<OL> <LI> Model preharvest interventions for E. coli O157:H7 in commercial feedlot cattle; <LI> Investigate dietary factors affecting fecal shedding of E. coli O157:H7 in cattle; <LI> Evaluate the effects of probiotics on fecal prevalence of E. coli O157:H7 in feedlot cattle and determine the potential mode of action; <LI> Evaluate house flies as potential source of E. coli O157:H7 to cattle; <LI> Identify genetic elements in E. coli O157:H7 strains that are associated with fecal shedding of E. coli O157:H7 at high concentrations in cattle
Non-Technical Summary: Although the food supply in the US is one of the safest in the world, foodborne illnesses do occur and frequently are associated with foods derived from animals. Escherichia coli O157:H7, a food borne pathogen, is an important public health concern. Cattle are natural reservoirs of this organism and shed the bacteria in their feces, which then serve as a major source of contamination of food and water for human infection. Improvement in detection and quantification of E. coli O157:H7 in feces and further understanding of the ecology of this organism in cattle could potentially lead to mitigation strategies to reduce pathogen prevalence and pathogen load in cattle. Control strategies aimed at reducing the prevalence and concentration of E. coli O157:H7 in cattle feces, thus reducing the overall number of bacteria entering both the food and environmental pathways, may be the most effective approach for reducing the overall risk of human infections <P> Approach: Mathematical modeling is an effective method to assess impacts of multiple interventions in a complex system. In order to demonstrate the potential, conditional effects of individual and multiple interventions for E. coli O157:H7 as well as the relative value of interventions, we propose to stochastically model interventions within the framework of other pre-harvest and harvest interventions. Stochastic models will be used to account for both the variability in parameters and efficacy of interventions as well as uncertainty regarding their true values and effects. For the second objective, we propose to test diets that would supply substrates or products to the hindgut, and in so doing, alter the microbial ecology to effect changes in the growth and survival of E. coli O157:H7. We will do this initially in cattle enrolled in nutritional studies or in an in vitro batch-culture fermentation system with fecal microbial inoculum to test the effects of diets and dietary ingredients on E. coli O157:H7. Once specific component or ingredient is identified, we will test in cattle that are prescreened and confirmed as positive for fecal shedding of E. coli O157:H7 and assigned to dietary treatments. We will evaluate the ability of one or more commercially available probiotics to reduce the prevalence of E. coli O157:H7 and determine the potential mode of action using in vitro procedures. Cattle confirmed as culture positive for E. coli O157:H7 will be randomly allocated to group with no added probiotic (control) or to the treatment group which will receive a daily dose of a probiotic. Study cattle will be monitored daily and fecal samples will be obtained at appropriate intervals. We will evaluate the anti-E. coli O157:H7 activities of probiotics in vitro using two models, pure culture direct inhibition and ruminal or fecal microbial fermentations with added probiotics. We have observed very large numbers of house flies (HF) infesting steam-flaked corn (SFC) feed in feedlot facilities. This likely represents a hotspot for contamination of cattle feed by E. coli O157:H7 from HF. The SFC will be sampled immediately as it is produced and after HF access and cultured E. coli O157:H7. In addition, HF will be collected from SFC and cultured for E. coli O157:H7. This experiment will be replicated three times and at different SFC producing facilities. In the fourth objective, strains that are shed at high concentrations will be compared to strains that are shed at low concentrations. Preliminary genomic DNA microarray analysis on three high and three low shedder strains did not reveal differences. Therefore, PCR and sequencing a larger portion or the whole genes, and studying the gene expressions at RNA level from high and low shedder strains are necessary to identify genetic markers for super shedding. We plan to work on both DNA and RNA levels to cover potential differences that may only exist in gene expressions, and use 3 high and 3 low shedding strains for the initial study. Gene expression levels between high and low shedder strains will be calculated to identify genes that may linked to bacterial shedding.