<i>In vitro</i> modeling of the female gut microbiome: effects of sex hormones and psychotropic drugs
Bibliographic record
Abstract
ABSTRACT Sex hormones play a crucial role in shaping gut microbiome composition and metabolism, with significant implications for mental health. This study investigated the effects of sex hormones and the psychotropic drug aripiprazole on the gut microbiome, using a novel in vitro colonic fermentation model adapted from the PolyFermS system. Fecal samples from four male and female donors were used to develop sexually divergent models, with the female model subjected to hormonal treatments mimicking different phases of the menstrual cycle. Microbiome composition and short-chain fatty acid (SCFA) metabolism were analyzed. The results demonstrated that sex hormones significantly influenced microbiota structure and diversity, with the female model exhibiting reduced α-diversity and distinct bacterial associations with SCFAs. Hormonal fluctuations across menstrual phases induced specific shifts in bacterial composition, notably increasing Bacteroidota while decreasing Bacillota and Pseudomonadota. In the female model, aripiprazole treatment led to increased microbial diversity and altered SCFA profiles, although the changes in SCFAs were not statistically significant ( P > 0.05). Differential abundance analysis revealed sex-specific enrichment of bacterial genera, such as Eubacterium coprostanoligenes and Agathobacter . These findings underscore the importance of considering sex-specific microbiome profiles and hormonal influences when optimizing psychotropic treatments for mental health disorders. IMPORTANCE The gut microbiome plays a crucial role in human health, affecting metabolism, immunity, and brain function. However, the role of sex hormones in shaping the gut microbiome composition and metabolism remains largely unexplored. This study introduces a novel in vitro colonic fermentation model to investigate the effects of sex hormone fluctuations and psychotropic drug exposure on the gut microbiome. By simulating a sexually divergent human colon environment and mimicking hormonal variations throughout the menstrual cycle, this model provides a controlled setting for studying microbiome response to external stimuli. Our findings revealed that sex hormones, such as estrogen, progesterone, and testosterone, shape microbial diversity and alter the microbiome composition compared to the control group. Additionally, this study examined the effect of psychotropic drug exposure on the microbiota of a simulated female colon, revealing alterations in the microbial composition and metabolism. These results highlight the importance of considering the role of the gut microbiome in drug response, given the widespread use of psychiatric medications, particularly among women. This novel colonic fermentation model offers a valuable tool for studying sex-specific microbiome dynamics and their broader implications for health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".