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• W2989706094 abstract "•Analyzing viral dark matter changes our understanding of the gut virome•Gene-based clustering can address the challenges of high inter-individual variation•Healthy human gut virome is dominated by a stable core of virulent bacteriophages•In Crohn’s disease, the virulent core is replaced with temperate bacteriophages The human gut virome is thought to significantly impact the microbiome and human health. However, most virome analyses have been performed on a limited fraction of known viruses. Using whole-virome analysis on a published keystone inflammatory bowel disease (IBD) cohort and an in-house ulcerative colitis dataset, we shed light on the composition of the human gut virome in IBD beyond this identifiable minority. We observe IBD-specific changes to the virome and increased numbers of temperate phage sequences in individuals with Crohn’s disease. Unlike prior database-dependent methods, no changes in viral richness were observed. Among IBD subjects, the changes in virome composition reflected alterations in bacterial composition. Furthermore, incorporating both bacteriome and virome composition offered greater classification power between health and disease. This approach to analyzing whole virome across cohorts highlights significant IBD signals, which may be crucial for developing future biomarkers and therapeutics. The human gut virome is thought to significantly impact the microbiome and human health. However, most virome analyses have been performed on a limited fraction of known viruses. Using whole-virome analysis on a published keystone inflammatory bowel disease (IBD) cohort and an in-house ulcerative colitis dataset, we shed light on the composition of the human gut virome in IBD beyond this identifiable minority. We observe IBD-specific changes to the virome and increased numbers of temperate phage sequences in individuals with Crohn’s disease. Unlike prior database-dependent methods, no changes in viral richness were observed. Among IBD subjects, the changes in virome composition reflected alterations in bacterial composition. Furthermore, incorporating both bacteriome and virome composition offered greater classification power between health and disease. This approach to analyzing whole virome across cohorts highlights significant IBD signals, which may be crucial for developing future biomarkers and therapeutics. The virome is likely to be one of the major forces shaping the human gut microbiome but is perhaps its least understood component. The virome is dominated by bacteriophage (phage), which play vital roles in many microbial communities by driving diversity, aiding nutrient turnover (Weitz et al., 2015Weitz J.S. Stock C.A. Wilhelm S.W. Bourouiba L. Coleman M.L. Buchan A. Follows M.J. Fuhrman J.A. Jover L.F. Lennon J.T. et al.A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes.ISME J. 2015; 9: 1352-1364Crossref PubMed Scopus (140) Google Scholar), and facilitating horizontal gene transfer (Canchaya et al., 2003Canchaya C. Fournous G. Chibani-Chennoufi S. Dillmann M.-L. Brüssow H. Phage as agents of lateral gene transfer.Curr. Opin. Microbiol. 2003; 6: 417-424Crossref PubMed Scopus (348) Google Scholar). Understanding the role of bacteriophages in microbial community structures will be essential if we are to understand or control the alterations in human gut microbiome composition and diversity associated with many diseases, including inflammatory bowel disease (IBD) (Gevers et al., 2014Gevers D. Kugathasan S. Denson L.A. Vázquez-Baeza Y. Van Treuren W. Ren B. Schwager E. Knights D. Song S.J. Yassour M. et al.The treatment-naive microbiome in new-onset Crohn’s disease.Cell Host Microbe. 2014; 15: 382-392Abstract Full Text Full Text PDF PubMed Scopus (1923) Google Scholar, Halfvarson et al., 2017Halfvarson J. Brislawn C.J. Lamendella R. Vázquez-Baeza Y. Walters W.A. Bramer L.M. D’Amato M. Bonfiglio F. McDonald D. Gonzalez A. et al.Dynamics of the human gut microbiome in inflammatory bowel disease.Nat. Microbiol. 2017; 2: 17004Crossref PubMed Scopus (589) Google Scholar), obesity (Le Chatelier et al., 2013Le Chatelier E. Nielsen T. Qin J. Prifti E. Hildebrand F. Falony G. Almeida M. Arumugam M. Batto J.M. Kennedy S. et al.MetaHIT consortiumRichness of human gut microbiome correlates with metabolic markers.Nature. 2013; 500: 541-546Crossref PubMed Scopus (2790) Google Scholar), and diabetes (Forslund et al., 2015Forslund K. Hildebrand F. Nielsen T. Falony G. Le Chatelier E. Sunagawa S. Prifti E. Vieira-Silva S. Gudmundsdottir V. Pedersen H.K. et al.MetaHIT consortiumDisentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota.Nature. 2015; 528: 262-266Crossref PubMed Scopus (1229) Google Scholar). Many gut bacteria (and potential phage hosts) remain difficult to culture (Forster et al., 2019Forster S.C. Kumar N. Anonye B.O. Almeida A. Viciani E. Stares M.D. Dunn M. Mkandawire T.T. Zhu A. Shao Y. et al.A human gut bacterial genome and culture collection for improved metagenomic analyses.Nat. Biotechnol. 2019; 37: 186-192Crossref PubMed Scopus (243) Google Scholar), which means that analyzing the virome depends heavily on metagenomic sequencing and bioinformatic approaches. However, a lack of universal marker genes on phage (similar to 16S rRNA in bacteria) and a subsequent lack of taxonomic information due to poorly populated databases (Krishnamurthy and Wang, 2017Krishnamurthy S.R. Wang D. Origins and challenges of viral dark matter.Virus Res. 2017; 239: 136-142Crossref PubMed Scopus (118) Google Scholar) means that database-independent methods are required and that virome analysis must be carried out at the level of metagenomic assembly or individual viral genomes. Early metagenomic studies highlighted the novelty and diversity of the human gut virome but were able to classify only a minor fraction (2%) of sequenced DNA (Minot et al., 2011Minot S. Sinha R. Chen J. Li H. Keilbaugh S.A. Wu G.D. Lewis J.D. Bushman F.D. The human gut virome: inter-individual variation and dynamic response to diet.Genome Res. 2011; 21: 1616-1625Crossref PubMed Scopus (632) Google Scholar). Improvements in high-throughput sequencing technologies have allowed the virome to be analyzed in unprecedented detail with studies sequencing up to 50 million reads per sample (Zuo et al., 2019Zuo T. Lu X.J. Zhang Y. Cheung C.P. Lam S. Zhang F. Tang W. Ching J.Y.L. Zhao R. Chan P.K.S. et al.Gut mucosal virome alterations in ulcerative colitis.Gut. 2019; 68: 1169-1179Crossref PubMed Scopus (173) Google Scholar). It has been confirmed that the virome is incredibly diverse, that the majority do not align to known sequences in databases (i.e., viral dark matter) (Roux et al., 2015bRoux S. Hallam S.J. Woyke T. Sullivan M.B. Viral dark matter and virus-host interactions resolved from publicly available microbial genomes.eLife. 2015; 4Crossref PubMed Google Scholar), and that composition is highly unique to individuals (Reyes et al., 2010Reyes A. Haynes M. Hanson N. Angly F.E. Heath A.C. Rohwer F. Gordon J.I. Viruses in the faecal microbiota of monozygotic twins and their mothers.Nature. 2010; 466: 334-338Crossref PubMed Scopus (810) Google Scholar, Moreno-Gallego et al., 2019Moreno-Gallego J.L. Chou S.P. Di Rienzi S.C. Goodrich J.K. Spector T.D. Bell J.T. Youngblut N.D. Hewson I. Reyes A. Ley R.E. Virome Diversity Correlates with Intestinal Microbiome Diversity in Adult Monozygotic Twins.Cell Host Microbe. 2019; 25: 261-272e5Abstract Full Text Full Text PDF PubMed Scopus (99) Google Scholar, Shkoporov et al., 2019Shkoporov A.N. Clooney A.G. Sutton T.D.S. Ryan F.J. Daly K.M. Nolan J.A. McDonnell S.A. Khokhlova E.V. Draper L.A. Forde A. et al.The Human Gut Virome Is Highly Diverse, Stable, and Individual Specific.Cell Host Microbe. 2019; 26: 527-541.e5Abstract Full Text Full Text PDF PubMed Scopus (255) Google Scholar). IBD, including Crohn’s disease (CD) and ulcerative colitis (UC), is a chronic disorder of the intestinal tract resulting in periods of flare and remission. Although the etiology of IBD remains unclear, it appears to be multifactorial and has been repeatedly associated with alterations in the human gut microbiome. These include decreased bacterial diversity and a reduced abundance of certain Firmicutes and Bacteroides. There is an emerging body of data providing evidence that the gut virome is altered in IBD (Norman et al., 2015Norman J.M. Handley S.A. Baldridge M.T. Droit L. Liu C.Y. Keller B.C. Kambal A. Monaco C.L. Zhao G. Fleshner P. et al.Disease-specific alterations in the enteric virome in inflammatory bowel disease.Cell. 2015; 160: 447-460Abstract Full Text Full Text PDF PubMed Scopus (736) Google Scholar, Zuo et al., 2019Zuo T. Lu X.J. Zhang Y. Cheung C.P. Lam S. Zhang F. Tang W. Ching J.Y.L. Zhao R. Chan P.K.S. et al.Gut mucosal virome alterations in ulcerative colitis.Gut. 2019; 68: 1169-1179Crossref PubMed Scopus (173) Google Scholar, Fernandes et al., 2019Fernandes M.A. Verstraete S.G. Phan T.G. Deng X. Stekol E. LaMere B. Lynch S.V. Heyman M.B. Delwart E. Enteric Virome and Bacterial Microbiota in Children With Ulcerative Colitis and Crohn Disease.J. Pediatr. Gastroenterol. Nutr. 2019; 68: 30-36Crossref PubMed Scopus (58) Google Scholar) with increased overall virome diversity and an increased relative abundance of the family Caudovirales. Yet nearly all findings have been drawn from compositional changes of the identifiable fraction of the virome, which can be as little as 15% of the data (Norman et al., 2015Norman J.M. Handley S.A. Baldridge M.T. Droit L. Liu C.Y. Keller B.C. Kambal A. Monaco C.L. Zhao G. Fleshner P. et al.Disease-specific alterations in the enteric virome in inflammatory bowel disease.Cell. 2015; 160: 447-460Abstract Full Text Full Text PDF PubMed Scopus (736) Google Scholar). This limits the overall understanding of the virome and hampers the identification of potential disease biomarkers. A database-independent analysis method is essential if we are to fully characterize changes in the gut virome in health and disease. This approach begins with metagenomic assembly of short reads to resolve viral genomes and subsequent alignment of reads to these assemblies to determine their relative abundance. Spurious alignments to repeat and conserved regions are removed from further analysis by using a breadth of coverage filter (Roux et al., 2017Roux S. Emerson J.B. Eloe-Fadrosh E.A. Sullivan M.B. Benchmarking viromics: an in silico evaluation of metagenome-enabled estimates of viral community composition and diversity.PeerJ. 2017; 5: e3817Crossref PubMed Scopus (125) Google Scholar). However, at this level of resolution, the virome exhibits enormous diversity and interpersonal variation (Reyes et al., 2010Reyes A. Haynes M. Hanson N. Angly F.E. Heath A.C. Rohwer F. Gordon J.I. Viruses in the faecal microbiota of monozygotic twins and their mothers.Nature. 2010; 466: 334-338Crossref PubMed Scopus (810) Google Scholar), obscuring any patterns in the virome across individuals and cohorts. As part of this study, we reanalyzed a previously published keystone dataset (Norman et al., 2015Norman J.M. Handley S.A. Baldridge M.T. Droit L. Liu C.Y. Keller B.C. Kambal A. Monaco C.L. Zhao G. Fleshner P. et al.Disease-specific alterations in the enteric virome in inflammatory bowel disease.Cell. 2015; 160: 447-460Abstract Full Text Full Text PDF PubMed Scopus (736) Google Scholar) consisting of subjects with CD and UC and healthy controls. We overcame the high levels of inter-individual variation associated with strain-level resolution by using protein homology and MCL (Markov cluster algorithm) to group viral sequences into putative higher taxonomic ranks. In this way, it was possible to describe compositional changes across the entire virome in health and disease beyond the known minority. We propose that a core virome in healthy individuals shifts toward a community that is less stable and dominated by temperate phage in IBD. We show that virome alterations mimic those of the bacteriome and that when used together, they offer an improved method for classifying IBD patients from healthy subjects. We also validated our results using a longitudinal cohort of patients with UC in both active and inactive states of disease. This analysis approach supports future virome studies by providing insight into changes in composition across the entire dataset. By comparing the whole-virome composition of other published datasets, it may also reveal further disease-specific alterations that had been previously obscured. For details of the analysis methods used in this study, see STAR Methods. We reanalyzed a previously published dataset of healthy and IBD gut viromes (Norman et al., 2015Norman J.M. Handley S.A. Baldridge M.T. Droit L. Liu C.Y. Keller B.C. Kambal A. Monaco C.L. Zhao G. Fleshner P. et al.Disease-specific alterations in the enteric virome in inflammatory bowel disease.Cell. 2015; 160: 447-460Abstract Full Text Full Text PDF PubMed Scopus (736) Google Scholar). The dataset was comprised of 165 virome samples from 130 subjects, which consisted of 61 healthy controls, 27 subjects with CD, and 42 with UC. Of these, six samples were known to be collected during CD flare, eight in CD remission, 13 in UC flare and 20 in UC remission. To expand upon these findings, we explored a second dataset of longitudinal samples for 40 subjects with UC, focusing on the impact of disease status (i.e., flare or remission) on gut virome composition. The cohort was part of the PURSUIT-M phase 3 clinical trial (STAR Methods). This dataset was generated in house and consisted of samples from periods of flare (82) and remission (31). For this dataset, disease activity was determined by Mayo score. For all subjects, initial samples were taken during a period of flare (week 0). Two further time points were taken for each subject at weeks 6 and 30. For both datasets, 16S rRNA gene-sequencing data was also obtained and performed on 149 (dataset 1) and 109 (dataset 2) samples. Initially, virome analysis was performed on the Norman et al., 2015Norman J.M. Handley S.A. Baldridge M.T. Droit L. Liu C.Y. Keller B.C. Kambal A. Monaco C.L. Zhao G. Fleshner P. et al.Disease-specific alterations in the enteric virome in inflammatory bowel disease.Cell. 2015; 160: 447-460Abstract Full Text Full Text PDF PubMed Scopus (736) Google Scholar dataset by aligning quality filtered reads to the final set of virus-like sequences (VLSs; see STAR Methods), made non-redundant at 90% identity over 90% of length. This resulted in a mean of 80.38% (±29.29%) quality-filtered reads per sample being used in the final analysis. Because VLSs represent groups of highly related viral genomes (whole or partial), analysis was carried out at a strain or species level. This was reflected in the extremely high levels of individuality among subjects. It was also observed that the individuals themselves were the primary drivers of separation and longitudinal samples grouped together (Figure 1A). This individual specificity masked compositional differences of the virome across cohorts and each of the cohorts (control, CD, and UC) showed little divergence. Principal coordinate (PC) axes 1 and 2 described very little of the variation (4.85% and 3.59%), suggesting that disease-specific changes in virome composition were not visible at the level of VLSs (patterns of β diversity were reproducible across various metrics; data not shown). Lower taxonomic resolution (i.e., a higher taxonomic rank) was required to overcome this high level of interpersonal variation and identify compositional changes in the virome associated with disease. This was achieved by clustering VLSs based on protein-coding gene-sharing networks (Bin Jang et al., 2019Bin Jang H. Bolduc B. Zablocki O. Kuhn J.H. Roux S. Adriaenssens E.M. Brister J.R. Kropinski A.M. Krupovic M. Lavigne R. et al.Taxonomic assignment of uncultivated prokaryotic virus genomes is enabled by gene-sharing networks.Nat. Biotechnol. 2019; 37: 632-639Crossref PubMed Scopus (249) Google Scholar) (see STAR Methods). The VLSs clustered into 472 viral clusters (VCs) of >2 members with 2,382 singletons remaining, henceforward referred to as a VC with 1 member. The resulting VCs formed a new count table, and a VC-based analysis of β diversity was carried out (Figure 1B). Samples largely grouped per condition with noticeable increases in the eigenvalues to 10.36% and 5.58% variation explained for PC-axes 1 and 2, respectively, meaning the biological signals that drove separation between samples were considerably stronger. However, it should be noted that samples with true deviation from the main cohort (such as subjects N208 and N56) remained distinctive, suggesting that the clustering process retains true compositional differences. To further determine if clustering VLSs could overcome the masking effect of inter-individual variation, the relative abundances of shared and unique VLSs and VCs were plotted for control subjects (Figure 1C). At a VLS level, inter-individual variation was represented by a high proportion of sequences unique to a given subject (relative abundance 14% ± 8%). Furthermore, sequences that were shared across 30% of individuals made up a minor proportion of the virome (relative abundance 1.7% ± 4%), and no VLSs were shared across 50% or more of individuals. In contrast, inter-individuality was far less evident at a VC level, and the proportion of VCs unique to an individual was lower (relative abundance 1.3% ± 3%). Shared VCs also made up a substantially larger proportion of the virome with a relative abundance of 15% ± 6% per subject shared across 30% of the cohort, 7.1% ± 6.6% across 50%, and 0.7% ± 1.4% across 70%. Furthermore, a total of eight VCs were shared across 30% of CD and UC cohorts (Figure 1D). Analysis was continued at a VC level, because these shared features made it possible to compare viromes across and between cohorts. In the Norman et al., 2015Norman J.M. Handley S.A. Baldridge M.T. Droit L. Liu C.Y. Keller B.C. Kambal A. Monaco C.L. Zhao G. Fleshner P. et al.Disease-specific alterations in the enteric virome in inflammatory bowel disease.Cell. 2015; 160: 447-460Abstract Full Text Full Text PDF PubMed Scopus (736) Google Scholar dataset, β diversity principal coordinate analysis (PCoA) (Spearman distances) yielded the greatest degree of separation between the viromes of CD patients (relapse and remission) and healthy controls (PERMANOVA, p = 0.0023 and p = 0.0032, respectively) followed by UC relapse and remission (PERMANOVA, p = 0.002 and p = 0.0023, respectively) (Figure 2A). Variations observed between disease states of each condition were not significant, which may be due to small sample sizes (PERMANOVA, p > 0.05). PCoA without the division of relapse or remission status showed that CD and UC β diversity significantly differed from healthy controls (PERMANOVA, p = 0.0002 and 0.0002, respectively; Figure S1A). The healthy cohort also had the greatest similarity across subjects, having the lowest pairwise distances between points (Figure S1B), which supports the previous observations of shared VCs across individuals (Figure 1D). This core virome (defined as presence across >50% of subjects) in the healthy cohort was composed of two VCs (vc2 and vc7) shared across >70% of subjects and six (vc1, vc10, vc23, vc25, vc32, and vc39) across >50%. vc1 was classified as temperate Siphoviridae with CRISPR hits to various Firmicutes and Parascardovia (phylum: Actinobacteria), and vc10 was classified as a crAss-like phage (Guerin et al., 2018Guerin E. Shkoporov A. Stockdale S.R. Clooney A.G. Ryan F.J. Sutton T.D.S. Draper L.A. Gonzalez-Tortuero E. Ross R.P. Hill C. Biology and Taxonomy of crAss-like Bacteriophages, the Most Abundant Virus in the Human Gut.Cell Host Microbe. 2018; 24: 653-664 e6Abstract Full Text Full Text PDF PubMed Scopus (126) Google Scholar). However, the majority of these VCs were unclassified (i.e., did not cluster with known viral genomes). This highlights the important biological signals that are often overlooked by database-dependent analysis methods. Core VCs were not found across UC subjects, and just one VC (vc32 unclassified, CRISPR hits to Bacteroides dorei) was found across >50% of CD subjects. Significant differences had been observed in the richness of both Caudovirales and the virome overall between health and disease in the original analysis (Norman et al., 2015Norman J.M. Handley S.A. Baldridge M.T. Droit L. Liu C.Y. Keller B.C. Kambal A. Monaco C.L. Zhao G. Fleshner P. et al.Disease-specific alterations in the enteric virome in inflammatory bowel disease.Cell. 2015; 160: 447-460Abstract Full Text Full Text PDF PubMed Scopus (736) Google Scholar). Contrary to those previous findings, there were no significant differences in virome richness across the cohorts or disease states when VC count tables were used (Wilcoxon test: CD flare versus remission, p = 0.31; UC flare versus remission, p = 0.96; CD versus healthy, p = 0.12; UC versus healthy, p = 0.83) (Figure 2B). The Shannon diversity metric also did not yield a significant difference (Wilcoxon test: CD versus healthy, p = 0.38; UC versus healthy, p = 0.25; UC versus CD, p = 0.76) (Figure S2A and S2B). When only VCs classified as the order Caudovirales were considered (Figure 2C), a significant increase in richness was observed in CD versus healthy only (Wilcoxon test, p = 0.024). This suggests that changes in the composition of identifiable fraction of the virome may not reflect the virome as a whole. Furthermore, although Anelloviridae were detected in our reanalysis of this dataset, significant differences in abundance were not observed across control CD or UC cohorts, contradictory to previous findings (Wilcoxon test, p > 0.05). Differential abundance analysis identified 37 VCs that were increased in CD relative to controls and 34 increased in UC relative to controls. Importantly, of these VCs increased in disease, over 80% appeared to be temperate (30 of the 37 VCs increased in CD and 28 of the 34 VCs increased in UC). Furthermore, temperate VCs made up just 32% and 24% of VCs increased in controls relative CD and UC, respectively. Further investigation of temperate VC abundance in each cohort indicated that temperate VCs recruited significantly more reads from CD subjects than healthy controls (Wilcoxon test, p = 0.012) (Figure 2D). The temperate, or virulent, switch was also reflected in the taxonomic classification of VCs, which were most differentially abundant. VCs that were increased in healthy cohorts were classified as the predominantly virulent Microviridae (two) and a crAss-like phage (one) (Figures 2E and 2F). Similarly, VCs increased in disease were classified as Siphoviridae (nine in CD and eight in UC) and Myoviridae (one in CD and two in UC), which feature a number of known temperate species. These findings also support the increased Caudovirales richness observed in CD. Furthermore, of the 17 Siphoviridae VCs increased in IBD relative to healthy (nine in CD and eight in UC), 15 were classified as temperate and had CRISPR hits to Firmicutes. These observations correspond with the reduced Firmicutes abundance observed in IBD (Frank et al., 2007Frank D.N. St Amand A.L. Feldman R.A. Boedeker E.C. Harpaz N. Pace N.R. Molecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases.Proc. Natl. Acad. Sci. USA. 2007; 104: 13780-13785Crossref PubMed Scopus (3225) Google Scholar) and further support evidence that increased temperate phage abundance is linked to disease. Induction of Firmicutes prophage in the IBD virome would explain the observed reduction in host abundance and increased temperate Firmicutes phage virions. Many of the most differentially abundant clusters were taxonomically unassigned and represent viral dark matter (49 VCs increased in control versus CD and 25 VCs increased in control versus UC) (Tables S1 and S2). The bacteriome also differs between patients with IBD and controls. Bacterial β diversity assessed through 16S rRNA gene fragment sequencing showed CD (relapse and remission) samples grouping furthest from controls (PERMANOVA, p = 0.0065 and p = 0.0332, respectively) followed by UC (relapse and remission) (PERMANOVA, p = 0.018 and p = 0.001, respectively) (Figure 3A), which was reflected in the virome composition. Interestingly, and in contrast to the virome, the largest degree of variation among samples was observed in the control cohort. Furthermore, the CD cohort exhibited the smallest distances between points (Figures S1C and S1D). Decreased bacterial α diversity was observed in the IBD cohorts versus healthy controls, with the largest differences observed in CD flare (Wilcoxon test, p = 0.012) and remission (Wilcoxon test, p = 0.018) along with UC Flare (Wilcoxon test, p = 0.051) (Figure 3B). Due to the small sample sizes, this analysis was also repeated without the division of disease status and using various metrics (Figures S2C and S2D). For both Chao1 diversity (Wilcoxon test: CD versus healthy, p = 1.8e−10; UC versus healthy, p = 1.6e−4) and Shannon diversity (Wilcoxon test: CD versus healthy, p = 4.8e−10; UC versus healthy, p = 3.3e−4), the healthy cohort was significantly higher than both IBD cohorts, while UC was also significantly increased when compared to CD (Wilcoxon test: Chao1 CD versus UC, p = 8.3e−4; Shannon CD versus UC, p = 9.7e−3). A large number of bacterial taxa were found to be differentially abundant between control versus CD (Figure 3C) and control versus UC (Figure 3D). A total of 113 RSVs (ribosomal sequence variants) were decreased in CD versus controls, while only 17 were increased. Similarly, 69 were increased in control versus UC, and only 21 significantly increased in UC (Tables S3 and S4). Many of the taxa increased in controls versus both IBD cohorts (such as the genus Faecalibacterium) were in accordance with previous reports (García-López et al., 2015García-López R. Vázquez-Castellanos J.F. Moya A. Fragmentation and Coverage Variation in Viral Metagenome Assemblies, and Their Effect in Diversity Calculations.Front. Bioeng. Biotechnol. 2015; 3: 141Crossref PubMed Scopus (21) Google Scholar, Lopez-Siles et al., 2018Lopez-Siles M. Enrich-Capó N. Aldeguer X. Sabat-Mir M. Duncan S.H. Garcia-Gil L.J. Martinez-Medina M. Alterations in the Abundance and Co-occurrence of Akkermansia muciniphila and Faecalibacterium prausnitzii in the Colonic Mucosa of Inflammatory Bowel Disease Subjects.Front. Cell. Infect. Microbiol. 2018; 8: 281Crossref PubMed Scopus (99) Google Scholar, Gevers et al., 2014Gevers D. Kugathasan S. Denson L.A. Vázquez-Baeza Y. Van Treuren W. Ren B. Schwager E. Knights D. Song S.J. Yassour M. et al.The treatment-naive microbiome in new-onset Crohn’s disease.Cell Host Microbe. 2014; 15: 382-392Abstract Full Text Full Text PDF PubMed Scopus (1923) Google Scholar, Pascal et al., 2017Pascal V. Pozuelo M. Borruel N. Casellas F. Campos D. Santiago A. Martinez X. Varela E. Sarrabayrouse G. Machiels K. et al.A microbial signature for Crohn’s disease.Gut. 2017; 66: 813-822Crossref PubMed Scopus (433) Google Scholar, Machiels et al., 2014Machiels K. Joossens M. Sabino J. De Preter V. Arijs I. Eeckhaut V. Ballet V. Claes K. Van Immerseel F. Verbeke K. et al.A decrease of the butyrate-producing species Roseburia hominis and Faecalibacterium prausnitzii defines dysbiosis in patients with ulcerative colitis.Gut. 2014; 63: 1275-1283Crossref PubMed Scopus (1016) Google Scholar). The most differentially abundant RSVs increased in IBD (such as Fusobacterium and Veillonella in CD or Clostridium sensu stricto and Lachnospiraceae family in UC) were also in accordance with the literature (Pascal et al., 2017Pascal V. Pozuelo M. Borruel N. Casellas F. Campos D. Santiago A. Martinez X. Varela E. Sarrabayrouse G. Machiels K. et al.A microbial signature for Crohn’s disease.Gut. 2017; 66: 813-822Crossref PubMed Scopus (433) Google Scholar, Strauss et al., 2011Strauss J. Kaplan G.G. Beck P.L. Rioux K. Panaccione R. Devinney R. Lynch T. Allen-Vercoe E. Invasive potential of gut mucosa-derived Fusobacterium nucleatum positively correlates with IBD status of the host.Inflamm. Bowel Dis. 2011; 17: 1971-1978Crossref PubMed Scopus (349) Google Scholar, Gevers et al., 2014Gevers D. Kugathasan S. Denson L.A. Vázquez-Baeza Y. Van Treuren W. Ren B. Schwager E. Knights D. Song S.J. Yassour M. et al.The treatment-naive microbiome in new-onset Crohn’s disease.Cell Host Microbe. 2014; 15: 382-392Abstract Full Text Full Text PDF PubMed Scopus (1923) Google Scholar, Joossens et al., 2011Joossens M. Huys G. Cnockaert M. De Preter V. Verbeke K. Rutgeerts P. Vandamme P. Vermeire S. Dysbiosis of the faecal microbiota in patients with Crohn’s disease and their unaffected relatives.Gut. 2011; 60: 631-637Crossref PubMed Scopus (684) Google Scholar, Willing et al., 2010Willing B.P. Dicksved J. Halfvarson J. Andersson A.F. Lucio M. Zheng Z. Jarnerot G. Tysk C. Jansson J.K. Engstrand L. A pyrosequencing study in twins shows that gastrointestinal microbial profiles vary with inflammatory bowel disease phenotypes.Gastroenterology. 2010; 139: 1844-1854e1Abstract Full Text Full Text PDF PubMed Scopus (752) Google Scholar). The drivers of significant shifts in β diversity were assessed through correlations between principal coordinates and the relative abundances of VCs (for the virome) and RSVs (for the bacteriome). There were 25 VCs significantly correlated to PC-axes 1 and/or 2 (Spearman, p < 0.05) (Figure 4A; Table S5). Dependent upon the correlation coefficient, the associations could further be broken down into four quadrants and largely supported differential abundance data. In quadrant 1 (top left, Figure 4A), toward subjects with IBD, there were 18 s" @default.
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• W2989706094 title "Whole-Virome Analysis Sheds Light on Viral Dark Matter in Inflammatory Bowel Disease" @default.
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