Vaccine effectiveness against COVID-19 hospitalisation in adults (≥ 20 years) during Alpha- and Delta-dominant circulation: I-MOVE-COVID-19 and VEBIS SARI VE networks, Europe, 2021.

IntroductionTwo large multicentre European hospital networks have estimated vaccine effectiveness (VE) against COVID-19 since 2021.AimWe aimed to measure VE against PCR-confirmed SARS-CoV-2 in hospitalised severe acute respiratory illness (SARI) patients ≥ 20 years, combining data from these networks during Alpha (March-June)- and Delta (June-December)-dominant periods, 2021.MethodsForty-six participating hospitals across 14 countries follow a similar generic protocol using the test-negative case-control design. We defined complete primary series vaccination (PSV) as two doses of a two-dose or one of a single-dose vaccine ≥ 14 days before onset.ResultsWe included 1,087 cases (538 controls) and 1,669 cases (1,442 controls) in the Alpha- and Delta-dominant periods, respectively. During the Alpha period, VE against hospitalisation with SARS-CoV2 for complete Comirnaty PSV was 85% (95% CI: 69-92) overall and 75% (95% CI: 42-90) in those aged ≥ 80 years. During the Delta period, among SARI patients ≥ 20 years with symptom onset ≥ 150 days from last PSV dose, VE for complete Comirnaty PSV was 54% (95% CI: 18-74). Among those receiving Comirnaty PSV and mRNA booster (any product) ≥ 150 days after last PSV dose, VE was 91% (95% CI: 57-98). In time-since-vaccination analysis, complete all-product PSV VE was > 90% in those with their last dose < 90 days before onset; ≥ 70% in those 90-179 days before onset.ConclusionsOur results from this EU multi-country hospital setting showed that VE for complete PSV alone was higher in the Alpha- than the Delta-dominant period, and addition of a first booster dose during the latter period increased VE to over 90%.

Vaccine effectiveness against COVID-19 hospitalisation in adults (≥ 20 years) during Omicron-dominant circulation: I-MOVE-COVID-19 and VEBIS SARI VE networks, Europe, 2021 to 2022.

IntroductionThe I-MOVE-COVID-19 and VEBIS hospital networks have been measuring COVID-19 vaccine effectiveness (VE) in participating European countries since early 2021.AimWe aimed to measure VE against PCR-confirmed SARS-CoV-2 in patients ≥ 20 years hospitalised with severe acute respiratory infection (SARI) from December 2021 to July 2022 (Omicron-dominant period).MethodsIn both networks, 46 hospitals (13 countries) follow a similar test-negative case-control protocol. We defined complete primary series vaccination (PSV) and first booster dose vaccination as last dose of either vaccine received ≥ 14 days before symptom onset (stratifying first booster into received < 150 and ≥ 150 days after last PSV dose). We measured VE overall, by vaccine category/product, age group and time since first mRNA booster dose, adjusting by site as a fixed effect, and by swab date, age, sex, and presence/absence of at least one commonly collected chronic condition.ResultsWe included 2,779 cases and 2,362 controls. The VE of all vaccine products combined against hospitalisation for laboratory-confirmed SARS-CoV-2 was 43% (95% CI: 29-54) for complete PSV (with last dose received ≥ 150 days before onset), while it was 59% (95% CI: 51-66) after addition of one booster dose. The VE was 85% (95% CI: 78-89), 70% (95% CI: 61-77) and 36% (95% CI: 17-51) for those with onset 14-59 days, 60-119 days and 120-179 days after booster vaccination, respectively.ConclusionsOur results suggest that, during the Omicron period, observed VE against SARI hospitalisation improved with first mRNA booster dose, particularly for those having symptom onset < 120 days after first booster dose.

Genomic monitoring of SARS-CoV-2 variants using sentinel SARI hospital surveillance.

Background: To support the COVID-19 pandemic response, many countries, including Belgium, implemented baseline genomic surveillance (BGS) programs aiming to early detect and characterize new SARS-CoV-2 variants. In parallel, Belgium maintained a sentinel network of six hospitals that samples patients with severe acute respiratory infections (SARI) and integrated SARS-CoV-2 detection within a broader range of respiratory pathogens. We evaluate the ability of the SARI surveillance to monitor general trends and early signals of viral genetic evolution of SARS-CoV-2 and compare it with the BGS as a reference model. Methods: Nine-hundred twenty-five SARS-CoV-2 positive samples from patients fulfilling the Belgian SARI definition between January 2020 and December 2022 were sequenced using the ARTIC Network amplicon tiling approach on a MinION platform. Weekly variant of concern (VOC) proportions and types were compared to those that were circulating between 2021 and 2022, using 96,251 sequences of the BGS. Results: SARI surveillance allowed timely detection of the Omicron (BA.1, BA.2, BA.4, and BA.5) and Delta (B.1.617.2) VOCs, with no to 2 weeks delay according to the start of their epidemic growth in the Belgian population. First detection of VOCs B.1.351 and P.1 took longer, but these remained minor in Belgium. Omicron BA.3 was never detected in SARI surveillance. Timeliness could not be evaluated for B.1.1.7, being already major at the start of the study period. Conclusions: Genomic surveillance of SARS-CoV-2 using SARI sentinel surveillance has proven to accurately reflect VOCs detected in the population and provides a cost-effective solution for long-term genomic monitoring of circulating respiratory viruses.

Transforming Shiga toxin-producing Escherichia coli surveillance through whole genome sequencing in food safety practices.

Introduction: Shiga toxin-producing Escherichia coli (STEC) is a gastrointestinal pathogen causing foodborne outbreaks. Whole Genome Sequencing (WGS) in STEC surveillance holds promise in outbreak prevention and confinement, in broadening STEC epidemiology and in contributing to risk assessment and source attribution. However, despite international recommendations, WGS is often restricted to assist outbreak investigation and is not yet fully implemented in food safety surveillance across all European countries, in contrast to for example in the United States. Methods: In this study, WGS was retrospectively applied to isolates collected within the context of Belgian food safety surveillance and combined with data from clinical isolates to evaluate its benefits. A cross-sector WGS-based collection of 754 strains from 1998 to 2020 was analyzed. Results: We confirmed that WGS in food safety surveillance allows accurate detection of genomic relationships between human cases and strains isolated from food samples, including those dispersed over time and geographical locations. Identifying these links can reveal new insights into outbreaks and direct epidemiological investigations to facilitate outbreak management. Complete WGS-based isolate characterization enabled expanding epidemiological insights related to circulating serotypes, virulence genes and antimicrobial resistance across different reservoirs. Moreover, associations between virulence genes and severe disease were determined by incorporating human metadata into the data analysis. Gaps in the surveillance system were identified and suggestions for optimization related to sample centralization, harmonizing isolation methods, and expanding sampling strategies were formulated. Discussion: This study contributes to developing a representative WGS-based collection of circulating STEC strains and by illustrating its benefits, it aims to incite policymakers to support WGS uptake in food safety surveillance.

Metagenomics to Detect and Characterize Viruses in Food Samples at Genome Level? Lessons Learnt from a Norovirus Study.

In this proof-of-concept study on food contaminated with norovirus, we investigated the feasibility of metagenomics as a new method to obtain the whole genome sequence of the virus and perform strain level characterization but also relate to human cases in order to resolve foodborne outbreaks. We tested several preparation methods to determine if a more open sequencing approach, i.e., shotgun metagenomics, or a more targeted approach, including hybrid capture, was the most appropriate. The genetic material was sequenced using Oxford Nanopore technologies with or without adaptive sampling, and the data were analyzed with an in-house bioinformatics workflow. We showed that a viral genome sequence could be obtained for phylogenetic analysis with shotgun metagenomics if the contamination load was sufficiently high or after hybrid capture for lower contamination. Relatedness to human cases goes well beyond the results obtained with the current qPCR methods. This workflow was also tested on a publicly available dataset of food spiked with norovirus and hepatitis A virus. This allowed us to prove that we could detect even fewer genome copies and two viruses present in a sample using shotgun metagenomics. We share the lessons learnt on the satisfactory and unsatisfactory results in an attempt to advance the field.

Towards Real-Time and Affordable Strain-Level Metagenomics-Based Foodborne Outbreak Investigations Using Oxford Nanopore Sequencing Technologies.

The current routine laboratory practices to investigate food samples in case of foodborne outbreaks still rely on attempts to isolate the pathogen in order to characterize it. We present in this study a proof of concept using Shiga toxin-producing Escherichia coli spiked food samples for a strain-level metagenomics foodborne outbreak investigation method using the MinION and Flongle flow cells from Oxford Nanopore Technologies, and we compared this to Illumina short-read-based metagenomics. After 12 h of MinION sequencing, strain-level characterization could be achieved, linking the food containing a pathogen to the related human isolate of the affected patient, by means of a single-nucleotide polymorphism (SNP)-based phylogeny. The inferred strain harbored the same virulence genes as the spiked isolate and could be serotyped. This was achieved by applying a bioinformatics method on the long reads using reference-based classification. The same result could be obtained after 24-h sequencing on the more recent lower output Flongle flow cell, on an extract treated with eukaryotic host DNA removal. Moreover, an alternative approach based on in silico DNA walking allowed to obtain rapid confirmation of the presence of a putative pathogen in the food sample. The DNA fragment harboring characteristic virulence genes could be matched to the E. coli genus after sequencing only 1 h with the MinION, 1 h with the Flongle if using a host DNA removal extraction, or 5 h with the Flongle with a classical DNA extraction. This paves the way towards the use of metagenomics as a rapid, simple, one-step method for foodborne pathogen detection and for fast outbreak investigation that can be implemented in routine laboratories on samples prepared with the current standard practices.

Whole Genome Sequencing Provides an Added Value to the Investigation of Staphylococcal Food Poisoning Outbreaks.

Through staphylococcal enterotoxin (SE) production, Staphylococcus aureus is a common cause of food poisoning. Detection of staphylococcal food poisoning (SFP) is mostly performed using immunoassays, which, however, only detect five of 27 SEs described to date. Polymerase chain reactions are, therefore, frequently used in complement to identify a bigger arsenal of SE at the gene level (se) but are labor-intensive. Complete se profiling of isolates from different sources, i.e., food and human cases, is, however, important to provide an indication of their potential link within foodborne outbreak investigation. In addition to complete se gene profiling, relatedness between isolates is determined with more certainty using pulsed-field gel electrophoresis, Staphylococcus protein A gene typing and other methods, but these are shown to lack resolution. We evaluated how whole genome sequencing (WGS) can offer a solution to these shortcomings. By WGS analysis of a selection of S. aureus isolates, including some belonging to a confirmed foodborne outbreak, its added value as the ultimate multiplexing method was demonstrated. In contrast to PCR-based se gene detection for which primers are sometimes shown to be non-specific, WGS enabled complete se gene profiling with high performance, provided that a database containing reference sequences for all se genes was constructed and employed. The custom compiled database and applied parameters were made publicly available in an online user-friendly interface. As an all-in-one approach with high resolution, WGS additionally allowed inferring correct isolate relationships. The different DNA extraction kits that were tested affected neither se gene profiling nor relatedness determination, which is interesting for data sharing during SFP outbreak investigation. Although confirming the production of enterotoxins remains important for SFP investigation, we delivered a proof-of-concept that WGS is a valid alternative and/or complementary tool for outbreak investigation.

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.

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

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.

Outbreak of Central American born Shigella sonnei in two youth camps in Belgium in the summer of 2019.

In 2019, an outbreak of Shigella sonnei occurred during two youth camps in Belgium. The clustering of isolates from both camps was confirmed by next-generation sequencing, as well as a secondary infection of a technician. The outbreak strain clustered with internationally isolated strains from patients with recent travel history to Central America. This report exemplifies enhanced surveillance and international collaboration between public health institutes by enabling to link local outbreaks to region-specific sublineages circulating abroad.

Impact of DNA extraction on whole genome sequencing analysis for characterization and relatedness of Shiga toxin-producing Escherichia coli isolates.

Whole genome sequencing (WGS) has proven to be the ultimate tool for bacterial isolate characterization and relatedness determination. However, standardized and harmonized workflows, e.g. for DNA extraction, are required to ensure robust and exchangeable WGS data. Data sharing between (inter)national laboratories is essential to support foodborne pathogen control, including outbreak investigation. This study evaluated eight commercial DNA preparation kits for their potential influence on: (i) DNA quality for Nextera XT library preparation; (ii) MiSeq sequencing (data quality, read mapping against plasmid and chromosome references); and (iii) WGS data analysis, i.e. isolate characterization (serotyping, virulence and antimicrobial resistance genotyping) and phylogenetic relatedness (core genome multilocus sequence typing and single nucleotide polymorphism analysis). Shiga toxin-producing Escherichia coli (STEC) was selected as a case study. Overall, data quality and inferred phylogenetic relationships between isolates were not affected by the DNA extraction kit choice, irrespective of the presence of confounding factors such as EDTA in DNA solution buffers. Nevertheless, completeness of STEC characterization was, although not substantially, influenced by the plasmid extraction performance of the kits, especially when using Nextera XT library preparation. This study contributes to addressing the WGS challenges of standardizing protocols to support data portability and to enable full exploitation of its potential.

A Practical Method to Implement Strain-Level Metagenomics-Based Foodborne Outbreak Investigation and Source Tracking in Routine.

The management of a foodborne outbreak depends on the rapid and accurate identification of the responsible food source. Conventional methods based on isolation of the pathogen from the food matrix and target-specific real-time polymerase chain reactions (qPCRs) are used in routine. In recent years, the use of whole genome sequencing (WGS) of bacterial isolates has proven its value to collect relevant information for strain characterization as well as tracing the origin of the contamination by linking the food isolate with the patient's isolate with high resolution. However, the isolation of a bacterial pathogen from food matrices is often time-consuming and not always successful. Therefore, we aimed to improve outbreak investigation by developing a method that can be implemented in reference laboratories to characterize the pathogen in the food vehicle without its prior isolation and link it back to human cases. We tested and validated a shotgun metagenomics approach by spiking food pathogens in specific food matrices using the Shiga toxin-producing Escherichia coli (STEC) as a case study. Different DNA extraction kits and enrichment procedures were investigated to obtain the most practical workflow. We demonstrated the feasibility of shotgun metagenomics to obtain the same information as in ISO/TS 13136:2012 and WGS of the isolate in parallel by inferring the genome of the contaminant and characterizing it in a shorter timeframe. This was achieved in food samples containing different E. coli strains, including a combination of different STEC strains. For the first time, we also managed to link individual strains from a food product to isolates from human cases, demonstrating the power of shotgun metagenomics for rapid outbreak investigation and source tracking.

Strain-Level Metagenomic Data Analysis of Enriched In Vitro and In Silico Spiked Food Samples: Paving the Way towards a Culture-Free Foodborne Outbreak Investigation Using STEC as a Case Study.

Culture-independent diagnostics, such as metagenomic shotgun sequencing of food samples, could not only reduce the turnaround time of samples in an outbreak investigation, but also allow the detection of multi-species and multi-strain outbreaks. For successful foodborne outbreak investigation using a metagenomic approach, it is, however, necessary to bioinformatically separate the genomes of individual strains, including strains belonging to the same species, present in a microbial community, which has up until now not been demonstrated for this application. The current work shows the feasibility of strain-level metagenomics of enriched food matrix samples making use of data analysis tools that classify reads against a sequence database. It includes a brief comparison of two database-based read classification tools, Sigma and Sparse, using a mock community obtained by in vitro spiking minced meat with a Shiga toxin-producing Escherichia coli (STEC) isolate originating from a described outbreak. The more optimal tool Sigma was further evaluated using in silico simulated metagenomic data to explore the possibilities and limitations of this data analysis approach. The performed analysis allowed us to link the pathogenic strains from food samples to human isolates previously collected during the same outbreak, demonstrating that the metagenomic approach could be applied for the rapid source tracking of foodborne outbreaks. To our knowledge, this is the first study demonstrating a data analysis approach for detailed characterization and phylogenetic placement of multiple bacterial strains of one species from shotgun metagenomic WGS data of an enriched food sample.

The Benefits of Whole Genome Sequencing for Foodborne Outbreak Investigation from the Perspective of a National Reference Laboratory in a Smaller Country.

Gradually, conventional methods for foodborne pathogen typing are replaced by whole genome sequencing (WGS). Despite studies describing the overall benefits, National Reference Laboratories of smaller countries often show slower uptake of WGS, mainly because of significant investments required to generate and analyze data of a limited amount of samples. To facilitate this process and incite policy makers to support its implementation, a Shiga toxin-producing Escherichia coli (STEC) O157:H7 (stx1+, stx2+, eae+) outbreak (2012) and a STEC O157:H7 (stx2+, eae+) outbreak (2013) were retrospectively analyzed using WGS and compared with their conventional investigations. The corresponding results were obtained, with WGS delivering even more information, e.g., on virulence and antimicrobial resistance genotypes. Besides a universal, all-in-one workflow with less hands-on-time (five versus seven actual working days for WGS versus conventional), WGS-based cgMLST-typing demonstrated increased resolution. This enabled an accurate cluster definition, which remained unsolved for the 2013 outbreak, partly due to scarce epidemiological linking with the suspect source. Moreover, it allowed detecting two and one earlier circulating STEC O157:H7 (stx1+, stx2+, eae+) and STEC O157:H7 (stx2+, eae+) strains as closely related to the 2012 and 2013 outbreaks, respectively, which might have further directed epidemiological investigation initially. Although some bottlenecks concerning centralized data-sharing, sampling strategies, and perceived costs should be considered, we delivered a proof-of-concept that even in smaller countries, WGS offers benefits for outbreak investigation, if a sufficient budget is available to ensure its implementation in surveillance. Indeed, applying a database with background isolates is critical in interpreting isolate relationships to outbreaks, and leveraging the true benefit of WGS in outbreak investigation and/or prevention.

NAuRA: Genomic Tool to Identify Staphylococcal Enterotoxins in Staphylococcus aureus Strains Responsible for FoodBorne Outbreaks.

Food contamination by staphylococcal enterotoxins (SEs) is responsible for many food poisoning outbreaks (FPOs) each year, and they represent the third leading cause of FPOs in Europe. SEs constitute a protein family with 27 proteins. However, enzyme immunoassays can only detect directly in food the five classical SEs (SEA-SEE). Thus, molecular characterization methods of strains found in food are now used for FPO investigations. Here, we describe the development and implementation of a genomic analysis tool called NAuRA (Nice automatic Research of alleles) that can detect the presence of 27 SEs genes in just one analysis- and create a database of allelic data and protein variants for harmonizing analyses. This tool uses genome assembly data and the 27 protein sequences of SEs. To include the different divergence levels between SE-coding genes, parameters of coverage and identity were generated from 10,000 simulations and a dataset of 244 assembled genomes from strains responsible for outbreaks in Europe as well as the RefSeq reference database. Based on phylogenetic inference performed using maximum-likelihood on the core genomes of the strains in this collection, we demonstrated that strains responsible for FPOs are distributed throughout the phylogenetic tree. Moreover, 71 toxin profiles were obtained using the NAuRA pipeline and these profiles do not follow the evolutionary history of strains. This study presents a pioneering method to investigate strains isolated from food at the genomic level and to analyze the diversity of all 27 SE-coding genes together.

Strategy for the identification of micro-organisms producing food and feed products: Bacteria producing food enzymes as study case.

Recent European regulations require safety assessments of food enzymes (FE) before their commercialization. FE are mainly produced by micro-organisms, whose viable strains nor associated DNA can be present in the final products. Currently, no strategy targeting such impurities exists in enforcement laboratories. Therefore, a generic strategy of first line screening was developed to detect and identify, through PCR amplification and sequencing of the 16S-rRNA gene, the potential presence of FE producing bacteria in FE preparations. First, the specificity was verified using all microbial species reported to produce FE. Second, an in-house database, with 16S reference sequences from bacteria producing FE, was constructed for their fast identification through blast analysis. Third, the sensitivity was assessed on a spiked FE preparation. Finally, the applicability was verified using commercial FE preparations. Using straightforward PCR amplifications, Sanger sequencing and blast analysis, the proposed strategy was demonstrated to be convenient for implementation in enforcement laboratories.

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).

Detection and discrimination of five E. coli pathotypes using a combinatory SYBR® Green qPCR screening system.

A detection and discrimination system for five Escherichia coli pathotypes, based on a combination of 13 SYBR® Green qPCR, has been developed, i.e., combinatory SYBR® Green qPCR screening system for pathogenic E. coli (CoSYPS Path E. coli). It allows the discrimination on isolates and the screening of potential presence in food of the following pathotypes of E. coli: shigatoxigenic (STEC) (including enterohemorrhagic (EHEC)), enteropathogenic (EPEC), enteroaggregative (EAggEC), enteroaggregative shigatoxigenic (EAggSTEC), and enteroinvasive (EIEC) E. coli. The SYBR® Green qPCR assays target the uidA, ipaH, eae, aggR, aaiC, stx1, and stx2 genes. uidA controls for E. coli presence and all the other genes are specific targets of E. coli pathotypes. For each gene, two primer pairs have been designed to guarantee a sufficient detection even in case of deletion or polymorphisms in the target gene. Moreover, all the qPCR have been designed to be run together in a single analytical PCR plate. This study includes the primer pairs' design, in silico and in situ selectivity, sensitivity, repeatability, and reproducibility evaluation of the 13 SYBR® Green qPCR assays. Each target displayed a selectivity of 100%. The limit of detection of the 13 assays is between 1 and 10 genomic copies. Their repeatability and reproducibility comply with the European requirements. As a preliminary feasibility study on food, the CoSYPS Path E. coli system was subsequently evaluated on four food matrices artificially contaminated with pathogenic E. coli. It allowed the detection of an initial contamination level as low as 2 to 7 cfu of STEC/25 g of food matrix after 24 h of enrichment.

Food-Borne Outbreak Investigation and Molecular Typing: High Diversity of Staphylococcus aureus Strains and Importance of Toxin Detection.

Staphylococcus aureus is an important aetiological agent of food intoxications in the European Union as it can cause gastro-enteritis through the production of various staphylococcal enterotoxins (SEs) in foods. Reported enterotoxin dose levels causing food-borne illness are scarce and varying. Three food poisoning outbreaks due to enterotoxin-producing S. aureus strains which occurred in 2013 in Belgium are described. The outbreaks occurred in an elderly home, at a barbecue event and in a kindergarten and involved 28, 18, and six cases, respectively. Various food leftovers contained coagulase positive staphylococci (CPS). Low levels of staphylococcal enterotoxins ranging between 0.015 ng/g and 0.019 ng/g for enterotoxin A (SEA), and corresponding to 0.132 ng/g for SEC were quantified in the food leftovers for two of the reported outbreaks. Molecular typing of human and food isolates using pulsed-field gel electrophoresis (PFGE) and enterotoxin gene typing, confirmed the link between patients and the suspected foodstuffs. This also demonstrated the high diversity of CPS isolates both in the cases and in healthy persons carrying enterotoxin genes encoding emetic SEs for which no detection methods currently exist. For one outbreak, the investigation pointed out to the food handler who transmitted the outbreak strain to the food. Tools to improve staphylococcal food poisoning (SFP) investigations are presented.

Evaluation of detection methods for non-O157 Shiga toxin-producing Escherichia coli from food.

Shiga toxin-producing Escherichia coli (STEC) remains a major foodborne pathogen of concern across the globe. Rapid detection and isolation of this pathogen is of great importance for public health reasons. In this study the detection and isolation of four non-O157 STEC strains (O26, O103, O111, O145) from different artificially contaminated matrices, namely ground (minced) beef, cattle carcass swab, lettuce mix and sprouted soy beans, were evaluated. Low amounts of STEC were used (0.25-1.40 cfu/g) to spike the samples. All samples were enriched in parallel in Buffered Peptone Water (BPW) and Brila broth. After enrichment, detection was performed using real-time PCR (qPCR), and isolation using two chromogenic agar media, CHROMagar™ STEC and ChromID™ EHEC. Inoculation on the agar media was performed either directly after enrichment or after the use of an acid treatment procedure. Furthermore, the use of this procedure was also tested on naturally contaminated food products, using 150 stx-positive samples. Although the qPCR Cycle Threshold (Ct) values were lower after enrichment in Brila broth, no significant differences in recovery were observed between both enrichment broths. Both agar media were equally suitable for the isolation of STEC, although a significantly higher recovery was obtained when using both agar media in parallel. For samples with a Ct value above 25, an acid treatment step prior to isolation ensured a significant improvement in the recovery of STEC due to the reduction in background microbiota. This acid treatment procedure proved especially useful for the isolation of STEC from sprouted soy bean samples.