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Int J Food Microbiol. 2003 Jun 15;83(2):147-60.

Influence of agitation, inoculum density, pH, and strain on the growth parameters of Escherichia coli O157:H7--relevance to risk assessment.

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USDA/Food Safety and Inspection Service, Office of Public Health and Science, Food Risk Assessment Center, 1400 Independence Ave., SW, Rm. 386 Aerospace Building, Washington, DC 20250-3700, USA.


Foods may differ in at least two key variables from broth culture systems typically used to measure growth kinetics of enteropathogens: initial population density of the pathogen and agitation of the culture. The present study used nine Escherichia coli O157:H7 strains isolated from beef and associated with human illness. Initial kinetic experiments with one E. coli O157:H7 strain in brain-heart infusion (BHI) broth at pH 5.5 were performed in a 2 x 2 x 3 factorial design, testing the effects of a low (ca. 1-10 colony-forming units [CFU]/ml) or high (ca. 1000 CFU/ml) initial population density, culture agitation or no culture agitation, and incubation temperatures of 10, 19, and 37 degrees C. Kinetic data were modeled using simple linear regression and the Baranyi model. Both model forms provided good statistical fit to the data (adjusted r(2)>0.95). Significant effects of agitation and initial population density were identified at 10 degrees C but not at 19 or 37 degrees C. Similar growth patterns were observed for two additional strains tested under the same experimental design. The lag, slope, and maximum population density (MPD) parameters were significantly different by treatment. Further tests were conducted in a 96-well microtiter plate system to determine the effect of initial population density and low pH (4.6-5.5) on the growth of E. coli O157:H7 strains in BHI at 10, 19, and 37 degrees C. Strain variability was more apparent at the boundary conditions of growth of low pH and low temperature. This study demonstrates the need for growth models that are specific to food products and environments for plausible extrapolation to risk assessment models.

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