Assessing the role of Rv1222 (RseA) as an anti-sigma factor of the Mycobacterium tuberculosis extracytoplasmic sigma factor SigE
Bibliographic record
Abstract
Abstract σ E is one of the 13 sigma factors encoded by the Mycobacterium tuberculosis chromosome, and its involvement in stress response and virulence has been extensively characterized. Several sigma factors are post-translationally regulated by proteins named anti-sigma factors, which prevent their binding to RNA polymerase. Rv1222 (RseA), whose gene lays immediately downstream sigE , has been proposed in the past as the σ E -specific anti sigma factor. However, its role as anti-sigma factor was recently challenged and a new mechanism of action was hypothesized predicting RseA binding to RNA polymerase and DNA to slow down RNA transcription in a not specific way. In this manuscript, using specific M. tuberculosis mutants, we showed that by changing the levels of RseA expression, M. tuberculosis growth rate does not change (as hypothesized in case of non-specific decrease of RNA transcription) and has an impact only on the transcription level of genes whose transcriptional control is under σ E , supporting a direct role of RseA as a specific anti-σ E factor.
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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) | 0.000 | 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 | 0.000 |
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".