Assessing Stress Adaptation And Associated Risks

Safety of food may be achieved using treatment factors that halt the growth of pathogens. The optimization of these treatments requires an understanding of the limits between conditions that support growth and those in which growth is not possible, also known as the growth-no-growth interface [96]. The growth-no-growth interface can be defined as the boundary at which the microbial growth rate is zero and the lag phase is infinite [97]. The behavior of foodborne pathogens at the growth-no-growth interface has been assessed using models that take into account combinations of temperature, pH, aw, and concentrations of chemical compounds [77,98-100]. These and other predictive and risk assessment models should consider the contribution of stress adaptation to the survivability and behavior of pathogens in food. The majority of models available to evaluate survival or inactivation of chemically stressed bacteria are based on primary models, which describe the fate of microbial populations as a function of time [96]. To develop reliable microbial inactivation models, researchers should consider the physiological state of the organism and the potential induction of stress-tolerance responses [97]. However, including stress adaptation in these models depends greatly on researchers' ability to monitor accurately and quantify the stress adaptation phenomenon experimentally.

Rapid and quantitative assessment of microbial adaptive response to a predefined stress remains a great challenge. Advances in this area would improve our understanding of how the microbial cell responds to multiple stresses, or its ability to exhibit multiple responses to a single stress, leading to cross protection. These techniques would also enable researchers to measure the response of microbial cells to a complex battery of stresses. Advances in genomic and proteomic research may bring the scientific community closer to this goal [20,33]. Although genome-wide microarray analysis enables researchers to identify genes expressed in response to stress, the technique does not distinguish between expressions leading to adaptation and those that are not directly related to this phenomenon. Fluorescence staining is a promising technique for rapidly assessing stress response. Instrumentation advances may enable researchers to monitor the effect of stress on membranes in real time with the use of fluorescent dyes. Reliable, quantitative measures of stress adaptation should facilitate the efforts to develop mathematical predictive models of stress-, adaptive-, and cross-protective responses. Change in these responses as a function of stress type and intensity, for example, would help predict the behavior of pathogens during food processing and storage, and their virulence in infected individuals.

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