Acetylation of lysine 182 inhibits the ability of <i>Mycobacterium tuberculosis</i> DosR to bind DNA and regulate gene expression during hypoxia
Bibliographic record
Abstract
The DosR regulon is believed to be a key factor in latency adaptation of Mycobacterium tuberculosis and is strongly induced by multiple stresses, including hypoxia. Previous studies have revealed reversible acetylation of the conserved core DNA-binding lysine residue 182 (K182) of DosR in M. tuberculosis. In this study, we demonstrated that acetylated K182 plays an important role in the DNA-binding ability of DosR and that acetylation of K182 completely abolished the affinity of DosR for DNA in vitro. Antibodies that specifically recognized acetyllysine at position 182 of DosR were used to monitor DosR acetylation. We found that in vitro acetylation of K182 could be removed by deacetylase Rv1151c and that either the deacetylase-deletion strain ∆npdA or treatment with a deacetylase inhibitor resulted in increased levels of K182 acetylation in vivo. The physiological significance of DosR acetylation was demonstrated by decreased levels of acetylated K182 in M. tuberculosis in response to hypoxia and by the effects of K182 acetylation on the transcript levels of DosR regulon genes. Since the DosR regulon plays a critical role during host infection by M. tuberculosis, our findings suggest that targeting DosR acetylation may be a viable strategy for antituberculosis drug development.
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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".