Aerobic Biodegradation of 2,2′-Dithiodibenzoic Acid Produced from Dibenzothiophene Metabolites
Bibliographic record
Abstract
Dibenzothiophene is a sulfur heterocycle found in crude oils and coal. The biodegradation of dibenzothiophene through the Kodama pathway by Pseudomonas sp. strain BT1d leads to the formation of three disulfides: 2-oxo-2-(2-thiophenyl)ethanoic acid disulfide, 2-oxo-2-(2-thiophenyl)ethanoic acid-2-benzoic acid disulfide, and 2,2'-dithiodibenzoic acid. When provided as the carbon and sulfur source in liquid medium, 2,2'-dithiodibenzoic acid was degraded by soil enrichment cultures. Two bacterial isolates, designated strains RM1 and RM6, degraded 2,2'-dithiodibenzoic acid when combined in the medium. Isolate RM6 was found to have an absolute requirement for vitamin B12, and it degraded 2,2'-dithiodibenzoic acid in pure culture when the medium was supplemented with this vitamin. Isolate RM6 also degraded 2,2'-dithiodibenzoic acid in medium containing sterilized supernatants from cultures of isolate RM1 grown on glucose or benzoate. Isolate RM6 was identified as a member of the genus Variovorax using the Biolog system and 16S rRNA gene analysis. Although the mechanism of disulfide metabolism could not be determined, benzoic acid was detected as a transient metabolite of 2,2'-dithiodibenzoic acid biodegradation by Variovorax sp. strain RM6. In pure culture, this isolate mineralized 2,2'-dithiodibenzoic acid, releasing 59% of the carbon as carbon dioxide and 88% of the sulfur as sulfate.
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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) | 0.001 | 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".