Integrated multi-omics analyses reveal the biochemical mechanisms and phylogenetic relevance of anaerobic androgen biodegradation in the environment
Bibliographic record
Abstract
Steroid hormones, such as androgens, are common surface-water contaminants. However, literature on the ecophysiological relevance of steroid-degrading organisms in the environment, particularly in anoxic ecosystems, is extremely limited. We previously reported that Steroidobacter denitrificans anaerobically degrades androgens through the 2,3-seco pathway. In this study, the genome of Sdo. denitrificans was completely sequenced. Transcriptomic data revealed gene clusters that were distinctly expressed during anaerobic growth on testosterone. We isolated and characterized the bifunctional 1-testosterone hydratase/dehydrogenase, which is essential for anaerobic degradation of steroid A-ring. Because of apparent substrate preference of this molybdoenzyme, corresponding genes, along with the signature metabolites of the 2,3-seco pathway, were used as biomarkers to investigate androgen biodegradation in the largest sewage treatment plant in Taipei, Taiwan. Androgen metabolite analysis indicated that denitrifying bacteria in anoxic sewage use the 2,3-seco pathway to degrade androgens. Metagenomic analysis and PCR-based functional assays showed androgen degradation in anoxic sewage by Thauera spp. through the action of 1-testosterone hydratase/dehydrogenase. Our integrative 'omics' approach can be used for culture-independent investigations of the microbial degradation of structurally complex compounds where isotope-labeled substrates are not easily available.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".