S56 Whole Genome Sequence Approaches as Applied to Salmonella: De Novo Tools for Use in Predictive Microbiology

Wednesday, August 3, 2016: 10:30 AM-12:00 PM
228-229 (America's Center - St. Louis)
Primary Contact: Lawrence Goodridge
Organizers: Lawrence Goodridge and Michelle Danyluk
Convenors: Lawrence Goodridge and Michelle Danyluk
Salmonella enterica is a major cause of global foodborne gastroenteritis, causing millions of cases annually. In the European Union, this pathogen is the leading cause of foodborne outbreaks. In the United States, it is responsible for the most hospitalizations and deaths of any foodborne pathogen.  There are more than 2500 serotypes of S. enterica, which inhabit a wide range of foods and ecological niches, including low water activity foods that typically do not seem to support the survival of other foodborne pathogens. The diverse nature of S. enterica serotypes and its presence in many different foods, makes the use of predictive modelling approaches imperative to define the risk of Salmonella contamination of a given food.  Whole genomic-based sequencing and gene expression analysis offer an emerging and unparalleled approach to study the emergence and persistence of foodborne pathogens. For example, selectively screening whole microbial genome sequences, and assessing gene expression via epigenetic methods allows for identification of  genes with specific functionalities, which can be used to identify potential food safety risks present in a single bacterial isolate or a food sample. The antibiotic resistance profile or virulence potential of a specific bacterium can be investigated by comparing its genome sequence to reference databases containing known resistance genes and virulence factors. Similar approaches have been described to evaluate the persistence of bacteria in food products and resistance to cleaning procedures commonly used in food production settings. Using the example of S. enterica, this symposium will highlight the application of whole genome sequencing and gene expression approaches as tools for development of predictive models of Salmonella virulence, survival, persistence and growth in foods and the food production environment.


10:30 AM
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