Corynebacterium glutamicum survives arsenic stress with arsenate reductases coupled to two distinct redox mechanisms
Bibliographic record
Abstract
Arsenate reductases (ArsCs) evolved independently as a defence mechanism against toxic arsenate. In the genome of Corynebacterium glutamicum, there are two arsenic resistance operons (ars1 and ars2) and four potential genes coding for arsenate reductases (Cg_ArsC1, Cg_ArsC2, Cg_ArsC1' and Cg_ArsC4). Using knockout mutants, in vitro reconstitution of redox pathways, arsenic measurements and enzyme kinetics, we show that a single organism has two different classes of arsenate reductases. Cg_ArsC1 and Cg_ArsC2 are single-cysteine monomeric enzymes coupled to the mycothiol/mycoredoxin redox pathway using a mycothiol transferase mechanism. In contrast, Cg_ArsC1' is a three-cysteine containing homodimer that uses a reduction mechanism linked to the thioredoxin pathway with a k(cat)/K(M) value which is 10(3) times higher than the one of Cg_ArsC1 or Cg_ArsC2. Cg_ArsC1' is constitutively expressed at low levels using its own promoter site. It reduces arsenate to arsenite that can then induce the expression of Cg_ArsC1 and Cg_ArsC2. We also solved the X-ray structures of Cg_ArsC1' and Cg_ArsC2. Both enzymes have a typical low-molecular-weight protein tyrosine phosphatases-I fold with a conserved oxyanion binding site. Moreover, Cg_ArsC1' is unique in bearing an N-terminal three-helical bundle that interacts with the active site of the other chain in the dimeric interface.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".