Title: Interactive effects of temperature, pH, and water activity on the growth kinetics of Shiga-toxin producing Escherichia coli O104:H4 Authors
|Wu, Vivian -|
|Harshavardhan, Thippareddi -|
Submitted to: Journal of Food Protection
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 15, 2013
Publication Date: May 1, 2014
Repository URL: http://handle.nal.usda.gov/10113/58846
Citation: Juneja, V.K., Mukhopadhyay, S., Ukuku, D.O., Hwang, C., Wu, V.C., Harshavardhan, T. 2014. Interactive effects of temperature, pH, and water activity on the growth kinetics of Shiga-toxin producing Escherichia coli O104:H4. Journal of Food Protection. 77(5):706-712 doi:10.431/0362-028XJFP-13-387. Interpretive Summary: Shiga-toxin producing Escherichia coli is a continuing concern to the food industry. This emphasizes the need to determine its growth potential in foods to provide an adequate degree of protection against growth of this pathogen. We developed a mathematical model for predicting the growth of this pathogen in foods as affected by temperature, pH and water activity. This model can be used to predict the growth of the pathogen in response to the interaction of the three variables assessed in this study. This information will be of immediate use to consumers and to the food industry and regulatory agencies to guard against the pathogen in foods.
Technical Abstract: The risk of non-O157 Escherichia coli strains has become a growing public health concern. Several studies characterized the behavior of E. coli O157:H7; however, no reports are available on the influence of multiple factors on E. coli O104:H4. This study examined the effects and interactions of temperature (7-46C), pH (4.5-8.5) and water activity (aw 0.95-0.99) on the growth kinetics of E. coli O104:H4 and developed predictive models to estimate its growth potential in foods. Growth kinetics studies for each of the 23 variable combinations from a central composite design were performed. Growth data were used to obtain the lag-phase duration (LPD), exponential growth rate (EGR), generation time (GT) and maximum population density (MPD). These growth parameters as a function of temperature, pH and aw as controlling factors were analyzed to generate second-order-response surface models. The results indicate that the observed MPD was dependent on the pH, aw and temperature of the growth medium. Increasing temperature resulted in a concomitant decrease in LPD. The regression analysis suggests that temperature, pH and aw significantly affect the LPD, EGR, GT and MPD of E. coli O104:H4. A comparison between the observed values and those of E. coli O157:H7 predictions obtained using the USDA-Pathogen Modeling Program indicated that E. coli O104:H4 grows faster than E. coli O157:H7. The developed models were validated with alfalfa and broccoli sprouts. These models will provide risk assessors and food safety managers a rapid means of estimating the likelihood that the pathogen, if present, would grow in response to the interaction of the three variables assessed.