Diet-derived urolithin A is produced by a dehydroxylase encoded by human gut Enterocloster species
Bibliographic record
Abstract
Urolithin A (uroA) is a polyphenol derived from the multi-step metabolism of dietary ellagitannins by the human gut microbiota. Once absorbed, uroA can trigger mitophagy and aryl hydrocarbon receptor signaling pathways, altering host immune function, mitochondrial health, and intestinal barrier integrity. Most individuals harbor a microbiota capable of uroA production; however, the mechanisms underlying the dehydroxylation of its catechol-containing precursor (uroC) are unknown. Here, we use a combination of untargeted bacterial transcriptomics, proteomics, and comparative genomics to uncover an inducible uroC dehydroxylase (ucd) operon in Enterocloster species. We show that the ucd operon encodes a predicted molybdopterin-dependent enzyme complex that dehydroxylates urolithins at a specific position (9-OH). By interrogating publicly available metagenomics datasets, we observed that uroC-metabolizing Enterocloster species and ucd operon genes are prevalent in human feces. In ex vivo experiments with human fecal samples, only samples actively transcribing ucd could produce uroA, possibly explaining differences in urolithin metabolism between individuals. Collectively, this work identifies Enterocloster species and the ucd operon as important contributors to uroA production and establishes a multi-omics framework to further our mechanistic understanding of polyphenol metabolism by the human gut 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".