Whole-Genome Sequencing for Drug Resistance Profile Prediction in .
Sebastian M Gygli, Peter M Keller, Marie Ballif, Nicolas Blöchliger, Rico Hömke, Miriam Reinhard, Chloé Loiseau, Claudia Ritter, Peter Sander, Sonia Borrell, Jimena Collantes Loo, Anchalee Avihingsanon, Joachim Gnokoro, Marcel Yotebieng, Matthias Egger, Sebastien Gagneux, Erik C Böttger
Author Information
Sebastian M Gygli: Swiss Tropical and Public Health Institute, Basel, Switzerland.
Peter M Keller: Institute of Medical Microbiology, University of Zürich, Zürich, Switzerland.
Marie Ballif: Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
Nicolas Blöchliger: Institute of Medical Microbiology, University of Zürich, Zürich, Switzerland.
Rico Hömke: Institute of Medical Microbiology, University of Zürich, Zürich, Switzerland.
Miriam Reinhard: Swiss Tropical and Public Health Institute, Basel, Switzerland.
Chloé Loiseau: Swiss Tropical and Public Health Institute, Basel, Switzerland.
Claudia Ritter: Institute of Medical Microbiology, University of Zürich, Zürich, Switzerland.
Peter Sander: Institute of Medical Microbiology, University of Zürich, Zürich, Switzerland.
Sonia Borrell: Swiss Tropical and Public Health Institute, Basel, Switzerland.
Jimena Collantes Loo: Instituto de Medicina Tropical Alexander von Humboldt, Universidad Peruana Cayetano Heredia, Lima, Peru.
Anchalee Avihingsanon: HIV-NAT/Thai Red Cross AIDS Research Centre, Bangkok, Thailand.
Joachim Gnokoro: Centre de Prise en Charge de Recherche et de Formation, Yopougon, Abidjan, Côte d'Ivoire.
Marcel Yotebieng: College of Public Health, Ohio State University, Columbus, Ohio, USA.
Matthias Egger: Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland.
Sebastien Gagneux: Swiss Tropical and Public Health Institute, Basel, Switzerland sebastien.gagneux@swisstph.ch boettger@imm.uzh.ch.
Erik C Böttger: Institute of Medical Microbiology, University of Zürich, Zürich, Switzerland sebastien.gagneux@swisstph.ch boettger@imm.uzh.ch.
Whole-genome sequencing allows rapid detection of drug-resistant 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 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 misclassifies 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.
