Antibiotic-induced socio-sexual behavioral deficits are reversed via cecal microbiota transplantation but not androgen treatment
Bibliographic record
Abstract
Recent evidence has demonstrated a sex-specific role of the gut microbiome on social behavior such as anxiety, possibly driven by a reciprocal relationship between the gut microbiome and gonadal hormones. For instance, gonadal hormones drive sex differences in gut microbiota composition, and certain gut bacteria can produce androgens from glucocorticoids. We thus asked whether the gut microbiome can influence androgen-dependent socio-sexual behaviors. We first treated C57BL/6 mice with broad-spectrum antibiotics (ABX) in drinking water to deplete the gut microbiota either transiently during early development (embryonic day 16-postnatal day [PND] 21) or in adulthood (PND 60-85). We hypothesized that if ABX interferes with androgens, then early ABX would interfere with critical periods for sexual differentiation of brain and thus lead to long-term decreases in males' socio-sexual behavior, while adult ABX would interfere with androgens' activational effects on behavior. We found that in males but not females, early and adult ABX treatment decreased territorial aggression, and adult ABX also decreased sexual odor preference. We then assessed whether testosterone and/or cecal microbiota transplantation (CMT) via oral gavage could prevent ABX-induced socio-sexual behavioral deficits in adult ABX-treated males. Mice were treated with same- or other-sex control cecum contents or with testosterone for two weeks. While testosterone was not effective in rescuing any behavior, we found that male CMT restored both olfactory preference and aggression in adult ABX male mice, while female CMT restored olfactory preference but not aggression. These results suggest sex-specific effects of the gut microbiome on socio-sexual behaviors, independent of androgens.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".