The emergence of epithelia was the foundation of metazoan expansion. Epithelial tissues are a hallmark of metazoans deeply rooted in the evolution of their complex developmental morphogenesis processes. However, studies on the epithelial features of non-bilaterians are still sparse and it remains unclear whether the last common metazoan ancestor possessed a fully functional epithelial toolkit or if it was acquired later during metazoan evolution.To investigate the early evolution of animal epithelia, we sequenced the genome and transcriptomes of two new sponge species to characterize epithelial markers such as the E-cadherin complex and the polarity complexes for all classes  of sponges (phylum Porifera) and compare them with their homologues in Placozoa and in Ctenophora. We found that Placozoa and most sponges possess orthologues of all essential genes encoding proteins characteristic of bilaterian epithelial cells, as well as their conserved interaction domains. In stark contrast, we found that ctenophores lack several major polarity complex components such as the Crumbs complex and Scribble. Furthermore, the E-cadherin ctenophore orthologue exhibits a divergent cytoplasmic domain making it unlikely to interact with its canonical cytoplasmic partners.These unexpected findings challenge the current evolutionary paradigm on the emergence of epithelia. Altogether, our results raise doubt on the homology of protein complexes and structures involved in cell polarity and adhesive-type junctions between Ctenophora and Bilateria epithelia.The online version of this article (10.1186/s12864-018-4715-9) contains supplementary material, which is available to authorized users. Multicellular organisms evolved from unicellular ancestors several times during the evolution of life , 2 resulFrom a morphological point of view, non bilaterian animals display a variety of cell sheet organizations. For example, the basal lamina is absent from all but one sponge classes , 12, in Despite the diversity of epithelial structures among animals, apico-basal cell polarity and AJs are believed to be present in all extant animal phyla , 15, 19.O. lobularis (belonging to the Homoscleromorpha class) and O. minuta (the first Hexactinellida), and used RNA-seq data to help with the annotation procedure. This new data was then combined with information available from public databases to carefully identify and analyze homologues of genes coding for proteins known to compose polarity complexes and adherens junctions for all classes of Porifera , several genera of Ctenophora with contrasted features [In the present study, we first sequenced the genomes of two additional sponge species, features  and Placfeatures , 36, Parfeatures , 37–40. Oopsacas minuta, the assembly yielded a total of 61.46 Mb of unique haploid genome sequence distributed in 365 contigs longer than 1 kb . Following the mapping of 207,529,788 RNAseq reads from a polyA+ cDNA library (mean Open Reading Frame (ORF) coverage = 1443), we predicted the presence of 17,043 protein-coding genes. The small final number of contigs and the above coverage values suggest that our delineation of the (protein-coding) gene content is very close to 100% completion.We used two platforms (Pacific Bioscience and Illumina) and a combination of paired end and mate pair sequencing approaches  to generate and assemble the data. Concerning Oscarella lobularis, we generated and assembled a total of 52.34 Mb of unique haploid genome sequence distributed in 2658 contigs longer than 1 kb . Following the mapping of 231,475,388 RNAseq reads from a polyA+ cDNA library (mean ORF coverage = 710), we predicted the presence of 17,885 protein-coding genes. The large, albeit unavoidable, proportion (> 50%) of sequence data from bacterial and archaean origin, as well as unfavorable (repeated or variable) genome structures caused the final number of contigs to remain significantly larger than for O. minuta. However, the above coverage values remain large enough to correspond to a near 100% complete delineation of the (protein-coding) gene content. The quality of our transcriptomes and genome drafts enables us to be confident on the completion of the predicted proteins and the number of copies found for each candidate gene.Concerning Sycon ciliatum to 32 in Trichoplax adhaerens units) that mediate trans-interactions with the extracellular domain of cadherins on opposing cells;The extracellular cadherin (EC) repeated domains (ranging from 3 in The transmembrane region (TM) and the cytoplasmic tail, which contains the conserved specific binding domain for p120-catenin in the juxta-membrane domain (JMD) and the β-catenin-binding domain (CBD);The epidermal growth factor (EGF) domains and Laminin G (Lam-G) domains in a membrane-proximal position considered typical of non-vertebrate classical cadherins , 42.Classical cadherins contain extracellular repeat domains that mediate trans-interactions with the extracellular domain of cadherins on opposing cells, and a cytoplasmic domain that binds p120 and β-catenin , 41–43. The alignment of E-cad JMD that mediates binding to p120 catenin Fig.  shows thMnemiopsis leidyi, in which the E-cadherin GBM motif is not conserved  confirm the presence of bona fide E-cadherin complexes in the four Porifera classes. Moreover, the motifs governing the interactions between the members of this CCC complex essential for the establishment of adherens junctions appear very conserved in Placozoa, Calcispongiae and Homoscleromorpha. Even if a few substitutions were identified in demosponges and glass sponges that may modulate these interactions and explain the absence of AJs in these two lineages, we can nevertheless infer that the last ancestor of Porifera already possessed all the component needed to build functional adherens junctions similar to those of bilaterians. However, this is probably not true of the ctenophores as their E-cadherin cytoplasmic domain lacks most bona fide E-cadherin cytoplasmic domain binding sites.In nce Fig. , which mThe Par complex made of atypical Protein Kinase C (aPKC), Partition defective 3 (Par3) and Partition defective 6 (Par6);The Scribble complex made of Scribble (Scrib/Src), lethal giant larvae (Lgl) and Disc large (Dlg);The Crumbs complex made of Crumbs (Crb), stardust  in mammals also known as Pals1 (protein associated with Lin-7 1) and Pals1-associated tight junction protein (Patj).Next we investigated whether placozoans, ctenophores, and sponges of all classes, harbor the polarity protein complexes that are necessary for epithelium formation and morphogenesis . There aFirst, we looked for the Par complex, considered to be a metazoan innovation . Par6 coNext, we investigated the presence of the Scribble polarity complex composed of Scrib, Dlg and Lgl members. Members of this complex contain multiple protein-protein interaction domains, in particular PDZ, Src homology 3 (SH3) domain and guanylate kinase (GUK) domains capable of recruiting a complex network of proteins.T. adhaerens (even though the L27 domain is lacking). In ctenophores, Dlg orthologous genes were found without GUK domain. Since Dlg predates the emergence of metazoans  [We identified with high confidence Dlg orthologous genes containing all specific domains (Lin2 and Lin7 binding domain (L27), GUK, SH3 and three PDZ domains) Fig.  in all sosporea) , 36, 51,osporea)  but was osporea) , 24 and M. leidyi, we investigated its presence in two other genera (Pleurobrachia and Beroe) and we confirmed the absence of Scribble homologue (the only LRRs domains we identified belong to other classes). The LRR domain is critical for Scribble function, since in Drosophila Scribble proteins mutated in the LRR domains mimic the complete loss of Scribble protein [Drosophila. The absence of a bona fide Scribble homologue in ctenophores might indicate a change in Dlg/Lgl localization or function.As previously reported, Scrib homologues were identified in all sponge classes  and plac protein . The PDZ protein  and for  protein  in DrosoWe then investigated the conservation of the Crumbs complex in metazoans. Crumbs is a central regulator of epithelial apical actin cytoskeleton organization and adherens junction formation in bilaterians and was proposed to be a metazoan innovation , 23. TheTrichoplax, most likely under evolutionary pressures maintaining the interaction with PDZ containing proteins (Sdt or Par6). A unique exception was found in hexactinellids were the ERLI motif in replaced by ETLI  while O. lobularis has a conserved FBM (RxxxGxYxPT) , which regulates the binding to Moesin, an ERM protein [Trichoplax, suggesting that this regulation by aPKC is an innovation shared by cnidarians and bilaterians (except for Caenorhabditis elegans) since at least one phosphorylation site is present in a Crumbs isoform of cnidarians (Nematostella)  with two essential sequence motifs  Fig. 5a5a. TheseTLI Fig. . This chPT) Fig.  suggestiPT) Fig. . Another protein . These tla) Fig. . Thus, ela) Fig. .Fig. 5a M. leidyi  exhibiting a significant similarity with the conserved cytoplasmic domain, while we identified homologues of transmembrane proteins with extracellular domains made of EGF and laminin-like repeats. This suggests that Crumbs proteins with a classical intracellular domain are present in all extant metazoans except ctenophores. Crumbs proteins interact with Sdt . Sdt encodes a membrane-associated guanylate kinase (MAGUK) protein containing two L27 domains, a single PDZ domain, a SH3 motif, a hook domain and a GUK domain [Oscarella lobularis and to a lesser extent in calcareans and demosponges. As no PatJ homologue was found in ctenophores, we can safely conclude that the whole Crumbs/Sdt/Patj complex is entirely absent in this phylum.Finally, the most unexpected result was the absence of any Crumbs-like gene or transcript in K domain . We idenM. leidyi possesses an E-cadherin-like cytoplasmic sequence divergent enough from canonical E-cadherin to raise doubt on its ability to interact with p120 catenin and with β-catenin. These unexpected findings are shedding a new light on the ongoing controversy about the morpho-anatomy of the last metazoan ancestor based on various phylogenetic reconstructions [By investigating the presence of genes and proteins involved in epithelial polarity and adherens junctions, we found that Placozoa and Porifera (despite some divergence observed in hexactinellids) possess all polarity complex members and adherens junction components. In contrast, ctenophores lack the Crumbs complex and Scribble as homologues of the corresponding genes were not found in currently available species. In addition, ructions , 60–62. ructions , 62, proructions , 61 in aructions , while tIn the context of the ctenophore-first evolutionary scenario, the compromised interactions between catenins and cadherins and the absence of two typical polarity complexes in ctenophora epithelia can be interpreted in two ways. Either it is the result of secondary losses, or it was inherited from an ancestral state. In this later case, it implies that additional components such as the Crumbs complex and p120 binding for E-cadherin were later acquired during the course of evolution in the last common ancestor of sponges and parahoxozoa.Beroe, Pleurobrachia and Mnemiopsis exhibit different epithelial features [. Consequently, gene inventories alone are not sufficient to explain tissue and structure diversity.Interestingly, the epithelial features of Ctenophora are very different , 63, 64 features  despite Altogether, our results raise a doubt on the homology of protein complexes and structures involved in cell polarity and adhesive type junctions between Ctenophora and Bilateria epithelia.Our study strongly advocates for more functional studies of the epithelium-like tissue of all non bilaterian animals. It is also an incentive to develop sponges and ctenophores as new experimental models for cellular biology to elucidate how epithelial cell layers that are key to the rise of animal diversity emerged throughout evolution.Oscarella lobularis (Schmidt 1862) and Oopsacas minuta Topsent, 1927 were collected by SCUBA diving in the north-western Mediterranean Sea (Marseille Bay). All new sequences are available on NCBI website: accession numbers and links are provided in Additional file  Schmidt 862 and OOscarella lobularis genome sequencing was performed using Illumina technology with DNA-seq paired-end and Nextera mate pair protocols on a HiSeq2500 sequencer. Adapter sequences were removed and low-quality bases were trimmed using Cutadapt [Cutadapt . RemainiCutadapt , PlatanuCutadapt , GapFillCutadapt  and cap3Cutadapt . A transCutadapt  to all cCutadapt  to prediCutadapt  to refinCutadapt , the covOopsacas minuta genome sequencing was first performed in the same conditions as Oscarella lobularis. In addition, a second genome sequencing step was performed using PacBio technology on an isolated sponge fragment to limit bacterial contaminations. These long reads were filtered based on their length and quality with Pacific Biosciences (PacBio) tools  then self-corrected with canu [Oscarella lobularis genome was applied to predict proteins and their functions. The mapping of the individual read to the Genome and transcriptome assembly resulted into an estimated coverage of 381, again ensuring a near 100% completeness of the gene content.ith canu . All Illith canu . The numith canu  and BLASith canu , Pilon [ith canu  and GapFO. lobularis and O. minuta de novo assembled genomes and transcriptomes (this work), and on available poriferan, placozoan, cnidarian and ctenophoran genomes and/or transcriptomes retrieved from the sources listed in Additional file D. melanogaster, M. musculus and A. queenslandica Epithelial cadherin, Crumbs, PAR and Scribble complexes retrieved from NCBI database were used to perform reciprocal best-hits with BLAST 2.3.0 run locally using an E-value cutoff of 10− 5.Epithelial hallmarks were investigated using data from various sources: http://exon.gatech.edu/gmhmme.cgi) [http://genes.mit.edu/GENSCAN.html) [http://bioinf.uni-greifswald.de/augustus/) [http://www.softberry.com/) [http://pfam.xfam.org/) run locally [http://www.ebi.ac.uk/interpro/) [http://smart.embl-heidelberg.de/) [Ab initio protein-coding gene prediction was performed on the best candidate genomic and/or transcriptomic contigs with GeneMark.hmm eukaryotic web serveur (mme.cgi) , GenScanAN.html) , Augustugustus/)  run locary.com/) . Protein locally , InterPrterpro/)  and SMARerg.de/) .http://mafft.cbrc.jp/alignment/server/) and/or MUSCLE v3.8.31 [http://hmmer.org/) using aligned sequences with an E-value cutoff of 10− 5. Retrieved motifs of potential homologues to the protein queries were used as new baits to recompute HMM profiles and perform further HMM searches. C-terminal characteristic parts were used to build HMM profiles of Crumbs and E-cadherin proteins.The newly identified early branching metazoan proteins were added to the previous database sequences for iterative BLAST searches to identify more potential homologues. Proteins containing repeated domains generate false positive and best-hits characteristic of protein motifs and /or domains were used to enhance the detection of real homologues. These motifs and domains were aligned with MAFFT.7  (http:// v3.8.31  (impleme v3.8.31 ) dependiSince Lin2/Lin7 (L27) (N)-terminal domain is important in the mediation of MAGUK family protein interactions with other proteins, a particular attention was given to this domain. To identify all potential MAGUK proteins, local BLAST searches (BLASTp and tBLASTn) were performed against complete or on-going genome projects - and (C)- terminal regions predicted on two different contigs, including L27 and PDZ domains on the first contig and the remaining PDZ domains on a second contig merged with Emboss merger webtool (http://www.bioinformatics.nl/cgi-bin/emboss/merger).L27 domain HMM searches led also to the identification of PATJ homologues but for some proteins containing multiple PDZ domains (MPDZ) no L27 domain was detected. For MPDZ lacking the L27 domain, a BLASTp was run locally using the PDZ domains retrieved from the Pfam database (PF00595) as reference. This step led to the identification of In addition to protein domain analyses, conservation of critical residues was investigated on aligned sequences according to previous publications. Alignments were visualized with JalView 2.9 using Clustalx amino acids color display .To confirm the annotation of identified sponge genes as well as other early branching metazoans, a maximum likelihood (ML) analysis with 100 bootstraps was conducted using PhyML v3.1  . This phylogeny includes MAGUK, Dlg, LRR and GUK domain, Zonula occludens (ZO), Caspase recruitment family (CARMA). Membrane-associated Guanylate kinase Inverted (MAGI) and Calcium channel β-subunit (CACNB) classes were also included even MAGI do not have a SH3 domain, their GUK domain is truncated, and Calcium Voltage-gated Channel auxiliary subunit beta (CACNB) are divergent.Once all proteins of MPP classes were clearly identified, another phylogenetic analysis was performed including the PDZ domains besides the SH3 + GUK domains previously used.The PATJ/MUPP-1/DLG/LIN phylogeny was performed on sequences identified using the L27 domains and the two following PDZ domains (except for the LIN family that exhibits a single PDZ domain).All sequences annotated and analyzed are listed in Additional file Additional file 1:Figure S1A. Comparison of p120 sequences. Residues involved in interaction with E-cadherin are boxed in red. Most of them are conserved. Figure S1B. Comparison of β-catenin sequences. A single β-catenin gene copy was identified in every studied species except for calcareous sponges that exhibit a duplication. All residues essential for E-cadherin interaction are boxed in pink and are highly conserved except for the R386 and N387 residues  in two hexactinellids and a more anecdotal change from A656 to S in placozoans. Residues boxed in blue are involved in α-catenin binding and in orange for the DTDL PDZ binding motif. Figure S1C. Analyses of α-catenins and vinculins sequences. Sequences of α-catenins and vinculins were aligned based on the structural domains helix0 to helix5 in Mus musculus α-catenin and vinculin. Helices are boxed and the numbers at the end of each sequence indicate the range encompassed in the alignment. Secondary structure prediction by JNet  identified six helices in all sponge α-catenin sequences except for A. queenslandica (missing the 4 first helices) and A. vastus (missing helix0). All species analyzed in this study have one copy of α-catenin and one copy of vinculin well-separated in Bayesian tree with high support (pp = 1) (bottom). Figure S2. Structure of Par3 proteins in metazoans. Par3 exhibits a conserved N-terminal domain (CR1), three central PDZ domains, and a C-terminal region containing multiple protein binding sites including the aPKC-binding motif. Figure S5. Domain composition of PatJ (D. melanogaster), INADL and MUPP1 (M. musculus) and Multiple PDZ containing protein (MPDZ) . Note that only O. lobularis exhibits an MPDZ with a well-detected L27 domain  as bilaterians. A. queenslandica and S. ciliatum MPDZ have a low-scoring L27 domain (shaded in grey) according to the HMM profile search. There is no recognizable similarity to the L27 domain in the N- terminal region of O. minuta MPDZ. Tables S1. and S2. Information on the domain structures of the Lethal giant larvae (LGL) and Scribble (Src) proteins in various metazoans. Spreadsheet containing Tables S3. and S4. The spreadsheet contains information on the characteristics of the new private databases and public databases (nature = genome/transcriptome) and links for new sequences used in this study. Spreadsheet containing Tables S5. and S6. The spreadsheet contains information on the accession numbers or contig/scaffold references where candidate genes were identified. In bold accession numbers of sequences annotated from our new transcriptomic and genomic sponge datasets. Links for new sequences used in this study are provided. (PDF 2610 kb)


Apis mellifera) are principal insect pollinators, whose worldwide distribution and abundance is known to largely depend on climatic conditions. However, the presence records dataset on potential distribution of honeybees in Indian Ocean Islands remain less documented. Presence records in shape format and probability of occurrence of honeybees with different temperature change scenarios is provided in this article across Zanzibar Island. Maximum entropy (Maxent) package was used to analyse the potential distribution of honeybees. The dataset provides information on the current and future distribution of the honey bees in Zanzibar Island. The dataset is of great importance for improving stakeholders understanding of the role of temperature change on the spatial distribution of honeybees.Honeybees ( Specifications TableValue of the data•The data provide information on the potential spatial distribution of honeybees in both Unguja and Pemba Islands in Zanzibar and which is accessible for reuse.•The data provide interesting and important information on future honeybee's distribution expansion in both Unguja and Pemba Islands in Zanzibar.•The data can be used for modeling the effect of climate change and land use/ cover on honeybee's distribution in Indian Ocean Islands, in particular Zanzibar Island.•The data can be useful for study genetic diversity of honeybees in Zanzibar Island.•The data are important to different stakeholder include beekeeper communities, policy makers, international and local non-government organization engaged in apiculture intervention, researchers, scholars and academics.12htt://www.york.ac.uk) of the Representative Concentration Pathways Scenarios, Fifth Assessment Report (RCPs-AR5) The dataset collected in this study is located in Zanzibar Island in Eastern and South Eastern coast of Africa


The fungal kingdom potentially has the most complex chitin synthase (CHS) gene family, but evolution of the fungal CHS gene family and its diversification to fulfill multiple functions remain to be elucidated. Here, we identified the full complement of CHSs from 231 fungal species. Using the largest dataset to date, we characterized the evolution of the fungal CHS gene family using phylogenetic and domain structure analysis. Gene duplication, domain recombination and accretion are major mechanisms underlying the diversification of the fungal CHS gene family, producing at least 7 CHS classes. Contraction of the CHS gene family is morphology-specific, with significant loss in unicellular fungi, whereas family expansion is lineage-specific with obvious expansion in early-diverging fungi. ClassV and ClassVII CHSs with the same domain structure were produced by the recruitment of domains PF00063 and PF08766 and subsequent duplications. Comparative analysis of their functions in multiple fungal species shows that the emergence of ClassV and ClassVII CHSs is important for the morphogenesis of filamentous fungi, development of pathogenicity in pathogenic fungi, and heat stress tolerance in Pezizomycotina fungi. This work reveals the evolution of the fungal CHS gene family, and its correlation with fungal morphogenesis and adaptation to ecological niches. The fungal kingdom, with an estimated 1.5 million different species, displays extraordinary evolutionary diversity, which is reflected in different life histories, developmental processes and ecological niches25et al. categorized the fungal CHSs into 8 classes using phylogenetic analyses, which had not been reported in previous studies investigating fungal CHSsThe fungal kingdom could be one of the eukaryotic groups with the most complex CHS gene family, but the number of CHSs varies significantly among fungi. One to 3 CHSs have been found in yeasts, whereas filamentous fungi usually have approximately 7 CHSs, with some species possessing more than 20 CHSs5101112Aspergillus nidulans, Colletrotrichum graminicola, Fusarium verticilliodes, Aspergillus fumigatus, Neurospora crassa and Ustilago maydis1617181920212223Botrytis cinerea25A. nidulans and A. fumigatus27A functional genomics conundrum concerns how a complex protein family such as the CHS gene family can diversify to fulfill multiple functionsMetarhizium robertsii. By analyzing the biological functions of CHSs in multiple fungal species, we investigated the relationship between the evolution of the fungal CHS gene family and development of fungal pathogenicity, heat stress tolerance and morphogenesis.In this study, we identified the full complement of CHSs from 231 fungal species encompassing 9 fungal phyla. Using the largest dataset to date, we characterized the evolution of the fungal CHS family using phylogenetic and domain structure analyses. The biological functions of CHSs have been characterized in fungi that are pathogenic to mammal, plants and in many saprophytic fungi. In this study, we characterized the biological functions of CHSs in the model insect pathogenic fungus Using an HMM (hidden Markov model) search, we retrieved putative CHSs from 231 fungal species encompassing 9 fungal phyla: Ascomycota, Basidiomycota, Glomeromycota, Zygomycota, Blastocladiomycota, Chytridiomycota, Neocallimastigomycota, Microsporidia, and Cryptomycota . False p61112The CON1 region that is encompassed by the QXXEY, QXRRW, and EDRXL motifs was extracted from the 1,571 CHSs; the length of CON1 regions varied among fungi . The lenThe dominant evolutionary mechanisms for expansion of the protein repertoire are duplication, divergence, and recombination of the domainsThree hundred and ten CHSs had Type A1, A3, B1 or B3 domain structures and were randomly scattered throughout the phylogenetic tree of CON1 ; there w65101112Rhizobium. spp  CHSs in 22 species from Metazoa, Choanoflagellida, Amoebozoa, Alveolata and Stramenopiles, and their domain structure were also analyzed . Ten bacium. spp  and usedium. spp  for the ium. spp . The claBecause the master tree  containsTo illustrate the expansion and contraction of the CHS gene family, the number of CHSs in each of the 231 fungal species was mapped to a fungal phylogenetic tree that was modified from the fungal life tree at JGI by replacing the parts consisting of Basidiomycota, Ascomycota, and Zygomycota with published phylogenetic treesThe average number of CHSs in the early-diverging fungi  was 16.5. Strikingly, almost all of the early-diverging fungi had multiple unclassified CHSs that had a Type B1 domain structure. CHSVI was identified in only 3 early-diverging fungal species.Enterocytozoon bieneusi) had 5 CHSs, and 2 species lacked CHSs. All of the other 14 species had 1 CHS. Excluding Edhazardia aedis, which had CHS IV, the other microsporidial species only had the unclassified CHSs with a Type B1 domain structure. In the basal fungus Rozella allomycis in Cryptomycota, only Division 2 CHSs (CHSIV and CHSV) were identified.Only one microsporidial species . There is one gene for each of 7 CHS classes in the 3 fungi, and all Chs genes had been previously disrupted in M. oryzae12Chs genes in M. robertsii (Chs mutant strains were significantly different from the wild type strain (WT), and consequently we did not describe these data and results in the text; however, they are presented in the figures and tables.Among the 95 Pezizomycotina fungi with mophilum , or theyobertsii . DetailsN. crassa, growth of the ChsV and ChsVII mutants was significantly inhibited by heat stress; ChsVI was also involved in heat stress tolerance   . The patirulence .ΔChsV, ΔChsVII and ΔChsVΔChsVII produced deformed appressoria (the infection structure) containing a large vacuole-like structure , the growth and conidial yields of ΔChsII, ΔChsIII, ΔChsIV and ΔChsVI were not significantly different from those of WT; however, compared with WT, the growth of ΔChsI, ΔChsV and ΔChsVII was significantly inhibited  (ructure)  and S6, ructure) . There wructure) .In the present study, two major mechanisms were found to drive the evolution of the CHS gene family, resulting in at least 7 classes of CHSs in the fungal kingdom. One mechanism is gene duplication and subfunctionalization. The second mechanism is domain recombination and domain accretion, which occurred in the paralogs generated from gene duplications, as supported by the consistency between the CHS phylogeny and domain structure observed herein . Fungal 6Thalassiosira pseudonana CCMP1335). T. pseudonana could have acquired PF00173 via independent domain recruitment. In the fungal kingdom, the protein resulting from the recruitment of PF00173 could duplicate, with one paralog retaining its original domain structure to become CHSIV. The other paralog could have undergone domain accretion by recruiting PF00063 and PF08766, and the resulting gene duplicated to produce CHSV and CHSVII. Although PF00063 was also identified in 4 CHSs in lophotrochozoans, fungal and lophotrochozoan PF00063 emerged from different kinds of myosinCryptomycota contains CHSIV and CHSV, but not CHSVII, the ancestor of CHSV and CHSVII might have undergone a duplication event after the divergence of the ancestor of the basal fungus from that of other fungi; this duplication could have occurred independently in taxonomically distinct fungi. In the Basidiomycota and early-diverging fungi, this duplication event could be ectopic because ChsV and ChsVII appeared to be scattered randomly throughout the genomes; in contrast, in the Ascomycota, a tandem duplication could have occurred because ChsV and ChsVII exhibit a head-to-head arrangement on the chromosome in 95% of this group of fungi. This tandem duplication could have taken place during the emergence of the Pezizomycota, but it is also possible that it occurred during the emergence of the Ascomycota with a subsequent loss of the product in subphyla other than the Pezizomycota.Fungal Division 2 CHSs have an intact PF03142, and they could share an ancestor with CHSs from the kingdoms Choanoflaggelida, Metazoa, Amoebozoa or Stramenopiles. The ancestor of Division 2 CHSs could experience domain accretion , resultiM. robertsii, M. oryzae and N. crassa. Previous studies have shown that CHSV and CHSVII are also involved in heat stress tolerance in A. fumigatus35A. fumigatus must overcome the host body temperature to achieve successful infection. Fungal infection induces behavioral fever in some insects such as locusts, in which insects raise their body temperature as a means of literally toasting a fungal invader; CHSV and CHSVII could be required by M. robertsii to evade such behavioral immunity. CHSV and CHSVII are also involved in the formation of the infection structure (appressorium) in M. robertsii. As in M. robertsii, CHSV and CHSVII are also involved in appressorial formation in plant pathogenic fungi12161718M. robertsii to proliferate in insects and thus for infection. Therefore, the emergence of CHSV and CHSVII is important for many fungi to adapt to their respective ecological niches.The emergence of CHSV and CHSVII is important for the development of fungal heat stress tolerance and pathogenicity in pathogenic fungi. Heat stress is a common abiotic stress that many fungi encounter in nature. In this study, we found that CHSV and CHSVII are involved in heat stress tolerance in 3 Pezizomycotina fungi: M. robertsii, N. crassa and A. fumigatus, but only CHSVII (not CHSV) is involved in heat stress tolerance in M. oryzae. In addition, CHSV and CHSVII are independently, i.e., not redundantly and compensatorily, important for aerial hyphal growth and conidiation in M. robertsii (in this study). In contrast, CHSV and CHSVII in A. nidulans perform compensatory functions in hyphal growth and conidiation2021Diversities also exist in the biological functions of CHSV and CHSVII among different fungi. For example, both CHSV and CHSVII are important for heat stress tolerance in Edhazardia aedis, which has CHS IV, 14 other microsporidial species only contain the unclassified CHSs containing the Type B1 domain structure. Microsporidia have the smallest known (nuclear) eukaryotic genomes because their parasitic lifestyle has led to the loss of many genesBased on the above analysis, all classes of fungal CHSs resulted from ancient domain recombination, domain accretion and gene duplications. However, the expansion and loss of CHSs have been commonly observed in the fungal kingdom. The loss of CHSs appears to be morphology-specific because it occurred most frequently in unicellular fungi . DivisioAllomyces macrogynus having the largest copy number (16) of such a CHS. The expansion of CHSIII and CHSIV has also been observed in most early-diverging fungi. Compared with the Ascomycota and Basidiomycota fungi, little is known about the biology of the early-diverging fungi and the biological functions of CHSs. Therefore, it is currently difficult to determine the contribution of the expansion of CHSs to the environmental adaptation of early-diverging fungi.The expansion of CHSs appears to be lineage-specific. Clear expansion has been observed in all 15 early-diverging fungi, with 16.5 CHSs per species, which is almost 3 times greater than the 5.8 CHSs per species determined in dikarya fungi . A clearIn conclusion, we identified the full complement of CHSs from 231 fungal species encompassing 9 phyla. Using the largest dataset to date, we characterized the evolution of the CHS gene family in the fungal kingdom based on phylogenetic and domain structure analyses. Gene duplication, domain recombination and accretion are major mechanisms underlying the diversification of the fungal CHS gene family. Contraction of the CHS gene family appears to be morphology-specific, with a significant loss of CHSs in unicellular fungi; in contrast, expansion is lineage-specific, with obvious expansion in early-diverging fungi. CHSV and CHSVII that have the same domain structure were produced by recruitment of the domains PF00063 and PF08766 and subsequent duplications; a comparative analysis of their biological functions in different fungi showed that such evolutionary events are important for the morphogenesis of filamentous fungi, development of pathogenicity in pathogenic fungi, and heat stress tolerance in Pezizomycotina fungi. The present work significantly advances our understanding of the evolution of the CHS gene family in the fungal kingdom and its correlation with fungal morphogenesis and adaptation to ecological niches.hmmbuild and hmmsearch in HMMER 3.1b1 (http://hmmer.org/) to implement the search experiments with default parameters .An HMM search was conducted to identify the full complement of CHS family members from a fungal genome. The protein databases of 231 fungal species were individually downloaded from NCBI  or JGI . Twenty-four CHSs that have been functionally characterized in previous studies  were useThree selection criteria were used to remove false positives from the HMM search. The first criterion was the presence of characteristic CHS domains (cd04190 from the CDD database and PF03142 from the Pfam database). The second criterion was the presence of conserved CON1 motifs 5Rhizobium were manually downloaded from the NCBI databases.The CHSs from non-fungi eukaryotes and the NodC proteins from The CON1 region in all CHSs was extracted using a local Perl script for the phylogenetic analysis. The protein sequences were aligned using MUSCLE 3.7 with default parametershttp://pfam.xfam.org/).Domains in CHSs were identified using the Batch Search program provided in the PFAM database  as previously describedDevelopment of the appressorium was observed against the hindwing of G. mellonella larvae  as previously described50 (the time required to kill 50% of the G. mellonella larvae) was determined using the SPSS Statistical Package . All bioassays were repeated three times with 30 insects per replicate. ΔChsV, ΔChsVII, and ΔChsVΔChsVII had a very low conidial yield, and sufficient conidia could not be obtained to prepare a conidial suspension at 107 conidia/mL, which is a common concentration used for bioassays of M. robertsii6conidia/mL were thus used in this study.Bioassays were conducted using last instar M. robertsii and M. oryzae. For M. robertsii, 5 μL of the conidial suspension (105conidia/mL) was applied to the center of a PDA plate and then allowed to grow. For M. oryzae, 200 μL of the conidial suspension (104 conidia/mL) was evenly plated on a PDA plate and allowed to grow at 27 °C for 5 days; a piece of mycelium with agar (diameter = 3 mm) was obtained from the plate and placed at the center of a new PDA plate and allowed to grow. The diameter of the colony was recorded daily for 5 days after inoculation. N. crassa produces fluffy a colony on PDA plates, and its colony diameter cannot be measured; its growth under heat stress was thus characterized by measuring the dry biomass cultured in Sabouraud dextrose broth (104 conidia in 100 mL of medium) at 42 °C for 5 days.Tolerance to heat stress was tested by measuring growth on PDA at 35 °C for How to cite this article: Liu, R. et al. Evolution of the chitin synthase gene family correlates with fungal morphogenesis and adaption to ecological niches. Sci. Rep.7, 44527; doi: 10.1038/srep44527 (2017).Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Mycoplasma hyopneumoniae, Actinobacillus pleuropneumoniae, porcine circovirus type II, porcine reproductive and respiratory syndrome virus, and Lawsonia intracellularis. Comparison was made to the change after a randomly selected date in herds not vaccinating against each of the infections. Danish sow herds initiating vaccination during 2007–2013 were included . Danish sow herds with no use of the vaccine in question were included as non-exposed herds . Antimicrobial prescriptions for weaners in sow herds and for finishers in receiving herds were extracted from the VetStat database for a period of 12 months before and 6–18 months after the first purchase of vaccine, or random date and quantified as average animal daily doses (ADDs) per 100 animals per day. The herd-level difference between ADD in the period after and before vaccination was the outcome in linear regression models for weaner pigs, and linear mixed-effects models for finishing pigs, taking into account sow herds delivering pigs to two or more finisher herds. Three plausible risk factors  and five confounders  were initially considered in all 10 models. The main significant effect in all models was the Baseline ADD; the higher the Baseline ADD was for weaner and finishing pigs, the larger the decrease in ADD was following vaccination (or random date for non-vaccinating herds). Regardless of vaccination status, almost equal proportions of herds experienced a decrease and an increase in ADD resulting in no overall Change in ADD. Furthermore, only minor effects were found, when vaccinations were used in combination. In conclusion, this study provided little support for the hypothesis that vaccination against five common endemic diseases provides a plausible general strategy to reduce antimicrobial use in Danish pig herds.It is often stated that vaccines may help reduce antimicrobial use in swine production. However, limited evidence is available outside clinical trials. We studied the change in amounts of antimicrobials prescribed for weaners and finishers in herds following initiation of vaccination against five common endemic infections:  Due to its large production, the Danish pig sector accounts for 76% of the total amount of antimicrobial substances used for livestock production per year in the country . OfficiaFor animal welfare and productivity reasons, diseased animals should be treated. However, an increased or improved use of vaccination has been suggested as a potential strategy to prevent specific diseases and/or secondary infections . Today, Mycoplasma hyopneumoniae (MYC), porcine circovirus type II (PCV2), Actinobacillus pleuropneumoniae (APP), porcine reproductive and respiratory syndrome (PRRS) virus, and Lawsonia intracellularis (LAW) represent some of the most important disease agents related to these indications, which are also preventable through vaccination of breeding animals and/or offspring.In Danish pig production, the majority of antimicrobials are used for treatment of gastrointestinal and respiratory indications in weaner pigs from 7–30 kg, followed by treatment of gastrointestinal indications in finishing pigs . Mycoplasma hyopneumoniae is a bacterium causing enzootic pneumonia in pigs. Enzootic pneumonia is most often seen in finishing pigs, where it is associated with productivity losses. The bacteria are considered to be present in all Danish conventional pig herds and in 67% of SPF herds  in weaner pigs. Nowadays, problems are mainly related to reduced growth and increased mortality in finishing pigs. PCV2 has an immuno-suppressive effect, which potentiates the impact of other pathogens, resulting in a need for antimicrobial treatment . TherefoActinobacillus pleuropneumoniae is a bacterium causing pleuropneumonia in pigs and is associated with reduced growth and increased mortality, primarily in finishing pigs. There are 15 different serotypes producing a combination of two or more of the four toxins responsible for the pathology leading to disease in pigs . In order to be considered a farrow-to-finisher production, the number of Weaner and Finisher pen places had to be at least 1.5 times the number of sow pen places, indicating that at least part of the offspring remained in the herd until the finishing stage.Type 1: farrow-to-finisher herds, which contained age groups Sows, Weaners, and Finishers registered under one CHR number (source herd) and with movement of growing pigs to herds with age group Finishers (receiving herd).Type 2: herds with age groups Sows and Weaners registered under one CHR number (source herd) and with movement of growing pigs to herds with age group Finishers (receiving herd).Type 3: herds with age groups Sows, Weaners, and Finishers registered under one CHR number (source herd) and with movement of growing pigs to herds with age groups Weaners and Finishers (receiving herd).Type 4: herds with age groups Sows and Weaners registered under one CHR number (source herd) and with movement of growing pigs to herds with age groups Weaners and Finishers (receiving herd).Type 5: herds with age groups Full-line conventional pig herds were identified using yearly data extractions from the Central Husbandry Register (CHR) and quarterly extractions of movements between pig herds from the Danish Pig Movement Database. The following types of herds were identified and included Figure :Type 1:It was a requirement that each receiving herd only received pigs from one source herd in each quarter of a year, whereas source herds could deliver pigs to more than one finisher pig herd. Moreover, only source herds with a minimum of 100 sow pen places and a minimum number of weaner pen places equal to or higher than 1.5 times the number of sow pen places were included, to make sure these herds were not sow-only or weaner-only. For receiving herds to be included, a minimum of 100 finisher pen places was required.No prior purchase of the vaccine in question either in the source herd or receiving herds from January 1, 2005.Purchase of the vaccine for at least 1 year following the first purchase.Purchase of more than a minimum threshold of vaccine doses per year per sow. The minimum of doses was determined based on evaluation of a histogram showing the distribution of vaccine coverage. The vaccine coverage was calculated as the number of doses in the first year of vaccination divided by the number of sows registered in the individual herd multiplied with 25, representing the average number of weaned pigs per sow per year in Denmark. For MYC and PCV2, the threshold was set at >0.5 and <1.5 corresponding to herds with a vaccine coverage between 50 and 150%. This large a margin around the 100% coverage was needed in order to include those herds representing the area on the histogram with the majority of the observations. For LAW, APP, and PRRS, the threshold was lowered in order to avoid too many herds being excluded due to this criterion. Therefore, only an upper threshold was set at <1.5.To study the effect of initiating vaccination against MYC, PCV2, APP, PRRS, and LAW, 10 different longitudinal studies were carried out on historical data; for each vaccine group, one study was made on the effect on antimicrobial use in weaner and finishing pigs. Purchase of vaccines for Danish pig herds is recorded in the Danish VetStat Database (VetStat). Data used in this study were raw historical data from VetStat, retrieved on June 1, 2015. Purchase of all vaccine products against the five disease agents was extracted for the source herds. All herds with their first purchase of a vaccine under study between January 1, 2007, and December 31, 2013, were included. A sow herd was considered to have initiated vaccination in this period and was included in the analyses if it fulfilled the following criteria:Non-vaccinating herds were identified based on extraction of all active source herds in CHR with no purchase of the vaccine in question, at any time within the period between January 1, 2005, and April 30, 2015. A herd was considered active when having recordings of antimicrobial prescriptions in VetStat for all quarters, in a period of 12 months before and 18 months after the first vaccine purchase.For each analysis, information about purchase of the remaining four types of vaccines within the period studied for each herd was included. For this, data on the general purchase of the vaccines in the period from January 1, 2005, until April 30, 2015, were extracted and summarized by quarter of the year, to be able to match correctly with the selected study period for each herd included. For a herd to be considered using other vaccines, the herd had to have purchased the given vaccine for at least 1 year in total and within at least one quarter of the study period for the individual herd.Herd-level antimicrobial prescription data extracted from the raw VetStat data were used in this study as a proxy for antimicrobial use. All prescriptions of antimicrobials, irrespective of indication for weaner and finishing pigs, were included in the study. For farrow-to-finisher herds, data on antimicrobial prescription for weaner and finishing pigs were extracted for the individual herd. For full-line herds identified using movement data, data on antimicrobial prescription for weaner pigs were extracted from the source herd, while for finishing pigs data were extracted from the receiving herds Figure .Antimicrobial data for weaner and finishing pigs were extracted for a period of 2.5 years. This consisted of data from 1 year before vaccination was initiated, until 1.5 years after vaccination was initiated. The period of the first 6 months after vaccination was initiated was considered a transition period, in which not all weaner and finishing pigs entering the stables had been vaccinated yet. Data from this period were excluded for the data analyses. Each prescription was converted into a number of ADD, using standardized doses per antimicrobial product developed by the Danish Veterinary and Food Administration. The ADD takes into account a standard average weight of a weaner pig (15 kg) and a finishing pig (50 kg), as well as the total amount and dose of the antimicrobial prescribed. All prescriptions in ADD were divided into quarterly prescriptions for each herd, over the given period of 2.5 years selected for analysis. Each herd had to have prescriptions in each of the quarters within this study period, in order to be considered an active producing herd and, therefore, be included in the study. The number of weaner and finishing pigs in each herd at the time of vaccination was provided by data from the CHR. These numbers were used in the calculation of the average ADD per 100 weaners per day, and of ADD per 100 finishers per day, in the 1-year period before (Baseline ADD) and 6–18 months after vaccination was initiated (ADD After) in each herd. The change in amount of prescribed antimicrobials (Change in ADD) following initiation of vaccination was calculated for each herd by subtracting Baseline ADD from the ADD After.For herds not vaccinating against a specific pathogen , a random date was chosen in the same period as for the vaccinating herds , and the same set-up was used around this date; antimicrobial prescription during 1 year before the random date was included, followed by 6 months of data, which were excluded, and then data on antimicrobial prescription covering 1 year were included. Also, Change in ADD was calculated for these herds, which acted as a comparison group. It should be noted that, in the analyses, it was still taken into account whether these herds that were not exposed to the specific vaccine in question  were vaccinated against any of the other vaccines .On rare occasions, prescription entry errors occur in the VetStat database, resulting in either negative or extreme values, when calculating ADD over a selected time period. When negative values of ADD were identified, the corresponding herd was excluded from the study. Also, a few herds with extremely high ADD values (>60 ADD/100 weaners/day and >20 ADD/100 finishers/day) were excluded, as these most likely reflected recording errors or dramatic unregistered changes in the herd population.Vaccination: categorical variable with two levels; “Yes” and “No,” representing vaccinating (exposed) and non-vaccinating (non-exposed) herds, respectively.Baseline ADD: continuous variable, representing a baseline measure of antimicrobial use. It was estimated as the antimicrobial prescription 1 year before vaccination (or random date for the non-vaccinating group), in average ADD per 100 animals per day, for weaned and finishing pig.Other vaccines: four categorical variables, one for each of the other four vaccines than the one under investigation in each study, with two levels; “Yes” and “No,” representing source herds that were or not using another vaccine when vaccination with the study-specific vaccine started.In all models, the outcome variable was the Change in ADD, and this variable was included as a continuous variable after checking for linearity. Three variables were tested as potential explanatory variables for Change in ADD:Sows: the number of sows in the individual source herd was included as a continuous variable, representing the herd size.Year: the year of the first purchase of vaccine (or random date) was included as a categorical variable, representing the different changes and levels of antimicrobial use, which has been seen in Danish pig production between 2007 and 2013. After initial analyses with individual years, this variable was further grouped into “Before 2010” (<2010) and “After 2010” (≥2010), representing the period before and after the Yellow Card Scheme was implemented in Denmark.Season: because it is known that antimicrobial use can fluctuate by season and a farmer may be more likely to initiate vaccination during seasons with high antimicrobial use, the season might confound the estimate of the effect of initiating vaccination. Therefore, the quarter of the year of the first purchase of vaccine (or random date for non-vaccinating herds) was included, to account for season as a categorical variable with four levels; “1,” “2,” “3,” and “4,” representing the first to the fourth quarter of the year.SPF: categorical variable with two levels; “SPF” and “Non-SPF,” representing source herds enrolled or not in the SPF system at the time of vaccination (or random date), respectively. Information about enrollment of each herd in the Danish SPF system was provided by SEGES Pig Research Centre (SEGES). The SPF variable was used as a measure of herd health status and considered as a potential confounder, as herds in the SPF system might have a better health status than non-SPF herds, which may influence the antimicrobial use in those herds.Export: categorical variable with two levels; “Yes” and “No,” representing source herds with and without export of growing pigs, respectively. For each herd, information about exporting of animals was assessed using the Danish Pig Movement Database, which contains all movements of animals from Danish herds to other countries. Besides having moved animals from the source to the receiving herd, some of the herds had also exported either 7 or 30 kg weaner pigs to other countries. This information was included as a potential confounder in the analyses, as importers might demand that pigs are vaccinated against specific diseases, even if the Danish herd was not infected with the given disease agent.In addition, five variables were included as potential confounders:Continuous variables were plotted against the outcome variable and against each other, to visually check for linearity and correlations. For categorical variables, distributions were checked for a reasonable number of observations in each variable level.All statistical analyses and data management were carried out using the software R version 3.1.3. Separate data analysis was conducted for each of the 10 models, representing the effect of the five types of vaccines in weaner and finishing pig herds. General linear regression models were used to model the Change in ADD for weaner pigs as a function of the potential explanatory variables and covariates.lme4 package in R , with the AIC closest to 0 indicating the best model. Confounding was assessed by evaluating the models with and without each of the potential confounders. A variable was considered a confounder, if it changed the parameter estimates of any of the other significant variables by >20%. When an interaction between vaccination with the study-specific vaccine and one of the other vaccines was statistically significant, the two were recoded as a four-way variable, to be included in the final multivariable model, allowing for the estimation of the effect and significance of each category defined by the pairwise combination of vaccination statuses . The statistical significance of differences observed between the four categories was assessed with Tukey’s “Honest Significant Difference” method, using the multcomp package in R. The final models were presented with parameter estimates including SE and P-values, as well as the explanatory degree of the model.The same variables were used to model the Change in ADD for finishers in a linear mixed-effects model, using the age in R . Source R2. ‘The explanatory degree’ of the mixed-effects models was assessed using the marginal pseudo-R2: (Re − Rfm)/Re, where Re is the residual variance of the model, only containing the random effect of source herd, and Rfm is the residual variance of the final model .There were no substantial differences between the mean and median values for Change in ADD, Baseline ADD, and Sows. Therefore, it was chosen to present the mean. Overall, the mean Change in ADD was close to 0, but with a large range, especially for weaner pigs. As expected, the largest Baseline ADD was found among weaner pigs, with a nearly five times higher Baseline ADD than observed for finishers. The mean number of sows in the farrow-to-finisher and source herds only differed 1–7% between the studies on effect in weaner and finishing . This happened because nearly the same source herds were used in the analyses for weaners and finishers for each type of vaccine.For each of the 10 studies, there were between 71 and 334 vaccinating source herds delivering pigs to between 89 and 365 receiving herds. For the group of non-vaccinating herds, there were between 130 and 570 source herds delivering pigs to between 158 and 662 receiving herds, in each of the studies.A summary of the main findings from each of the final regression models is presented in Table No study-specific vaccinations were found to have a significant impact on the antimicrobial consumption, when analyzed independently. The baseline antimicrobial consumption before initiation of vaccination (Baseline ADD) was the only consistently significant independent variable in all models, indicating that herds with a higher Baseline ADD obtained a larger reduction in ADD, when compared to herds with a lower Baseline ADD. The interaction between Baseline ADD and vaccination status was non-significant in all models, meaning that the effect of Baseline ADD was the same for herds initiating vaccination as for non-vaccinating herds. For those reasons, plots presented in this manuscript are based on the effect of Baseline ADD on Change in ADD, added with specific variables of interest, depending on the case Figures  and 3.For weaners, all five final models showed an effect of year, either as a direct effect or as interacting effect with Baseline ADD, while for finishers this was only the case for two of the five models Table . The effThe effect of initiating study-specific vaccinations was only significant in an interaction with the use of another vaccine in the same period for LAW and PRRS vaccination in finishers Table . An incrThe number of sows, representing herd size, was significantly associated with an increase in ADD in the PCV2 model for finishers, as well as in the LAW and APP models for weaners. For the latter model, the number of sows was only associated with an increase in ADD in the period before 2010, which was shown by the significant interaction between year and Sows , and way of purchasing breeding animals.Herds with no disease problems are at a constant risk of getting disease outbreaks. This is either due to the presence or introduction of various infectious disease agents, which can result in a sudden increase in antimicrobial use. The estimated change in antimicrobial use in pig herds over time, regardless of vaccination status, showed signs of regression toward the mean. This makes sense as, in population-based distributions, the conditional expectation of values located in the tails are typically closer to the overall mean, than to its observed value. Therefore, herds with high consumption are more likely to present a decrease, and herds with low consumption are more likely to increase.An increase in ADD for vaccinating herds should not be interpreted as a missing effect of the vaccines. The increase may be a result of the increased occurrence of diseases other than the one being vaccinated against. In this study, we used the total ADD, since the validity of the different disease indications varies, and some prescriptions do not have an indication assigned to it . They would, therefore, not be included, if the ADDs were split into disease indications.A reason for reducing antimicrobial use, other than mitigating disease in a pig herd, could be demands from authorities. In general, there has been much focus on reducing antimicrobial use in the general pig population in Denmark, as also seen in many other EU countries. Demands from Danish authorities increased after 2010, when the Yellow Card Scheme was implemented, and an effect on the antimicrobial level was seen already from mid-2010, when permitted limits were announced  is not necessarily equal to substantial disease problems and poor pig health. Therefore, a positive effect of vaccination may be more difficult to see in the country, with a more visible increase in antimicrobial use, since the Baseline is already at a low level, when compared to many other EU countries . In the Temtem et al.  found thDenmark is a country with a large pig production. Only a proportion of Danish pig herds were included in this study, due to different reasons and criteria. Some herds initiated vaccination before the beginning of the study period in 2007 and were, therefore, not included in the study. Only herd types allowing us to follow the pigs from vaccination in the sow herd, through weaning and finishing, were selected for this study. Other types of herds, for example herds with only one age group registered, also vaccinated against the five agents of interest within the study period. But for these types of herds, it would have been impractical to trace back and forth the vaccine dosages and antimicrobial prescriptions to include. The sample of herds included here covered around 50–70% of all Danish vaccinating herds, depending on the study .Some herds were excluded due to extreme or negative values. These could have been further investigated, but that would require a large amount of time-consuming manual work, to identify and correct the reason for these outliers. Only a few percent of the total number of herds were excluded in each study, due to extreme or negative values. Hence, this should not have biased the results.In the present study, it was necessary to loosen up on the criterion regarding number of vaccine doses purchased. Not many herds would have been included in the study testing effect of APP, PRRS, and LAW, if the same criteria were used as for the study testing effect of MYC and PCV2. This may reflect that these vaccines are applied differently in Danish pig herds. This could, for example, reflect the use of vaccines for other age groups than what they are licensed for. Another explanation could be the use of half dosages, or not using the vaccine continuously throughout the year. We knew that herds included in the study had purchased vaccines for at least 1 year, but it was difficult to get more information than that, besides the number of doses purchased and the number of animals expected to be vaccinated. Again, this could also explain the missing effect of initiating vaccination against these agents.This study provided little support for the hypothesis that vaccination against five common endemic diseases provides a plausible strategy to reduce antimicrobial use in Danish pig herds, overall speaking. Still, vaccination can be an asset in some situations.AK contributed to the design and interpretation of the work, performed the data analyses, and drafted the manuscript. LK contributed by re-evaluating and re-running the analyses for the models containing interactions between vaccines, producing the plots and figures, and collaborated in the interpretation and new text for the revised version. LN and LA contributed to the design and interpretation of the work and revised the manuscript. All the authors did the final approval of the version to be published and hereby agreed to be accountable for all aspects of the work.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The Functional Assessment of Cancer Therapy–Leukemia (FACT-Leu) scale, a leukemia-specific instrument for determining the health-related quality of life (HRQOL) in patients with leukemia, had been developed and validated, but there have been no reports on the development of a simplified Chinese version of this scale. This is a new exploration to analyze the reliability of the HRQOL measurement using multivariate generalizability theory (MGT). This study aimed to develop a Chinese version of the FACT-Leu scale and evaluate its reliability using MGT to provide evidence to support the revision and improvement of this scale.The Chinese version of the FACT-Leu scale was developed by four steps: forward translation, backward translation, cultural adaptation and pilot-testing. The HRQOL was measured for eligible inpatients with leukemia using this scale to provide data. A single-facet multivariate Generalizability Study (G-study) design was demonstrated to estimate the variance–covariance components and then several Decision Studies (D-studies) with varying numbers of items were analyzed to obtain reliability coefficients and to understand how much the measurement reliability could be vary as the number of items in MGT changes.G) and the indexes of dependability (Ф) for four of the five domains were approximately equal to or greater than 0.80 except for the Emotional Well-being (EWB) domain (>0.70 but <0.80). For the overall scale, the composite G and composite Ф coefficients were greater than 0.90. Based on the G coefficient and Ф coefficient, two decision options for revising this scale considering the number of items were obtained: one is a 37-item version while the other is a 45-item version.One-hundred and one eligible inpatients diagnosed with leukemia were recruited and completed the HRQOL measurement at the time of admission to the hospital. In the G-study, the variation component of the patient-item interaction was largest while the variation component of the item was the smallest for the four of five domains, except for the leukemia-specific (LEUS) domain. In the D-study, at the level of domain, the generalizability coefficients  contains supplementary material, which is available to authorized users. Leukemia, the first major cause of cancer-related deaths for children and adults under 35 years old, is an increasingly common health care problem in the world. It can be divided into two categories, i.e., acute leukemia and chronic leukemia, based on the natural course and the cellular differentiation degree. In China, it has been estimated that there were 75,300 new cases of leukemia and 53,400 deaths in 2015 [Consequently, several leukemia-specific instruments have been developed and used, which include the Life Ingredient Profile for hematologic malignancies , the MedWhat is the reliability of the Chinese version of the FACT-Leu scale?What impact does the test length (number of items) have on the reliability of the Chinese version of the FACT-Leu scale?How should the number of items for every domain in the Chinese version of the FACT-Leu scale be changed to obtain better reliability in the future?Although the original English FACT-Leu scale has been tested and determined to be a valid, reliable, and efficient instrument for evaluating the leukemia-specific HRQOL in both acute and chronic disease , it is nThe FACT-Leu scale was translated from the original English version into simplified Chinese. In the translation procedures four steps were carried out: forward translation, backward translation, cultural adaptation, and pilot-testing. In the first step, the original English version was independently translated into simplified Chinese by two translators  whose native language is Chinese but who are proficient in English. Then the two forward translated versions were compared by a research coordinator to find any differences. When the differences were identified, the research coordinator discussed them with the two translators until they all agreed on a reconciled Chinese version. In the second step, the reconciled Chinese version was translated into English by two back-translators who had never read the original English version. The two back-translators are both oncologist who are proficient in English. Then, the backward translation and the original English version were compared, and the reconciled Chinese version was further modified accordingly by the same coordinator. The process was repeated until the backward translation was identical or nearly identical to the original English version. After that, the items that were likely to lead to confusion or misunderstanding due to cultural differences were modified based on the results from an in-depth interview of oncologists and a focus group discussion. In the final step, a pilot test was carried out among 15 patients diagnosed with leukemia and who satisfied the eligibility criteria. They were asked to independently complete the scale acquired in the third step and then were interviewed using a questionnaire. Any item that was upsetting or difficult to understand should be marked and given appropriate suggestions during the interview. Based on the suggestions from the patients, necessary modifications were made and a final Chinese version for use in the formal measurement of the HRQOL was obtained.The structure of the Chinese version of the FACT-Leu scale is the same as that of the original English version; it is composed of two subscales . The FACT-G consists of four domains: the 7-item Physical Well-being (PWB) domain, the 7-item Social/Family Well-being (SWB) domain, the 6-item Emotional Well-being (EWB) domain and the 6-item Functional Well-being (FWB) domain. For ease of description, the leukemia-specific subscale is called the LEUS domain in this article. Each item of the FACT-Leu scale was rated on a five-level scoring system, namely, not at all, a little bit, somewhat, quite a bit, and very much. The positive items received scores from 0 to 4 points, while the negative items were designed with scoring in the reverse order.This study recruited inpatients diagnosed with leukemia at the First Affiliated Hospital of Kunming Medical University and the First People’s Hospital of Yunnan Province during October 2013 to March 2014. Eligible participants were aged 18 years or older, at least 2 months post diagnosis of any type or stage of leukemia, had a life expectancy of more than 3 months, and were able to read and understand the questionnaires. Exclusion criteria included a diagnosis of psychosis or dementia and illiteracy.The investigators  obtained informed consents from the patients who agreed to participate in the study and met the inclusion criteria. The Chinese version of the FACT-Leu scale was used to measure the HRQOL of the included leukemia patients after the investigators explained the study and the scale. The HRQOL is a self-report measurement, so each patient was asked to answer the scale by himself or herself. The answers were immediately checked by the investigators to verify completeness. If missing items were found, the scale was returned to the patients immediately to fill in the missing items. The patients completed the 44-item FACT-Leu scale at the time of admission to the hospital.GT contains two stages: Generalizability Study (G-study) and Decision Study (D-study). The G-study serves as a “pilot” study that decomposes the variance and covariance components related to various error sources to help confirm the relationship between the measurement goal and measurement facets based on the data collected and using analysis of variance (ANOVA) or multiple analysis of variance (MANOVA). In the D-study, the information from the G-study is used for the planning of an “optimal” measurement protocol so that the best possible reliability can be achieved while balancing other factors.In generalizability theory, a latent trait is defined by sets of conditions under which it may be observed; each set of conditions is called a facet. Usually, the latent trait is the object of measurement . In thisp” in the design and the items facet (abbreviated as “i”) is the only facet of measurement because the HRQOL is a self-report measurement and there is no rater. The items facet is a random facet because a different set of items can be involved in each replication. The HRQOL data are unbalanced because there are unequal numbers of items within each domain. The domains facet (abbreviated as “h”) is treated as the fixed facet because every replication of the measurement of the HRQOL involved the same domains. It is defined that the facet i was nested within the facet h. In addition, facet p is completely crossed with facet i because every patient answers every item in the FACT-Leu scale. In the univariate G-study sense, this design is expressed as p × (i : h), where p, i, and h represent patients, items, and domains facets, respectively. The fixed domains facet and the random effect variance component design associated with each fixed domain level yield a multivariate G study design, p• × i∘, with the number of levels for the fixed domains facet being nh. The solid circle, ·, indicates that the patients facet is crossed with the fixed multivariate variable  whereas the empty circle, ∘, indicates that the items facet is nested within the fixed multivariate variable. In other words, there is a random effect p• × i∘ design within each of the five fixed domains and any single item is only associated with a single domain [p• × i∘ design can be defined asAs the first step, the G-study includes design, data collection, and estimation of the relevant variance-covariance components under the design conditions. In the current study, the measurement goal is the HRQOL of patients with leukemia, which is abbreviated as “e domain . The matorXpih is the observed score that results from a single observation in the hth domain and this score may be decomposed into an overall mean and several effects according to the analysis of variance model. In the right-hand side of Equation 1, μh means the overall mean in the hth domain; μph ∼ (μph ∼ = μph − μh) means the patient effect in the hth domain because μph is the average score of all items for patient “p” in the hth domain; μi : h ∼ (μi : h ∼ = μi : h − μh) means the item effect on the observed score in the hth domain because μi : h is the average score per person for item“i” in the hth domain; and μpi : h,e ~ means the residual effects in the hth domain, including the patient-item interaction effect and other effects. The FACT-Leu scale has five domains (nh = 5), and the model equations for the different domains can be presented as follows:In Equation 1, p, ∑i and ∑pi. Note that ∑p is the variance–covariance component matrix among patients, ∑i is the variance–covariance component matrix for items within a domain, and ∑pi is the patient-item interaction within a domain. As all patients contribute data to all levels of domains facet but the items are nested in different levels of domains facet, ∑p is a full matrix while ∑i and ∑pi are diagonal [It follows that the variance and covariance components for the population and the UAO can be grouped into three symmetric matrices: ∑diagonal .G) and the index of dependability (Ф) for every domain and the overall scale. Several D-studies under the original measurement protocol and the new measurement protocols modified by changing the number of items were analyzed to understand how the measurement reliability could vary with a changing number of items.Once the variance and covariance matrix from the G-study results are available, they could be used in the D-study to estimate the variance components of the universe score and the variance components of the corresponding error to calculate the two reliability coefficients: the generalizability coefficients  and the definition of the variance for the composite, we could define ∑P = ∑p, ∑I = ∑i/nih′ and ∑PI = ∑pi/∑nih in the multivariate D-study. Note that ∑i/nih′ means the hth diagonal element in ∑i divided by the corresponding number of items (nih′), and ∑pi/∑nih means the hth diagonal element in ∑pi divided by nih′, because ∑nih was designed to be a diagonal matrix containing the numbers of items within the levels of h  in this study).Following the method in a univariate p• × i∘ design, the patient-item interaction within domain (pi:h) component alone constitutes the variation of the relative error, while the variation of the absolute error contains both the patient-item interaction within domain (pi:h) component and the item within domain (i:h) component. Therefore, the variance component of the relative error for every domain (σδh2) and the variance component of the absolute error for every domain (σΔh2) can be calculated using Equation 4 and Equation 5.In the p• × i∘ design, σδh2 equals to ∑PI and σΔh2 equals to the direct sum of diagonal matrices ∑PI and ∑I. The G coefficient and the Ф coefficient are calculated using Equation 6 and Equation 7, respectively. In Equation 6 and 7, σh2(P) is the variance component of the patients in the D-study, which is the diagonal elements in matrix ∑P(∑P = ∑p).Actually, in the wh) reflects the proportion of the total number of items in the measurement procedure that were associated with each h in the overall scale. It is commonly defined as wh = nih/ni ·, where nih is the number of items in the hth domain and ni · designates the total number of items in all domains of the overall scale, that is, ni · = nih(1) + nih(2) + nih(3) + nih(4) + nih(5). The weight coefficient is applied to the corresponding variance (σh2) or covariance (σc2(P)) can be calculated by Equation 8, while the composite variance of the relative error (σδc2) and the absolute error (σΔc2) for the overall scale can be calculated by Equations 9 and 10, respectively.In the MGT framework, not only these indexes for every domain of scale but also the corresponding composite values of these indexes for the overall scale obtained by defining a weight coefficient are important. The weight coefficient (σc2(P), σδc2 and σΔc2 are obtained by Equations 8 ~ 10, the composite G coefficient and the composite Ф coefficient for the overall scale can be calculated by making use of the same principles as used in Equation 6 and 7. The estimated variance-covariance component matrices and all indexes used to reflect the measurement error and reliability in MGT can be calculated using a specialized software, mGENOVA. The software and the manual for mGENOVA [http://www.uiowa.edu/~itp or http://www.uiowa.edu/~casma. mGENOVA can process an almost unlimited number of observations very rapidly.After  mGENOVA , 34 can In this research, the execution process of mGENOVA included three steps. Step1: A database was established and saved or transformed into a text file in the same folder as the mGENOVA application on the basis of its data structure ′ = nih(SWB)′ = nih(FWB)′ = 4, nih(EWB)′ = 3 and nih(LEUS)′ = 9 because the number of items was rounded off. It was assumed that there were 4 random parallel items each of the PWB domain, SWB domain, and FWB domain, 3 items in the EWB domain and 9 items in the LEUS domain. Based on the results of previous D studies and the criteria that an optimal reliability coefficient is usually defined as greater than 0.80, we could determine which domain should be increased and which domain should be decreased based on the number of items. Then, the range in which the number of items of every domain should be changed in the next D-study analysis was defined.In the first step, the test length (the number of items) was varied proportionally to three test lengths: the original test length and half and double test lengths. For example, the “half” test length had a total of 24 items, where G coefficient or Ф coefficient just above 0.8 with simultaneously observed large composite G and composite Ф coefficients (>0.90). To describe the results of every scenario more concisely, the “appropriate number of items” that made the G coefficient just larger than 0.8 was defined as niG, and the “appropriate number of items” that made the Ф coefficient just larger than 0.8 was defined as niϕ.In the second step, five scenarios were designed. In each scenario, only the number of items in one domain was changed, while the other four domains kept their original test lengths. In the first scenario, scenario A, the number of items in the PWB domain was changed in the range defined in the first step, while the other four domains kept their original test lengths; the same steps were followed for scenario B, C, D and E by changing the number of items in domains SWB, EWB, FWB and LEUS, respectively. Several multivariate D-studies were conducted for each scenario to find the appropriate number of items for each domain, deemed to be the number that made either the niG for each domain and the niϕ for each domain found in the second step to provide two decision options for the further modification of the scale, and two multivariate D-studies were then conducted for the two decision options.In the third step, the numbers of items for the five domains were reallocated based on the After excluding the patients who were not willing or unable to participate, 101 eligible inpatients diagnosed with leukemia were included. The patients were aged 18 ~ 80 years old (the mean age was 40.46 ± 15.12 years old); 55.4% were males and most (80.2%) were of the Han ethnicity. For their education level, 60.4% completed high school. 76.2% were married and most (92.1%) had public insurance. Only 10.9% thought their economic status was well-off. 69 patients 68.3%) were diagnosed with acute leukemia, and 32 (31.7%) were diagnosed with chronic leukemia. The characteristics of the patients are provided in Additional file % were diAs discussed previously, the MGT applications include the G-study and D-study. Table σp2) represented the estimated “true score” variance across the patients on the specific domain of the scale. Based on the results, this variance component was the largest (0.679) for the FWB domain, followed by the PWB domain (0.642) and the EWB domain (0.491). The variance component of the LEUS domain was the lowest (0.327). Such information suggested that, relatively speaking, the HRQOL of the patients with leukemia differed most on the FWB domain and least on the LEUS domain. The correlation coefficients between the five domains were relatively large, those between the PWB domain and EWB domain, PWB domain and LEUS domain, and EWB domain and LEUS domain, with values of 0.912, 0.949 and 0.976, respectively. These results further corroborated that it was very suitable to use MGT methods to evaluate the reliability of the FACT-Leu scale.Each of the variance components of the patients (σpi2) was the largest, the variation component of the patient was in the second place and only a small amount of variation was due to the item. Similar results were observed for three of the other four domains , except for the LEUS domain, in which the variation component of the item ranked second. Given that the largest source of variation in a domain score was from the person-item interaction, we can assume that different subjects might react to the same item in different ways, despite having the same total score on the scale.The sources of variation for every domain were grouped into three parts: from patient, from item and from patient-item interaction. For the PWB domain, among the three sources, the variation component of the patient-item interaction  when the test length was changed. Figure G coefficient was still greater than 0.90 and the composite Ф coefficient was still greater than 0.85.Firstly, Fig. G and Ф coefficients were the largest for the PWB domain whereas they were the smallest for the EWB domain. After the test length was reduced to a half, the G and Ф coefficients for the EWB domain were both smaller than 0.70. Given that an optimal reliability coefficient is usually defined as one that is greater than 0.80, the number of items of the EWB domain needs to be increased from the original test length, and the changing range of the number of items in the next D-study analysis was defined as from 6 to 12. In the same way, the numbers of items of the PWB domain, FWB domain, FWB domain and LEUS domain could be slightly decreased from the original test length, and the changing ranges of the numbers of items for three of the domains  were defined as from 4 to 7, while the changing ranges of the number of items for the LEUS domain was defined as from 9 to 17. Information on the reallocation of the numbers of items in the five scenarios is provided in Additional file As described in Table G and Ф coefficients increased with the number of items. As shown in the first panel (Scenario A) of Fig. niG and niϕ for the PWB domain were both 5, and the composite G and Ф coefficients were both greater than 0.90. Similar results were presented in the second panel (Scenario B) except that niG and niϕ for the SWB domain were both 7. In turn, it could be seen that niG for the EWB domain was 8 and niϕ was 10 in Scenario C of Fig. niG for the FWB domain was 5 and niϕ was 6 in Scenario D, and niG for LEUS domain was 12 and niϕ was 17 in Scenario E.Several multivariate D-studies were conducted for each scenario designed in the second step, and the results are presented in Fig. niG and niϕ for each domain are shown in Table niG, could be decreased from 44 to 37, while the total number of items for the overall scale in decision option B, where the numbers of items for five domains were reallocated based on niϕ, would be slightly increased from 44 to 45. It is clear that the composite G and Ф coefficients were both greater than 0.90 for both decision option A and decision option B. In decision option A,the G coefficients for all domains were greater than or approximately equal to 0.80, but only Ф coefficients for the PWB and SWB domains were greater than or equal to 0.80. In decision option B, the G and Ф coefficients for all domains were greater than or approximately equal to 0.80.The results of the two multivariate D-studies for the two decision options designed based on these above-mentioned G and Ф coefficients are two important reliability coefficients that are used to depict the reliability for the “relative decision” and “absolute decision”, respectively. Within the GT framework, the “relative decision” depends on the norm-referenced score interpretation, which considers the consistency of the relative standings of the individuals rather than the consistency of the actual scores, while the “absolute decision” depends on criterion-referenced score interpretation which considers both the consistency of the relative standings of the individuals and the consistency of the actual scores [G coefficient should be selected to specifically determine the HRQOL and quantify the dependability of the score. If one’s goal is to perform a criterion-referenced test to investigate the HRQOL of patients (absolute decision), the Ф coefficient should be used to inform about how dependable a score is. It is clear that the Ф coefficient is typically lower than the G coefficient for every domain because the variance component of item within domain (i:h) is factored into the absolute error variance and Ф coefficient but not the relative error variance or G coefficient.The reliability is the extent of variation reflected by the measured results that is the result of accidental errors in the system. In other words, the reliability refers to the dependability, reproducibility, stability, and consistency of the measurement. In GT, the l scores . The coeG coefficient or Ф coefficient) are greater 0.8 in GT. The composite G and Ф coefficients were greater than 0.90 for the Chinese version of the FACT-Leu scale with the two indexes for four of the five domains all approximately equal to or greater than 0.80 except for the EWB domain  based on the original test length. Even though the number of items was reduced to a half, the composite G coefficient was still greater than 0.90 and the composite Ф coefficient was still greater than 0.85. These results indicated a very high level of measurement reliability for the Chinese version of the FACT-Leu scale as a whole, and the measurement reliability was also good at the domain levels. Additionally, the results that the contributioin rate for the composite universe score approached the proportion of the domain score in the original design for most domains (except for the SWB domain) exemplified that the allocation of the scale items was reasonable in general. However, it is worth paying attention to the quality of the items in the SWB domain in the future because the relative difference between these two indexes in the SWB domain was the greatest and the difference value was negative.Some researchers , 35, 36 Ф coefficients increased with the number of items and were both greater than 0.8 in the double test length design. However, doubling the test length might not be realistic in practice, because it is possible that the reliability would conversely decrease with the inclusion of too many items due to an excessive consumption of time. An interesting finding in Fig. The G and It is worth noting that the sample size of the study is not very large, which may affect the findings to some extent. In addition, the study subjects were from the inpatient population at hospitals, which may affect the generalizability of the scale. Therefore, larger and additional studies in which the study subjects are expanded to other populations such as outpatients are needed to validate the scale. Using MGT analysis, we put forward the suggestions about varying the number of items for every domain from the macroscopic point of view. However, we cannot answer which items would be removed by using MGT analysis. In the follow-up study, we should screen and select the items through the item response theory (IRT) methods.To sum up, the Chinese version of the FACT-Leu scale has good reliability as a whole based on the results of MGT, and the implementation of MGT could lead to more informed decisions in complex questionnaire design and improvement. If the Chinese version of the FACT-Leu scale will be modified in the future, there will be two available choices depending on the decision needed (relative decision or absolute decision) based on our analytical results: a 37-item version and a 45-item version.Additional file 1:Data Structure and a Screenshot. (DOC 365 kb)Additional file 2:Example Code of mGENOVA. (DOC 23 kb)Additional file 3:Table S1. General characteristics of the patients included. Table S2. Allocation of the numbers of items per domain for the five scenarios. (DOC 53 kb)Supplementary Results.