Human enteric viruses autonomously shape inflammatory bowel disease phenotype through divergent innate immunomodulation
Bibliographic record
Abstract
Altered enteric microorganisms in concert with host genetics shape inflammatory bowel disease (IBD) phenotypes. However, insight is limited to bacteria and fungi. We found that eukaryotic viruses and bacteriophages (collectively, the virome), enriched from non-IBD, noninflamed human colon resections, actively elicited atypical anti-inflammatory innate immune programs. Conversely, ulcerative colitis or Crohn's disease colon resection viromes provoked inflammation, which was successfully dampened by non-IBD viromes. The IBD colon tissue virome was perturbed, including an increase in the enterovirus B species of eukaryotic picornaviruses, not previously detected in fecal virome studies. Mice humanized with non-IBD colon tissue viromes were protected from intestinal inflammation, whereas IBD virome mice exhibited exacerbated inflammation in a nucleic acid sensing-dependent fashion. Furthermore, there were detrimental consequences for IBD patient-derived intestinal epithelial cells bearing loss-of-function mutations within virus sensor MDA5 when exposed to viromes. Our results demonstrate that innate recognition of IBD or non-IBD human viromes autonomously influences intestinal homeostasis and disease phenotypes. Thus, perturbations in the intestinal virome, or an altered ability to sense the virome due to genetic variation, contribute to the induction of IBD. Harnessing the virome may offer therapeutic and biomarker potential.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".