TY - JOUR
T1 - Whole-Genome Sequencing for Drug Resistance Profile Prediction in Mycobacterium tuberculosis
AU - Gygli, Sebastian M.
AU - Keller, Peter M.
AU - Ballif, Marie
AU - Blöchliger, Nicolas
AU - Hömke, Rico
AU - Reinhard, Miriam
AU - Loiseau, Chloé
AU - Ritter, Claudia
AU - Sander, Peter
AU - Borrell, Sonia
AU - Loo, Jimena Collantes
AU - Avihingsanon, Anchalee
AU - Gnokoro, Joachim
AU - Yotebieng, Marcel
AU - Egger, Matthias
AU - Gagneux, Sebastien
AU - Böttger, Erik C.
N1 - Funding Information:
We thank Alexandra Mushegian for critically reading the manuscript and improving the writing. Whole-genome analysis was performed at the sciCORE (http://scicore .unibas.ch/) scientific computing core facility at the University of Basel. This work was supported by the European Research Council (grant number 309540-EVODRTB), the Swiss National Science Foundation (IZRJZ3_164171, 310030-166687, IZLSZ3_170834, CRSII5_177163, 31003A_153349, 320030_153442/1, and special project funding 174281), and SystemsX.ch. The International Epidemiology Databases to Evaluate AIDS (IeDEA) is supported by the U.S. National Institutes of Health’s National Institute of Allergy and Infectious Diseases, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Cancer Institute, the National Institute of Mental Health, and the National Institute on Drug Abuse: Asia-Pacific, U01AI069907; CCASAnet, U01AI069923; Central Africa, U01AI096299; Southern Africa, U01AI069924; West Africa,
Publisher Copyright:
Copyright © 2019 Gygli et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.
PY - 2019/4
Y1 - 2019/4
N2 - Whole-genome sequencing allows rapid detection of drug-resistant Mycobacterium tuberculosis isolates. However, the availability of high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been limited. We determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from the Democratic Republic of the Congo, Ivory Coast, Peru, Thailand, and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD Bactec MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared DST results with predicted drug resistance profiles inferred by whole-genome sequencing. Classification of strains by the two phenotypic DST methods into resistotype/wild-type populations was concordant in 73 to 99% of cases, depending on the drug. Our data suggest that the established critical concentration (5 mg/liter) for ethambutol resistance (MGIT 960 system) is too high and mis-classifies strains as susceptible, unlike 7H10 agar dilution. Increased minimal inhibitory concentrations were explained by mutations identified by whole-genome sequencing. Using whole-genome sequences, we were able to predict quantitative drug resistance levels for the majority of drug resistance mutations. Predicting quantitative levels of drug resistance by whole-genome sequencing was partially limited due to incompletely understood drug resistance mechanisms. The overall sensitivity and specificity of whole-genome-based DST were 86.8% and 94.5%, respectively. Despite some limitations, whole-genome sequencing has the potential to infer resistance profiles without the need for time-consuming phenotypic methods.
AB - Whole-genome sequencing allows rapid detection of drug-resistant Mycobacterium tuberculosis isolates. However, the availability of high-quality data linking quantitative phenotypic drug susceptibility testing (DST) and genomic data have thus far been limited. We determined drug resistance profiles of 176 genetically diverse clinical M. tuberculosis isolates from the Democratic Republic of the Congo, Ivory Coast, Peru, Thailand, and Switzerland by quantitative phenotypic DST for 11 antituberculous drugs using the BD Bactec MGIT 960 system and 7H10 agar dilution to generate a cross-validated phenotypic DST readout. We compared DST results with predicted drug resistance profiles inferred by whole-genome sequencing. Classification of strains by the two phenotypic DST methods into resistotype/wild-type populations was concordant in 73 to 99% of cases, depending on the drug. Our data suggest that the established critical concentration (5 mg/liter) for ethambutol resistance (MGIT 960 system) is too high and mis-classifies strains as susceptible, unlike 7H10 agar dilution. Increased minimal inhibitory concentrations were explained by mutations identified by whole-genome sequencing. Using whole-genome sequences, we were able to predict quantitative drug resistance levels for the majority of drug resistance mutations. Predicting quantitative levels of drug resistance by whole-genome sequencing was partially limited due to incompletely understood drug resistance mechanisms. The overall sensitivity and specificity of whole-genome-based DST were 86.8% and 94.5%, respectively. Despite some limitations, whole-genome sequencing has the potential to infer resistance profiles without the need for time-consuming phenotypic methods.
KW - Drug resistance
KW - Drug resistance level prediction
KW - Mycobacterium tuberculosis
KW - Quantitative phenotypic drug susceptibility testing
KW - Whole-genome sequencing
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U2 - 10.1128/AAC.02175-18
DO - 10.1128/AAC.02175-18
M3 - Article
C2 - 30718257
AN - SCOPUS:85063643800
SN - 0066-4804
VL - 63
JO - Antimicrobial Agents and Chemotherapy
JF - Antimicrobial Agents and Chemotherapy
IS - 4
M1 - e02175-18
ER -