Molecular characterization of Yersinia enterocolitica strains to evaluate virulence associated genes.

INTRODUCTION: Yersinia enterocolitica (Ye) species is divided into 6 biotypes (BT), 1A, 1B, 2, 3, 4, 5 classified based on biochemical reactions and about 70 serotypes, classified based on the structure of the lipopolysaccharide O-antigen. The BT1A is considered non-pathogenic, while the BT 1B-5 are considered pathogenic. METHODS: Evaluate the distribution of eleven chromosomal and plasmid virulence genes, ail, ystA, ystB, myfA, hreP, fes, fepD, ymoA, sat, virF and yadA, in 87 Ye strains isolated from food, animals and humans, using two SYBR Green real-time PCR platforms. RESULTS: The main results showed the presence of the ail and ystA genes in all the pathogenic bioserotypes analyzed. The ystB, on the other hand, was identified in all non-pathogenic strains biotype 1A. The target fes, fepD, sat and hreP were found in both pathogenic biotypes and in BT1A strains. The myfA gene was found in all pathogenic biotype and in some Ye BT1A strains. The virF and yadA plasmid genes were mainly detected in bioserotype 4/O:3 and 2/O:9, while ymoA was identified in all strains. CONCLUSIONS: The two molecular platforms could be used to better define some specific molecular targets for the characterization and rapid detection of Ye in different sources which important implications for food safety and animal and human health.

IRIDA-ARIES Genomics, a key player in the One Health surveillance of diseases caused by infectious agents in Italy.

Pathogen genomics is transforming surveillance of infectious diseases, deepening our understanding of evolution and diffusion of etiological agents, host-pathogen interactions and antimicrobial resistance. This discipline is playing an important role in the development of One Health Surveillance with public health experts of various disciplines integrating methods applied to pathogen research, monitoring, management and prevention of outbreaks. Especially with the notion that foodborne diseases may not be transmitted by food only, the ARIES Genomics project aimed to deliver an Information System for the collection of genomic and epidemiological data to enable genomics-based surveillance of infectious epidemics, foodborne outbreaks and diseases at the animal-human interface. Keeping in mind that the users of the system comprised persons with expertise in a wide variety of domains, the system was expected to be used with a low learning curve directly by the persons target of the analyses' results, keeping the information exchange chains as short as possible. As a result, the IRIDA-ARIES platform (https://irida.iss.it/) provides an intuitive web-based interface for multisectoral data collection and bioinformatic analyses. In practice, the user creates a sample and uploads the Next-generation sequencing reads, then an analysis pipeline is launched automatically performing a series of typing and clustering operations fueling the information flow. Instances of IRIDA-ARIES host the Italian national surveillance system for infections by Listeria monocytogenes (Lm) and the surveillance system for infections by Shigatoxin-producing Escherichia coli (STEC). As of today, the platform does not provide tools to manage epidemiological investigations but serves as an instrument of aggregation for risk monitoring, capable of triggering alarms on possible critical situations that might go unnoticed otherwise.

One Health surveillance-A cross-sectoral detection, characterization, and notification of foodborne pathogens.

Introduction: Several Proficiency Test (PT) or External Quality Assessment (EQA) schemes are currently available for assessing the ability of laboratories to detect and characterize enteropathogenic bacteria, but they are usually targeting one sector, covering either public health, food safety or animal health. In addition to sector-specific PTs/EQAs for detection, cross-sectoral panels would be useful for assessment of the capacity to detect and characterize foodborne pathogens in a One Health (OH) perspective and further improving food safety and interpretation of cross-sectoral surveillance data. The aims of the study were to assess the cross-sectoral capability of European public health, animal health and food safety laboratories to detect, characterize and notify findings of the foodborne pathogens Campylobacter spp., Salmonella spp. and Yersinia enterocolitica, and to develop recommendations for future cross-sectoral PTs and EQAs within OH. The PT/EQA scheme developed within this study consisted of a test panel of five samples, designed to represent a theoretical outbreak scenario. Methods: A total of 15 laboratories from animal health, public health and food safety sectors were enrolled in eight countries: Denmark, France, Italy, the Netherlands, Poland, Spain, Sweden, and the United Kingdom. The laboratories analyzed the samples according to the methods used in the laboratory and reported the target organisms at species level, and if applicable, serovar for Salmonella and bioserotype for Yersinia. Results: All 15 laboratories analyzed the samples for Salmonella, 13 for Campylobacter and 11 for Yersinia. Analytical errors were predominately false negative results. One sample (S. Stockholm and Y. enterocolitica O:3/BT4) with lower concentrations of target organisms was especially challenging, resulting in six out of seven false negative results. These findings were associated with laboratories using smaller sample sizes and not using enrichment methods. Detection of Salmonella was most commonly mandatory to notify within the three sectors in the eight countries participating in the pilot whereas findings of Campylobacter and Y. enterocolitica were notifiable from human samples, but less commonly from animal and food samples. Discussion: The results of the pilot PT/EQA conducted in this study confirmed the possibility to apply a cross-sectoral approach for assessment of the joint OH capacity to detect and characterize foodborne pathogens.

Shifting national surveillance of Shigella infections toward geno-serotyping by the development of a tailored Luminex assay and NGS workflow.

The phylogenetically closely related Shigella species and enteroinvasive Escherichia coli (EIEC) are responsible for millions of episodes of bacterial dysenteriae worldwide. Given its distinct epidemiology and public health relevance, only Shigellae are subject to mandatory reporting and follow-up by public health authorities. However, many clinical laboratories struggle to differentiate non-EIEC, EIEC, and Shigella in their current workflows, leading to inaccuracies in surveillance and rising numbers of misidentified E. coli samples at the National Reference Centre (NRC). In this paper, we describe two novel tools to enhance Shigella surveillance. First, we developed a low-cost Luminex-based multiplex assay combining five genetic markers for species identification with 11 markers for serotype prediction for S. sonnei and S. flexneri isolates. Using a test panel of 254 clinical samples, this assay has a sensitivity of 100% in differentiation of EIEC/Shigella pathotype from non-EIEC strains, and 68.7% success rate in distinction of Shigella and EIEC. A novel, and particularly successful marker was a Shigella-specific deletion in the spermidine acetyltransferase gene speG, reflecting its metabolic decay. For Shigella serotype prediction, the multiplex assay scored a sensitivity and specificity of 96.6% and 98.4%, respectively. All discrepancies were analyzed with whole-genome sequencing and shown to be related to causative mutations (stop codons, indels, and promoter mutations) in glycosyltransferase genes. This observation spurred the development of an in silico workflow which extracts the Shigella serotype from Next-Generation Sequencing (NGS) data, taking into account gene functionality. Both tools will be implemented in the workflow of the NRC, and will play a major role in the shift from phenotypic to genotyping-based surveillance of shigellosis in Belgium.