An official website of the United States government.
A multidisciplinary approach is proposed for developing science-based microbial food safety criteria. Current regulations for foodborne pathogens are commonly based on historical taxonomic identifications that may not correlate to the ability of an organism to cause human disease. This project will identify distinct genetic criteria that define the specific human pathogenic potentials of clonal bacterial groups focusing on Listeria monocytogenes. <OL> <LI> Assemble a collection of animal, human, and environmental (where applicable) bacterial isolates to be characterized by molecular subtyping methods. <LI> Characterize representative Listeria monocytogenes isolates for virulence using tissue culture cytopathogenicity. <LI> Identify clonal types of L. monocytogenes isolates by screening for genome-level divergence as reflected by various typing strategies.
NON-TECHNICAL SUMMARY: Foodborne diseases cause an estimated 76 million illnesses and 5000 deaths annually in the US. To protect consumers from these diseases it is important to understand exactly which bacteria can cause human disease. This project examines bacteria from humans and animals with bacterial diseases and from contaminated foods by DNA fingerprinting methods to define which bacterial types cause human foodborne disease.
<P>
APPROACH: <BR> Objective 1: Human, food, and animal isolates of L. monocytogenes will be collected in collaboration with the NYS Veterinary Diagnostic Laboratory, the Dept. of Agriculture and Markets and the Dept. of Health. All isolates will be characterized by DNA subtyping methods which may include Southern blotting, ribotyping and sequencing of selected virulence genes. <BR><BR>Objective 2: Selected subgroups differing in human and animal host specificities will be used to infect appropriate tissue culture cell lines to determine differences in their pathogenic potentials. <BR><BR>Objective 3: Bacterial subtype distribution among human, food, and animal isolates will be statistically analyzed to identify specific subgroups linked to human infections.