CNIEL
1 Projects, page 1 of 1
assignment_turned_in ProjectFrom 2024Partners:SECALIM, CNIEL, ADRIA Développement, AERIAL, LABORATOIRE UNIVERSITAIRE DE BIODIVERSITE ET ECOLOGIE MICROBIENNE +2 partnersSECALIM,CNIEL,ADRIA Développement,AERIAL,LABORATOIRE UNIVERSITAIRE DE BIODIVERSITE ET ECOLOGIE MICROBIENNE,PAM,Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement - Centre de Recherche PACA - Sécurité et Qualité des Produits d'Origine VégétaleFunder: French National Research Agency (ANR) Project Code: ANR-23-CE21-0008Funder Contribution: 900,461 EURThe 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.
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