Modeling and predicting the growth of lactic acid bacteria in lightly preserved seafood and their inhibiting effect on Listeria monocytogenes

Microbiological and physicochemical profile of Italian steak tartare and predicting growth potential of Listeria monocytogenes

In the present study, growth potential of Listeria monocytogenes in steak tartare samples taken at retail and belonging to 13 brands marketed in Northern Italy was investigated. The samples were submitted to microbiological and chemical-physical characterization. The data obtained were used as inputs for the application of the predictive microbiology software FSSP that allows the estimation of the growth of L. monocytogenes during the shelf-life. Lactic acid bacteria, the main component of the microflora, gave variable counts among the brands (from 3.38 to 6.24 log CFU/g). pH and aw values were always higher than 5.3 and 0.96, respectively, thus they could not be considered as single efficient hurdles to prevent the growth of L. monocytogenes according to the EC Reg. 2073/2005; the same was observed for salt content (constantly <2 %) and nitrites (not quantifiable in all the samples, even if declared in some labels). Nevertheless, the combination of all the hurdles, evaluated by predictive microbiology using critical development factors, resulted in an estimated growth <0.5 log CFU/g throughout the shelf life; this output allowed us to consider all the steak tartare analysed as unfavourable substrate for L. monocytogenes growth. The information obtained could be useful for tartare producers as well as for competent authority to evaluate the effective risk concerning these typology of products.

Development of a quantitative microbiological spoilage risk assessment (QMSRA) model for cooked ham sliced at retail

A quantitative microbiological spoilage risk assessment model (QMSRA) for cooked ham sliced at retail was developed based on a stochastic growth model for lactic acid bacteria (LAB), which are considered as the specific spoilage organisms (SSO), and a "spoilage-response" relationship characterizing the variability in consumer's perception of spoilage. In a simulation involving 10,000 cooked ham purchases, the QMSRA model predicted a median of zero spoilage events for up to 4.5 days of storage. After storage times of 5 and 6 days, the model predicted 1,790 and 8,570 spoilage events, respectively. A sensitivity analysis showed that domestic storage temperature was the most significant factor affecting LAB concentration in cooked ham, followed by the LAB contamination level at slicing. A scenario analysis was performed testing better temperature control of consumer's refrigerators, better hygiene conditions during slicing and a combination of the two strategies. Among the tested scenarios, a 2 log reduction in the LAB contamination at slicing combined with a 2 °C decrease in domestic storage temperature resulted in zero risk of spoilage for up to 12 days of storage. The QMSRA model developed in the present study can be a useful tool for quality management decisions.

Microbiological safety of aged meat

The impact of dry-ageing of beef and wet-ageing of beef, pork and lamb on microbiological hazards and spoilage bacteria was examined and current practices are described. As 'standard fresh' and wet-aged meat use similar processes these were differentiated based on duration. In addition to a description of the different stages, data were collated on key parameters (time, temperature, pH and aw) using a literature survey and questionnaires. The microbiological hazards that may be present in all aged meats included Shiga toxin-producing Escherichia coli (STEC), Salmonella spp., Staphylococcus aureus, Listeria monocytogenes, enterotoxigenic Yersinia spp., Campylobacter spp. and Clostridium spp. Moulds, such as Aspergillus spp. and Penicillium spp., may produce mycotoxins when conditions are favourable but may be prevented by ensuring a meat surface temperature of -0.5 to 3.0°C, with a relative humidity (RH) of 75-85% and an airflow of 0.2-0.5 m/s for up to 35 days. The main meat spoilage bacteria include Pseudomonas spp., Lactobacillus spp. Enterococcus spp., Weissella spp., Brochothrix spp., Leuconostoc spp., Lactobacillus spp., Shewanella spp. and Clostridium spp. Under current practices, the ageing of meat may have an impact on the load of microbiological hazards and spoilage bacteria as compared to standard fresh meat preparation. Ageing under defined and controlled conditions can achieve the same or lower loads of microbiological hazards and spoilage bacteria than the variable log10 increases predicted during standard fresh meat preparation. An approach was used to establish the conditions of time and temperature that would achieve similar or lower levels of L. monocytogenes and Yersinia enterocolitica (pork only) and lactic acid bacteria (representing spoilage bacteria) as compared to standard fresh meat. Finally, additional control activities were identified that would further assure the microbial safety of dry-aged beef, based on recommended best practice and the outputs of the equivalence assessment.

Potential of multiparametric characterization of foodstuffs by nuclear magnetic resonance to better predict microbial behavior

Numerous predictive microbiology models have been proposed to describe bacterial population behaviors in foodstuffs. These models depict the growth kinetics of particular bacterial strains based on key physico-chemical parameters of food matrices and their storage temperature. In this context, there is a prominent issue to accurately characterize these parameters, notably pH, water activity (a_w ), and NaCl and organic acid concentrations. Usually, all these product features are determined using one destructive analysis per parameter at macroscale (>5 g). Such approach prevents an overall view of these characteristics on a single sample. Besides, it does not take into account the intra-product microlocal variability of these parameters within foods. Nuclear magnetic resonance (NMR) is a versatile non-invasive spectroscopic technique. Experiments can be recorded successively on a same collected sample without damaging it. In this work, we designed a dedicated NMR approach to characterize the microenvironment of foods using 10-mg samples. The multiparametric mesoscopic-scale approach was validated on four food matrices: a smear soft cheese, cooked peeled shrimps, cold-smoked salmon, and smoked ham. Its implementation in situ on salmon fillets enabled to observe the intra-product heterogeneity and to highlight the impact of process on the spatial distribution of pH, NaCl, and organic acids. This analytical development and its successful application can help address the shortcomings of monoparametric methods traditionally used for predictive microbiology purposes.

Microbial Safety and Sensory Analyses of Cold-Smoked Salmon Produced with Sodium-Reduced Mineral Salts and Organic Acid Salts

Cold-smoked (CS) salmon contains high levels of sodium salts, and excess dietary sodium intake is associated with an array of health complications. CS salmon may also represent a food safety risk due to possible presence and growth of the foodborne pathogen Listeria monocytogenes which may cause fatal human infections. Here we determine how reformulated CS salmon using commercial sodium-reduced salt replacers containing KCl (e.g., Nutek, Smart Salt, SOLO-LITE) and acetate-based preservative salts (Provian K, proviant NDV) affect sensory properties, quality, and microbial safety. Initial sensory screening of sodium-reduced CS salmon was followed by L. monocytogenes growth analyses in selected variants of reformulated CS salmon, and finally by analyses of CS salmon variants produced in an industrial smokehouse. Projective mapping indicated overall minor sensory changes in sodium-replaced samples compared with a conventional product with NaCl. Growth of L. monocytogenes was temperature-dependent (4 °C vs. 8 °C storage) with similar growth in sodium-reduced and conventional CS salmon. The addition of 0.9% of the preservative salts Provian K or Provian NDV gave up to 4 log lower L. monocytogenes counts in both sodium-reduced and conventional cold-smoked salmon after 29 days of chilled storage. No changes in pH (range 6.20−6.33), aw levels (range 0.960−0.973), or weight yield (96.8 ± 0.2%) were evident in CS salmon with salt replacers or Provian preservative salts. Analyses of CS salmon produced with selected mineral salt and preservative salt combinations in an industrial salmon smokery indicated marginal differences in sensory properties. Samples with the preservative salt Provian NDV provided L. monocytogenes growth inhibition and low-level total viable counts (<2.8 log/g) dominated by Photobacterium and Carnobacterium during storage. Production of sodium-reduced CS salmon with inhibiting salts provides a simple method to achieve a healthier food product with increased food safety.

Use of Food Spoilage and Safety Predictor for an “A Priori” Modeling of the Growth of Lactic Acid Bacteria in Fermented Smoked Fish Products

Fermentation is one of the oldest methods to assure the safety and quality of foods, and to prolong their shelf life. However, a successful fermentation relies on the correct kinetics depending on some factors (i.e., ingredients, preservatives, temperature, inoculum of starter cultures). Predictive microbiology is a precious tool in modern food safety and quality management; based on the product characteristics and the conditions occurring in food processing, the inactivation of or increase in microbial populations could be accurately predicted as a function of the relevant intrinsic or extrinsic variables. The main aim of this study was the optimization of the formula of a smoked fermented fish product using predictive modeling tools (tertiary and secondary models) in order to define the role of each factor involved in the formulation and assure a correct course of fermentation. Product optimization was conducted through the software Food Spoilage and Safety Predictor (FSSP), by modeling the growth of lactic acid bacteria (LAB) as a function of some key parameters such as temperature, pH, salt, liquid smoke, carbon dioxide, and nitrites. The variables were combined through a fractional design of experiments (DoE) (3^k-p), and the outputs of the software, i.e., the maximal growth rate (μ_max) and the time to attain the critical threshold (t_crit), were modeled through a multiple regression procedure. The simulation, through FSSP and DoE, showed that liquid smoke is the most critical factor affecting fermentation, followed by temperature and salt. Concerning temperature, fermentation at 20–25 °C is advisable, although a low fermentation temperature is also possible. Other parameters are not significant.

A mathematical model to predict the antilisteria bioprotective effect of Latilactobacillus sakei CTC494 in vacuum packaged cooked ham

Biopreservation is a strategy that has been extensively covered by the scientific literature from a variety of perspectives. However, the development of quantitative modelling approaches has received little attention, despite the usefulness of these tools for the food industry to assess the performance and to set the optimal application conditions. The objective of this study was to evaluate and model the interaction between the antilisteria strain Latilactobacillus sakei CTC494 (sakacin K producer) and Listeria monocytogenes in vacuum-packaged sliced cooked ham. Cooked ham was sliced under aseptic conditions and inoculated with L. monocytogenes CTC1034 and/or L. sakei CTC494 in monoculture and coculture at 10:10, 10:10³ and 10:10⁵ cfu/g ratios of pathogen:bioprotective cultures. Samples were vacuum packaged and stored at isothermal temperature (2, 5, 10 and 15 °C). The growth of the two bacteria was monitored by plate counting. The Logistic growth model was applied to estimate the growth kinetic parameters (N₀, λ, μ_max, N_max). The effect of storage temperature was modelled using the hyperbola (λ) and Ratkowsky (μ_max) models. The simple Jameson-effect model, its modifications including the N_cri and the interaction γ factor, and the predator-prey Lotka Volterra model were used to characterize the interaction between both microorganisms. Two additional experiments at non-isothermal temperature conditions were also carried out to assess the predictive performance of the developed models through the Acceptable Simulation Zone (ASZ) approach. In monoculture conditions, L. monocytogenes and L. sakei CTC494 grew at all temperatures. In coculture conditions, L. sakei CTC494 had an inhibitory effect on L. monocytogenes by lowering the N_max, especially with increasing levels of L. sakei CTC494 and lowering the storage temperature. At the lowest temperature (2 °C) L. sakei CTC494 was able to completely inhibit the growth of L. monocytogenes when added at a concentration 3 and 5 Log higher than that of the pathogen. The inhibitory effect of the L. sakei CTC494 against L. monocytogenes was properly characterized and modelled using the modified Jameson-effect with interaction γ factor model. The developed interaction model was tested under non-isothermal conditions, resulting in ASZ values ≥83%. This study shows the potential of L. sakei CTC494 in the biopreservation of vacuum-packaged cooked ham against L. monocytogenes. The developed interaction model can be useful for the industry as a risk management tool to assess and set biopreservation strategies for the control of L. monocytogenes in cooked ham.

Quantifying the bioprotective effect of Lactobacillus sakei CTC494 against Listeria monocytogenes on vacuum packaged hot-smoked sea bream

In this study, the bioprotective potential of Lactobacillus sakei CTC494 against Listeria monocytogenes CTC1034 was evaluated on vacuum packaged hot-smoked sea bream at 5 °C and dynamic temperatures ranging from 3 to 12 °C. The capacity of three microbial competition interaction models to describe the inhibitory effect of L. sakei CTC494 on L. monocytogenes was assessed based on the Jameson effect and Lotka-Volterra approaches. A sensory analysis was performed to evaluate the spoiling capacity of L. sakei CTC494 on the smoked fish product at 5 °C. Based on the sensory results, the bioprotection strategy against the pathogen was established by inoculating the product at a 1:2 ratio (pathogen:bioprotector, log CFU/g). The kinetic growth parameters of both microorganisms were estimated in mono-culture at constant storage (5 °C). In addition, the inhibition function parameters of the tested interaction models were estimated in co-culture at constant and dynamic temperature storage using as input the mono-culture kinetic parameters. The growth potential (δ log) of L. monocytogenes, in mono-culture, was 3.5 log on smoked sea bream during the experimental period (20 days). In co-culture, L. sakei CTC494 significantly reduced the capability of L. monocytogenes to grow, although its effectiveness was temperature dependent. The LAB strain limited the growth of the pathogen under storage at 5 °C (<1 log increase) and at dynamic profile 2 (<2 log increase). Besides, under storage at dynamic profile 1, the growth of L. monocytogenes was inhibited (<0.5 log increase). These results confirmed the efficacy of L. sakei CTC494 for controlling the pathogen growth on the studied fish product. The Lotka-Volterra competition model showed slightly better fit to the observed L. monocytogenes growth response than the Jameson-based models according to the statistical performance. The proposed modelling approach could support the assessment and establishment of bioprotective culture-based strategies aimed at reducing the risk of listeriosis linked to the consumption of RTE hot-smoked sea bream.

Modeling the Growth and Interaction Between Brochothrix thermosphacta, Pseudomonas spp., and Leuconostoc gelidum in Minced Pork Samples

The aim of this study was to obtain the growth parameters of specific spoilage micro-organisms previously isolated in minced pork (MP) samples and to develop a three-spoilage species interaction model under different storage conditions. Naturally contaminated samples were used to validate this approach by considering the effect of the food microbiota. Three groups of bacteria were inoculated on irradiated samples, in mono- and in co-culture experiments (n = 1152): Brochothrix thermosphacta, Leuconostoc gelidum, and Pseudomonas spp. (Pseudomonas fluorescens and Pseudomonas fragi). Samples were stored in two food packaging [food wrap and modified atmosphere packaging (CO2 30%/O2 70%)] at three isothermal conditions (4, 8, and 12°C). Analysis was carried out by using both 16S rRNA gene amplicon sequencing and classical microbiology in order to estimate bacterial counts during the storage period. Growth parameters were obtained by fitting primary (Baranyi) and secondary (square root) models. The food packaging shows the highest impact on bacterial growth rates, which in turn have the strongest influence on the shelf life of food products. Based on these results, a three-spoilage species interaction model was developed by using the modified Jameson-effect model and the Lotka Volterra (prey-predator) model. The modified Jameson-effect model showed slightly better performances, with 40-86% out of the observed counts falling into the Acceptable Simulation Zone (ASZ). It only concerns 14-48% for the prey-predator approach. These results can be explained by the fact that the dynamics of experimental and validation datasets seems to follow a Jameson behavior. On the other hand, the Lotka Volterra model is based on complex interaction factors, which are included in highly variable intervals. More datasets are probably needed to obtained reliable factors, and so better model fittings, especially for three- or more-spoilage species interaction models. Further studies are also needed to better understand the interaction of spoilage bacteria between them and in the presence of natural microbiota.

Growth Potential of Listeria monocytogenes in Chef-Crafted Ready-to-Eat Fresh Cheese-Filled Pasta Meal Stored in Modified Atmosphere Packaging

This study evaluated the growth of lactic acid bacteria (LAB) in a fresh, filled-pasta meal, stored in modified atmosphere packaging and the influence of lactic acid (LA) and pH on the growth of Listeria monocytogenes (Lm). Samples were taken from three lots manufactured by a local catering company and stored at both 6 and 14°C. LAB numbers, LA concentration, pH, and the presence of Lm were evaluated at 1, 4, 6, 8, 10, 12, and 14 days of shelf life and the undissociated LA concentration ([LA]) was calculated. The LAB maximum cell density was greater in the products stored at 14°C than those stored at 6°C (10.1 ± 1.1 versus 5.6 ± 1.5 log CFU/g) and [LA] at 14 days was 9 to 21 ppm at 6°C and 509 to 1,887 ppm at 14°C. Challenge tests were made to evaluate the interference of LAB and [LA] on Lm growth. Aliquots of the samples (25 g) were inoculated at 1 to 10 days of shelf life and incubated at 9°C for 7 days, and the difference between Lm numbers at the end and at the beginning of the test (δ) was calculated. Logistic regression was used to model the probability of growth of Lm as a function of LAB and [LA]. The products inoculated at 1 day of shelf life had δ values between 4.2 and 5.6 log CFU/g, but the growth potential was progressively reduced during the shelf life. Lm growth was never observed in the products stored at 14°C. In those stored at 6°C, it grew only in the samples with LAB <5.7 log CFU/g. LAB interaction might thus inhibit the growth of Lm in temperature-abused products and limit its growth in refrigerated products. Logistic regression estimated that the probability of Lm growth was <10% if LAB was >6.6 log CFU/g or log[LA] was >2.2 ppm. The growth or inactivation kinetic of Lm was investigated with a homogenate of three samples with LAB numbers close to the maximum population density. After an initial growth, a subsequent reduction in the number of Lm was observed. This means that the maximum numbers of Lm might not be detected at the end of the product shelf life.

Modelling the interaction of the sakacin-producing Lactobacillus sakei CTC494 and Listeria monocytogenes in filleted gilthead sea bream (Sparus aurata) under modified atmosphere packaging at isothermal and non-isothermal conditions

The objective of this work was to quantitatively evaluate the effect of Lactobacillus sakei CTC494 (sakacin-producing bioprotective strain) against Listeria monocytogenes in fish juice and to apply and validate three microbial interaction models (Jameson, modified Jameson and Lotka Volterra models) through challenge tests with gilthead sea bream (Sparus aurata) fillets under modified atmosphere packaging stored at isothermal and non-isothermal conditions. L. sakei CTC494 inhibited L. monocytogenes growth when simultaneously present in the matrix (fish juice and fish fillets) at different inoculation ratios pathogen:bioprotector (i.e. 1:1, 1:2 and 1:3). The higher the inoculation ratio, the stronger the inhibition of L. monocytogenes growth, with the ratio 1:3 yielding no growth of the pathogen. The maximum population density (N_max) was the most affected parameter for L. monocytogenes at all inoculation ratios. According to the microbiological and sensory analysis outcomes, an initial inoculation level of 4 log cfu/g for L. sakei CTC494 would be a suitable bioprotective strategy without compromising the sensory quality of the fish product. The performance of the tested interaction models was evaluated using the Acceptable Simulation Zone approach. The Lotka Volterra model showed slightly better fit than the Jameson-based models with 75-92% out of the observed counts falling into the Acceptable Simulation Zone, indicating a satisfactory model performance. The evaluated interaction models could be used as predictive modelling tool to simulate the simultaneous behaviour of bacteriocin-producing Lactobacillus strains and L. monocytogenes; thus, supporting the design and optimization of bioprotective culture-based strategies against L. monocytogenes in minimally processed fish products.

Inhibitory Effect of Lactic Acid Bacteria on Foodborne Pathogens: A Review

Foodborne pathogens are serious challenges to food safety and public health worldwide. Fermentation is one of many methods that may be used to inactivate and control foodborne pathogens. Many studies have reported that lactic acid bacteria (LAB) can have significant antimicrobial effects. The current review mainly focuses on the antimicrobial activity of LAB, the mechanisms of this activity, competitive growth models, and application of LAB for inhibition of foodborne pathogens.

Modeling Growth of Listeria and Lactic Acid Bacteria in Food Environments

Predictive food microbiology models can facilitate the assessment and management of microbial food safety. Importantly, the combined effect of storage conditions and product characteristics can be predicted by successfully validated models. This makes it easier and faster to develop or reformulation safe food recipes and predictions can be used to documents safety of available foods. The effect of various product characteristics and storage conditions must be taken into account and extensive mathematical models including the effect of these environmental factors are needed. Here the development, evaluation and application of an extensive growth and growth boundary model for Listeria monocytogenes including the effect of 12 environmental factors as well as the growth dampening effect of lactic acid bacteria is described. The Food Spoilage and Safety Predictor software is used to illustrate how predictions can be applied.

The STARTEC Decision Support Tool for Better Tradeoffs between Food Safety, Quality, Nutrition, and Costs in Production of Advanced Ready-to-Eat Foods

A prototype decision support IT-tool for the food industry was developed in the STARTEC project. Typical processes and decision steps were mapped using real life production scenarios of participating food companies manufacturing complex ready-to-eat foods. Companies looked for a more integrated approach when making food safety decisions that would align with existing HACCP systems. The tool was designed with shelf life assessments and data on safety, quality, and costs, using a pasta salad meal as a case product. The process flow chart was used as starting point, with simulation options at each process step. Key parameters like pH, water activity, costs of ingredients and salaries, and default models for calculations of Listeria monocytogenes, quality scores, and vitamin C, were placed in an interactive database. Customization of the models and settings was possible on the user-interface. The simulation module outputs were provided as detailed curves or categorized as "good"; "sufficient"; or "corrective action needed" based on threshold limit values set by the user. Possible corrective actions were suggested by the system. The tool was tested and approved by end-users based on selected ready-to-eat food products. Compared to other decision support tools, the STARTEC-tool is product-specific and multidisciplinary and includes interpretation and targeted recommendations for end-users.

Modelling the effect of temperature, water activity and carbon dioxide on the growth of Aspergillus niger and Alternaria alternata isolated from fresh date fruit

AIMS

To quantify and model the combined effects of temperature (T) (10-40°C), water activity (a_w ) (0·993-0·818) and CO₂ concentration (9·4-55·1%, v/v) on the growth rate of Aspergillus niger and Alternaria alternata that cause spoilage during the storage and packaging of dates.

METHODS AND RESULTS

The effects of environmental factors were studied using the γ-concept. Cardinal models were used to quantify the effect of studied environmental factors on the growth rates. Firstly, the cardinal parameters were estimated independently from experiments carried out on potato dextrose agar using a monofactorial design. Secondly, model performance evaluation was conducted on pasteurized date paste. The boundary between growth and no-growth was predicted using a deterministic approach. Aspergillus niger displayed a faster growth rate and higher tolerance to low a_w than Al. alternata, which in turn proved more resistant to CO₂ concentration. Minimal cardinal parameters of T and a_w were lower than those reported in the literature.

CONCLUSIONS

The combination of the a_w and CO₂ effects significantly affected As. niger and Al. alternata growth. The γ-concept model overestimated growth rates, however, it is optimistic and provides somewhat conservative predictions.

SIGNIFICANCE AND IMPACT OF THE STUDY

The developed model provides a decision support tool for the choice of the date fruit conservation mode (refrigeration, drying, modified atmospheric packaging or their combination) using T, a_w and CO₂ as environmental factors.

Predictive Modeling for Estimation of Bacterial Behavior from Farm to Table

Microbial contamination is inevitable for raw and/or minimally processed ready-to-eat foods. As a consequence of the pathogenic bacterial contamination, the risk of food-borne illness increases during distribution and storage until consumption. Prediction of microbial growth and/or inactivation in/on those foods provides important information for ensuring the microbial food safety. Although numerous predictive models for bacterial growth have been proposed for various microorganisms, this review focuses on the modeling of pathogenic bacterial growth in raw and minimally processed ready-to-eat foods such as fresh-cut produce and raw minced-tuna, a common ingredient for sushi. The growth models described here take into account both the environment temperature and microbial competition in the food matrix. Microbial competition plays a key role in real food environments. Food-based predictive models enable not only to directly estimate the microbial growth on those foods, but also to apply to validation of culture-medium-based predictive models. Furthermore, toward a development of accurate and/or realistic bacterial dose-response models, a model for inactivation of pathogenic bacteria during simulated gastric fluid is also introduced.

Invasibility of resident biofilms by allochthonous communities in bioreactors

Invasion of non-native species can drastically affect the community composition and diversity of engineered and natural ecosystems, biofilms included. In this study, a molecular community fingerprinting method was used to monitor the putative establishment and colonization of allochthonous consortia in resident multi-species biofilms. To do this, biofilms inoculated with tap water or activated sludge were grown for 10 days in bubble column reactors W1 and W2, and S, respectively, before being exposed to non-native microbial consortia. These consortia consisted of fresh activated sludge suspensions for the biofilms inoculated with tap water (reactors W1 and W2) and of transplanted mature tap water biofilm for the activated sludge biofilm (reactor S). The introduction of virgin, unoccupied coupons into W1 and W2 enabled us to additionally investigate the competition for new resources (space) among the resident biofilm and the allochthonous consortia. CE-SSCP revealed that after the invasion event changes were mostly observed in the abundance of the dominant species in the native biofilms rather than their composition. This suggests that the resident communities within a bioreactor immediately outcompete the allochthonous microbes and shape the microbial community assemblage on both new coupons and already colonized surfaces for the short term. However, with time, latent members of the allochthonous community might grow up affecting the diversity and composition of the original biofilms.

Effect of cell immobilization on the growth dynamics of Salmonella Typhimurium and Escherichia coli at suboptimal temperatures

Predictive microbiology has recently acknowledged the impact of the solid(like) food structure on microbial behavior. The presence of this solid(like) structure causes microorganisms to grow as colonies and no longer planktonically as in liquid. In this paper, the growth dynamics of Salmonella Typhimurium and Escherichia coli were studied as a function of temperature, considering different growth morphologies, i.e., (i) planktonic cells, (ii) immersed colonies and (iii) surface colonies. For all three growth morphologies, both microorganisms were grown in petri dishes. While E. coli was grown under optimal pH and water activity (aw), for S. Typhimurium pH and aw were adapted to 5.5 and 0.990. In order to mimic a solid(like) environment, 5% (w/v) gelatin was added. All petri dishes were incubated under static conditions at temperatures in the range [8.0°C-22.0°C]. Cell density was determined via viable plate counting. This work demonstrates that the growth morphology (planktonic vs. colony) has a negligible effect on the growth dynamics as a function of temperature. The observation of almost equal growth rates for planktonic cultures and colonies is in contrast to literature where, mostly, a difference is observed, i.e., μplanktonic cells≥μimmersed colonies≥μsurface colonies. This difference might be due to shaking of the liquid culture in these studies, which results in a nutrient and oxygen rich environment, in contrast to the diffusion-limited gel system. Experiments also indicate that lag phases for solid(like) systems are similar to those for the planktonic cultures, as can be found in literature for similar growth conditions. Considering the maximum cell density, no clear trend was deducted for either of the microorganisms. This study indicates that the growth parameters in the suboptimal temperature range do not depend on the growth morphology. For the considered experimental conditions, models previously developed for liquid environments can be used for solid(like) systems.

Modelling the effect of lactic acid bacteria from starter- and aroma culture on growth of Listeria monocytogenes in cottage cheese

Four mathematical models were developed and validated for simultaneous growth of mesophilic lactic acid bacteria from added cultures and Listeria monocytogenes, during chilled storage of cottage cheese with fresh- or cultured cream dressing. The mathematical models include the effect of temperature, pH, NaCl, lactic- and sorbic acid and the interaction between these environmental factors. Growth models were developed by combining new and existing cardinal parameter values. Subsequently, the reference growth rate parameters (μref at 25°C) were fitted to a total of 52 growth rates from cottage cheese to improve model performance. The inhibiting effect of mesophilic lactic acid bacteria from added cultures on growth of L. monocytogenes was efficiently modelled using the Jameson approach. The new models appropriately predicted the maximum population density of L. monocytogenes in cottage cheese. The developed models were successfully validated by using 25 growth rates for L. monocytogenes, 17 growth rates for lactic acid bacteria and a total of 26 growth curves for simultaneous growth of L. monocytogenes and lactic acid bacteria in cottage cheese. These data were used in combination with bias- and accuracy factors and with the concept of acceptable simulation zone. Evaluation of predicted growth rates of L. monocytogenes in cottage cheese with fresh- or cultured cream dressing resulted in bias-factors (Bf) of 1.07-1.10 with corresponding accuracy factor (Af) values of 1.11 to 1.22. Lactic acid bacteria from added starter culture were on average predicted to grow 16% faster than observed (Bf of 1.16 and Af of 1.32) and growth of the diacetyl producing aroma culture was on average predicted 9% slower than observed (Bf of 0.91 and Af of 1.17). The acceptable simulation zone method showed the new models to successfully predict maximum population density of L. monocytogenes when growing together with lactic acid bacteria in cottage cheese. 11 of 13 simulations of L. monocytogenes growth were within the acceptable simulation zone, which demonstrated good performance of the empirical inter-bacterial interaction model. The new set of models can be used to predict simultaneous growth of mesophilic lactic acid bacteria and L. monocytogenes in cottage cheese during chilled storage at constant and dynamic temperatures. The applied methodology is likely to be applicable for safety prediction of other types of fermented and unripened dairy products where inhibition by lactic acid bacteria is important for growth of pathogenic microorganisms.

Development and validation of a stochastic model for potential growth of Listeria monocytogenes in naturally contaminated lightly preserved seafood

A new stochastic model for the simultaneous growth of Listeria monocytogenes and lactic acid bacteria (LAB) was developed and validated on data from naturally contaminated samples of cold-smoked Greenland halibut (CSGH) and cold-smoked salmon (CSS). During industrial processing these samples were added acetic and/or lactic acids. The stochastic model was developed from an existing deterministic model including the effect of 12 environmental parameters and microbial interaction (O. Mejlholm and P. Dalgaard, Food Microbiology, submitted for publication). Observed maximum population density (MPD) values of L. monocytogenes in naturally contaminated samples of CSGH and CSS were accurately predicted by the stochastic model based on measured variability in product characteristics and storage conditions. Results comparable to those from the stochastic model were obtained, when product characteristics of the least and most preserved sample of CSGH and CSS were used as input for the existing deterministic model. For both modelling approaches, it was shown that lag time and the effect of microbial interaction needs to be included to accurately predict MPD values of L. monocytogenes. Addition of organic acids to CSGH and CSS was confirmed as a suitable mitigation strategy against the risk of growth by L. monocytogenes as both types of products were in compliance with the EU regulation on ready-to-eat foods.

Growth modeling of Listeria monocytogenes in pasteurized liquid egg

The growth kinetics of Listeria monocytogenes and natural flora in commercially produced pasteurized liquid egg was examined at 4.1 to 19.4°C, and a growth simulation model that can estimate the range of the number of L. monocytogenes bacteria was developed. The experimental kinetic data were fitted to the Baranyi model, and growth parameters, such as maximum specific growth rate (μ(max)), maximum population density (N(max)), and lag time (λ), were estimated. As a result of estimating these parameters, we found that L. monocytogenes can grow without spoilage below 12.2°C, and we then focused on storage temperatures below 12.2°C in developing our secondary models. The temperature dependency of the μ(max) was described by Ratkowsky's square root model. The N(max) of L. monocytogenes was modeled as a function of temperature, because the N(max) of L. monocytogenes decreased as storage temperature increased. A tertiary model of L. monocytogenes was developed using the Baranyi model and μ(max) and N(max) secondary models. The ranges of the numbers of L. monocytogenes bacteria were simulated using Monte Carlo simulations with an assumption that these parameters have variations that follow a normal distribution. Predictive simulations under both constant and fluctuating temperature conditions demonstrated a high accuracy, represented by root mean square errors of 0.44 and 0.34, respectively. The predicted ranges also seemed to show a reasonably good estimation, with 55.8 and 51.5% of observed values falling into the prediction range of the 25th to 75th percentile, respectively. These results suggest that the model developed here can be used to estimate the kinetics and range of L. monocytogenes growth in pasteurized liquid egg under refrigerated temperature.

Quality of raw and smoked fillets from clinically healthy Atlantic salmon, Salmo salar L., following an outbreak of pancreas disease (PD)

Pancreas disease (PD) is a viral disease of farmed salmonid fish, which causes huge economic losses. Pathological changes in skeletal muscle, pancreas and heart are hallmarks of PD. Stakeholders in the fish-smoking industry have claimed that fillets from PD-affected Atlantic salmon, Salmo salar L., are of poor quality. We therefore examined harvest-ready, clinically healthy Atlantic salmon from a population of fish previously affected by PD. Histopathological changes in skeletal muscle tissues ranged from minor to severe. Fillet quality measurements showed that fish with severe skeletal muscle changes provided a paler raw fillet and a yellowish and harder cold-smoked fillet than normal. PD had no significant effect on fillet gaping, bacteriological quality or off-odour development during storage. An unexpected finding was a significant subendocardial fibrosis in 23% of the PD-affected fish. The latter may indicate susceptibility to stress-related heart failure.

Effect of Curing Method and Freeze-Thawing on Subsequent Growth of Listeria monocytogenes on Cold-Smoked Salmon

The presence of the foodborne pathogen Listeria monocytogenes on cold-smoked salmon is a major concern for the seafood industry. Understanding processing and postprocessing handling factors that affect the ability of this pathogen to grow on cold-smoked salmon is critical for developing effective control strategies. In this study, we investigated the effect of curing method and freeze-thawing of cold-smoked salmon on (i) physicochemical properties and (ii) subsequent growth of genetically diverse strains of L. monocytogenes (inoculated after freeze-thawing) and endogenous lactic acid bacteria. The majority of the measured physicochemical properties were unaffected by freezing and thawing. Overall, wet-cured cold-smoked salmon had higher pH, water activity, and moisture, as well as lower fat, water-phase salt, and phenolic content compared with dry-cured cold-smoked salmon. The curing method and freeze-thawing did not affect growth of endogenous lactic acid bacteria. Freeze-thawing cold-smoked salmon prior to inoculation led to pronounced growth of L. monocytogenes at 7°C. The increase in cell density between days 0 and 30 was significantly (P = 0.0078) greater for cold-smoked salmon that was frozen and thawed prior to inoculation compared with nonfrozen cold-smoked salmon. On dry-cured, freeze-thawed cold-smoked salmon, L. monocytogenes had a lag phase ranging from 3.7 ± 0.1 to 11.2 ± 1.4 days compared with salmon that was wet cured and freeze-thawed, on which L. monocytogenes began to grow within 24 h. Variation in growth among L. monocytogenes strains was also observed, indicating the significance of assessing multiple strains. Further efforts to understand the impact of processing and postprocessing handling steps of cold-smoked salmon on the growth of genetically diverse L. monocytogenes will contribute to improved challenge study designs and data. This, in turn, will likely lead to more reliable and unbiased risk assessments and control measures.

Modelling of growth, growth/no-growth interface and nonthermal inactivation areas of Listeria in foods

Growth, growth boundary and inactivation models have been extensively developed in predictive microbiology and are commonly applied in food research nowadays. Few studies though report the development of models which encompass all three areas together. A tiered modelling approach, based on the Gamma hypothesis, is proposed here to predict the behaviour of Listeria. Datasets of Listeria spp. behaviour in laboratory media, meat, dairy, seafood products and vegetables were collected from literature, unpublished sources and from the databases ComBase and Sym'Previus. The explanatory factors were temperature, pH, water activity, lactic and sorbic acids. For the growth part, 697 growth kinetic datasets were fitted. The estimated growth rates and 2021 additional growth primary datasets were used to fit the secondary growth models. In a second step, the fitted model was used to predict the growth/no-growth boundary. For the inactivation modelling phase, 535 inactivation curves were used. Gamma models with and without interactions between the explanatory factors were used for the growth and boundary models. The correct prediction percentage (predicted growth when growth is observed+predicted inactivation when inactivation is observed) varied from 62% to 81% for the models without interactions, and from 85% to 87% for the models with interactions. The median error for the predicted population size was less than 0.34 log(10)(CFU/mL) for all models. The kinetics of inactivation were fitted with modified Weibull primary models and the estimated bacterial resistance was then modelled as a function of the explanatory factors. The error for the predicted microbial population size was less than 0.71 log(10)(CFU/mL) with a median value of less than 0.21 for all foods. The model enables the quantification of the increase or decrease in the bacterial population for a given formulation or storage condition. It might also be used to optimise a food formulation or storage condition in the case of a targeted increase or decrease of the bacterial population.