Next generation quantitative microbiological risk assessment: Refinement of the cold smoked salmon-related listeriosis risk model by integrating genomic data

Abstract

Recent developments in genome sequencing open new opportunities for explaining the intraspecific variability of phenotypes (e.g. virulence, growth behavior). Successful association between WGS-data and specific phenotypes is thought to contribute to better predicting microbial behaviors. Implementing this information in hazard identification, exposure assessment, and hazard characterization processes will refine quantitative microbial risk assessments (QMRA) models. The aim of this study was to explore the refinements in QMRA studies when considering phenogenotype associations for the hazard properties, particularly related to the growth ability at low temperature (minimal growth temperature, Tmin) and the virulence. The used QMRA-model was previously developed for the assessment of the number of listeriosis cases associated to cold-smoked salmon in France. The global prevalence in the existing model was replaced by the specific prevalence for each genotypic subgroup (clonal complex - CC) in Europe. In order to describe the variability of Listeria monocytogenes’ growth characteristics more accurately, two different distributions of Tmin were implemented. For risk characterization, three different groups of virulence were considered according to the CCs. Each group was associated with a specific dose-response model. The new QMRA model showed that CCs contributing the most in consumer exposure were not those that contributed the most to listeriosis cases. The most prevailing CCs led to few listeriosis cases, whereas uncommon high virulent strains were responsible for the majority of predicted cases. Similarly, the less prevailing group of strains with high Tmin was approximately two times less implicated when considering human listeriosis in comparison to food contamination. Considering genotypic data in QMRA opens the way for the establishment of risk based measures specific to distinct sub-groups of L. monocytogenes.