Commensal bacterial-derived retinoic acid primes host defense to intestinal infection
Bibliographic record
Abstract
Summary Interactions between the microbiota and mammalian host are essential for effective defense against pathogenic infection; however, the microbial-derived cues that mediate this beneficial relationship remain unclear. Here, we find that the intestinal epithelial cell (IEC)-associated commensal bacteria, Segmented Filamentous Bacteria (SFB), promotes early protection against the bacterial pathogen, Citrobacter rodentium , independently of CD4 + T cells. Global analyses demonstrated that SFB induced histone modifications in IECs at sites enriched for the retinoic acid receptor (RAR) motif. Interestingly, SFB-colonized mice exhibited greater expression of RAR targets during infection relative to germ-free mice, suggesting SFB may enhance defense through retinoic acid (RA) signaling. Consistent with this, supplementing germ-free mice with RA decreased pathogen levels. Further, mice with impaired RA-responsiveness in IECs displayed increased susceptibility to C. rodentium infection. RA was elevated in the intestine of mice colonized with SFB, indicating that the presence of commensal bacteria can modulate intestinal RA levels. However, this regulation by SFB was not dependent on mammalian RA production. Sequence analyses suggested that RA-generating enzymes are expressed by a subset of commensal bacteria. Remarkably, RA was produced by intestinal bacteria including SFB, and inhibiting RA signaling blocked SFB-induced protection against C. rodentium infection. These data collectively reveal RA as an unexpected microbiota-derived metabolite that primes innate intestinal defense and suggests that pre- and probiotic approaches to elevate RA could prevent or combat pathogenic infection.
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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 | 0.001 |
| 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".