Metabolites Detected during Biodegradation of <sup>13</sup>C<sub>6</sub>-Benzene in Nitrate-Reducing and Methanogenic Enrichment Cultures
Bibliographic record
Abstract
The mechanism for anaerobic metabolism of benzene remains unknown. To date, there have been only a few studies reporting metabolites of anaerobic benzene biodegradation, in part because anaerobic benzene-degrading enrichment cultures are not very common and only two isolates have been characterized to date. Phenol and benzoate, metabolites consistent with benzene hydroxylation or benzene carboxylation, have been identified previously in mixed cultures, and more recently benzene methylation to toluene has been proposed as another possible mechanism for anaerobic benzene degradation. In this study, 13C6-benzene was added to nitrate-reducing and methanogenic enrichment cultures and specific 13C-labeled metabolites were monitored over time. The putative metabolites were detected by gas chromatography/mass spectrometry in ether extracts of 100-mL samples of culture taken at each time point. This method of analysis provided the sensitivity required to accurately quantify low concentrations of these compounds. In addition, benzoate trapping was used in an attemptto increase concentrations of upstream metabolites. In both cultures, in the presence and absence of unlabeled benzoate (trap), [ring-13C]-toluene and [ring-13C]benzoate were detected transiently during degradation. The data strongly support initial methylation of benzene to toluene, followed bytransformation to benzoate. Although benzene methylation has been proposed previously, this is the first direct evidence to supportthis pathway. In the methanogenic culture only, 13C6-phenol was also detected. The transient appearance of phenol, which appeared to be further transformed to benzoate, suggests that a pathway involving hydroxylation to phenol, as proposed in other studies, was also operative.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".