Whole genome sequencing-based drug resistance predictions of multidrug-resistant isolates from Tanzania.

Background: Rifampicin- or multidrug-resistant (RR/MDR) complex (MTBC) strains account for considerable morbidity and mortality globally. WGS-based prediction of drug resistance may guide clinical decisions, especially for the design of RR/MDR-TB therapies.

Methods: We compared WGS-based drug resistance-predictive mutations for 42 MTBC isolates from MDR-TB patients in Tanzania with the MICs of 14 antibiotics measured in the Sensititre™ MycoTB assay. An isolate was phenotypically categorized as resistant if it had an MIC above the epidemiological-cut-off (ECOFF) value, or as susceptible if it had an MIC below or equal to the ECOFF.

Results: Overall, genotypically non-wild-type MTBC isolates with high-level resistance mutations (gNWT-R) correlated with isolates with MIC values above the ECOFF. For instance, the median MIC value (mg/L) for rifampicin-gNWT-R strains was >4.0 (IQR 4.0-4.0) compared with 0.5 (IQR 0.38-0.50) in genotypically wild-type (gWT-S, < 0.001); isoniazid-gNWT-R >4.0 (IQR 2.0-4.0) compared with 0.25 (IQR 0.12-1.00) among gWT-S (= 0.001); ethionamide-gNWT-R 15.0 (IQR 10.0-20.0) compared with 2.50 (IQR; 2.50-5.00) among gWT-S (< 0.001). WGS correctly predicted resistance in 95% (36/38) and 100% (38/38) of the rifampicin-resistant isolates with ECOFFs >0.5 and >0.125 mg/L, respectively. No known resistance-conferring mutations were present in genes associated with resistance to fluoroquinolones, aminoglycosides, capreomycin, bedaquiline, delamanid, linezolid, clofazimine, cycloserine, or p-amino salicylic acid.

Conclusions: WGS-based drug resistance prediction worked well to rule-in phenotypic drug resistance and the absence of second-line drug resistance-mediating mutations has the potential to guide the design of RR/MDR-TB regimens in the future.