Modulation of Gut Microbiota Composition by Serotonin Signaling Influences Intestinal Immune Response and Susceptibility to Colitis
Bibliographic record
Abstract
Background & Aims Serotonin (5-hydroxytryptamine [5-HT]) is synthesized mainly within enterochromaffin (EC) cells in the gut, and tryptophan hydroxylase 1 (Tph1) is the rate-limiting enzyme for 5-HT synthesis in EC cells. Accumulating evidence suggests the importance of gut microbiota in intestinal inflammation. Considering the close proximity of EC cells and the microbes, we investigated the influence of gut-derived 5-HT on the microbiota and the susceptibility to colitis. Methods Gut microbiota of Tph1 -/- and Tph1 +/- mice were investigated by deep sequencing. Direct influence of 5-HT on bacteria was assessed by using in vitro system of isolated commensals. The indirect influence of 5-HT on microbiota was assessed by measuring antimicrobial peptides, specifically β-defensins, in the colon of mice and HT-29 colonic epithelial cells. The impact of gut microbiota on the development of dextran sulfate sodium–induced colitis was assessed by transferring gut microbiota from Tph1 -/- mice to Tph1 +/- littermates and vice versa, as well as in germ-free mice. Results A significant difference in microbial composition between Tph1 -/- and Tph1 +/- littermates was observed. 5-HT directly stimulated and inhibited the growth of commensal bacteria in vitro, exhibiting a concentration-dependent and species-specific effect. 5-HT also inhibited β-defensin production by HT-29 cells. Microbial transfer from Tph1 -/- to Tph1 +/- littermates and vice versa altered colitis severity, with microbiota from Tph1 -/- mice mediating the protective effects. Furthermore, germ-free mice colonized with microbiota from Tph1 -/- mice exhibited less severe dextran sulfate sodium–induced colitis. Conclusions These findings demonstrate a novel role of gut-derived 5-HT in shaping gut microbiota composition in relation to susceptibility to colitis, identifying 5-HT–microbiota axis as a potential new therapeutic target in intestinal inflammatory disorders.
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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".