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

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dc.contributor.authorMbelele, Peter
dc.contributor.authorUtpatel, Christian
dc.contributor.authorSauli, Elingarami
dc.contributor.authorMpolya, Emmanuel
dc.contributor.authorMutayoba, Beatrice
dc.contributor.authorBarilar, Ivan
dc.contributor.authorDreyer, Viola
dc.contributor.authorMerker, Matthias
dc.contributor.authorSariko, Margaretha
dc.contributor.authorSwema, Buliga
dc.contributor.authorMmbaga, Blandina
dc.contributor.authorGratz, Jean
dc.contributor.authorAddo, Kennedy
dc.contributor.authorPletschette, Michel
dc.contributor.authorNiemann, Stefan
dc.contributor.authorHoupt, Eric
dc.contributor.authorMpagama, Stellah
dc.contributor.authorHeysell, Scott
dc.date.accessioned2022-07-21T05:23:03Z
dc.date.available2022-07-21T05:23:03Z
dc.date.issued2022-04-21
dc.descriptionThis research article published by Oxford University Press, 2022en_US
dc.description.abstractBackground: Rifampicin- or multidrug-resistant (RR/MDR) Mycobacterium tuberculosis 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 pa tients 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) cor related 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, P,0.001); isoniazid-gNWT-R .4.0 (IQR 2.0–4.0) compared with 0.25 (IQR 0.12–1.00) among gWT-S (P= 0.001); ethionamide-gNWT-R 15.0 (IQR 10.0–20.0) compared with 2.50 (IQR; 2.50–5.00) among gWT-S (P, 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.en_US
dc.identifier.urihttps://doi.org/10.1093/jacamr/dlac042
dc.identifier.urihttps://dspace.nm-aist.ac.tz/handle/20.500.12479/1446
dc.language.isoenen_US
dc.publisherOxford University Pressen_US
dc.subjectResearch Subject Categories::NATURAL SCIENCESen_US
dc.titleWhole genome sequencing-based drug resistance predictions of multidrug-resistant Mycobacterium tuberculosis isolates from Tanzaniaen_US
dc.typeArticleen_US

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