Bacterial Bile Metabolising Gene Abundance in Crohn's, Ulcerative Colitis and Type 2 Diabetes Metagenomes
Bibliographic record
Abstract
We performed an analysis to determine the importance of bile acid modification genes in the gut microbiome of inflammatory bowel disease and type 2 diabetic patients. We used publicly available metagenomic datasets from the Human Microbiome Project and the MetaHIT consortium, and determined the abundance of bile salt hydrolase gene (bsh), 7 alpha-dehydroxylase gene (adh) and 7-alpha hydroxysteroid dehydrogenase gene (hsdh) in fecal bacteria in diseased populations of Crohn's disease (CD), Ulcerative Colitis (UC) and Type 2 diabetes mellitus (T2DM). Phylum level abundance analysis showed a significant reduction in Firmicute-derived bsh in UC and T2DM patients but not in CD patients, relative to healthy controls. Reduction of adh and hsdh genes was also seen in UC and T2DM patients, while an increase was observed in the CD population as compared to healthy controls. A further analysis of the bsh genes showed significant differences in the correlations of certain Firmicutes families with disease or healthy populations. From this observation we proceeded to analyse BSH protein sequences and identified BSH proteins clusters representing the most abundant strains in our analysis of Firmicute bsh genes. The abundance of the bsh genes corresponding to one of these protein clusters was significantly reduced in all disease states relative to healthy controls. This cluster includes bsh genes derived from Lachospiraceae, Clostridiaceae, Erysipelotrichaceae and Ruminococcaceae families. This metagenomic analysis provides evidence of the importance of bile acid modifying enzymes in health and disease. It further highlights the importance of identifying gene and protein clusters, as the same gene may be associated with health or disease, depending on the strains expressing the enzyme, and differences in the enzymes themselves.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".