The objectives of the FLUOPATH project are 1) to find new biomarkers (promoeters that induce the expression of genes of interest) coupled to a fluorescent biosensor allowing to acquire new knowledge in bacterial cell physiology related to the impact of technological disturbances inducing stresses. The study will be focused on the growth, survival and virulence of two pathogens in dairy products (milk, diluted cheese and if possible solid cheese) and 2) to use this knowledge combined with the knowledge present in the scientific literature to improve the models for predicting the microbiological risk in dairy products. The pathogens considered will be L. monocytogenes and B. cereus. The matrices considered will be liquid milk as well as model diluted and undiluted cheese (gelified matrix). New models based on the use at the scale of the single cell and the whole population of biomarkers will be developed to predict growth, resistance and virulence (invasive capacity for L. monocytogenes and entry into sporulation and toxin production for B. cereus) to stress while taking into account cellular variability. A precise quantification of the impact of stressful industrial conditions will be carried out on bacterial responses at the cellular level: probability of single cell / whole poulation growth, survival, toxin production, spore formation, invasive capacity. The challenge is to design and validate in food matrices bacterial biomarkers of phenotypes of interest in risk assessment in order to incorporate the intensity of biomarker response into exposure assessment models.

Food spoilage leads to significant wastes and losses, and is an important economic issue in food industry. In the case of meat, a large part of spoilage is the consequence of bacterial growth and subsequent metabolic activities causing organoleptic spoilage of the final product (defects in texture, color, odor, or aspect), leading finally to products that are lost because they do not fit the quality standards. In addition, meat production chain requires energy, water and cost consuming operations (i.e. animal breeding, slaughtering, and transformation and storage which are usually performed at low temperature). Therefore meat product spoilage that appears at the end of the process or during shelf life affects the whole production chain performances as well as the sustainability label of the meat sector. The objective of the project is to reduce food losses by predicting, early in the production process, the onset of bacterial spoilage during storage in order to propose decision-support tools for directing process. Pork and poultry meat, the two main meats consumed in France will be studied. The economic impact of losses of these products will be assessed. Dynamics of bacterial communities will be monitored during processing steps (from primary cuts to end products at use-by-date and beyond) and various descriptors of spoilage will be measured. The natural variability between batches and that associated with production processes will be considered. Data will be used to identify accurate spoilage markers and to compute innovative mathematical models for predicting spoilage occurrence as a function of the initial composition of the microbiota (diversity and abundance) and some abiotic parameters (storage temperature, modified atmosphere packaging). The models will be validated on meat products, including the economic aspect in order to propose decision-support tools for the food producers.