Nod1 and Nod2 signaling does not alter the composition of intestinal bacterial communities at homeostasis
Bibliographic record
Abstract
Patients with inflammatory bowel diseases (IBD) harbour intestinal bacterial communities with altered composition compared with healthy counterparts; however, it is unknown whether changes in the microbiota are associated with genetic susceptibility of individuals for developing disease or instead reflect other changes in the intestinal environment related to the disease itself. Since deficiencies in the innate immune receptors Nod1 and Nod2 are linked to IBD, we tested the hypothesis that Nod-signaling alters intestinal immune profiles and subsequently alters bacterial community structure. We used qPCR to analyze expression patterns of selected immune mediators in the ileum and cecum of Nod-deficient mice compared with their Nod-sufficient littermates and assessed the relative abundance of major bacterial groups sampled from the ileum, cecum and colon. The Nod1-deficient ileum exhibited significantly lower expression of Nod2, Muc2, α- and β-defensins and keratinocyte-derived chemokine (KC), suggesting a weakened epithelial barrier compared with WT littermates; however, there were no significant differences in the relative abundance of targeted bacterial groups, indicating that Nod1-associated immune differences alone do not promote dysbiosis. Furthermore, Nod2-deficient mice did not display any changes in the expression of immune markers or bacterial communities. Shifts in bacterial communities that were observed in this study correlated with housing conditions and were independent of genotype. These findings emphasize the importance of using F2 littermate controls to minimize environmental sources of variation in microbial analyses, to establish baseline conditions for host-microbe homeostasis in Nod-deficient mice and to strengthen models for testing factors contributing to microbial dysbiosis associated with IBD.
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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) | 0.000 | 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 | 0.001 |
| 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".