Open AccessEvaluation of WGS performance for bacterial pathogen characterization with the Illumina technology optimized for time-critical situations
Author(s) -
Bert Bogaerts,
Raf Winand,
Julien Van Braekel,
Stefan Hoffman,
Nancy Roosens,
Sigrid C. J. De Keersmaecker,
Kathleen Marchal,
Kevin Vanneste
Publication year - 2021
Publication title -
microbial genomics
Language(s) - English
Resource type - Journals
ISSN - 2057-5858
DOI - 10.1099/mgen.0.000699
Subject(s) - illumina dye sequencing , computational biology , biology , neisseria meningitidis , multilocus sequence typing , whole genome sequencing , dna sequencing , neisseria , genome , genetics , gene , genotype , bacteria
Whole genome sequencing (WGS) has become the reference standard for bacterial outbreak investigation and pathogen typing, providing a resolution unattainable with conventional molecular methods. Data generated with Illumina sequencers can however only be analysed after the sequencing run has finished, thereby losing valuable time during emergency situations. We evaluated both the effect of decreasing overall run time, and also a protocol to transfer and convert intermediary files generated by Illumina sequencers enabling real-time data analysis for multiple samples part of the same ongoing sequencing run, as soon as the forward reads have been sequenced. To facilitate implementation for laboratories operating under strict quality systems, extensive validation of several bioinformatics assays (16S rRNA species confirmation, gene detection against virulence factor and antimicrobial resistance databases, SNP-based antimicrobial resistance detection, serotype determination, and core genome multilocus sequence typing) for three bacterial pathogens ( Mycobacterium tuberculosis , Neisseria meningitidis , and Shiga-toxin producing Escherichia coli ) was performed by evaluating performance in function of the two most critical sequencing parameters, i.e. read length and coverage. For the majority of evaluated bioinformatics assays, actionable results could be obtained between 14 and 22 h of sequencing, decreasing the overall sequencing-to-results time by more than half. This study aids in reducing the turn-around time of WGS analysis by facilitating a faster response in time-critical scenarios and provides recommendations for time-optimized WGS with respect to required read length and coverage to achieve a minimum level of performance for the considered bioinformatics assay(s), which can also be used to maximize the cost-effectiveness of routine surveillance sequencing when response time is not essential.