DSFAS: Towards the Biogeography of Foodborne Pathogen Genomic Diversity

Our proposal aims to integrate AI and ML with open-source molecular data to define the spatial and temporal distributions of expansive genomic diversity of foodborne pathogens. The data-analytic workflows that we buildwill have innovative technological applications for food and agricultural industries to support food safety, nutrition, and health. Objective 1:Establish systematic pipeline to elucidate the biogeography of genomic diversity of foodborne pathogens.Objective 2:Benchmark metagenomic tools for foodborne pathogen detection in simulated microbial communities.These independent, yet interrelated objectives will test ouroverarching hypothesisthat environmental stressors along the agricultural continuum to consumers impose selective pressures that drive adaptive responses of diverse foodborne pathogens -C. jejuni,C. sakazakii, andL. monocytogenes- and the emergence of key genes and pathways (e.g., persistence, antimicrobial resistance, virulence) that hold potential for informing novel applications to promote food safety.