Sulfide oxidation in gram-negative bacteria by expression of the sulfidequinone reductase gene of<i>Rhodobacter capsulatus</i>and by electron transport to ubiquinone
Bibliographic record
Abstract
The oxidation of sulfide was studied in recombinant bacteria expressing the sulfidequinone reductase gene (sqr) from Rhodobacter capsulatus. Sulfide was oxidized by the Escherichia coli strain W3110 harboring the sqr construct (pKKSQ) under anaerobic conditions and nitrate was utilized as a terminal electron acceptor. Following the oxidation, elemental sulfur and nitrite were produced as the final reaction products. This activity was retained in the membrane preparation and was sensitive towards antimycin A, stigmatellin, and azide. As a consequence of the ubiquinone deficiency, this activity was markedly decreased. In additon, by recovery of ubiquinone, the oxidation was also restored to rates similar to those of the wild-type strain. These results indicate that sulfide oxidation in this strain occurs via the quinone pool in vivo, and that this sulfidequinone reductase (SQR) in particular utilizes ubiquinone as a more appropriate electron acceptor than menaquinone or demetylmenaquinone. To our knowledge, this is the first study to show a direct interaction between SQR and ubiquinone in cells. When expressed in Pseudomonas putida and Rhizobium meliloti, the SQR conferred on these organisms the ability to oxidize sulfide as well as E. coli in vivo.Key words: SQR, quinone, anaerobic sulfide oxidation, heterogeneous expression.
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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 | 0.000 | 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".