The Murine Caecal MicroRNA Signature Depends on the Presence of the Endogenous Microbiota
Bibliographic record
Abstract
The intestinal messenger RNA expression signature is affected by the presence and composition of the endogenous microbiota, with effects on host physiology. The intestine is also characterized by a distinctive micronome. However, it is not known if microbes also impact intestinal gene expression epigenetically. We investigated if the murine caecal microRNA expression signature depends on the presence of the microbiota, and the potential implications of this interaction on intestinal barrier function. Three hundred and thirty four microRNAs were detectable in the caecum of germ-free and conventional male mice and 16 were differentially expressed, with samples from the two groups clustering separately based on their expression patterns. Through a combination of computational and gene expression analyses, including the use of our curated list of 527 genes involved in intestinal barrier regulation, 2,755 putative targets of modulated microRNAs were identified, including 34 intestinal barrier-related genes encoding for junctional and mucus layer proteins and involved in immune regulation. This study shows that the endogenous microbiota influences the caecal microRNA expression signature, suggesting that microRNA modulation is another mechanism through which commensal bacteria impact the regulation of the barrier function and intestinal homeostasis. Through microRNAs, the gut microbiota may impinge a much larger number of genes than expected, particularly in diseases where its composition is altered. In this perspective, abnormally expressed microRNAs could be considered as novel therapeutic targets.
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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".