attempt to examine whether diet and gizzard muscularity affect chicken grit use behaviors throughout ingestion, retention, and excretion. This experiment strongly suggests that, under the experimental conditions used here, grit characteristics were primarily affected by diet and secondarily by the muscularity of the gizzard (Fig. <ns0:ref type='figure' target='#fig_15'>5</ns0:ref>, Table <ns0:ref type='table' target='#tab_1'>1</ns0:ref>, 2).</ns0:p><ns0:p>The flexibility of grit use in response to the needs of digesting tough, coarse ingesta may reflect the omnivorous nature of Gallus gallus domesticus and might facilitate easy shifts between herbivorous and carnivorous diets. Because numerous other bird species are known to be omnivorous and experience seasonal diet shifts <ns0:ref type='bibr'>(e.g., del Hoyo et al., 2005)</ns0:ref>, flexibility in the use of grit in the gizzard may not be limited to domestic chickens. Rather, it might be common, and may support the wide dietary range of omnivorous birds, together with phenotypic flexibility of the gizzard <ns0:ref type='bibr'>(Dekinga et al., 2001;</ns0:ref><ns0:ref type='bibr'>Starck, 1999;</ns0:ref><ns0:ref type='bibr'>van Gils et al., 2005)</ns0:ref>. Further studies on other birds are required to test this hypothesis.</ns0:p></ns0:div> <ns0:div><ns0:head>CONCLUSION</ns0:head><ns0:p>This experiment on chick grit use behaviors demonstrated that diet and gizzard muscularity affect the size, amount, and the shape of ingested and excreted grit. It also revealed that grit in the gizzard was greatly modified through abrasion; therefore, grit did not retain its original sizes nor shapes upon ingestion. Instead, gizzard grit shapes reflected gizzard activity, as determined by chick diet and gizzard muscularity: roughest in the chicks with less-muscular gizzards on a non-herbivorous diet and smoothest in the chicks with muscular gizzards on a herbivorous diet. Selective ingestion of rough grit regardless of diet and gizzard muscularity is likely an innate selective behavior. On the other hand, the ingestion of a larger amount of grit by the herbivorous groups may be a behavioral adaptation to ensure an adequate supply of grit as it is abraded during the course of the grinding action of coarse ingesta. The flexibility of grit use by Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 2</ns0:note><ns0:p>Representatives offered grit, uningested grit, grit in the gizzard, and excreted grit.</ns0:p><ns0:p>Note that the grit shown here are only few representatives from hundreds of grit therefore Manuscript to be reviewed Manuscript to be reviewed</ns0:p><ns0:note type='other'>Figure 4</ns0:note><ns0:p>Boxplots comparing grit shapes. Manuscript to be reviewed Manuscript to be reviewed Average values of chick status, grit amount, and grit size.</ns0:p><ns0:p>Note that average sizes of offered and remained grit cannot be calculated, but assumed from the amount of stones ingested per size class. See Fig. <ns0:ref type='figure' target='#fig_13'>3</ns0:ref> and Table <ns0:ref type='table'>S3</ns0:ref> for detail.</ns0:p><ns0:p>Abbreviations: H-lM, herbivorous diet with a less-muscular gizzard; H-M, herbivorous diet with a muscular gizzard; nH-lM, non-herbivorous diet with a less-muscular gizzard; nH-M, nonherbivorous diet with a muscular gizzard.</ns0:p><ns0:p>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:p><ns0:p>Manuscript to be reviewed Manuscript to be reviewed Average values of shape indexes.</ns0:p><ns0:p>Abbreviations: H-lM, herbivorous diet with a less-muscular gizzard; H-M, herbivorous diet with a muscular gizzard; nH-lM, non-herbivorous diet with a less-muscular gizzard; nH-M, nonherbivorous diet with a muscular gizzard.</ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_10'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)Manuscript to be reviewed individuals of a different diet, which is expected to reflect gizzard activity, may reflect the omnivorous nature of chickens, and possibly facilitate their seasonal diet shifts in nature.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_11'><ns0:head /><ns0:label /><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_12'><ns0:head /><ns0:label /><ns0:figDesc>they may not reflect true size/shape distribution. Abbreviations: H-lM, herbivorous diet with a less-muscular gizzard; H-M, herbivorous diet with a muscular gizzard; nH-lM, non-herbivorous diet with a less-muscular gizzard; nH-M, non-herbivorous diet with a muscular gizzard. Scale = 50 mm. PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_13'><ns0:head>Figure 3</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_14'><ns0:head>(</ns0:head><ns0:label /><ns0:figDesc>A) Boxplots comparing shapes of the initial grits and the remained grits by each experimental group, shown per grit size categories. (B) Boxplots comparing shapes of the grit in the gizzard by the experimental groups, shown per grit size categories. The brackets represent significant differences at p &lt; 0.05. Abbreviations: H-lM, herbivorous diet with a less-muscular gizzard; H-M, herbivorous diet with a muscular gizzard; nH-lM, non-herbivorous diet with a less-muscular gizzard; nH-M, non-herbivorous diet with a muscular gizzard. PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_15'><ns0:head>Figure 5</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_16'><ns0:head>a- e</ns0:head><ns0:label>e</ns0:label><ns0:figDesc>Means within a colum sharing a common superscript differ significantly at p &lt; 0.05. PeerJ reviewing PDF | (2020:03:46973:2:0:NEW 25 Sep 2020)</ns0:figDesc></ns0:figure> <ns0:figure type='table' xml:id='tab_1'><ns0:head>Table 1 (on next page)</ns0:head><ns0:label>1</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> <ns0:figure type='table' xml:id='tab_3'><ns0:head>Table 2 (on next page)</ns0:head><ns0:label>2</ns0:label><ns0:figDesc /><ns0:table /></ns0:figure> </ns0:body> "

"Okayama University of Science Ridaicho Kitaku Okayama 700-0005 Japan Tel: 81-80-3833-9083 [email protected] September 25, 2020 Dear Editors We are grateful to the reviewers for their productive comments on the manuscript. We edited the manuscript to address their concerns. The issues pointed out by the reviewers are discussed in the manuscript. Detailed explanations are added to figure and table legends for better readability. Additionally, the manuscript is reviewed by a native English speaker and the language problems are resolved. We believe that the manuscript is now suitable for publication in PeerJ. Dr. Ryuji Takasaki Postdoctoral researcher On behalf of all authors. Reviewer 1 (Oliver Wings) Basic reporting Thank you for your revision, there definitely has been an improvement in this manuscript, however, I still think it is not ready for publication yet. Please excuse the delay, but it is holiday and field season right now and due to time constraints I was unable to look at the manuscript with the scrutiny I would have preferred. Especially, I had not the time to check on the statistics. Also, I did not find the figure captions. Response: Thank you for another review. Your comments greatly improved our manuscript. The manuscript is modified as follows, following your suggestions. I am not a native English speaker, but for me there are still many language issues which need fixing, Response: English is reviewed by a native English speaker, Dr. Greg Funston. for example in line 26: How can the ingested grit be sharper (do you mean more angular?) than the offered grit. I thought the ingested grit is part of the offered grit? Do you mean that the proportion of the grit ingested compared to all grit particles that were offered had on average a more angular outline? Response: Yes, the ingested grit are suggested to be sharper (more angular) than the offered grit in average. This is confirmed by comparing the shapes of the offered grit and the uningested grit (Fig. 4A, Tables 2, S6). Also, I would rather limit the use of the term “sharp” here since it is commonly used in connection to sharp edges on tools. Why not use the term “angular”? If you do not wish to use the established geological terminology for roundness, please explain why and at least compare your findings with the six standard categories (Very angular; Angular; Sub-angular; Sub-rounded; Rounded; Well-rounded) at least once. Response: Words “rough” and “smooth” are now used to describe grit shapes. We prefer not using the term “angular” to avoid confusion with “angular” defined in Best & Gionfriddo (1991), because the shape evaluation methods are completely different. Following your suggestion, present quantitative method is shortly compared with the qualitative method in the method section. 123: what are silicastic stones? do you mean siliciclastic? if so, do you mean that the stones were composed of siliciclastic sediments (i.e. quartz sandstone) or were they rather composed as one solid vein quartz clast? After looking at fig. S2, I assume that latter, but please be precise as this strongly affects the outcome of your experiments. Also, some clasts on S2 look like chert to me, there might even be a difference in the abrasion rate between vein quartz and chert, at least the development of polish on the surface of chert gastroliths indicate this. Response: We meant quartzite stones, so they include metamorphic chart. Thank you for pointing out. We are also aware that abrasion rate may slightly differ among the stones. However, we consider that is not a big issue, at least under this experiment, because offered grit share the same source and all chicks randomly consume stones among them. Therefore, chicks are expected to have similar proportions of easily-worn and hardly-worn stones. 210: I do not understand. 3g were ingested on average, 1g was found in the gizzard, and 2.52g were excreted? where does that additional mass of 0.52g of grit come from? Response: Sorry for confusion. Excretion of 2.52g of grit is describing the total amount of the grit excreted on the last day of the experiment. Modified the sentence for clarification. also, with “excreted grit on the last day” you mean the total excreted grit, right? or do you mean that the combined excreted grit of all chicks on only the last day had this mass? if so, why do you give that amount here when discussing average amounts? and why did you only check the excreted grit mass on the last day? Response: We did so because unlike the ingested grit and grit in gizzard, excreted grit is evaluated on a group basis. Since it causes confusions, we deleted the total amount. We checked excreted grit only on the last day because there was a limit on time and effort we can spend at one time. Taking care of 68 chicks and taking records of everything everyday is quite a lot of work so we had to chose. 272 Why did you not check the feces of at least a few chicks during the complete experiment? Response: You are right, we should have done so. However, there was a limit on the things we could do at once. 294 ability? I am not convinced, they probably just had no need to retain the grit with this diet Response: changed “had ability” to “could not”. 301 I am not sure this is entirely true. From hundreds of sets of bird gastroliths I have seen, the fast majority has rather rounded gastroliths. I think it was a rather artificial setting to allow them access to so many angular clasts. This is not what birds usually find in their natural habitats and also not the standard in bird gastroliths. I assume that rounded gastroliths also allow effective trituration of foodstuffs, not by cutting, but by squashing and grinding. Which shape is indeed more effective still needs to be demonstrated. Response: We agree that rounded grit are also effective in mechanical processing of ingesta, and we have no intention to insist that cutting is the only way to aid digestion. We also agree that effectiveness of digestion by different grit shape need to be further tests. However, we should not ignore the results of Moore (1998), which showed the possibility that sharper grit are more effective in digestion. Therefore, based on the current knowledge we have at this point, we interpreted the active consumption of sharper grit among the offered grit by the chicks may be a behavior adopted for better digestion efficiency. The manuscript is modified to incorporate the above discussions. 308-310 Well this is definitely caused by your artificially angular shape of grit particles. Virtually no depositional environment in natural habitats provides birds with such angular stones. I am sure if an ostrich would get access to similarly very angular stones as gastroliths, you would also see an identical very fast change in grit shape. For how fast even the surfaces of quartz gastroliths are altered, see https://www.researchgate.net/publication/307758683_A_simulated_bird_gastric_mill_and_its_implications_for_fossil_gastrolith_authenticity Response: We deleted the comparison with ostrich. 310-312 I highly doubt that, see above. Response: We deleted the comparison with ostrich. 319-323 I disagree, as stated above are such angular grit shapes not natural. Response: We would be happy to know why you think angular stones are non-existent in nature. We consider that angular stones are common out in the nature and that is why a number of geological papers estimate roundness of sedimentary particles using indexes such as Power’s scale of roundness. In addition, wild birds also contain similarly angular grit. We have also checked hundreds of sets of wild bird gastroliths (manuscript under prep.) and here is an example from Streptopelia orientalis. Therefore, we are quite confident that stones like our offered grit is naturally accessible to natural birds and that shapes of grit in gizzard is strongly affected by diet and gizzard muscularity. Also, less muscular gizzards are virtually non-existant in free-ranging herbivorous birds including chicken. Response: We agree that less-muscular gizzard herbivorous (or seed-eating) bird is non-existent in the wild, and that is why we conducted this experiment. Because of the experiment, we now know that effects of grit use are not always same between diet and gizzard muscularity. For that you would have needed another experimental setting, providing the chicks also access to “normal” rounded grit. Response: As we believe the stones like our “offered grit” are naturally accessible, we feel no need of another experiment with “normal” rounded grit. All you can say is that in addition to the valid conclusions of Ginofriddo & Best gastroliths shape is also dependent on diet and the strength of gizzard muscles. Response: To reflect the above discussions, following sentence is added to the manuscript: “At the same time, however, it should be noted that in cases where birds can only access smoother stones for use as grit in natural conditions, grit might be expected to be less abraded in the gizzard and may thus more strongly reflect the original shape. Investigations using broader taxonomic datasets based on wild birds would be expected to provide further insights”. Also, if you would have continued your experiment for more than a week (i.e. several months) you would surely have seen that the roundness of the gastroliths would have increased. Not all gastroliths are excreted or replaced within such a short time span. Response: We agree that longer experiment may result in less-sharp grit. However, the point of this section is that diet and gizzard muscularity affect shapes of grit in gizzard, and we don’t think this result would change by longer experiment duration. Here is a result of a very simple simulation. You can see that each group reach different levels of equilibrium within first few weeks. The simulation could be reproduced by running the following code on R. #Define variables duration <- 52 #weeks grit_number <- 1000 excretion_rate <- 2/3 #proportion excreted per week herbivore_abrasion_rate <- 0.50 carnivore_abrasion_rate <- 0.30 #Make random vector containing 'grit_number' integers randomely chosen from 1 to 5. Add abrasion rates to each number. #Note that 'shape index' here is not equivalent with that in the experiment for simplification herbivores <- carnivores <- matrix(NA, duration, grit_number) herbivores[1,] <- carnivores[1,] <- sample(1:5, grit_number, replace = T) #Update grit until reaches the duration for (i in 1:(duration - 1)) { herbivores[i+1, ] <- c(sample(herbivores[i, ], floor((grit_number*(1-excretion_rate))), replace = F), sample(1:5, ceiling((grit_number* excretion_rate)), replace = T)) + herbivore_abrasion_rate carnivores[i+1, ] <- c(sample(carnivores[i, ], floor((grit_number*(1-excretion_rate))), replace = F), sample(1:5, ceiling((grit_number* excretion_rate)), replace = T)) + carnivore_abrasion_rate } herbivores_average <- rowMeans(herbivores) carnivores_average <- rowMeans(carnivores) plot(herbivores_average, col = 'green', pch = 19, ylim = c(min(c(herbivores_average, carnivores_average)), max(c(herbivores_average, carnivores_average))), xlab = 'Weeks', ylab = 'shape index') par(new = T) plot(carnivores_average, col = 'red', pch = 19, ylim = c(min(c(herbivores_average, carnivores_average)), max(c(herbivores_average, carnivores_average))), xlab = '', ylab = '') 329 digesting tuff? Response: modified to tough. Figure S1 – Please crop the images and add a scale bar. Figure S2 -Please bring all images to the same scale. Response: Modified as suggested. Experimental design see above Validity of the findings see above References: Best LB, and Gionfriddo JP. 1991. Characterization of grit use by cornfield birds. Wilson Bulletin 103:68-82. Moore SJ. 1998. Use of an artificial gizzard to investigate the effect of grit on the breakdown of grass. Journal of Zoology 246:119-124. Reviewer 2 (Marcus Clauss) Basic reporting In my view, this is generally fine. I made some changes in the attached mmanuscript to more accurately reflect the results in my view. I also make suggestions, both in the word file and in the pdf file, for improvements to the figures. I would include Fig. S2 in the main paper, because it is a very cool and impressive figure - but irrespective of whether it is in supplement or in main document, the scale of all sub-figures needs to be the same, otherwise its effect is lost (right now, it looks as if uningested grit was larger than offered grit, due to the difference in scale). Supplementary files all need legends in the documents themselves (e.g., all excel tables lack a legend in the excel, and they need units, explanation of abbreviations etc.). Response: Thank you very much for your productive comments and suggestions. We modified the manuscript following your comments. As for Fig. S2, we put it in the supplement because the grit in the figure are just representatives --- there are larger and smaller grit than shown in the figure, and they may not reflect true size/shape distribution. We added the explanation and adjusted all scales to be the same. We added legends to all supplementary tables as suggested. Experimental design This is fine. There is one thing that is a pity - when the authors counted the 500 pieces of grit from offered or leftover grit, they could have weighed these as well so that they could have made an estimate of the total number of pieces in the offered and uningested grit, which would have allowed them to calculate mean sizes as they did for gizzard and excreted grit. In case this data is available, that should be added and done. But if it is not available, this is not a problem. I added a statement on this in the methods. Response: We agree it would be the best if we could calculate the mean sizes of the offered and the uningested grit, but the data is not available. Validity of the findings no comment Comments for the Author please see both the annotated word file (for text and comments on supplements) and the annotated pdf file (for comments on figures and tables of the main text). This was in my view a very good revision and it is a very nice paper. Thank you for heeding the previous comments so well. In my view, further review is not necessary. sincerely m clauss Response: Thank you once again for spending your time and effort to review our manuscript. Please see below for reply on comments in the annotated pdf and word files. ps: I just noted that I cannot attach the annotated word file, so I will send it via email to the corresponding author and the editor. Annotated manuscript The reviewer has also provided an annotated manuscript as part of their review: Comments from the annotated manuscript Table 1: units are missing throughout the table - add everywhere where they apply Response: Modified as suggested. Table 1: these abbreviations need to be defined in table legend or in a footnote, otherwise readers have to look through the text to understand the table Response: Modified as suggested. Table 1: please add the results of post-hoc comparisons (from Table S2) as superscript letters within columns to this table, so readers see in this table already which values differed significantly from one another Response: Modified as suggested. Table 1: 'remained' and 'feces' should get footnotes explaining tha tthe values were on a group level, not on an individual level. Values in this table on individual level (body mass, gizzard mass, amount of ingested grit, gizzard grit, feces grit (?) should be given with their standrad deviation Response: Modified as suggested Table 2: abbreviations need to be explained Response: Modified as suggested Figure 2: Figure 2 is not needed as all data are given in Table 1. Table 1 should be supplemented with the SD, however. Response: Modified as suggested. Figure 3: these abbreviations need to be explained in the figure legend Response: Modified as suggested. Figure3: please modify the figure: 1. make vertical thin lines that separate the different size classes from each other (otherwise, readers wondern why the first red column on the left and the last green column on the right are not significantly different, for example 2. add explanations about indications of significance in the figure legend 3. a unit is missing on the y-axis (gram) and on the x-axis (mm) Response: Modified as suggested. Figure 4: I do not understand the figure legend. 1. why do you use the word 'stones'? This is never done enywhere else. This is grit, right? 2. the legend does not say what (B) represents - grit in the gizzard, I think Response: Modified as suggested. Figure 4: again: 1. unit missing on x-axis (mm) 2. add thin vertical lines to separate size classes 3. explain abbreviations of the groups in the figure legend Response: Modified as suggested. Figure 5: I think your results do not justify drawing the size of grit in the non-herbivorous group so much smaller Response: Right, thank you for pointing this out. Modified as suggested Comments from the annotated word file 65-72: deleted sentences were in my view superfluous Response: Accepted the change. 90: please choose: either “mixed with”, which means that you have a pellet, and mix it with the hulls; or “included into the ingredient mix of the starter pellet” which means the hulls were included in the pellet. I do not know which is correct. Response: “mixed with” is correct. 91: or, if mixed into the pellet, “prior to inclusion in the ingredient mix” Response: “mixed with” is correct. 171: I do not understand then how, e.g. in Table S2, you can make statistical comparisons for excreted grit size between the groups if you have only n=1 value per group. Response: Sizes of the excreted grit are comparable since there are multiple excreted grit per group, even though which chick excreted which grit. On the other hand, statistical comparison is not possible on weights of excreted grit (so we did not do that). 194: The table requires a Legend on top. Please also give indication of the direction of the effect (positive or negative). It must be indicated in the table legend that what you see in the table are p-values. Response: Modified as suggested 196: please add letters that indicate the results of post hoc tests to Table 1 Response: Modified as suggested. 222: please indicate the direction of the effect Response: Modified as suggested 234: how can you make a statistical comparison with n=1 measurement per group? Where does the p-value come from? Response: Sizes of the excreted grit are comparable since there are multiple excreted grit per group, even though which chick excreted which grit. 289: give latin name Response: Modified as suggested 301: give latin name Response: Modified as suggested 341: They cannot “select the shape of excreted grit”! Response: The sentence modified as suggested. comments on figures and tables – please see the attached pdf of the submitted manuscript Response: Please see the response above. We basically modified as suggested. comments on supplementary materials: for all supplementary figures and tables: include proper, stand-along legends that appear on the excel and on the image files, which also explain abbreviations Response: Modified as suggested. Fig. S2 – please ensure that the scale is the same in all images. At the moment, it looks as if offered grit is actually SMALLER than uningested grit, but this is because the scale of the images is different. These images only have value, in my view, if the scale is consistent. I would suggest to add this figure, with consistent scaling of all images, to the main text, because it helps a lot for understanding. Delete the individual scales after scaling all images to the same scale, so that only one scale is on the figure. Response: Modified as suggested. Please note that the grit on the images are only few representatives out of hundreds of grit, so they may or may not reflect true size/shape distribution of each group. This statement is included in the figure legend. Figures S3-S5: in my view, these should be arranged differently. As they are at the moment I have to go back and forth between the figures to see a difference in shape of offered vs. gizzard, or gizzard vs. excreted ... I do not want to see roundness and solidity in the same picture, but I want to see, for one measure (e.g. roundness), offered, uningested, gizzard and excreted in the same picture. Response: The figures are rearranged into a single figure (S2) for better visibility. "

Here is a paper. Please give your review comments after reading it.

"<ns0:abstract xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:p>Reindeer (Rangifer tarandus) have lengthy seasonal migrations on land, and their feet with excellent locomotor characteristics can adapt to complex terrains. In this study, the kinematics and vertical ground reaction force (GRF) at reindeer forelimb joints (interphalangeal joint b, metacarpophalangeal joint c, and wrist joint d) under walk, trot 1, or trot 2 were measured using a motion tracking system and Footscan pressure plates.</ns0:p><ns0:p>Significant differences among different locomotor activities were found in joint angles, but not in the changes in joint angles (&#945; b , &#945; c , &#945; d ) during the stance phase. Peak vertical GRF increased with the rising locomotor speed. Net joint moment, power, and work at the forelimb joints were calculated via inverse dynamics. The peak joint moments and net joint power related to vertical GRF were increased as the locomotor speed rose. The feet needed to absorb and generate more energy at the joints. During different locomotor activities, the contribution of work of the forelimb changed with both gait and speed. In the stance phase, the metacarpophalangeal joint absorbed more energy than the other two joints during trotting, and thus performed well in elastic energy storage. The joint angles changed very little (about 5&#176;) during about 0 to 75% of the stance phase, which reflected the stability of the reindeer wrist joints. Compared with typical ungulates, the toe joints of reindeer are more stable. The stability and energy storage of the forelimb joints contribute to locomotor performance in reindeer.</ns0:p></ns0:div> </ns0:abstract> <ns0:body xmlns:ns0='http://www.tei-c.org/ns/1.0'> <ns0:div><ns0:head>Introduction</ns0:head><ns0:p>Large animals such as ungulates and humans exhibit better locomotor efficiency than small animals such as mice <ns0:ref type='bibr' target='#b0'>[1,</ns0:ref><ns0:ref type='bibr' target='#b1'>2]</ns0:ref>. This is because large animals use the ground reaction force (GRF) to store mechanical energy in their elastic feet and to drive the trunks forward in the locomotor cycle. Storage and generation of elastic energy in the feet is an efficient way to reduce metabolic energy cost during locomotion <ns0:ref type='bibr' target='#b3'>[3]</ns0:ref>. Stretch of compliant tendons also allows limb muscles to save energy by isometric contracting under load <ns0:ref type='bibr' target='#b4'>[4]</ns0:ref>. Therefore, muscle-tendon units of foot joints in large animals have important functions of energy storage, stabilization, and shock absorption.</ns0:p><ns0:p>Can muscle-tendon units of ungulate feet play an important role in energy saving? For horses during different locomotor activities such as walking and trotting, the long digital flexor tendons stretch and recoil from metacarpophalangeal (MCP) dorsiflexion and plantarflexion, leading to elastic energy storage and energy generation at the joints <ns0:ref type='bibr' target='#b6'>[5]</ns0:ref>. This action is like a passive spring and benefits the forelimbs during locomotion <ns0:ref type='bibr' target='#b7'>[6]</ns0:ref>. The MCP joints are controlled by long tendons, superficial and deep digital flexor tendons, accessory ligaments, and muscles. These tendons are ideal structures for energy storage and generation <ns0:ref type='bibr' target='#b8'>[7]</ns0:ref>.</ns0:p><ns0:p>Is the stability of limb joints important to ungulates? Stability of foot joints is associated with animal locomotion. For a trotting horse, both the elbows and shoulders of forelimbs have net extension moments, but there is little joint movement when the moments maximize. These joints are relatively rigid, which allow the trunk muscles to absorb and transmit energy <ns0:ref type='bibr' target='#b10'>[8]</ns0:ref>. The soft tissues at animal joints have important functionality during locomotion. In addition, kinematic parameters, such as joint angle, joint speed and plantar pressure, all differ depending on both the locomotor speeds and gaits <ns0:ref type='bibr' target='#b11'>[9,</ns0:ref><ns0:ref type='bibr' target='#b13'>10]</ns0:ref>.</ns0:p><ns0:p>Gaits refer to the patterns and orders of limb locomotion in animals. Most animals use different gaits according to the terrain and locomotor speeds <ns0:ref type='bibr' target='#b15'>[11,</ns0:ref><ns0:ref type='bibr' target='#b16'>12]</ns0:ref>. Gaits are categorized by the order of ground contact into walking, trotting and galloping <ns0:ref type='bibr' target='#b17'>[13]</ns0:ref>. Quadrupeds choose different gaits depending on the locomotor speeds, and select walking, trotting and galloping during low-, moderate-and high-speed locomotion activities respectively. During walking and trotting, the limbs are in symmetrical gaits, and the left and right limbs are almost under constant relative phases and at least one limb is in the stance phase. During galloping, the limbs are in asymmetrical gaits, as the left and right limbs change the relative phases with locomotor speeds, PeerJ reviewing PDF | (2020:04:47437:1:1:NEW 10 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed and a swing phase exists in which the four limbs are simultaneously in the air <ns0:ref type='bibr' target='#b18'>[14]</ns0:ref>. Studies on the gaits of horses, deer, and cheetahs in terms of mechanics, energy, kinematics and dynamics clarify that the mechanism of gait selection corresponding to locomotor speeds is related to animal balance, speed and energy saving <ns0:ref type='bibr' target='#b19'>[15,</ns0:ref><ns0:ref type='bibr' target='#b20'>16,</ns0:ref><ns0:ref type='bibr' target='#b21'>17,</ns0:ref><ns0:ref type='bibr' target='#b23'>18,</ns0:ref><ns0:ref type='bibr' target='#b25'>19]</ns0:ref>.</ns0:p><ns0:p>Based on locomotion speed and GRF, researchers used various methods to study the dynamics of animal limbs in detail. Pandy et al. calculated the inter-articular force, joint moment, and power of goats during different locomotion activities by using GRF and limb movement, and found that the foot inertia was small and negligible relative to the trunk inertia <ns0:ref type='bibr' target='#b15'>[11]</ns0:ref>. <ns0:ref type='bibr'>Dutto et al. measured</ns0:ref> the GRF, joint angle, moment and power during trotting and analyzed kinematics and dynamics of the four limbs as well as the energy storage and consumption of tendons <ns0:ref type='bibr' target='#b26'>[20,</ns0:ref><ns0:ref type='bibr' target='#b27'>21]</ns0:ref>. Moreover, the muscle stress of horse limbs during galloping was 200-400 kpa, and long tendons and extremely short pinnate muscle fibers made force production economical and enhanced the storage of tendon elastic energy <ns0:ref type='bibr' target='#b28'>[22]</ns0:ref>.</ns0:p><ns0:p>The load bearing and locomotion are both different between the forelimbs and hindlimbs of animals. During trotting, the maximum vertical GRFs in the forelimbs and hindlimbs of German Shepherds are about 63% and 37% of body weight, respectively, and the impact on the forelimbs is more significant <ns0:ref type='bibr' target='#b29'>[23]</ns0:ref>. During walking and trotting, the maximum vertical GRFs of the forelimbs are about 1.7 and 1.4 times those of the hindlimbs respectively <ns0:ref type='bibr' target='#b31'>[24]</ns0:ref>. The functions of horse forelimbs also differ depending on the GRFs, as the forelimbs mainly exert a braking effect and decrease the speed and kinetic energy, but the hindlimbs mainly play a propulsive role <ns0:ref type='bibr' target='#b32'>[25,</ns0:ref><ns0:ref type='bibr' target='#b33'>26]</ns0:ref>. During trotting, the maximum vertical GRFs of the forelimbs and hindlimbs are about ten times both the horizontal reaction force and the lateral reaction force, and the vertical GRFs are much larger than the other component forces <ns0:ref type='bibr' target='#b33'>[26]</ns0:ref>. The GRFs of limbs from walking cows and gibbons are the same <ns0:ref type='bibr' target='#b35'>[27,</ns0:ref><ns0:ref type='bibr' target='#b36'>28]</ns0:ref>.</ns0:p><ns0:p>Reindeer, a typical Arctic migratory animal, have a limb structure suitable for migration in complex environments <ns0:ref type='bibr' target='#b39'>[29]</ns0:ref>. They can adapt to various terrains, such as ice, snow, wetland, and sand <ns0:ref type='bibr' target='#b41'>[30]</ns0:ref>. Reindeer seasonally migrate long distances on land and some populations migrate farther than other terrestrial mammals <ns0:ref type='bibr' target='#b42'>[31]</ns0:ref>. But is the function of reindeer limb joints different from typical ungulates? In addition, all fibers in the skeletal muscles of reindeer have a high oxidative capacity, which may be related to endurance activity <ns0:ref type='bibr' target='#b44'>[32]</ns0:ref>. The sizes and structures of foot soles are both different between forelimbs and hindlimbs <ns0:ref type='bibr' target='#b46'>[33]</ns0:ref>. The foot soles of forelimbs are longer than those of hindlimbs (87.0&#177;1.6 vs. 74.6&#177;1.0 cm). We speculate this difference may be attributed to the different functions between the forelimbs and hindlimbs of reindeer during long migration. How does the work of forelimbs change with gait or speed?</ns0:p><ns0:p>The toe joints and wrist joint of reindeer forelimbs were more stable than those of typical ungulates, and the stability of the wrist joint was the highest. The MCP joint of reindeer plays the same role of energy storage as in typical ungulates. In addition, the contribution of work from the forelimbs changes with gait or speed. In this study, the plantar pressure, kinematics, net joint power and locomotor strategy about reindeer forelimbs were studied using the vertical GRF and limb movement of reindeer during different locomotion activities. Based on previous studies, we used inverse dynamics and the static approach to explore the functions of the main joints of forelimbs, such as energy saving and stabilization. We investigated whether the functions of interphalangeal joint b, MCP joint c, and wrist joint d in reindeer forelimbs were related to energy saving and stabilization during different locomotion activities. Depending on the locomotor postures and speeds, reindeer locomotion was classified as walk, trot 1, and trot 2. In different locomotion activities, the temporal changes in plantar pressure and joint angles in the right forelimbs of four healthy adult male reindeer were measured. Based on inverse dynamics, we calculated the net joint moment and net joint power of the right forelimbs and studied the energy absorption and generation by the limbs at the joints.</ns0:p></ns0:div> <ns0:div><ns0:head>Materials and Methods</ns0:head></ns0:div> <ns0:div><ns0:head>Samples</ns0:head><ns0:p>Fifteen healthy 8-year-old adult reindeer, including seven males and eight females, were selected from the Evenki ethnic group in Genhe City, China. The eight females were abandoned to exclude sex differences. Three males rushed to the fence and suffered foot injuries during training, and thus were not used. Finally, four easily-trained and healthy male reindeer were selected as experimental samples. The ethical examination at the animal laboratory of Jilin University passed ethical approval (No. 3130068). The masses, shoulder widths, and body lengths of the tested reindeer were 118.75&#177;14.93 kg, 1.22&#177;0.51 m, and 1.89&#177;0.83 m, respectively (mean&#177;standard deviation). The tested reindeer were in healthy condition and had not undergone any surgical treatment or other invasive procedures. The reindeer were kept in an outdoor fenced area (2&#215;10 3 m 2 ) during the day with unrestricted food and water, which was close to a semi-wild state, and were released into a wild forest at night. Before data collection, each reindeer was trained to walk and trot on the runaway, for no less than 30 minutes, twice a day for one month.</ns0:p><ns0:p>Four right forelimbs of naturally dead reindeer were purchased. The forelimbs were amputated at the wrist joints. The lower half of each forelimb was obtained and scanned by computed tomography (CT).</ns0:p></ns0:div> <ns0:div><ns0:head>Test field construction</ns0:head><ns0:p>A 80-m-long test site with a 1.5-m-high fence containing a 3-m-long and 1.5-m-wide data acquisition area was built (Fig. <ns0:ref type='figure'>1</ns0:ref>). The outside of the data acquisition area was a 77-m-long and 2-m-wide hard ground runaway. Stones, weeds, and other debris were removed to ensure that the runaway was flat and there were rest areas for reindeer to rest and eat at both ends. A pressure plate (2096&#215;472 mm 2 , 500 Hz sampling, 16384 sensors with 0.5&#215;0.7 cm 2 , USBII interface; Olen, Belgium) was placed on the runaway and positionally adjusted to ensure that it was on the same plane as the runaway. The pressure plate was connected via a signal conditioner (National Instruments, Austin TX, USA) to a computer (Dell, Xiamen, China) to record data. One camera was placed on one side of the data acquisition area and two cameras were placed on the other side. A high-speed camera system involving three synchronous digital cameras (Casio Exilim EX-FH25, Tokyo, Japan; 120 frame&#8226;s -1 ) was established. Prior to experimental testing, a 36-point, three-dimensional calibration frame, located in the plane of movement over the force platform, was recorded for calibration.</ns0:p><ns0:p>During the procedures, the feeder used food or training instructions to guide the reindeer to the runaway for steady walking and trotting. Adequate rest and food were provided for the animals within this period to prevent fluctuations in the test data. The locomotion of reindeer was divided by the gaits and speeds into walk (u=0.44&#177;0.08), trot 1 (u=0.95&#177;0.15), and trot 2 (u=1.46&#177;0.24).</ns0:p></ns0:div> <ns0:div><ns0:head>Markers and joint angles</ns0:head><ns0:p>We tested the three-dimensional (3D) coordinates of the five joints (a, b, c, d, e (Fig. <ns0:ref type='figure' target='#fig_4'>2A</ns0:ref>)) in the right forelimbs and three joint angles (&#945; b , &#945; c , &#945; d ) using a three-camera motion tracking system (Simi Motion 2D/3D &#174; 7.5 software, SIMI Reality Motion Systems GmbH, Germany). The right forelimbs of the four adult reindeer were scanned by CT, and a 3D geometric model consisting of metacarpal, second, third, fourth and fifth digits was established (Fig. <ns0:ref type='figure' target='#fig_4'>2C</ns0:ref>). Marks a (the dorsal of the hoof at the third digit), b (the proximal phalanx and the middle phalanx of the third digit at the joint), c (MCP joint), and d (wrist joint) were located according to the 3D limb model. The location of e (elbow joint) was determined based on the joint anatomy.</ns0:p><ns0:p>Regular circular reflective stickers (R=1.5 cm), as markers, were attached to the main joints of the right forelimbs (Fig. <ns0:ref type='figure' target='#fig_4'>2A</ns0:ref>). As reported, the relative locations of the distal phalanx and the middle phalanx were almost on one straight line <ns0:ref type='bibr' target='#b47'>[34]</ns0:ref>. Since the distal phalanx inside the hoof was unmeasurable, the hoof and distal phalanx were taken as one part ( the partial square in Fig. <ns0:ref type='figure' target='#fig_4'>2C</ns0:ref>) and mark a on the hoof was considered as the joint of the middle phalanx and the distal phalanx.</ns0:p><ns0:p>Three joint angles were defined (Fig. <ns0:ref type='figure' target='#fig_4'>2E</ns0:ref>), including the joint angles between the middle phalanx and the proximal phalanx (&#945; b ), between the proximal phalanx of the third digit and the metacarpal (&#945; c ), and between the metacarpal and radius (&#945; d ).</ns0:p></ns0:div> <ns0:div><ns0:head>Vertical GRF</ns0:head><ns0:p>The vertical GRF of each right forelimb was measured by the pressure plate. Before the measurement, the sample weight was input into the computer and then the sample reindeer moved on the pressure plate to complete the calibration. The pressure data for the right forelimb were collected and analyzed using Footscan 7Gait 2nd generation (RSscan International, Oren, Belgium). Footscan was used to export the fore-aft coordinates of the COP during the full stance phase duration. We calculated the average path of the centre of pressure (COPy; fore-aft component) for a series of forefoot sequences within the same speed. In terms of the kinematic data, when the displacement of the ungula cusps on Z-axis changes from a negative value to 0, it was identified as the touch-down moment of pressure plate data. When the displacement of the ungula cusps on Z-axis changes from 0 to a positive value, it was identified as the lift-off moment of pressure plate data (Fig. <ns0:ref type='figure' target='#fig_4'>2</ns0:ref>). Taking the ungula cusps as the origin, the coordinates of the COP and the joints relative to the ungula cusp were calculated, and then a global coordinates of the kinematic data and the COP was obtained. The relationship between GRF and time was drawn and normalized to the sample mass. Angular velocity, stance phase, vertical GRF, net joint moment, power, and work were calculated on Origin Pro 2015 (OriginLab Corporation, Northampton, MA, USA) based on the data from the joint 3D coordinates.</ns0:p></ns0:div> <ns0:div><ns0:head>Net joint moment</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:47437:1:1:NEW 10 Aug 2020)</ns0:p></ns0:div> <ns0:div><ns0:head>Manuscript to be reviewed</ns0:head><ns0:p>The mass of the animal foot is small and the toe joints (the joint of the middle phalanx and the distal phalanx, the joint of the proximal phalanx and the middle phalanx) and wrist joint during the stance phase displaced less than other proximal joints <ns0:ref type='bibr' target='#b48'>[35,</ns0:ref><ns0:ref type='bibr' target='#b49'>36]</ns0:ref>. Therefore, we used a static approach that ignored gravity and inertia. The net joint moment (M m ) was determined by vertical GRF and joint position (Fig. <ns0:ref type='figure' target='#fig_4'>2D</ns0:ref>) and was equal to the product of vertical GRF (averaged from four sample reindeer at walk, trot 1, and trot 2) and L (vertical distance vector from the joint marker to the GRF) <ns0:ref type='bibr' target='#b50'>[37]</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_0'>) 1 ( m L GRF M &#61655; &#61501;</ns0:formula><ns0:p>We defined the positive direction of the forelimb joint moment of the reindeer (Fig. <ns0:ref type='figure' target='#fig_4'>2D</ns0:ref>):</ns0:p><ns0:p>&#8226; For the wrist joint (d), net extension moment is positive (produced by extensor muscle), and net flexion moment is negative (produced by flexor muscle);</ns0:p><ns0:p>&#8226; For the joints of the toes (b, c), net flexion moment is positive (produced by the plantar flexor muscle) and net extension moment is negative (produced by the plantar extensor muscle).</ns0:p></ns0:div> <ns0:div><ns0:head>Net joint power and work</ns0:head><ns0:p>To estimate the energy absorbed and generated by the interphalangeal joint b, the MCP joint c, and the wrist joint d, we calculated the net joint power. Joint angular velocity was calculated from the joint angle versus the time derivative using a differential function (central difference method). The positive direction of angular velocity is the same as that of joint moment (Fig. <ns0:ref type='figure' target='#fig_4'>2E</ns0:ref>).</ns0:p><ns0:p>The net joint power (P m) generated at the joint is equal to the product of net joint moment (M m ) and joint angular velocity (&#969;), where &#969; is averaged from the four sample reindeer at walk, trot 1, and trot 2 <ns0:ref type='bibr' target='#b48'>[35]</ns0:ref>:</ns0:p><ns0:formula xml:id='formula_1'>) 2 ( m m &#969; M P &#61655; &#61501;</ns0:formula><ns0:p>When the directions of the joint moment and joint angular velocity are the same, the net joint power is positive, and otherwise it is negative. The work done at the joint is the integral of the net joint power with respect to time. Positive work and negative work represent the energy generated and absorbed by muscle-tendon units respectively <ns0:ref type='bibr' target='#b52'>[38]</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Gaits and speeds</ns0:head><ns0:p>Each reindeer completed at least five groups of tests (walk, trot 1, and trot 2) on a hard ground.</ns0:p><ns0:p>We combined the research on the gaits of other animals (e.g. goats and horses <ns0:ref type='bibr' target='#b16'>[12,</ns0:ref><ns0:ref type='bibr' target='#b25'>19]</ns0:ref>) and the reindeer locomotor postures and thereby sorted out the gaits and the order of footprints (Fig. <ns0:ref type='figure'>1B</ns0:ref>).</ns0:p><ns0:p>The reindeer postures of the right forelimbs at walk, trot 1, and trot 2 during the stance phase were shown in Fig. <ns0:ref type='figure' target='#fig_5'>3</ns0:ref>. The moments of touch-down, mid-stance, and lift-off are 0%, 50% and 100% of the stance phase respectively.</ns0:p><ns0:p>&#8226; Walk: Symmetrical gait. At any time during the stance phase, at least two limbs are on the ground and four limbs leave the ground in sequence (e.g. the leaving sequence of left rear -left front -right rear -right front) (Fig. <ns0:ref type='figure' target='#fig_4'>2B</ns0:ref>).</ns0:p><ns0:p>&#8226; Trot: Symmetrical gait. Any forelimb and its diagonal hindlimb move in the same phase, and only two limbs are in the stance period (sometimes four legs are in the swing phase at the same time, e.g. the leaving sequence of left rear and right front-right rear and left front) (Fig. <ns0:ref type='figure' target='#fig_4'>2B</ns0:ref>).</ns0:p><ns0:p>Speed data were normalized by Froude number (u), where v and l are the average velocity and the height of the shoulder joint from touch-down to lift-off, respectively; g is the acceleration of gravity:</ns0:p><ns0:p>)</ns0:p><ns0:formula xml:id='formula_2'>3 ( l g v u &#61655; &#61501;</ns0:formula><ns0:p>In order to examine changes with speed, relevant variables from all trotting trials were divided into two bins indicative of trot 1 ( range of u: 0.8-1.1) and trot 2 (range of u: 1.1-1.7). The speeds of reindeer at walk, trot 1, and trot 2 after nondimensionalization are 0.44&#177;0.08, 0.95&#177;0.15, and 1.46&#177;0.24 (mean&#177;S.D.).</ns0:p></ns0:div> <ns0:div><ns0:head>Statistical analysis</ns0:head><ns0:p>Vertical GRF, net joint moment and net joint work were normalized to stance duration and to reindeer mass. Statistical analyses were conducted to examine the differences in different gaits and speeds, three key indicators (joint angles at touch-down, mid-stance and lift-off) between slow walking and trotting gaits/ trot 1 and trot 2 speeds using Origin Pro 2015 (OriginLab Corporation, Northampton, MA, USA). We used one-way ANOVA statistical technique to analyze the effect of locomotor gait and speed on each joint angle indicator. F-test was conducted to test whether these two variations are significantly different. Statistical significance level was considered as P &lt; 0.05.</ns0:p></ns0:div> <ns0:div><ns0:head>Results</ns0:head></ns0:div> <ns0:div><ns0:head>Joint angles</ns0:head><ns0:p>PeerJ reviewing PDF | (2020:04:47437:1:1:NEW 10 Aug 2020)</ns0:p><ns0:p>Manuscript to be reviewed During different activities, the maximum and minimum values of &#945; b and &#945; c during the stance phase and the corresponding time points differed. Also the joint range of motion (ROM) was larger at the trotting gaits than at the walking gait. The ROMs of &#945; d among the three joint angles were the greatest, and were around 29&#176;, 30&#176; and 35&#176; during walk, trot 1 and trot 2, respectively.</ns0:p><ns0:p>The ROMs of &#945; b were the smallest, and were around 26&#176;, 27&#176; and 33&#176; during walk, trot 1 and trot 2, respectively. Therefore, the relationships of joint angles with gaits and speeds showed that reindeer joints can adapt to different gaits and locomotor speeds.</ns0:p></ns0:div> <ns0:div><ns0:head>Vertical GRF</ns0:head><ns0:p>The reindeer forelimbs have different vertical GRFs at different time points during the stance phase. According to the time corresponding to the peak vertical GRF, reindeer forelimb locomotion can be divided into a braking phase and a propulsive phase <ns0:ref type='bibr' target='#b53'>[39]</ns0:ref>. The vertical GRF increased with time during the braking phase, and decreased with time during the propulsive phase (Fig. <ns0:ref type='figure' target='#fig_8'>6</ns0:ref>).</ns0:p><ns0:p>The peak vertical GRFs (normalized to body mass) during walk, trot 1, and trot 2 were 8.95, 11.33, and 12.80 times the body mass, respectively, and the corresponding peaking time was 57.03%, 50.45%, and 47.78% of the stance phase, respectively. The gaits and locomotor speeds of reindeer affect the vertical GRF. As for different gaits, the peak vertical GRF at trot was larger than that at walk. At the same gait, the peak vertical GRF at trot 2 was larger than that at trot 1.</ns0:p></ns0:div> <ns0:div><ns0:head>Net joint moment</ns0:head><ns0:p>In different activities, the forelimb joints b and c of reindeer in the stance phase (about 0 to 100%) produced positive net flexion moment by the plantar flexor (Fig. <ns0:ref type='figure' target='#fig_9'>7</ns0:ref>). Joint d in the early stance phase (about 0 to 75%) and late stance phase (about 75 to 100%) produced the negative net flexion moment and positive net extension moment respectively by the flexor and extensor muscles (Fig. <ns0:ref type='figure'>8</ns0:ref>). Reindeer and horses have similar net joint moment curves for joints c and d during trotting on hard ground <ns0:ref type='bibr' target='#b26'>[20]</ns0:ref>.</ns0:p><ns0:p>In different activities, reindeer have different peak net joint moments at the forelimb joints.</ns0:p><ns0:p>Joints b, c, and d reached the peak net joint moments at about 45%, 50% and 30% of the stance phase, respectively. The peak net joint moments at walk, trot 1, and trot 2 were 0.28, 0.37, and 0.42 Nm&#8226;kg -1 , respectively at joint b, were 0.55, 0.79, and 0.93 Nm&#8226;kg -1 , respectively at joint c, and were -0.95, -1.35, and -1.78 Nm&#8226;kg -1 , respectively at point d. The vertical GRF of reindeer forelimbs increased with the rising locomotor speed and the peak joint moment also rose. Since the vertical distance vector of vertical GRF from joint d was the largest, joint d had the greatest peak joint moment, followed successively by joint c and joint b.</ns0:p></ns0:div> <ns0:div><ns0:head>Net joint power and work</ns0:head><ns0:p>The net joint moment reflects the muscles (extensors and flexors) and activity (extension and flexion), but not the changes of energy in the muscle-tendon units at the joints. Net joint power and work, which are directly related to the energy absorption and generation at the limb joints <ns0:ref type='bibr' target='#b54'>[40]</ns0:ref>, at reindeer forelimb joints were shown in Figs. <ns0:ref type='figure' target='#fig_9'>7 and 8</ns0:ref>. Clearly, the net joint moment and angular velocity at the forelimb joints increased with the rise of locomotor speed. Therefore, the net joint power at the joints increased too. The net joint power ranges at joint c were the largest and were -0.37 to 0.06, -0.19 to 0.21, and -4.37 to 2.46 W&#8226;kg -1 at walk, trot 1, and trot 2, respectively. As the locomotor speed was accelerated, the net joint power range was enlarged and thus the feet needed to absorb and generate more energy at the joints.</ns0:p><ns0:p>In different activities, reindeer had similar work patterns at the same joint. From about 0 to 55% of the stance phase, the dorsiflexion of joint c produced a net flexion moment and the foot absorbed energy at the joint. From about 55% to 100% of the stance phase, joint c plantarly flexed and the plantar flexor and extensor muscles generated and absorbed energy, respectively (details of energy absorption and generation at each joint are shown in Table <ns0:ref type='table'>1</ns0:ref>). The energy changes at the limb joints are related to joint functions, such as energy storage and stabilization <ns0:ref type='bibr' target='#b55'>[41,</ns0:ref><ns0:ref type='bibr' target='#b56'>42]</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Discussion</ns0:head><ns0:p>We investigated whether the functions of interphalangeal joint b, MCP joint c, and wrist joint d in the forelimbs were correlated with energy saving and stability. Depending on the locomotor postures and speeds, locomotor activities of the reindeer were divided into walk, trot 1, and trot 2.</ns0:p><ns0:p>In different locomotion activities, we measured the temporal changes in plantar pressure and joint angles in the right forelimbs of four healthy adult male reindeer. Based on inverse dynamics, we calculated the net joint moment and net joint power of the right forelimbs and the energy absorption and generation by the limb joints.</ns0:p><ns0:p>To adapt to different locomotor gaits and speeds, animals adopt different locomotor strategies.</ns0:p><ns0:p>For example, goat limbs adjust the work of muscles and tendons to adapt to walk and trot locomotion on slope-variable surfaces <ns0:ref type='bibr' target='#b57'>[43]</ns0:ref>. Horses rely on minimization of metabolic costs, and choose gaits in a range of different locomotion speeds, including the the most energy-efficient trot gait <ns0:ref type='bibr' target='#b23'>[18]</ns0:ref>. In our study, during different gaits (walk and trot) and speeds (trot 1 and trot 2), significant differences were found in the reindeer joint angles at the moments of touch-down, mid-stance, and lift-off. (Fig. <ns0:ref type='figure'>9</ns0:ref>), which may be associated with the locomotor strategies of reindeer.</ns0:p><ns0:p>Even though reindeer selected different locomotor strategies during different gaits and speeds, we still found some similarities, such as the elastic energy saving function of joint b, and the effect of joint d in increasing joint stability.</ns0:p></ns0:div> <ns0:div><ns0:head>Contribution of work change with gaits and speeds</ns0:head><ns0:p>Most animals use the inverted pendulum model in the walking gait and restore mechanical energy via periodic conversion of kinetic energy and potential energy <ns0:ref type='bibr' target='#b58'>[44,</ns0:ref><ns0:ref type='bibr' target='#b60'>45]</ns0:ref>. In the trotting, the spring-mass system and the inverted pendulum model are used and the limbs act as springs that can store and generate energy, as characterized by a significant reduction in the difference between potential and kinetic energy during the stance phase <ns0:ref type='bibr' target='#b61'>[46,</ns0:ref><ns0:ref type='bibr' target='#b62'>47]</ns0:ref>. In our study, significant Manuscript to be reviewed difference was found in joint angles &#945; b and &#945; c between walking and trotting gaits and in &#945; b and &#945; d between trot 1 and trot 2 (Fig. <ns0:ref type='figure'>9</ns0:ref>). In the trotting gait, the MCP joint absorbed more energy than the other two joints (Table <ns0:ref type='table'>1</ns0:ref>), but in the walking gait, the MCP joint absorbed less energy than the wrist joint. This may be attributed to the preference of animals over the inverted pendulum gait at low speed and over the mass spring inverted gait at high speed, which both enhanced locomotor performance and energy saving <ns0:ref type='bibr' target='#b63'>[48,</ns0:ref><ns0:ref type='bibr' target='#b64'>49]</ns0:ref>. The different motion patterns among different gaits and speeds in the forelimb joints of reindeer may be caused by the choice of the energy mechanism.</ns0:p><ns0:p>Reindeer have the enhanced MCP joints. During walking, the proximal phalanx pivots about joint b (at stance phase of ~ 0-10%) (Fig. <ns0:ref type='figure' target='#fig_7'>5A</ns0:ref>), with slight downwards and upwards. However, during the trot, the distal phalanx moves downward (joint b plantarflexion) for a prolonged period of time (at stance phase of ~ 0 -20%) (Fig. <ns0:ref type='figure' target='#fig_7'>5A</ns0:ref>). Due to stretching and recoiling of the plantar flexor tendons, the plantarflexion and dorsiflexion of interphalangeal joint b are typical of a loading and rebounding pattern. This indicates that the elastic elements at the toe joints offset the GRF, and the trotting gait can reduce the pressure and protect the soft tissues of toes by prolonging the foot-to-ground contact time ratio.</ns0:p><ns0:p>As reported, when the horse locomotor speed was accelerated, the positive and negative work done at the MCP joint c was raised significantly and the elastic energy storage and generation were increased <ns0:ref type='bibr' target='#b26'>[20]</ns0:ref>. This finding is very consistent with our test results. When the ROM of MCP joints and net flexion moment increased with the rising locomotor speed, the foot work of reindeer at the joint was also raised. The difference in the ROM of the wrist joint d was small among different activities (about 5&#176;), but the faster locomotor speed led to an increase in vertical GRF and angular velocity and thus in net joint moments and power. Compared with the trotting gait, the power of the wrist joint was smaller, but fluctuated more severely, during the walking gait (Fig. <ns0:ref type='figure'>8A</ns0:ref>). Slow locomotor activity may require a higher level of neural control <ns0:ref type='bibr' target='#b65'>[50]</ns0:ref>.</ns0:p></ns0:div> <ns0:div><ns0:head>Comparison between the forelimb joints of reindeer and typical ungulates</ns0:head><ns0:p>Ungulate locomotion of animals has evolved in vastly different designs depending on the specific habitat of each species <ns0:ref type='bibr' target='#b66'>[51]</ns0:ref>. Compared with horse forelimbs, the toe joints of reindeer are stable, as the ROMs between interphalangeal joints and MCP joints are smaller. The ROMs of interphalangeal joint b of reindeer and horse were about 30&#176; and 40&#176;, respectively, and the ROMs of MCP joint c of reindeer and horse were about 31&#176; and 40&#176;, respectively <ns0:ref type='bibr' target='#b26'>[20]</ns0:ref>. These differences indicate that reindeer forelimbs have stable toe joints. Measurement with a linked segment model and the spring coefficients of a spring model demonstrated that the stiffness of goat limbs was twice that of dog limbs during different activities, suggesting that goats have adapted to a rougher and steeper ground <ns0:ref type='bibr' target='#b67'>[52]</ns0:ref>. The wrist joint d flexion produced a net flexion moment, which generated propulsion in the middle stance phase (about 45 to 75%) <ns0:ref type='bibr' target='#b68'>[53]</ns0:ref>. In the last 20% of the stance phase, the long digital flexor tendons at interphalangeal joint b and MCP joint c recoiled and the joint plantarflexion produced a net flexion moment, but the net flexion moment and propulsion were small (Fig. <ns0:ref type='figure' target='#fig_9'>7</ns0:ref>). The wrist joint d changed letter at 0% to 75% of the stance phase (about 5&#176;). During trotting, the change trend of wrist joint d of horses was similar with that of reindeer. The wrist joint angle of horses maintained at 180&#176;-190&#176; within 0%-60% of the stance phase and then gradually decreased <ns0:ref type='bibr' target='#b26'>[20]</ns0:ref>. Therefore, the wrist joint d of reindeer maintained stable with time. Reportedly, horse knees during the stance phase produce a net flexion moment and the flexor muscles assist foot movement, where the extensor muscles can stabilize the joints <ns0:ref type='bibr' target='#b65'>[50]</ns0:ref>. Similarly, the reindeer wrist joint d displayed the stabilizing ability during the early and middle of stance phase (about 0~75%). The very little change in joint angle (about 5&#176;) indicates the wrist joint plays a role in stabilizing foot locomotion. The low flexibility and high stability of the forelimb joints might be beneficial to long distance migration.</ns0:p></ns0:div> <ns0:div><ns0:head>MCP joints as an energy storage device</ns0:head><ns0:p>The MCP joints of most animals can elastically store and generate energy because they are mainly composed of small muscles, short pinnate muscle fibers, and long tendons <ns0:ref type='bibr' target='#b10'>[8,</ns0:ref><ns0:ref type='bibr' target='#b69'>54,</ns0:ref><ns0:ref type='bibr' target='#b70'>55]</ns0:ref>.</ns0:p><ns0:p>Ligaments have a protective effect on joints <ns0:ref type='bibr' target='#b71'>[56]</ns0:ref>, and tendons also provide an energy advantage in high-speed locomotion <ns0:ref type='bibr' target='#b65'>[50]</ns0:ref>.</ns0:p><ns0:p>Reportedly, the relatively short muscle fibers and long tendons of turkey hindlimbs act like springs <ns0:ref type='bibr' target='#b72'>[57]</ns0:ref>, as the short muscle fibers contribute to more economical muscular energy, and the stretching of long tendons allows muscle fibers to generate energy with little change in length, decreasing metabolic costs <ns0:ref type='bibr' target='#b73'>[58,</ns0:ref><ns0:ref type='bibr' target='#b74'>59]</ns0:ref>. The MCP joints at reindeer feet also absorb and generate energy in different locomotor activities (Table <ns0:ref type='table'>1</ns0:ref>), as manifested by an elastic system for energy storage and generation (Fig. <ns0:ref type='figure' target='#fig_9'>7</ns0:ref>). The distal joints in horse forelimbs recover 40% of energy during the stance phase <ns0:ref type='bibr' target='#b55'>[41]</ns0:ref>. Furthermore, 70%-80% of plantar flexors stretched at the Manuscript to be reviewed metatarsal joints during the stance phase, and the Achilles tendons, long plantarflexion tendons, and plantar connective tissues of feet absorbed energy and converted it into elastic potential <ns0:ref type='bibr' target='#b53'>[39]</ns0:ref>.</ns0:p><ns0:p>The MCP joints of reindeer, at the same position in forelimbs, also performed well in energy storage among different locomotor activities. The MCP joints at walk, trot 1, and trot 2 absorbed 6.42&#215;10 -2 , 0.20 and 0.33 J&#8226;kg -1 of energy (negative power), respectively.</ns0:p></ns0:div> <ns0:div><ns0:head>Conclusions</ns0:head><ns0:p>The forelimb joint angles of reindeer (&#945; b , &#945; c , &#945; d ) changed in similar patterns during different locomotor stance phases. The peak vertical GRF increased with the rising locomotor speed. The peak vertical GRFs (normalized to body mass) at walk, trot 1 and trot 2 were 8.95, 11.33 and 12.80 times the body mass, respectively. Among different locomotor activities, the joint angles were significantly different at the touchdown, mid-stance, and lift-off moments. During the trotting gaits, the MCP joint absorbed more energy than the other two joints, but during walking gaits, it absorbed less energy than the wrist joint. Across different gaits and speeds in locomotion, the forelimbs adopted different locomotor strategies to improve locomotor performance and save energy.</ns0:p><ns0:p>As the reindeer speed was accelerated, the peak joint moment and net joint power both increased.</ns0:p><ns0:p>The feet needed to absorb and generate more energy at the joints. The feet first absorbed energy and then generated energy at the MCP joint during the stance phase and performed well in elastic energy storage. In the middle of stance phase (about 45% -75%), the feet exerted a propulsive effect during the flexion of the wrist joint. In the early and middle of stance phase (about 0-75%), the joint angle changed little (about 5&#176;) and the wrist joint can stabilize the feet. During longdistance migration, forelimbs play a role of maintaining stability and energy storage.</ns0:p></ns0:div> <ns0:div><ns0:head>Forecast</ns0:head><ns0:p>The kinematics of hindlimb and the coordination of hindlimb and forelimb of reindeer would be analyzed to research the effect of reindeer foot joint on movement in a follow-up study. Manuscript to be reviewed </ns0:p></ns0:div><ns0:figure xml:id='fig_0'><ns0:head /><ns0:label /><ns0:figDesc>During walk, trot 1, and trot 2 in the stance phase, the reindeer interphalangeal joint angle &#945; b (Fig 4A), MCP joint angle &#945; c (Fig 4B), and wrist joint angle &#945; d (Fig 4C) showed similar patterns and ranges. Therefore, the data of joint angles of the four sample reindeer were combined to analyze the temporal variation of joint angles during the stance phase. The stick figure of the reindeer forelimbs during different locomotor stance phases was shown in Fig. 4D. At the moment of touch-down, the limb joints (b, c, d) first moved toward the ground and then left the ground after touching the lowest point. This pattern of motion may relate to energy saving. The integrated data correspond to the means and variances of &#945; b , &#945; c and &#945; d (Fig. 5A-C) at walk, trot 1, and trot 2 in the stance phases. The joint angles (&#945; b , &#945; c , &#945; d ) displayed similar patterns during different locomotor stance phases. The &#945; b increased (joint plantarflexion) during the early stance phase (about 0-30%), decreased (joint dorsiflexion) in the middle stance phase (about 30%-80%), and rose (joint plantarflexion) in the late stance phase (about 80%-100%). The interphalangeal joint b flexed plantarly in the late stance phase, and the hoof gradually lifted off the ground with the tip still in contact with the ground.</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_1'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47437:1:1:NEW 10 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_2'><ns0:head /><ns0:label /><ns0:figDesc>PeerJ reviewing PDF | (2020:04:47437:1:1:NEW 10 Aug 2020)</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_3'><ns0:head>Figure 1 Schematic 2 )</ns0:head><ns0:label>12</ns0:label><ns0:figDesc>Figure 1</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_4'><ns0:head>Figure 2 Reindeer</ns0:head><ns0:label>2</ns0:label><ns0:figDesc>Figure 2</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_5'><ns0:head>Figure 3 Locomotor</ns0:head><ns0:label>3</ns0:label><ns0:figDesc>Figure 3</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_6'><ns0:head>Figure 4 Stick</ns0:head><ns0:label>4</ns0:label><ns0:figDesc>Figure 4</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_7'><ns0:head>Figure 5 Mean</ns0:head><ns0:label>5</ns0:label><ns0:figDesc>Figure 5</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_8'><ns0:head>Figure 6 Mean</ns0:head><ns0:label>6</ns0:label><ns0:figDesc>Figure 6</ns0:figDesc></ns0:figure> <ns0:figure xml:id='fig_9'><ns0:head>Figure 7 Mean</ns0:head><ns0:label>7</ns0:label><ns0:figDesc>Figure 7</ns0:figDesc></ns0:figure> <ns0:figure><ns0:head /><ns0:label /><ns0:figDesc /><ns0:graphic coords='23,42.52,70.87,525.00,408.75' type='bitmap' /></ns0:figure> </ns0:body> "

"Rebuttal Letter Dear Editors and Reviewers, Thank you for your email dated xxx with the reviewers’ comments concerning our manuscript entitled “Forelimb Joints Contributing to Locomotor Performance in Reindeer (Rangifer Tarandus) by maintaining stability and energy storage” (2020:04:47437:0:1:REVIEW). After reviewing the comments, we revised the manuscript accordingly. The amendments are highlighted in red (revised contents) in the Manuscript (tracked changes). Point by point responses to the reviewers’ comments are listed below this letter. We would like to express our sincere gratitude to the editors and reviewers for the constructive and comments. Yours sincerely, Rui Zhang Replies to Reviewer 1: Basic reporting: Comment 1: In general, the writing was clear. There are some word choices that should be changed. For examples a careful proof reading will find many of these: Abstract Line 18: “…vertical GRF were increased as the locomotor…” The word increased is more important than enhanced. Introduction, Line 54: use ‘terrain’ instead of “landforms” Line 116: “…tested reindeer were in healthy condition and…” Line 118: “…outdoor fenced area (2 x 10…” Discussion, Line 312: why use the word “permanently” here? Discussion, Line 320: “work” not “works”. Answer: Thank you for the comments. We have revised relevant content according to the reviewer’s suggestion. Please refer to Abstract, Introduction, Samples and Discussion. . • Comment 2: The review of literature in the introduction accounts for previous work in the field. The paper is generally well referenced, however there are papers that are cited which contain more information relevant to the study than indicated. For example, the paper by Dutto et al (2004) has joint angle, moment, and power during trotting in horses and it is not in the references. The focus on comparison with other ungulates is relevant, particularly with regard to the morphology of the forelimb and associated function. Comparing morphology and mechanics of the reindeer with other, similar quadrupeds would provide a good analysis. That is only done peripherally as part of the overall paper. Answer: Thank you for the comments. We have revised relevant texts and added the suggested reference. Meanwhile, we compared the mechanics of the reindeer with other similar quadrupeds. Please refer to Introduction, Discussion and References. The new reference is as follows. Dutto, D. J., Hoyt, D. F., Cogger, E. A., & Wickler, S. J. (2004). Ground reaction forces in horses trotting up an incline and on the level over a range of speeds. Journal of Experimental Biology, 207(20), 3507-3514. • Comment 3: Figures are generally of high quality. Here some issues: Figure 2. It was unclear where the dotted line in Fig 2C is located to indicate the distal foot. Is it the partial square? It did not come through very clear in the copy I received. Figures 4, 5, 6,7,8: It is helpful to have all plots within a figure to have the same scale. This allows for an easier visual comparison of each joint/condition. Figure 7 and 9. The caption is cut off so that some of the text is missing. Answer: Thank you for pointing out the issues. The distal foot is in the partial square. And We have added the caption of the figures 7 and 9. Please refer to Figure 7 and 9. • Comment 4: Finally, there is raw data supplied. However, I was not able to open all of the data files, as I got an error when attempting to do so. Answer: Sorry for the problem. All of the data files can be opened via Excel. According to the requirements of the journal, we saved the data in Excel and zipped the files. Please try to open it with Excel. Experimental design: • Comment 5: Determining the forelimb kinetics of a cursorial, quadrupedal, ungulate is relatively novel. It appears that the research questions being addressed are: 1. “Is the function of reindeer limb joints different from other ungulates?” 2. “Do reindeer adopt different strategies across different gaits and speeds? These are good questions. However, neither one is answered well in the context of the paper. Some of the confusion might be with the wording of the question. For example, if the second question was “Does the contribution of work of the forelimb change with gait or speed?”, it would provide more clarity and focus on what was being discussed. Additionally, the comparison with other ungulates is relevant due to the type of terrain over which these animals must traverse. Providing more in-depth comparison with previously published work would help to illustrate the function of the limb in the animal pertinent to the environment. Answer: Thank you for the comments on the paper. We have revised relevant content according to the reviewer’s suggestion. The research questions being addressed are: 1. “Is the function of reindeer limb joints different from typical ungulates?” 2. “Does the contribution of work of the forelimb change with gait or speed?” Please refer to Introduction and Discussion. • Comment 6: The methods, in general, are appropriate for an investigation of this type. Creating a space to safely test animals such as these can be challenging, especially given the tricky nature of capturing both video and ground reaction force. The set-up is sound. With regards to the video and reconstruction of three-dimensional coordinates, there is no information given on the calibration of the capture space. Also, since just three cameras were used, obtaining accurate reconstruction of the marker trajectories can be tricky. Did the investigators validate their set-up? Were the cameras synchronized? How was the video synchronized with the pressure plate data? Answer: Thank you for the comments. Prior to experimental testing, a 36-point, three-dimensional calibration frame, located in the plane of movement over the force platform, was recorded for calibration. Three cameras were positioned in a 3D arrangement (not aligned), which could make three-dimensional observations. We had done a similar kinematic experiment a few years ago, and the article was “Zhang R , Ji, Q L , Luo G , et al. Phalangeal joints kinematics during ostrich (struthio camelus) locomotion. Peerj, 2017, 5(1), e2857”. In terms of the kinematic data, when the displacement of the ungula cusps on Z-axis changes from a negative value to 0, it was identified as the touch-down moment of pressure plate data. When the displacement of the ungula cusps on Z-axis changes from 0 to a positive value, it was identified as the lift-off moment of pressure plate data. The method was used by Arnold, and the article was “Vereecke E E , Aerts P. The mechanics of the gibbon foot and its potential for elastic energy storage during bipedalism[J]. Journal of Experimental Biology, 2008, 211(23):3661-3670”. Please refer to Test field construction and Vertical GRF. • Comment 7: It indicates that “each reindeer completed at least five groups of tests”. Does this mean that the results provided are an average of 5 trials at each gait condition for an animal? How were data combined if so? Or was just one trial used for each animal? Answer: Thank you for the comments. Yes, the results provided are an average of 5 trials at each gait condition for an animal. The method is a weighted sum. • Comment 8: With regard to pressure plate, how was the center of pressure validated? How was this combined with the kinematic data? How was calibration of the entire set-up (force and kinematics) done to insure accuracy? Small discrepancies in COP location relative to marker locations can have a significant effect on joint moment calculations. Answer: The center of pressure was measured by an RSscan International Pressure Plate (2,096 × 472 mm2, 500 Hz sampling, 16,384 sensors with 0.5×0.7 cm2, USBII interface; Olen, Belgium). Footscan software was used to export the fore–aft coordinates of the COP during the full stance phase duration. We calculated the average path of the centre of pressure (COPy; fore–aft component) for a series of forefoot sequences within the same speed range. Taking the ungula cusps as the origin, the coordinates of the COP and the joints relative to the ungula cusp were calculated, and then a global coordinates of the kinematic data and the COP was obtained. Please refer to Vertical GRF. • Comment 9: For both the kinematic and kinetic data, did any data processing/reduction occur? Were the data smoothed or resampled in any way? There is a fair amount of noise in the power data, but not in the moment or presented angle data.  Answer: The kinematic data was smoothed with Simi Motion 2D/3D® 7.5 software. Both ground reaction force data and the power data were not smoothed. Creatures are a complex system consisting of bones and muscles that undergoes compressible deformation during movements. It is one of the factors causing fluctuation. • Comment 10: How were the speed bins chosen for trot 1 and trot 2? Answer: In order to examine changes with speed, relevant variables from all trotting trials were divided into two bins indicative of trot 1 ( range of u: 0.8–1.1) and trot 2 (range of u: 1.1–1.7). Please refer to Gaits and speeds. • Comment 11: The sample size is very small, which is not uncommon with these types of data collection. In order to confidently indicate that differences were present, statistical analysis is required. Further, consistent indication of variability (such as standard deviation) is relevant. Using the questions posed in the introduction, perform specific statistical assessments on your data for comparison. This will strengthen any conclusions you have to make. Answer: Thank you for the comments on the paper. Based on a number of preliminary experiments on 15 samples, 4 typical male reindeer were selected, with weight, height, attack speed and running speed taken into consideration. The research of Witte and Vereecke supports the credibility of small-size animal testing. For your reference, the articles are “Witte, T. H., Knill, K., Wilson, A. M. (2004). Determination of peak vertical ground reaction force from duty factor in the horse (equus caballus). Journal of Experimental Biology, 207(21), 3639-3648.” and “Vereecke, E. E., Aerts, Peter (2008). The mechanics of the gibbon foot and its potential for elastic energy storage during bipedalism. Journal of Experimental Biology, 211(23), 3661-3670”. Validity of the findings: • Comment 12: The observations of the study are relatively novel. Similar results have been observed from trotting in horses, dogs, goats, and other animals. However, the apparent structure of the distal limb (foot) lends import to the observations. A more detailed comparison with previous literature on quadrupeds would strengthen the findings. In terms of whether energy savings are occurring, understanding function of the proximal joints, and the general metabolic cost of transport will help to provide relevance. One other consideration is that previous work has found that the forelimb acts more for support and less for propulsion during locomotion (Dutto, et al 2006, Payne et al, 2005). I suspect that this is similar for the reindeer. The relative energy absorption of the MCP is helping to control the vertical motion. Combining these results with what is occurring mechanistically in the hindlimb, will give a better overall picture of the changes associated with gait and how similar or dissimilar these animals are from other ungulates. Answer: We have revised relevant content about the propulsion function of the forelimb. Besides a comparison between the forelimb joints of reindeer and typical ungulates has been added. The study of the hindlimb may be included our next work. Please refer to Discussion. The above revised contents are only a point-by-point response to the reviews. In order to fully understand the revised contents, please read the revised manuscript. Replies to Reviewer 2: Basic reporting: • Comment 1: The grammar and writing are acceptable. There are a few instances where corrections are advisable and these are noted in my comments. The authors have met criteria for references, background, professional article structure, figures and tables. They have also provided the raw data. The results are self-contained and relevant to the introduction in the article. I would only ask that they make their hypotheses or expectations explicit in the introduction (though they somewhat implicit; see General Comments). Answer: Thank you for the comments. We have added the hypotheses and expectations in the introduction. The research questions being addressed are: 1. “Is the function of reindeer limb joints different from typical ungulates?” 2. “Does the contribution of work of the forelimb change with gait or speed?” Please refer to Introduction, Materials and methods, Results and Discussion. Experimental design: • Comment 2: This is original primary research that is within the aims and scope of the journal. The research questions are somewhat well defined (though I would like to see explicit hypotheses/expectations; see General Comments), relevant and meaningful. The authors state how this study fills a gap in the literature. The authors provided a rigorous investigation of reindeer forelimb mechanics using inverse dynamics and appear to have met institutional ethical requirements. The methods have been described sufficiently to allow for replication. Answer: We have stated the hypotheses and expectations explicitly in the introduction. The research questions being addressed are: 1. “Is the function of reindeer limb joints different from typical ungulates?” 2. “Does the contribution of work of the forelimb change with gait or speed?” Please refer to Introduction. Validity of the findings: • Comment 3: The findings in this study are valid, robust, and are sound. The authors used statistics but did not indicate what tests were used (see General Comments). The authors conclusions are well stated, though not linked to well defined hypotheses/expectations setup in the introduction. There are a few instances of speculation that need to be identified as the authors novel hypothesis or require elaboration (see General Comments). Answer: We have added the statistical analysis, as well as the hypotheses and expectations in the introduction. The research questions being addressed are: 1. “Is the function of reindeer limb joints different from typical ungulates?” 2. “Does the contribution of work of the forelimb change with gait or speed?” Please refer to Statistical analysis and Introduction. Comments for the Author: • Comment 4: Overall, this is a well done study of forelimb mechanics in reindeer. However, I do have some questions and suggestions: I think the title needs to be more specific and relay the what the authors did in the study or what their findings were. The current title ‘Forelimb joints contributing to locomotor performance in reindeer’ is a statement that could be made without the contents of this manuscript and should be ‘Forelimb joints contribute to locomotor performance in reindeer’. In what way do they contribute? Answer: Thank you for the comments. We have revised the title to be ‘Forelimb Joints Contribute to Locomotor Performance in Reindeer (Rangifer tarandus) Through Maintaining Stability and Energy Storage’ Please refer to the title. Comment 5: The abstract would benefit from a conclusion statement or discussion point. This is just a summary of methods and results. Answer: Thank you for the comment. relevant content have been revised according to the reviewer’s suggestion. Please refer to Abstract. • Comment 6: The introduction is comprehensive, but it took a long time to get to your question. I think a statement of the question/problem early on would help frame the introduction and background necessary to understand what we know and what we don’t know. Answer: Thank you for the comment. We have stated the hypotheses and expectations explicitly in the introduction. Please refer to Introduction. • Comment 7: Did you collect data from the female reindeer and then exclude them because they showed differences compared to males or did you not collect data on them? Are there expectations that female reindeer forelimb mechanics will differ from males other than body size effects? Answer: Thank you for the comment. We didn't collect data on female reindeer. • Comment 8: Is there a reason why you didn’t calculate joint work for the shoulder to characterize joint work/power for the entire forelimb? Answer: Thank you for the comment. That is because the shoulder joint is located in the trunk, where the skin is loose. During locomotion, the skin of the trunk vabrates. The Marks sway with the skin, affecting the observation and results of the experiment. • Comment 9: In Fig 9, the authors present statistical results, but don’t indicate what statistical test was used. Please put this in methods. Answer: Thank you for the comment. We have added the statistical analysis. Please refer to Statistical analysis. • Comment 10: Overall, I think this paper would benefit from some predictions or hypotheses. The introduction is comprehensive and following a discussion of previous findings in horses and other ungulates, the authors could setup a few expectations that they could use as a comparison in the results or discussion section. This could just be a couple of paragraphs in total. As is, the manuscript is fine and provides a sufficient description of their findings. However, I think the overarching conclusion that reindeer use different strategies, presumably to moderate energy costs at different speeds (which should be the null hypothesis) needs to be expanded on a little bit. The headings the authors used in the discussion (e.g., ‘Wrist joints as a stabilizer and pusher’) would be perfectly suitable as predictions that could be setup in the introduction. Answer: Thank you for the comment. We have stated the hypotheses and expectations in the introduction, and revised the discussion. Please refer to Introduction and Discussion. • Comment 11: Figure 2B is a little challenging to interpret. It might be easier to follow if you labeled the circles in the figure so you don’t have to keep referencing the figure legend. One option is to put labels like FL (front left) in the circle. Answer: Thank you for the comment. We have revised relevant content according to the reviewer’s suggestion. Please refer to Figure 2B. • Comment 12: Figure 8. I assume Walk is (A), Trot 1 is (B) and Trot 2 is (C), but these should be listed in the figure legend. Answer: Thank you for the comment. We have revised relevant content according to the reviewer’s suggestion. Please refer to Figure 8. • Comment 13: [LINE 111] The more appropriate term is ‘sex’ in reindeer. Gender refers to identity. Answer: Thank you for the comment. We have revised relevant content according to the reviewer’s suggestion. Please refer to Samples. • Comment 14: [LINE 139] How did you decide to separate trot speeds into 2 categories? Were speeds bimodal? Was it arbitrary? Answer: Thank you for the comment. In order to examine changes in speed, relevant variables from all trotting trials were divided into two bins indicative of trot 1 ( range of u: 0.8–1.1) and trot 2 (range of u: 1.1–1.7). Please refer to Gaits and speeds. • Comment 15: [LINE 141] I suggest defining what a, b, c, d, and e represent or at least reference Figure 2A here. Answer: Thank you for the comment. We have revised relevant content according to the reviewer’s suggestion. Please refer to Markers and joint angles. • Comment 16: [LINE 162] In the sentence beginning ‘Relationship between GRF and time’ should begin as ‘The relationship between GRF and time’. Answer: Thank you for the comment. We have revised relevant content according to the reviewer’s suggestion. Please refer to Vertical GRF. • Comment 17: [LINE 164] Please include vendor information for Origin. Answer: Thank you for the comment. We have added relevant content according to the reviewer’s suggestion. Please refer to Vertical GRF. • Comment 18: [LINE 166] This is the first time that I see that you have referred to the ‘toe joint’. Please define it here using terms you used previously or use terminology from Figure 2. Answer: Thank you for the comment. We have added relevant content according to the reviewer’s suggestion. Please refer to Net joint moment. • Comment 19: [LINE 173] “a positive joint moment supports the weight in the normal standing state” needs to be rephrased to be an accurate statement (and I think you want to say ‘body weight’ instead of ‘the weight). I think you’re just trying to suggest that in a lot of species, a positive joint moment as an extensor moment, but that is not the case for reindeer at every joint. I would also suggest that while Vereecke et al 2008 [36] is a fine paper, I’m not sure it’s the most appropriate for citing generalities about extensor moments. That said, I think it would be reasonable to just delete the sentence on line 173 and just state which joints have positive moments for extension and for flexion. Answer: Thank you for the comment. We have deleted relevant content according to the reviewer’s suggestion. Please refer to Net joint moment. • Comment 20: [LINE 205] The sentence beginning “The data of speed” should probably be “Speed data” or “Animal velocity”. Additionally, “normalized by the Froude number and the nondimensionalized speed u” should probably be “normalized by Froude number” since Froude number is a nondimensionalized speed. How did you measure speed? Did you use a joint marker? Was this a mean value from TD to LO? Answer: Thank you for the comment. Yes, we used a joint marker to measure the average velocity of the shoulder joint from TD to LO. Relevant content has been revised according to the reviewer’s suggestion. . Please refer to Gaits and speeds. • Comment 21: [LINE 234] Wouldn’t you expect these variables to differ in a walk vs a trot and at different speeds? Is this different than what you would predict based on other ungulates? Answer: Thank you for the comment. We have added the comparison between the forelimb joints of reindeer and typical ungulates. Please refer to Discussion. • Comment 22: [LINE 312] “Reindeer have permanently enhanced MCP joints” – Relative to what? Answer: Thank you for the comment. This might indicate the MCP joint has good energy storage performance. Please refer to “Zhang R , Ji, Q L , Luo G , et al. Phalangeal joints kinematics during ostrich (struthio camelus) locomotion. Peerj, 2017, 5(1), e2857”. Please refer to Contribution of work change with gaits and speeds. • Comment 23: [LINE 319] Do you present data on contact time to substantiate this? Answer: Thank you for the comment. Compared with the walking trial, the foot-to-ground contact time ratio of the running trial was larger (Fig. 5A). Please refer to Contribution of work change with gaits and speeds. • Comment 24: [LINE 320] ‘…positive and negative works’ should be ‘positive and negative work’. Answer: Thank you for the comments on the paper. We have revised relevant content according to the reviewer’s suggestion. Please refer to Contribution of work change with gaits and speeds. • Comment 25: [LINE 322] Does improved elastic energy storage mean increased? Answer: Thank you for the comments on the paper. Yes, the improved elastic energy storage mean increased. Please refer to Contribution of work change with gaits and speeds. • Comment 26: [LINE 332] Is the hypothesis that increased ROM in reindeer toes is an ecological adaptation a result of the findings of this paper or an existing hypothesis? Answer: Thank you for the comment. We are sorry for the mistake. In fact, the toe joints of reindeer are stable, as the ROMs between interphalangeal joints and MCP joints are smaller than horse forelimbs. Revised relevant content has been revised. Please refer to Comparison between the forelimb joints of reindeer and typical ungulates. • Comment 27: [LINE 352] “…for stability and propulsion through other forms”. Can you elaborate on what you mean by forms? Answer: Thank you for the comments on the paper. We have deleted the sentence, because of the modification of the part of “ Comparison between the forelimb joints of reindeer and typical ungulates”. Please refer to Comparison between the forelimb joints of reindeer and typical ungulates. • Comment 28: [LINE 388-389] If the authors are going to say that these results underlie bionic foot design of extreme environment robots, I think you will need to elaborate on this. Or remove this statement. Answer: Thank you for the comments on the paper. We have removed this statement. Please refer to Conclusions. • Comment 29: [LINE 360, 366, 367] There are some unnecessary placements of “the” – ‘the foot’ ‘the horse knees’. Answer: Thank you for the comments on the paper. We have revised relevant content according to the reviewer’s suggestion. Please refer to Comparison between the forelimb joints of reindeer and typical ungulates. • Comment 30: [LINE 362] I’m not sure that you need to include a discussion of human foot mechanics. I think it would be fine to just discuss mechanics in horses. But, if the authors feel it is important, then they can keep it in. Answer: Thank you for the comments on the paper. We have removed the discussion of human foot mechanics Please refer to Comparison between the forelimb joints of reindeer and typical ungulates. The above revised contents are only a point-by-point response to the reviews. In order to fully understand the revised contents, please read the revised manuscript. "

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