The gut microbiota of toll‐like receptor 2‐deficient mice exhibits lineage‐specific modifications
Bibliographic record
Abstract
Mutations in toll-like receptors that mediate bacterial recognition by the mammalian innate immune system have the potential to substantially alter the composition of an individual's microbiota. Here we tested this hypothesis by comparing the intestinal microbiota of toll-like receptor 2-deficient mice, both young and middle aged, with that of wild-type mice of the same genetic background, housed together under specific pathogen-free conditions. Bacterial DNA was extracted from mouse caecal tissue samples, amplified using universal bacterial 16S ribosomal RNA gene primers, and cloned into a plasmid vector. Insert-containing colonies were picked for high-throughput sequencing, and sequence data were analysed yielding species-level phylogenetic data. Clone libraries were compared by phylogenetic composition analysis using UniFrac. While pairwise differences in phylogenetic population structure between mutant and wild-type mice were not statistically significant, anosim analysis did demonstrate a significant difference between toll-like receptor 2-deficient mice and their wild-type counterparts. The difference observed was probably due to a high level of colonization of the toll-like receptor 2-deficient mice by two distinct Helicobacter phylotypes that were totally absent from wild-type mice. Principal coordinate analysis clustering indicated that age is a weaker determinate than genotype and maternal heritage in the mouse caecal microbiota. The findings suggest that although mutations in toll-like receptors may cause increased susceptibility to specific opportunistic bacteria, they do not dramatically alter the phylogenetic structure of microbiota.
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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 | 0.001 | 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) | 0.001 | 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".