GPR109A expressed on medullary thymic epithelial cells affects thymic Treg development
Bibliographic record
Abstract
Abstract Regulatory T cells (Treg) maintain immune homeostasis due to their anti‐inflammatory functions. They can be generated either centrally in the thymus or in peripheral organs. Metabolites such as short‐chain fatty acids produced by intestinal microbiota can induce peripheral Treg differentiation, by activating G‐protein‐coupled‐receptors like GPR109A. In this study, we identified a novel role for GPR109A in thymic Treg development. We found that Gpr109a−/− mice had increased Treg under basal conditions in multiple organs compared with WT mice. GPR109A was not expressed on T cells but on medullary thymic epithelial cells (mTECs), as revealed by single‐cell RNA sequencing in both mice and humans and confirmed by flow cytometry in mice. mTECs isolated from Gpr109a−/− mice had higher expression of autoimmune regulator (AIRE), the key regulator of Treg development, while the subset of mTECs that did not express Gpr109a in the WT displayed increased Aire expression and also enhanced signaling related to mTEC functionality. Increased thymic Treg in Gpr109a−/− mice was associated with protection from experimental autoimmune encephalomyelitis, with ameliorated clinical signs and reduced inflammation. This work identifies a novel role for GPR109A and possibly the gut microbiota, on thymic Treg development via its regulation of mTECs.
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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".