Microbiota shape the colon epithelium controlling inter-crypt absorptive goblet cells via butyrate–GP R109A signalling
Bibliographic record
Abstract
The colonic epithelium is a key interface between the gut microbiota and the host. How microbiota-derived signals influence epithelial cell identity and function remains incompletely understood. Here, we used single-cell transcriptomics, antibiotic-mediated microbiota depletion, germ-free mice and colonization experiments in mice to uncover cell-type-specific responses to microbiota changes, highlighting changes in the cell composition and functional diversities in enterocytes. Our analysis demonstrates that the microbiota control the absorptive profile of the colon epithelial cells and reveals non-canonical inter-crypt goblet cells as microbiota-responsive constituents that combine absorptive and secretory features and whose abundance is regulated by the gut microbiota. We found that their number is suppressed through the short-chain fatty acid butyrate and its receptor GPR109A. Analysis in mouse and humans indicates that the expansion of this hybrid population increases with age and that this expansion is driven by microbiome changes. Our work reveals a previously unrecognized level of epithelial plasticity driven by microbial triggers and highlights butyrate, acting as a signaling molecule that shapes the colon micro-anatomy.
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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 | 0.000 | 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".