Abstract
Whole-genome sequencing (WGS) of Mycobacterium tuberculosis (MTB) isolates can be used to get an accurate diagnosis, to guide clinical decision making, to control tuberculosis (TB) and for outbreak investigations. We evaluated the performance of long-read (LR) and/or short-read (SR) sequencing for anti-TB drug-resistance prediction using the TBProfiler and Mykrobe tools, the fraction of genome recovery, assembly accuracies and the robustness of two typing approaches based on core-genome SNP (cgSNP) typing and core-genome multi-locus sequence typing (cgMLST). Most of the discrepancies between phenotypic drug-susceptibility testing (DST) and drug-resistance prediction were observed for the first-line drugs rifampicin, isoniazid, pyrazinamide and ethambutol, mainly with LR sequence data. Resistance prediction to second-line drugs made by both TBProfiler and Mykrobe tools with SR- and LR-sequence data were in complete agreement with phenotypic DST except for one isolate. The SR assemblies were more accurate than the LR assemblies, having significantly (P<0.05) fewer indels and mismatches per 100 kbp. However, the hybrid and LR assemblies had slightly higher genome fractions. For LR assemblies, Canu followed by Racon, and Medaka polishing was the most accurate approach. The cgSNP approach, based on either reads or assemblies, was more robust than the cgMLST approach, especially for LR sequence data. In conclusion, anti-TB drug-resistance prediction, particularly with only LR sequence data, remains challenging, especially for first-line drugs. In addition, SR assemblies appear more accurate than LR ones, and reproducible phylogeny can be achieved using cgSNP approaches.
Highlights
Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is one of the top-ranking causes of death from infectious diseases worldwide, with an estimated 10 million new cases and 1.5 million deaths in 2018 [1]
We looked at the SNP calls made using LR or SR sequence data and their concordance to phenotypic drug-susceptibility testing (DST) (Fig. 2, Table 1)
Most of the discrepancies between phenotypic DST and drug-resistance prediction were observed for first-line drugs, and mainly when using LRs (Fig. 2, Table 1a)
Summary
Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), is one of the top-ranking causes of death from infectious diseases worldwide, with an estimated 10 million new cases and 1.5 million deaths in 2018 [1]. Rapid and accurate diagnosis is necessary for timely and appropriate antimicrobial therapy This prevents transmission and emergence/spread of multidrug-resistant (MDR)/extensively drug-resistant (XDR) tuberculosis [2]. Next- generation sequencing (NGS) technologies have been shown to have a high potential to overcome many of the challenges associated with conventional DST and the limitations of the current molecular tests by providing detailed sequence information for specific gene regions or the whole genome [2]. Since the complete genome sequencing of the first MTB [5], whole-genome sequencing (WGS) has been applied to a wide range of clinical situations: diagnosis, treatment, outbreak investigation and surveillance to guide clinical decision making and TB disease control [6, 7]. Improved diagnosis and treatment options with new drug regimens should be prioritized to combat the MDR-TB pandemic [10, 11]
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