Modelling the growth kinetics of Listeria as a function of temperature, pH and organic acid concentration

Relationships between the inhibitory efficacy and physicochemical properties of six organic acids and monolaurin against Bacillus weihenstephanensis KBAB4 growth in liquid medium

Organic acids are widely used in foodstuffs to inhibit pathogen and spoiler growth. In this study, six organic acids (acetic, lactic, propionic, phenyllactic, caprylic, and lauric acid) and monolaurin were selected based on their physicochemical properties: their molecular structure (carbon chain length), their lipophilicity (logP), and their ability to dissociate in a liquid environment (pKa). The relation between these physicochemical properties and the inhibitory efficacy against B. weihenstephanensis KBAB4 growth was evaluated. After assessing the active form of these compounds against the strain (undissociated, dissociated or both forms), their MIC values were estimated in nutrient broth at pH 6.0 and 5.5 using two models (Lambert & Pearson, 2000; Luong, 1985). The use of two models highlighted the mode of action of an antibacterial compound in its environment, thanks to the additional estimation of the curve shape α or the Non-Inhibitory Concentration (NIC). The undissociated form of the tested acids is responsible for growth inhibition, except for lauric acid and monolaurin. Moreover, long-carbon chain acids have lower estimated MICs, compared to short-chain acids. Thus, the inhibitory efficacy of organic acids is strongly related to their carbon chain length and lipophilicity. Lipophilicity is the main mechanism of action of a membrane-active compound, it can be favored by long chain structure or high pKa in an acid environment like food.

A stochastic approach for modelling the in-vitro effect of osmotic stress on growth dynamics and persistent cell formation in Listeria monocytogenes

Persistent bacteria (or persisters) can be defined as a microbial subpopulation that, exposed to bactericidal treatment, is killed more slowly than the rest of the population they are part of. They stochastically originate in response to environmental stressors or spontaneously without external signals. When transferred into a fresh medium, persisters can resume active replication although they spend more time adapting to the new conditions remaining in the lag phase longer. They were studied for decades for their ability to survive antibiotic treatments while studies on their formation in food and potential impact on their safety are lacking. The most common food preservation techniques may act as stressors that trigger the formation of persistent bacteria able to survive bactericidal treatments and grow later in foods during storage. This study aimed to investigate a possible relationship between exposure to different salt concentrations (osmotic stress) and the amount of persisters triggered in a strain of Listeria monocytogenes. Furthermore, we described this phenomenon from a mathematical perspective through predictive microbiology models commonly used in the food field. The lag time distribution of a L. monocytogenes ATCC 7644 strain grown in broth with additional 2 %, 4 % and 6 % NaCl was evaluated using the software ScanLag. It uses office scanners to automatically record the colony growth on agar plates and evaluate the frequency distribution of their appearance times (lag phase) by automated image analysis. The same broth cultures were diluted to equalize salt concentration and transferred into a fresh broth to evaluate how the previous salt exposure impacted their growth kinetics. The observed growth curves were reproduced using predictive models in which the mean duration of the lag phase of the whole population took into account the occurrence of persisters with a longer lag phase. The models were solved first using a deterministic approach and then a stochastic one introducing a stochastic term that mimics the variability of lag phase duration due to the persisters occurrence. Results showed that the growth of L. monocytogenes in broth with additional NaCl might trigger the formation of persistent cells whose number increased consistently with salt concentrations. The proposed predictive approach reproduced the observed real curves in strong agreement, especially through the stochastic resolution of the models. Persistence is currently a neglected bacterial defence strategy in the food sector but the persisters' formation during production cannot be excluded; therefore, further insights on the topic are certainly desirable.

Inter-strain variability on the cardinal parameters (pH and Aw) of clinical and food isolates of Listeria monocytogenes using turbidimetric measurements

Listeria monocytogenes is a foodborne pathogen which, in 2021, was considered the fifth most commonly reported zoonosis in humans in the European Union (EU). Ready-to-eat (RTE) fishery products, deli meats or soft cheeses have been mostly involved in food safety alerts and outbreaks in the last years. Hurdle technology by food industries has been widely used to enhance the safety of foods. Among the barriers, the application of acid and osmotic stress during processing is extensively used worldwide. This study aims to gain knowledge about the inter-strain variability of twenty-six clinical and food L. monocytogenes isolates with the estimation of their cardinal parameters using turbidimetric measurements. To analyse the data and to obtain the estimated cardinal values, a common statistical procedure was set up. The estimation of cardinal parameters showed a high inter-strain variability of L. monocytogenes, and no correlation was observed between Aw min and pHmin values for the studied strains. By grouping the strains in clinical, meat and fish origin, it was observed that strains from the meat group presented the lowest average pHmin values (4.57), thus showing potential acid adaptation. This work contributes to gain knowledge of the inter-strain variability of L. monocytogenes in relation with pH and Aw cardinal values, as well as provide a starting point for future validation studies in fish and meat food matrices.

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.

A new cheese population in Penicillium roqueforti and adaptation of the five populations to their ecological niche

Domestication is an excellent case study for understanding adaptation and multiple fungal lineages have been domesticated for fermenting food products. Studying domestication in fungi has thus both fundamental and applied interest. Genomic studies have revealed the existence of four populations within the blue-cheese-making fungus Penicillium roqueforti. The two cheese populations show footprints of domestication, but the adaptation of the two non-cheese populations to their ecological niches (i.e., silage/spoiled food and lumber/spoiled food) has not been investigated yet. Here, we reveal the existence of a new P. roqueforti population, specific to French Termignon cheeses, produced using small-scale traditional practices, with spontaneous blue mould colonisation. This Termignon population is genetically differentiated from the four previously identified populations, providing a novel source of genetic diversity for cheese making. The Termignon population indeed displayed substantial genetic diversity, both mating types, horizontally transferred regions previously detected in the non-Roquefort population, and intermediate phenotypes between cheese and non-cheese populations. Phenotypically, the non-Roquefort cheese population was the most differentiated, with specific traits beneficial for cheese making, in particular higher tolerance to salt, to acidic pH and to lactic acid. Our results support the view that this clonal population, used for many cheese types in multiple countries, is a domesticated lineage on which humans exerted strong selection. The lumber/spoiled food and silage/spoiled food populations were not more tolerant to crop fungicides but showed faster growth in various carbon sources (e.g., dextrose, pectin, sucrose, xylose and/or lactose), which can be beneficial in their ecological niches. Such contrasted phenotypes between P. roqueforti populations, with beneficial traits for cheese-making in the cheese populations and enhanced ability to metabolise sugars in the lumber/spoiled food population, support the inference of domestication in cheese fungi and more generally of adaptation to anthropized environments.

Cardinal models to describe the effect of temperature and pH on the growth of Anoxybacillus flavithermus & Bacillus licheniformis

Anoxybacillus flavithermus and Bacillus licheniformis are among the predominant spore-formers of heat-processed foods. To our knowledge, no systematic analysis of growth kinetic data of A. flavithermus or B. licheniformis is currently available. In the present study, the growth kinetics of A. flavithermus and B. licheniformis in broth at various temperature and pH conditions were studied. Cardinal models were used to model the effect of the above-mentioned factors on the growth rates. The estimated values for the cardinal parameters T_min,T_opt,T_max,pH_min and pH_1/2 for A. flavithermus were 28.70 ± 0.26, 61.23 ± 0.16 and 71.52 ± 0.32 °C, 5.52 ± 0.01 and 5.73 ± 0.01, respectively, while for B. licheniformis they were 11.68 ± 0.03, 48.05 ± 0.15, 57.14 ± 0.01 °C, 4.71 ± 0.01 and 5.670 ± 0.08, respectively. The growth behaviour of these spoilers was also investigated in a pea beverage at 62 and 49 °C, respectively, to adjust the models to this product. The adjusted models were further validated at static and dynamic conditions and demonstrated good performance with 85.7 and 97.4% of predicted populations for A. flavithermus and B. licheniformis, respectively, being within the -10%-10% relative error (RE) zone. The developed models can be useful tools in assessing the potential of spoilage of heat-processed foods including plant-based milk alternatives.

Modeling of Growth and Organic Acid Kinetics and Evolution of the Protein Profile and Amino Acid Content during Lactiplantibacillus plantarum ITM21B Fermentation in Liquid Sourdough

The application of mathematical modeling to study and characterize lactic acid bacterial strains with pro-technological and functional features has gained attention in recent years to solve the problems relevant to the variabilities of the fermentation processes of sourdough. Since the key factors contributing to the sourdough quality are relevant to the starter strain growth and its metabolic activity, in this study, the cardinal growth parameters for pH, temperature (T), water activity (a_w), and undissociated lactic acid of the sourdough strain Lactiplantibacillus plantarum ITM21B, were determined. The strain growth, pH, organic acids (lactic, acetic, phenyllactic, and hydroxy-phenyllactic), total free amino acids, and proteins were monitored during fermentation of a liquid sourdough based on wheat flour and gluten (Bio21B) after changing the starting T, pH, and inoculum load. Results demonstrated that the different fermentation conditions affected the strain growth and metabolite pattern. The organic acid production and growth performance were modeled in Bio21B, and the resulting predictive model allowed us to simulate in silico the strain performances in liquid sourdough under different scenarios. This mathematical predictive approach can be useful to optimize the fermentation conditions needed to obtain the suitable nutritional and technological characteristics of the L. plantarum ITM21B liquid sourdough.

Predicting the Growth of Listeria monocytogenes in Cooked, Sliced Deli Turkey Breast as a Function of Clean-Label Antimicrobials, pH, Moisture, and Salt

ABSTRACT

The use of antimicrobials in formulated ready-to-eat meat and poultry products has been identified as a major strategy to control Listeria monocytogenes. The U.S. Department of Agriculture's Food Safety and Inspection Service recommends no more than 2 log of Listeria outgrowth over the stated shelf life if antimicrobials are used as a control measure for a product with postlethality environmental exposure. This study was designed to understand the efficacy of a clean-label antimicrobial agents against the growth of L. monocytogenes as affected by the product attributes. A response surface method-central composite design was used to investigate the effects of product pH, moisture, salt content, and a commercial "clean-label" antimicrobial agent on the growth of L. monocytogenes in a model turkey deli meat formulation. Thirty treatment combinations of pH (6.3, 6.5, and 6.7), moisture (72, 75, and 78%), salt (1.0, 1.5, and 2.0%), and antimicrobials (0.75, 1.375, and 2.0%), with six replicated center points and eight design star points were evaluated. Treatments were surface inoculated with a 3-log CFU/g target of a five-strain L. monocytogenes cocktail, vacuum packaged, and stored at 5°C for up to 16 weeks. Populations of L. monocytogenes were enumerated from triplicate samples every week until the stationary growth phase was reached. The enumeration data was fitted to a Baranyi and Roberts growth curve to calculate the lag time and maximum growth rate for each treatment. Linear least-squares regression of the lag time and growth rate against the full quadratic, including the second-order interaction terms, design matrix was performed. Both lag time and maximum growth rate were significantly affected (P < 0.01) by the antimicrobial concentration and product pH. Product moisture and salt content affected (P < 0.05) lag phase and maximum growth rate, respectively. The availability of a validated growth model assists meat scientists and processors with faster product development and commercialization.

HIGHLIGHTS

The effect of pH on the growth rate of Bacillus cereus sensu lato: Quantifying strain variability and modelling the combined effects of temperature and pH

In this study, the effect of pH, alone or in combination with temperature, on the maximum growth rate (μ_max) of B. cereus sensu lato was investigated. In phase 1, the effect of pH at 30 °C was studied for 16 mesophilic strains and 2 psychrotrophic strains of Bacillus cereus sensu lato. The μ_max vs. pH relationship was found to show a similar pattern for all the strains. Several pH models from literature were evaluated and the best performing 'growth rate vs. pH' model selected. A stochastic model was then developed to predict the maximum specific growth rate of mesophilic B. cereus at 30 °C as a function of pH, the intra-species variability being incorporated via considering the model parameters (e.g. pH_min) randomly distributed. The predicted maximum specific growth rates were acceptably close to independent published data. In phase 2, the combined effects of temperature and pH were studied. Growth rates were also generated at 15, 20 and 40 °C for a selection of strains and the pH model was fitted at each temperature. Interestingly, the results showed that the estimates for the pH_min parameter for mesophilic strains were lower at 20-30 °C than near the optimum temperature (40 °C), suggesting that experiments for the determination of this parameter should be conducted at lower-than-optimum temperatures. New equations were proposed for the relationship between temperature and the minimum pH-values, which were also consistent with the experimental growth boundaries. The parameters defining this equation quantify the minimum temperature for growth observed experimentally, the temperature of maximum enzyme stability and the maximum temperature for growth. Deviations from the Gamma hypothesis (multiplicative effects of environmental factors on the maximum specific growth rate) were observed near the growth limits, especially at 40 °C. To improve model performance, two approaches, one based on a minimum pH-term (doi: https://doi.org/10.3389/fmicb.2019.01510) and one based on an interaction term (doi: http://dx.doi.org/10.1016/S0168-1605(01)00640-7) were evaluated.

A model to predict the fate of Listeria monocytogenes in different cheese types - A major role for undissociated lactic acid in addition to pH, water activity, and temperature

Undissociated lactic acid has been shown to play a major role in complete growth inhibition of Listeria monocytogenes in Gouda cheese. In addition, low water activity conditions may contribute to growth inhibition. In the current study, it was assessed whether the major factors that inhibit growth of L. monocytogenes in Gouda cheese are the factors that determine growth in other types of ready-to-eat cheese as well. Various types of cheeses were selected, some of which had been associated with listeriosis, while others had not. Based on the composition of the different cheese types, the concentrations of undissociated lactic acid were calculated for each type. The ability to support growth of L. monocytogenes was predicted using the Gamma model, based on literature data on total lactic acid content, moisture content, fat content, pH, Aw, and temperature, and optimal growth rates in milk at 30-37 °C. In addition, the actual specific growth rates of L. monocytogenes in the various cheeses were calculated based on available experimental growth data. In 9 out of the 10 RTE cheeses reviewed, the undissociated lactic acid concentrations and a_w determined growth/no growth of L. monocytogenes. No growth was correctly predicted for feta, Cheddar and Gouda, and growth was correctly predicted for ricotta, queso fresco, Camembert, high-moisture mozzarella, cottage and blue cheese. Growth of L. monocytogenes was not observed in practice upon inoculation of Emmental, whereas growth in this cheese type was predicted when including the above mentioned factors in the models. Other factors, presumably acetic and propionic acid, are thought to be important to inhibit growth of the pathogen in Emmental. The results from our study show that for cheeses in which lactic acid is a main acid, our model based on undissociated lactic acid, temperature, pH and a_w gives a good prediction of potential outgrowth of L. monocytogenes. Implications for L. monocytogenes legislation are discussed per type of RTE cheese reviewed.

The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art

Predictive microbiology has steadily evolved into one of the most important tools to assess and control the microbiological safety of food products. Predictive models were traditionally developed based on experiments in liquid laboratory media, meaning that food microstructural effects were not represented in these models. Since food microstructure is known to exert a significant effect on microbial growth and inactivation dynamics, the applicability of predictive models is limited if food microstructure is not taken into account. Over the last 10-20 years, researchers, therefore, developed a variety of models that do include certain food microstructural influences. This review provides an overview of the most notable microstructure-including models which were developed over the years, both for microbial growth and inactivation.

Cardinal parameter growth and growth boundary model for non-proteolytic Clostridium botulinum - Effect of eight environmental factors

A new cardinal parameter growth and growth boundary model for non-proteolytic C. botulinum was developed and validated for fresh and lightly preserved seafood and poultry products. 523 growth rates in broth were used to determine cardinal parameter values and terms for temperature, pH, NaCl/water activity, acetic, benzoic, citric, lactic and sorbic acids. The new growth and growth boundary model included the inhibiting interactive effect between these factors and it was calibrated using growth curves from 10 challenge tests with unprocessed seafood. For model evaluation, 40 challenge tests with well characterized fresh and lightly preserved seafood were performed. Comparison of these observed growth curves and growth rates (μ_max-values) predicted by the new model resulted in a bias factor (B_f) of 1.12 and an accuracy factor (A_f) of 1.40. Furthermore, the new model was evaluated with 94 growth rates and 432 time to toxin formation data extracted from the scientific literature for seafood, poultry, meat, pasta and prepared meals. These data included responses for 36 different toxigenic strains of non-proteolytic C. botulinum. The obtained B_f-/A_f-values were 0.97/2.04 for μ_max-values and 0.96/1.80 for time to toxin formation. The model correctly predicted 93.8% of the growth responses with 5.6% being fail-safe and <1% fail-dangerous. A cocktail of four non-toxin producing Clostridium spp. isolates was used to develop the new model and these isolates had more than 99.8% 16S rRNA gene similarity to non-proteolytic C. botulinum (Group II). The high number of environmental factors included in the new model makes it a flexible tool to facilitate development or reformulation of seafood and poultry products that do not support the growth of non-proteolytic C. botulinum. Further, evaluation of the new model with well characterized products is desirable particularly for meat, vegetables, pasta and prepared meals as well as for dairy products that was not included in the present study.

Fungal G-Protein-Coupled Receptors: A Promising Mediator of the Impact of Extracellular Signals on Biosynthesis of Ochratoxin A

G-protein-coupled receptors (GPCRs) are transmembrane receptors involved in transducing signals from the external environment inside the cell, which enables fungi to coordinate cell transport, metabolism, and growth to promote their survival, reproduction, and virulence. There are 14 classes of GPCRs in fungi involved in sensing various ligands. In this paper, the synthesis of mycotoxins that are GPCR-mediated is discussed with respect to ligands, environmental stimuli, and intra-/interspecific communication. Despite their apparent importance in fungal biology, very little is known about the role of ochratoxin A (OTA) biosynthesis by Aspergillus ochraceus and the ligands that are involved. Fortunately, increasing evidence shows that the GPCR that involves the AF/ST (sterigmatocystin) pathway in fungi belongs to the same genus. Therefore, we speculate that GPCRs play an important role in a variety of environmental signals and downstream pathways in OTA biosynthesis. The verification of this inference will result in a more controllable GPCR target for control of fungal contamination in the future.

From Cheese-Making to Consumption: Exploring the Microbial Safety of Cheeses through Predictive Microbiology Models

Cheeses are traditional products widely consumed throughout the world that have been frequently implicated in foodborne outbreaks. Predictive microbiology models are relevant tools to estimate microbial behavior in these products. The objective of this study was to conduct a review on the available modeling approaches developed in cheeses, and to identify the main microbial targets of concern and the factors affecting microbial behavior in these products. Listeria monocytogenes has been identified as the main hazard evaluated in modelling studies. The pH, a_w, lactic acid concentration and temperature have been the main factors contemplated as independent variables in models. Other aspects such as the use of raw or pasteurized milk, starter cultures, and factors inherent to the contaminating pathogen have also been evaluated. In general, depending on the production process, storage conditions, and physicochemical characteristics, microorganisms can grow or die-off in cheeses. The classical two-step modeling has been the most common approach performed to develop predictive models. Other modeling approaches, including microbial interaction, growth boundary, response surface methodology, and neural networks, have also been performed. Validated models have been integrated into user-friendly software tools to be used to obtain estimates of microbial behavior in a quick and easy manner. Future studies should investigate the fate of other target bacterial pathogens, such as spore-forming bacteria, and the dynamic character of the production process of cheeses, among other aspects. The information compiled in this study helps to deepen the knowledge on the predictive microbiology field in the context of cheese production and storage.

Guidance on date marking and related food information: part 1 (date marking)

A risk-based approach was developed to be followed by food business operators (FBO) when deciding on the type of date marking (i.e. 'best before' date or 'use by' date), setting of shelf-life (i.e. time) and the related information on the label to ensure food safety. The decision on the type of date marking needs to be taken on a product-by-product basis, considering the relevant hazards, product characteristics, processing and storage conditions. The hazard identification is food product-specific and should consider pathogenic microorganisms capable of growing in prepacked temperature-controlled foods under reasonably foreseeable conditions. The intrinsic (e.g. pH and aw), extrinsic (e.g. temperature and gas atmosphere) and implicit (e.g. interactions with competing background microbiota) factors of the food determine which pathogenic and spoilage microorganisms can grow in the food during storage until consumption. A decision tree was developed to assist FBOs in deciding the type of date marking for a certain food product. When setting the shelf-life, the FBO needs to consider reasonably foreseeable conditions of distribution, storage and use of the food. Key steps of a case-by-case procedure to determine and validate the shelf-life period are: (i) identification of the relevant pathogenic/spoilage microorganism and its initial level, (ii) characterisation of the factors of the food affecting the growth behaviour and (iii) assessment of the growth behaviour of the pathogenic/spoilage microorganism in the food product during storage until consumption. Due to the variability between food products and consumer habits, it was not appropriate to present indicative time limits for food donated or marketed past the 'best before' date. Recommendations were provided relating to training activities and support, using 'reasonably foreseeable conditions', collecting time-temperature data during distribution, retail and domestic storage of foods and developing Appropriate Levels of Protection and/or Food Safety Objectives for food-pathogen combinations.

Antimicrobial effect of nisin in processed cheese - Quantification of residual nisin by LC-MS/MS and development of new growth and growth boundary model for Listeria monocytogenes

This study tested the hypothesis that growth of Listeria monocytogenes in processed cheese with added nisin can be predicted from residual nisin A concentrations in the final product after processing. A LC-MS/MS method and a bioassay were studied to quantify residual nisin A concentrations and a growth and growth boundary model was developed to predict the antilisterial effect in processed cheese. 278 growth rates were determined in broth for 11 L. monocytogenes isolates and used to determine 13 minimum inhibitory concentration (MIC) values for nisin between pH 5.5 and 6.5. To supplement these data, 67 MIC-values at different pH-values were collected from the scientific literature. A MIC-term was developed to describe the effect of pH on nisin MIC-values. An available growth and growth boundary model (doi: https://doi.org/10.1016/j.fm.2019.103255) was expanded with the new MIC-term for nisin to predict growth in processed cheese. To generate data for model evaluation and further model development, challenge tests with a total of 45 growth curves, were performed using processed cheese. Cheeses were formulated with 11.2 or 12.0 ppm of nisin A and heat treated to obtain residual nisin A concentrations ranging from 0.56 to 5.28 ppm. Below 15 °C, nisin resulted in extended lag times. A global regression approach was used to fit all growth curves determined in challenge tests. This was obtained by combining the secondary growth and growth boundary model including the new term for the inhibiting effect of nisin on μ_max with the primary logistic growth model with delay. This model appropriately described the growth inhibiting effect of residual nisin A and showed that relative lag times depended on storage temperatures. With residual nisin A concentrations, other product characteristics and storage temperature as input the new model correctly predicted all observed growth and no-growth responses for L. monocytogenes. This model can support development of nisin A containing recipes for processed cheese that prevent growth of L. monocytogenes. Residual nisin A concentrations in processed cheese were accurately quantified by the developed LC-MS/MS method with recoveries of 83 to 110% and limits of detection and quantification being 0.04 and 0.13 ppm, respectively. The tested bioassay was less precise and nisin A recoveries varied for 53% to 94%.

Control of Biological Hazards in Insect Processing: Application of HACCP Method for Yellow Mealworm (Tenebrio molitor) Powders

Entomophagy has been part of human diets for a long time in a significant part of the world, but insects are considered to be a novel food everywhere else. It would appear to be a strategic alternative in the future of human diet to face the challenge of ensuring food security for a growing world population, using more environmentally sustainable production systems than those required for the rearing of other animals. Tenebrio molitor, called yellow mealworm, is one of the most interesting insect species in view of mass rearing, and can be processed into a powder that ensures a long shelf life for its use in many potential products. When considering insects as food or feed, it is necessary to guarantee their safety. Therefore, manufacturers must implement a Hazard Analysis Critical Control plan (HACCP), to limit risks for consumers' health. The aim of this case study was to develop a HACCP plan for Tenebrio molitor larvae powders for food in a risk-based approach to support their implementation in industry. Specific purposes were to identify related significant biological hazards and to assess the efficiency of different manufacturing process steps when used as Critical Control Points. Then, combinations of four different processes with four potential uses of powders by consumers in burger, protein shake, baby porridge, and biscuits were analyzed with regard to their safety.

Predicting growth of Listeria monocytogenes at dynamic conditions during manufacturing, ripening and storage of cheeses - Evaluation and application of models

Mathematical models were evaluated to predict growth of L. monocytogenes in mould/smear-ripened cheeses with measured dynamic changes in product characteristics and storage conditions. To generate data for model evaluation three challenge tests were performed with mould-ripened cheeses produced by using milk inoculated with L. monocytogenes. Growth of L. monocytogenes and lactic acid bacteria (LAB) in the rind and in the core of cheeses were quantified together with changes in product characteristics over time (temperature, pH, NaCl/a_w, lactic- and acetic acid concentrations). The performance of nine available L. monocytogenes growth models was evaluated using growth responses from the present study and from literature together with the determined or reported dynamic product characteristics and storage conditions (46 kinetics). The acceptable simulation zone (ASZ) method was used to assess model performance. A reduced version of the Martinez-Rios et al. (2019) model (https://doi.org/10.3389/fmicb.2019.01510) and the model of Østergaard et al. (2014) (https://doi.org/10.1016/j.ijfoodmicro.2014.07.012) had acceptable performance with a ASZ-score of 71-70% for L. monocytogenes growth in mould/smear-ripened cheeses. Models from Coroller et al. (2012) (https://doi.org/10.1016/j.ijfoodmicro.2011.09.023) had close to acceptable performance with ASZ-scores of 67-69%. The validated models (Martinez-Rios et al., 2019; Østergaard et al., 2014) can be used to facilitate the evaluation of time to critical L. monocytogenes growth for mould/smear-ripened cheeses including modification of recipes with for example reduced salt/sodium or to support exposure assessment studies for these cheeses.

Growth of Listeria monocytogenes in ready-to-eat "shrimp cocktail": Risk assessment and possible preventive interventions

The present study investigated the presence, growth potential, and public health risk posed by Listeria monocytogenes in a ready-to-eat "shrimp cocktail". The pathogen was detected in 4 out of the 104 samples, and there were no counts above the enumeration limit (1 Log colony-forming unit (CFU)/g); the product was a suitable substrate for pathogen growth owing to its chemical/physical properties. A stochastic quantitative microbial risk assessment (QMRA) was performed to estimate the expected number of invasive listeriosis cases caused by the consumption of 10,000 servings of the product on the last day of its shelf life, considering a population comprising healthy consumers, those susceptible, and transplant recipients. The model predicted no cases for this scenario. Uncertainties were included by considering alternative scenarios; even when considering an increased mean bacterial concentration (up to 3-4 Log CFU/g), no cases were estimated. Following a producer's demand, the exposure assessment model was also used to estimate the probability of the product exceeding the threshold of 2 log CFU/g during the shelf life. The possibility of Listeria growth in the product could not be avoided. Therefore, a modification of the production process was tested to re-classify the product as unsuitable for Listeria growth (EC Reg. 2073/2005). The shrimps were conditioned in three different organic acid solutions comprising: acetic acid (1500 ppm) (A); benzoic acid (1500 ppm) + acetic acid (500 ppm) + lactic acid (750 ppm) (BLA); and lactic acid (4500 ppm) + sodium acetate (2500 ppm) (LSA). Testing was conducted over various treatment durations (1 day-5 days). Treatment for 2 days in the LSA solution was selected based on efficacy, the absence of consumer-perceptible sensorial modifications, and the producers' production rate requirements. The concentration of L. monocytogenes decreased when the new process was applied, which confirmed the usefulness and effectiveness of the treatment relative to the traditional process. Thus, the product obtained by the modified production process did not support the growth of L. monocytogenes.

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 and growth boundary model with terms for melting salts to predict growth responses of Listeria monocytogenes in spreadable processed cheese

The aim of this study was to develop and validate a growth and growth boundary model with terms for melting salts to predict growth of Listeria monocytogenes in spreadable processed cheese. Cardinal parameter terms for phosphate salts and citric acid were developed in broth studies and used to expand an available growth and growth boundary model. The expanded model includes the effect of nine environmental factors (temperature, pH, a_w, lactic acid, acetic acid, citric acid, orthophosphate, di-phosphate and tri-phosphate). To generate growth data for model evaluation challenge tests with inoculated commercial (n = 10) and customized (n = 10) spreadable processed cheeses were performed. Evaluation of the new model by comparison of observed and predicted μ_max-values resulted in a bias factor of 1.12 and an accuracy factor of 1.33 (n = 42). Prediction of growth and no-growth responses in processed cheese (n = 60) were 89% correct with 11% fail-safe and 0% fail-dangerous predictions. The developed model can be used to support product development, reformulation or risk assessment for spreadable processed cheese.

New Term to Quantify the Effect of Temperature on pH min -Values Used in Cardinal Parameter Growth Models for Listeria monocytogenes

The aim of this study was to quantify the influence of temperature on pH_min-values of Listeria monocytogenes as used in cardinal parameter growth models and thereby improve the prediction of growth for this pathogen in food with low pH. Experimental data for L. monocytogenes growth in broth at different pH-values and at different constant temperatures were generated and used to determined pH_min-values. Additionally, pH_min-values for L. monocytogenes available from literature were collected. A new pH_min-function was developed to describe the effect of temperatures on pH_min-values obtained experimentally and from literature data. A growth and growth boundary model was developed by substituting the constant pH_min-value present in the Mejlholm and Dalgaard (2009) model (J. Food. Prot. 72, 2132–2143) by the new pH_min-function. To obtain data for low pH food, challenge tests were performed with L. monocytogenes in commercial and laboratory-produced chemically acidified cheese including glucono-delta-lactone (GDL) and in commercial cream cheese. Furthermore, literature data for growth of L. monocytogenes in products with or without GDL were collected. Evaluation of the new and expanded model by comparison of observed and predicted μ_max-values resulted in a bias factor of 1.01 and an accuracy factor of 1.48 for a total of 1,129 growth responses from challenge tests and literature data. Growth and no-growth responses of L. monocytogenes in seafood, meat, non-fermented dairy products, and fermented cream cheese were 90.3% correctly predicted with incorrect predictions being 5.3% fail-safe and 4.4% fail-dangerous. The new pH_min-function markedly extended the range of applicability of the Mejlholm and Dalgaard (2009) model from pH 5.4 to pH 4.6 and therefore the model can now support product development, reformulation or risk assessment of food with low pH including chemically acidified cheese and cream cheese.

An Agent-Based Model for Pathogen Persistence and Cross-Contamination Dynamics in a Food Facility

We used an agent-based modeling (ABM) framework and developed a mathematical model to explain the complex dynamics of microbial persistence and spread within a food facility and to aid risk managers in identifying effective mitigation options. The model explicitly considered personal hygiene practices by food handlers as well as their activities and simulated a spatially explicit dynamic system representing complex interaction patterns among food handlers, facility environment, and foods. To demonstrate the utility of the model in a decision-making context, we created a hypothetical case study and used it to compare different risk mitigation strategies for reducing contamination and spread of Listeria monocytogenes in a food facility. Model results indicated that areas with no direct contact with foods (e.g., loading dock and restroom) can serve as contamination niches and recontaminate areas that have direct contact with food products. Furthermore, food handlers' behaviors, including, for example, hygiene and sanitation practices, can impact the persistence of microbial contamination in the facility environment and the spread of contamination to prepared foods. Using this case study, we also demonstrated benefits of an ABM framework for addressing food safety in a complex system in which emergent system-level responses are predicted using a bottom-up approach that observes individual agents (e.g., food handlers) and their behaviors. Our model can be applied to a wide variety of pathogens, food commodities, and activity patterns to evaluate efficacy of food-safety management practices and quantify contamination reductions associated with proposed mitigation strategies in food facilities.

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.

A low-complexity metabolic network model for the respiratory and fermentative metabolism of Escherichia coli

Over the last decades, predictive microbiology has made significant advances in the mathematical description of microbial spoiler and pathogen dynamics in or on food products. Recently, the focus of predictive microbiology has shifted from a (semi-)empirical population-level approach towards mechanistic models including information about the intracellular metabolism in order to increase model accuracy and genericness. However, incorporation of this subpopulation-level information increases model complexity and, consequently, the required run time to simulate microbial cell and population dynamics. In this paper, results of metabolic flux balance analyses (FBA) with a genome-scale model are used to calibrate a low-complexity linear model describing the microbial growth and metabolite secretion rates of Escherichia coli as a function of the nutrient and oxygen uptake rate. Hence, the required information about the cellular metabolism (i.e., biomass growth and secretion of cell products) is selected and included in the linear model without incorporating the complete intracellular reaction network. However, the applied FBAs are only representative for microbial dynamics under specific extracellular conditions, viz., a neutral medium without weak acids at a temperature of 37℃. Deviations from these reference conditions lead to metabolic shifts and adjustments of the cellular nutrient uptake or maintenance requirements. This metabolic dependency on extracellular conditions has been taken into account in our low-complex metabolic model. In this way, a novel approach is developed to take the synergistic effects of temperature, pH, and undissociated acids on the cell metabolism into account. Consequently, the developed model is deployable as a tool to describe, predict and control E. coli dynamics in and on food products under various combinations of environmental conditions. To emphasize this point,three specific scenarios are elaborated: (i) aerobic respiration without production of weak acid extracellular metabolites, (ii) anaerobic fermentation with secretion of mixed acid fermentation products into the food environment, and (iii) respiro-fermentative metabolic regimes in between the behaviors at aerobic and anaerobic conditions.

The impact of shelf life on exposure as revealed from quality control data associated with the quargel outbreak

A cluster of 34 human cases of listeriosis was traced to consumption of contaminated quargel cheese, a sour milk specialty sold in Austria, Germany and Czech Republic. Here, we try to assess how many portions were consumed by the Austrian population at a certain contamination level (CL). In total, 1623 cheese lots were produced during the outbreak period resulting in >3 million portions of cheese delivered to the market. From 650 sets of quality control data provided by the food business operator, we reconstructed the contamination scenario over time and identified 84 lots that were found to be positive. With regard to another sixteen lots, a CL was found ranging from one to 3,84 log₁₀ CFU L. monocytogenes/g, measured in product stored between one to 23 days after production. However the number of storage days at home before consumption is unknown. To resolve this issue, we modelled the theoretical CL of the product if consumed either 20, 30, 40 or 50 days post production. We found that 10 lots (approx. 27,350 portions) would have been contaminated at CLs higher than 3 log₁₀ CFU L. monocytogenes/g if all cheese had been consumed after 20 days of storage. This number shifts to 20 lots (approx. 54,700 portions) after 30 days of storage. If all cheese had been consumed at the end of shelf life (50 days of storage), theoretically 242,5 lots would have exceeded a CL of 6 log₁₀ CFU L. monocytogenes/g. We concluded that the extended shelf life given to the product was a driver of the outbreak scenario. It is stunning to note that so few cases were reported in spite of consumers' massive exposure to L. monocytogenes. We hypothesized that a low pathogenicity of both quargel outbreak clones (QOC1 and QOC2) could have contributed to this discrepancy. Our hypothesis was falsified since both strains QOC1 and QOC2 are fully virulent in an oral infection mouse model, showing even higher pathogenicity than the reference strain EGDe.

Selection of indigenous lactic acid bacteria presenting anti-listerial activity, and their role in reducing the maturation period and assuring the safety of traditional Brazilian cheeses

Artisanal raw milk cheeses are highly appreciated dairy products in Brazil and ensuring their microbiological safety has been a great need. This study reports the isolation and characterization of lactic acid bacteria (LAB) strains with anti-listerial activity, and their effects on Listeria monocytogenes during refrigerated shelf-life of soft Minas cheese and ripening of semi-hard Minas cheese. LAB strains (n = 891) isolated from Minas artisanal cheeses (n = 244) were assessed for anti-listerial activity by deferred antagonism assay at 37 °C and 7 °C. The treatments comprised the production of soft or semi-hard Minas cheeses using raw or pasteurized milk, and including the addition of selected LAB only [Lactobacillus brevis 2-392, Lactobacillus plantarum 1-399 and 4 Enterococcus faecalis (1-37, 2-49, 2-388 and 1-400)], L. monocytogenes only, selected LAB co-inoculated with L. monocytogenes, or without any added cultures. At 37 °C, 48.1% of LAB isolates showed anti-listerial capacity and 77.5% maintained activity at 7 °C. Selected LAB strains presented a bacteriostatic effect on L. monocytogenes in soft cheese. L. monocytogenes was inactivated during the ripening of semi-hard cheeses by the mix of LAB added. Times to attain a 4 log-reduction of L. monocytogenes were 15 and 21 days for semi-hard cheeses produced with raw and pasteurized milk, respectively. LAB with anti-listerial activity isolated from artisanal Minas cheeses can comprise an additional barrier to L. monocytogenes growth during the refrigerated storage of soft cheese and help shorten the ripening period of semi-hard cheeses aged at ambient temperature.

Listeria monocytogenes contamination of ready-to-eat foods and the risk for human health in the EU

Food safety criteria for Listeria monocytogenes in ready-to-eat (RTE) foods have been applied from 2006 onwards (Commission Regulation (EC) 2073/2005). Still, human invasive listeriosis was reported to increase over the period 2009-2013 in the European Union and European Economic Area (EU/EEA). Time series analysis for the 2008-2015 period in the EU/EEA indicated an increasing trend of the monthly notified incidence rate of confirmed human invasive listeriosis of the over 75 age groups and female age group between 25 and 44 years old (probably related to pregnancies). A conceptual model was used to identify factors in the food chain as potential drivers for L. monocytogenes contamination of RTE foods and listeriosis. Factors were related to the host (i. population size of the elderly and/or susceptible people; ii. underlying condition rate), the food (iii. L. monocytogenes prevalence in RTE food at retail; iv. L. monocytogenes concentration in RTE food at retail; v. storage conditions after retail; vi. consumption), the national surveillance systems (vii. improved surveillance), and/or the bacterium (viii. virulence). Factors considered likely to be responsible for the increasing trend in cases are the increased population size of the elderly and susceptible population except for the 25-44 female age group. For the increased incidence rates and cases, the likely factor is the increased proportion of susceptible persons in the age groups over 45 years old for both genders. Quantitative modelling suggests that more than 90% of invasive listeriosis is caused by ingestion of RTE food containing > 2,000 colony forming units (CFU)/g, and that one-third of cases are due to growth in the consumer phase. Awareness should be increased among stakeholders, especially in relation to susceptible risk groups. Innovative methodologies including whole genome sequencing (WGS) for strain identification and monitoring of trends are recommended.

Mechanistic modelling of the inhibitory effect of pH on microbial growth

Modelling and simulation of microbial dynamics as a function of processing, transportation and storage conditions is a useful tool to improve microbial food safety and quality. The goal of this research is to improve an existing methodology for building mechanistic predictive models based on the environmental conditions. The effect of environmental conditions on microbial dynamics is often described by combining the separate effects in a multiplicative way (gamma concept). This idea was extended further in this work by including the effects of the lag and stationary growth phases on microbial growth rate as independent gamma factors. A mechanistic description of the stationary phase as a function of pH was included, based on a novel class of models that consider product inhibition. Experimental results on Escherichia coli growth dynamics indicated that also the parameters of the product inhibition equations can be modelled with the gamma approach. This work has extended a modelling methodology, resulting in predictive models that are (i) mechanistically inspired, (ii) easily identifiable with a limited work load and (iii) easily extended to additional environmental conditions.

An interaction model for the combined effect of temperature, pH and water activity on the growth rate of E. coli K12

Previous research has indicated that more complex model structures than the commonly used gamma model are needed to obtain an accurate prediction of the effect of multiple environmental conditions on the microbial growth rate. Due to the complexity associated with the development of such model structures, it is recommended that the model structure is compatible with a modular model building method. In this research, a gamma-interaction model was built to describe the combined effect of temperature, pH and water activity on the microbial growth rate of E. coli K12 based on a dataset of 68 bioreactor experiments. This novel interaction model was compared with the standard gamma model. The model structures were tested separately for the combined effects of (i) temperature and pH, (ii) pH and water activity, (iii) temperature and water activity and (iv) temperature, pH and water activity. Based on the results of this research, it was concluded that models for the combined effect of environmental conditions need to allow for sufficient flexibility for the description of combined effects of environmental conditions to obtain accurate model predictions. In the current study, this flexibility was successfully introduced by using the gamma-interaction model. A cross-validation study also demonstrated that the predictions of the interaction model are more robust with respect to the specific data used than the gamma model. As such, the gamma-interaction model provides food producers and food safety authorities with a more accurate and reliable tool for the prediction of the microbial growth rate as a function of multiple environmental conditions.

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.

Modeling Lactic Fermentation of Gowé Using Lactobacillus Starter Culture

A global model of the lactic fermentation step of gowé was developed by assembling blocks hosting models for bacterial growth, lactic acid production, and the drop of pH during fermentation. Commercial strains of Lactobacillus brevis and of Lactobacillus plantarum were used; their growth was modeled using Rosso's primary model and the gamma concept as a secondary model. The optimum values of pH and temperature were 8.3 ± 0.3, 44.6 ± 1.2 °C and 8.3 ± 0.3, 3.2 ± 37.1 °C with μmax values of 1.8 ± 0.2 and 1.4 ± 0.1 for L. brevis and L. plantarum respectively. The minimum inhibitory concentration of undissociated lactic acid was 23.7 mM and 35.6 mM for L. brevis and L. plantarum, respectively. The yield of lactic acid was five times higher for L. plantarum than for L. brevis, with a yield of glucose conversion to lactic acid close to 2.0 for the former and 0.8 for the latter. A model was developed to predict the pH drop during gowé fermentation. The global model was partially validated during manufacturing of gowé. The global model could be a tool to aid in the choice of suitable starters and to determine the conditions for the use of the starter.

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 Model of Listeria Monocytogenes’ Growth Rate Under Different Temperatures and Acids

A response surface model of Listeria monocytogenes’ growth rate was built in this study under different temperatures (10 °C, 15 °C, 20 °C, 25 °C and 30 °C) and acid concentrations: citric acid (0–0.4%) and ascorbic acid (0–0.4%); two ingredients which are often used in the food industry as preservatives. Mathematical validation was performed with additional samples at different conditions within the range of the model, obtaining acceptable values of root mean square error (0.0466), standard error of prediction (18.84%), bias factor (1.05) and accuracy factor (1.16). The inhibitory effect on growth was more effective with citric acid than ascorbic acid, possibly due to the major dissociation of citric acid occurring inside microbial cells. The different conditions considered in the model will potentially allow L. monocytogenes’ response to be predicted in foods having a similar composition to the chemical and physical factors set out in this paper.

Evaluation of Phenylpropanoids in Ten Capsicum annuum L. Varieties and Their Inhibitory Effects on Listeria monocytogenes Murray, Webb and Swann Scott A

Extracts of pepper from ten different varieties of Capsicum annuumL. were prepared and their phenylpropanoids content was analysed by HPLC. There were seven different compounds identified at varying concentrations depending on pepper variety (L-phenylalanine, t-cinnamic acid, o-coumaric acid, mcoumaric acid, ferulic acid, caffeic acid and capsaicin) which are intermediates of the capsaicinoids pathway. The inhibitory action of the pepper extracts was evaluated against Listeria monocytogenes Murray, Webb and Swann Scott A by the agar diffusion test. Results showed that three of the 10 extracts had an antibacterial effect. Guajillo San Luis pepper presented the highest inhibitory effect, and contained the major concentration of cinnamic and caffeic acids. In order to analyse the individual contribution of every phenylpropanoid to the bacteriostatic effect, different concentrations were tested on the growth and survival of L. monocytogenesSwann Scott A.There were no significant differences (p> 0.05) in the t-cinnamic, o-coumaric, m-coumaric, ferulic acids and capsaicin among the samples. However, a significant difference was found between these compounds and the bactericidal action of caffeic acid. The results confirmed that L. monocytogenesSwann Scott A is inhibited by some pepper extracts, and also that some specific phenylpropanoids had a bacteriostatic effect.

Modeling and Validation of the Ecological Behavior of Wild-Type Listeria monocytogenes and Stress-Resistant Variants

Listeria monocytogenes exhibits a heterogeneous response upon stress exposure which can be partially attributed to the presence of stable stress-resistant variants. This study aimed to evaluate the impact of the presence of stress-resistant variants of Listeria monocytogenes and their corresponding trade-offs on population composition under different environmental conditions. A set of stress robustness and growth parameters of the wild type (WT) and an rpsU deletion variant was obtained and used to model their growth behavior under combined mild stress conditions and to model their kinetics under single- and mixed-strain conditions in a simulated food chain. Growth predictions for the WT and the rpsU deletion variant matched the experimental data generally well, although some deviations from the predictions were observed. The data highlighted the influence of the environmental conditions on the ratio between the WT and variant. Prediction of performance in the simulated food chain proved to be challenging. The trend of faster growth and lower stress robustness for the WT than for the rpsU variant in the different steps of the chain was confirmed, but especially for the inactivation steps and the time needed to resume growth after an inactivation step, the experimental data deviated from the model predictions. This report provides insights into the conditions which can select for stress-resistant variants in industrial settings and discusses their potential persistence in food processing environments.

IMPORTANCE

Listeria monocytogenes exhibits a heterogeneous stress response which can partially be attributed to the presence of genetic variants. These stress-resistant variants survive better under severe conditions but have, on the other hand, a reduced growth rate. To date, the ecological behavior and potential impact of the presence of stress-resistant variants is not fully understood. In this study, we quantitatively assessed growth and inactivation behavior of wild-type L. monocytogenes and its stress-resistant variants. Predictions were validated under different conditions, as well as along a model food chain. This work illustrates the effects of environmental factors on population dynamics of L. monocytogenes and is a first step in evaluating the impact of population diversity on food safety.