Microbiota Inhibit Epithelial Pathogen Adherence by Epigenetically Regulating C-Type Lectin Expression
Bibliographic record
Abstract
Numerous bacterial pathogens infect the mammalian host by initially associating with epithelial cells that line the intestinal lumen. Recent work has revealed that commensal bacteria that reside in the intestine promote defense against pathogenic infection, however whether the microbiota direct host pathways that alter pathogen adherence is not well-understood. Here, by comparing germ-free mice, we identify that the microbiota decrease bacterial pathogen adherence and dampen epithelial expression of the cell surface glycoprotein C-type lectin 2e (Clec2e). Functional studies revealed that overexpression of this lectin promotes adherence of intestinal bacterial pathogens to mammalian cells. Interestingly, microbiota-sensitive downregulation of Clec2e corresponds with decreased histone acetylation of the Clec2e gene in intestinal epithelial cells. Histone deacetylation and transcriptional regulation of Clec2e depends on expression and recruitment of the histone deacetylase HDAC3. Thus, commensal bacteria epigenetically instruct epithelial cells to decrease expression of a C-type lectin that promotes pathogen adherence, revealing a novel mechanism for how the microbiota promote innate defense against 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".