Scientists report on WGS use for E. coli in France

Scientists have described the main lessons learned from the use of whole genome sequencing (WGS) of E. coli in France.

WGS is routine for surveillance of Shiga toxin–producing E. coli (STEC) human isolates. Experts assessed implementation of WGS between 2018 and 2022 for 1,002 sequenced isolates. From genomic distances of serotypes O26:H11, O157:H7, O80:H2, and O103:H2, they determined thresholds for cluster determination and compared those with 5 allelic differences (HC5) clusters. A cluster is defined as cases grouped in space, time, or both. An outbreak is cases for which an epidemiologic link is identified.

Thresholds varied by serotype, 5 to 16 allelic distances and 15 to 20 single-nucleotide polymorphisms, showing limits of a single-threshold approach. The research team confirmed validity of HC5 screening for three serotypes. For O80:H2, results suggest that HC5 is less reliable, and other approaches may be needed.

WGS was implemented in France for STEC in 2017. Surveillance uses the EnteroBase core-genome multilocus sequence typing (cgMLST) hierarchical clustering method (HierCC) for E. coli as an initial screening step for cluster detection at under 5 allelic differences. HC5 clusters are confirmed by core-genome single-nucleotide polymorphism (SNP) tree analysis.

Using five years of data from STEC surveillance, the study, published in Emerging Infectious Diseases, assessed implementation of WGS for cluster detection protocols in France. 

Detected clusters
STEC surveillance and outbreak detection rely on two voluntary systems: epidemiological surveillance of hemolytic uremic syndrome (HUS) in children younger than 15 years old and microbiological surveillance coordinated by the National Reference Center for E. coli, Shigella, Salmonella (NRC-ESS) and its associated NRC at Robert Debré hospital, Paris.

Epidemiologists assess cluster characteristics such as size, space-time distribution, and clinical severity, to decide whether investigations should be opened. Decisions to investigate small or temporally dispersed WGS clusters with under 5 isolates also depends on the availability of human resources.

Almost 500 O26:H11, 226 O80:H2, 223 O157:H7, and 75 O103:H2 isolates were included in the research. The number of HC5 clusters increased with serotype frequency: six for O103:H2, 19 for O157:H7, 23 for O80:H2, and 39 for O26:H11.

Scientists identified 87 HC5 clusters comprising 449 isolates over the study period. Most comprised 2 to 10 isolates; 70 clusters had 2 to 4 isolates, and 11 had 5 to 10 isolates.

For clusters with 2 to 10 isolates, 58 comprised isolates with sampling dates within 1 year of each other. Twenty clusters had a duration of 1 to 2 years, and four had a duration of more than 3 years. Of the six HC5 clusters with more than 10 isolates, four lasted more than 3 years. 

Researchers linked six HC5 clusters with less than five isolates to household transmission. Of the other 27 clusters that led to investigations, a confirmed or suspected link was found for 20 clusters, corresponding to 146 isolates. 

During 2018 to 2022, epidemiologists regularly investigated WGS-linked isolates with patients closely related in space or time, but with no common source suspected despite case interviews. Documentation of epidemiological information for all WGS-linked isolates would provide more complete data to explore and interpret relatedness but would require changes in the prioritization of activities or additional human resources. 

“In summary, after five years of implementation of WGS for STEC surveillance, our results validate the current approach of using cgMLST HC5 as a screening step for cluster detection for three major serotypes in France. For the fourth major serotype, O80:H2, our results indicate that HC5 is less reliable. Exploring possibilities for routinely collecting epidemiologic data for WGS clusters could enrich the capacity to describe the relationship between WGS-linked isolates and epidemiologic links,” said scientists.

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