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Summary: Despite the constant development of novel thermal and nonthermal technologies, knowledge on the mechanisms of microbial inactivation is still very limited. Technologies such as high pressure, ultraviolet light, pulsed light, ozone, power ultrasound and cold plasma (advanced oxidation processes) have shown promising results for inactivation of micro‐organisms. The efficacy of inactivation is greatly enhanced by combination of conventional (thermal) with nonthermal, or nonthermal with another nonthermal technique. The key advantages offered by nonthermal processes in combination with sublethal mild temperature (<60°C) can inactivate micro‐organisms synergistically. Microbial cells, when subjected to environmental stress, can be either injured or killed. In some cases, cells are believed to be inactivated, but may only be sublethally injured leading to their recovery or, if the injury is lethal, to cell death. It is of major concern when micro‐organisms adapt to stress during processing. If the cells adapt to a certain stress, it is associated with enhanced protection against other subsequent stresses. One of the most striking problems during inactivation of micro‐organisms is spores. They are the most resistant form of microbial cells and relatively difficult to inactivate by common inactivation techniques, including heat sterilization, radiation, oxidizing agents and various chemicals. Various novel nonthermal processing technologies, alone or in combination, have shown potential for vegetative cells and spores inactivation. Predictive microbiology can be used to focus on the quantitative description of the microbial behaviour in food products, for a given set of environmental conditions. [ABSTRACT FROM AUTHOR]

Aims: When subjected to dynamic temperatures surpassing the expected maximum growth temperature, Escherichia coli K12 MG1655 shows disturbed growth curves. These irregular population dynamics were explained by considering two subpopulations, i.e. a thermoresistant and a thermosensitive one ( Van Derlinden et al. 2010a ). In this paper, the influence of the initial cell concentration on the subpopulations' dynamics is evaluated. Methods and Results: Experiments were performed in a bioreactor with the temperature increasing from 42 to 65·2°C (1 and 4°C h−1) with varying initial cell concentrations [6, 12 and 18 ln(CFU ml−1)]. When started from the highest cell concentration, the population was characterized by a higher overall maximum growth temperature and a higher inactivation temperature. For all experimental set-ups, resistant cells were still growing at the final temperature of 65·2°C. Conclusions: The initial cell concentration had no effect on temperature resistance. The increase in temperature resistance of the sensitive subpopulation was because of the change of the physiological state to the stationary phase. Significance and Impact of the Study: A higher initial cell concentration leads to higher heat stress adaptation when cultures reach a maximum cell concentration. The observed growth at a temperature of 65·2°C is very important for food safety and the temperature treatment of micro-organisms. [ABSTRACT FROM AUTHOR]

Aims: The objective of this study was to investigate whether bacterial cells could develop resistance (as a part of their adaptation strategy) to high-pressure CO2 (HPCD) inactivation. Methods and Results: Alternating cycles of exposure to pressurized CO2 (10·5 MPa, 35°C, 400 min−1, 70% working volume ratio during 10 min) and re-growth of the surviving subpopulation were used to investigate possible increases in the resistance of Escherichia coli and Listeria monocytogenes to HPCD. The results show an increased resistance of both pathogens tested after seven cycles of inactivation. Increase in the resistance after 15 cycles resulted in a difference of 2·4 log CFU ml−1 in log N0/Ni when parental (N0) and treated cultures (Ni) of E. coli and L. monocytogenes were compared. Conclusions: Current findings indicate the ability of micro-organisms to adapt to HPCD preservation technology. Significance and Impact of the Study: The occurrence of HPCD-resistant micro-organisms could pose a new hazard to the safety and stability of HPCD-processed foods. [ABSTRACT FROM AUTHOR]

Aims: Non-sigmoid growth curves of Escherichia coli obtained at constant temperatures near the maximum growth temperature ( Tmax) were previously explained by the coexistence of two subpopulations, i.e. a stress-sensitive and a stress-resistant subpopulation. Mathematical simulations with a heterogeneous model support this hypothesis for static experiments at 45°C. In this article, the behaviour of E. coli, when subjected to a linearly increasing temperature crossing Tmax, is studied. Methods and Results: Subpopulation dynamics are studied by culturing E. coli K12 MG1655 in brain heart infusion broth in a bioreactor. The slowly increasing temperature (°C h−1) starting from 42°C results in growth up to 60°C, a temperature significantly higher than the known Tmax. Given some additional presumptions, mathematical simulations with the heterogeneous model can describe the dynamic experiments rather well. Conclusions: This study further confirms the existence of a stress-resistant subpopulation and reveals the unexpected growth of E. coli at temperatures significantly higher than Tmax. Significance and Impact of the Study: The growth of the small stress-resistant subpopulation at unexpectedly high temperatures asks for a revision of currently applied models in food safety and food quality strategies. [ABSTRACT FROM AUTHOR]

Aims: Previous work showed that the exponential phase of Escherichia coli K12 MG1655, grown in Brain Heart Infusion broth at temperatures close to its maximum growth temperature, is disturbed. Based on plate count data, microscopic images and literature, the existence of a heat-resistant subpopulation was hypothesized. Here, this hypothesis is mathematically explored via a heterogeneous model. Methods and Results: A heat-sensitive and a heat-resistant subpopulation are considered. A large fraction of the population is inactivated, while the remaining smaller fraction is able to resist (or adapt to) the inimical temperature and grows. A heterogeneous model that encloses a growth model (resistant population) and an inactivation model (sensitive population) is used to describe the global population dynamics. Most experimental data can be predicted when taking parameter uncertainty via Monte Carlo simulation into account. Conclusions: The heterogeneous model accurately describes disturbed growth curves at superoptimal temperatures, except for high initial cell densities. Significance and Impact of the Study: This study strengthens the hypothesis of the existence of a (small) heat-resistant subpopulation in typical inoculum cultures of E. coli K12 MG1655. [ABSTRACT FROM AUTHOR]

Aims: To evaluate a novel secondary model structure ( Int J Food Microbiol 2008; 128: 67) that describes the effect of medium structure on the maximum specific growth rate ( μmax) of Salmonella Typhimurium on the growth of S. Typhimurium, Listeria innocua, Lactococcus lactis and Listeria monocytogenes. Methods and Results: In the present study, the novel secondary model is validated for S. Typhimurium in more realistic media, namely, pasteurized milk and a cheese mimicking medium. The predictions were accurate. Next, the secondary model structure was evaluated in a two step and a global regression procedure on literature data. On the one hand, the growth of two other micro-organisms, namely L. innocua and L. lactis, in monoculture for varying gelatine concentrations was tested and on the other hand the growth rate of L. monocytogenes was fitted in a broth of which the viscosity was altered with polyvinylpyrrolidone. The model was able to describe the effect of increasing gelatine concentration or viscosity accurately. Conclusions: The proposed secondary model structure is able to describe the effect of gelatine concentration on the μmax of the micro-organisms tested in this study. Significance and Impact of the Study: In predictive microbiology, much attention has been paid to the effect of food structure on the μmax of bacteria. However, to the authors’ knowledge, a lack of secondary models still exists to describe this effect. Although the proposed model is empirical, the model parameters have clear biological meaning. The predictive power of the model to describe the effect of food structure is clearly illustrated. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to extract information on cell number and colony volume dynamics of Salmonella Typhimurium colonies. Methods and Results: Both cell number and colony volume of Salmonella Typhimurium in gelatin were monitored during the exponential and the stationary phase with varying pH and water activity, by plate counts and microscopic image analysis respectively. The exponential growth rates of cell numbers and colony volumes were correlated. The exponential growth rate of cell numbers was estimated based on this correlation and a secondary model that describes the effect of pH and water activity on the growth rate of the colony volumes. During the stationary phase, the cell number was constant, while colony volume increased, thus indicating the formation of a dead fraction. Models were developed to describe the living and dead population. Conclusions: By comparing colony volumes and cell numbers, the formation of dead fraction can be noticed from the beginning of the stationary phase, which indicates that the stationary phase is a dynamic – including both cell death and cell growth – rather than a static phase. Significance and Impact of the Study: This study was the first to investigate the proportion of living and dead bacteria within a stationary colony quantitatively. [ABSTRACT FROM AUTHOR]

Aims: The dynamics of Escherichia coli near the maximum temperature for growth in a rich medium are analysed. The effects of temperature history, medium composition and physiological state of the inoculum are evaluated. Methods and Results: Kinetics of E. coli K12 MG1655 is studied in ‘brain–heart infusion’ broth in a temperature controlled environment. Based on viable counts, ‘smooth’ growth curves are observed at 40, 41, 42 and 43°C. The exponential growth phase at 44 and 45°C is interrupted. At 46°C, a period of exponential growth is followed by inactivation. Neither the physiological state of the inoculum nor medium enrichment alters the dynamics, whilst temperature pre-adaptation or chemical chaperones restore regular cell growth and division (‘smooth’ exponential growth). Conclusions: Atypical, nonexponential growth at 44, 45 and 46°C seems related to protein destabilization and can (partly) be restored by an appropriate medium design (i.e. addition of chemical chaperones) or temperature history (i.e. selection of a more resistant subpopulation). Significance and Impact of the Study: This study indicates that the maximum temperature for growth is dependent on the temperature history and the chemical environment. These observations and the nonexponential kinetics have important implications for the development of predictive models for food safety and quality. [ABSTRACT FROM AUTHOR]

Aims:  In previous studies the microbial kinetics of Escherichia coli K12 have been evaluated under static and dynamic conditions ( Valdramidis et al. 2005, 2006 ). An acquired microbial thermotolerance following heating rates lower than 0·82°C min−1 for the studied micro-organism was observed. Quantification of this induced physiological phenomenon and incorporation, as a model building block, in a general microbial inactivation model is the main outcome of this work. Methods and Results:  The microbial inactivation rate observed ( kobs) under time-varying temperature conditions is studied and expressed as a function of the heating rate (d T/ d t). Hereto, a model building block related to the microbial physiology ( kphys) under stress conditions is developed. Evaluation of the performance of the developed mathematical approach depicts that physiological adaptation is an essential issue to be considered when modelling microbial inactivation. Conclusions:  Consideration, at a mathematical level, of microbial responses resulting in physiological adaptations contribute to the reliable quantification of the safety risks during food processing. Significance and Impact of the Study:  By taking into account the physiological adaptation, the microbiological evolution during heat processing can be accurately assessed, and overly conservative or fail dangerous food processing designs can be avoided. [ABSTRACT FROM AUTHOR]

Aims: This paper studies and models the effect of the amplitude of a sudden temperature upshift Δ T on the adaptation period of Escherichia coli, in terms of the work to be done by the cells during the subsequent lag phase (i.e., the product of growth rate μmax and lag phase duration λ). Methods and Results: Experimental data are obtained from bioreactor experiments with E. coli K12 MG1655. At a predetermined time instant during the exponential growth phase, a sudden temperature upshift is applied (no other environmental changes take place). The length of the (possibly) induced lag phase and the specific growth rate after the shift are quantified with the growth model of Baranyi and Roberts (Int J Food Microbiol 23, 1994, 277 ). Different models to describe the evolution of the product λ × μmax as a function of the amplitude of the temperature shift are statistically compared. Conclusions: The evolution of λ × μmax is influenced by the amplitude of the temperature shift Δ T and by the normal physiological temperature range. As some cut-off is observed, the linear model with translation is preferred to describe this evolution. Significance and Impact of the Study: This work contributes to the characterization of microbial lag phenomena, in this case for E. coli K12 MG1655, in view of accurate predictive model building. [ABSTRACT FROM AUTHOR]

Aims: The variability in growth between individual Listeria monocytogenes cells was investigated on liver pâté and cooked ham. These results were compared to Monte Carlo simulations based on data collected previously in broths (Francois et al., submitted for publication). Methods and Results: Single cells were isolated by a dilution protocol and inoculated on 15 g samples of liver pâté and cooked ham, pasteurized in the packaging. Of each product, 250 samples were inoculated, of which 50 samples were analysed for L. monocytogenes on each analysis day. Results were compared to simulations, based on distributions that describe the variability of the individual cell lag phases and generation times of L. monocytogenes cultivated in broths. Based on the same simulation techniques, the variability effect was investigated for different inoculum levels (10, 100, 1000 and 10 000 cells). It was demonstrated that the expected variability of the outgrowth of L. monocytogenes in a challenge test is very high for low inoculum levels. Conclusions: The variability in growth characteristics observed between different single L. monocytogenes cells on foods is very large. The simulations based on the previously collected optical density data in broths, could be confirmed by foods inoculated with single L. monocytogenes cells. Significance and Impact of the Study: The large variability between different individual L. monocytogenes cells has serious consequences for the experimental design of a challenge test. One thousand cells per portion are necessary in order to reduce the variability to acceptable levels and quantify the behaviour of the pathogen consistently with a reasonable number of challenge tests. [ABSTRACT FROM AUTHOR]

Aims: The effect of temperature (2–30°C), pH (4·8–7·4) and water activity (0·946–0·995) on the relationship between optical density (OD) at 600 nm and the plate count (CFU ml−1) was investigated for Listeria monocytogenes. Methods and Results: Calibration curves, relating OD with plate counts, were collected by measuring the OD of consecutive one-half dilution series, before determining the cell density by classic plate count methods. The calibration curves were observed to be shifting in a parallel way, with increasing stress levels. Especially pH influenced the curve in a great extent, while the other variables were showing more synergetic effects. The reason for the shift was investigated by a microscopic viability test, showing a viability decrease with increasing stress levels, causing the shift of the calibration curve. In a last step a model was made describing the effect of environmental factors on the calibration curve, with different data transformations being tested. A polynomial equation was fitted to the data, taking into account a set of constraints to incorporate microbiological knowledge in the black box model. Hence, illogical interpolation results and overfitting of the data could be avoided. Conclusions: Different stress factors are affecting the relationship between the OD and the cell count of L. monocytogenes by lowering the cell viability. These effects could be modelled using a constrained polynomial model. Significance and Impact of the Study: The observed phenomena are important when calculating growth parameters, like growth rate and lag phase, based on OD data. [ABSTRACT FROM AUTHOR]