Ancestral antibiotic resistance in <i>Mycobacterium tuberculosis</i>
Bibliographic record
Abstract
Chemotherapeutic options to treat tuberculosis are severely restricted by the intrinsic resistance of Mycobacterium tuberculosis to the majority of clinically applied antibiotics. Such resistance is partially provided by the low permeability of their unique cell envelope. Here we describe a complementary system that coordinates resistance to drugs that have penetrated the envelope, allowing mycobacteria to tolerate diverse classes of antibiotics that inhibit cytoplasmic targets. This system depends on whiB7, a gene that pathogenic Mycobacterium shares with Streptomyces, a phylogenetically related genus known as the source of diverse antibiotics. In M. tuberculosis, whiB7 is induced by subinhibitory concentrations of antibiotics (erythromycin, tetracycline, and streptomycin) and whiB7 null mutants (Streptomyces and Mycobacterium) are hypersusceptible to antibiotics in vitro. M. tuberculosis is also antibiotic sensitive within a monocyte model system. In addition to antibiotics, whiB7 is induced by exposure to fatty acids that pathogenic Mycobacterium species may accumulate internally or encounter within eukaryotic hosts during infection. Gene expression profiling analyses demonstrate that whiB7 transcription determines drug resistance by activating expression of a regulon including genes involved in ribosomal protection and antibiotic efflux. Components of the whiB7 system may serve as attractive targets for the identification of inhibitors that render M. tuberculosis or multidrug-resistant derivatives more antibiotic-sensitive.
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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 | 0.001 | 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".