Overcoming the pitfalls of automatic interpretation of whole genome sequencing data by online tools for the prediction of pyrazinamide resistance in Mycobacterium tuberculosis

PloS One
Tomotada IwamotoSatoshi Mitarai

Abstract

Automated online software tools that analyse whole genome sequencing (WGS) data without the need for bioinformatics expertise can motivate the implementation of WGS-based molecular drug susceptibility testing (DST) in routine diagnostic settings for tuberculosis (TB). Pyrazinamide (PZA) is a key drug for current and future TB treatment regimens; however, it was reported that predictive power for PZA resistance by the available tools is low. Therefore, this low predictive power may make users hesitant to use the tools. This study aimed to elucidate why and to uncover the real performance of the tools when taking into account their variation calling lists (manual inspection), not just their automated reporting system (default setting) that was evaluated by previous studies. WGS data from 191 datasets comprising 108 PZA-resistant and 83 susceptible strains were used to evaluate the potential performance of the available online tools (TB Profiler, TGS-TB, PhyResSE, and CASTB) for predicting phenotypic PZA resistance. When taking into consideration the variation calling lists, 73 variants in total (47 non-synonymous mutations and 26 indels) in pncA were detected by TGS-TB and PhyResSE, covering all mutations for the 108 PZA-resistan...Continue Reading

References

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Citations

Aug 1, 2019·Expert Review of Clinical Pharmacology·Regina KrattingerReinhard Dummer
Mar 7, 2020·Microbiology and Molecular Biology Reviews : MMBR·Elise A LamontAnthony D Baughn
Feb 4, 2021·Memórias do Instituto Oswaldo Cruz·Arthur Emil Dos Santos GuimarãesEmilyn Costa Conceição
Apr 17, 2021·Infection, Genetics and Evolution : Journal of Molecular Epidemiology and Evolutionary Genetics in Infectious Diseases·Muhammad Tahir KhanDong Qing Wei
Sep 29, 2021·Microbial Drug Resistance : MDR : Mechanisms, Epidemiology, and Disease·Mohammad BagheriMohammad Javad Nasiri

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Datasets Mentioned

BETA
DRA006844

Methods Mentioned

BETA
DNA-seq
Profiler
PCR

Software Mentioned

PhyResSE
EZR
- TB
TGS
TB Profiler
Mykrobe predictor
CASTB
TB
Genoscholar

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