<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bert Bogaerts</style></author><author><style face="normal" font="default" size="100%">Thomas Delcourt</style></author><author><style face="normal" font="default" size="100%">Karine Soetaert</style></author><author><style face="normal" font="default" size="100%">Samira Boarbi</style></author><author><style face="normal" font="default" size="100%">Pieter-Jan Ceyssens</style></author><author><style face="normal" font="default" size="100%">Raf Winand</style></author><author><style face="normal" font="default" size="100%">Julien Van Braekel</style></author><author><style face="normal" font="default" size="100%">Sigrid C.J. De Keersmaecker</style></author><author><style face="normal" font="default" size="100%">Nancy Roosens</style></author><author><style face="normal" font="default" size="100%">Marchal, Kathleen</style></author><author><style face="normal" font="default" size="100%">Vanessa Mathys</style></author><author><style face="normal" font="default" size="100%">Kevin Vanneste</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">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</style></title><secondary-title><style face="normal" font="default" size="100%">J Clin Microbiol</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Antimicrobial resistance</style></keyword><keyword><style  face="normal" font="default" size="100%">Mycobacterium tuberculosis</style></keyword><keyword><style  face="normal" font="default" size="100%">national reference center</style></keyword><keyword><style  face="normal" font="default" size="100%">public health</style></keyword><keyword><style  face="normal" font="default" size="100%">single nucleotide polymorphism</style></keyword><keyword><style  face="normal" font="default" size="100%">VALIDATION</style></keyword><keyword><style  face="normal" font="default" size="100%">whole genome sequencing</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2021 Mar 31</style></date></pub-dates></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The use of whole genome sequencing (WGS) for routine typing of bacterial isolates has increased substantially in recent years. For (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, /RD, , 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 modified datasets allowing to greatly increase the set of evaluated mutations. The workflow demonstrated very high performance with performance metrics &amp;gt;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.&lt;/p&gt;
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