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Accuracy of an amplicon-sequencing nanopore approach to identify variants in tuberculosis drug-resistance-associated genes
Author(s) -
Carla Mariner-Llicer,
Galo A. Goig,
Laura Zaragoza-Infante,
Manuela Torres-Puente,
Luis M Villamayor,
David Navarro,
Rafael Borrás,
Álvaro ChinerOms,
Iñaki Comas
Publication year - 2021
Publication title -
microbial genomics
Language(s) - English
Resource type - Journals
ISSN - 2057-5858
DOI - 10.1099/mgen.0.000740
Subject(s) - minion , nanopore sequencing , amplicon , biology , drug resistance , computational biology , genetics , dna sequencing , whole genome sequencing , mycobacterium tuberculosis , deep sequencing , genome , gene , tuberculosis , polymerase chain reaction , medicine , pathology
A rapid and accurate diagnostic assay represents an important means to detect Mycobacterium tuberculosis , identify drug-resistant strains and ensure treatment success. Currently employed techniques to diagnose drug-resistant tuberculosis include slow phenotypic tests or more rapid molecular assays that evaluate a limited range of drugs. Whole-genome-sequencing-based approaches can detect known drug-resistance-conferring mutations and novel variations; however, the dependence on growing samples in culture, and the associated delays in achieving results, represents a significant limitation. As an alternative, targeted sequencing strategies can be directly performed on clinical samples at high throughput. This study proposes a targeted sequencing assay to rapidly detect drug-resistant strains of M. tuberculosis using the Nanopore MinION sequencing platform. We designed a single-tube assay that targets nine genes associated with drug resistance to seven drugs and two phylogenetic-determining regions to determine strain lineage and tested it in nine clinical isolates and six sputa. The study’s main aim is to calibrate MinNION variant calling to detect drug-resistance-associated mutations with different frequencies to match the accuracy of Illumina (the current gold-standard sequencing technology) from both culture and sputum samples. After calibrating Nanopore MinION variant calling, we demonstrated 100% agreement between Illumina WGS and our MinION set up to detect known drug resistance and phylogenetic variants in our dataset. Importantly, other variants in the amplicons are also detected, decreasing the recall. We identify minority variants and insertions/deletions as crucial bioinformatics challenges to fully reproduce Illumina WGS results.

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