Mutations in <i>emb</i> B406 are associated with low-level ethambutol resistance in Canadian <i>Mycobacterium tuberculosis</i> isolates
Bibliographic record
Abstract
Abstract Background In Mycobacterium tuberculosis , molecular predictions of ethambutol resistance rely primarily on the detection of mutations within emb B. However, discordance between emb B406 mutations and phenotypic drug sensitivity questions its clinical significance. This study aims to decipher the association of emb B406 mutations with ethambutol resistance in M. tuberculosis . Methods All M. tuberculosis isolates from our culture collection containing emb B406 mutations (n=16) and pan-sensitive control isolates (n=10) were selected for this study. Phenotypic drug susceptibility testing for ethambutol was performed in duplicate on the BACTEC™ MGIT™ 960 at concentrations of 2, 3, 4, and 5 μg/mL with strain H37Rv as assay control. Whole genome sequencing was performed on Illumina Miseq for drug resistance predictions (MyKrobe Predictor v.0.7.0), phylogenomics (SNVPhyl v.1.2.3) and single nucleotide polymorphism analysis (Snippy). Results Two emb B406 mutation subtypes were found among 16 strains: Gly406Asp and Gly406Ala. MyKrobe predicted all strains of either subtype to be ethambutol resistant. However, 12 of 16 strains appear phenotypically sensitive at 5 μg/mL but exhibit variable resistance between 2-4 μg/mL. Of these 12 strains, a newly described frameshift mutation in regulator embR (Gln258fs) was found in 9 strains. Conclusions Mutations in emb B406 are associated with low-level ethambutol resistance currently undetectable by the critical concentration of 5 μg/mL for ethambutol. Novel mutations are predicted to exacerbate variability in ethambutol resistance. We suggest amendment to molecular and phenotypic drug susceptibility testing to improve ethambutol DST sensitivity and specificity as well as concordance between rapid and gold standard methods.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".