Proteolytic bacteria expansion during colitis amplifies inflammation through cleavage of the external domain of PAR2
Bibliographic record
Abstract
Imbalances in proteolytic activity have been linked to the development of inflammatory bowel diseases (IBD) and experimental colitis. Proteases in the intestine play important roles in maintaining homeostasis, but exposure of mucosal tissues to excess proteolytic activity can promote pathology through protease-activated receptors (PARs). Previous research implicates microbial proteases in IBD, but the underlying pathways and specific interactions between microbes and PARs remain unclear. In this study, we investigated the role of microbial proteolytic activation of the external domain of PAR2 in intestinal injury using mice expressing PAR2 with a mutated N-terminal external domain that is resistant to canonical activation by proteolytic cleavage. Our findings demonstrate the key role of proteolytic cleavage of the PAR2 external domain in promoting intestinal permeability and inflammation during colitis. In wild-type mice expressing protease-sensitive PAR2, excessive inflammation leads to the expansion of bacterial taxa that cleave the external domain of PAR2, exacerbating colitis severity. In contrast, mice expressing mutated protease-resistant PAR2 exhibit attenuated colitis severity and do not experience the same proteolytic bacterial expansion. Colonization of wild-type mice with proteolytic PAR2-activating Enterococcus and Staphylococcus worsens colitis severity. Our study identifies a previously unknown interaction between proteolytic bacterial communities, which are shaped by inflammation, and the external domain of PAR2 in colitis. The findings should encourage new therapeutic developments for IBD by targeting excessive PAR2 cleavage by bacterial proteases.
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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".