Chlorotonils exhibit potent activity against <i>Mycobacterium tuberculosis</i> , while resistance is mediated by MmpR5-MmpL5
Bibliographic record
Abstract
Abstract Treatment of Mycobacterium tuberculosis (Mtb) is challenging and requires administration of at least four different antibiotics. Unfortunately, multi-drug resistant Mtb strains continue to emerge, undermining the effectiveness of current treatment regimens and highlighting the urgent need for new therapeutics. In this study, we evaluated the potential of natural product-derived chlorotonils as anti-Mtb agents. We demonstrate that chlorotonils exhibit nanomolar potency against a range of attenuated and virulent Mtb strains. Mechanistic studies and resistance profiling in Mtb revealed that chlorotonils affect both lipid and energy metabolism. Through systems biology approaches, including the construction of an Mtb CRISPRi library specifically designed for chemical-genomic profiling, we identified MmpR5/MmpL5 as major driver of chlorotonil-resistance in Mtb leading also to cross-resistance with bedaquiline. Our findings highlight chlorotonils as valuable chemical tools to further dissect the role and function of the MmpS5-MmpL5 efflux pump in drug-resistant Mtb.
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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) | 0.002 | 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".