WGS can address multiple questions in one experiment - study
The work demonstrated the benefit of WGS to address questions on virulence, antimicrobial resistance, source attribution, surveillance and outbreak detection and investigation, in a single experiment and provide high quality, unambiguous data.
The main objective was to compare L. monocytogenes isolates collected in the EU from ready-to-eat (RTE) foods, compartments along the food chain and human cases.
It compared L. monocytogenes isolates from the EU-wide baseline survey on RTE foods in 2010-11.
Statens Serum Institut (SSI), French Agency for Food, Environmental and Occupational Health & Safety (ANSES), Public Health England (PHE) and University of Aberdeen (UA) did the work.
Experience from complex outbreaks
WGS analysis such as cgMLST and cgSNP-based typing approaches have been shown to have unparalleled strain typing resolution and WGS is able to link previously undetected cases to outbreaks and detect clusters of cases previously undetected.
Limitations have less to do with the actual sequencing and the analyses but more dependent on representative sampling of isolates and requirement for good epidemiological data to further investigate genetically linked by WGS.
This study supports the use of WGS for L. monocytogenes outbreak investigations although experience from more complex outbreaks would be valuable.
To maximise the advantages of using WGS for outbreak detection it would be highly valuable to use it for the surveillance of listeriosis across Europe.
Listeriosis is transmitted by contaminated food with ready-to-eat meat and fish products and soft and semi-soft cheeses often identified as sources of infection.
Due to its ability to survive under conditions of stress, L. monocytogenes can persist in processing environments and often this is the route by which RTE food becomes contaminated.
A total of 1,143 L. monocytogenes isolates were selected, including 333 human clinical and 810 isolates from the food chain.
Isolates were whole genome sequenced at Public Health England with the Illumina HiSeq.
Virulence factors and analysis of outbreaks
WGS data were assessed for 115 putative markers of virulence. More than 80% of markers were present in 95% of isolates suggesting most putative markers in the literature are ubiquitous across L. monocytogenes lineages I and II.
“The majority of markers not present in all isolates were over-represented in food and/or lineage II isolates with markers associated with stress survival or cell wall modification being particularly enriched.
“Conversely, the recently discovered Listeria pathogenicity island 3 and the surface protein VIP were more likely to be found in clinical and/or lineage I isolates.”
Retrospective analysis of nine outbreaks showed that WGS is a powerful tool in national and international investigations as it can accurately rule isolates in or out of outbreaks.
Two outbreaks were over an extended time period and the variation may reflect diversity within the source over a long period.
“Most of the outbreaks are tightly clustered; six out of nine show a typical point-source-like pattern with a median pairwise distance of ≤5 SNP and a maximum pairwise distance ≤10 SNP,” said the study.
“The results also indicate that every outbreak should be considered in its own context and that one should not use a single universal cut off value for separating an outbreak from background isolates.”
Three allelic based typing methods were used, multi-locus sequence typing (MLST), core genome MLST (cgMLST) and ribosomal MLST (rMLST) and Single Nucleotide Polymorphisms (SNPs).
Researchers investigated the phylogeny of L. monocytogenes isolates and made data sets to provide a framework for further analyses on genetic diversity and potential epidemiological associations.
“This was carried out using a range of bioinformatic procedures including several gene-by-gene based approaches such as 7-gene MLST, rMLST, cgMLST as well as SNP-based methods including cg SNP analysis.
“This study has facilitated the WGS analysis of a unique and large data set of L. monocytogenes isolates and has enabled the population to be defined to an unprecedented level of resolution from linage to nucleotide.”
The WGS data generated is available for additional analysis to address questions and represents a resource for further studies.
Source: EFSA supporting publication 2017:EN-1151. 170 pp
“Closing gaps for performing a risk assessment on Listeria monocytogenes in ready-to-eat (RTE) foods: activity 3, the comparison of isolates from different compartments along the food chain, and from humans using whole genome sequencing (WGS) analysis”
Authors: Eva Møller Nielsen, Jonas T. Björkman, Kristoffer Kiil, Kathie Grant, Tim Dallman, Anaïs Painset, Corinne Amar, Sophie Roussel, Laurent Guillier, Benjamin Félix, Ovidiu Rotariu, Francisco Perez-Reche, Ken Forbes and Norval Strachan
