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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Coleman, P and Tamplin, ML and Phillips, J and Marmer, B, Influence of agitation, inoculum density, pH, and strain on the growth parameters of Escherichia coli O157:H7 - relevance to risk assessment, International Journal of Food Microbiology, 83, (2) pp. 147-160. ISSN 0168-1605 (2003) [Refereed Article]
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 2×2×3 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°C. Kinetic data were modeled using simple linear regression and the Baranyi model. Both model forms provided good statistical fit to the data (adjusted r2>0.95). Significant effects of agitation and initial population density were identified at 10°C but not at 19 or 37°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°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. © 2002 Elsevier Science B.V. All rights reserved.
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