History repeats itself: consumption of a local traditional roast pork meat recipe leads to Salmonella ser. Give cases in Greece.

INTRODUCTION: An outbreak of gastroenteritis due to Salmonella Give, a very rarely identified serotype in human isolates in Greece, occurred in participants of a religious festival in a rural area of southern Greece, in September 2022. The objectives of this study were to describe the outbreak in terms of epidemiology, identify the vehicle of transmission of the foodborne pathogen and recommend prevention measures. METHODS: The outbreak was linked to the consumption of a local traditional recipe of roasted pork meat served by a street food vendor. In 2018, the same food item, served in a restaurant in the same region, was implicated in another S. Give outbreak. RESULTS: Outbreak investigations revealed that outbreak-associated isolates, of food and human origin, belonged to the same S. Give strain. Significant deficiencies regarding food safety practices were identified. CONCLUSION: Technical knowledge about pathogen transmission paths is important in order for both food handlers and consumers to follow hygiene and sanitary measures, mainly in cases of mass gatherings, where large quantities of food are prepared, handled, cooked and served. Efficient official supervision, mainly during summer festivals, is required in order to avoid recurrence of foodborne infections by different combinations of pathogens/food commodities.

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.

Use of metagenomic microbial source tracking to investigate the source of a foodborne outbreak of cryptosporidiosis.

Cryptosporidium is a protozoan parasite of global public health importance that causes gastroenteritis in a variety of vertebrate hosts, with many human outbreaks reported yearly, often from ingestion of contaminated water or food. Despite the major public health implications, little is typically known about sources of contamination of disease outbreaks caused by Cryptosporidium. Here, we study a national foodborne outbreak resulted from infection with Cryptosporidium parvum via romaine lettuce, with the main goal to trace the source of the parasite. To do so, we combined traditional outbreak investigation methods with molecular detection and characterization methods (i.e. PCR based typing, amplicon and shotgun sequencing) of romaine lettuce samples collected at the same farm from which the contaminated food was produced. Using 18S rRNA typing, we detected C. parvum in two out of three lettuce samples, which was supported by detections in the metagenome analysis. Microbial source tracking analysis of the lettuce samples suggested sewage water as a likely source of the contamination, albeit with some uncertainty. In addition, the high degree of overlap in bacterial species content with a public human gut microbial database corroborated the source tracking results. The combination of traditional and molecular based methods applied here is a promising tool for future source tracking investigations of food- and waterborne outbreaks of Cryptosporidium spp. and can help to control and mitigate contamination risks.

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.