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.
Highlights
Foodborne bacteria pose a major threat to public health
A total of 29 O and 25 H serogroups were identified from the whole genome sequencing (WGS) data of the 30 O and 26 H serogroups detected by conventional methods, one O118 serogroup isolate was not detected by WGS data, and an H47 isolate was typed as an H7 by WGS
For the H serogroup, 95.9% (164/171) of the H antigens were accurately predicted from the WGS data, H antigen detection for non-motile isolates was not counted since such isolates are non-typable by the phenotypic methods (Table 1)
Summary
Foodborne bacteria pose a major threat to public health. To prevent widespread infections due to these bacteria as well as detect outbreaks, rapid and accurate identification and subtyping of these bacteria is key. Workflows at public health laboratories for characterization for STEC can vary, current methods for characterization of STEC in the Enteric Diseases Laboratory Branch at the Centers for Disease Control and Prevention include panels of 22–49 phenotypic tests for identification, agglutination assays with 270 pooled and individual O- and H-specific antisera for serotyping (determination of 188 O and 53 H antigens), panels of five to 10 PCR assays for virulence profiling and broth microdilution assays for antimicrobial susceptibility testing These methods require complex workflows, expensive reagents, labor-intensive quality control procedures, specialized training, and typically take 1–3 weeks to complete. A need exists to simplify workflows and reduce costs and time associated with subtyping and characterization of STEC, possibly through whole genome sequencing
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