Ability of the gut microbiota to produce PUFA‐derived bacterial metabolites: Proof of concept in germ‐free versus conventionalized mice
Bibliographic record
Abstract
SCOPE: The gut microbiota is able to modulate host physiology through the production of bioactive metabolites. Our recent studies suggest that changes in gut microbiota composition upon prebiotics supplementation alter tissue levels of PUFA-derived metabolites in mice. However, in vivo evidence that gut microbes produces PUFA-derived metabolites is lacking. This study aimed to decipher the contribution of gut microbes versus that of the host in PUFA-derived metabolite production. METHODS AND RESULTS: To achieve this goal, we compared the proportion of PUFA-derived metabolites and the expression of fatty acid desaturases in germ-free (GF) and conventionalized (CONV) mice fed either a low fat or Western diet. Higher concentrations of PUFA-derived metabolites were found in the colonic contents of conventionalized mice (CONV) mice compared to GF mice. The abundance of these metabolites in host tissues was modulated by dietary treatments but not by microbial status. Although microbial status did significantly influence desaturase expression, no correlations between host enzymes and tissue PUFA-derived metabolite levels were observed. CONCLUSION: Together, these results highlight the ability of the gut microbiota to produce PUFA-derived metabolites from dietary PUFA. However, microbial production of these metabolites in colonic contents is not necessarily associated with modifications of their concentration in host tissues.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".