RskA Is a Dual Function Activator-Inhibitor That Controls SigK Activity Across Distinct Bacterial Genera
Bibliographic record
Abstract
It has been previously shown that RskA, the anti-Sigma factor K of M. tuberculosis, inhibits SigK and that mutations in RskA promote high expression of the SigK regulon. The latter observation led us to hypothesize that RskA mutations lead to loss of the anti-Sigma factor function. In this report, we used natural and artificial mutations in RskA to determine the basis of the SigK-RskA partnership. Consistent with predictions, the N-terminal cytoplasmic portion of RskA was sufficient on its own to inhibit SigK. Unexpectedly, RskA also served as an activator of SigK. This activation depended on the same N-terminal region and was enhanced by the membrane-extracellular portion of RskA. Based on this, we engineered similar truncations in a Gram-negative bacterium, namely Yersinia enterocolitica. Again, we observed that, with specific alterations of RskA, we were able to enhance SigK activity. Together these results support an alternative mechanism of anti-Sigma factor function, that we could term modulator (activator-inhibitor) in both Actinobacteria and Gram-negative bacteria, suggesting that Sigma factor activation by anti-Sigma factors could be under-recognized.
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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 | 0.001 |
| 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 | 0.001 |
| 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".