The microbial metabolite <i>p</i> -Cresol induces autistic-like behaviors in mice by remodeling the gut microbiota
Bibliographic record
Abstract
ABSTRACT Background Autism Spectrum Disorders (ASD) are associated with dysregulation of the microbiota-gut-brain axis resulting in changes in microbiota composition as well as fecal, serum and urine levels of microbial metabolites. Yet, a causal relationship between dysregulation of the microbiota-gut-brain axis and ASD remains to be demonstrated. Here, we hypothesized that the microbial metabolite p -Cresol, which is more abundant in ASD patients compared to neurotypical individuals, could induce ASD-like behavior in mice. Results Mice exposed to p -Cresol for 4 weeks in drinking water presented social behavior deficits, stereotypies, and perseverative behaviors, but no changes in anxiety, locomotion, or cognition. Abnormal social behavior induced by p -Cresol was associated with decreased activity of central dopamine neurons involved in the social reward circuit. Further, p -Cresol induced changes in microbiota composition and social behavior deficits could be transferred from p -Cresol-treated mice to control mice by fecal microbiota transplantation (FMT). We also showed that mice transplanted with the microbiota of p -Cresol-treated mice exhibited increased fecal p- Cresol levels compared to mice transplanted with the microbiota of control mice and identified possible p -Cresol bacterial producers. Lastly, the microbiota of control mice rescued social interactions, dopamine neurons excitability and fecal p -Cresol levels when transplanted to p- Cresol-treated mice. Conclusions The microbial metabolite p- Cresol induces ASD core behavioral symptoms in mice via a gut microbiota-dependent mechanism. Our study paves the way for therapeutic interventions targeting the microbiota to treat patients with ASD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".