Bile acid metabolites control Th17 and Treg cell differentiation
Bibliographic record
Abstract
Abstract Bile acids are abundantly present in the mammalian gut, where they undergo bacteria-mediated transformation, generating a large pool of bioactive molecules. While they have been shown to affect host metabolism, cancer progression and innate immunity, it is unknown whether bile acids affect the function of adaptive immune cells such as T cells expressing IL-17a (Th17 cells) and regulatory T cells (Tregs) that mediate inflammatory and anti-inflammatory responses, respectively. By screening a small-molecule library primarily composed of bile acid metabolites, we identified two distinct derivatives of lithocholic acid (LCA), 3-oxoLCA and isoalloLCA, as specific regulators of Th17 and Treg cells. While 3-oxoLCA inhibited Th17 cell differentiation by directly binding to its key transcription factor RORγt (retinoid-related orphan receptor γt), isoalloLCA enhanced Treg differentiation through the production of mitochondrial reactive oxygen species (mitoROS), leading to increased FoxP3 expression. IsoalloLCA-mediated Treg enhancement required an intronic FoxP3 enhancer the conserved noncoding sequence 3 (CNS3), suggesting a distinct mode of action from other previously identified Treg enhancing metabolites that require CNS1. Lastly, oral administration of 3-oxoLCA and isoalloLCA to mice led to reduced Th17 and increased Treg cell differentiation in the intestinal lamina propria. Altogether, our data suggest novel mechanisms by which bile acid metabolites control host immune responses by directly modulating the Th17 and Treg balance.
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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) | 0.002 | 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".