Evidence of Complex Transcriptional, Translational, and Posttranslational Regulation of the Extracytoplasmic Function Sigma Factor σ <sup>E</sup> in <i>Mycobacterium tuberculosis</i>
Bibliographic record
Abstract
The extracytoplasmic factor (ECF) sigma factor sigma(E) is one of the most studied sigma factors of Mycobacterium tuberculosis. It has been shown to be involved in virulence as well as in survival under conditions of high temperature, alkaline pH, and exposure to detergents and oxidative stress. Unlike many ECF sigma factors, sigma(E) does not directly regulate the transcription of its own gene. Two promoters have been identified upstream of the sigE gene; one is regulated by the two-component system MprAB, while the other has been shown to be sigma(H) dependent. In this paper, we further characterize the regulation of sigma(E) by identifying its anti-sigma factor and a previously unknown promoter. Finally, we show that sigE can be translated from three different translational start codons, depending on the promoter used. Taken together, our data demonstrate that sigma(E) not only is subjected to complex transcriptional regulation but is also controlled at the translational and posttranslational levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".