La Mellefont

Modelling the effects of temperature, water activity, pH and lactic acid concentration on the growth rate of Escherichia coli

An extended square root-type model describing Escherichia coli growth rate was developed as a function of temperature (7.63-47.43 degrees C), water activity (0.951-0.999, adjusted with NaCl), pH (4.02-8.28) and lactic acid concentration (0-500 mM). The new model, based on 236 growth rate data, combines and extends previously published square root-type models and incorporates terms for upper and lower limiting temperatures, upper and lower limiting pH, minimum inhibitory concentrations of dissociated and undissociated lactic acid and lower limiting water activity. A term to describe upper limiting water activity was developed but could not be fitted to the E. coli data set because of the difficulty of generating data in the super-optimal water activity range (i.e. >0.998). All data used to generate the model are presented. The model provides an excellent description of the experimental data.

Predicting growth rates and growth boundary of Listeria monocytogenes - An international validation study with focus on processed and ready-to-eat meat and seafood.

The performance of six predictive models for Listeria monocytogenes was evaluated using 1014 growth responses of the pathogen in meat, seafood, poultry and dairy products. The performance of the growth models was closely related to their complexity i.e. the number of environmental parameters they take into account. The most complex model included the effect of nine environmental parameters and it performed better than the other less complex models both for prediction of maximum specific growth rates (micro(max) values) and for the growth boundary of L. monocytogenes. For this model bias and accuracy factors for growth rate predictions were 1.0 and 1.5, respectively, and 89% of the growth/no-growth responses were correctly predicted. The performance of three other models, including the effect of five to seven environmental parameters, was considered acceptable with bias factors of 1.2 to 1.3. These models all included the effect of acetic acid/diacetate and lactic acid, one of the models also included the effect of CO(2) and nitrite but none of these models included the effect of smoke components. Less complex models that did not include the effect of acetic acid/diacetate and lactic acid were unable to accurately predict growth responses of L. monocytogenes in the wide range of food evaluated in the present study. When complexity of L. monocytogenes growth models matches the complexity of foods of interest, i.e. the number of hurdles to microbial growth, then predicted growth responses of the pathogen can be accurate. The successfully validated models are useful for assessment and management of L. monocytogenes in processed and ready-to-eat (RTE) foods.

The effect of abrupt shifts in temperature on the lag phase duration of Escherichia coli and Klebsiella oxytoca

The effect of temperature of incubation on lag times of two gram-negative foodborne bacteria was investigated. Bacteria were instantaneously transferred between temperatures within and beyond the normal physiological temperature range (NPTR). Abrupt temperature shifts induced lag phases, but the degree of the response was dependent on the direction and magnitude of the shift. Temperature downshifts induced larger relative lag times (RLT; the ratio of lag time to generation time), than equivalent upshifts. The hypothesis of Robinson et al. [Int. J. Food Microbiol. 44 (1998) 83] that lag time can be understood in terms of the amount of work to be done to adjust to new environmental conditions and the rate at which that work is done was supported. Deviation of the reported proportionality between lag time and generation time was observed when late-exponential phase cells were subjected to abrupt temperature shifts from beyond the normal physiological range.

The effect of abrupt osmotic shifts on the lag phase duration of foodborne bacteria

The effects of osmotic environment and inoculum history on lag times were examined. Abrupt osmotic shifts of cultures were found to induce lag phases in a variety of foodborne bacteria. Relative lag times (RLT; the ratio of lag time to generation time) were used to differentiate the effects of the shift from those of the outgrowth environment. In general, osmotic downshifts induced larger RLTs than equivalent upshifts. An observed reduction in RLT at very low a(w), however, was unexpected. For an osmotic downshift, differences were observed in the RLT response of the Gram-negative and -positive strains tested. RLTs were usually extended for Gram-negative organisms as conditions became less favourable for growth. In comparison, RLT remained relatively unaffected for Gram-positive organisms. The observations reported in this study demonstrate that lag time can be understood in terms of the amount of work to be done to adjust to new environmental conditions and the rate at which that work is done, and are consistent with known strategies for osmoregulation employed by the various organisms studied.

Performance evaluation of a model describing the effects of temperature, water activity, pH and lactic acid concentration on the growth of Escherichia coli.

A square root-type model for Escherichia coli growth in response to temperature, water activity, pH and lactic acid was developed by Ross et al. [Int. J. Food Microbiol. (2002).]. Predicted generation times from the model were compared to the literature data using bias and accuracy factors, graphical comparisons and plots of residuals for data obtained from both liquid growth media and foods. The model predicted well for 1025 growth rate estimates reported in the literature after poor quality or unrepresentative data (n=215) was excluded, with a bias factor of 0.92, and an accuracy factor of 1.29. In a detailed comparison to two other predictive modes for E. coli growth, Pathogen Modeling Program (PMP) and Food MicroModel (FMM), the new model generally performed better. The new model consistently gave better predictions than the other models at generation times </=5 h. Inclusion of the lactic acid term in the model is proposed to account for the consistently good performance of the model for comparisons to growth in meat, a parameter that is not explicitly included in the other models considered in the comparisons.

The effect of abrupt osmotic shifts on the lag phase duration of physiologically distinct populations of Salmonella typhimurium

Relative lag time (RLT), i.e. lag time divided by generation time, was used to characterise the lag phase response of exponential and stationary phase Salmonella typhimurium subjected to NaCl-mediated hyperosmotic shifts. Abrupt hyperosmotic shifts induced lag phases. The RLT, however, varied with the physiological history of the inoculum and the magnitude of the shift. Turbidimetric data showed that exponential phase cells had larger RLTs (up to approximately 8 units) than stationary phase cells (up to 2-4 units). Inocula containing exponential and stationary phase cells mixed in known proportions gave intermediate results. For viable count data, there was little difference in RLT between exponential and stationary phase cells. The RLT response determined turbidimetrically was reproducible for exponential phase cells, but less so for stationary phase cells. It is suggested that there may be a lower limit for resolution of RLT, in the range 0-2 units, and that this may account for the lack of reproducibility in RLTs of stationary phase cells. It is hypothesised that stationary phase cells have enhanced resistance to osmotic stress and are able to exploit new growth environments at low a(w) more rapidly than exponential phase cells, resulting in shorter lag phases. However, the data indicate that turbidimetry may not accurately describe the lag phase response of exponential phase cells subjected to large osmotic shifts. Viable count data is required to investigate this hypothesis further.

The influence of non-lethal temperature on the rate of inactivation of vegetative bacteria in inimical environments may be independent of bacterial species

The influence of non-lethal temperature on the survival of two species of food-borne bacteria under growth-preventing pH and water activity conditions was investigated. Specifically, inactivation rates of four strains of Escherichia coli and three strains of Listeria monocytogenes were determined in culture broth adjusted to pH 3.5 and water activity 0.90, to prevent growth of both species, and for temperatures in the range 5-45 degrees C at 5 degrees C intervals. Sixty-three inactivation rates were obtained, plotted on Arrhenius co-ordinates, and lines of best-fit determined by simple linear regression. Differences in the mean inactivation rate of each species at a given temperature were not significant (p < 0.05) with the exception of the rates at 25 degrees C. The inactivation rate responses of both species were comparable to those reported by McQuestin et al. (Appl. Environ. Microbiol., 75:6963-6972, 2009) for a variety of E. coli strains under a wide range of growth-preventing pH and water activity conditions. The results support the hypothesis that non-lethal temperature is a key factor governing the rate of inactivation of vegetative bacteria in foods when other hurdles prevent their growth and indicate that the temperature effect may also be independent of bacterial species.

Combined effect of chilling and desiccation on survival of Escherichia coli suggests a transient loss of culturability

Dry air carcass chilling regimes used in some Australian meat works, which not only rapidly reduce the temperature of the carcasses but also dry the meat surface initially, are reported to cause reductions in the number of Escherichia coli present on carcasses after processing. This study used a laboratory broth model system to systematically investigate the basis of such reductions by simulating chilling and desiccation profiles observed on carcasses separately and, finally, in combination. Observed growth was compared to the predictions generated by a strain-specific modification of a validated E. coli growth model (Mellefont et al., 2003; Performance evaluation of a model describing the effects of temperature, water activity, pH and lactic acid concentration on the growth of E. coli). Good agreement between observed and predicted growth was evident when chilling or desiccation profiles were simulated individually. However, when chilling and desiccation profiles were applied simultaneously the observed population kinetics deviated from those predicted by the model. An initial reduction in cell numbers, not predicted by the model, was observed followed by an anomalously rapid increase in population density before growth resumed at a rate expected for the conditions imposed. From our analysis of the kinetics of the population changes, we suggest that the initial decrease in cell numbers was unlikely due to cell death, because conditions were growth permissive. Considering all possible explanations from the observed population kinetics, we propose that a temporary loss of the ability to produce colonies on agar plates may occur. These results may explain reports of increases in E. coli numbers two to three days after commencement of chilling, compared to those observed after 16-24h, despite the imposition of growth-preventing temperatures.