Stochastic Single Cell Modeling of Biofilm Formation and Inactivation by Sanitizers of Salmonella and Listeria monocytogenes and their Impacts on Food Safety

Abstract

Studies have shown that cross contamination/recontamination during food processing is one of the main factors contributing to the occurrence of foodborne disease outbreaks (FBDs). Cross contamination/recontamination is associated with persistence of Salmonella and Listeria monocytogenes in food processing environments, wich is remarkable linked to the ability of these microorganisms to form biofilms. The persistence phenomenon can also be attributed to an increased tolerance to sanitizers or due to a greater adhesion ability to abiotic surfaces by a given clone (strain) of a pathogen. Despite the advances in understanding the impact of variability between strains, for example, in the ability to form biofilms, it is known that this approach has several limitations, of which the fact that the responses are considered for the microbial population as a whole and that differences among individual cells are not taken into account. The importance of understanding the behaviour and variability between individual cells precisely emerges with the emergence of quantitative risk assessment. It is understood that approaches to understand the variability among individual cells with respect to their ability to form biofilms and to resist to sanitizing agents are of utmost importance for improving the efficiency of cleaning procedures. Thus, this project aims to: i) to use stochastic single cell modeling to study the resistance of Salmonella and L. monocytogenes to different sanitizers ii) to use stochastic single cell modeling to assess the resistance to sanitizes of sub-populations of one specific strain of each pathogen and iii) to use stochastic single cell modeling to study biofilm formation by Salmonella and L. monocytogenes.