High salt diet exacerbates colitis in mice by decreasing Lactobacillus levels and butyrate production
Bibliographic record
Abstract
BACKGROUND: Changes in hygiene and dietary habits, including increased consumption of foods high in fat, simple sugars, and salt that are known to impact the composition and function of the intestinal microbiota, may explain the increase in prevalence of chronic inflammatory diseases. High salt consumption has been shown to worsen autoimmune encephalomyelitis and colitis in mouse models through p38/MAPK signaling pathway. However, the effect of high salt diet (HSD) on gut microbiota and on intestinal immune homeostasis, and their roles in determining vulnerability to intestinal inflammatory stimuli are unknown. Here, we investigate the role of gut microbiota alterations induced by HSD on the severity of murine experimental colitis. RESULTS: Compared to control diet, HSD altered fecal microbiota composition and function, reducing Lactobacillus sp. relative abundance and butyrate production. Moreover, HSD affected the colonic, and to a lesser extent small intestine mucosal immunity by enhancing the expression of pro-inflammatory genes such as Rac1, Map2k1, Map2k6, Atf2, while suppressing many cytokine and chemokine genes, such as Ccl3, Ccl4, Cxcl2, Cxcr4, Ccr7. Conventionally raised mice fed with HSD developed more severe DSS- (dextran sodium sulfate) and DNBS- (dinitrobenzene sulfonic acid) induced colitis compared to mice on control diet, and this effect was absent in germ-free mice. Transfer experiments into germ-free mice indicated that the HSD-associated microbiota profile is critically dependent on continued exposure to dietary salt. CONCLUSIONS: Our results indicate that the exacerbation of colitis induced by HSD is associated with reduction in Lactobacillus sp. and protective short-chain fatty acid production, as well as changes in host immune status. We hypothesize that these changes alter gut immune homeostasis and lead to increased vulnerability to inflammatory insults.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".