Culex australicus mosquitoes. The 1:1 dilution represented the viral load of one RRV-infected mosquito in a pool of 100 mosquitoes. The subsamples underwent nucleic acid extraction, mosquito-specific ribosomal RNA depletion, and Illumina HiSeq sequencing. The viral load of the subsamples was also measured using reverse transcription droplet digital PCR (RT-ddPCR) and quantitative PCR (RT-qPCR). Metatranscriptomic sequencing detected both RRV and UMAV in the 1:1, 1:20 and 1:400 subsamples. A high specificity was achieved, with 100% of RRV and 99.6% of UMAV assembled contigs correctly identified. Metatranscriptomic sequencing was not as sensitive as RT-qPCR or RT-ddPCR; however, it recovered whole genome information and detected 19 other viruses, including four first detections for Australia. These findings will assist arbovirus surveillance programs in utilising metatranscriptomics in routine surveillance activities to enhance arbovirus detection.The ability to identify all the viruses within a sample makes metatranscriptomic sequencing an attractive tool to screen mosquitoes for arboviruses. Practical application of this technique, however, requires a clear understanding of its analytical sensitivity and specificity. To assess this, five dilutions  of Ross River virus (RRV) and Umatilla virus (UMAV) isolates were spiked into subsamples of a pool of 100  The successful utilisation of metatranscriptomics in a range of surveillance applications suggests it has potential to enhance current arbovirus (arthropod-borne virus) surveillance programs.Metatranscriptomics  enables nontargeted, high-throughput detection and characterisation of viruses in a sample. It can be used to detect both known and novel viruses while providing whole genome information, making it a powerful surveillance tool. Metatranscriptomics has been used in a range of surveillance situations, including detecting viruses in human sewage5. Surveillance programs act as an early warning system for increased transmission risk and enlist tools such as mosquito trapping, virus isolation in cell culture, and targeted molecular virus detection using quantitative PCR (qPCR) assays8. Metatranscriptomics is a nontargeted method that offers many advantages for arbovirus surveillance programs. It can detect viruses without culturing them, does not require a priori knowledge of the viral sequence, has the potential to identify new arboviral threats, elucidates mixed infections, and can provide whole genome or specific protein sequences for molecular epidemiological investigations of outbreaks9. Furthermore, it can detect other organisms in a mosquito pool, including endosymbionts such as Wolbachia10, and parasites such as Leishmania11. The capacity to screen large pools of mosquitoes simultaneously makes metatranscriptomics scalable to adapt to heightened vector abundance12.Arboviruses represent a significant burden to human and animal health and include pathogens such as dengue, yellow fever, Zika, chikungunya, bluetongue and equine encephalitis viruses, with dengue virus alone infecting an estimated 390 million people per year13, Ion Torrent14 and Oxford Nanopore15 sequencing. More often, pools of mosquitoes are sequenced, ranging from five specimens11 to 6,700 specimens12. These studies largely focus on exploring the viral diversity present in various mosquito populations. However, there is a lack of studies looking at gold standard test metrics, such as sensitivity and specificity, of metatranscriptomics when testing large pools of mosquitoes for arbovirus surveillance purposes. This is critical when assessing transmission risk and understanding temporal changes in virus abundance. The relationship between viral load and sequencing output needs to be well-defined in order to avoid inaccurate interpretations of sequence data that lead to false positive results (detecting a virus that is not present in the mosquito pool) and false negative results (failing to detect a virus that is present in the mosquito pool).In order to use metatranscriptomics for arbovirus surveillance, the sensitivity and specificity of the method when testing pools of mosquitoes must first be established. A number of studies have used a metatranscriptomic approach to detect viruses in individual mosquitoes using Illumina16, PEG precipitation17 or sequence-independent amplification12. While this does increase the number of viral sequences, enrichment can also introduce bias19. An alternate way to increase the number of viral sequences is by depleting the mosquito RNA, generally by targeting highly abundant ribosomal RNA (rRNA). A variety of rRNA depletion kits are available, however, these are not specific to mosquitoes and so custom probes based on mosquito rRNA sequences need to be generated21.Laboratory workflows can substantially affect the ability of metatranscriptomic sequencing to detect arboviruses in a mosquito pool. A popular way to increase sensitivity is by enriching for arbovirus using size filtration22. One way to overcome this problem is by performing de novo assembly, where short reads are assembled into longer contiguous sequences (contigs), and then comparing these contigs to a database containing viral reference sequences. This approach can improve specificity because longer fragments are taxonomically classified with greater accuracy23. Any viruses detected by the contig-based analysis can then be cross-validated by mapping the sample reads back to the virus reference, which will indicate the breadth and depth of coverage of the virus genome by the reads.The bioinformatic analyses chosen to process the metatranscriptomic reads can also affect sensitivity and specificity. A common method used to detect viruses in a sample is by mapping reads back to viral reference sequences. However, when dealing with short reads this can lead to false positive results if a virus is present with partial sequence homology to a virus of interest22. Due to these complications, it can be challenging to establish criteria for positive detection of an arbovirus in a mosquito pool compared to methods like PCR, which is a more targeted detection tool and not impacted by these variables in the same way. As with other detection methods, the use of controls in metatranscriptomics can be used to account for these variables and establish criteria for positive detection. For instance, the addition of a negative control sample that does not contain any viruses can be used to detect viral sequences resulting from physical or cross contamination during the laboratory workflow. Sequence data from the negative control sample can then be used to calculate normalised ratios, for instance the reads per million ratio (RPM-r) where the virus RPM of the sample (RPMsample) is divided by the virus RPM of the negative control (RPMneg). An RPM-r threshold value of 10 has been used to distinguish a true positive detection from contamination for bacteria, fungi and parasites24.A range of other variables can affect the sensitivity and specificity of metatranscriptomic sequencing including the size and structure (monopartite vs. multipartite) of the virus genome, depth of sequencing, accuracy and completeness of the viral reference database, and the level of host background nucleic acid in the sampleTogaviridae and Reoviridae) were spiked into clarified subsamples of a pool of 100 mosquitoes . The mosquitoes were morphologically identified using taxonomic keys27 on top of a cold plate and stored at −20 °C.Adult mosquitoes were collected using carbon dioxide-baited encephalitis virus surveillance trapsCulex (Culex) australicus Dobrotworsky & Drummond 1953 (part of the Culex pipiens complex) mosquitoes was homogenised in 2 mL of Buffer AVL (Qiagen) using 10 glass beads  and two 1 minute 1,500 rpm cycles on a 2010 Geno/Grinder (SPEX SamplePrep). The homogenised pool was centrifuged for 5 minutes at 15,344 × g and six 120 µL subsamples were taken from the supernatant.A pool consisting of 100 Togaviridae, genus Alphavirus)28 was grown in Vero cells . RRV is a single-stranded, positive-sense RNA virus with a genome approximately 11.8 kb in length29. Umatilla virus (UMAV) strain M4941_15 30 was grown in C6/36 cells . UMAV is a double-stranded RNA virus with a 10-segment genome approximately 19.4 kb in length31. The viral load of the RRV isolate was 6.9 × 104 copies/ng of RNA, and for the UMAV isolate it was 1.8 × 105 copies/ng of RNA, as measured by RT-ddPCR (see Supplementary Information for details). The S1 clarified mosquito subsample was spiked with 10 µL of the RRV isolate and the S5 subsample was spiked with 10 µL of the UMAV isolate (1:1 spike dilution). This spike represents the viral load of a pool of 100 mosquitoes containing one mosquito infected with RRV as previously described32, which was assembled and measured by RT-qPCR for comparison  were spiked with differing dilutions of two cell culture-derived viral isolates  and then stored at −80 °C until further analysis.Nucleic acid was extracted from the six clarified mosquito subsamples using the QIAamp Viral RNA Mini Kit (Qiagen) according to manufacturers’ instruction, except that carrier RNA was not used. The final elution volume of 80 µL in Buffer AVE was split into three 25 µL aliquots to create technical replicates for each of the spiked clarified mosquito subsamples. This resulted in a total of 15 RNA samples, and one negative control sample  as preliminary experiments suggested undiluted RNA yielded more viral reads Fig. . LibraryCustomised insert dependent adaptor cleavage (InDA-C) ssDNA probes were used to deplete the sample of unwanted mosquito rRNA sequences. A total of 480 InDA-C probes (16–25 bp) were designed by NuGEN based on sequences provided by the authors. Specifically, these included both GenBank rRNA from a variety of mosquito species and highly abundant assembled mosquito contigs from previous metatranscriptomic sequencing of mosquito pools . Preliminary experiments indicated usage of the InDA-C probes at the recommended 500 nM did not effectively deplete mosquito rRNA, however usage at 100 µM resulted in a substantial reduction of mosquito rRNA in both 100 and 1,000 mosquito pool libraries, leading to increases in virus reads Fig. . When usAfter customised rRNA depletion the libraries were amplified using 14 PCR cycles and purified. All purification steps were performed using AMPure XP beads (Beckman Coulter). The size of the completed libraries was determined with a 2200 TapeStation using the D5000 ScreenTape assay (Agilent Technologies), and concentration quantified with a Qubit dsDNA HS Assay Kit. The libraries were pooled together in equimolar concentrations, diluted to 10 pM and sequenced on a HiSeq 3000 lane (Illumina) using 2 × 150 bp reads.34 with the read trimming (–trimmomatic) and normalisation  options selected. The assembled contigs were taxonomically classified using BLASTn v2.7.1 + with the NCBI nucleotide (nt) database (acquired 5th February 2019). BLASTn was used to identify the spiked virus contigs as it produced more specific results than BLASTx . Correlation between RPM and virus spike levels was calculated using a Spearman rank correlation test with R v3.6.138. The read alignments were also used to determine depth of coverage with the SAMtools depth command and visualised with the ggplot2 package v3.1.039 as implemented in RStudio v1.1.46340. The BBMap pileup command36 was used to calculate average fold coverage of the virus genome by the reads.Cross-validation of the spiked virus detections was performed by mapping trimmed, interleaved reads from the individual samples to the same set of full-length RRV and UMAV contigs with BWA-MEM. Counts were derived from the alignments with the SAMtools v1.9de novo assembly of all the sample reads combined using Trinity. For taxonomical classification, the assembled contigs were compared to the NCBI non-redundant (nr) database (acquired 5th February 2019) using DIAMOND BLASTx v0.9.22.12341. BLASTx was used as opposed to BLASTn to enable detection of divergent viruses. Trimmed, interleaved reads from each individual sample were mapped to the assembled contigs from the combined sample reads with BWA-MEM and counts were summed from viral contig alignments to measure the relative abundance of viral families. Contigs were excluded from the count if they were <500 bp long, or if they also matched to the Culex quinquefasciatus (part of the Culex pipiens complex) genome (GCA_000209185.1) or the cell lines used to grow the RRV and UMAV spiked into the samples (unpublished data).The presence of other viruses in the mosquito pool was also assessed by performing a single To investigate the incidence of index cross-talk among the samples, the demultiplexed reads were mapped to the PhiX genome (NC_001422.1) using BWA-MEM. PhiX is an unindexed spike-in control added to Illumina runs prior to sequencing and theoretically should not be present in the demultiplexed sample reads. Furthermore, the raw HiSeq data was re-demultiplexed using bcl2fastq Conversion Software v2.20 (Illumina) with the number of index mismatches changed from 1 to 0. The re-demultiplexed reads were also mapped to the PhiX genome.The HiSeq FASTQ files used in this study have been uploaded to the NCBI Sequence Read Archive (SRA) under project ID PRJNA559742.To determine the source of contaminating RRV and UMAV reads, the negative control was re-sequenced without the spiked subsamples. First, the negative control library was re-quantified using a Qubit dsDNA HS Assay Kit. The library was then diluted to 10 pM and sequenced on a NovaSeq 6000 System (Illumina) using 2 × 150 bp reads to the same depth as the previously sequenced samples (25 million paired-end reads). The re-sequenced negative control reads were interleaved and mapped to the same set of full-length RRV and UMAV contigs as used in the analysis above.42. The primer and probe sequences used can be found in Table 29. The UMAV primers and probe were designed using the Primer3 algorithm in Geneious R843 (www.geneious.com) based on an Australian strain of UMAV using the VP2/T2 gene (NC_012755.1) reference sequence33.The viral load of the 15 spiked mosquito pool samples was determined using reverse transcription droplet digital PCR (RT-ddPCR), a highly sensitive method that allows absolute quantification without the need for a standard curveThe One-Step RT-ddPCR Advanced Kit for Probes (Bio-Rad) was used to prepare 22 µL reaction mixtures consisting of: 5 µL of Supermix (Bio-Rad); 2 µL of reverse transcriptase (Bio-Rad); 1 µL of 300 mM dithiothreitol ; 1.98 µL of each forward and reverse 10 µM virus-specific primer (Sigma-Aldrich); 0.55 µL of 10 µM virus-specific probe (Integrated DNA Technologies); 7.49 µL of UltraPure water (Invitrogen); and 2 µL of heat-denatured RNA. The reaction mixtures were loaded into an AutoDG Instrument (Bio-Rad) to generate droplets using Automated Droplet Generation Oil for Probes (Bio-Rad). The droplets were then used for RT-ddPCR using the following cycling conditions: 50 °C for 60 min; 95 °C for 10 min; 40 cycles of 95 °C for 30 s, 57 °C for 1 min; 98 °C for 10 min. After RT-ddPCR, positive and negative droplets were counted using a QX200 Droplet Reader (Bio-Rad) with FAM and HEX channels. The number of positive and negative droplets were used to calculate the concentration of RRV and UMAV as copies per µL of the final reaction  using QuantaSoft Software (Bio-Rad). Correlation between copies/µL and virus spike levels was calculated using a Spearman rank correlation test with R v3.6.1.The unspiked negative control sample was also tested for RRV and UMAV using RT-ddPCR with the same specifications as above.In addition to RT-ddPCR, the viral load of the 15 spiked mosquito pool samples was measured using RT-qPCR. A one-step reaction was performed with 25 µL mixtures consisting of: 12.5 µL RT-PCR Buffer (Applied Biosystems); 1 µL of each forward and reverse 10 µM virus-specific primer (Sigma-Aldrich); 1 µL of 3.12 µM virus-specific probe (Integrated DNA Technologies); 1 µL RT-PCR Enzyme Mix (Applied Biosystems); 6 µL of UltraPure water (Invitrogen); and 2.5 µL of heat-denatured RNA. The same primer and probe sequences used for the RT-ddPCR were also used for the RT-qPCR Table . The cycThe unspiked negative control sample was also tested for RRV and UMAV using RT-qPCR, however instead of a probe-based assay, a SYBR-based assay was used to detect potential genetically divergent viral strains. The same reaction volumes and PCR cycle were used as above, however the 1 µL of virus-specific probe was replaced with 1 µL of 10X SYBR Green I (Invitrogen), and a melt curve protocol was added to the end of the cycle: 5 seconds at 0.5 °C increments between 65 °C and 95 °C. The negative control sample melt peak was compared to RRV and UMAV positive control melt peaks to determine if any virus was present.A consistent level of sequence reads  were obtained across the 15 spiked mosquito pool subsamples and negative control. The percentage of viral reads  and number of viral contigs  were also consistent across all samples Table .3 virus copies/µL  Table . An incr/µL Fig. . The 1:1Cross-validation of the samples was performed by mapping sample reads to the spiked virus genomes to measure average fold coverage (Fold Coverage by Reads - FCR) Fig. . Like wiThe PCC from the contig assembly and FCR from the read mapping approach were both used to assess the analytical sensitivity of metatranscriptomic sequencing from virus spiked mosquito pool samples. However, the determination of sensitivity was confounded by the presence of virus contigs Table  and readFor the contig assembly, the three lowest RRV spike subsamples  contained a mean of two contigs covering 4.6% of the RRV genome, and the negative control had 2 RRV contigs covering 3.7% of the genome. Similarly, the two lowest UMAV spike subsamples  contained a mean of 10.5 UMAV contigs covering 14.3% of the UMAV genome, and the negative control had six contigs covering 7.9% of the genome.As for the read mapping approach, the two lowest RRV spike subsamples  had a mean 0.17 fold coverage of the genome, while the negative control had 0.11 fold coverage of the genome. For UMAV, the two lowest subsamples  had a mean 1.01 fold coverage of the genome, while the negative control had 0.91 fold coverage of the genome.sample) is divided by the negative control (PCCneg). A sample with a PCC-r ≥ 2 was considered positive, which represents at least twice the level seen in the negative control. The minimum PCCneg is set as 1% to prevent overinflated PCC-r values, which means ≥ 2% PCCsample is required for positive detection of virus. The same calculation and parameters were used for a normalised FCR ratio (FCR-r). In order for a sample to be considered positive for a virus, the PCC-r and FCR-r must both be ≥ 2.To address the confounding negative control results, we established a detection criterion based on PCC and FCR Table . To deteThe 1:1, 1:20, 1:400, 1:8,000 and 1:160,000 spike subsamples had an RRV PCC-r of 26.7, 25.9, 2.4, 0.5 and 0.8 respectively, and a UMAV PCC-r of 12.6, 12.6, 11.3, 2.0 and 1.7 respectively. The RRV FCR-r for the 1:1, 1:20, 1:400, 1:8,000 and 1:160,000 spike subsamples was 8,283.3, 181.1, 7.0, 1.4 and 1.8 respectively, and the UMAV FCR-r was 1.1, 1.1, 9.7, 204.2 and 6,353.4 respectively. Only the three highest spike subsamples  had both PCC-r and FCR-r ≥ 2 for RRV and UMAV and were therefore considered positive for both viruses.Umatilla virus species44. On closer inspection of the two contigs it was found the sequences matching KHV were in an untranslated region (UTR), and the UMAV reference in the nt database did not contain UTR sequences.Specificity was based on the accuracy of taxonomic classification of the spiked virus contigs assembled for each sample. The BLASTn search of the nt database correctly identified all RRV contigs from the individual samples as RRV, whereas all but two (0.4%) of the UMAV contigs were correctly identified as UMAV Table . Those tR = 0.927, p = < 0.001) and copies/µL , and negatively correlated with Ct . The lowest concentration spike subsample  was detectable by both RT-ddPCR and RT-qPCR, with mean 0.1 copies/µL and Ct 38.8 for RRV, and mean 1.9 copies/µL and Ct 34.0 for UMAV. Based on the PCC-r and FCR-r criterion, only the three highest spike subsamples were considered positive for RRV and UMAV . The lowest of these (1:400) corresponded to mean 1.6 RPM, 88.6 copies/µL and Ct 27.8 for RRV, and mean 30.6 RPM, 625.1 copies/µL and Ct 26.2 for UMAV.To compare the three virus detection methods: RPM from the metatranscriptomic sequencing results; the copies/µL measurement from the RT-ddPCR; and the cycle threshold (Ct) value from the RT-qPCR were used Table . Virus sCx. australicus mosquitoes , Tombusviridae (16%) and Reoviridae (15%) or were unclassified (31%). Nineteen previously characterised viruses were present in the pool  was derived, and then cross-validated with read mapping to the virus genomes, from which Fold Coverage by Reads (FCR) was derived. While there was a strong relationship between PCC/FCR and the viral copies/µL Fig. , the presample and FCRsample for a virus is divided by the PCCneg and FCRneg, respectively, to produce normalised ratios (PCC-r and FCR-r). Both ratios must be ≥ 2 for that sample to be considered positive for a virus. Using this criterion, only the three highest spike subsamples  were positive for both RRV and UMAV (Table neg 0.11 vs. 0.91). This pattern was also present in the RRV and UMAV PCC-r and PCCneg values. The higher UMAV contamination in the negative control was due to the subsamples having higher concentrations of UMAV than RRV  was the most frequently assembled segment  and interestingly, has the longest UTR sequence that has been recorded for an orbivirus31. It is possible the varying lengths of the UTR sequences for each segment may have affected the assembly56. Further work to investigate this anomaly could include the comparison of different transcriptome assemblers when working with segmented genomes.When investigating the assembly of the 10 UMAV genome segments, we found that certain segments assembled in every sample, while other segments, regardless of segment size, only assembled in higher concentration spike samples Table , suggestUmatilla virus species) occurred because the UMAV genome in the nt database did not contain any UTR sequences, demonstrating how incomplete reference databases can lead to errors. The specificity was also dependent on the taxonomic classification approach – when BLASTx (translated nucleotide query to protein database) was used instead of BLASTn (nucleotide query to nucleotide database), it led to a decrease in specificity  confirms that the metatranscriptomic protocol used is capable of sequencing DNA viruses, despite being targeted at RNA viruses. With DNase-treated RNA as the input material it is possible this is mRNA produced by the circovirus, and it could also be DNA if the DNase treatment was not 100% efficient68. A recent study on contaminating viral sequences in virome data suggests circovirus-like viruses are a common contaminant derived from laboratory components69. Other types of DNA viruses would need to be tested to determine if this protocol can detect both RNA and DNA without separate nucleic acid library preparations. Whilst the known viruses identified in this pool of mosquitoes are not known to cause disease in mammalian cells, the ability to detect these viruses without targeting them highlights the value of metatranscriptomic sequencing in arbovirus surveillance.The nontargeted nature of metatranscriptomics meant that not only were the whole genomes of the spiked viruses sequenced, so were other viruses present in the pool of 100 ies Fig. , which iies Fig. . These ret al.70. The second largest cost is sequencing, with the ~20 million reads per sample used in this study costing approximately AUD$100 using an Illumina NovaSeq sequencer71. This depth of sequencing enabled detection of RRV in the 1:400 spike subsample, which is equivalent to 1 positive mosquito in 40,000, therefore the sequencing depth and cost could be halved whilst remaining considerably sensitive. These suggested changes lower the overall cost per sample to approximately AUD$110. This cost does not include labour time, which amounts to approximately three days for the nucleic acid extraction and library preparation of 32 samples. Automation of some of the steps could increase the number of samples processed simultaneously. The NovaSeq run time is 40 hours71, resulting in a week turnaround time. Due to the cost and time involved, metatranscriptomic sequencing is currently suited as an additional tool to routine surveillance, providing in-depth information on viral activity in mosquito populations at regular intervals throughout the season, perhaps on a monthly basis. It is likely the time and cost associated with metatranscriptomic sequencing will decrease in the future, allowing it to be used more routinely.The wealth of information provided by metatranscriptomic sequencing enhances arbovirus surveillance, however this tool needs to be affordable in order to be broadly utilised in surveillance programs. Processing a sample with the same commercial kits and depth of sequencing used in this study costs approximately AUD$230. Over half of this cost is attributed to the library preparation with customised rRNA depletion, and could be reduced by using a cheaper kit (e.g. NEBNext Ultra II RNA) and an in-house depletion method, such as the Cas9-based approach described in Gu This study has provided information on the sensitivity and specificity of metatranscriptomic sequencing for detection of arboviruses in large pools of mosquitoes, which is essential for the incorporation of this technique into arbovirus surveillance programs. Metatranscriptomic sequencing successfully detected a virus in a pool of 100 mosquitoes at biologically relevant levels, and also in a pool of 1,000 mosquitoes Fig. . While mSupplementary Information


Coronaviridae family, in specific the Alphacoronavirus genus) of global importance. Clinical presentation is characterized with acute diarrhoea, vomiting and dehydration in pigs of all ages, with a possible high mortality in suckling piglets. The disease emerged in the USA in 2013 causing heavy losses, and re-emerged in Europe in 2014, but with milder consequences.Porcine epidemic diarrhoea (PED) is an emergent/re-emergent viral pig disease  strain responsible for the outbreak was of the S-INDEL genotype, much the same as other European PEDV strains. In 2017, a post-outbreak serology was carried out in three counties in Eastern Croatia, revealing seropositivity in pigs bred on four large industrial holdings (9.09%). The seroprevalence across PEDV-positive holdings was up to 82.8%. The latter holdings were unanimously managed by an enterprise that had never reported PED before.PED has emerged in Croatian pig population causing potentially considerable losses. The circulating strain was of the S-INDEL genotype. Serological workup proved PEDV spread to another four agricultural holdings, demonstrating the importance of not only external, but also internal biosecurity measures. Coronaviridae family (genus Alphacoronavirus) [Porcine epidemic diarrhoea (PED) is a viral pig disease having a significant impact on pig production worldwide. Clinical presentation is characterized with acute diarrhoea, vomiting and dehydration in pigs of all ages, with a possible high mortality in suckling piglets . The caunavirus) . The PEDnavirus) . The fulnavirus) .Even though PED was first recognized in the 1970s , it gainPEDV is a highly contagious virus easily spread by people, via transportation means, feed, aerosol and wild animals taking a faecal-oral route , 15–17. Croatia has been considered PED-free until the spring of 2016, when the suspicion on PED outbreak was first reported to the Croatian Veterinary Institute. This manuscript brings data on the very first PEDV outbreak in Croatia, together with the results of molecular characterization of the causative PEDV strain and post-outbreak serological workup.The presence of PEDV genome was confirmed in samples of piglets’ intestinal content using the real-time RT-PCR S gene  and N gene  protocol. Transmissible gastroenteritis virus (TGEV) and rotavirus A (RVA) were excluded as culprit agents since both of them tested negative.N = 48,256), among which only four were mapped against the PEDV reference genome (KU297956) (data not shown). Furthermore, 347 reads were assigned to Enterobacteriaceae, while 30,869 showed significant sequence resemblance to the Caudovirales. Among Caudovirales, 20,194 reads were assigned to Myoviridae , while 10,377 were assigned to Podoviridae .The NGS sequencing resulted in 42,168 merged reads  and partial ORF3 gene sequence  of the PEDV genome . Phylogenetic analysis revealed the presence of PEDV of the S-INDEL genotype  and M (524 nt) genome segments further confirmed that the virus responsible for the outbreak was PEDV Fig. , not a TWe attempted to grow the first Croatian PEDV strain in vitro, however the results were negative. The real-time S gene RT-PCR was positive for the inoculum (Ct = 27.25) and confirmed the first passage carryover (Ct = 35.53), but in the second passage the virus growth could not be detected (no Ct).PEDV IgG ELISA test making use of a commercial IDVet ELISA kit resulted in 62 positive pigs 15.62%) and four positive agricultural holdings (9.09%) (Table 5.62% andN = 61) were finishers bred on three large neighbouring agricultural holdings seated in the Vukovar-Srijem County. Only one aborted sow originating from a large holding located in the Osijek-Baranja County tested positive  for necropsy (voluntarily submitted by the owner). The agricultural holding of origin  was located in the Osijek-Baranja County  was prepared in the 199 Medium  and the supernatant was used for RNA isolation on an iPrep instrument using an iPrep PureLink Virus kit . The samples were tested for the presence of PEDV S gene [A 10%-suspension of the intestinal content . The BLAST output was used to create a taxonomic classification of the reads and contigs with the Megan 6.15.2. [Caudovirales family, the obtained virus reads were extracted and further mapped against the GenBank viral non-redundant protein dataset (BLASTx) for confirmation. Furthermore, reads were mapped against the PEDV reference genome downloaded from the NCBI (KU297956).Next Generation Sequencing (NGS) was performed on a MiSeq instrument  as described previously . Sequenc 6.15.2. . With thConventional amplification of the PEDV S gene was carried out in three steps. The first two steps included the implementation of PEDV-S1F/PEDV-S1R and PEDV-S2F/PEDV-S2R primer sets  and a QiOrthocoronavirinae subfamily (RdRp gene) and to some members of the Alphacoronavirus genus  were applied [In order to rule the circulation of TGEV-PEDV recombinant strains  out, two additional conventional RT-PCR reactions for the amplification of RdRp and M gene segments were performed. To that effect, previously published primer sets that are pan-reactive to the representatives of the  applied . The pri applied .Multiple sequence alignment and phylogenetic analysis were conducted using the MEGA7 Software  and neig25 flasks using the cell culturing protocol that does not imply inoculum removal , as described by US scientists [Virus propagation in vitro was attempted on Vero cells (ATCC® CCL-81™) in Tientists . Virus gBlood sampling of healthy pigs  for the sake of serological workup was organized in the first half of 2017, together with sampling performed within the frame of the regular annual monitoring for classical swine fever and Aujeszky disease . An agricultural holding that provided samples of aborted sows was included, as well. In total, 397 pig blood samples were retrieved from 44 randomly selected agricultural holdings  seated in three eastern Croatian counties  (Fig.


This study investigates the predictors of serum cobalamin concentrations in community-dwelling older adults and the relationship between serum cobalamin and plasma homocysteine.Serum cobalamin and plasma homocysteine were measured by SimulTRAC-SNB radio assay and HPLC, respectively. Linear multiple regression analyses were performed with cross-sectional data of 352 participants aged 60–90 years to examine (1) the predictors of serum cobalamin and (2) the association between cobalamin and homocysteine status. Age, sex, body composition, diet, supplement use, smoking, serum folate, serum pyridoxal 5´-phosphate, serum creatinine, and selected diseases were considered as potential predicting/confounding factors.P > 0.05). In contrast, age , serum folate  and diagnosis of chronic inflammatory bowel disease (IBD)  were positively and cancer diagnosis  was negatively associated with serum cobalamin. The model explained 23% of the variability of serum cobalamin. After exclusion of subjects with IBD/cancer diagnosis and/or vitamin B/multi-vitamin supplementation, only serum folate remained as positive predictor of serum cobalamin . Serum cobalamin was positively associated with inverse-transformed plasma homocysteine before  and after  multiple adjustments.Median values of serum cobalamin, plasma homocysteine, and dietary cobalamin intake were 256 pmol/L, 9.7 µmol/L, and 5.7 µg/day, respectively. In multiple regression analysis, cobalamin intake, sex, body composition, serum creatinine and smoking did not predict serum cobalamin (all Serum folate but not cobalamin intake or age proves to be a main predictor of cobalamin status. Nevertheless, independent of serum folate and other potential confounders, serum cobalamin is inversely associated with plasma homocysteine. There is an ongoing debate on whether cobalamin intake should be increased in advanced age compared to younger ages. In light of this, higher reference values for older adults are discussed, as well as the necessity of cobalamin supplements in advanced age. This is based on observations that older individuals more often have an inferior cobalamin status –3, whichThe clinical relevance of a lower cobalamin status found in older subjects is unclear. First, the observed lower levels of cobalamin status parameters in these studies were not accompanied by classical hematological manifestations ; second,Although pernicious anemia and severe atrophic gastritis are more prevalent in older than in younger subjects and cause clinical cobalamin deficiency , this re6 status.Therefore, the present study investigates whether dietary cobalamin intake is associated with serum cobalamin in older subjects independently of age, sex, body composition, supplement use, smoking behavior, serum folate, serum creatinine, and selected diseases. Furthermore, the association of serum cobalamin with plasma homocysteine is investigated by considering folate and vitamin BSubjects were participants in a prospective cohort study, in which the nutritional and health status of community-dwelling senior citizens in Giessen, Germany (GISELA study) were investigated between 1994 and 2014 on multiple follow-ups. The study protocol was approved by the Ethical Committee of the Faculty of Medicine, Justus Liebig University, Giessen, Germany. All participants provided written informed consent. Recruitment was accomplished through notices at senior citizens’ meetings and medical practices, advertisements in local newspapers and subjects already participating. For enrollment, subjects had to be at least 60 years of age, physically mobile and available around Giessen on a long-term basis. Measurements took place after an overnight fast in the Institute of Nutritional Science in Giessen between July and October. A total of 587 subjects were enrolled but not all of the subjects participated in every follow-up.n = 3), body composition (n = 2), dietary intake (n = 34), general use of supplements/medicine (n = 18) and smoking behavior (n = 15). Two subjects declared non-fasting conditions and thus were not included in the analysis. The final study cohort consisted of 246 women and 106 men.The present analysis is based on cross-sectional data from the follow-up year 2002, which provided the largest sample size. From the 403 subjects participating in that year, subjects were excluded because of missing data on serum cobalamin  and the formula of Roubenoff et al. . Likewise, serum cobalamin did not differ between subjects with dietary intake levels < and ≥ 4.0 µg/day . Vitamin B/multi-vitamin supplement users had higher serum cobalamin than non-users . The unadjusted association between lg10 dietary cobalamin intake and lg10 serum cobalamin stratified by sex is illustrated in Fig. Serum cobalamin, plasma homocysteine and dietary cobalamin intake ranged between 12.8 and 4767 pmol/L, 3.8 and 30.9 µmol/L, and 1.2 and 28.2 µg/day, respectively. Serum cobalamin ≤ 148 pmol/L was present in 17% of the subjects, and 20% showed a dietary cobalamin intake < 4.0 µg/day, with no sex differences in this respect (n = 67), liver/gall bladder disease (n = 64) or urinary tract/kidney disease (n = 15) until 2002 did not differ in serum cobalamin from subjects without such a disease . Subjects with cancer diagnosis (n = 44) had lower serum cobalamin than those not reporting cancer diagnosis , but had equal dietary cobalamin intakes . Subjects with IBD (n = 10) had higher serum cobalamin  and higher dietary cobalamin intake  than subjects without IBD. Subjects who reported to use stomach medicine (n = 41) did not differ in serum cobalamin  or dietary cobalamin intake  from subjects who reported not to use these medications.Subjects diagnosed with stomach disease  vs. 5.7 (4.3–7.9) µg/day, P = 0.617]. In sex-specific analysis, no differences in serum cobalamin according to smoking behavior were evident (P > 0.05).The results of the Spearman correlation are given in Table 10 serum folate, as well as diagnosis of cancer and IBD were significant predictors of lg10 serum cobalamin. The regression model explained 23% of the variance in lg10 serum cobalamin. After nine subjects with extreme cobalamin concentrations (12.8 and ≥ 1000 pmol/L) were excluded to approximate normal distribution of residuals, similar results were found, except for the age effect, which became non-significant, and an increase in the explained variance to 28% (data not shown). The results remained unchanged when lg10 dietary cobalamin intake (µg/day) was replaced by consumption of milk/milk products (g/day) or by lg10 cobalamin intake via milk/milk products (µg/day) (data not shown). Furthermore, when lg10 dietary cobalamin intake was replaced by lg10 total cobalamin intake, the results were equal  and after  adjustments for age, sex, %FM, smoking behavior, lg10 serum folate, lg10 serum PLP and use of vitamin B/multi-vitamin supplements. The results remained unchanged when lg10 intakes of cobalamin, folate and vitamin B6, as well as serum creatinine and diagnosis of cancer and IBD were considered as additional covariables . In this analysis, the sample size was reduced to 341 subjects because of missing values for serum creatinine. After excluding subjects with serum cobalamin ≥ 1000 pmol/L (n = 8), lg10 serum cobalamin was still associated with inverse-transformed plasma homocysteine before  and after  adjustments for age, sex, %FM, smoking behavior, lg10 serum folate, lg10 serum PLP and use of vitamin B/multi-vitamin supplements.In linear regression analyses, lg6 status in community-dwelling older adults.The main findings of the present study are that (1) neither dietary cobalamin intake nor the use of supplements are predictors of serum cobalamin after considering other covariables, whereas serum folate and diseases, such as IBD and cancer, are main predictors and (2) serum cobalamin is associated with plasma homocysteine independent of folate and vitamin BAt present, there is no generally accepted cut-off value with regard to adequate serum cobalamin concentrations. For the diagnosis of cobalamin deficiency, the cut-off of 148 pmol/L has shown a good sensitivity , 23 and In the present study, a significant number of subjects had low serum cobalamin (< 148 pmol/L), which could not be explained by low intakes. A similar finding was reported in younger women . DespiteLikewise, the use of vitamin B/multi-vitamin supplements did not predict serum cobalamin after adjustments for other covariables. The same was true when the use of cobalamin supplements within 3 days before examination was analyzed as potentially predicting variable (data not shown). As described earlier, the amounts of cobalamin taken via supplements were rather modest in the GISELA study . NormallIn the present study, serum folate was the main predictor of serum cobalamin. Significant correlations of serum/plasma folate with serum/plasma cobalamin were reported in other studies –36. WhilIn our cohort, besides serum folate, only IBD and cancer proved as robust predictors of serum cobalamin. Cobalamin and folic acid deficiencies are common in patients with IBD for which reason cobalamin preparations may be advised or given parenterally , what maIn the present study, sex, body composition and lifestyle factors were no predictors of serum cobalamin and the initially observed positive effect of age vanished in sub-analyses. Thus, we cannot confirm an independent negative effect of age on serum cobalamin in community-dwelling older adults.Despite higher cobalamin intakes, male subjects had lower serum cobalamin before adjustments. This was also reported in an elderly population in the Netherlands . One expInverse correlations between current/past smoking and serum cobalamin were reported in some studies , 42, whiSerum cobalamin was a negative predictor of plasma homocysteine before and after multiple adjustments including serum folate and PLP. We are not aware of any other observational study showing an independent effect of serum cobalamin on homocysteine in community-dwelling older subjects having mostly cobalamin intakes and serum concentrations within reference ranges. A meta-analysis of studies on effects of folic acid supplementation with or without cobalamin on homocysteine levels showed that the addition of cobalamin resulted in additional reductions of homocysteine beyond those due to folic acid . In anot6, serum creatinine and body composition were considered as relevant covariables.Some limitations must be considered when interpreting the results of this study. Due to the cross-sectional design reverse causality cannot be excluded. We rely on one biomarker to assess cobalamin status and could not include genetic profiles in our assessment. Because of the low prevalence of IBD and cancer, these results should be interpreted with caution. As strengths of our study, we want to point out that the participants were community-dwelling subjects mainly without cobalamin deficiency and that folate, vitamin Bper se are significant predictors of serum cobalamin, whereas diseases, such as IBD or cancer, may affect cobalamin status. The underlying mechanisms of the strong positive association between serum folate and cobalamin, as well as the robust independent negative association between serum cobalamin and homocysteine warrant further research.In conclusion, our results emphasize that in community-dwelling older adults neither cobalamin intake nor age


Sclerotium rolfsii, which causes southern blight in a wide variety of crops, is a devastating plant pathogen worldwide. Mycoviruses that induce hypovirulence in phytopathogenic fungi are potential biological control resources against fungal plant diseases. However, in S. rolfsii, mycoviruses are rarely reported. In a previous study, we found a hypovirulent strain carrying a diverse pattern of dsRNAs. Here, we utilized the RNA_Seq technique to detect viral sequences. Deep sequencing, RT-PCR and Sanger sequencing validation analyses revealed that this strain harbors various new viral species that show affinity to the distinctly established and proposed families Benyviridae, Endornaviridae, Fusariviridae, Hypoviridae, and Fusagraviridae. Moreover, some viral sequences that could not be assigned to any of the existing families or orders were also identified and showed similarities to the Alphavirus, Ourmiavirus, phlegivirus-like and Curvularia thermal tolerance virus-like groups. In addition, we also conducted deep sequencing analysis of small RNAs in the virus-infecting fugal strain. The results indicated that the Dicer-mediated gene silencing mechanism was present in S. rolfsii. This is the first report of viral diversity in a single S. rolfsii fungal strain, and the results presented herein might provide insight into the taxonomy and evolution of mycoviruses and be useful for the exploration of mycoviruses as biocontrol agents. Sclerotinia sclerotiorum hypovirulence-associated DNA virus 1 (SsHADV-1) was proven to possess the potential for biologically controlling sclerotinia disease under field conditions  technologies and bioinformatics have greatly enhanced the discovery of new viruses in many organisms, including fungi  Tu Kimbrough] is a soil-borne pathogen that causes southern blight disease in a wide variety of crops , 7908 nt in length, was predicted to encode proteins showing similarity to the replicases of Benyvirus-like viruses, such as Agaricus bisporus virus 8 (AbV8), beet soil-borne mosaic virus (BsBMV), and Mangifera indica latent virus (MiLV)  with a 45% identity. ORF2 was incomplete and had no sequence identity to any other sequences in the database. Although benyviruses often have four to five linear positive-sense ssRNAs that are 6.7, 4.6, 1.8, 1.4, and 1.3 kb in size, with the first RNA encoding the RdRp , bat hepevirus (BHV), and hepatitis E virus (HEV), with identities ranging from 25 to 26%. SsRv-L is a +ssRNA virus with a 6,403 nt genome containing a single ORF that encodes a polyprotein with three domains: viral methyltransferase (pfam0l660), viral_helicase l (pfam0 l443), and RdRP  , Sclerotium rolfsii alphavirus-like virus 2 (SraLV2) and Sclerotium rolfsii alphavirus-like virus 3 (SraLV3)  showed similarity to products encoded by alphavirus-like +ssRNA viruses, such as Sclerotium rolfsii fusarivirus 1  and Sclerotium rolfsii fusarivirus 2  , Pleospora typhicola fusarivirus 1 (PtFV1), and Rosellinia necatrix fusarivirus 1 (RnFV1). Phylogenetic analysis based on ORF1 indicated that consistent with the homology search, SrFV1 and SrFV2 were clustered in the fusarivirus clade. Considering the genome organization and genome sizes, the two viruses likely represent the nearly complete genomes of novel members of the Fusariviridae family.Two RNA sequences showed similarity to members of the family Fusariviridae, the two viral sequences of ) Figure . Both SrHypoviridae, with Sclerotinia sclerotiorum hypovirus 2 (SsHV2) being the best match at 57% identity  and CHV1, with identities ranging from 25 to 26%. Hence, diverse infectious hypoviruses belonging to Gamahypovirus and Alphahypovirus might exist.A viral sequence 16,050 bp in length was identified. The predicted amino acid sequences of the viral genome were similar to those of viruses in the family Sclerotium rolfsii ourmia-like virus 1 (SrOLV1). A BLASTx search showed that this virus was similar to ourmiavirus-like mycoviruses, including Magnaporthe oryzae ourmia-like virus (MoOLV) and Rhizoctonia solani ourmia-like virus 1 RNA 1, with identities of 42 and 39%, respectively. Ourmiavirus genomes have three ssRNA segments of 2.8, 1.1, and 0.9 kb, with the largest RNA segment encoding the viral replicase, and the smallest segment encompassing the coat protein  , putative DEXDc, viral helicase (Hel) and RdRp. Consistent with the homology search, phylogenetic analysis based on the conserved RdRp domain suggested that SrEV1 is a new putative species in the family Endornaviridae.Several RNA sequences showed similarity to members of the family ) Figure . The fulSclerotinia sclerotiorum dsRNA mycovirus-L (SsNsV-L), Phlebiopsis gigantea mycovirus dsRNA 2 (PgV2), Macrophomina phaseolina dsRNA virus 2, Botrytis cinerea RNA virus 1 and other viruses that could be grouped into the recently proposed family Fusagraviridae  and Sclerotium rolfsii RNA virus 2 (SrRV2), with lengths of 6,720 bp and 6,182 bp, respectively (dsRNA1 and dsRNA2). BLASTx searches showed that the partially predicted amino acid sequences of the two dsRNAs were similar to those of viruses in the proposed family Fusagraviridae. The sequence of SrRV1 contained two ORFs. The predicted amino acid sequence of SrRV1 ORF2 was similar to that of the RdRps of Rosellinia necatrix fusagravirus 2 at a 35% identity. SrRV2 also contained two ORFs, ORF1 and an incomplete ORF2. The predicted amino acid sequence of SrRV2 ORF2 showed 37% identity to that of the Phlebiopsis gigantea mycovirus dsRNA 2 encoding RdRp (CAJ34335.2). Hence, SrRV1 and SrRV2 likely represent new members of the Fusagraviridae family.Four viral sequences were associated with SsNLV1-like group mycoviruses, such as e Figure . The gapSclerotium rolfsii mycovirus dsRNA 1 (SrMYV1), as previously described , Thelephora terrestris virus 1 (TtV1), and Lentinula edodes mycovirus HKB (Lev-HKB). The gap between the contigs was filled by RT-PCR, and the 5′ terminal sequence was also determined by RACE. All the sequences were assembled as a 10,713 bp RNA sequence, named d Figure . SrMYV1 Sclerotium rolfsii unassigned dsRNA virus 1 (SrURV1) and Sclerotium rolfsii unassigned dsRNA virus 2 (SrURV2). HetRV6 is an unassigned dsRNA virus composed of a single genomic band of approximately 2 kbp encoding a putative viral RNA polymerase that is distantly related to Curvularia thermal tolerance virus (CThTV) and Fusarium graminearum virus 4 (FgV4)  were identified and designated as We used RT-PCR and Sanger sequencing to confirm the origins of these assembled mycoviral sequences. When PCR amplification was performed using reverse transcription products synthesized from the total RNA of the fungal strain BLH-1 as templates, products of corresponding size were obtained and matched to these viruses Figure . HoweverS. sclerotiorum-infecting hypoviruses SsHV2/SX247 and SsHV2/5472  tail at the 3' terminus. In comparison, the nearly complete genome of the high-throughput sequencing-assembled contig of SrHV1 was 16050 nt, indicating 99.61% coverage of the SrHV1 genome. SrHV1 was determined to contain a 13,815 nt long ORF  encoding a 513.37 kDa polyprotein of 4604 aa residues that was predicted to contain the domains of a papain-like cysteine protease (Pro), RdRp and helicase (Hel), like reported for SsHV2/5472 and SsHV2/sx247. The 5′-UTR (untranslated region) and 3′-UTR of SrHV1 were 1,184 and 1,094 nt, respectively. The genomic organization of SrHV1 is depicted in Figure Hypoviridae, with SsHV2 being the best match at 57% , followed by CHV2 , CHV1  and Fusarium graminearum hypovirus 1 (FgHV1) . Based on its sequence similarity to hypoviruses, we suggest that SrHV1 is a ssRNA mycovirus in the family Hypoviridae.A homology search using the polyprotein aa sequences of SrHV1 showed significant identity with polyproteins encoded by members of the family Hypoviridae members, a phylogenetic tree was constructed, and SrHV1 clearly clustered with SsHV2-SX-247, forming a branch distinct from members of Alphahypovirus. At aa positions 3872 to 4189, downstream from the RdRp domain, a Hel domain was identified. As previously described in other hypoviruses, the Hel domain of SrHV1 also contained three characteristic motifs of the Hel superfamily 2  on the Illumina platform, resulting in 33 million reads.To survey the presence and mechanism of antiviral immune response in S. rolfsii genome, and the unmapped reads were then aligned against the SrHV1 and SrEV1 genomes. Abundant small RNAs were matched to the target genome. These small RNAs were mainly distributed from 19 to 24 nt, with a peak at 21 nt, and exhibited characteristics typical of Dicer-produced virus derived small interfering RNAs (vsiRNAs), which are produced from dsRNA intermediates upon binding to Dicer  domain is present in the proteins encoded by betahypoviruses, while alphahypoviruses lack this domain. Hu et al.  and argonaute-like genes (agl-2) have been demonstrated to be necessary for antiviral silencing  are biased toward associating with sRNAs with 5′ U terminal nucleotides  as a primary defense against virus infections, as described commonly in V1 Nuss, . When thV1 Nuss, . For exaV1 Nuss, . In our V1 Nuss, , whereasV1 Nuss, . The perHypoviridae, like CHV1. In addition, the S. rolfsii strain BLH-1 was defective in sclerotia production, and SrHV1 showed an intimate affinity with SsHV2, both of which contain the papain-like proteinases that are closely related to the CHV1-encoded p29. We presume that SrHV1 might also have an RSS that functions to resist host antiviral defenses and determines or participates in host hypovirulence actions, such as growth, virulence, and sclerotia production. However, to validate this hypothesis, additional gene function characterization studies are needed.The p29 of CHV1, a papain-like protease that shares sequence and functional similarities with the helper-component proteases (HC-Pro) of potyviruses, a symptom determinant, has been shown to act as an RNA silencing suppressor (RSS) in the fungal host  at 27°C. Total RNA was extracted by mycelium harvest using the RNeasy mini kit  and quantitatively evaluated using the NanoDrop ND-1000 spectrophotometer . High-quality RNAs were subjected to RNA-seq. Sequencing cDNA library was constructed from poly(A) selected total RNA, using the TruSeq™ RNA Sample Prep Kit .The fungal strain BLH-1, originally isolated from a southern blight disease-infected de novo assembled with Trinity . Reads were de novo assembled viral contigs. The amplicons were analyzed by agarose gel electrophoresis and sequenced by Sanger sequencing.To confirm that the viral sequences were determined from mycoviruses infecting the fungal host rather than from sequences integrated into the host genome, RT-PCR and PCR assays were separately performed using templates of total RNA and DNA extracted from the fungal strain BLH-1 and primers designed based on the To completely sequence the genomes of some of the mycoviruses, sequence gaps not covered by the transcriptome sequencing assembly were filled by RT-PCR amplification using designed primers based on the obtained viral sequences flanking the gaps. The 5′ and 3′ terminal sequences were elucidated using a ligase-mediated terminal amplification method as described previously (Zhong et al., S. rolfsii strain BLH-1 replicates was extracted. The small RNAs were purified from 17% denaturing polyacrylamide gels, ligated with 5′ and 3′ adaptors and then subjected to small RNA library generation and Illumina sequencing.The pooled total RNA from three SRR7754484.After the adapter sequences and low-quality reads were removed, the data were subjected to bioinformatics analysis, and sequences 18–30 nt in length were extracted. To identify SrHV1 and SrEV1-derived vsiRNAs, the clean reads were respectively mapped to the SrHV1 and SrEV1 genomes using the BLAST search function. vsiRNA analyses, including the nucleotide size, composition of the 5′ nucleotide and polar distribution, were performed using Perl scripts and Microsoft Excel as previously described (Wang et al., JZ and QZ: conceived and designed the experiments; JZZ and JZ: performed the experiments; JZ, BDG, and HJZ: analyzed the data; JZZ: Wrote the paper.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.


Human immunoglobulin G (IgG) binding with zinc ions was examined using zinc ions immobilized on chelating Sepharose beads (Zn-beads). Human IgG bound to Zn-beads but not to Sepharose beads (control beads). Mouse, rat, bovine and equine IgGs also bound to Zn-beads, similar to human IgG. The human IgG F(c) fragment showed zinc ion–binding activity whereas the Fab fragment did not. Ethylenediaminetetraacetic acid (EDTA)-treated Zn-beads no longer bound human IgG; however, washing the beads, followed by the addition of zinc ions, restored the binding activity towards human IgG. Zn-beads saturated with human fibrinogen could bind human IgG, and Zn-beads saturated with human IgG could bind fibrinogen. These results suggest that animal IgGs, including human, specifically bind zinc ions, probably through a zinc-binding site in the F(c) fragment and not in the Fab fragment. In addition, IgG and fibrinogen interact with each other and/or bind zinc ions through different mechanisms. Aspergillus niger [It was recognized in 1869 that zinc is necessary for the growth of us niger ,3 and laus niger ,3. Nutrius niger . Zinc adus niger ,3,4.2 and T-bet [Immune functions are very sensitive to zinc restriction . Zinc isnd T-bet . High cond T-bet . Zinc rend T-bet ,2. Furthnd T-bet .2-macroglobuin, haptoglobulin, ceruloplasmin, immunoglobulins , complement C4, prealbumin, C-reactive protein, and fibrinogen [Homeostasis of the intracellular zinc level is strictly regulated by the zinc transporter . There abrinogen ,11,12,13brinogen . IgG is A number of zinc ion binding proteins have been identified, and the cellular uptake of zinc ions, the effect of zinc ion uptake on cellular function, and the essential need of immune cells and enterocytes for zinc have been revealed. However, the binding mechanism of zinc ions by circulating zinc ion binding proteins remains unclear. This study presents a binding analysis of zinc ions with human IgG and speculates on the zinc-binding form of the protein in circulation.Human IgG was incubated with zinc ion immobilized on chelating Sepharose beads (Zn-beads) or Sepharose beads (control beads: CB), and then the suspension was centrifuged. Human IgG was detected by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis in the supernatant of CB but not Zn-beads a: the CBThe zinc-binding activity of human IgG to EDTA-treated Zn-beads was decreased compared to its binding to untreated beads . The remThe binding of mammalian IgGs, including those of humans, to zinc ions is a common characteristic of IgGs, and therefore the binding of the Fab and F(c) fragments of human IgG to zinc ions was examined a,b. HumaZn-beads were saturated with human fibrinogen; after centrifugation, unbound fibrinogen was detected in the supernatant (data not shown). In addition, human IgG was added to a suspension containing Zn-beads saturated with fibrinogen and containing unbound fibrinogen. Human fibrinogen was separated by SDS-PAGE into three bands corresponding to the Aα, Bβ and γ subunits, with molecular masses of 67 kDa, 56 kDa and 50 kDa, respectively, as shown in purified sample (F). The IgG H band appeared to comigrate with the γ band of fibrinogen present in the supernatant (S) of CB and present in the pelleted Zn-beads (B), as shown in Zinc ions affect thrombin absorption with fibrin and shorten blood clotting time . Fibrino2-macroglobuin, haptoglobulin, ceruloplasmin, immunoglobulins , complement C4, prealbumin, C-reactive protein, and fibrinogen [Zinc plays multiple roles in animals, including humans ,2,3. Morbrinogen ,12,13,14Zinc supplementation is effective in relieving oxidative stress and in decreasing the levels of pro-inflammatory cytokines such as TNF-α, IL-6 and IL-10 ,3,4,6. TTM Fast Flow and Sepharose 4B were purchased from GE Healthcare . Other analytical grade chemicals were purchased from Wako Pure Chemical Industries Ltd. . Pure water (Elix water) was produced from tap water using an Elix Advantage Water Purification System .Human and rat IgGs were purchased from Invitrogen Corp. . Human IgG Fab and F(c) fragements and equine IgG were purchased from Rockland Immunochemicals Inc. . Human fibrinogen and bovine IgG were purchased from Sigma . Mouse IgG was purchased from Innovative Research Inc. . Chelating SepharoseSDS-PAGE was performed essentially according to the method of Laemmli  using sl4 according to the manufacturer’s instructions and the beads were suspended to 50% (v/v) in phosphate-buffered saline . One mL PBS containing IgG, human IgG Fab or IgG F(c) fragments (25 µg each) and a suspension of 40 µL 50% (v/v) zinc ion–immobilized (Zn-beads) or Sepharose 4B (CB: control beads) beads was prepared (net volume of beads per sample: 20 µL) and the mixture was rotated at 4 °C overnight. The mixture was centrifuged at 14,000× g for 7 min at 4 °C, providing supernatant and pelleted beads for SDS-PAGE. One mL of washing solution  was added to the pelleted beads and the suspension was centrifuged as described above. One mL of washing solution was then added, the beads were suspended, and centrifugation was repeated to further wash the beads. This washing step was repeated three times in total and the final pelleted beads were suspended in sample buffer for SDS-PAGE and used for SDS-PAGE (net volume of beads per lane: 8 µL).Zinc ion was immobilized to Chelating Sepharose Fast Flow beads using 0.2 M ZnSOv/v) suspension in PBS. Human IgG was also incubated with treated and untreated Zn-beads and CB as previously described. In another experiment, the EDTA-treated Zn-beads or CB were exhaustively washed, then 1 mL PBS containing 50 mM ZnSO4 was added to the pelleted beads. The mixture was rotated at 4 °C overnight, then the beads were exhaustively washed, suspended to 50% (v/v) with PBS, and incubated with IgG (25 µg) as described above. In all experiments, beads were washed and centrifuged, the resulting supernatant and the pelleted beads were treated as described above, and these samples were subjected to SDS-PAGE.The effect of EDTA on the binding between human IgG and Zn-beads was investigated by preincubating Zn-beads and CB in the presence and absence of 1 mL of 50 mM EDTA (pH 7.4), then IgG was added and the beads were incubated at 4 °C overnight. The treated and untreated beads were exhaustively washed as described above and the beads were suspended to provide a 50% (v/v) Zn-beads or CB beads was prepared (net volume of beads per sample: 20 µL) and the mixture was rotated at 4 °C overnight. The presence of human fibrinogen or IgG was detected in the supernatant, suggesting that the Zn-beads were saturated with fibrinogen or IgG (data not shown). A 20 microliter aliquot of human IgG (100 µg) and fibrinogen (100 µg) in PBS were added to a suspension of beads saturated with fibrinogen and IgG, respectively, and further incubated as described above. The mixture was centrifuged at 14,000× g for 7 min at 4 °C to provide supernatant and pelleted beads for SDS-PAGE. Pelleted beads were applied to gel as much as possible due to natural sedimentation. CB were treated and analyzed in an identical manner.One mL PBS containing human fibrinogen (600 µg) or IgG (500 µg) and a suspension of 40 µL 50% . The human IgG F(c) fragment bound with Zn-beads whereas the Fab fragment did not, suggesting that IgG binds Zn ions through the F(c) fragment. EDTA-treated Zn-beads could not bind human IgG, but regeneration with zinc ions recovered the zinc-binding activity with human IgG. Human IgG retains zinc-binding activity even after addition to Zn-beads saturated with fibrinogen and fibrinogen binds to Zn-beads saturated with IgG. These results demonstrate that human IgG specifically binds zinc ions, suggesting a zinc-binding site in the Fc fragment, and IgG binds fibrinogen and/or zinc ions through a different mechanism.


Bacillus cereus HG10 was immobilized and used to control biofouling in a bioreactor. QQ beads caused extracellular polymeric substance reduction and significantly hindered biofilm formation on a submerged membrane. Community profiling of 16S rRNA gene amplicons revealed that QQ beads dramatically altered the bacterial community structure in activated sludge but not in biofilm. Bacterial structure in the presence of QQ beads showed a clear divergence from that of the control groups at phylum, class, order, family, and genus taxonomic ranks. A significant enrichment of several bacterial genera, including Acinetobacter, Aeromonas, Delftia, Bacillus, and Pseudomonas, and depletion of over 12 bacterial genera were observed. These findings would contribute to a better understanding of why and how immobilized QQ bacteria impair membrane biofouling in QQ-MBRs.Quorum quenching-membrane bioreactors (QQ-MBRs) have been studied widely in recent decades. However, limited information is known about the influence of QQ on the microbial community. In this study, the indigenous QQ bacterium  Membrane bioreactors (MBRs) have drawn substantial attention worldwide as wastewater treatment technology. MBRs outcompete other technologies because of several advantages, including smaller footprints, better effluent quality, and less sludge production. However, membrane biofouling, a critical obstacle, hindered the widespread use of the technology and remains to be overcome ,2,3. MemWhile activated sludge in MBRs consists of diverse microbiota, biofilm formation on the membrane is known to be regulated by QS ,12. SeveBacillus cereus HG10, isolated from activated sludge, in sodium alginate beads. The QQ performance of the HG10 beads was then assessed in a batch bioreactor. Furthermore, microbial community analysis in both activated sludge and biofilm formed on the membrane in a batch bioreactor was conducted using high-throughput 16S rRNA barcoding and sequencing.Although there is broad interest to interrupt bacterial QS by QQ bacteria, limited attempts have been made to disclose the mechanism and influence of QQ bacteria on the microbial community inside bioreactors. Microbial community profiling by 16S ribosomal RNA (rRNA) gene analysis may offer valuable information to determine the impact of QQ bacteria on the bacterial community structure and unveil the relationship between QS and QQ bacteria. In this study, QQ beads were prepared by immobilizing an indigenous QQ bacterium, Flat-sheet Durapore polyvinyl difluoride (PVDF) membrane  was purchased from Merck Millipore (USA). Sodium alginate was purchased from Sigma (USA). Luria-Bertani (LB), agar, yeast extract and tryptone were purchased from HKM (China). Glutaraldehyde and anhydrous ethanol were purchased from Xilong Science (China). SYTO9 dye was purchased from Molecular Probes (USA). The PowerSoil® DNA Isolation Kit was purchased from MOBIO . Agarose was purchased from Biowest (Spain). The 2x Premix Taq DNA polymerase (Cat. #R004A) was purchased from TAKARA . Universal primers 27F (5’-AGAGTTTGATCCTGGCTCAG-3’) and 1492R (5’-GGCTACCTTGTTACGACTT-3’) were synthesized by the Beijing Genomics Institute .4Cl, 87 mg KH2PO4, 9.8 mg CaCl2, 128 mg MgSO4.7H2O, 9.44 mg MnCl2.4H2O, 8 mg FeCl3.6H2O, and 1022 mg NaHCO3 [Each liter of synthetic wastewater (pH 7.0–7.5) constituted 1600 mg glucose, 56 mg yeast extract, 460 mg tryptone, 340 mg NHg NaHCO3 . SteriliBacillus cereus HG10 , the strain with the highest AHL-degrading activity, was chosen as the candidate for anti-biofouling and microbial community shift evaluation in this research.QQ bacteria were isolated and screened from activated sludge in a wastewater treatment plant  according to Ochiai et al. . The AHL2. The mixture was incubated at 4 °C for 12 h to allow full crosslinking of the chemicals. Vacant beads were prepared following the same procedure without the addition of bacteria. The characteristics of the beads were then examined by scanning electron microscopy .Both vacant and HG10-entrapped beads were prepared as described by Kim et al. [A conical flask (150 mL) was chosen to simulate a batch bioreactor. Sixty conical flasks were divided into three groups  and operated in parallel. Forty-nine milliliters of synthetic wastewater and 1 mL of acclimated activated sludge  together with a sheet of PVDF membrane were added to each batch bioreactor. Activated sludge was mixed well with wastewater during the entire growth period with shaking. Finally, 15 HG10 entrapping beads or vacant beads were added to the QQ and VB groups, respectively. The bioreactors were then incubated with shaking at 30 °C, 70 r/min. A 48-h adaption time was allowed for the adaption of entrapped QQ bacteria to the system. At each 24 h time point, 25 mL of the synthetic wastewater in each batch bioreactor was replaced with freshly prepared wastewater. The biofilm formation process and biofouling conditions of each membrane were observed and recorded in all samples operated in parallel. Activated sludge and membrane samples were taken and analyzed on 1, 8, and 20 days respectively.American Public Health Association, APHA 5520 C closed reflux titrimetric method [Extracellular polymeric substances (EPS) were extracted from the membrane by the heat extraction method  on the eStructures of HG-10 entrapping and vacant beads were observed by scanning electron microscopy . The beads were washed three times using deionized water and then fixed with 2.5% (V/V) glutaraldehyde at 4 °C for 2 h. The fixative was then washed off. The sample was then dehydrated using a graded series of ethanol  for 15 min each and finalized with 100% ethanol for 20 min. Finally, the samples were freeze-dried, and the cross sections of the beads were cut and sputtered with gold for 15 s. Then, the cross sections of beads were visualized and characterized with 1000, 2000, and 6000× magnificationMeanwhile, biofilms on the membranes at the initial (first day) and relatively mature stage (eighth day) were also observed using SEM. A piece (1 × 1 cm) of the membrane fiber was cut and observed by SEM at 1000, 5000, and 10,000× magnification. 2O. The microbe suspension was then taken and stored at −80 °C for 16S rRNA gene sequencing. DNA extraction was performed using a MO BIO PowerSoil® DNA Isolation Kit. DNA quality was monitored by 1% agarose gel electrophoresis.Three milliliters of water samples were collected on days 1, 11, and 20 from each group. Samples were frozen at −80 °C immediately after collection. Meanwhile, biofilm samples were collected by cutting a piece of each membrane sample (1 × 1 cm). The membrane pieces were then ultrasound-treated for 3–5 min with 3 mL of ddHThe V3–V5 regions of 16S rRNA genes were amplified using primers 515F and 806R. PCR was carried out in a BioRad S1000 . PCR amplification was carried out as follows: 94 °C for 5 min, followed by 30 cycles each of 94 °C for 30 s, 52 °C for 30 s, and 72 °C for 30 s and a final extension at 72 °C for 10 min. Amplicons were generated , quality controlled , then sequenced (IlluminaHiseq2500).All microorganisms or microbial communities mentioned in this research refer to the bacterial community based on 16S rRNA sequencing. Raw sequence data were deposited in the NCBI Sequence Read Archive database. The SRA accession number is SRP158107.Paired-end raw reads quality filtering were performed to obtain high-quality reads according to the Trimmomatic (V0.33)  quality The average size of beads was shown to be 3–4 mm . No obviA flat-sheet membrane was submerged in each conical flask  to simulate biofilm formation and microbial community structure on the membrane surface in an MBR.Bacillus cereus has been known for generating lactonase that can degrade AHL signal molecules [Bacillus cereus HG10 strain showed substantial C6-HSL-degrading ability (data not shown). Thus, HG10 beads attenuated biofilm formation by reducing EPS excretion.Extracellular polymeric substances (EPS) are considered key components for the structure of biofilms. The amount of EPS (carbohydrates and proteins) in the biofilm on the eighth day were measured . In the olecules ,32,33. IBiofilms on the membrane surface in the batch bioreactors with and without beads were visualized on days 1 and 8 using scanning electron microscopy (SEM) . For theIn summary, HG10-entrapped QQ beads effectively prevented or delayed the maturation of biofilms, proving that the QQ bacteria have anti-biofouling abilities under the experimental conditions in this study. Furthermore, HG10 QQ beads caused a reduction in EPS and thus inhibited biofilm formation without interfering with wastewater treatment efficiency.After running the three bioreactor groups in parallel for 20 days, a total of 601,341 high-quality sequencing reads were obtained from nine activated sludge and nine biofilm samples by 16S rRNA gene amplification. Low-quality sequences were removed, and the remaining effective reads were then clustered into 3613 operational taxonomic units (OTUs) at 97% sequence similarity. Rarefaction curves indicated that the sequencing depth was sufficient to detect all the genera within each sample. The results also indicated that the total number of sequences and OTUs in the QQ samples were less than those in the paralleled control samples.Although QQ beads have been demonstrated as an effective method to overcome biofouling in MBRs, little is known about the influence of QQ beads on the bacterial community, composition, and diversity. To investigate the effect of QQ beads on the microbial community structure of the activated sludge and the biofilms, bacterial community profiling analysis was conducted before and after the addition of QQ and vacant beads. In As shown in Bacilli increased with time of incubation in activated sludge with QQ beads from 1.8% (day 1) to 38% (day 20). However, it remained almost constant in the other two groups (with an average of 0.2%). In contrast, certain classes of bacteria, including Bacteroidia, Clostridia, Deltaproteobacteria, and Campylobacteria, were diminished in activated sludge with QQ beads.In addition, the composition and abundance of microbes changed with incubation time  both in activated sludge a and in However, no similar fluctuations in the microbial community were observed among the biofilms in all three groups , as shown in The heatmaps drawn at the family level further illustrated a dissimilar composition and abundance of microbial structures between activated sludge with QQ beads and those in the other two groups a. At theTo evaluate the difference in species complexity in both activated sludge and biofilms of the three groups, β-diversity (inter-sample diversity) was compared using Bray-Curtis distances. Principal coordinate analysis (PCoA) was performed . This anAcinetobacter_OTU1, Aeromonas_OTU2, Delftia_OTU4, Bacillus_OTU5, and Pseudomonas_OTU11 and hindered the growth of Macellibacteroides_OTU3, Niabella_OTU6 and OTU32, Christensenellaceae_R-7_group_OTU8, Ottowia_OTU75, Pseudomonas_OTU10, Nannocystis_OTU17, Desulfovibrio_OTU25, Sedimentibacter_OTU15, Acetoanaerobium_OTU20, and Blvii28_wastewater-sludge_group_OTU14/OTU26.To further uncover the difference in dominant species between different groups, the OTU representative sequence was analyzed with the relative abundance of the first 50 and annotated to the level of genus for the activated sludge in three groups  . At the Bacillus cereus, which is the same bacterial species that was embedded into the beads. The highest count of this species in the control group  was only 17, whereas in the QQ group , the number reached up to 1523 on the 11th day. The count of Delftia also increased dramatically with QQ beads. Interestingly, several species of the Delftia genera have been reported as having AHL-degrading activity and can inhibit QS. Singh et al. demonstrated that Delftia tsuruhatensis attenuates biofilm formation of Pseudomonas aeruginosa [Delftia sp. interferes with QS by producing AHL acylase and can use AHL as the sole carbon source [Delftia acidovorans has been reported to inhibit QS by modifying C6- to C8-HSL [Delftia tsuruhatensis strain NBRC 16741 and Bacillus cereus HG10 from the same activated sludge sample. This strain also showed high AHL-degrading activity (data not shown). Aeromonas_OTU2 and Pseudomonas_OTU11 were also successfully defined to the species level as Aeromonas hydrophila subsp. hydrophila and Pseudomonas plecoglossicida, respectively. However, limited reports have been found about these two strains.It is noteworthy that OTU5 was successfully defined to the level of species as ruginosa . Others n source . Delftiao C8-HSL . ConcurrPseudomonas_OTU10 was annotated to the level of species as Pseudomonas otitidis. This strain has been reported to have biofilm forming ability and has been applied to degrade oil in biofilm-based reactors [Among the genera that were downregulated, Blvii28_wastewater-sludge_group has been commonly found in wastewater or wastewater treatment systems ,39. Resereactors .Although several studies have reported the effectiveness of QQ in biofouling control, limited information is available on the influence of QQ bacteria on microbial community composition, diversity, and richness. Here, we demonstrated a significant influence of QQ beads on the microbial community structure in activated sludge while reducing biofouling on the membrane surface. These results raised the possibility that QQ bacteria, by interfering with cell-cell communication between biofilm-forming bacteria, might trigger other native quorum-quenching bacteria to flourish in the community and initiate quorum quenching in a synergistic manner. However, the detailed synergism or antagonism relationship between those microbes and their detailed mechanisms are intriguing and remain to be elucidated.Bacillus cereus effectively reduced biofouling on a membrane in a bioreactor. Remarkably, the bacterial community profiling data revealed a broad impact of QQ beads on the microbial distribution and abundance in activated sludge in a bioreactor. Clear separation of bacterial structure was observed at all genera and phyla taxonomic ranks. Certain OTUs clustered to the genus level, including Acinetobacter, Aeromonas, Delftia, Bacillus, and Pseudomonas, were strikingly enriched by QQ beads in activated sludge. Meanwhile, more than 12 other OTUs in activated sludge were depleted. Whereas biofilm formation on membranes with QQ beads was delayed, microbial structure divergence in biofilms was not as dramatic as that observed in the activated sludge in the bioreactor. Our results provide new insight into how QQ bacteria battle biofilm-forming microbes while affecting the entire bacterial community. The mechanisms turned out to be more complex than expected. Our observation implies the possibility that embedded QQ bacteria could trigger certain native microbial taxa to flourish and inhibit biofouling in a synergistic manner by interfering with bacterial communication. Thus, it might provide helpful information for future QQ-MBR design.Immobilized indigenous


Nuclear localization of paramyxovirus proteins is crucial for virus life cycle, including the regulation of viral replication and the evasion of host immunity. We previously showed that a recombinant Newcastle disease virus (NDV) with nuclear localization signal mutation in the matrix (M) protein results in a pathotype change and attenuates viral pathogenicity in chickens. However, little is known about the nuclear localization functions of NDV M protein. In this study, the potential functions of the M protein in the nucleus were investigated. We first demonstrate that nuclear localization of the M protein could not only promote the cytopathogenicity of NDV but also increase viral RNA synthesis and transcription efficiency in DF-1 cells. Using microarray analysis, we found that nuclear localization of the M protein might inhibit host cell transcription, represented by numerous up-regulating genes associated with transcriptional repressor activity and down-regulating genes associated with transcriptional activator activity. The role of representative up-regulated gene prospero homeobox 1 (PROX1) and down-regulated gene aryl hydrocarbon receptor (AHR) in the replication of NDV was then evaluated. The results show that siRNA-mediated knockdown of PROX1 or AHR significantly reduced or increased the viral RNA synthesis and viral replication, respectively, demonstrating the important roles of the expression changes of these genes in NDV replication. Together, our findings demonstrate for the first time that nuclear localization of NDV M protein promotes virus replication by affecting viral RNA synthesis and transcription and inhibiting host cell transcription, improving our understanding of the molecular mechanism of NDV replication and pathogenesis.The online version of this article (10.1186/s13567-019-0640-4) contains supplementary material, which is available to authorized users. Paramyxoviruses describe a family of non-segmented negative-sense RNA viruses (NNSV) responsible for significant human and animal diseases, such as measles virus (MeV), mumps virus (MuV), Nipah virus (NiV), Hendra virus (HeV), Sendai virus (SeV), parainfluenza virus types 1–5, and Newcastle disease virus (NDV) , 3. Of a247KKGKKVIFDKIEEKIRR263) through the RanGTP-dependent pathway ), which generated GFP reporter gene mRNA and more gRNA(+).Additional file 2.Modeling of the signaling pathway of transcriptional misregulation in DF-1 cells infected with rSS1GFP at 12 hpi (A) and 18 hpi (B). The signaling pathway of transcriptional misregulation induced by rSS1GFP infection was drawn, and the significantly differentially expressed genes involved in this pathway are indicated: a red label indicates up-regulated genes; a green label indicates down-regulated genes.


Endometriosis has a significant cost of illness burden in Europe, UK and the USA, with the majority of costs coming from reductions in productivity. However, information is scarce on if there is a differing impact between endometriosis and other causes of chronic pelvic pain, and if there are modifiable factors, such as pain severity, that may be significant contributors to the overall burden.An online survey was hosted by SurveyMonkey and the link was active between February to April 2017. Women aged 18–45, currently living in Australia, who had either a confirmed diagnosis of endometriosis via laparoscopy or chronic pelvic pain without a diagnosis of endometriosis were included. The retrospective component of the WERF EndoCost tool was used to determine direct healthcare costs, direct non-healthcare costs (carers) and indirect costs due to productivity loss. Estimates were extrapolated to the Australian population using published prevalence estimates.407 valid responses were received. The cost of illness burden was significant in women with chronic pelvic pain  irrespective of whether they had a diagnosis of endometriosis. The majority of costs (75–84%) were due to productivity loss. Both absolute and relative productivity costs in Australia were higher than previous estimates based on data from Europe, UK and USA. Pain scores showed the strongest relationship to productivity costs, a 12.5-fold increase in costs between minimal to severe pain. The total economic burden per year in Australia in the reproductive aged population  was 6.50 billion Int $.Similar to studies in European, British and American populations, productivity costs are the greatest contributor to overall costs. Given pain is the most significant contributor, priority should be given to improving pain control in women with pelvic pain Chronic pelvic pain (CPP) is pain in the pelvis of greater than six months duration, and is severe enough to cause functional disability or require medical intervention . Common A large multi-centre study across Europe, UK and the USA found that the total cost per woman with endometriosis per year was €9579 with the bulk of costs €6298) being due to absence from work  being du, 4, therThe aim of this survey and cost of illness (COI) analysis was to determine the economic impact of both women having chronic pelvic pain either with and without a current diagnosis of endometriosis on healthcare costs, employment related costs and other costs related to childcare and household maintenance for women in the Australian healthcare context. Whilst it is recognized that health and economic systems differ significantly between countries, even within close geographical areas , assessiwww.surveymonkey.com). The tool consisted of ninety-nine questions including direct healthcare costs (e.g. costs of medications and doctors visits), direct non-healthcare costs (e.g. transportation costs), and indirect costs of productivity loss. Total time to complete the survey was between 30–45 minutes. Modifications were made to income and ethnicity to adapt to Australian norms as per the Australian Bureau of Statistics [The WERF EndoCost tool was developed by the World Endometriosis Research Foundation (WERF) EndoCost Consortium, and the original protocol consists of validated prospective hospital questionnaires and both retrospective and prospective patient questionnaires . Our stuatistics . Brand nThe survey link was distributed via the social media platforms  of Endometriosis Australia, EndoActive and Pelvic Pain Foundation of Australia. The total combined reach of these organisations on social media was just over 35k followers. Each organisation made two social media posts regarding the survey, the second post 3–5 weeks after the first. The survey link was active from February 2017 to April 2017, for a total of eight weeks. Data collection was closed once there had been no new responses for five days. Ethical approved was provided by the Western Sydney University Human Research Ethics Committee, approval number H12019.Women were eligible to participate in the survey if they were aged 18–45, currently living in Australia and either had a surgically confirmed diagnosis of endometriosis, or if they had chronic pelvic pain from any cause. Chronic pelvic pain was defined as pain in the pelvis for at least six months that caused the woman to seek medical attention and if they had either; a laparoscopy that did not show evidence of endometriosis or had not undergone a laparoscopy at the time of survey. All data collected was from participants themselves. Following standard practice in cost-of-illness studies, this study measured costs rather than test a specific hypothesis and so no sample size calculation was necessary .In Australia, there is a mixed public and private health care system. All residents have automatic access to the public system comprising: (i) primary , allied health and selected pharmaceuticals), and (ii) secondary care . The government provides subsided care, and includes a co-payment mechanism resulting in patient out-of-pocket costs. The purchase of private insurance does not preclude using public hospitals. The assumption in this study was that patients visited public providers.A ‘societal perspective’ was adopted, incorporating (i) health sector impacts, often termed ‘direct costs’, (ii) productivity impacts, often termed ‘indirect costs,’ using the human capital approach, incorporating multiplier impact  and  women with a diagnosis of endometriosis, and (ii) women reported suffering from general chronic pelvic pain, without an associated diagnosis. The average cost per person was estimated and for the age categories of 18–24, 25–30, 31–38 and 39+ years. Analysis was conducted by endometriosis and chronic pelvic pain separately. Mean and 95% confidence intervals were reported derived using bootstrapping with 5,000 replications . An a prResults from the survey were extrapolated by multiplying: (i) estimates of the prevalence of endometriosis using a rate of 10% , the mosAn ‘analysis of extremes’ was conducted, where the key structural assumptions of the main analysis were altered to generate lower bound estimates. First, the Human Capital Approach was substituted with the Frictional Cost Approach where productivity impacts were capped at 3 months with the assumption of replacement in the workforce. Second, to account for potential uncertainty regarding unit costs estimates all estimates of costs and productivity estimates were lowered by 10%. Third, the population prevalence of endometriosis and CPP was then lowered to 5%.Costs were estimated for one year and in AUD $ 2017 prices. Following standard practice, to enable comparison of the economic burden between countries, costs were converted to International dollars (Int $) using purchasing power parity (PPP) conversion factors so that Int $1 is equivalent to US $1 in the United States . S2 File407 valid responses were received. 340 of these women had endometriosis (84%) and 67 (16%) had chronic pelvic pain without a current diagnosis of endometriosis (hereafter referred to just as CPP). The cost of illness was broken down into three categories; health related costs, productivity costs and cost for carers. The breakdown of costs in each category is outlined in For endometriosis, average per person, per year costs was estimated to be Int $ 2640 (95% CI 2158 to 3272) for total health costs, $17484 (95% CI 16407 to 18679) for productivity costs and $774 (95% CI 433 to 1262) for carer costs, for a total of $20,898  for all ages combined.For women with CPP, average per person, per year costs was estimated to be Int $ 3215 (95% CI 2528 to 4234) for total health costs, $12,789  for productivity costs and $966 (95% CI 393 to 1499) for carer costs, for a total of $16,970  for all ages combined.The major point of difference between the two cohorts were the social support structures; with women with endometriosis having mostly in-kind support (87%) with regards to carers, while women with CPP reported they did not receive any in-kind support, and all carer related costs were paid.The total female population in Australia aged between 18–45 was 4.80 million in 2017 , and theIn the sensitivity analyses, where lower bound estimates were generated the economic impacts fell substantially, as expected.At a per person level, when a Frictional Cost Approach (FCA) was used  and unit costs were reduced by 10%, then average per person costs were Int $ 8,116  for endometriosis and Int $ 8,563 (95% CI 7230 to 9765) for CPP. Regarding the population impact, if a prevalence rate of 5% (rather than 10%) was also used, then total costs were 1.37 billion Int $.Women in Australia with endometriosis or other causes of CPP, have a substantial financial burden caused by their condition. We found the per person cost of endometriosis was Int $20,898  in 2017 prices. This is higher than previous work that also used the same tool where the estimated per person cost was Int $13,536, when converted to 2017 Int $.The higher cost per patient found in our study may also reflect our recruitment strategy with participants drawn from social media engagement through major Australian endometriosis or pelvic pain support and advocacy groups . SimilarImportantly, the use of the WERF EndoCost tool in all of these surveys allows comparability and increases the body of evidence in this field. Our data reported not only on women surgically confirmed with endometriosis, but also with other forms of chronic pain–some of whom may be diagnosed with endometriosis in the future. It is important to recognize that women will present with ‘pain’ and not with ‘endometriosis’ and whilst we move to clinical diagnosis of endometriosis being more widely accepted, women wOur sensitivity analyses demonstrate that the economic burden varies from $1.4 billion (low) to $6.5 billion (high), mainly due to uncertainty regarding the true prevalence rates of endometriosis (5% or 10%), and the form of economic valuation regarding productivity impacts (HCA or the FCA). The HCA was used in the main analysis to represent the full impact on women affected by the conditions and was used by Simeons in a similar study . The FCAWe chose to stratify cost of illness burden by pain, rather than ASRM disease stage, since the relationship between disease stage and pain is very poor –26. Our Women with endometriosis report issues achieving adequate pain management  with NSALimitations of this study include the limited sample size, due in part to the in-depth nature of the questionnaires completed and information obtained. Whilst this is the first Australian study for endometriosis and there exist similar estimates from other countries, there are no previous studies on CPP. We asked women to answer the endometriosis section only if they had a histologically confirmed surgical diagnosis of endometriosis and confirmatory evidence is not possible due to the anonymous nature of the survey. Given the significant time and effort burden of filling in the survey (30–45 minutes) it’s unlikely that women without endometriosis would have undertaken this but we cannot rule this out. That would place them into the CPP group. Conversely, many women categorized as CPP may have undiagnosed endometriosis. Previous work suggests that the diagnosis of endometriosis may range from 33%  to 75% . ImportaOver 43% of participants had pain in the most severe range and without population level data on pain distribution, we cannot determine how representative our sample is of the larger endometriosis/CPP population and these data may over-represent those not responding well to medical or surgical management. We did not collect data on geographical location of respondents, so it is possible that our sample did not represent potential differences in the cost of illness that may exist between women in urban, rural and remote areas. However, based on our previous work in this population using the same recruitment strategies  we expecThis research clarifies that endometriosis and chronic pelvic pain have considerable impact for the women affected; the health sector; the wider economy and to carers. Given the huge financial burden of endometriosis and CPP, there is an urgent need for accurate epidemiological studies to assess the true prevalence rate of endometriosis, and for substantive longitudinal studies that determine these economic impacts with greater accuracy to guide policy at a national and international level. The inclusion of economic evaluations alongside future intervention studies to assess cost effectiveness, will allow a greater understanding of how the economic burden is reduced, including improvements in quality of life for women suffering with endometriosis and other forms of CPP.S1 File(PDF)Click here for additional data file.S2 File(PDF)Click here for additional data file.S3 File(XLSX)Click here for additional data file.S4 File(DOCX)Click here for additional data file.S1 Table(PDF)Click here for additional data file.S2 Table(PDF)Click here for additional data file.