Mutations in embB406 Are Associated with Low-Level Ethambutol Resistance in Canadian Mycobacterium tuberculosis Isolates
Bibliographic record
Abstract
In Mycobacterium tuberculosis, molecular predictions of ethambutol resistance rely primarily on the detection of mutations within embB. However, discordance between embB406 mutations and gold standard phenotypic drug sensitivity testing (DST) questions the significance of embB406 mutations used in molecular DST. This study tabulates embB mutations found in Canadian M. tuberculosis isolates and evaluates the impact of specific mutations on ethambutol resistance. The National Reference Centre for Mycobacteriology culture collection (n = 2796) was screened for isolates with embB mutations. Phenotypic DST was performed on the BACTEC™ MGIT™ 960 at ethambutol concentrations of 2–5 μg/mL. Whole genome sequencing was used for drug resistance predictions, phylogenomics and single nucleotide polymorphism analysis. Detection of resistance-associated embB mutations corresponded to a positive predictive value of 64.3%, negative predictive value of 99.2%, 98.7% specificity, and 73.3% sensitivity compared to phenotypic DST. Two embB406 mutation subtypes (Gly406Asp, Gly406Ala) were found among 16 isolates, of which 12 were sensitive at 5 µg/mL ethambutol with variable resistance between 2–4 µg/mL. A novel frameshift mutation in regulator embR (Gln258fs) was found in nine isolates. Mutations in embB406 were associated with low-level ethambutol resistance undetectable at the recommended critical concentration (5 μg/mL). These novel mutations may exacerbate variability in ethambutol resistance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".