Jean-Christophe Augustin

Mathematical modelling of the growth rate and lag time for Listeria monocytogenes

Growth data for Listeria monocytogenes were collected from the literature and a global model built with existing secondary models describing independently the effects of environmental factors on the growth rate and lag time was based on these data. The growth rates calculated with this model were consistent with the published ones but the fit was poor near the limits of growth of the micro-organism. The model was also less accurate to describe the lag time. It seems then that reliable predictions of the growth rate of L. monocytogenes could be obtained in a wide range of growth conditions, but models should take into account interactions between environmental factors. Furthermore, it is necessary to better model the lag phase duration and particularly to model the effect of the history of the inoculum on the subsequent lag time.

Influence of Stress on Individual Lag Time Distributions of Listeria monocytogenes

ABSTRACT The effects of nine common food industry stresses on the times to the turbidity (Td) distribution of Listeria monocytogenes were determined. It was established that the main source of the variability of Td for stressed cells was the variability of individual lag times. The distributions of Td revealed that there was a noticeable difference in response to the stresses encountered by the L. monocytogenes cells. The applied stresses led to significant changes of the shape, the mean, and the variance of the distributions. The variance of Td of wells inoculated with single cells issued from a culture in the exponential growth phase was multiplied by at least 6 and up to 355 for wells inoculated with stressed cells. These results suggest stress-induced variability may be important in determining the reliability of predictive microbiological models.

Growth rate and growth probability of Listeria monocytogenes in dairy, meat and seafood products in suboptimal conditions.

Aims:  To evaluate the performances of models predicting the growth rate or the growth probability of Listeria monocytogenes in food.

Significance of inoculum size in the lag time of Listeria monocytogenes.

ABSTRACT The lag time of Listeria monocytogenes growing under suboptimal conditions (low nutrient concentrations, pH 6, and 6.5°C) was extended when the inoculum was severely stressed by starvation and the inoculum size was very small. Predictive microbiology should deal with bacterial stress and stochastic approaches to improve its value for the agro-food industry.

Estimation of temperature dependent growth rate and lag time of Listeria monocytogenes by optical density measurements.

An automated turbidimetric system, Bioscreen C, was used to monitor growth of ten strains of Listeria monocytogenes at different temperatures. Several methods for estimation of maximum specific growth rate (mu(max)) and lag time (lag) from turbidimetric data were compared to values estimated from viable count data. By using a calibration factor, reliable estimations of mu(max) could be obtained from turbidimetric measurements. On the other hand, accurate estimations of lag required some viable count data.

Applicability of biological time temperature integrators as quality and safety indicators for meat products.

The objective of this study was to evaluate (eO), a biological time temperature integrator (TTI) as a quality and safety indicator for ground beef packed under modified atmosphere and spiced cooked chicken slices packed under modified atmosphere. Storage trials and challenge tests were thus performed on several batches of the studied food to monitor and model the behavior of Listeria monocytogenes, Salmonella, Staphylococcus aureus and the indigenous food flora. Then, two different prototypes of the TTI (eO) were set and manufactured according to the studied products shelf lives. The TTI evolution with time at static and dynamic temperatures was monitored and modeled. Finally, exposure assessment models were set and used under several realistic storage profiles to assess the distributions of the concentration of the indigenous food flora and the distributions of the increase in the pathogens populations obtained at the end of the product shelf life or at the end point of the TTI, taking into account the TTIs batch variability. Results showed that in case of poor storage conditions, TTI can reduce the consumer exposure to altered or hazardous foods.

A model describing the effect of temperature history on lag time for Listeria monocytogenes

A model was built to describe the influence of the temperature and the duration of pre-incubation on the lag time for regrowth of Listeria monocytogenes at low temperature. This model is consistent with the usual procedure used to calculate lag times of cultures growing under fluctuating temperatures. It also describes the effect of prolonged starvation conditions on the regrowth lag time and takes into account the influence of the physiological state of inocula in predictive models.

Design of challenge testing experiments to assess the variability of Listeria monocytogenes growth in foods.

The assessment of the evolution of micro-organisms naturally contaminating food must take into account the variability of biological factors, food characteristics and storage conditions. A research project involving eight French laboratories was conducted to quantify the variability of growth parameters of Listeria monocytogenes obtained by challenge testing in five food products. The residual variability corresponded to a coefficient of variation (CV) of approximately 20% for the growth rate (μ(max)) and 130% for the parameter K = μ(max) × lag. The between-batch and between-manufacturer variability of μ(max) was very dependent on the food tested and mean CV of approximately 20 and 35% were observed for these two sources of variability, respectively. The initial physiological state variability led to a CV of 100% for the parameter K. It appeared that repeating a limited number of three challenge tests with three different batches (or manufacturers) and with different initial physiological states seems often necessary and adequate to accurately assess the variability of the behavior of L. monocytogenes in a specific food produced by a given manufacturer (or for a more general food designation).

Validation of a stochastic modelling approach for Listeria monocytogenes growth in refrigerated foods

A stochastic modelling approach was developed to describe the distribution of Listeria monocytogenes contamination in foods throughout their shelf life. This model was designed to include the main sources of variability leading to a scattering of natural contaminations observed in food portions: the variability of the initial contamination, the variability of the biological parameters such as cardinal values and growth parameters, the variability of individual cell behaviours, the variability of pH and water activity of food as well as portion size, and the variability of storage temperatures. Simulated distributions of contamination were compared to observed distributions obtained on 5 day-old and 11 day-old cheese curd surfaces artificially contaminated with between 10 and 80 stressed cells and stored at 14°C, to a distribution observed in cold smoked salmon artificially contaminated with approximately 13 stressed cells and stored at 8°C, and to contaminations observed in naturally contaminated batches of smoked salmon processed by 10 manufacturers and stored for 10 days a 4°C and then for 20 days at 8°C. The variability of simulated contaminations was close to that observed for artificially and naturally contaminated foods leading to simulated statistical distributions properly describing the observed distributions. This model seems relevant to take into consideration the natural variability of processes governing the microbial behaviour in foods and is an effective approach to assess, for instance, the probability to exceed a critical threshold during the storage of foods like the limit of 100 CFU/g in the case of L. monocytogenes.

Influence of Stress on Single-Cell Lag Time and Growth Probability for Listeria monocytogenes in Half Fraser Broth

ABSTRACT The impacts of 12 common food industry stresses on the single-cell growth probability and single-cell lag time distribution of Listeria monocytogenes were determined in half Fraser broth, the primary enrichment broth of the International Organization for Standardization detection method. First, it was determined that the ability of a cell to multiply in half Fraser broth is conditioned by its history (the probability for a cell to multiply can be decreased to 0.05), meaning that, depending on the stress in question, the risk of false-negative samples can be very high. Second, it was established that when cells are injured, the single-cell lag times increase in mean and in variability and that this increase represents a true risk of not reaching the detection threshold of the method in the enrichment broth. No relationship was observed between the impact on single-cell lag times and that on growth probabilities. These results emphasize the importance of taking into account the physiological state of the cells when evaluating the performance of methods to detect pathogens in food.