Alterations in fecal β-defensin-3 secretion as a marker of instability of the gut microbiota
Bibliographic record
Abstract
Compositional changes in the microbiota (dysbiosis) may be a basis for Irritable Bowel Syndrome (IBS), but biomarkers are currently unavailable to direct microbiota-directed therapy. We therefore examined whether changes in fecal β-defensin could be a marker of dysbiosis in a murine model. Experimental dysbiosis was induced using four interventions relevant to IBS: a mix of antimicrobials, westernized diets (high-fat/high-sugar and high salt diets), or mild restraint stress. Fecal mouse β-defensin-3 and 16S rRNA-based microbiome profiles were assessed at baseline and during and following these interventions. Each intervention, except for mild restraint stress, altered compositional and diversity profiles of the microbiota. Exposure to antimicrobials or a high-fat/high-sugar diet, but not mild restraint stress, resulted in decreased fecal β-defensin-3 compared to baseline. In contrast, exposure to the high salt diet increased β-defensin-3 compared to baseline. Mice exposed to the mix of antimicrobials showed the largest compositional changes and the most significant correlations between β-defensin-3 levels and bacterial diversity. The high salt diet was also associated with significant correlations between changes in β-defensin-3 and bacterial diversity, and this was not accompanied by discernible inflammatory changes in the host. Thus, dietary change or antimicrobial exposure, both recognized factors in IBS exacerbations, induced marked dysbiosis that was accompanied by changes in fecal β-defensin-3 levels. We propose that serial monitoring of fecal β-defensins may serve as a marker of dysbiosis and help identify those IBS patients who may benefit from microbiota-directed therapeutic interventions.
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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".