Universidad Peruana Cayetano Heredia

Whole-Genome Sequencing for Drug Resistance Profile Prediction in Mycobacterium tuberculosis

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dc.contributor.author Gygli, Sebastian M.
dc.contributor.author Keller, Peter M.
dc.contributor.author Ballif, Marie
dc.contributor.author Blochliger, Nicolas
dc.contributor.author Homke, Rico
dc.contributor.author Reinhard, Miriam
dc.contributor.author Loiseau, Chloe
dc.contributor.author Ritter, Claudia
dc.contributor.author Sander, Peter
dc.contributor.author Borrell, Sonia
dc.contributor.author Collantes Loo, Jimena
dc.contributor.author Avihingsanon, Anchalee
dc.contributor.author Gnokoro, Joachim
dc.contributor.author Yotebieng, Marcel
dc.contributor.author Egger, Matthias
dc.contributor.author Gagneux, Sebastien
dc.contributor.author Bottger, Erik C.
dc.date.accessioned 2019-07-04T17:01:24Z
dc.date.available 2019-07-04T17:01:24Z
dc.date.issued 2019
dc.identifier.uri https://hdl.handle.net/20.500.12866/6952
dc.description.abstract 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 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. en_US
dc.language.iso eng
dc.publisher American Society for Microbiology
dc.relation.ispartofseries Antimicrobial Agents and Chemotherapy
dc.rights info:eu-repo/semantics/restrictedAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject Mycobacterium tuberculosis en_US
dc.subject drug resistance en_US
dc.subject drug resistance level prediction en_US
dc.subject quantitative phenotypic drug susceptibility testing en_US
dc.subject whole-genome sequencing en_US
dc.title Whole-Genome Sequencing for Drug Resistance Profile Prediction in Mycobacterium tuberculosis en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://doi.org/10.1128/AAC.02175-18
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.03.08
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.01.05
dc.relation.issn 1098-6596


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