Implementation of Whole Genome Sequencing (WGS) for Identification and Characterization of Shiga Toxin-Producing Escherichia coli (STEC) in the United States

Abstract

Shiga toxin-producing Escherichia coli (STEC) is an important foodborne pathogen capable of causing severe disease in humans. Rapid and accurate identification and characterization techniques are essential during outbreak investigations. Current methods for characterization of STEC are expensive and time-consuming. With the advent of rapid and cheap whole genome sequencing (WGS) benchtop sequencers, the potential exists to replace traditional workflows with WGS. The aim of this study was to validate tools to do reference identification and characterization from WGS for STEC in a single workflow within an easy to use commercially available software platform. Publically available serotype, virulence, and antimicrobial resistance databases were downloaded from the Center for Genomic Epidemiology (CGE) (www.genomicepidemiology.org) and integrated into a genotyping plug-in with in silico PCR tools to confirm some of the virulence genes detected from WGS data. Additionally, down sampling experiments on the WGS sequence data were performed to determine a threshold for sequence coverage needed to accurately predict serotype and virulence genes using the established workflow. The serotype database was tested on a total of 228 genomes and correctly predicted from WGS for 96.1% of O serogroups and 96.5% of H serogroups identified by conventional testing techniques. A total of 59 genomes were evaluated to determine the threshold of coverage to detect the different WGS targets, 40 were evaluated for serotype and virulence gene detection and 19 for the stx gene subtypes. For serotype, 95% of the O and 100% of the H serogroups were detected at > 40x and ≥ 30x coverage, respectively. For virulence targets and stx gene subtypes, nearly all genes were detected at > 40x, though some targets were 100% detectable from genomes with coverage ≥20x. The resistance detection tool was 97% concordant with phenotypic testing results. With isolates sequenced to > 40x coverage, the different databases accurately predicted serotype, virulence, and resistance from WGS data, providing a fast and cheaper alternative to conventional typing techniques.

Validation and Implementation of Clinical Laboratory Improvements Act-Compliant Whole-Genome Sequencing in the Public Health Microbiology Laboratory

“…Overall, we achieved high accuracy, reproducibility, repeatability, diagnostic sensitivity, and specificity for all assay analytes ranging from 99 to 100%, which exceeds the 90% threshold for LDT performance parameters per CLIA requirements. These findings are in agreement with several recent reports of 93% to 100% accuracies in WGS identification, subtyping, and antimicrobial resistance gene detection for a number of pathogens (44–47). We determined SNP detection at coverages of 5× to 60× and established an LOD for SNP detection at 60×, which was the lowest coverage that yielded accurate SNP detection in all of the samples.…”

Validation and Implementation of CLIA-Compliant Whole Genome Sequencing (WGS) in Public Health Laboratory

“…Overall, we achieved high accuracy, precision, sensitivity and specificity for all test analytes ranging from 99-100%, which well exceeds 90% threshold for these performance parameters for LDT as per CLIA. These findings are in agreement with recent reports of 93%-100% accuracy in WGS identification, subtyping, and antimicrobial resistance genes detection in a number of pathogens [50–53].…”

Construction of a Pan-Genome Allele Database of Salmonella enterica Serovar Enteritidis for Molecular Subtyping and Disease Cluster Identification

“…The wgMLST approach has been used as a subtyping tool in the epidemiological study of various bacterial pathogens (Cody et al, 2013; Bratcher et al, 2014; Kohl et al, 2014; Leopold et al, 2014; Antwerpen et al, 2015; de Been et al, 2015; Jackson et al, 2016; Lindsey et al, 2016; Raphael et al, 2016). This gene-by-gene comparison method is able to provide high-resolution typing results to allow accurate discrimination between epidemiologically related isolates and unrelated isolates.…”

“…With the advance of next generation sequencing (NGS) techniques, whole genome sequencing (WGS) has become a rapid and inexpensive method for the characterization of bacteria. WGS-based analysis has been increasingly used in public health laboratories to characterize bacterial pathogens and perform subtyping for epidemiologic study (Deng et al, 2016; Fratamico et al, 2016; Lindsey et al, 2016). …”