Scientific Opinion on the evaluation of molecular typing methods for major food-borne microbiological hazards and their use for attribution modelling, outbreak investigation and scanning surveillance: Part 2 (surveillance and data management activities)

Application of a strain-level shotgun metagenomics approach on food samples: resolution of the source of a Salmonella food-borne outbreak

Food-borne outbreak investigation currently relies on the time-consuming and challenging bacterial isolation from food, to be able to link food-derived strains to more easily obtained isolates from infected people. When no food isolate can be obtained, the source of the outbreak cannot be unambiguously determined. Shotgun metagenomics approaches applied to the food samples could circumvent this need for isolation from the suspected source, but require downstream strain-level data analysis to be able to accurately link to the human isolate. Until now, this approach has not yet been applied outside research settings to analyse real food-borne outbreak samples. In September 2019, a Salmonella outbreak occurred in a hotel school in Bruges, Belgium, affecting over 200 students and teachers. Following standard procedures, the Belgian National Reference Center for human salmonellosis and the National Reference Laboratory for Salmonella in food and feed used conventional analysis based on isolation, serotyping and MLVA (multilocus variable number tandem repeat analysis) comparison, followed by whole-genome sequencing, to confirm the source of the contamination over 2 weeks after receipt of the sample, which was freshly prepared tartar sauce in a meal cooked at the school. Our team used this outbreak as a case study to deliver a proof of concept for a short-read strain-level shotgun metagenomics approach for source tracking. We received two suspect food samples: the full meal and some freshly made tartar sauce served with this meal, requiring the use of raw eggs. After analysis, we could prove, without isolation, that Salmonella was present in both samples, and we obtained an inferred genome of a Salmonella enterica subsp. enterica serovar Enteritidis that could be linked back to the human isolates of the outbreak in a phylogenetic tree. These metagenomics-derived outbreak strains were separated from sporadic cases as well as from another outbreak circulating in Europe at the same time period. This is, to our knowledge, the first Salmonella food-borne outbreak investigation uniquely linking the food source using a metagenomics approach and this in a fast time frame.

Development of food safety risk assessment tools based on molecular typing and WGS of Campylobacter jejuni genome

The ‘learning‐by‐doing’ EU‐FORA fellowship programme in the development of risk assessment tools based on molecular typing and WGS of Campylobacter jejuni genome was structured into two main activities: the primary one focused on training on risk assessment methodology and the secondary one in starting and enhancing the cooperation between the hosting and home organisations, or other joint activities. The primary activities had three subsequent work packages (WPs): WP1 data organisation, WP2 cluster and association analyses, and WP3 development of risk assessment models. The secondary activities have branched into one workshop and the initiation of a cooperation programme between the hosting and home organisations. In the last quarter, the fellow had contributed to the characterisation of some pathogens in possible response to a changing climate, part of the CLEFSA project. The fellow attended various forms of training: online and on‐site courses, and also participated at several conferences and meetings for improving his knowledge and skills, contributing to performing the Campylobacter risk assessment and source attribution.

An international outbreak of Salmonella enterica serotype Enteritidis linked to eggs from Poland: a microbiological and epidemiological study

BACKGROUND

Salmonella spp are a major cause of food-borne outbreaks in Europe. We investigated a large multi-country outbreak of Salmonella enterica serotype Enteritidis in the EU and European Economic Area (EEA).

METHODS

A confirmed case was defined as a laboratory-confirmed infection with the outbreak strains of S Enteritidis based on whole-genome sequencing (WGS), occurring between May 1, 2015, and Oct 31, 2018. A probable case was defined as laboratory-confirmed infection with S Enteritidis with the multiple-locus variable-number tandem repeat analysis outbreak profile. Multi-country epidemiological, trace-back, trace-forward, and environmental investigations were done. We did a case-control study including confirmed and probable cases and controls randomly sampled from the population registry (frequency matched by age, sex, and postal code). Odds ratios (ORs) for exposure rates between cases and controls were calculated with unmatched univariable and multivariable logistic regression.

FINDINGS

18 EU and EEA countries reported 838 confirmed and 371 probable cases. 509 (42%) cases were reported in 2016, after which the number of cases steadily increased. The case-control study results showed that cases more often ate in food establishments than did controls (OR 3·4 [95% CI 1·6-7·3]), but no specific food item was identified. Recipe-based food trace-back investigations among cases who ate in food establishments identified eggs from Poland as the vehicle of infection in October, 2016. Phylogenetic analysis identified two strains of S Enteritidis in human cases that were subsequently identified in salmonella-positive eggs and primary production premises in Poland, confirming the source of the outbreak. After control measures were implemented, the number of cases decreased, but increased again in March, 2017, and the increase continued into 2018.

INTERPRETATION

This outbreak highlights the public health value of multi-country sharing of epidemiological, trace-back, and microbiological data. The re-emergence of cases suggests that outbreak strains have continued to enter the food chain, although changes in strain population dynamics and fewer cases indicate that control measures had some effect. Routine use of WGS in salmonella surveillance and outbreak response promises to identify and stop outbreaks in the future.

FUNDING

European Centre for Disease Prevention and Control; Directorate General for Health and Food Safety, European Commission; and National Public Health and Food Safety Institutes of the authors' countries (see Acknowledgments for full list).

GenomeGraphR: A user-friendly open-source web application for foodborne pathogen whole genome sequencing data integration, analysis, and visualization

Food safety risk assessments and large-scale epidemiological investigations have the potential to provide better and new types of information when whole genome sequence (WGS) data are effectively integrated. Today, the NCBI Pathogen Detection database WGS collections have grown significantly through improvements in technology, coordination, and collaboration, such as the GenomeTrakr and PulseNet networks. However, high-quality genomic data is not often coupled with high-quality epidemiological or food chain metadata. We have created a set of tools for cleaning, curation, integration, analysis and visualization of microbial genome sequencing data. It has been tested using Salmonella enterica and Listeria monocytogenes data sets provided by NCBI Pathogen Detection (160,000 sequenced isolates in 2018). GenomeGraphR presents foodborne pathogen WGS data and associated curated metadata in a user-friendly interface that allows a user to query a variety of research questions such as, transmission sources and dynamics, global reach, and persistence of genotypes associated with contamination in the food supply and foodborne illness across time or space. The application is freely available (https://fda-riskmodels.foodrisk.org/genomegraphr/).

Current Barriers to Large-scale Interoperability of Traceability Technology in the Seafood Sector

Interoperability is a critical component of full-chain digital traceability, but is almost nonexistent in the seafood industry. Using both quantitative and qualitative methodology, this study explores the barriers impeding progress toward large-scale interoperability among digital traceability systems in the seafood sector from the perspectives of seafood companies, technology vendors, and supply chains as a whole. We highlight lessons from recent research and field work focused on implementing traceability across full supply chains and make some recommendations for next steps in terms of overcoming challenges and scaling current efforts.

Towards an integrated food safety surveillance system: a simulation study to explore the potential of combining genomic and epidemiological metadata

Foodborne infection is a result of exposure to complex, dynamic food systems. The efficiency of foodborne infection is driven by ongoing shifts in genetic machinery. Next-generation sequencing technologies can provide high-fidelity data about the genetics of a pathogen. However, food safety surveillance systems do not currently provide similar high-fidelity epidemiological metadata to associate with genetic data. As a consequence, it is rarely possible to transform genetic data into actionable knowledge that can be used to genuinely inform risk assessment or prevent outbreaks. Big data approaches are touted as a revolution in decision support, and pose a potentially attractive method for closing the gap between the fidelity of genetic and epidemiological metadata for food safety surveillance. We therefore developed a simple food chain model to investigate the potential benefits of combining 'big' data sources, including both genetic and high-fidelity epidemiological metadata. Our results suggest that, as for any surveillance system, the collected data must be relevant and characterize the important dynamics of a system if we are to properly understand risk: this suggests the need to carefully consider data curation, rather than the more ambitious claims of big data proponents that unstructured and unrelated data sources can be combined to generate consistent insight. Of interest is that the biggest influencers of foodborne infection risk were contamination load and processing temperature, not genotype. This suggests that understanding food chain dynamics would probably more effectively generate insight into foodborne risk than prescribing the hazard in ever more detail in terms of genotype.

Tracing sources of Listeria contamination in traditional Italian cheese associated with a US outbreak: investigations in Italy

In 2012 a US multistate outbreak of listeriosis was linked to ricotta salata imported from Italy, made from pasteurized sheep's milk. Sampling activities were conducted in Italy to trace the source of Listeria monocytogenes contamination. The cheese that caused the outbreak was produced in a plant in Apulia that processed semi-finished cheeses supplied by five plants in Sardinia. During an 'emergency sampling', 179 (23·6%) out of 758 end-products tested positive for L. monocytogenes, with concentrations from <10 c.f.u./g to 1·1 × 106 c.f.u./g. Positive processing environment samples were found in two out of four processing plants. A 'follow-up sampling' was conducted 8 months later, when environmental samples from three out of six plants tested positive for L. monocytogenes and for Listeria spp. PFGE subtyping showed 100% similarity between US clinical strains and isolates from ricotta salata, confirming the origin of the outbreak. The persistence of strains in environmental niches of processing plants was demonstrated, and is probably the cause of product contamination. Two PFGE profiles from clinical cases of listeriosis in Italy in 2011, stored in the MSS-TESSy database, were found to have 100% similarity to one PFGE profile from a US clinical case associated with the consumption of ricotta salata, according to the US epidemiological investigation (sample C, pulsotype 17). However, they had 87% similarity to the only PFGE profile found both in the US clinical case and in 14 ricotta cheese samples collected during the emergency sampling (sample B, pulsotype 1). Sharing of molecular data and availability of common characterization protocols were key elements that connected the detection of the US outbreak to the investigation of the food source in Italy. Simultaneous surveillance systems at both food and human levels are a necessity for the efficient rapid discovery of the source of an outbreak of L. monocytogenes.

Extending RAD tag analysis to microbial ecology: a comparison between MultiLocus Sequence Typing and 2b-RAD to investigate Listeria monocytogenes genetic structure

The advent of next-generation sequencing (NGS) has dramatically changed bacterial typing technologies, increasing our ability to differentiate bacterial isolates. Despite it is now possible to sequence a bacterial genome in a few days and at reasonable costs, most genetic analyses do not require whole-genome sequencing, which also remains impractical for large population samples due to the cost of individual library preparation and bioinformatics. More traditional sequencing approaches, however, such as MultiLocus Sequence Typing (mlst) are quite laborious and time-consuming, especially for large-scale analyses. In this study, a genotyping approach based on restriction site-associated (RAD) tag sequencing, 2b-RAD, was applied to characterize Listeria monocytogenes strains. To verify the feasibility of the method, an in silico analysis was performed on 30 available complete genomes. For the same set of strains, in silico mlst analysis was conducted as well. Subsequently, 2b-RAD and mlst analyses were experimentally carried out on 58 isolates collected from food samples or food-processing sites. The obtained results demonstrate that 2b-RAD predicts mlst types and often provides more detailed information on population structure than mlst. Moreover, the majority of variants differentiating identical sequence type isolates mapped against accessory fragments, thus providing additional information to characterize strains. Although mlst still represents a reliable typing method, large-scale studies on molecular epidemiology and public health, as well as bacterial phylogenetics, population genetics and biosafety could benefit of a low cost and fast turnaround time approach such as the 2b-RAD analysis proposed here.