Exposure to a social stressor disrupts the community structure of the colonic mucosa-associated microbiota
Bibliographic record
Abstract
BACKGROUND: The microbiota of the mammalian gastrointestinal (GI) tract consists of diverse populations of commensal bacteria that interact with host physiological function. Dysregulating these populations, through exogenous means such as antibiotics or dietary changes, can have adverse consequences on the health of the host. Studies from laboratories such as ours have demonstrated that exposure to psychological stressors disrupts the population profile of intestinal microbiota. To date, such studies have primarily focused on prolonged stressors (repeated across several days) and have assessed fecal bacterial populations. It is not known whether shorter stressors can also impact the microbiota, and whether colonic mucosa-associated populations can also be affected. The mucosa-associated microbiota exist in close proximity to elements of the host immune system and the two are tightly interrelated. Therefore, alterations in these populations should be emphasized. Additionally, stressors can induce differential responses in anxiety-like behavior and corticosterone outputs in variant strains of mice. Thus, whether stressor exposure can have contrasting effects on the colonic microbiota in inbred C57BL/6 mice and outbred CD-1 mice was also examined. RESULTS: In the present study, we used high throughput pyrosequencing to assess the effects of a single 2-hour exposure to a social stressor, called social disruption (SDR), on colonic mucosa-associated microbial profiles of C57BL/6 mice. The data indicate that exposure to the stressor significantly changed the community profile and significantly reduced the relative proportions of two genera and one family of highly abundant intestinal bacteria, including the genus Lactobacillus. This finding was confirmed using a quantitative real-time polymerase chain reaction (qPCR) technique. The use of qPCR also identified mouse strain-specific differences in bacterial abundances. L. reuteri, an immunomodulatory species, was decreased in stressor-exposed CD-1 mice, but not C57BL/6 mice. CONCLUSIONS: These data illustrate that stressor exposure can affect microbial populations, including the lactobacilli, that are closely associated with the colonic mucosa. Because the lactobacilli can have beneficial effects on human health, stressor-induced reductions of their population could have important health implications.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".