Journal
JOURNAL OF CLINICAL MICROBIOLOGY
Volume 59, Issue 6, Pages -Publisher
AMER SOC MICROBIOLOGY
DOI: 10.1128/JCM.00202-21
Keywords
Mycobacterium tuberculosis; whole genome sequencing; validation; public health; national reference center; single nucleotide polymorphism; antimicrobial resistance
Categories
Funding
- Wellcome Trust
- Belgian Ministry of Social Affairs
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The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates, particularly Mycobacterium tuberculosis (MTB), has shown significant advantages in reducing time compared to conventional methods. While various solutions for analyzing WGS MTB data have been developed, successful integration in clinical laboratories is hindered by validation requirements and the lack of a consensus framework.
The use of whole-genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For Mycobacterium tuberculosis (MTB), in particular, WGS has the benefit of drastically reducing the time required to generate results compared to most conventional phenotypic methods. Consequently, a multitude of solutions for analyzing WGS MTB data have been developed, but their successful integration in clinical and national reference laboratories is hindered by the requirement for their validation, for which a consensus framework is still largely absent. We developed a bioinformatics workflow for (Illumina) WGS-based routine typing of MTB complex (MTBC) member isolates allowing complete characterization, including (sub)species confirmation and identification (16S, csb/RD, hsp65), single nucleotide polymorphism (SNP)-based antimicrobial resistance (AMR) prediction, and pathogen typing (spoligotyping, SNP barcoding, and core genome multilocus sequence typing). Workflow performance was validated on a per-assay basis using a collection of 238 in-house-sequenced MTBC isolates, extensively characterized with conventional molecular biology-based approaches supplemented with public data. For SNP-based AMR prediction, results from molecular genotyping methods were supplemented with in silico modified data sets, allowing us to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics of similar to 99% for all assays, except for spoligotyping, where sensitivity dropped to >90%. The validation framework for our WGS-based bioinformatics workflow can aid in the standardization of bioinformatics tools by the MTB community and other SNP-based applications regardless of the targeted pathogen(s). The bioinformatics workflow is available for academic and non-profit use through the Galaxy instance of our institute at https://galaxy.sciensano.be.
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