Jan. 1, 2016 - Dec. 31, 2017Award Number
Martin Wiedmann, Ph.D
Effective control of foodborne disease-causing microbes (“pathogens”) requires science-based validation of interventions and control strategies. For example, it is important to show that a given antimicrobial treatment can reduce bacterial numbers with a certain target efficiency, regardless of the specific genetic type of organism and regardless of the conditions under which an organism was grown prior to treatment. This is important, as it has been shown that Salmonella exposed to dry environments can be >100 times more resistant to some treatment (e.g., heat) than Salmonella grown in the presence of high levels of water. This project will assemble a collection of diverse microbes that are appropriate for validation of pathogen interventions in the produce industry, and will evaluate these organisms to determine whether and how exposure to different environmental conditions will affect the ability of these organisms to survive stressful conditions and control strategies. The resulting data, along with the bacterial collection developed as part of this project, will facilitate more reliable identification of effective control strategies that can reduce the risk of foodborne illnesses and pathogen contamination.
Studies evaluating produce-relevant pathogen interventions and growth and survival of pathogens in produce are essential to (i) develop improved pathogen control strategies, and (ii) allow for accurate and industry relevant risk assessments. Typically these types of studies are conducted using multiple pathogen strains, which may be used separately or in cocktails (mixtures of multiple distinct pathogen strains) (Scott et al., 2005). While it has been well established that different strains and/or genetic lineages of a pathogens may differ in their ability to survive and grow under different stress conditions, the physiological state of bacterial cells and the conditions under which bacteria are grown also have a considerable impact on the ability of foodborne pathogens to survive produce-relevant interventions and to grow and survive in produce. We specifically hypothesize that pre-growth conditions have a significantly greater effect on subsequent stress survival and stress response than genetic diversity within produce relevant pathogens, including Salmonella, Listeria monocytogenes, and Shiga toxin-producing E. coli (STEC). To test this hypothesis, we propose to evaluate pathogen strains exposed to different produce relevant stress conditions for their ability to (i) survive different interventions used in produce, and (ii) grow on different relevant produce types. Pathogens targeted will include Salmonella, STEC, and L. monocytogenes as well as non-pathogenic Listeria spp. and other surrogate, indicator, and index organisms (e.g., Enterococcus faecium [Kopit et al., 2014]; Enterococcus faecalis [Kim et al., 2012]). A key step for this project will be to assemble a collection of Salmonella, L. monocytogenes, STEC, and relevant surrogate, indicator, and index organisms representing national and international strain diversity associated with produce. This strain collection will be made available to the industry, government, and researchers, facilitating future studies on pathogen interventions and control strategies in produce. In addition, the data generated with the strains in this collection will improve the ability of investigators to select appropriate strains and growth conditions for future studies. In particular, the data created will provide guidance on the relative importance of either testing different strains or testing strains grown under different conditions prior to exposure to a given intervention or control strategy. These data are important as there are only few studies that have directly compared the relative impact of strain diversity and pre-growth conditions on the phenotypic response of pathogens to produce-relevant stress conditions.
The development of a well-characterized produce-specific pathogen strain collection, along with relevant data on the effect of genetic diversity and growth condition on produce-relevant phenotypes will provide an essential resource that will allow for more rapid and scientifically well justified validation studies in the produce industry, facilitating compliance with food safety regulations that emphasize control strategies that have strong scientific support.