Comparison of Whole-Genome Sequencing-Coupled Analytic Pipelines for Assessing the Drug Resistance Signatures of Mycobacterium tuberculosis to RIF, INH, and PZA

The persistent emergence of multidrug-resistant Mycobacterium tuberculosis (MTB) strains exacerbates the global tuberculosis (TB) epidemic to a worldwide health issue. The phenomenon has highlighted the demand for fast and accurate identification of drug-resistant signatures of MTB isolates, which remains a major challenge for determining the precise regimen. Whole-genome sequencing (WGS) possesses the potential to infer drug-resistant profiles before phenotypic approaches, thereby enabling the formulation of personalized regimens for TB disease. In this study, WGS-generated data assessed with distinct databases, including ONT EPI2ME v1.0.16, ResFinder v4.7.2 for MTB, TBProfiler v6.6.2, Mykrobe v0.10.0, and CLC Genomics Workbench software v25.0.2, were used to identify single nucleotide variants (SNVs) within the rpoB, katG, inhA, and pncA genes relevant to three major first-line drugs in 105 clinical MTB isolates with the phenotypic drug susceptibility test (DST) results. All these analytic tools demonstrated convincing performance in predicting the sensitivity (>90%) and specificity (>90%) of rifampicin resistant (RR)-MTB isolates. The TBProfiler and ResFinder databases stood out for their efficient performance in predicting the drug-resistant signatures of isoniazid resistant (HR)-MTB isolates. Remarkably, the deployment of the CLC-GW pipeline showed exceptional performance in predicting the sensitivity (96%) and specificity (100%) of multi drug resistant (MDR)-MTB isolates. In this study, we assessed the reliability and effectiveness of WGS-coupled analyses in determining the drug-resistant signatures of MTB, thereby contributing to the advancement of MTB treatment.