A288 DISTINCT ROLES IN INNATE HOST DEFENSE AND SUSCEPTIBILITY TO COLONIC INJURY IN MUC2 MUCIN DEFICIENT AND SUFFICIENT MICROBIOTA
Bibliographic record
Abstract
The intestinal epithelium is covered with a thick viscous MUC2 mucin bilayer that acts as a protective barrier and is the habitat for 1014 microorganisms that form the microbiota. Even though disruption of colonic mucus and alterations in microbial composition are intimately linked to gastrointestinal health and disease, their distinct contribution in the pathogenesis of colitis is not well understood. To interrogate the impact of alterations in the microbial composition in animals with/without Muc2 mucus in colonic epithelial barrier dysfunction and inflammation. To quantify the role of the microbiota in disease pathogenesis Muc2+/+ and Muc2-/- littermates were treated with a cocktail of antibiotics that reduced indigenous bacteria (up to 80%) as revealed by 16s rRNA sequencing analysis, and then fecal transplanted (FMT) with littermate stool and susceptibility to chemical (dextran sulphate sodium (DSS)) and pathogen-induced (Citrobacter rodentium) quantified. Sequencing analysis revealed that even though Muc2+/+ and Muc2-/- mice share similar phyla distribution, their distinct gastrointestinal phenotypes remained intact. Muc2-/- animals basally show low-grade ongoing inflammation, increased gastrointestinal permeability and alterations in tight junction proteins that were significantly restored following antibiotic treatment. In FMT studies, Muc2+/+ mice that received Muc2-/- microbiota were highly susceptible to DSS-induced colitis/mortality as compared to Muc2+/+ receiving their own microbiota. Sequencing analysis revealed that this impact could be explained through OTUs from distinctive families (Bacteroidaceae, Enterobacteriaceae, Verrucomicrobiaceae) that are transplantable to Muc2+/+ littermates. Similarly, following antibiotic treatment, Muc2+/+ but not Muc2-/- were more susceptible to C. rodentium pathology and DSS-induced colitis with rapid weight lost and mortality. These studies highlight that Muc2+/+ microbiota with an intact mucus barrier play a protective innate role against DSS-induced colitis, while microbiota from Muc2 deficient animals does not. Importantly, Muc2 deficiency alters the colonic microbiota that enhanced susceptibility to pathogen and DSS-induced colitis in Muc2+/+ littermates demonstrating a critical role for Muc2 mucus in shaping a healthy microbiota in intestinal homeostasis. CCCCONACyT
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".