Issues to overcome before widespread use of WGS

By Joseph James Whitworth

- Last updated on GMT

Picture: Istock/Eraxion
Picture: Istock/Eraxion

Related tags E. coli Escherichia coli

Whole Genome Sequencing (WGS) has been found to hold ‘significant potential’ to replace gold-standard typing methods such as PFGE for routine surveillance and detection of outbreaks.

Advantages include increased discriminatory power and genetic resolution but barriers such as initial capital expense, computing infrastructure, and validated automated, user-friendly WGS analysis software remain before it can be widely implemented.

Quality metrics and standardised protocols including definitions for isolate relatedness are required before routine application of WGS in public health laboratories, said the report in Eurosurveillance.

It assessed the capacity of high-throughput polymerase chain reaction (PCR) of 49 virulence genes, core-genome single nt variants (SNVs) or k​-mer clustering to discriminate between outbreak-associated and sporadic E. coli O157:H7 isolates.

k​-mer phylogenies demonstrated increased discriminatory power compared with core SNV phylogenies.

Pulsed-field gel electrophoresis (PFGE) and multilocus variable-number tandem repeat analysis (MLVA) were comparator typing methods.

WGS or virulence gene profiling

For typing of E. coli O157:H7, WGS was found to be a suitable typing method but not virulence gene profiling involving the genetic targets used in the study.

“The high prevalence of the genetic markers used in this study in E. coli O157:H7, prevents the use of any assay that detects the presence or absence of these genes for the purpose of accurate discrimination between isolates.

“Shiga toxin subtyping was able to differentiate isolates only in cases where the subtypes differed from the most prevalent subtypes (stx1a​ and stx2a​),​ a result similarly observed in an analysis of Albertan E. coli O157:H7 isolates collected from 2004 to 2012.”

Three outbreaks and multiple sporadic isolates from Alberta, Canada were included. Two occurred in 2014 and one in 2012.

The virulence gene profiles of isolates from the 2012 and 2014 Alberta outbreaks and contemporary sporadic isolates were mostly identical; therefore the set of virulence genes in this study were not discriminatory enough to distinguish between outbreak clusters.

From 14 July to 17 September 2014, 149 clinical isolates of E. coli O157:H7 were received by the Alberta ProvLab for molecular typing.

Three outbreaks studied

The first outbreak involved ten patients (four of whom developed HUS) with isolates collected from 14 to 22 July.

There was one unique PFGE pattern combination and three MLVA patterns among outbreak isolates. No food or environmental isolates were recovered.

The second outbreak was the largest in Alberta since PulseNet Canada’s (PNC’s) inception in 2000.

In 2014, 182 clinical isolates of E. coli O157:H7 were collected and referred to the Alberta ProvLab. A total of 111 cases were reported and five developed HUS. Epidemiological investigations revealed a common exposure to contaminated pork produced and distributed in Alberta.

This finding was confirmed by matching PFGE and MLVA profiles in human and food/environmental outbreak isolates (five food and one environmental isolates were received by Alberta ProvLab.

As more isolates were received at the ProvLab, PFGE and MLVA subtyping revealed the outbreak consisted of several isolates with variant, yet closely related PFGE and MLVA patterns.

In 2012, there was a beef-associated E. coli O157:H7 outbreak involving 18 human-clinical cases across Canada. All human-clinical and beef isolates had one indistinguishable PFGE/MLVA profile.

Isolate comparison

Genetic relationships among outbreak-associated isolates were determined by WGS using the PHAC-NML bioinformatics SNVphyl pipeline and k-​mer tree analysis.

Unlike MLVA and/or PFGE using PulseNet standardised methods, k-​mer and core SNV methods do not generate a numerical ‘barcode’ for the organisms, which makes it difficult to compare isolates from different laboratories.

A large shared and curated database will be required to generate cluster identifiers that could act as the organism’s ‘barcode’, said the researchers. 

For WGS to be used standardised protocols, quality validation metrics and a robust method to determine isolate relatedness will need to be established.

“Published reports use different sequencing platforms and bioinformatics pipelines to assemble and analyse WGS data, prohibiting direct comparisons between studies.

“Other considerations encompass the ethical, legal or political barriers to sharing complete genomics data between various health authorities.”​ 

Source: Eurosurveillance, Volume 20, Issue 47, 26 November 2015

“The utility of multiple molecular methods including whole genome sequencing as tools to differentiate Escherichia coli O157:H7 outbreaks”

Authors: BM Berenger, C Berry, T Peterson, P Fach, S Delannoy​, V Li, L Tschetter, C Nadon, L Honish, M Louie, L Chu

Related topics Food Safety & Quality

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