Changes in social environment impact primate gut microbiota composition
Bibliographic record
Abstract
BACKGROUND: The gut microbiota (GM) has proven to be essential for both physical health and mental wellbeing, yet the forces that ultimately shape its composition remain opaque. One critical force known to affect the GM is the social environment. Prior work in humans and free-ranging non-human primates has shown that cohabitation and frequent social interaction can lead to changes in GM composition. However, it is difficult to assess the direction of causation in these studies, and interpretations are complicated by the influence of uncontrolled but correlated factors, such as shared diet. RESULTS: We performed a 15-month longitudinal investigation wherein we disentangled the impacts of diet and social living conditions on GM composition in a captive cohort of 13 male cynomolgus macaques. The animals were in single housing for the first 3 months of the study initially with a variable diet. After baseline data collection they were placed on a controlled diet for the remainder of the study. Following this diet shift the animals were moved to paired housing for 6 months, enabling enhanced social interaction, and then subsequently returned to single housing at the end of our study. This structured sequencing of diet and housing changes allowed us to assess their distinct impacts on GM composition. We found that the early dietary adjustments led to GM changes in both alpha and beta diversity, whereas changes in social living conditions only altered beta diversity. With respect to the latter, we found that two particular bacterial families - Lactobacillaceae and Clostridiaceae - demonstrated significant shifts in abundance during the transition from single housing to paired housing, which was distinct from the shifts we observed based on a change in diet. Conversely, we found that other bacteria previously associated with sociality were not altered based on changes in social living conditions but rather only by changes in diet. CONCLUSIONS: Together, these findings decouple the influences that diet and social living have on GM composition and reconcile previous observations in the human and animal literatures. Moreover, the results indicate biological alterations of the gut that may, in part, mediate the relationship between sociality and wellbeing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".