Climate change threatens the microbiological stability of non-refrigerated foods.

Most studies on the impact of climate change on foods focus on the consequences to security and safety. In the present study we provide scientific evidence on an overlooked aspect of climate change related to the microbiological stability of foods. Most microbiologically stable processed foods are contaminated with spores of thermophilic spoilage bacteria which are highly heat-resistant and can survive thermal processing. Current temperatures during distribution and storage in temperate climates do not allow growth of thermophilic bacteria to levels that can cause spoilage, ensuring their microbiological stability. Our findings suggest that the latter limiting condition can be eliminated by global warming. By assessing different global warming scenarios for 38 European cities in a case study with canned milk, we show that failing to limit the increase of global mean surface temperature below 2 °C can lead to a very high risk of spoilage and subsequently cause a collapse of the shelf-stable food chain.

Strain variability in biofilm formation: A food safety and quality perspective.

The inherent differences in microbial behavior among identically treated strains of the same microbial species, referred to as "strain variability", are regarded as an important source of variability in microbiological studies. Biofilms are defined as the structured multicellular communities with complex architecture that enable microorganisms to grow adhered to abiotic or living surfaces and constitute a fundamental aspect of microbial ecology. The research studies assessing the strain variability in biofilm formation are relatively few compared to the ones evaluating other aspects of microbial behavior such as virulence, growth and stress resistance. Among the available research data on intra-species variability in biofilm formation, compiled and discussed in the present review, most of them refer to foodborne pathogens as compared to spoilage microorganisms. Molecular and physiological aspects of biofilm formation potentially related to strain-specific responses, as well as information on the characterization and quantitative description of this type of biological variability are presented and discussed. Despite the considerable amount of available information on the strain variability in biofilm formation, there are certain data gaps and still-existing challenges that future research should cover and address. Current and future advances in systems biology and omics technologies are expected to aid significantly in the explanation of phenotypic strain variability, including biofilm formation variability, allowing for its integration in microbiological risk assessment.

Characterization of Fungal Surface Contaminants of the Small Maltese June Pear, Pyrus communis var. bambinella.

ABSTRACT: Fungal pathogens cause surface contamination and potential premature fruit spoilage of bambinella, a fruit endemic to the Maltese islands, leading to the loss of fruit during the postharvest phase. The objective of this study was to isolate, quantify, and characterize fungal contaminants of the small Maltese June Pear and describe their growth kinetics. In total, 284 fungicide-free fruits were collected over three consecutive summers (2014, 2015, 2016). The isolated fungi were identified by using forward and reverse colonial morphology. Species identification was determined using PCR-based methods. The number of CFU per square centimeter of bambinella outer skin was calculated. Mycelium diameter growth rate studies of the isolates were also carried out at seven different temperatures, ranging from 5 to 35°C. Fungi isolated from bambinella included Cladosporium ramotenellum, Alternaria arborescens, Penicillium lanosum, Penicillium expansum, and Aspergillus sydowii, listed from the most abundant to the least abundant. The Rosso model was fitted to the growth kinetic data and showed that the optimal temperatures for growth of all five fungi were in the range of 20 to 22°C, whereas growth was slower at temperatures below 10°C and above 30°C. As observed in the diameter studies, the order of highest to lowest germination rate was found to be P. expansum, A. sydowii, P. lanosum, C. ramotenellum, and A. arborescens. Germination studies showed that the highest germination rate was observed for P. lanosum, followed by A. arborescens, C. ramotenellum, P. expansum, and A. sydowii, in descending order. The highest germination lag time was observed for A. arborescens, followed by C. ramotenellum, P. expansum, P. lanosum, and A. sydowii, in ascending order.

Effect of chlorine stress on the subsequent growth behavior of individual Salmonella cells.

The present work investigates the effect of chlorine stress on the subsequent growth behavior of individual Salmonella cells. A time-lapse microscopy method was used which allowed to evaluate the effect of chlorine on the division times of Salmonella individual cells and the percentage of cells able to divide after the treatment. The results showed that the percentage of cells able to divide after the chlorine treatment decreased from 92.7% for untreated cells to 43.12% and 22% for cell exposed to 127 and 150 mg/l chlorine for 3 min, respectively. The first division time of Salmonella cells was not affected by the chlorine stress at the lower tested concentration of 11 mg/l. Exposure at higher chlorine concentrations however, resulted in significantly longer and more variable division times. The mean first division times were 1.46 ±â€¯0.61, 1.41 ±â€¯0.53, 1.69 ±â€¯0.59, 5.34 ±â€¯4.03 and 19.2 ±â€¯8.71 h after 3 min treatments with 0, 11, 61, 127 and 150 mg/l chlorine, respectively. The effect of chlorine on the second division time of the cells was milder compared to the first division. Exposure of cells to chlorine concentrations up to 61 mg/l did not affect the second division. These results indicate that the daughter cells have no "memory" of the chlorine treatment at these concentrations. For cells exposed to the highest tested chlorine concentration of 150 mg/l the mean second division time was almost 3.5 times longer compared to untreated cells indicating that potential damages of the cells caused by the chlorine treatment are not fully repaired in the second generation. The quantitative data provided by this study at the level of individual cell may lead to a better understanding of microbial resistance to chlorine and improve sanitation and decontamination procedures in the food industry.

Assessment of Escherichia coli O157:H7 growth in ground beef in the Greek chill chain.

A predictive mathematical model of the effect of temperature (10-47 °C) on the growth of Escherichia coli O157:H7 in natural contaminated ground beef was developed. The estimated values for the cardinal parameters Tmin, Tmax, Topt and the optimum maximum specific growth rate (µopt) of E. coli O157:H7 were found to be 3.36, 46.87, 43.16 °C and 1.385/h, respectively. The developed model was further validated against observed growth of E. coli O157:H7 in ground beef at non - isothermal chilling conditions by using two periodically changing temperature profiles with temperature ranging from 0 to 15 °C. Overall the model predicted satisfactorily the growth of E. coli O157:H7 in ground beef at dynamic temperature conditions. The model was combined with temperature data collected from ground beef chill chain in Greece in order to assess the growth of the pathogen from purchase of the product at retail to consumption. Retail storage average temperature from 50 retail cabinets in Greek super markets ranged from 0.1 to 7.4 °C with a mean of 3.2 °C and a mean standard deviation of 1.7 °C. The predicted growth of the pathogen after 7 days of storage at retail ranged between 0 and 2.03 log10 CFU/g, with an average growth to 0.31 log10 CFU/g. The growth of the pathogen during transportation from retail to domestic refrigerators ranged between 0.03 and 0.45 log10 CFU/g, with an average growth to 0.16 log10 CFU/g. The average temperature of 160 domestic refrigerators ranged from -2.7 to 18.1 °C. Differences in the temperature among the shelves of the refrigerators were observed. The predicted growth of E. coli O157:H7 in ground beef stored in domestic refrigerators for 1 day ranged between 0.00 and 2.3 log10 CFU/g. For a scenario storage of ground beef in retail for 3 days, transportation from retail domestic refrigerators over a period of 6 h and storage in domestic refrigerators for 3 days the 99th percentile of the total growth was 4.83 log10 CFU/g for storage at the upper self of the domestic refrigerator. The data and models provided in the present work can be further used in a quantitative risk assessment model of E. coli O157:H7 in ground beef consumed in Greece.

Simultaneous growth, survival and death: The trimodal behavior of Salmonella cells under osmotic stress giving rise to "Phoenix phenomenon".

Time-lapse microscopy methods were used to monitor growth, survival and death of Salmonella enterica serotype Agona individual cells on solid laboratory medium (tryptone soy agar) in the presence of various salt concentrations (0.5%, 3.5%, 4.5% and 5.7% NaCl). The results showed a highly heterogeneous behavior. As NaCl concentration increased, the distribution of the first division time was shifted to higher values and became wider. The mean first division time increased from 1.8 h at 0.5% NaCl to 5.48 h, 16.2 h, and 35.9 h at 3.5%, 4.5% and 5.7% NaCl, respectively. The concentration of NaCl in the growth medium also affected the ability of the cells to divide. The percentage of cells able to grow decreased from 88.9% at 0.5% NaCl to 66.5%, 32.8%, and 6.9% at 3.5%, 4.5% and 5.7% NaCl, respectively. In the latter case (5.7% NaCl), 74 cells out of 406 cells tested (18%) died with mean time to death 5.03 h and standard deviation 6.70 h. To investigate the effect of the behavior of individual cells on the dynamics of the whole population, simulation analysis was used. The simulation results showed that the simultaneous growth, survival and death of cells observed under osmotic stress can lead to a total population behavior known as the "Phoenix" phenomenon. The simulation findings were confirmed by validation experiments using both viable counts and time lapse microscopy. The results of the present study show the high heterogeneity of individual cell responses and the complexity in the behavior of microbial populations at conditions approaching the boundaries of growth.

Mapping the risk of evaporated milk spoilage in the Mediterranean region based on the effect of temperature conditions on Geobacillus stearothermophilus growth.

A predictive model for the effect of storage temperature on the growth of Geobacillus stearothermophilus was applied in order to assess the risk of evaporated milk spoilage in the markets of the Mediterranean region. The growth of G. stearothermophilus in evaporated milk was evaluated during a shelf life of one year based on historical temperature profiles (hourly) covering 23 Mediterranean capitals for five years over the period 2012-2016 obtained from the Weather Underground database (http://www.wunderground.com/). In total, 115 scenarios were tested simulating the distribution and storage conditions of evaporated milk in the Mediterranean region. The highest growth of G. stearothermophilus was predicted for Marrakech, Damascus and Cairo over the period 2012-2016 with mean values of 7.2, 7.4 and 5.5 log CFU/ml, respectively, followed by Tunis, Podgorica and Tripoli with mean growth of 2.8, 2.4 and 2.3 log CFU/ml, respectively. For the rest 17 capitals the mean growth of the spoiler was <1.5 log CFU/ml. The capitals Podgorica, Cairo, Tunis and Ankara showed the highest variability in the growth during the 5 years examined with standard deviation values for growth of 2.01, 1.79, 1.77 and 1.25 log CFU/ml, respectively. The predicted extent and the variability of growth during the shelf life were used to assess the risk of spoilage which was visualised in a geographical risk map. The growth model of G. stearothermophilus was also used to evaluate adjustments of the evaporated milk expiration date which can reduce the risk of spoilage. The quantitative data provided in the present study can assist the food industry to effectively evaluate the microbiological stability of these products throughout distribution and storage at a reduced cost (by reducing sampling quality control) and assess whether and under which conditions (e.g. expiration date) will be able to export a product to a country without spoilage problems. This decision support may lead to a significant benefit for both the competitiveness of the food industry and the consumer.

Development and validation of predictive models for the effect of storage temperature and pH on the growth boundaries and kinetics of Alicyclobacillus acidoterrestris ATCC 49025 in fruit drinks.

This study was undertaken to provide quantitative tools for predicting the behavior of the spoilage bacterium Alicyclobacillus acidoterrestris ATCC 49025 in fruit drinks. In the first part of the study, a growth/no growth interface model was developed, predicting the probability of growth as a function of temperature and pH. For this purpose, the growth ability of A. acidoterrestris was studied at different combinations of temperature (15-45 °C) and pH (2.02-5.05). The minimum pH and temperature where growth was observed was 2.52 (at 35 and 45 °C) and 25 °C (at pH ≥ 3.32), respectively. Then a logistic polynomial regression model was fitted to the binary data (0: no growth, 1: growth) and, based on the concordance index (98.8%) and the Hosmer-Lemeshow statistic (6.226, P = 0.622), a satisfactory goodness of fit was demonstrated. In the second part of the study, the effects of temperature (25-55 °C) and pH (3.03-5.53) on A. acidoterrestris growth rate were investigated and quantitatively described using the cardinal temperature model with inflection and the cardinal pH model, respectively. The estimated values for the cardinal parameters Tmin, Tmax, Topt and pHmin, pHmax, pHopt were 18.11, 55.68, 48.60 °C and 2.93, 5.90, 4.22, respectively. The developed models were validated against growth data of A. acidoterrestris obtained in eight commercial pasteurized fruit drinks. The validation results showed a good performance of both models. In all cases where the growth/no growth interface model predicted a probability lower than 0.5, A. acidoterrestris was, indeed, not able to grow in the tested fruit drinks; similarly, when the model predicted a probability above 0.9, growth was observed in all cases. A good agreement was also observed between growth predicted by the kinetic model and the observed kinetics of A. acidoterrestris in fruit drinks at both static and dynamic temperature conditions.

Effect of storage temperature on the lag time of Geobacillus stearothermophilus individual spores.

The lag times (λ) of Geobacillus stearothermophilus single spores were studied at different storage temperatures ranging from 45 to 59 °C using the Bioscreen C method. A significant variability of λ was observed among individual spores at all temperatures tested. The storage temperature affected both the position and the spread of the λ distributions. The minimum mean value of λ (i.e. 10.87 h) was observed at 55 °C, while moving away from this temperature resulted in an increase for both the mean and standard deviation of λ. A Cardinal Model with Inflection (CMI) was fitted to the reverse mean λ, and the estimated values for the cardinal parameters Tmin, Tmax, Topt and the optimum mean λ of G. stearothermophilus were found to be 38.1, 64.2, 53.6 °C and 10.3 h, respectively. To interpret the observations, a probabilistic growth model for G. stearothermophilus individual spores, taking into account λ variability, was developed. The model describes the growth of a population, initially consisting of N0 spores, over time as the sum of cells in each of the N0 imminent subpopulations originating from a single spore. Growth simulations for different initial contamination levels showed that for low N0 the number of cells in the population at any time is highly variable. An increase in N0 to levels exceeding 100 spores results in a significant decrease of the above variability and a shorter λ of the population. Considering that the number of G. stearothermophilus surviving spores in the final product is usually very low, the data provided in this work can be used to evaluate the probability distribution of the time-to-spoilage and enable decision-making based on the "acceptable level of risk".

Image analysis driven single-cell analytics for systems microbiology.

BACKGROUND: Time-lapse microscopy is an essential tool for capturing and correlating bacterial morphology and gene expression dynamics at single-cell resolution. However state-of-the-art computational methods are limited in terms of the complexity of cell movies that they can analyze and lack of automation. The proposed Bacterial image analysis driven Single Cell Analytics (BaSCA) computational pipeline addresses these limitations thus enabling high throughput systems microbiology. RESULTS: BaSCA can segment and track multiple bacterial colonies and single-cells, as they grow and divide over time (cell segmentation and lineage tree construction) to give rise to dense communities with thousands of interacting cells in the field of view. It combines advanced image processing and machine learning methods to deliver very accurate bacterial cell segmentation and tracking (F-measure over 95%) even when processing images of imperfect quality with several overcrowded colonies in the field of view. In addition, BaSCA extracts on the fly a plethora of single-cell properties, which get organized into a database summarizing the analysis of the cell movie. We present alternative ways to analyze and visually explore the spatiotemporal evolution of single-cell properties in order to understand trends and epigenetic effects across cell generations. The robustness of BaSCA is demonstrated across different imaging modalities and microscopy types. CONCLUSIONS: BaSCA can be used to analyze accurately and efficiently cell movies both at a high resolution (single-cell level) and at a large scale (communities with many dense colonies) as needed to shed light on e.g. how bacterial community effects and epigenetic information transfer play a role on important phenomena for human health, such as biofilm formation, persisters' emergence etc. Moreover, it enables studying the role of single-cell stochasticity without losing sight of community effects that may drive it.

Risk assessment of fungal spoilage: A case study of Aspergillus niger on yogurt.

A quantitative risk assessment model of yogurt spoilage by Aspergillus niger was developed based on a stochastic modeling approach for mycelium growth by taking into account the important sources of variability such as time-temperature conditions during the different stages of chill chain and individual spore behavior. Input parameters were fitted to the appropriate distributions and A. niger colony's diameter at each stage of the chill chain was estimated using Monte Carlo simulation. By combining the output of the growth model with the fungus prevalence, that can be estimated by the industry using challenge tests, the risk of spoilage translated to number of yogurt cups in which a visible mycelium of A. niger is being formed at the time of consumption was assessed. The risk assessment output showed that for a batch of 100,000 cups in which the percentage of contaminated cups with A. niger was 1% the predicted numbers (median (5th, 95th percentiles)) of the cups with a visible mycelium at consumption time were 8 (5, 14). For higher percentages of 3, 5 and 10 the predicted numbers (median (5th, 95th percentiles)) of the spoiled cups at consumption time were estimated to be 24 (16, 35), 39 (29, 52) and 80 (64, 94), respectively. The developed model can lead to a more effective risk-based quality management of yogurt and support the decision making in yogurt production.

Quantifying the effect of water activity and storage temperature on single spore lag times of three moulds isolated from spoiled bakery products.

The inhibitory effect of water activity (aw) and storage temperature on single spore lag times of Aspergillus niger, Eurotium repens (Aspergillus pseudoglaucus) and Penicillium corylophilum strains isolated from spoiled bakery products, was quantified. A full factorial design was set up for each strain. Data were collected at levels of aw varying from 0.80 to 0.98 and temperature from 15 to 35°C. Experiments were performed on malt agar, at pH5.5. When growth was observed, ca 20 individual growth kinetics per condition were recorded up to 35days. Radius of the colony vs time was then fitted with the Buchanan primary model. For each experimental condition, a lag time variability was observed, it was characterized by its mean, standard deviation (sd) and 5th percentile, after a Normal distribution fit. As the environmental conditions became stressful (e.g. storage temperature and aw lower), mean and sd of single spore lag time distribution increased, indicating longer lag times and higher variability. The relationship between mean and sd followed a monotonous but not linear pattern, identical whatever the species. Next, secondary models were deployed to estimate the cardinal values (minimal, optimal and maximal temperatures, minimal water activity where no growth is observed anymore) for the three species. That enabled to confirm the observation made based on raw data analysis: concerning the temperature effect, A. niger behaviour was significantly different from E. repens and P. corylophilum: Topt of 37.4°C (standard deviation 1.4°C) instead of 27.1°C (1.4°C) and 25.2°C (1.2°C), respectively. Concerning the aw effect, from the three mould species, E. repens was the species able to grow at the lowest aw (awmin estimated to 0.74 (0.02)). Finally, results obtained with single spores were compared to findings from a previous study carried out at the population level (Dagnas et al., 2014). For short lag times (≤5days), there was no difference between lag time of the population (ca 2000 spores inoculated in one spot) and mean (nor 5th percentile) of single spore lag time distribution. In contrast, when lag time was longer, i.e. under more stressful conditions, there was a discrepancy between individual and population lag times (population lag times shorter than 5th percentiles of single spore lag time distribution), confirming a stochastic process. Finally, the temperature cardinal values estimated with single spores were found to be similar to those obtained at the population level, whatever the species. All these findings will be used to describe better mould spore lag time variability and then to predict more accurately bakery product shelf-life.

Variability in the adaptive acid tolerance response phenotype of Salmonella enterica strains.

The objective of this study was the assessment of the stationary-phase, low-pH-inducible acid tolerance response (ATR) of different Salmonella enterica strains. For this purpose, 30 strains of the pathogen were grown in tryptone soy broth in the absence (non-adapted cultures) and presence (1% w/v; acid-adapted cultures) of glucose, and then subjected to 4-h acid challenge trials at pH 3.0. Surviving populations of each strain were determined at 1-h intervals, and the Weibull model was fitted to the derived microbiological data. Extensive variability in the acid stress responses of the tested S. enterica strains was observed, with the total population reductions (log CFU/ml) attained in 4 h of acid challenge ranging from 0.9 to 5.5 and from 0.6 to 7.0 for the non-adapted and acid-adapted cultures, respectively. As demonstrated by the model scale parameter δ and shape parameter p, the effect of acid adaptation on the inactivation curves was strain-specific. Although acid adaptation resulted in enhanced acid survival for the majority of the tested strains, there were strains exhibiting similar or decreased acid resistance compared to their non-adapted counterparts. Moreover, acid adaptation appeared to decrease the strain variability of δ whereas increasing the strain variability of p: the coefficient of variation of δ among the tested strains was 97.2 and 54.9% for the non-adapted and acid-adapted cultures, respectively, while the corresponding values for p were 12.7 and 48.1%. The data of the present study, which is the first one to systematically evaluate the adaptive ATR of multiple S. enterica strains, clearly demonstrate that this phenotype (attempted to be induced by growing the pathogen in the presence of glucose) is strain-dependent.

Individual cell heterogeneity in Predictive Food Microbiology: Challenges in predicting a "noisy" world.

Gene expression is a fundamentally noisy process giving rise to a significant cell to cell variability at the phenotype level. The phenotypic noise is manifested in a wide range of microbial traits. Heterogeneous behavior of individual cells is observed at the growth, survival and inactivation responses and should be taken into account in the context of Predictive Food Microbiology (PMF). Recent methodological advances can be employed for the study and modeling of single cell dynamics leading to a new generation of mechanistic models which can provide insight into the link between phenotype, gene-expression, protein and metabolic functional units at the single cell level. Such models however, need to deal with an enormous amount of interactions and processes that influence each other, forming an extremely complex system. In this review paper, we discuss the importance of noise and present the future challenges in predicting the "noisy" microbial responses in foods.

Development and application of Geobacillus stearothermophilus growth model for predicting spoilage of evaporated milk.

The presence of Geobacillus stearothermophilus spores in evaporated milk constitutes an important quality problem for the milk industry. This study was undertaken to provide an approach in modelling the effect of temperature on G. stearothermophilus ATCC 7953 growth and in predicting spoilage of evaporated milk. The growth of G. stearothermophilus was monitored in tryptone soy broth at isothermal conditions (35-67 °C). The data derived were used to model the effect of temperature on G. stearothermophilus growth with a cardinal type model. The cardinal values of the model for the maximum specific growth rate were Tmin = 33.76 °C, Tmax = 68.14 °C, Topt = 61.82 °C and µopt = 2.068/h. The growth of G. stearothermophilus was assessed in evaporated milk at Topt in order to adjust the model to milk. The efficiency of the model in predicting G. stearothermophilus growth at non-isothermal conditions was evaluated by comparing predictions with observed growth under dynamic conditions and the results showed a good performance of the model. The model was further used to predict the time-to-spoilage (tts) of evaporated milk. The spoilage of this product caused by acid coagulation when the pH approached a level around 5.2, eight generations after G. stearothermophilus reached the maximum population density (Nmax). Based on the above, the tts was predicted from the growth model as the sum of the time required for the microorganism to multiply from the initial to the maximum level ( [Formula: see text] ), plus the time required after the [Formula: see text] to complete eight generations. The observed tts was very close to the predicted one indicating that the model is able to describe satisfactorily the growth of G. stearothermophilus and to provide realistic predictions for evaporated milk spoilage.

Towards lag phase of microbial populations at growth-limiting conditions: The role of the variability in the growth limits of individual cells.

The water activity (aw) growth limits of unheated and heat stressed Listeria monocytogenes individual cells were studied. The aw limits varied from 0.940 to 0.997 and 0.951 to 0.997 for unheated and heat stressed cells, respectively. Due to the above variability a decrease in aw results in the presence of a non-growing fraction in the population leading to an additional pseudo-lag in population growth. In this case the total apparent lag of the population is the sum of the physiological lag of the growing cells (time required to adjust to the new environment) and the pseudo-lag. To investigate the effect of aw on the above lag components, the growth kinetics of L. monocytogenes on tryptone soy agar with aw adjusted to values ranging from 0.997 to 0.940 was monitored. The model of B&R was fitted to the data for the estimation of the apparent lag. In order to estimate the physiological lag of the growing fraction of the inoculum, the model was refitted to the growth data using as initial population level the number of cells that were able to grow (estimated from the number of colonies formed on the agar at the end of storage) and excluding the rest data during the lag. The results showed that for the unheated cells the apparent lag was almost identical to the physiological lag for aw values ranging from 0.997 to 0.970, as the majority of the cells in the initial population was able to grow in these conditions. As the aw decreased from 0.970 to 0.940 however, the number of cells in the population which were able to grow, decreased resulting to an increase in the pseudo-lag. The maximum value of pseudo-lag was 13.1h and it was observed at aw=0.940 where 10% of the total inoculated cells were able to grow. For heat stressed populations a pseudo-lag started to increase at higher aw conditions (0.982) compared to unheated cells. In contrast to the apparent lag, a linear relation between physiological lag and aw was observed for both unheated and heat stressed cells.

Modelling biofilm formation of Salmonella enterica ser. Newport as a function of pH and water activity.

The effect of pH and water activity (aw) on the formation of biofilm by Salmonella enterica ser. Newport, previously identified as a strong biofilm producer, was assessed. Biofilm formation was evaluated in tryptone soy broth at 37 °C and at different combinations of pH (3.3-7.8) and aw (0.894-0.997). In total, 540 biofilm formation tests in 108 pH and aw combinations were carried out in polystyrene microtiter plates using crystal violet staining and optical density (OD; 580 nm) measurements. Since the individual effects of pH and aw on biofilm formation had a similar pattern to that observed for microbial growth rate, cardinal parameter models (CPMs) were used to describe these effects. CPMs described successfully the effects of these two environmental parameters, with the estimated cardinal values of pHmin, pHopt, pHmax, awmin and awopt being 3.58, 6.02, 9.71, 0.894 and 0.994, respectively. The CPMs assumption of the multiplicative inhibitory effect of environmental factors was validated in the case of biofilm formation using additional independent data (i.e. 430 OD data at 86 different combinations of pH and aw). The validation results showed a good agreement (r(2) = 0.938) between observed and predicted OD with no systematic error. In the second part of this study, a probabilistic model predicting the pathogen's biofilm formation boundaries was developed, and the degree of agreement between predicted probabilities and observations was as high as 99.8%. Hence, the effect of environmental parameters on biofilm formation can be quantitatively expressed using mathematical models, with the latter models, in turn, providing useful information for biofilm control in food industry environments.

Modeling red cabbage seed extract effect on Penicillium corylophilum: Relationship between germination time, individual and population lag time.

The inhibitory effect of a red cabbage seed extract on germination time, individual (single spore) and population lag time of Penicillium corylophilum was studied. First, to compare the biological variability of single spore germination and lag times under stressful conditions, data were collected at levels of red cabbage seed extract varying from 0 to 10 mg/g (150 spores observed in each trial of germination, ca 50 spores in each individual lag experiment). Experiments were performed on malt agar at 25 °C, pH 5.2, aw 0.99. The data, without any transformation, were statistically analyzed; several probability distribution functions were used to fit the cumulated germination times and the individual lag times of spores. In both cases, the best fit was obtained with the Normal distribution. In parallel, lag times at the population level (ca 2000 spores per trial) were collected for the same range of plant extract. Not surprisingly, the difference between individual and population lag times could be explained by a stochastic process. More interestingly, it was shown that under stressful conditions, the population lag time did not correspond to the time required for germination of 95% of spores, but to a much longer time. Finally, it was deduced from the statistical analysis, completed by microscopic observations, that the plant extract affected mainly the hyphal elongation (and then the lag time) and not the germination. Next, secondary models were developed to quantify the effect of red cabbage seed extract on the median of germination times, individual and population lag times. The Minimum Inhibitory Concentrations (MICs) were estimated. It was shown that the red cabbage seed extract MIC for P. corylophilum lag time did not depend on the inoculum load. Application of the secondary models allowed us to conclude that under the conditions of our experiment, the addition of 10 mg/g of red cabbage seed extract enabled extension of lag time to two weeks.

Individual cell heterogeneity as variability source in population dynamics of microbial inactivation.

A statistical modeling approach was applied for describing and evaluating the individual cell heterogeneity as variability source in microbial inactivation. The inactivation data (Nt vs time) of Salmonella enterica serotype Agona, with initial concentration N0 = 10(9) CFU/ml in acidified tryptone soy broth (pH 3.5), were transformed to (N0 - Nt)/N0 vs time leading to the cumulative probability distribution of the individual cell inactivation times (ti), which was further fitted to a variety of continuous distributions using @Risk software. The best-fitted ti distribution (Gamma) was used to predict the inactivation of S. Agona populations of various N0 using Monte Carlo simulation, with the number of iterations in each simulation being equal to N0 and the number of simulations representing the variability of the population inactivation behavior. The Monte Carlo simulation results for a population with N0 = 10,000 CFU/ml showed that the variability in the predicted inactivation behavior is negligible for concentrations down to 100 cells. As the concentration decreases below 100 cells, however, the variability increases significantly. The results also indicated that the D-value used in deterministic first order kinetic models is valid only for large populations. For small populations, D-value shows a high variability, originating from individual cell heterogeneity, and, thus, can be better characterized by a probability distribution rather than a uniform value. Validation experiments with small populations confirmed the variability predicted by the statistical model. The use of the proposed approach to quantify the variability in the inactivation of mixed microbial populations, consisting of subpopulations with different probability distributions of ti, was also demonstrated.

Strain variability of the behavior of foodborne bacterial pathogens: a review.

Differences in phenotypic responses among strains of the same microbial species constitute an important source of variability in microbiological studies, and as such they need to be assessed, characterized and taken into account. This review provides a compilation of available research data on the strain variability of four basic behavioral aspects of foodborne bacterial pathogens including: (i) virulence; (ii) growth; (iii) inactivation; and (iv) biofilm formation. A particular emphasis is placed on the foodborne pathogens Listeria monocytogenes and Salmonella enterica. The implications of strain variability for food safety challenge studies and microbial risk assessment are discussed also. The information provided indicates that the variability among strains of foodborne bacterial pathogens with respect to their behavior can be significant and should not be overlooked. However, in order for the mechanisms underlying the observed strain variability to be elucidated and understood, phenotypic variability data, such as those reviewed here, should be evaluated in conjunction with corresponding findings of studies assessing the molecular/physiological basis of this variability.