Identification of novel resistance-associated mutations and discrimination within whole-genome sequences of fluoroquinolone-resistant <i>Mycobacterium tuberculosis</i> isolates
Bibliographic record
Abstract
ABSTRACT This study aims to elucidate additional mutation loci associated with fluoroquinolone (FQ) resistance and evaluate the discriminatory capacity of mutation loci and allele mutation frequencies in identifying FQ-resistant Mycobacterium tuberculosis (MTB) isolates. A random selection of isolates was extracted from an ongoing collection. Drug resistance was determined using the resazurin microtiter assay (REMA) as the gold standard. Mutation loci and the burden of mutations in the quinolone resistance-determining region (QRDR) were elucidated through whole-genome sequencing (WGS). Novel amino acid mutations, namely, G520D and G520T, were identified in the gyrB and associated with FQ resistance. In the context of distinguishing FQ-resistant isolates, the AUC for the QRDR mutation frequency burden (0.969) surpassed that of the mutation locus (0.929), and this difference was statistically significant ( P = 0.03). Furthermore, using the resistance mutation locus as a reference, setting the QRDR mutation frequency burden threshold at 1.31% resulted in a 3.60% increase in the accuracy of classifying FQ-resistant isolates (NRI = 3.60%, P < 0.001). The QRDR mutation frequency burden appears to offer superior diagnostic efficacy in discriminating FQ-resistant isolates compared to qualitative detection of mutant loci. IMPORTANCE Fluoroquinolone (FQ) drugs are recommended as second-line drugs for the treatment of multidrug-resistant tuberculosis. With the massive use of FQ drugs in the clinical treatment of tuberculosis (TB), there is an increasing rate of drug resistance to FQ drugs. In this study, we identified and demonstrated novel amino acid mutations associated with FQ resistance in Mycobacterium tuberculosis (MTB), and we quantified the mutation sites and identified the quinolone resistance-determining region (QRDR) mutation frequency burden as a novel diagnostic method for FQ resistance. We hope that the results of this study will provide data support and a theoretical basis for the rapid diagnosis of FQ-resistant MTB.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".