Whole-Genome Sequencing for Resistance Level Prediction in Multidrug-Resistant Tuberculosis

Area of Science:

• Microbiology
• Genomics
• Drug Resistance Studies

Background:

• Whole-genome sequencing (WGS) shows promise for predicting tuberculosis drug resistance.
• Quantitative phenotypic drug susceptibility testing (measuring minimum inhibitory concentrations - MICs) is crucial for treatment guidance.
• A gap exists between WGS data and corresponding MIC data for many tuberculosis isolates.

Purpose of the Study:

• To determine MICs for nine antituberculosis drugs for 154 multidrug-resistant tuberculosis isolates.
• To compare WGS-inferred resistance profiles with experimentally determined MICs.
• To investigate the relationship between specific mutations, MICs, and drug resistance levels.

Main Methods:

• Determination of MICs for 154 multidrug-resistant tuberculosis isolates using MYCOTBI plates.
• Comparison of MIC data with drug resistance profiles predicted by whole-genome sequencing (WGS).

Main Results:

• WGS accurately predicted resistance levels to isoniazid, rifampicin, streptomycin, fluoroquinolones, and aminoglycosides.
• Identified mutations potentially not associated with drug resistance (e.g., EmbB D328G, gid gene mutations, C-12T in eis promoter).
• Observed significant MIC variation (≥8-fold) for strains with identical mutations (e.g., RpsL K88R, fabG1 C-15T, embB, rpoB), possibly due to genetic background.
• 32.3% of rifampicin-resistant isolates were rifabutin-susceptible, with specific rpoB mutations implicated.

Conclusions:

• WGS can predict tuberculosis drug resistance levels, but variations in MICs for strains with the same mutations necessitate further research into genetic background influences.
• Understanding the relationship between rifampicin resistance mutations and rifabutin susceptibility is key to improving WGS-guided treatment selection.
• The study provides valuable MIC distribution data for rarer mutations, aiding future research and clinical interpretation.