Experimental confirmation that an uncommon, yet clinically relevant mutation (G878A) in the <i>rrs</i> gene of <i>Mycobacterium tuberculosis</i> confers resistance to streptomycin
Bibliographic record
Abstract
ABSTRACT The effective treatment of patients diagnosed with drug resistant tuberculosis (TB) is highly dependent upon the ability to rapidly and accurately determine the antibiotic resistance/ susceptibility profile of the Mycobacterium tuberculosis isolate(s) involved. Thus, as more and more clinical microbiology laboratories advance towards the routine use of DNA sequence-based diagnostics, it is imperative that their predictive functions extend beyond the well-known resistance-conferring mutations, in order to also encompass as many of the lower-frequency mutations as possible. However, in most cases, the fundamental experimental proof that links these uncommon mutations with phenotypic resistance is still lacking. One such example is the G878A polymorphism within the rrs gene encoding the 16s rRNA. We, and others, have identified this mutation within a small number of drug-resistant M. tuberculosis isolates, although prior to this study a consensus regarding exactly which aminoglycoside antibiotic(s) it conferred resistance toward seems not to have been reached. Here we have employed oligo-mediated recombineering to specifically introduce the G878A polymorphism into the rrs gene of M. bovis BCG - a species very closely related to M. tuberculosis - and demonstrate that it confers low-level resistance to streptomycin alone. In our hands, it does not confer cross-resistance towards amikacin, capreomycin, nor kanamycin. We also demonstrate that the rrs G878A mutation exerts a substantial fitness defect in vitro , that may at least in part explain why clinical M. tuberculosis isolates bearing this mutation appear to be quite rare. Overall, this study provides clarity to the resistance phenotype attributable to the rrs G878A mutation and is relevant to the future implementation of genomics-based diagnostics, as well as the clinical management of patients in situations where this particular polymorphism is encountered.
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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 | 0.001 | 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 | 0.001 |
| 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".