A Bioinformatics Whole-Genome Sequencing Workflow for Clinical Mycobacterium tuberculosis Complex Isolate Analysis, Validated Using a Reference Collection Extensively Characterized with Conventional Methods and In Silico Approaches

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Abstract
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 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 datasets allowing to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics >99% for all assays, except for spoligotyping where sensitivity dropped to ∼90%. The validation framework for our WGS-based bioinformatics workflow can aid 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 usage through the Galaxy instance of our institute at https://galaxy.sciensano.be.

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