Nur, a nickel‐responsive regulator of the Fur family, regulates superoxide dismutases and nickel transport in <i>Streptomyces coelicolor</i>
Bibliographic record
Abstract
Nickel serves as a cofactor for various microbial enzymes including superoxide dismutase (SOD) found in Streptomyces spp. In Streptomyces coelicolor, nickel represses and induces production of Fe-containing and Ni-containing SODs, respectively, primarily at the transcriptional level. We identified the nickel-responsive regulator (Nur), a Fur (ferric-uptake regulator) homologue, which binds to the promoter region of the sodF gene encoding FeSOD in the presence of nickel. Disruption of the nur gene caused constitutive expression of FeSOD and no induction of NiSOD in the presence of nickel. The intracellular level of nickel was higher in a Deltanur mutant than in the wild type, suggesting that Nur also regulates nickel uptake in S. coelicolor. A putative nickel-transporter gene cluster (nikABCDE) was identified in the genome database. Its transcription was negatively regulated by Nur in the presence of nickel. Purified Nur protein bound to the nikA promoter region in a nickel-dependent way. These results support the action of Nur as a regulator of nickel homeostasis and antioxidative response in S. coelicolor, and add a novel nickel-responsive member to the list of versatile metal-specific regulators of the Fur family.
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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) | 0.001 | 0.001 |
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".