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.

Listeria in Food: Prevalence and Control.

Listeria monocytogenes is a foodborne pathogen characterized by its psychrotrophic and ubiquitous nature as well as its ability to survive and proliferate in a wide range of harsh environments and foods [...].

Modeling the Growth of Six Listeria monocytogenes Strains in Smoked Salmon Pâté.

In this study, the growth of six L. monocytogenes strains isolated from different fish products was quantified and modeled in smoked salmon pâté at a temperature ranging from 2 to 20 °C. The experimental data obtained for each strain was fitted to the primary growth model of Baranyi and Roberts to estimate the following kinetic parameters: lag phase (λ), maximum specific growth rate (µmax), and maximum cell density (Nmax). Then, the effect of storage temperature on the obtained µmax values was modeled by the Ratkowsky secondary model. In general, the six L. monocytogenes strains showed rapid growth in salmon pâté at all storage temperatures, with a relatively short lag phase λ, even at 2 °C. The growth behavior among the tested strains was similar at the same storage temperature, although significant differences were found for the parameters λ and µmax. Besides, the growth variations among the strains did not follow a regular pattern. The estimated secondary model parameter Tmin ranged from -4.25 to -3.19 °C. This study provides accurate predictive models for the growth of L. monocytogenes in fish pâtés that can be used in shelf life and microbial risk assessment studies. In addition, the models generated in this work can be implemented in predictive modeling tools and repositories that can be reliably and easily used by the fish industry and end-users to establish measures aimed at controlling the growth of L. monocytogenes in fish-based pâtés.

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, µmax, Nmax). The effect of storage temperature was modelled using the hyperbola (λ) and Ratkowsky (µmax) models. The simple Jameson-effect model, its modifications including the Ncri 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 Nmax, 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.

A new expanded modelling approach for investigating the bioprotective capacity of Latilactobacillus sakei CTC494 against Listeria monocytogenes in ready-to-eat fish products.

Understanding the role of food-related factors on the efficacy of protective cultures is essential to attain optimal results for developing biopreservation-based strategies. The aim of this work was to assess and model growth of Latilactobacillus sakei CTC494 and Listeria monocytogenes CTC1034, and their interaction, in two different ready-to-eat fish products (i.e., surimi-based product and tuna pâté) at 2 and 12 °C. The existing expanded Jameson-effect and a new expanded Jameson-effect model proposed in this study were evaluated to quantitatively describe the effect of microbial interaction. The inhibiting effect of the selected lactic acid bacteria strain on the pathogen growth was product dependent. In surimi product, a reduction of lag time of both strains was observed when growing in coculture at 2 °C, followed by the inhibition of the pathogen when the bioprotective L. sakei CTC494 reached the maximum population density, suggesting a mutualism-antagonism continuum phenomenon between populations. In tuna pâté, L. sakei CTC494 exerted a strong inhibition of L. monocytogenes at 2 °C (<0.5 log increase) and limited the growth at 12 °C (<2 log increase). The goodness-of-fit indexes indicated that the new expanded Jameson-effect model performed better and appropriately described the different competition patterns observed in the tested fish products. The proposed expanded competition model allowed for description of not only antagonistic but also mutualism-based interactions based on their influence on lag time.

Evaluation of the effect of Lactobacillus sakei strain L115 on Listeria monocytogenes at different conditions of temperature by using predictive interaction models.

In this study, the inhibitory capacity of Lactobacillus sakei strain L115 against Listeria monocytogenes has been assayed at 4, 8, 11, 15 and 20 °C in broth culture. Besides, the use of predictive microbiology models for describing growth of both microorganisms in monoculture and coculture has been proposed. A preliminary inhibitory test confirmed the ability of Lb. sakei strain L115 to prevent the growth of a five-strain cocktail of L. monocytogenes. Next, the growth of microorganisms in isolation, i.e. in monoculture, was monitored and kinetic parameters maximum specific growth rate (µsp;max) and maximum population density (Nmax) were estimated by fitting the Baranyi model to recorded data. Inhibition coefficients (α) were calculated for the two kinetic parameters tested (µsp:max and Nmax) to quantify the percentage of reduction of growth when the microorganisms were in coculture in comparison with monoculture. The kinetic parameters were input into three interaction models, developed based on modifications of the Baranyi growth model, namely Jameson effect, new modified version of the Jameson effect and Lotka-Volterra models. Two approaches were utilized for simulation, one using the monoculture µsp;max, under the hypothesis that the growth potential is similar under monoculture and coculture conditions provided the environmental conditions are not modified, and the other one, based on adjusting the monoculture kinetic parameter by applying the corresponding α to reproduce the observed µsp;max under coculture conditions, assuming, in this approach, that the existence of a heterogeneous population can change the growth potential of each microbial population. It was observed that in coculture, µsp;max of L. monocytogenes decreased (e.g., α = 31% at 4 °C) and the Nmax was much lower than that of monoculture (e.g., α = 36% at 4 °C). The best simulation performance was achieved applying α to adjust the estimated monoculture growth rate, with the modified Jameson and Lotka-Volterra models showing better fit to the observed microbial interaction data as demonstrated by the fact that 100% data points fell within the acceptable simulation zone (±0.5 log CFU/mL from the simulated data). More research is needed to clarify the mechanisms of interaction between the microorganisms as well as the role of temperature.

Modelling of the Behaviour of Salmonella enterica serovar Reading on Commercial Fresh-Cut Iceberg Lettuce Stored at Different Temperatures.

The aim of this study was to model the growth and survival behaviour of Salmonella Reading and endogenous lactic acid bacteria on fresh pre-cut iceberg lettuce stored under modified atmosphere packaging for 10 days at different temperatures (4, 8 and 15 °C). The Baranyi and Weibull models were satisfactorily fitted to describe microbial growth and survival behaviour, respectively. Results indicated that lactic acid bacteria (LAB) could grow at all storage temperatures, while S. Reading grew only at 15 °C. Specific growth rate values (µmax) for LAB ranged between 0.080 and 0.168 h-1 corresponding to the temperatures 4 and 15 °C while for S. Reading at 15 °C, µmax = 0.056 h-1. This result was compared with published predictive microbiology models for other Salmonella serovars in leafy greens, revealing that predictions from specific models could be valid for such a temperature, provided they were developed specifically in lettuce regardless of the type of serovars inoculated. The parameter delta obtained from the Weibull model for the pathogen was found to be 16.03 and 18.81 for 4 and 8 °C, respectively, indicating that the pathogen underwent larger reduction levels at lower temperatures (2.8 log10 decrease at 4 °C). These data suggest that this Salmonella serovar is especially sensitive to low temperatures, under the assayed conditions, while showcasing that a correct refrigeration could be an effective measure to control microbial risk in commercial packaged lettuce. Finally, the microbiological data and models from this study will be useful to consider more specifically the behaviour of S. Reading during transport and storage of fresh-cut lettuce, elucidating the contribution of this serovar to the risk by Salmonella in leafy green products.

Probabilistic risk model of norovirus transmission during handling and preparation of fresh produce in school foodservice operations.

Human noroviruses (NoV) are recognized worldwide as important pathogens and the primary cause of foodborne disease outbreaks from contaminated food in the U.S. They are often transmitted by infected food handlers manipulating foods during preparation, such as fresh fruits and vegetables. This paper provides a study to model the transfer of NoV between food handlers and vegetables during salad preparation in school food services based on direct observation data. Three transfer pathways were modeled by considering different initial contamination sources (environment, handlers and contaminated produce). The probability of infection by NoV was also estimated based on the NoV levels at consumption obtained from each simulated transfer pathway. A scenario analysis ranging a wide concentration from 102 to 107 NoV infective particles was performed to represent different levels of NoV in the initial contamination sources. In addition, a sensitivity analysis was applied to identify the most important model inputs and determine the safest handling practices to be implemented in school food service operations. The pathway describing transfer from contaminated surfaces or handlers to foods indicated that initial levels of ≤104 NoV particles/fomite resulted in <0.5% cases per serving of NoV infection. When initial levels were higher, % cases of NoV infection was estimated to be ca. 3%. This rise in % cases of infection was linked to higher doses (5% serving with ≥15 NoV particles/serving) and prevalence levels at consumption (>0.2). In the pathway modeling cross contamination from contaminated vegetables to non-contaminated vegetables, all scenarios could lead to infected individuals, although number of cases of infection were lower (<1.3%), despite concentration levels were higher. On the contrary, for this pathway, prevalence was 2-fold lower than that observed in the pathways describing transfer from contaminated surfaces and hands. Based on the sensitivity analysis, NoV transfers to fresh produce may be minimized by improving hand washing, and therefore effective training programs need to be carried out specifically addressing hand washing. Moreover, the produce's washing step showed to be an effective control measure, depending on the desinfectant efficacy, by reducing % cases of NoV infection from 6 to 1%. The model in this study might be used, in the future, to evaluate the impact on the risk associated with NoV transmission of specific and effective training programs, aimed at food chain operators.

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 (Nmax) 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.

'MicroHibro': A software tool for predictive microbiology and microbial risk assessment in foods.

A tool able to quantitatively assess the fate of potential pathogenic microorganisms in foods along the food chain and their impact on public health is highly valuable for food safety decision-makers. The aim of this work was to present an overview of the Predictive Microbiology software MicroHibro, which is able to assess the evolution of potential pathogens and spoilage microorganisms along the food chain, providing estimates for the exposure level and risk associated with a food product. The application is built on an extensive Predictive Microbiology Model Data Base (PMDB) including kinetic processes like growth, inactivation, transfer as well as dose-response models. PMDB can be populated with new models by using an on-line tool in combination with a standardized method for describing Predictive Microbiology models. This enables MicroHibro to be easily updated, increasing its applicability and use. Estimation of microbial risk associated with a food product can be achieved, in MicroHibro, by describing steps in any food chain using four different microbial processes (growth, inactivation, transfer and partitioning). As a result, an estimate of the concentration and prevalence of microorganisms in the food of interest as well as attendant risk are provided. Also, MicroHibro allows comparing different predictive models and validate them by introducing user's data. In this paper, examples are provided to illustrate how predictive models can be incorporated in MicroHibro, and then, used to develop a Quantitative Microbial Risk Assessment model. The use of expert computational systems is a powerful tool for supporting food safety and quality activities by Health Authorities and the food industry. They represent a breakthrough in the assessment and management of food safety based on scientific evidence.

Modelling the growth of Listeria monocytogenes in Mediterranean fish species from aquaculture production.

Over the last couple of decades, several studies have evaluated growth dynamics of L. monocytogenes in lightly processed and ready-to-eat (RTE) fishery products mostly consumed in Nordic European countries. Other fish species from aquaculture production are of special interest since their relevant consumption patterns and added value in Mediterranean countries, such as sea bream and sea bass. In the present study, the growth of L. monocytogenes was evaluated in fish-based juice (FBJ) by means of optical density (OD) measurements in a temperature range 2-20 °C under different atmosphere conditions (i.e. reduced oxygen and aerobic). The Baranyi and Roberts model was used to estimate the maximum growth rate (µmax) from the observed growth curves. The effect of storage temperature on µmax was modelled using the Ratkowsky square root model. The developed models were validated using experimental growth data for L. monocytogenes in sea bream and sea bass fillets stored under static and dynamic temperature conditions. Overall, models developed in FBJ provided fail-safe predictions for L. monocytogenes growth. For the model generated under reduced oxygen conditions, bias and accuracy factor for growth rate predictions were 1.15 and 1.25, respectively, showing good performance to adequately predict L. monocytogenes growth in Mediterranean fish products. The present study provides validated predictive models for L. monocytogenes growth in Mediterranean fish species to be used in microbial risk assessment and shelf-life studies.

Effect of food microstructure on growth dynamics of Listeria monocytogenes in fish-based model systems.

Traditionally, predictive growth models for food pathogens are developed based on experiments in broth media, resulting in models which do not incorporate the influence of food microstructure. The use of model systems with various microstructures is a promising concept to get more insight into the influence of food microstructure on microbial dynamics. By means of minimal variation of compositional and physicochemical factors, these model systems can be used to study the isolated effect of certain microstructural aspects on microbial growth, survival and inactivation. In this study, the isolated effect on microbial growth dynamics of Listeria monocytogenes of two food microstructural aspects and one aspect influenced by food microstructure were investigated, i.e., the nature of the food matrix, the presence of fat droplets, and microorganism growth morphology, respectively. To this extent, fish-based model systems with various microstructures were used, i.e., a liquid, a second more viscous liquid system containing xanthan gum, an emulsion, an aqueous gel, and a gelled emulsion. Growth experiments were conducted at 4 and 10 °C, both using homogeneous and surface inoculation (only for the gelled systems). Results regarding the influence of the growth morphology indicated that the lag phase of planktonic cells in the liquid system was similar to the lag phase of submerged colonies in the xanthan system. The lag phase of submerged colonies in each gelled system was considerably longer than the lag phase of surface colonies on these respective systems. The maximum specific growth rate of planktonic cells in the liquid system was significantly lower than for submerged colonies in the xanthan system at 10 °C, while no significant differences were observed at 4 °C. The maximum cell density was higher for submerged colonies than for surface colonies. The nature of the food matrix only exerted an influence on the maximum specific growth rate, which was significantly higher in the viscous systems than in the gelled systems. The presence of a small amount of fat droplets improved the growth of L. monocytogenes at 4 °C, resulting in a shorter lag phase and a higher maximum specific growth rate. The obtained results could be useful in the determination of a set of suitable microstructural parameters for future predictive models that incorporate the influence of food microstructure on microbial dynamics.