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

BACKGROUND: 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 com...

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Autores principales: Mbelele, Peter M., Utpatel, Christian, Sauli, Elingarami, Mpolya, Emmanuel A., Mutayoba, Beatrice K., Barilar, Ivan, Dreyer, Viola, Merker, Matthias, Sariko, Margaretha L., Swema, Buliga M., Mmbaga, Blandina T., Gratz, Jean, Addo, Kennedy K., Pletschette, Michel, Niemann, Stefan, Houpt, Eric R., Mpagama, Stellah G., Heysell, Scott K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021016/
https://www.ncbi.nlm.nih.gov/pubmed/35465240
http://dx.doi.org/10.1093/jacamr/dlac042
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author Mbelele, Peter M.
Utpatel, Christian
Sauli, Elingarami
Mpolya, Emmanuel A.
Mutayoba, Beatrice K.
Barilar, Ivan
Dreyer, Viola
Merker, Matthias
Sariko, Margaretha L.
Swema, Buliga M.
Mmbaga, Blandina T.
Gratz, Jean
Addo, Kennedy K.
Pletschette, Michel
Niemann, Stefan
Houpt, Eric R.
Mpagama, Stellah G.
Heysell, Scott K.
author_facet Mbelele, Peter M.
Utpatel, Christian
Sauli, Elingarami
Mpolya, Emmanuel A.
Mutayoba, Beatrice K.
Barilar, Ivan
Dreyer, Viola
Merker, Matthias
Sariko, Margaretha L.
Swema, Buliga M.
Mmbaga, Blandina T.
Gratz, Jean
Addo, Kennedy K.
Pletschette, Michel
Niemann, Stefan
Houpt, Eric R.
Mpagama, Stellah G.
Heysell, Scott K.
author_sort Mbelele, Peter M.
collection PubMed
description BACKGROUND: 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 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, 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.
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spelling pubmed-90210162022-04-21 Whole genome sequencing-based drug resistance predictions of multidrug-resistant Mycobacterium tuberculosis isolates from Tanzania Mbelele, Peter M. Utpatel, Christian Sauli, Elingarami Mpolya, Emmanuel A. Mutayoba, Beatrice K. Barilar, Ivan Dreyer, Viola Merker, Matthias Sariko, Margaretha L. Swema, Buliga M. Mmbaga, Blandina T. Gratz, Jean Addo, Kennedy K. Pletschette, Michel Niemann, Stefan Houpt, Eric R. Mpagama, Stellah G. Heysell, Scott K. JAC Antimicrob Resist Original Article BACKGROUND: 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 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, 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. Oxford University Press 2022-04-21 /pmc/articles/PMC9021016/ /pubmed/35465240 http://dx.doi.org/10.1093/jacamr/dlac042 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of British Society for Antimicrobial Chemotherapy. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Original Article
Mbelele, Peter M.
Utpatel, Christian
Sauli, Elingarami
Mpolya, Emmanuel A.
Mutayoba, Beatrice K.
Barilar, Ivan
Dreyer, Viola
Merker, Matthias
Sariko, Margaretha L.
Swema, Buliga M.
Mmbaga, Blandina T.
Gratz, Jean
Addo, Kennedy K.
Pletschette, Michel
Niemann, Stefan
Houpt, Eric R.
Mpagama, Stellah G.
Heysell, Scott K.
Whole genome sequencing-based drug resistance predictions of multidrug-resistant Mycobacterium tuberculosis isolates from Tanzania
title Whole genome sequencing-based drug resistance predictions of multidrug-resistant Mycobacterium tuberculosis isolates from Tanzania
title_full Whole genome sequencing-based drug resistance predictions of multidrug-resistant Mycobacterium tuberculosis isolates from Tanzania
title_fullStr Whole genome sequencing-based drug resistance predictions of multidrug-resistant Mycobacterium tuberculosis isolates from Tanzania
title_full_unstemmed Whole genome sequencing-based drug resistance predictions of multidrug-resistant Mycobacterium tuberculosis isolates from Tanzania
title_short Whole genome sequencing-based drug resistance predictions of multidrug-resistant Mycobacterium tuberculosis isolates from Tanzania
title_sort whole genome sequencing-based drug resistance predictions of multidrug-resistant mycobacterium tuberculosis isolates from tanzania
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021016/
https://www.ncbi.nlm.nih.gov/pubmed/35465240
http://dx.doi.org/10.1093/jacamr/dlac042
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