Disease-specific Alterations in the Enteric Virome in Inflammatory Bowel Disease
By J. Norman, S. Handley, Megan T. Baldridge, L. Droit, Catherine Y. Liu, B. Keller, Amal Kambal, Cynthia L. Monaco, Guoyan Zhao, P. Fleshner and 10 more. Cell, 2015
1,135 citations recorded by the source corpus.
SUMMARY Decreases in the diversity of enteric bacterial populations are observed in patients with Crohn’s disease (CD) and ulcerative colitis (UC). Less is known about the virome in these diseases. We show that the enteric virome is abnormal in CD and UC patients. In-depth analysis of preparations enriched for free virions in the intestine revealed that CD and UC were associated with a significant expansion of Caudovirales bacteriophages. The viromes of CD and UC patients were disease- and cohort-specific. Importantly, it did not appear that expansion and diversification of the enteric virome was secondary to changes in bacterial populations. These data support a model in which changes in the virome may contribute to intestinal inflammation and bacterial dysbiosis. We conclude that the virome is a candidate for contributing to, or being a biomarker for, human inflammatory bowel disease and speculate that the enteric virome may play a role in other diseases.
Subfields: Accounting, Economics and Econometrics
View Paper: https://www.semanticscholar.org/paper/ea816c30e0df51a631c56379404b292501a4ca82
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Citations in the corpus
- Mechanisms and consequences of intestinal dysbiosis (2017, background): “Bacteriophage richness, as defined by the number of taxa per sample, was increased in these diseases, whereas bacterial richness was concomitantly decreased [174].”
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- Inflammation, Antibiotics, and Diet as Environmental Stressors of the Gut Microbiome in Pediatric Crohn’s Disease (2015, background): “A recent report proposed that tailed phages (Caudovirales) were enriched in viral concentrates from stool of IBD patients (Norman et al., 2015).”
- The human gut virome is highly diverse, stable and individual-specific (2019, background): “Illustrating this 329 point, many previous studies only looked at a fraction of identifiable sequences (14-30%), 330 effectively ignoring the rest of the virome (D’arc et al., 2018; Norman et al., 2015).”
- Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights (2016, background): “More recently, shotgun metagenomics [19] provided expanded resolution to the level of microbial species [20-22] and strain [23], to the fungal and viral kingdoms [24], and to the level of individual genes across the metagenome [25,26].”
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