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Project
Quantification of the Heterogeneous Heat Stress Response of E. coli
Nowadays, the tendency towards milder processing conditions in food industry in order to retain the desirable sensory and nutrient characteristics can lead to adapted pathogens and spoilage micro-organisms that resist the processing conditions presumed to be lethal. Microorganisms can adapt to stress by different mechanisms such as production of protecting factors or increased heterogeneity by phenotypic means or by mutation. The specific aim of this PhD is to study and quantify the influence of dynamic temperature conditions on the heat stress adaptation of Escherichia coli</> K12. </>
Preliminary research showed that subjecting E. coli</> to linear increasing temperatures resulted in a heterogeneous response, i.e., the population is divided in a temperature sensitive subpopulation that inactivates at the maximum growth temperature, and a heat resistant subpopulation that could withstand extreme high temperatures and grow until the maximum cell concentration of the resistant subpopulationis attained.</>
In this context, this PhD specifically focused on the effect of both (1) the initial cell concentration and (2) the heating rate on heat stress adaptation, and (3) the dynamics of the adapted resistant subpopulation. A subpopulation-type model was applied to analyse the experimental data. The research results can be summarized as follows.</>
Generally, the initial cell concentration did not influence the microbial dynamics, except in conditions where an intermediate stationaryphase was attained. In these starvation conditions, the cells were moreresistant to the heat stress which was reflected in an increased inactivation temperature.</>
A lower heating rate resulted in a lower inactivation rate, i.e., inactivation is more spread in time, which indicatesincreased heterogeneity with part of the population that is more adapted to the high temperature conditions. The decimal reduction time as function of the heating rate is efficiently described by a tertiary model. </>
The dynamics of the resistant cells were identified by the technique of selective plating on a salt medium. Combination of these kinetics with the previously observed kinetics of the whole E. coli</> populationunder dynamic conditions enabled to further define the heterogeneous subpopulation type model yielding a final set of equations that accuratelydescribes the subpopulations and the overall population. </></>
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This PhD is a first step towards the efficient and accurate modeling of microbial dynamics under time-varying environmental conditions. This research meets the current need for quantitative approaches of the stress response mechanisms in response to the trend towards milder processing techniques.</>
Preliminary research showed that subjecting E. coli</> to linear increasing temperatures resulted in a heterogeneous response, i.e., the population is divided in a temperature sensitive subpopulation that inactivates at the maximum growth temperature, and a heat resistant subpopulation that could withstand extreme high temperatures and grow until the maximum cell concentration of the resistant subpopulationis attained.</>
In this context, this PhD specifically focused on the effect of both (1) the initial cell concentration and (2) the heating rate on heat stress adaptation, and (3) the dynamics of the adapted resistant subpopulation. A subpopulation-type model was applied to analyse the experimental data. The research results can be summarized as follows.</>
Generally, the initial cell concentration did not influence the microbial dynamics, except in conditions where an intermediate stationaryphase was attained. In these starvation conditions, the cells were moreresistant to the heat stress which was reflected in an increased inactivation temperature.</>
A lower heating rate resulted in a lower inactivation rate, i.e., inactivation is more spread in time, which indicatesincreased heterogeneity with part of the population that is more adapted to the high temperature conditions. The decimal reduction time as function of the heating rate is efficiently described by a tertiary model. </>
The dynamics of the resistant cells were identified by the technique of selective plating on a salt medium. Combination of these kinetics with the previously observed kinetics of the whole E. coli</> populationunder dynamic conditions enabled to further define the heterogeneous subpopulation type model yielding a final set of equations that accuratelydescribes the subpopulations and the overall population. </></>
</>
This PhD is a first step towards the efficient and accurate modeling of microbial dynamics under time-varying environmental conditions. This research meets the current need for quantitative approaches of the stress response mechanisms in response to the trend towards milder processing techniques.</>
Date:27 Oct 2008 → 15 Mar 2013
Keywords:Microbial Dynamics
Disciplines:Catalysis and reacting systems engineering, Chemical product design and formulation, General chemical and biochemical engineering, Process engineering, Separation and membrane technologies, Transport phenomena, Other (bio)chemical engineering
Project type:PhD project