Gut Microbiota Modulates Behavior in Adult Mice: Potential Role for Microbial‐ Metabolite Sensors in the Brain
Bibliographic record
Abstract
The gut microbiota plays a defined role in the physiology of the gastrointestinal (GI) tract, digesting foods, metabolizing essential vitamins, and protecting the host against opportunistic pathogens. Composed of a complex community of microorganisms, the microbiota is reasonably stable in the adult individual. Due to the extensive bidirectional communication of the GI tract and the central nervous system, it has been demonstrated that the gut microbiota is capable of modulating brain function. However, the contributions of the microbiota to psychological behaviors in the adult are incompletely understood. Moreover, mechanism(s) by which this modulation occurs have also still to be completely elucidated. We hypothesize that gut microbiota influence brain activity and host behavior, signaling via bacterial metabolites acting at distinct receptors in the brain. Metabolites generated by the microbiota are found in the bloodstream and they are altered in accordance with microbial changes, such as in antibiotic treatment. Therefore, antibiotic treatment represents an attractive means for us to test our hypothesis. We assessed the expression of potential microbial‐metabolite sensors in the brain of C57Bl/6 male mice. A broad‐spectrum antibiotic cocktail was administered to mice for 2 weeks to deplete the bacterial community of the intestinal microbiota. The efficacy of antibiotic administration was verified through quantification of the bacterial load and composition in the cecal matter after treatment. Following treatment, behavior was assessed applying the elevated plus maze and the open field test for anxiety‐like behavior and locomotion; the 3‐chamber test for social preference; and the tail suspension test for depression‐like behavior. Microbial metabolite sensing receptors were analyzed in the brain by qPCR. Mice treated with antibiotics had reduced bacterial load and altered composition in the cecal matter, without changes in body weight. No changes were observed in anxiety‐like behavior, locomotion, and social preference when compared to controls. Interestingly, antibiotic‐treated mice presented with a reduction in depressive‐like behavior. Measurement of microbial‐metabolite sensors (e.g. aryl hydrocarbon receptor, AHR; pregnane X receptor; PXR) in the brain were performed to correlate their expression with the phenotypic behavior observed. mRNA of AHR was highly expressed in different regions of the brain ‐ hippocampus, amygdala, and hypothalamus, while levels of PXR mRNA were low in all regions. Moreover, antibiotic treatment reduced expression of AHR mRNA in hippocampus compared to control, whilst no alterations were observed in the amygdala and hypothalamus. These data suggest that changes in the intestinal microbiota lead to specific behavioral alterations. These changes may be driven, in part, by alterations in the expression and/or activity of microbial‐metabolite sensing receptors in the brain. Further work is required to determine if AHR activity directly modulates brain regions responsible for depression‐like behavior. Support or Funding Information Canadian Institutes of Health Research (CIHR) and National Counsel of Technological and Scientific Development (CNPq – Brazil) This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".