Inclusion of minor alleles improves catalogue-based prediction of fluoroquinolone resistance inMycobacterium tuberculosis

Abstract

Fluoroquinolone resistance poses a threat to the successful treatment of tuberculosis. Whole genome sequencing (WGS), and the subsequent detection of catalogued resistance- associated mutations, offers an attractive solution to fluoroquinolone susceptibility testing. However, the bioinformatic pipelines used often mask the recognition of minor alleles which are implicated in fluoroquinolone resistance. Using the Comprehensive Resistance Prediction for Tuberculosis: an International Consortium's (CRyPTIC) dataset of globally diverse WGS Mycobacterium tuberculosis isolates, with matched minimum inhibitory concentrations for two fluoroquinolone drugs, we show that detecting minor alleles increased the sensitivity of WGS for moxifloxacin resistance prediction from 85.4% to 94.0%, without significantly reducing specificity. We also found no correlation between the proportion of an M. tuberculosis population containing a resistance-conferring allele and the magnitude of resistance. Together our results highlight the importance of detecting minor resistance conferring alleles when using WGS, or indeed any sequencing-based approach, to diagnose fluoroquinolone resistance.

Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach

“…Limitations to this study include the lower number of isolates resistant to newer drugs, the lack of isolates from lineages 5 and 6, which are responsible for a significant proportion of cases in sub-Saharan Africa, potential misattribution of mutational effects outside our target genes or due to exclusion of insertions/deletions >50 bp in size from our model, and the use of ECOFFs that have not yet been extensively validated against other methods, although we have shown good concordance with MGIT and MODS results 17 . In addition, it has been shown that minor alleles at sites associated with resistance can influence MIC 55 . While we have tried to limit this effect by removing isolates for which we could not confidently call a variant at a site previously associated with resistance, it is possible that novel resistance-associated sites with minor alleles could affect our model.…”

Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach

“…Limitations to this study include the lower number of isolates resistant to newer drugs, the lack of isolates from lineages 5 and 6, which are responsible for a significant proportion of cases in sub-Saharan Africa, potential misattribution of mutational effects outside our target genes or due to exclusion of insertions/deletions > 50bp in size from our model, and the use of ECOFFs that have not yet been extensively validated against other methods, although we have shown good concordance with MGIT and MODS results 17 . In addition, it has been shown that minor alleles at sites associated with resistance can influence MIC 56 . While we have tried to limit this effect by removing isolates for which we could not confidently call a variant at a site previously associated with resistance, it is possible that novel resistance-associated sites with minor alleles could affect our model.…”

Drug resistance prediction for Mycobacterium tuberculosis with reference graphs

“…Other frequent consensus FP calls included fabG1 c-15t, which is associated with ethionamide (n=441) and isoniazid (n=241) resistance, and rrs a1401g, which is associated with resistance to capreomycin (n=241), amikacin (n=70) and kanamycin (n=48). In addition, there were common false positives from gyrA mutations A90V and D94G, which are associated with resistance to the fluoroquinolones levofloxacin (n=108 and n=70, respectively), moxifloxacin (n=419 and n=349) and ofloxacin (n=19 and n=17), and are known to cause heteroresistance and minimum inhibitory concentrations (MICs) close to the critical concentration threshold [56][57][58].…”