A probabilistic modeling approach in thermal inactivation: estimation of postprocess Bacillus cereus spore prevalence and concentration

Mechanistic insights into the adaptive evolvability of spore heat resistance in Bacillus cereus sensu lato

Wet heat treatment is a commonly applied method in the food and medical industries for the inactivation of microorganisms, and bacterial spores in particular. While many studies have delved into the mechanisms underlying wet heat killing and spore resistance, little attention has so far been dedicated to the capacity of spore-forming bacteria to tune their resistance through adaptive evolution. Nevertheless, a recent study from our group revealed that a psychrotrophic strain of the Bacillus cereus sensu lato group (i.e. Bacillus weihenstephanensis LMG 18989) could readily and reproducibly evolve to acquire enhanced spore wet heat resistance without compromising its vegetative cell growth ability at low temperatures. In the current study, we demonstrate that another B. cereus strain (i.e. the mesophilic B. cereus sensu stricto ATCC 14579) can acquire significantly increased spore wet heat resistance as well, and we subjected both the previously and currently obtained mutants to whole genome sequencing. This revealed that five out of six mutants were affected in genes encoding regulators of the spore coat and exosporium pathway (i.e. spoIVFB, sigK and gerE), with three of them being affected in gerE. A synthetically constructed ATCC 14579 ΔgerE mutant likewise yielded spores with increased wet heat resistance, and incurred a compromised spore coat and exosporium. Further investigation revealed significantly increased spore DPA levels and core dehydration as the likely causes for the observed enhanced spore wet heat resistance. Interestingly, deletion of gerE in Bacillus subtilis 168 did not impose increased spore wet heat resistance, underscoring potentially different adaptive evolutionary paths in B. cereus and B. subtilis.

3-D stochastic modeling approach in thermal inactivation: estimation of thermal survival kinetics of Escherichia coli O157:H7 in a hamburger after exposure to desiccation stress

Desiccation tolerance of pathogenic bacteria is one strategy for survival in harsh environments, which has been studied extensively. However, the subsequent survival behavior of desiccation-stressed bacterial pathogens has not been clarified in detail. Herein, we demonstrated that the effect of desiccation stress on the thermotolerance of Escherichia coli O157:H7 in ground beef was limited, and its thermotolerance did not increase. E. coli O157:H7 was inoculated into a ground beef hamburger after exposure to desiccation stress. We combined a bacterial inactivation model with a heat transfer model to predict the survival kinetics of desiccation-stressed E. coli O157:H7 in a hamburger. The survival models were developed using the Weibull model for two-dimensional pouched thin beef patties (ca. 1 mm), ignoring the temperature gradient in the sample, and a three-dimensional thick beef patty (ca. 10 mm), considering the temperature gradient in the sample. The two-dimensional (2-D) and three-dimensional (3-D) models were subjected to stochastic variations of the estimated Weibull parameters obtained from 1,000 replicated bootstrapping based on isothermal experimental observations as uncertainties. Furthermore, the 3-D model incorporated temperature gradients in the sample calculated using the finite element method. The accuracies of both models were validated via experimental observations under non-isothermal conditions using 100 predictive simulations. The root mean squared errors in the log survival ratio of the 2-D and 3-D models for 100 simulations were 0.25-0.53 and 0.32-2.08, respectively, regardless of the desiccation stress duration (24 or 72 h). The developed approach will be useful for setting appropriate process control measures and quantitatively assessing food safety levels.IMPORTANCEAcquisition of desiccation stress tolerance in bacterial pathogens might increase thermotolerance as well and increase the risk of foodborne illnesses. If a desiccation-stressed pathogen enters a kneaded food product via cross-contamination from a food-contact surface and/or utensils, proper estimation of the internal temperature changes in the kneaded food during thermal processing is indispensable for predicting the survival kinetics of desiccation-stressed bacterial cells. Various survival kinetics prediction models that consider the uncertainty or variability of pathogenic bacteria during thermal processing have been developed. Furthermore, heat transfer processes in solid food can be estimated using finite element method software. The present study demonstrated that combining a heat transfer model with a bacterial inactivation model can predict the survival kinetics of desiccation-stressed bacteria in a ground meat sample, corresponding to the temperature gradient in a solid sample during thermal processing. Combining both modeling procedures would enable the estimation of appropriate bacterial survival kinetics in solid food.

Modeling strain variability in Campylobacter jejuni thermal inactivation by quantifying the number of strains required

There is a limited understanding of the survival responses of Campylobacter jejuni during thermal processing, which must be investigated for appropriate risk assessment and processing. Therefore, we aimed to elucidate the survival response of C. jejuni and develop a predictive model considering strain variability and uncertainty, which are important for quantitative microbial risk assessment (QMRA) or risk-based processing control measures. We employed the most probable curve (MPC) method to consider the uncertainty in cell concentrations. Further, the multivariate normal (MVN) distribution served as a model for strain variability in bacterial survival behavior. The prediction curves from the MVN successfully captured the parameter variability of the most probable curves of each strain. More than ten reference strains effectively described the strain variability in parameters using the MVN distribution. The findings indicated that, with sufficient strain data, the MVN could estimate the strain variability, including unknown strains. The multi-level model for strain variability can potentially become a specialized tool for QMRA and risk-based processing controls. The combined approach of MPC and MVN provides valuable insights into strain variability, emphasizing the importance of accounting for variability and uncertainty in predictive models for QMRA and risk-based processing control measures.

Spore Heat Resistance and Growth Ability at Refrigeration Temperatures of Bacillus spp. and Paenibacillus spp

In this study, spore heat resistance and growth ability at refrigeration temperatures of Bacillus spp. and Paenibacillus spp. were determined. The spore D_90°C of 67.6% (23 of 34 strains) of Bacillus and 73.9% (17 of 23 strains) of Paenibacillus was less than 15 min. The growth abilities of both genera were equivalent at 10°C. However, 71.1% (32 of 45 strains) of Paenibacillus and only 6.3% (3 of 48 strains) of Bacillus cereus group could grow at 4°C. Eight B. cereus strains formed spores with higher heat resistance compared to the other Bacillus strains assessed; however, they did not grow at tempreratures below 10°C. Conversely, four Paenibacillus strains formed spores with heat resistance equivalent to that of the eight B. cereus strains and grew at 6°C or lower. In particular, Paenibacillus sp. JCM13343 formed the highest heat-resistant spores (D_90°C = 136.1 min) and grew well at 4°C. These results indicate that Paenibacillus can grow in processed foods during refrigerated storage and has the potential to cause spoilage as well as Bacillus. Therefore, Paenibacillus should be considered as one of the targets for microbiological control in refrigerated processed foods.

The COM-Poisson Process for Stochastic Modeling of Osmotic Inactivation Dynamics of Listeria monocytogenes

Controlling harmful microorganisms, such as Listeria monocytogenes, can require reliable inactivation steps, including those providing conditions (e.g., using high salt content) in which the pathogen could be progressively inactivated. Exposure to osmotic stress could result, however, in variation in the number of survivors, which needs to be carefully considered through appropriate dispersion measures for its impact on intervention practices. Variation in the experimental observations is due to uncertainty and biological variability in the microbial response. The Poisson distribution is suitable for modeling the variation of equi-dispersed count data when the naturally occurring randomness in bacterial numbers it is assumed. However, violation of equi-dispersion is quite often evident, leading to over-dispersion, i.e., non-randomness. This article proposes a statistical modeling approach for describing variation in osmotic inactivation of L. monocytogenes Scott A at different initial cell levels. The change of survivors over inactivation time was described as an exponential function in both the Poisson and in the Conway-Maxwell Poisson (COM-Poisson) processes, with the latter dealing with over-dispersion through a dispersion parameter. This parameter was modeled to describe the occurrence of non-randomness in the population distribution, even the one emerging with the osmotic treatment. The results revealed that the contribution of randomness to the total variance was dominant only on the lower-count survivors, while at higher counts the non-randomness contribution to the variance was shown to increase the total variance above the Poisson distribution. When the inactivation model was compared with random numbers generated in computer simulation, a good concordance between the experimental and the modeled data was obtained in the COM-Poisson process.

Impact of shoulders on the calculus of heat sterilization treatments with different bacterial spores

To date, heat is still the most used technology in food preservation. The calculus of heat treatments is usually based on Bigelow observations i.e. treatment time is an exponential function of the heat treatment temperature. However, a number of researchers have reported deviations from linearity in heat inactivation curves that caused errors in the calculus. This research was designed to evaluate the variability of shoulder length among different sporulated species, the impact of treatment temperature on these shoulders and the relationship between the traditional D_T value and shoulder length. The heat inactivation kinetics of five bacterial spores of importance for the food industry was evaluated. B. weihenstephanensis and B. cereus did not show shoulders and D_T values calculated ranged from 0.99 to 0.23 and from 1.33 to 0.56 respectively at temperatures from 100 to 102.5 °C. On the other side B. subtilis, B. licheniformis and G. stearothermophilus showed shoulders of 1.75-0.42, 1.92-0.43 and 3.22-0.78 and D_T values of 1.52-0.32, 2.12-0.59 and 2.22-0.48 respectively in the range of temperatures tested. From the results obtained it was concluded that the presence and magnitude of shoulders depended on the bacterial spore species, the longest being those on the bacterial spores which showed greatest heat resistance. It has also been proved that shoulder lengths vary with treatment temperature in the same proportion of traditional D_T values, with the relationship Sl/D_T being constant. Thus, an equation which included the constant Sl/D_T was proposed.

Variability in microbial inactivation: From deterministic Bigelow model to probability distribution of single cell inactivation times

Phenotypic heterogeneity seems to be an important component leading to biological individuality and is of great importance in the case of microbial inactivation. Bacterial cells are characterized by their own resistance to stresses. This inherent stochasticity is reflected in microbial survival curve which, in this context, can be considered as cumulative probability distribution of lethal events. The objective of the present study was to present an overview on the assessment and quantification of variability in microbial inactivation originating from single cells and discuss this heterogeneity in the context of predicting microbial behavior and Risk assessment studies. The detailed knowledge of the distribution of the single cells' inactivation times can be the basis for stochastic inactivation models which, in turn, may be employed in a risk - based food safety approach.

Describing the Individual Spore Variability and the Parameter Uncertainty in Bacterial Survival Kinetics Model by Using Second-Order Monte Carlo Simulation

The objective of this study was to separately describe the fitting uncertainty and the variability of individual cell in bacterial survival kinetics during isothermal and non-isothermal thermal processing. The model describing bacterial survival behavior and its uncertainties and variabilities during non-isothermal inactivation was developed from survival kinetic data for Bacillus simplex spores under fifteen isothermal conditions. The fitting uncertainties in the parameters used in the primary Weibull model was described by using the bootstrap method. The variability of individual cells in thermotolerance and the true randomness in the number of dead cells were described by using the Markov chain Monte Carlo (MCMC) method. A second-order Monte Carlo (2DMC) model was developed by combining both the uncertainties and variabilities. The 2DMC model was compared with reduction behavior under three non-isothermal profiles for model validation. The bacterial death estimations were validated using experimentally observed surviving bacterial count data. The fitting uncertainties in the primary Weibull model parameters, the individual thermotolerance heterogeneity, and the true randomness of inactivated spore counts were successfully described under all the iso-thermal conditions. Furthermore, the 2DMC model successfully described the variances in the surviving bacterial counts during thermal inactivation for all three non-isothermal profiles. As a template for risk-based process designs, the proposed 2DMC simulation approach, which considers both uncertainty and variability, can facilitate the selection of appropriate thermal processing conditions ensuring both food safety and quality.

Transforming kinetic model into a stochastic inactivation model: Statistical evaluation of stochastic inactivation of individual cells in a bacterial population

Kinetic models performing point estimation are effective in predicting the bacterial behavior. However, the large variation of bacterial behavior appearing in a small number of cells, i.e. equal or less than 10² cells, cannot be expressed by point estimation. We aimed to predict the variation of Escherichia coli O157:H7 behavior during inactivation in acidified tryptone soy broth (pH3.0) through Monte Carlo simulation and evaluated the accuracy of the developed model. Weibullian fitted parameters were estimated from the kinetic survival data of E. coli O157:H7 with an initial cell number of 10⁵. A Monte Carlo simulation (100 replication) based on the obtained Weibullian parameters and the Poisson distribution of initial cell numbers successfully predicted the results of 50 replications of bacterial inactivation with initial cell numbers of 10¹, 10², and 10³ cells. The accuracy of the simulation revealed that more than 83% of the observed survivors were within predicted range in all condition. 90% of the distribution in survivors with initial cells less than 100 is equivalent to a Poisson distribution. This calculation transforms the traditional microbial kinetic model into probabilistic model, which can handle bacteria number as discrete probability distribution. The probabilistic approach would utilize traditional kinetic model towards exposure assessment.

Stochastic modeling of variability in survival behavior of Bacillus simplex spore population during isothermal inactivation at the single cell level using a Monte Carlo simulation

The control of bacterial reduction is important to maintain food safety during thermal processing. The goal of this study was to illustrate and describe variability in bacterial population behavior during thermal processing as a probability distribution based on individual cell heterogeneity regarding heat resistance. Toward this end, we performed a Monte Carlo simulation via computer, and compared and validated the simulated estimations with observed values. Weibullian fitted parameters were estimated from the kinetic survival data of Bacillus simplex during thermal treatment at 94 °C. The variability in reductions of bacterial sporular populations was illustrated using Monte Carlo simulation based on the Weibull distribution of the parameters. In particular, variabilities in viable spore counts and survival probability of the B. simplex spore population were simulated in various replicates. We also experimentally determined the changes in survival probability and distributions of survival spore counts; notably, these were successfully predicted by the Monte Carlo simulation based on the kinetic parameters. The kinetic parameter-based Monte Carlo simulation could thus successfully illustrate bacterial population behavior variability during thermal processing as a probability distribution. The simulation approach may contribute to improving food quality through risk-based processing designs and enhance risk assessment model accuracy.

Heterogeneity of single cell inactivation: Assessment of the individual cell time to death and implications in population behavior

A direct microscopic time-lapse method, using appropriate staining for cell viability in a confocal scanning laser microscope, was used for the direct assessment of Salmonella Agona individual cell inactivation in small two-dimensional colonies exposed to osmotic stress. Individual cell inactivation times were fitted to a variety of continuous distributions using @Risk software. The best fitted distribution (LogLogistic) was further used to predict the inactivation of Salmonella populations of various initial levels using Monte Carlo simulation. The simulation results showed that the variability in inactivation kinetics is negligible for concentrations down to 100 cells and the population behavior can be described with a deterministic model. As the concentration decreases below 100 cells, however, the variability increases significantly indicating that the traditional D-value used in deterministic first order kinetic models is not valid. At a second stage, single cell behavior was monitored in larger three dimensional colonies. The results showed that colony size can affect the inactivation pattern. The effect of colony size on microbial inactivation was confirmed with validation experiments which showed a higher inactivation rate for populations consisting of single cells or small colonies compared to those consisting of cells organized in larger colonies.

Stochastic simulation for death probability of bacterial population considering variability in individual cell inactivation time and initial number of cells

Decimal reduction time (D-value) based on the first-order survival kinetics model is not sufficient for reliable estimation of the bacterial survivors of inactivation treatment because the model does not consider inactivation curvature. However, even though doubt exists in the calculation of D-value, it is still widely used for risk assessment and sterilisation time estimation. This paper proposes an approach for estimating the time-to-inactivation and death probability of bacterial population that considers individual cell heterogeneity and initial number of cells via computer simulation. In the proposed approach, Weibull and Poisson distributions are respectively used to provide individual cell inactivation time variability and initial number of cells variability. Our simulation results show that the time-to-inactivation significantly depends on kinetics curvature and initial number of cells. For example, with increases in the initial number of cells, the respective variance of the time-to-inactivation of log-linear, concave downward curve, and concave upward curve remains constant, decreases, and increases, respectively. The death probability contour plot was successfully generated via our computer simulation approach without using D-value estimation. Further, the death probability calculated using our stochastic approach was virtually the same as that obtained using inactivation kinetics. We validated the simulation by using literature data for acid inactivation of Salmonella population. The results of this study indicate that inactivation curvature can replace D-value extrapolation to estimate the death probability of bacterial population. Further, our computer simulation facilitates realistic estimation of the time-to-inactivation of bacterial population. The R code used for the above stochastic calculation is outlined.

Modeling Stochastic Variability in the Numbers of Surviving Salmonella enterica, Enterohemorrhagic Escherichia coli, and Listeria monocytogenes Cells at the Single-Cell Level in a Desiccated Environment

Despite effective inactivation procedures, small numbers of bacterial cells may still remain in food samples. The risk that bacteria will survive these procedures has not been estimated precisely because deterministic models cannot be used to describe the uncertain behavior of bacterial populations. We used the Poisson distribution as a representative probability distribution to estimate the variability in bacterial numbers during the inactivation process. Strains of four serotypes of Salmonella enterica, three serotypes of enterohemorrhagic Escherichia coli, and one serotype of Listeria monocytogenes were evaluated for survival. We prepared bacterial cell numbers following a Poisson distribution (indicated by the parameter λ, which was equal to 2) and plated the cells in 96-well microplates, which were stored in a desiccated environment at 10% to 20% relative humidity and at 5, 15, and 25°C. The survival or death of the bacterial cells in each well was confirmed by adding tryptic soy broth as an enrichment culture. Changes in the Poisson distribution parameter during the inactivation process, which represent the variability in the numbers of surviving bacteria, were described by nonlinear regression with an exponential function based on a Weibull distribution. We also examined random changes in the number of surviving bacteria using a random number generator and computer simulations to determine whether the number of surviving bacteria followed a Poisson distribution during the bacterial death process by use of the Poisson process. For small initial cell numbers, more than 80% of the simulated distributions (λ = 2 or 10) followed a Poisson distribution. The results demonstrate that variability in the number of surviving bacteria can be described as a Poisson distribution by use of the model developed by use of the Poisson process.

IMPORTANCE We developed a model to enable the quantitative assessment of bacterial survivors of inactivation procedures because the presence of even one bacterium can cause foodborne disease. The results demonstrate that the variability in the numbers of surviving bacteria was described as a Poisson distribution by use of the model developed by use of the Poisson process. Description of the number of surviving bacteria as a probability distribution rather than as the point estimates used in a deterministic approach can provide a more realistic estimation of risk. The probability model should be useful for estimating the quantitative risk of bacterial survival during inactivation.

Do bacterial cell numbers follow a theoretical Poisson distribution? Comparison of experimentally obtained numbers of single cells with random number generation via computer simulation

We investigated a bacterial sample preparation procedure for single-cell studies. In the present study, we examined whether single bacterial cells obtained via 10-fold dilution followed a theoretical Poisson distribution. Four serotypes of Salmonella enterica, three serotypes of enterohaemorrhagic Escherichia coli and one serotype of Listeria monocytogenes were used as sample bacteria. An inoculum of each serotype was prepared via a 10-fold dilution series to obtain bacterial cell counts with mean values of one or two. To determine whether the experimentally obtained bacterial cell counts follow a theoretical Poisson distribution, a likelihood ratio test between the experimentally obtained cell counts and Poisson distribution which parameter estimated by maximum likelihood estimation (MLE) was conducted. The bacterial cell counts of each serotype sufficiently followed a Poisson distribution. Furthermore, to examine the validity of the parameters of Poisson distribution from experimentally obtained bacterial cell counts, we compared these with the parameters of a Poisson distribution that were estimated using random number generation via computer simulation. The Poisson distribution parameters experimentally obtained from bacterial cell counts were within the range of the parameters estimated using a computer simulation. These results demonstrate that the bacterial cell counts of each serotype obtained via 10-fold dilution followed a Poisson distribution. The fact that the frequency of bacterial cell counts follows a Poisson distribution at low number would be applied to some single-cell studies with a few bacterial cells. In particular, the procedure presented in this study enables us to develop an inactivation model at the single-cell level that can estimate the variability of survival bacterial numbers during the bacterial death process.

Bacillus cereus in personal care products: risk to consumers

Bacillus cereus is ubiquitous in nature and thus occurs naturally in a wide range of raw materials and foodstuffs. B. cereus spores are resistant to desiccation and heat and able to survive dry storage and cooking. Vegetative cells produce several toxins which on ingestion in sufficient numbers can cause vomiting and/or diarrhoea depending on the toxins produced. Gastrointestinal disease is commonly associated with reheated or inadequately cooked foods. In addition to being a rare cause of several acute infections (e.g. pneumonia and septicaemia), B. cereus can also cause localized infection of post-surgical or trauma wounds and is a rare but significant pathogen of the eye where it may result in severe endophthalmitis often leading to loss of vision. Key risk factors in such cases are trauma to the eye and retained contaminated intraocular foreign bodies. In addition, rare cases of B. cereus-associated keratitis (inflammation of the cornea) have been linked to contact lens use. Bacillus cereus is therefore a microbial contaminant that could adversely affect product safety of cosmetic and facial toiletries and pose a threat to the user if other key risk factors are also present. The infective dose in the human eye is unknown, but as few as 100 cfu has been reported to initiate infection in a susceptible animal model. However, we are not aware of any reports in the literature of B. cereus infections in any body site linked with use of personal care products. Low levels of B. cereus spores may on occasion be present in near-eye cosmetics, and these products have been used by consumers for many years. In addition, exposure to B. cereus is more likely to occur through other routes (e.g. dustborne contamination) due to its ubiquity and resistance properties of spores. The organism has been recovered from the eyes of healthy individuals. Therefore, although there may be a perceived hazard, the risk of severe eye infections as a consequence of exposure through contaminated near-eye cosmetics is judged to be vanishingly small. It is unlikely that more stringent microbiological standards for near-eye cosmetics will have any impact on the risk of severe eye infections caused by B. cereus, as these are not linked to use of personal care products.

Incidence, diversity and characteristics of spores of psychrotolerant spore formers in various REPFEDS produced in Belgium

The major objectives of this study were to determine the incidence of psychrotolerant spore formers from REPFEDS marketed in Belgium, and their diversity and characteristics. Spore formers in general were found as spores on 38.3% of the food samples and in 85% food products types evaluated. 76% of the food samples containing spore formers had spores before enrichment. A total of 86 spore formers were isolated from the samples. 28 of 86 bacterial spore formers (32.6%) were capable of vegetative growth at 7 °C. 96% (27/28) of these psychrotolerant spore formers were determined to belong to Bacillus or related genera. According to a (GTG)5-PCR analysis, 24 of these 28 isolates were genetically distinct from each other. 10.7% (3/28) of the bacilli were determined to belong to the Bacillus cereus group, namely B. cereus (chicken curry and Edam cheese) and Bacillus mycoides (Emmental cheese). Almost half of the bacilli (12/27) were putatively identified as Bacillus pumilus, which occurs ubiquitously in nature and has been associated with outbreaks of foodborne disease. Only one psychrotolerant clostridium, Clostridium tyrobutyricum, was isolated in the study. The results of this study show the highly diverse ecology and spoilage potential of psychrotolerant spore formers in REPFEDs marketed in Belgium.

The combined effect of pasteurization intensity, water activity, pH and incubation temperature on the survival and outgrowth of spores of Bacillus cereus and Bacillus pumilus in artificial media and food products

The objective of the study was to evaluate the combined effects of pasteurization intensity (no heat treatment and 10 min at 70, 80 and 90 °C), water activity (aw) (0.960-0.990), pH (5.5-7.0) and storage temperature (7 and 10 °C) on the survival and outgrowth of psychrotolerant spores of Bacillus cereus FF119b and Bacillus pumilus FF128a. The experiments were performed in both artificial media and a validation was performed on real food products (cream, béchamel sauce and mixed vegetable soup). It was determined that in general, heat treatments of 10 min at 70 °C or 80 °C activated the spores of both B. cereus FF119b and B. pumilus FF128a, resulting in faster outgrowth compared to native (non-heat treated) spores. A pasteurization treatment of 10 min at 90 °C generally resulted in the longest lag periods before outgrowth of both isolates. Some of the spores were inactivated by this heat treatment, with more inactivation being observed the lower the pH value of the heating medium. Despite this, it was also observed that under some conditions the remaining (surviving) spores were actually activated as their outgrowth took place after a shorter period of time compared to native non-heated spores. While the response of B. cereus FF119b to the pasteurization intensity in cream and béchamel sauce was similar to the trends observed in the artificial media at 10 °C, in difference, outgrowth was only observed at 7 °C in both products when the spores had been heated for 10 min at 80 °C. Moreover, no inactivation was observed in cream or béchamel sauce when the spores were heated for 10 min at 90 °C in these two products. This was attributed to the protective effect of fat in the cream and the ingredients in the béchamel sauce. The study provides some insight into the potential microbial (stability and safety) consequences of the current trend towards milder heat treatments which is being pursued in the food industry.

Promoting Bacillus cereus spore germination for subsequent inactivation by mild heat treatment

Sublethal heat treatment may activate dormant spores and thereby potentiate the conversion of spores to vegetative cells. As the germinated spore is known to possess lower heat resistance than its dormant counterpart, it has been postulated that double heat treatment, i.e., spore heat activation followed by germination and then by heat inactivation, can be used to control spores in foods. Production of refrigerated processed foods of extended durability often includes more than one heat treatment of the food components. This work simulates conventional heat treatment procedures and evaluates double heat treatment as a method to improve spore control in model food matrixes of meat broth and cream sauce. Bacillus cereus NVH 1230-88 spores were supplemented in food model matrixes and heat activated at 70°C and then heat inactivated at 80 or 90°C. The samples were held at 29 to 30°C for 1 h between primary and secondary heat treatments, to allow spore germination. Nutrients naturally present in the food matrixes, e.g., amino acids and inosine, could act as germinants that induce germination. The levels of germinants could be too low to produce effective germination within 1 h. Following primary heat treatment, some samples were therefore supplemented with a combination of L-alanine and inosine, a germinant mixture known to be effective for B. cereus spores. In both matrixes, a combination of double heat treatment (heat activation, germination, and inactivation) and addition of germinants gave a reduction in spore counts equivalent to or greater than that obtained with a single heat treatment for 12 min at 90°C. Addition of germinants was essential to induce effective germination in cream sauce during 1 h at 29 to 30°C, and germinants were therefore a crucial supplement to obtain an effect of double heat treatment in this matrix. These data will be valuable when setting up temperature-time-germinant combinations for an optimized spore reduction in mild-heat-treated foods.

Validated empirical models describing the combined effect of water activity and pH on the heat resistance of spores of a psychrotolerant Bacillus cereus strain in broth and béchamel sauce

The major objective of this study was to evaluate and model the combined effect of the water activity (a(w)) and pH of the heating menstrum on the heat resistance of spores of a psychrotolerant Bacillus cereus strain isolated from béchamel sauce. Two models, a quadratic polynomial equation and a reparameterized function, were assessed for their ability to describe the combined influence of a(w) and pH on the D(85°C)-values of the B. cereus isolate in tryptone soy broth. The performance of the models was validated by challenging the models with data independently collected in broth and béchamel sauce. Both models were found to adequately describe the validation data obtained in broth. However, it was determined that in béchamel sauce the predictions of the polynomial function not only showed bias (bias factor = 1.156) but were also fail-dangerous, as they deviated from the validation data by 17.2%. The reparameterized function was determined to be a good predictor of the D(85°C)-values in béchamel sauce as it showed no bias (bias factor = 1.033) and its predictions differed by only 7.9% from the validation data. The reparameterized function can be used to provide estimates of the minimum processing conditions required to achieve desired levels of spore inactivation within the a(w) and pH ranges studied and to determine the potential changes in heat resistance of B. cereus spores when a(w) and pH are changed, for example, during product reformulation. As validation of heat resistance models is rarely performed, let alone in actual food products, the models evaluated and validated in this study (in particular the reparameterized function) are of immediate relevance to the food industry.

A probabilistic approach to determine thermal process setting parameters: application for commercial sterility of products

The objective of the probabilistic data analysis presented in this paper was to enable the thermal process to be set on actual data rather than on generic or conservative rules. The application was an ambient stable soup product, heated in a continuous UHT line. The data set comes from a decade of microbiological analysis: initial spore load and survival spore concentration after moderate heat-treatment (100°C for 15 min and 110°C for 15 min) have been enumerated in forty eight ingredients. The probabilistic analysis was carried out within a risk-based context, considering a Performance Objective, PO, set after the heat-treatment process and an initial spore contamination (H₀) at the ingredient mixing step. The probabilistic analysis was based upon Bayesian inference, chosen for its flexibility when dealing with censored data (some values were reported as less than 1 log cfu/g) and also for its ability to incorporate in the data analysis prior information. Beforehand, Z values around 10°C for aerobic bacterial spores, and log count error around 1 log, were assumed. The methodology and the results are reported using two ingredients (garlic and milk powder) illustrating the 'not detected' (censored data) issue and also the inter-ingredient variability. Indeed, Z was estimated to be 13.6°C (mean) for spores selected from garlic and 5.9°C for those selected from milk powder. Based upon a hypothetical soup recipe with these two ingredients, the sterilization value was estimated to be 13 min (95th percentile). The potential use of similar methodology to design and set the sterilization value for the thermal process of future products, is discussed.

Probabilistic model for Listeria monocytogenes growth during distribution, retail storage, and domestic storage of pasteurized milk

A survey on the time-temperature conditions of pasteurized milk in Greece during transportation to retail, retail storage, and domestic storage and handling was performed. The data derived from the survey were described with appropriate probability distributions and introduced into a growth model of Listeria monocytogenes in pasteurized milk which was appropriately modified for taking into account strain variability. Based on the above components, a probabilistic model was applied to evaluate the growth of L. monocytogenes during the chill chain of pasteurized milk using a Monte Carlo simulation. The model predicted that, in 44.8% of the milk cartons released in the market, the pathogen will grow until the time of consumption. For these products the estimated mean total growth of L. monocytogenes during transportation, retail storage, and domestic storage was 0.93 log CFU, with 95th and 99th percentiles of 2.68 and 4.01 log CFU, respectively. Although based on EU regulation 2073/2005 pasteurized milk produced in Greece belongs to the category of products that do not allow the growth of L. monocytogenes due to a shelf life (defined by law) of 5 days, the above results show that this shelf life limit cannot prevent L. monocytogenes from growing under the current chill chain conditions. The predicted percentage of milk cartons-initially contaminated with 1 cell/1-liter carton-in which the pathogen exceeds the safety criterion of 100 cells/ml at the time of consumption was 0.14%. The probabilistic model was used for an importance analysis of the chill chain factors, using rank order correlation, while selected intervention and shelf life increase scenarios were evaluated. The results showed that simple interventions, such as excluding the door shelf from the domestic storage of pasteurized milk, can effectively reduce the growth of the pathogen. The door shelf was found to be the warmest position in domestic refrigerators, and it was most frequently used by the consumers for domestic storage of pasteurized milk. Furthermore, the model predicted that a combination of this intervention with a decrease of the mean temperature of domestic refrigerators by 2 degrees C may allow an extension of pasteurized milk shelf life from 5 to 7 days without affecting the current consumer exposure to L. monocytogenes.

Physiological response of Bacillus cereus vegetative cells to simulated food processing treatments

Vegetative cells of the spore-former Bacillus cereus were exposed to a number of treatments commonly used in commercial food preparation or during equipment cleaning and decontamination. Treated suspensions were then analyzed for reductions (CFU per milliliter) by plate counting and changes in levels of ATP and ADP released from cells with a bioluminescence-based assay. With the use of flow cytometry (FCM), the physiological status of individual cells before and after exposure to treatments was determined by staining of control and treated cells with three pairs of physiological dyes (SYTO 9/propidium iodide, carboxyfluorescein diacetate/Hoechst 33342, and C12-resazurin/SYTOX Green). Good agreement was found between plate counting and FCM. In general, treatments giving rise to the highest count reductions also had the greatest effects on cell membrane permeability (measured with the use of propidium iodide or SYTOX Green), esterase activity (measured with carboxyfluorescein diacetate), or redox activity (C12-resazurin). FCM data demonstrated the extent of heterogeneity of vegetative cell responses to treatments in, for example, the treatment with 5% H2O2, which caused a 6-log reduction in which approximately 95% of the population was composed of membrane-damaged cells (as reflected by their permeability to SYTOX Green), whereas in treatment with 0.09% (wt/vol) potassium sorbate, which caused only a 1-log reduction, not more than 40% of cells were membrane damaged. The approaches described in this work can be applied to gain a greater understanding of bacterial responses to food control measures, generate more accurate inactivation models, or screen novel prospective food control measures.

Acid and NaCl limits to growth of Listeria monocytogenes and influence of sequence of inimical acid and NaCl levels on inactivation kinetics

Variability in growth limits of Listeria monocytogenes in response to low pH (adjusted with HCl) or high salinity (NaCl) was evaluated for 127 strains in brain heart infusion broth at 25 degrees C. Over 95% of strains habituated at pH 5.0 grew subsequently at pH 4.2, while 25% were able to grow at pH 4.1. More than 85% of strains preadapted to growth at 8.5% NaCl (wt/vol) subsequently grew in the presence of 11.3% NaCl, while 25% were able to grow at 13% NaCl, and 4.7% grew in the presence of 13.9% NaCl. The results extend the generally accepted growth limits for L. monocytogenes in response to these hurdles. Two strains, one of which was relatively tolerant of both hurdles, and another that was less tolerant of both hurdles, were subjected to different sequences of lethal acid (pH 3.5) and NaCl (14%, wt/vol) stresses to determine whether survival was affected by growth limits, or by sequence of application of treatment. There was no significant difference in the inactivation kinetics of the two strains, but inactivation rates were affected by different treatments. For both strains, the inactivation rates, from fastest to slowest, resulted from: (i) lethal pH and then by lethal water activity, or lethal water activity and then by lethal pH; (ii) lethal pH and water activity applied simultaneously; (iii) lethal pH; and (iv) lethal water activity. The results demonstrated that the sequence of lethal stress application strongly influences L. monocytogenes inactivation, and that L. monocytogenes growth limits are not good predictors of survival in inimical environments.

Applying the food safety objective and related standards to thermal inactivation of Salmonella in poultry meat

The objective of this study was to investigate the practicality of designing a heat treatment process in a food manufacturing operation for a product governed by a Food Safety Objective (FSO). Salmonella in cooked poultry meat was taken as the working example. Although there is no FSO for this product in current legislation, this may change in the (near) future. Four different process design calculations were explored by means of deterministic and probabilistic approaches to mathematical data handling and modeling. It was found that the probabilistic approach was a more objective, transparent, and quantifiable approach to establish the stringency of food safety management systems. It also allowed the introduction of specific prevalence rates. The key input analyzed in this study was the minimum time required for the heat treatment at a fixed temperature to produce a product that complied with the criterion for product safety, i.e., the FSO. By means of the four alternative process design calculations, the minimum time requirement at 70 degrees C was established and ranged from 0.26 to 0.43 min. This is comparable to the U.S. regulation recommendations and significantly less than that of 2 min at 70 degrees C used, for instance, in the United Kingdom regulation concerning vegetative microorganisms in ready-to-eat foods. However, the objective of this study was not to challenge existing regulations but to provide an illustration of how an FSO established by a competent authority can guide decisions on safe product and process designs in practical operation; it hopefully contributes to the collaborative work between regulators, academia, and industries that need to continue learning and gaining experience from each other in order to translate risk-based concepts such as the FSO into everyday operational practice.

Predictive microbiology: Quantitative science delivering quantifiable benefits to the meat industry and other food industries

Predictive microbiology is considered in the context of the conference theme "chance, innovation and challenge", together with the impact of quantitative approaches on food microbiology, generally. The contents of four prominent texts on predictive microbiology are analysed and the major contributions of two meat microbiologists, Drs. T.A. Roberts and C.O. Gill, to the early development of predictive microbiology are highlighted. These provide a segue into R&D trends in predictive microbiology, including the Refrigeration Index, an example of science-based, outcome-focussed food safety regulation. Rapid advances in technologies and systems for application of predictive models are indicated and measures to judge the impact of predictive microbiology are suggested in terms of research outputs and outcomes. The penultimate section considers the future of predictive microbiology and advances that will become possible when data on population responses are combined with data derived from physiological and molecular studies in a systems biology approach. Whilst the emphasis is on science and technology for food safety management, it is suggested that decreases in foodborne illness will also arise from minimising human error by changing the food safety culture.