Predictive modeling of the growth of Listeria monocytogenes in CO2 environments

Effects of carbon dioxide and oxygen on the growth rate of various food spoilage bacteria

The growth of six bacterial species (Carnobacterium maltaromaticum, Bacillus weihenstephanensis, Bacillus cereus, Paenibacillus spp., Leuconostoc mesenteroides and Pseudomonas fragi) was studied in various gas compositions. Growth curves were obtained at various oxygen concentrations (between 0.1 and 21%), or various carbon dioxide concentrations (between 0 and 100%). Decreasing the O₂ concentration from 21% to about 3-5% has no effect on the bacterial growth rates, which are only affected by low oxygen levels. For each strain studied, the growth rate decreased linearly with carbon dioxide concentration, except for L. mesenteroides which remained insensible to this gas. Conversely, the most sensitive strain was totally inhibited by 50% of carbon dioxide in the gas phase at 8 °C. Predictive models were fitted, and the parameters characterizing the inhibitory effect of these two gases were estimated. This study provides new tools to help the food industry design suitable packaging for MAP storage.

Modeling carbon dioxide effect in a controlled atmosphere and its interactions with temperature and pH on the growth of L. monocytogenes and P. fluorescens

The effect of carbon dioxide, temperature, and pH on growth of Listeria monocytogenes and Pseudomonas fluorescens was studied, following a protocol to monitor microbial growth under a constant gas composition. In this way, the CO₂ dissolution didn't modify the partial pressures in the gas phase. Growth curves were acquired at different temperatures (8, 12, 22 and 37 °C), pH (5.5 and 7) and CO₂ concentration in the gas phase (0, 20, 40, 60, 80, 100% of the atmospheric pressure, and over 1 bar). These three factors greatly influenced the growth rate of L. monocytogenes and P. fluorescens, and significant interactions have been observed between the carbon dioxide and the temperature effects. Results showed no significant effect of the CO₂ concentration at 37 °C, which may be attributed to low CO2 solubility at high temperature. An inhibitory effect of CO₂ appeared at lower temperatures (8 and 12 °C). Regardless of the temperature, the gaseous CO₂ is sparingly soluble at acid pH. However, the CO₂ inhibition was not significantly different between pH 5.5 and pH 7. Considering the pKa of the carbonic acid, these results showed the dissolved carbon under HCO₃^- form didn't affect the bacterial inhibition. Finally, a global model was proposed to estimate the growth rate vs. CO₂ concentration in the aqueous phase. This dissolved concentration is calculated according to the physical equations related to the CO₂ equilibriums, involving temperature and pH interactions. This developed model is a new tool available to manage the food safety of MAP.

Effects of Soluble Gas Stabilisation, Modified Atmosphere, Gas to Product Volume Ratio and Storage on the Microbiological and Sensory Characteristics of Ready-to-Eat Shrimp (Pandalus borealis)

The effects of storage time, modified atmospheres (30% or 60% CO2), soluble gas stabilisation and gas to product volume ( g/ p) ratio were investigated on the microbiological and sensory characteristics of cooked, peeled and brined ready-to-eat (RTE) deep-water shrimps ( Pandalus borealis). Soluble gas stabilisation (SGS) treatment prior to packaging (2h) increased the CO2 content in the packaged shrimp and counteracted package collapse, even at low g/ p ratios (0.66). SGS treatment reduced significantly (P 0.01) the aerobic plate count and psychrotrophic count. The increase of CO2 levels during modified atmosphere (MA) packaging and the application of SGS significantly enhanced (P 0.01) the sensory quality of the shrimps. The exudates in the packages (%) were significantly reduced (P 0.01) when applying SGS treatment. Therefore, SGS treatment in combination with MA packaging can be used successfully on RTE shrimps to reduce the package volume and to improve the microbiological and sensory characteristics.

Validation of a predictive model coupling gas transfer and microbial growth in fresh food packed under modified atmosphere

Predicting microbial safety of fresh products in modified atmosphere packaging implies to take into account the dynamic of O2, CO2 and N2 exchanges in the system and its effect on microbial growth. In this paper a mechanistic model coupling gas transfer and predictive microbiology was validated using dedicated challenge-tests performed on poultry meat, fresh salmon and processed cheese, inoculated with either Listeria monocytogenes or Pseudomonas fluorescens and packed in commercially used packaging materials (tray + lid films). The model succeeded in predicting the relative variation of O2, CO2 and N2 partial pressure in headspace and the growth of the studied microorganisms without any parameter identification. This work highlighted that the respiration of the targeted microorganism itself and/or that of the naturally present microflora could not be neglected in most of the cases, and could, in the particular case of aerobic microbes contribute to limit the growth by removing all residual O2 in the package. This work also confirmed the low sensitivity of L. monocytogenes toward CO2 while that of P. fluorescens permitted to efficiently prevent its growth by choosing the right combination of packaging gas permeability value and initial % of CO2 initially flushed in the pack.

Control of Escherichia coli and Listeria monocytogenes in suckling-lamb meat evaluated using microbial challenge tests

Escherichia coli and Listeria monocytogenes microbial challenge tests were performed on fresh suckling-lamb meat. Hind leg slices were chilly stored under two modified atmosphere packaging (MAP) environments (A: 15%O2/60%CO2/25%N2, B: 15%O2/30%CO2/55%N2) and vacuum packaging (V). Only E. coli was reduced between 0.72-1.25 log cfu/g from day 1 to day 4 by the combined use of MAP/V, chilling storage and the growth of native lactic acid bacteria. However, L. monocytogenes was not inhibited by the application of V or MAP. Even do, in inoculated samples, this pathogen increased between 1.2-2.7 log cfu/g throughout the study. Consequently, a second experiment that combined the effects of MAP/V and a protective culture (Leuconostoc pseudomesenteroides PCK 18) against L. monocytogenes was designed. Two different levels of protective cultures were assayed (4 and 6 log cfu/g). Lc. pseudomesenteroides PCK 18 was able to control the growth of L. monocytogenes when the differences between them are higher than 2 log cfu/g. Moreover, when high level of protective culture was used a significant reduction of L. monocytogenes counts were noticed in samples packaged in 60% of CO2 along the storage period, although sensory properties were also affected.

Mechanistic model coupling gas exchange dynamics and Listeria monocytogenes growth in modified atmosphere packaging of non respiring food

A mechanistic model coupling O2 and CO2 mass transfer (namely diffusion and solubilisation in the food itself and permeation through the packaging material) to microbial growth models was developed aiming at predicting the shelf life of modified atmosphere packaging (MAP) systems. It was experimentally validated on a non-respiring food by investigating concomitantly the O2/CO2 partial pressure in packaging headspace and the growth of Listeria monocytogenes (average microbial count) within the food sample. A sensitivity analysis has revealed that the reliability of the prediction by this "super-parametrized" model (no less than 47 parameters were required for running one simulation) was strongly dependent on the accuracy of the microbial input parameters. Once validated, this model was used to decipher the role of O2/CO2 mass transfer on microbial growth and as a MAP design tool: an example of MAP dimensioning was provided in this paper as a proof of concept.

Modified Atmosphere Packaging Technology of Fresh and Fresh-cut Produce and the Microbial Consequences-A Review

Modified atmosphere packaging (MAP) technology offers the possibility to retard the respiration rate and extend the shelf life of fresh produce, and is increasingly used globally as value adding in the fresh and fresh-cut food industry. However, the outbreaks of foodborne diseases and emergence of resistant foodborne pathogens in MAP have heightened public interest on the effects of MAP technology on the survival and growth of pathogenic organisms. This paper critically reviews the effects of MAP on the microbiological safety of fresh or fresh-cut produce, including the role of innovative tools such as the use of pressurised inert/noble gases, predictive microbiology and intelligent packaging in the advancement of MAP safety. The integration of Hazard Analysis and Critical Control Points-based programs to ensure fresh food quality and microbial safety in packaging technology is highlighted.

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.

Characterization of human invasive isolates of Listeria monocytogenes in Sweden 1986-2007

Since 1986, 68% of the Listeria monocytogenes isolates from human cases of invasive listeriosis in Sweden are available for retrospective studies. The aim of the present study was to characterize 601 human invasive isolates of L. monocytogenes in Sweden from 1986 to 2007 by using serotyping and pulsed-field gel electrophoresis. Since 1996, serovar 4b was permanently reduced to the second or third most common serovar in human cases in Sweden. During the latter period, 2000-2007, only 13% belonged to serovar 4b and 71% to 1/2a. The dendrogram, based on pulsovars, reveals two clusters with different serovars. Cluster 1 exhibits serovars 4b and 1/2b, whereas cluster 2 consists of serovar 1/2a. Serovar 1/2a seems to be more heterogeneous than serovar 4b.

Dynamic modeling of Listeria monocytogenes growth in pasteurized vanilla cream after postprocessing contamination

A product-specific model was developed and validated under dynamic temperature conditions for predicting the growth of Listeria monocytogenes in pasteurized vanilla cream, a traditional milk-based product. Model performance was also compared with Growth Predictor and Sym'Previus predictive microbiology software packages. Commercially prepared vanilla cream samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 102 CFU g(-1), and stored at 3, 5, 10, and 15 degrees C for 36 days. The growth kinetic parameters at each temperature were determined by the primary model of Baranyi and Roberts. The maximum specific growth rate (mu(max)) was further modeled as a function of temperature by means of a square root-type model. The performance of the model in predicting the growth of the pathogen under dynamic temperature conditions was based on two different temperature scenarios with periodic changes from 4 to 15 degrees C. Growth prediction for dynamic temperature profiles was based on the square root model and the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. Model performance was based on the bias factor (B(f)), the accuracy factor (A(f)), the goodness-of-fit index (GoF), and the percent relative errors between observed and predicted growth. The product-specific model developed in the present study accurately predicted the growth of L. monocytogenes under dynamic temperature conditions. The average values for the performance indices were 1.038, 1.068, and 0.397 for B(f), A(f), and GoF, respectively for both temperature scenarios assayed. Predictions from Growth Predictor and Sym'Previus overestimated pathogen growth. The average values of B(f), A(f), and GoF were 1.173, 1.174, 1.162, and 0.956, 1.115, 0.713 for [corrected] Growth Predictor and Sym'Previus, respectively.

Modeling the physiological state of the inoculum and CO2 atmosphere on the lag phase and growth rate of Listeria monocytogenes

In previous studies, the growth of L. monocytogenes has been modeled under different CO2 headspace concentrations; however, the inoculum cells were always in the stationary phase. In this study, the growth of L. monocytogenes under different CO2 concentrations as affected by the physiological state of the cells was investigated. Exponential-growth-phase, stationary-phase, dried, and starved cells were prepared and inoculated at 5 degrees C into brain heart infusion broths that had been preequilibrated under atmospheres of 0, 20, 40, 60, or 80% CO2 (the balance was N2). Lag-phase duration times (LDTs) and exponential growth rates were determined by enumerating cells at appropriate time intervals and by fitting the data to a three-phase linear function that has a lag period before the initiation of exponential growth. Longer LDTs were observed as the CO2 concentration increased, with no growth observed at 80% CO2. For example, the LDTs for exponential-phase, stationary-phase, starved, and dried cells were 2.21, 8.27, 9.17, and 9.67 days, respectively, under the 40% CO2 atmosphere. In general, exponential-growth-phase cells had the shortest LDT followed by starved cells and stationary-phase cells. Dried cells had the longest LDT. Exponential growth rates decreased as the CO2 concentrations increased. Once exponential growth was attained, no retained differences among the various initial physiological states of the cells for any of the atmospheres were observed in the exponential growth rates. The exponential growth rates under 0, 20, 40, 60, and 80% CO2 averaged 0.39, 0.37, 0.23, 0.23, and 0.0 log CFU/day, respectively. Dimensionless factors were calculated that describe the inhibitory action of CO2 on the LDTs and exponential growth rates for the various physiological states.

Modeling the effect of storage atmosphere on growth-no growth interface of Listeria monocytogenes as a function of temperature, sodium lactate, sodium diacetate, and NaCl

The effect of aerobic and anaerobic conditions on growth initiation by a 10-strain composite of Listeria monocytogenes (10(4) CFU/ml) was evaluated in tryptic soy broth with 0.6% yeast extract (TSBYE) as a function of 220 combinations of pH (3.82 to 7.42), sodium lactate (SL) (0 to 10%, vol/vol), and sodium diacetate (SD) (0 to 0.5%, wt/vol) at 10 or 30 degrees C (a slightly abusive and the optimal growth temperature, both above the growth limiting range of 0 to 3 degrees C for L. monocytogenes) in 96-well microplates. In addition, four probability-of-growth models were developed to quantify the effect of 346 aerobic and 346 anaerobic combinations of temperature (4 to 30 degrees C), SL (0 to 6%, vol/vol), and SD (0 to 0.5%, wt/vol) in the presence of NaCl (0.5 or 2.5%, wt/vol) on the growth-no growth responses of the same L. monocytogenes strain composite, with a microplate reader. Growth responses were evaluated turbidimetrically (620 nm) every 5 days for a total of 40 days. Data were modeled with logistic regression to determine the growth-no growth interfaces. The minimum pH values at which growth of L. monocytogenes occurred were higher under anaerobic than under aerobic conditions, and this difference was more evident at 10 degrees C or at higher SL and SD concentrations. The MIC of SD decreased with increasing SL levels. Anaerobic storage reduced the levels of SL-SD, allowing the growth of L. monocytogenes compared with aerobic storage, especially at low temperatures. In the presence of 2.5% NaCl, the MICs for SD were lower than those obtained with 0.5% NaCl, especially at 4 and 10 degrees C, or in the presence of 5 to 6% SL. The developed models for anaerobic incubation showed good performance (80% successful predictions; i.e., in 40 of 50 comparisons) with independent data from studies on survival-growth of L. monocytogenes on meat products. The study provides quantitative data on the antimicrobial activity of SL (0 to 10%) and SD (0 to 0.5%), temperature (4 to 30 degrees C), and pH (3.82 to 7.42) and on the probability of growth of L. monocytogenes under anaerobic or aerobic conditions in the presence of 0.5 or 2.5% NaCl, and hence, addresses important needs for risk assessment activities.

Response surface model for prediction of growth parameters from spores of Clostridium sporogenes under different experimental conditions

Clostridium sporogenes is considered to be a non-toxingenic equivalent of proteolytic Clostridium botulinum, and it also causes food spoilage. The effects of temperature (16.6-33.4 degrees C), pH value (5.2-6.8) and concentration of sodium chloride (0.6-7.4%) on the growth parameters of C. sporogenes spores were investigated. The growth curves generated within different conditions were fitted using Baranyi function. Two growth parameters (growth rate, GR; lag-time, LT) of the growth curves under combined effects of temperature, pH and sodium chloride were modeled using a quadratic polynomial equation of response surface (RS) model. Mathematical evaluation demonstrated that the standard error of prediction (%SEP) obtained by RS model was 1.033% for GR and was 0.166% for LT for model establishing. The %SEP for model validation were 43.717% and 5.895% for GR and LT, respectively. The root-mean-squares error (RMSE) was in acceptable range which was less than 0.1 for GR and was less than 8.0 for LT. Both the bias factor (B(f)) and accuracy factor (A(f)) approached 1.0, which were within acceptable range. Therefore, RS model provides a useful and accurate method for predicting the growth parameters of C. sporogenes spores, and could be applied to ensure food safety with respect to proteolytic C. botulinum control.

Detection and Characterization of Listeria monocytogenes in São Jorge (Portugal) Cheese Production

Listeria monocytogenes is a foodborne pathogen that can cause serious invasive disease in humans. Because human listeriosis cases have previously been linked to consumption of contaminated cheese, control of this pathogen throughout the cheese production chain is of particular concern. To understand the potential for L. monocytogenes transmission via São Jorge cheese, a Portuguese artisanal cheese variety that bears a Protected Denomination of Origin classification, 357 raw milk, curd, natural whey starter, and cheese samples representative of the production chain of this cheese were collected over one year and tested for the presence of L. monocytogenes and selected physicochemical parameters. Although neither L. monocytogenes nor other Listeria spp. were detected in whey, curd, or cheese samples, 2 of the 105 raw milk samples analyzed were positive for L. monocytogenes. These 2 raw milk isolates represented a ribotype that has previously been linked to multiple human listeriosis outbreaks and cases elsewhere, indicating the potential of these isolates to cause human listeriosis. On average, physicochemical parameters of São Jorge cheese ripened for 4 mo presented values that likely minimize the risk of L. monocytogenes outgrowth during ripening and storage (mean pH = 5.48; mean moisture = 37.79%; mean NaCl concentration = 4.73%). However, some cheese samples evaluated in this study were characterized by physicochemical parameters that may allow growth and survival of L. monocytogenes. Even though our results indicate that raw milk used for São Jorge cheese manufacture as well as finished products is rarely contaminated with L. monocytogenes, continued efforts to control the presence of this pathogen in the São Jorge cheese production chain are urged and are critical to ensure the safety of this product.

Dynamic modeling of Listeria monocytogenes growth in pasteurized milk

AIMS

The development and validation of a dynamic model for predicting Listeria monocytogenes growth in pasteurized milk stored at both static and dynamic temperature conditions.

METHODS AND RESULTS

Growth of inoculated L. monocytogenes in a commercial pasteurized whole milk product was monitored at various isothermal conditions from 1.5 to 16 degrees C. The kinetic parameters of the pathogen were modelled as a function of temperature using a square root type model, which was further validated using data from 92 published growth curves from eight different milk products. Compared to four published models for L. monocytogenes growth, the model developed in this study performed better, with a per cent discrepancy and bias of 49.1 and -1.01%, respectively. The performance of the model in predicting growth at dynamic temperature conditions was evaluated at four different fluctuating temperature scenarios with periodic temperature changes from -2 to 16 degrees C. The prediction of growth at dynamic storage temperature was based on the square root model in conjunction with the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. The per cent relative errors between the observed and the predicted growth of L. monocytogenes were less than 10% for all temperature scenarios tested.

CONCLUSIONS

Available models from experiments conducted in laboratory media may result in significant overestimation of L. monocytogenes growth in pasteurized milk because they do not take into account factors such as milk composition (e.g. natural antimicrobial compounds present in milk) and the interactions of the pathogen with the natural microflora. The product-targeted model developed in the present study showed a high performance in predicting growth of L. monocytogenes in pasteurized milk under both static and dynamic temperature conditions.

SIGNIFICANCE AND IMPACT OF THE STUDY

Temperature fluctuations often occur during the transportation and storage of pasteurized milk. A high performance, dynamic model for the growth of L. monocytogenes can be a useful tool for effective management and optimization of product safety and can lead to more realistic estimations of pasteurized-milk related safety risks.

Predictive modelling and validation of Listeria innocua growth at superatmospheric oxygen and carbon dioxide concentrations

The effect of superatmospheric oxygen and carbon dioxide concentrations on the growth of Listeria innocua, which was used as a model organism for the pathogen Listeria monocytogenes, was evaluated. The bacteria were grown on a nutrient agar surface at 7 degrees C. Three carbon dioxide levels (0%, 12.5% and 25%) were combined with different levels of high oxygen concentrations (above 20%) based on a mixture design. The applied oxygen concentrations did not significantly influence the growth. High CO2 concentrations, on the contrary, reduced the maximum specific growth rate and prolonged the lag time. An overall model to describe the growth of L. innocua under high carbon dioxide conditions was constructed based on nine growth experiments, using a weighted one-step regression procedure. The influence of carbon dioxide on lag time and maximum specific growth rate was described using Ratkowsky-type models and inserted in the Baranyi equation. The model described the growth very well. To assess the validity of the model, 14 additional experiments were carried out. There was a good correlation of the model predictions and observed validation data.

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.

METHODS AND RESULTS

Cardinal and square root type models including or not interactions between environmental factors and probability models were evaluated for their ability to describe the behaviour of L. monocytogenes in liquid dairy products, cheese, meat and seafood products. Models excluding interactions seemed sufficient to predict the growth rate of L. monocytogenes. However, the accurate prediction of growth/no-growth limits needed to take interactions into account. A complete and a simplified form (preservatives deducted) of a new cardinal model including interactions and parameter values were suggested to predict confidence limits for the growth rate of L. monocytogenes in food. This model could also be used for the growth probability prediction.

CONCLUSIONS

The new cardinal model including interactions was efficient to predict confidence limits for the growth rate of L. monocytogenes and its growth probability in liquid dairy products, meat and seafood products. In cheese, the model was efficient to predict the absence of growth of the pathogen.

SIGNIFICANCE AND IMPACT OF THE STUDY

The suggested model can be used for risk assessment and risk management concerning L. monocytogenes in dairy, meat and seafood products.

Quantifying the robustness of a broth-based model for predicting Listeria monocytogenes growth in meat and poultry products

Given the importance of Listeria monocytogenes as a risk factor in meat and poultry products, there is a need to evaluate the relative robustness of predictive growth models applied to meat products. The U.S. Department of Agriculture-Agricultural Research Service Pathogen Modeling Program is a tool widely used by the food industry to estimate pathogen growth, survival, and inactivation in food. However, the robustness of the Pathogen Modeling Program broth-based L. monocytogenes growth model in meat and poultry application has not, to our knowledge, been specifically evaluated. In the present study, this model was evaluated against independent data in terms of predicted microbial counts and covered a range of conditions inside and outside the original model domain. The robustness index was calculated as the ratio of the standard error of prediction (root mean square error of the model against an independent data set not used to create the model) to the standard error of calibration (root mean square error of the model against the data set used to create the model). Inside the calibration domain of the Pathogen Modeling Program, the best robustness index for application to meat products was 0.37; the worst was 3.96. Outside the domain, the best robustness index was 0.40, and the worst was 1.22. Product type influenced the robustness index values (P < 0.01). In general, the results indicated that broth-based predictive models should be validated against independent data in the domain of interest; otherwise, significant predictive errors can occur.

Genetic diversity and safety aspects of enterococci from slightly fermented sausages

AIMS

To determine the biodiversity of enterococci from slightly fermented sausages (chorizo and fuet) at species and strain level by molecular typing, while considering their safety aspects.

METHODS AND RESULTS

Species-specific PCR and partial sequencing of 16S rRNA and sodA genes were used to identify enterococcal population. Enterococcus faecium was the most frequently isolated species followed by E. faecalis, E. hirae and E. durans. Randomly amplified polymorphic DNA (RAPD)-PCR revealed species-specific clusters and allowed strain typing. Sixty strains of 106 isolates exhibited different RAPD profiles indicating a high genetic variability. All the E. faecalis strains carried virulence genes (efaAfs, esp, agg and gelE) and all E. faecium isolates carried efaAfm gene. Enterococcus faecalis showed higher antibiotic resistance than the other species. Only one E. faecium strain showed vanA genotype (high-level resistance to glycopeptides) and E. gallinarum and E. casseliflavus/flavescens isolates showed vanC1 and vanC2/C3 genotypes (low-level resistance only to vancomycin) respectively.

CONCLUSIONS

E. faecalis has been mainly associated with virulence factors and antimicrobial multi-resistance and, although potential risk for human health is low, the presence of this species in slightly fermented sausages should be avoided to obtain high quality products.

SIGNIFICANCE AND IMPACT OF THE STUDY

The enterococcal population of slightly fermented sausages has been thoroughly characterized. Several relevant safety aspects have been revealed.

Predictive modeling of microorganisms: LAG and LIP in monotonic growth

The variety of models that are currently being used in "Predictive Microbiology" or "Microbial Ecology" aiming at reproducing the growth curve of microorganisms motivates this study. It is widely agreed that no model can reproduce generically and consistently the "LAG Phase" of microorganism growth. To promote the objective of "predictive modeling", we present here a model that was derived from first biological and physical principles, which is shown to reproduce qualitatively as well as quantitatively all typical features captured experimentally in microorganism growth. In particular, this paper focuses on capturing and controlling of the "LAG Phase" a typical phase in microorganisms growth, at the initial growth stages, as well as the inflection point on the "ln curve" of the cell concentration, i.e. a Logarithmic Inflection Point referred here as "LIP". The proposed model also captures the Logistic Growth curve as a special case. Comparison of the solutions obtained from the proposed model with experimental data confirms its quantitative validity, as well as its ability to recover a wide range of qualitative features captured in experiments.

Changes in growth, rRNA content, and cell morphology of Listeria monocytogenes induced by CO2 up- and downshift

Cell morphology, rRNA content, and growth were examined for Listeria monocytogenes LO28 and EGD, respectively, grown in brain-heart infusion (BHI) and on slices of sausage at 10 degrees C in 100% CO2, 100% N2, and air. In CO2, filamentous cells were formed by both strains on sausage slices and by L. monocytogenes EGD in BHI. Filamentation was not induced by anaerobiosis only. Fluorescent in situ rRNA hybridization (FISH) of cells grown in BHI showed that the L. monocytogenes EGD filaments consisted of chains of individual slightly elongated cells. The rods formed by L. monocytogenes LO28 had the same size in air and CO2. Septation and cell division were induced in the filaments after a CO2 downshift (i.e., exposure to air). In BHI, the number of colony forming units increased rapidly when L. monocytogenes EGD grown in CO2 was exposed to air whereas the number of L. monocytogenes LO28 remained almost unchanged. On sausage slices, the number of colony forming units also increased rapidly for both strains in response to CO2 downshift. Large variations in rRNA content of individual cells were observed in the tested scenarios. The results demonstrate the risk of underestimating the number of infectious units under circumstances where filamentation may occur. Furthermore, the study illustrates the lack of residual inhibitory effect of CO2 in this type of products after opening.

Effect of chemicals on the microbial evolution in foods

In contrast with most chemical hazardous compounds, the concentration of food pathogens changes during processing, storage, and meal preparation, making it difficult to estimate the number of microorganisms or the concentration of their toxins at the moment of ingestion by the consumer. These changes are attributed to microbial proliferation, survival, and/or inactivation and must be considered when exposure to a microbial hazard is assessed. The number of microorganisms can also change as a result of physical removal, mixing of food ingredients, partitioning of a food product, or cross-contamination (M. J. Nauta. 2002. Int. J. Food Microbiol. 73:297-304). Predictive microbiology, i.e., relating these microbial evolutionary patterns to environmental conditions, can therefore be considered a useful tool for microbial risk assessment, especially in the exposure assessment step. During the early development of the field (late 1980s and early 1990s), almost all research was focused on the modeling of microbial growth over time and the influence of temperature on this growth. Later, modeling of the influence of other intrinsic and extrinsic parameters garnered attention. Recently, more attention has been given to modeling of the effects of chemicals on microbial inactivation and survival. This article is an overview of different applied strategies for modeling the effect of chemical compounds on microbial populations. Various approaches for modeling chemical growth inhibition, the growth-no growth interface, and microbial inactivation by chemicals are reviewed.

The effect of growth atmosphere on the ability of Listeria monocytogenes to survive exposure to acid, proteolytic enzymes and bile salts

Four isolates of Listeria monocytogenes from food, human and environmental sources were grown separately in broth (pH 6.0 at 8 degrees C) under atmospheres of air, 100% N(2), 40% CO(2):60% N(2) or 100% CO(2). Exponential and stationary phase cells were harvested to determine if growth atmosphere and growth phase influenced this pathogen's ability to survive exposure to an acid environment coupled with proteolytic enzymes, and the activity of bile salts. In general, isolates were more resistant to the acid environment than the bile salts environment and stationary phase cells were significantly more resistant to both environments than exponential phase cells. Irrespective of prior growth atmosphere, none of the isolates when in exponential phase remained detectable following full exposure to the acid environment (110 min at 37 degrees C) or the bile environment (3 h at 37 degrees C). With the exception of one isolate grown under the atmosphere of 40% CO(2):60% N(2), all isolates when in stationary phase were detectable following full exposure to the acid environment but death rates varied significantly. Stationary phase cells of all isolates grown under 40% CO(2):60% N(2) and 100% CO(2) were highly susceptible to the bile salts environment: cells were not detectable after a 2-min exposure whereas stationary phase cells grown under air or 100% N(2) were recovered following full exposure to the bile environment. Survival curves were characterised by a population decline of at least 3 log(10)/ml (from an initial level of 7 log(10) CFU/ml) in the first 15 min; thereafter a constant population number of approximately 4 log(10)/ml was maintained over the remaining exposure period. No survival was observed when stationary phase cells of L. monocytogenes FRRB 2538 grown in air and 100% N(2) were subjected to the acid environment followed by immediate exposure to the bile salts environment. The results showed that growth atmosphere and growth phase could influence survival of this pathogen against conditions that imitate the extremes of the most important nonspecific defence mechanisms against microbial infection: the acid environment of the stomach coupled with the activity of proteolytic enzymes, and the activity of bile salts in the small intestine.

Effects of carbon dioxide on bacterial growth parameters in milk as measured by conductivity

Inhibition of bacterial growth by dissolved carbon dioxide (CO2) has been well established in many foods including dairy foods. However, the effects of dissolved CO2 on specific growth parameters such as length of lag phase, time to maximum growth rate, and numbers of organisms at the stationary phase have not been quantified for organisms of concern in milk. The effect of dissolved CO2 concentrations of 0.6 to 61.4 mM on specific bacterial growth parameters in raw or single organism inoculated sterile milk was determined at 15 degrees C by conductance. Commingled raw or sterile milks were amended to a final concentration of 0.5 mg/ml each of urea and arginine HCl. Sterile milks were inoculated singly with one of six different microorganisms to a final concentration of approximately 10(2) to 10(3) cfu/ml; raw milk was adjusted to a final indigenous bacterial population of approximately 10(3) cfu/ml. Conductivity of the milk was recorded every 60 s over 4 to 5 d in a circulating apparatus at 15 degrees C. Conductivity values were fit to Gompertz equations and growth parameters calculated. Conductance correlated with plate counts and was satisfactory for monitoring microbial growth. Data fit the Gompertz equation with high correlation (R2 = 0.96 to 1.00). In all cases, dissolved CO2 significantly inhibited growth of raw milk bacteria, influencing lag, exponential, and stationary growth phases as well as all tested monocultures.

Development and validation of growth model for Yersinia enterocolitica in cooked chicken meats packaged under various atmosphere packaging and stored at different temperatures

Mathematical models that can predict the growth of Yersinia enterocolitica in chicken meats were evaluated in this study. The growth curves for Y. enterocolitica in chicken meats variously packaged (air, vacuum, and modified atmosphere packaging [MAP]) and stored at various temperatures (4, 10, 16, 22, 28, and 34 degrees C) were constructed. The Gompertz model was applied to fit each of the experimental curves for the conditions mentioned above. The variations in the parameters, including lag time (lambda) and specific growth rate (mu), at various temperatures were then described by the following models: the variations in lag time were described by the Adair and Smith models and the variations in the specific growth rate were described by the Ratkowsky and Zwietering models. The various models were then compared using graphical and mathematical analyses such as mean square error (MSE), regression coefficient (r2), bias factor, and accuracy factor. The results indicate that the mean r values in the Gompertz model for chicken meats packaged in air, vacuum, and MAP were 0.99, 0.99, and 0.95, respectively. The lag time modeled with the Adair and Smith functions exhibited a greater variance and demonstrated larger errors. The MSEs were 0.0015 and 0.0017 for Ratkowsky and Zwietering models, respectively. The r2 values in the Ratkowsky and Zwietering models were both 0.99. The bias factor was 1.017 for the Ratkowsky model and 1.096 for the Zwietering model. The accuracy factor of the Zwietering model was 1.174, which was lower than that in the Ratkowsky model (1.275), indicating that the former model was more accurate than the latter in predicting the specific growth rate of Y. enterocolitica in chicken meats.

Behaviour of Listeria monocytogenes and autochthonous flora on meat stored under aerobic, vacuum and modified atmosphere packaging conditions with or without the presence of oregano essential oil at 5 degrees C

The effect of aerobic, modified atmosphere packaging (MAP; 40% CO2/30% O2/30% N2) and vacuum packaging (VP) on the growth/survival of Listeria monocytogenes on sterile and naturally contaminated beef meat fillets was studied in relation to film permeability and oregano essential oil. The dominant micro-organism(s) and the effect of the endogenous flora on the growth/survival of L. monocytogenes were dependent on the type of packaging film. The fact that L. monocytogenes increased whenever pseudomonads dominated, i.e. aerobic storage and MAP/VP in high-permeability film, and even earlier than on sterile tissue, suggests that this spoilage group enhanced growth of the pathogen. Brochothrix thermosphacta constituted the major proportion of the total microflora in MAP/VP within the low-permeability film, where no growth of L. monocytogenes was detected either on naturally contaminated or sterile meat fillets. The addition of 0.8% (v/w) oregano essential oil resulted in: (i) an initial reduction of 2-3 log10 of the majority of the bacterial population, with lactic acid bacteria and L. monocytogenes indicating the most apparent decrease in all gaseous environments, and (ii) limited growth aerobically and survival/death of L. monocytogenes in MAP/VP, regardless of film permeability.

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.

Modelling the growth rate of Listeria monocytogenes with a multiplicative type model including interactions between environmental factors

A multiplicative secondary model previously published to describe independently the effects of environmental factors on the growth rate of Listeria monocytogenes (Augustin and Carlier, 2000) was improved by taking into account interactions between these environmental factors. The proposed model allowed to decrease the rate of fail-safe growth predicted from 13.5% to 12.1% and the rate of fail-dangerous no growth predicted from 16.1% to 7.1%.

Comparison of simple neural networks and nonlinear regression models for descriptive modeling of Lactobacillus helveticus growth in pH-controlled batch cultures

A set of 20 Lactobacillus helveticus growth curves was obtained from pH-controlled batch cultures with different pH setpoints, whey permeate and yeast extract concentrations. To find the best descriptive model of the biomass concentration versus time (y = X(t)) growth curve, fitting results of a large number of models were compared with statistical and approximate methods. Models studied included simple neural networks, reparameterized Logistic, Gompertz, Richards, Schnute, Weibull, and Morgan-Mercier-Flodin models, Amrane-Prigent model, and four new models based on autonomous growth functions. Simple neural networks with only four weights were good descriptive models of the growth curves and fitting qualities were similar to those of the best existing four-parameter models, such as the Logistic model. However, meaningful parameters had to be calculated numerically and use of simple neural networks yielded no distinctive advantages over other models. A new five-parameter model, based on an autonomous growth function, yielded the best fitting results, even when the number of model parameters was accounted for in the comparisons. However, the maximum specific growth rate was not always well estimated. Therefore the five-parameter Richards model was chosen as the best descriptive model of the growth curve.

Validation of predictive models describing the growth of Listeria monocytogenes

In this study, predictions for growth rate of Listeria on food products were evaluated by both general applicable models and specific growth models. Literature values, obtained from a large number of publications, for growth rates in/on a variety of foods were compared by graphical and mathematical analysis with predictions given by various models. Apart for the great advantage of being generally applicable, the general models performed best. However, only small differences between the various models were observed. Model predictions were accurate within a factor of about two to four, depending on the type of product. The predictions should therefore not be considered as absolute; it is important to understand the limitations of the performance of models. All results and all assumptions should be criticised, but in many cases the accuracy will be sufficient to use these types of models as a tool in management decisions.

Shelf life of modified atmosphere packed cooked meat products: a predictive model

The effect of temperature, concentration of dissolved CO2 and water activity on the growth of Lactobacillus sake was investigated by developing predictive models for the lag phase and the maximum specific growth rate of this specific spoilage organism for gas-packed cooked meat products. Two types of predictive model were compared: an extended Ratkowsky model and a response surface model. In general, response surface models showed a slightly better correlation, but the response surface model for the maximum specific growth rate showed illogical predictions at low water activities. The concentration of dissolved CO2 proved to be a significant independent variable for the maximum specific growth rate as well as for the lag phase of L. sake. Synergistic actions on the shelf life-extending effect were noticed between temperature and dissolved CO2, as well as between water activity and dissolved CO2. The developed models were validated by comparison with the existing model of Kant-Muermans et al. (1997) and by means of experiments in gas-packed cooked meat products. Both developed models proved to be useful in the prediction of the microbial shelf life of gas-packed cooked meat products.

The combined affects of modified atmosphere, temperature, nisin and ALTA 2341 on the growth of Listeria monocytogenes

A cocktail of seven Listeria monocytogenes isolates of food, human and environmental origin was used to assess the antilisterial activity of the bacteriocins nisin and ALTA 2341 in combination with various atmospheres: air, 100% N2, 40% CO2:60% N2, or 100% CO2. Buffered tryptone soya broth (pH 6.0) was used as the growth medium and incubation was at 4 degrees C (21 days) or 12 degrees C (7 days), or when temperature fluctuated between these values for defined periods. It was observed that atmosphere alone influenced the growth rate of L. monocytogenes, with 100% CO2 exerting the greatest inhibition. A 5 log population increase was observed in all atmospheres after 7 days at 12 degrees C. At 4 degrees C a 4-5 log population increase was observed in air, 100% N2 and 40% CO2:60% N2 within 21 days. Growth was prevented by 100% CO2. In the presence of nisin (400 IU/ml), an increase in the lag phase was observed before growth (5 log population increase after 7 days) in all atmospheres at 12 degrees C. This effect was enhanced at 4 degrees C where a maximum 2 log population increase was observed in all atmospheres except 100% CO2, in which growth was prevented. Increasing the concentration of nisin to 1250 IU/ml prevented L. monocytogenes growth in all atmosphere combinations at 4 and 12 degrees C. Two concentrations of ALTA 2341 were also tested. In the presence of 0.1% ALTA 2341 and at 12 degrees C, a 3-5 log population increase was observed in all atmospheres with the exception of 100% CO2, which prevented L. monocytogenes growth. At 4 degrees C, growth was observed in the combination of 0.1% ALTA 2341 and 100% N2 only (3 log population increase). Use of a higher concentration of ALTA 2341 (1.0%) resulted in a population decrease below the detection level within 24 h in all atmosphere/temperature combinations. Re-growth occurred in the presence of 1.0% ALTA 2341 in all atmospheres at 12 degrees C, and in combination with air or 100% N2 at 4 C. When the effectiveness of either nisin or ALTA 2341 and atmosphere was tested against L. monocytogenes as temperature fluctuated for periods between 4 and 12 degrees C, only the combination of 100% CO2 and 1.0% ALTA 2341 prevented growth. Cells surviving exposure to nisin or ALTA 2341 were recovered from 28 of the 32 combinations tested that contained bacteriocin. Nisin survivors remained sensitive to the bacteriocin. ALTA 2341 survivors had become resistant to the bacteriocin.

Predictive model of the effect of CO2, pH, temperature and NaCl on the growth of Listeria monocytogenes

The growth responses of L. monocytogenes as affected by CO2 concentration (0-100% v/v, balance nitrogen), NaCl concentration (0.5-8.0% w/v), pH (4.5-7.0) and temperature (4-20 degrees C) were studied in laboratory medium. Growth curves were fitted using the model of Baranyi and Roberts, and specific growth rates derived from the curve fit were modelled. Predictions for specific growth rate, doubling time and time to a 1000-fold increase could be made for any combination of conditions within the matrix. Predictions of growth from the model were compared with published data and this showed the model to be suitable for predicting growth of L. monocytogenes in a range of foods packaged under a modified atmosphere.