Validation strategy of a bioinformatics whole genome sequencing workflow for Shiga toxin-producing Escherichia coli using a reference collection extensively characterized with conventional methods.

Bert Bogaerts,Florence Crombé,Raf Winand,Julien Van Braekel,Bavo Verhaegen,Kathleen Marchal,Denis Piérard,Sigrid C J De Keersmaecker,Qiang Fu,Kevin Vanneste,Nancy H C Roosens,Sarah Denayer,Stéphanie Nouws

doi:10.1099/mgen.0.000531

Abstract

Whole genome sequencing (WGS) enables complete characterization of bacterial pathogenic isolates at single nucleotide resolution, making it the ultimate tool for routine surveillance and outbreak investigation. The lack of standardization, and the variation regarding bioinformatics workflows and parameters, however, complicates interoperability among (inter)national laboratories. We present a validation strategy applied to a bioinformatics workflow for Illumina data that performs complete characterization of Shiga toxin-producing Escherichia coli (STEC) isolates including antimicrobial resistance prediction, virulence gene detection, serotype prediction, plasmid replicon detection and sequence typing. The workflow supports three commonly used bioinformatics approaches for the detection of genes and alleles: alignment with blast+, kmer-based read mapping with KMA, and direct read mapping with SRST2. A collection of 131 STEC isolates collected from food and human sources, extensively characterized with conventional molecular methods, was used as a validation dataset. Using a validation strategy specifically adopted to WGS, we demonstrated high performance with repeatability, reproducibility, accuracy, precision, sensitivity and specificity above 95 % for the majority of all assays. The WGS workflow is publicly available as a ‘push-button’ pipeline at https://galaxy.sciensano.be. Our validation strategy and accompanying reference dataset consisting of both conventional and WGS data can be used for characterizing the performance of various bioinformatics workflows and assays, facilitating interoperability between laboratories with different WGS and bioinformatics set-ups.

Highlights

Whole genome sequencing (WGS) has revolutionized foodborne outbreak investigation and surveillance of a wide variety of microbial pathogens [1]
All other false negatives (FNs) were caused by alleles present in the EnteroBase scheme missing from the PubMLST scheme, even though both databases were assessed at the same time and alleles that were added to EnteroBase more recently than the missing ones from PubMLST were available in both
We present an updated validation framework to extensively validate a bioinformatics workflow (Fig. 1) for the characterization of Shiga toxin-p roducing Escherichia coli (STEC) isolates using WGS data

Summary

Introduction

Whole genome sequencing (WGS) has revolutionized foodborne outbreak investigation and surveillance of a wide variety of microbial pathogens [1]. WGS-b ased methods for relatedness investigation can be scaled up from case-b y-c ase applications to routine surveillance, as illustrated by EnteroBase for cgMLST [6], and SnapperDB for wgSNP [7] analysis Because of these advantages, the use of WGS for pathogen typing in both outbreak situations and routine surveillance is becoming more widespread, with many national reference centres (NRCs, human) and laboratories (NRLs, food and feed) integrating it into their routine activities [1, 8, 9]. The second hurdle, i.e. the need for validation of bioinformatics assays to demonstrate that they are ‘fit-for-purpose’ and adhere to certain predefined quality characteristics, as

Methods

Results

Conclusion